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Case Report of a 63-Year-Old Patient With Alzheimer Disease and a Novel Presenilin 2 Mutation

Wells, Jennie L. BSc, MSc, MD, FACP, FRCPC, CCRP *,† ; Pasternak, Stephen H. MD, PhD, FRCPC †,‡,§

* Department of Medicine, Division of Geriatric Medicine, Schulich School of Medicine and Dentistry, Western University

† St. Joseph’s Health Care London—Parkwood Institute

‡ Molecular Medicine Research Group, Robarts Research Institute

§ Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada

The authors declare no conflicts of interest.

Reprints: Jennie L. Wells, BSc, MSc, MD, FACP, FRCPC, CCRP, Department of Medicine, Division of Geriatric Medicine, St. Joseph’s Health Care London—Parkwood Institute, Room A2-129, P.O. Box 5777 STN B, London, ON, Canada N6A 4V2 (e-mail: [email protected] ).

This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/

Early onset Alzheimer disease (EOAD) is a neurodegenerative dementing disorder that is relatively rare (<1% of all Alzheimer cases). Various genetic mutations of the presenilin 1 ( PSEN1 ) and presenilin 2 ( PSEN2 ) as well as the amyloid precursor protein (APP) gene have been implicated. Mutations of PSEN1 and PSEN2 alter γ-secretase enzyme that cleaves APP resulting in increase in the relative amount of the more amyloidogenic Aβ42 that is produced. 1

PSEN2 has been less studied than PSEN1 and fewer mutations are known. Here, we report a case of a 63-year-old woman (at the time of death) with the clinical history consistent with Alzheimer D, an autopsy with brain histopathology supporting Alzheimer disease (AD), congophylic angiopathy, and Lewy Body pathology, and whose medical genetic testing reveals a novel PSEN2 mutation of adenosine replacing cytosine at codon 222, nucleotide position 665 (lysine replacing threonine) that has never been previously reported. This suggests that genetic testing may be useful in older patients with mixed pathology.

CASE REPORT

The patient was referred to our specialty memory clinic at the age of 58 with a 2-year history of repetitiveness, memory loss, and executive function loss. Magnetic resonance imaging scan at age 58 revealed mild generalized cortical atrophy. She is white with 2 years of postsecondary education. Retirement at age 48 from employment as a manager in telecommunications company was because family finances allowed and not because of cognitive challenges with work. Progressive cognitive decline was evident by the report of deficits in instrumental activities of daily living performance over the past 9 months before her initial consultation in the memory clinic. Word finding and literacy skills were noted to have deteriorated in the preceding 6 months according to her spouse. Examples of functional losses were being slower in processing and carrying out instructions, not knowing how to turn off the stove, and becoming unable to assist in boat docking which was the couple’s pastime. She stopped driving a motor vehicle about 6 months before her memory clinic consultation. Her past medical history was relevant for hypercholesterolemia and vitamin D deficiency. She had no surgical history. She had no history of smoking, alcohol, or other drug misuse. Laboratory screening was normal. There was no first-degree family history of presenile dementia. Neurocognitive assessment at the first clinic visit revealed a Mini Mental State Examination (MMSE) score of 14/30; poor verbal fluency (patient was able to produce only 5 animal names and 1 F-word in 1 min) as well as poor visuospatial and executive skills ( Fig. 1 ). She had fluent speech without semantic deficits. Her neurological examination was pertinent for normal muscle tone and power, mild ideomotor apraxia on performing commands for motor tasks with no suggestion of cerebellar dysfunction, normal gait, no frontal release signs. Her speech was fluent with obvious word finding difficulties but with no phonemic or semantic paraphrasic errors. Her general physical examination was unremarkable without evidence of presenile cataracts. She had normal hearing. There was no evidence of depression or psychotic symptoms.

At the time of the initial assessment, her mother was deceased at age 79 after a hip fracture with a history long-term smoking and idiopathic pulmonary fibrosis. Her family believes that there is possible German and Danish descent on her father’s side. Her father was alive and well at age 80 at the time of her presentation with a history coronary artery disease. He is still alive and well with no functional or cognitive concerns at age 87 at the time of writing this report. Her paternal grandfather died at approximately age 33 of appendicitis with her paternal grandmother living with mild memory loss but without known dementia or motor symptoms until age 76, dying after complications of abdominal surgery. Her paternal uncle was diagnosed with Parkinson disease in his 40s and died at age 58. Her maternal grandmother was reported to be functionally intact, but mildly forgetful at the time of her death at age 89. The maternal grandfather had multiple myocardial infarctions and died of congestive heart failure at age 75. She was the eldest of 4 siblings (ages 44 to 56 at the time of presentation); none had cognitive problems. She had no children.

Because of her young age and clinical presentation with no personality changes, language or motor change, nor fluctuations, EOAD was the most likely clinical diagnosis. As visuospatial challenges were marked at her first visit and poor depth perception developing over time, posterior cortical variant of AD was also on the differential as was atypical presentation of frontotemporal dementias. Without fluctuations, Parkinsonism, falls, hallucinations, or altered attention, Lewy Body dementia was deemed unlikely. After treatment with a cholinesterase inhibitor, her MMSE improved to 18/30, tested 15 months later with stability in function. Verbal fluency improved marginally with 7 animals and 3 F-words. After an additional 18 months, function and cognition declined (MMSE=13/30) so memantine was added. The stabilizing response to the cholinesterase inhibitor added some degree of confidence to the EOAD diagnosis. In the subsequent 4 years, she continued to decline in cognition and function such that admission to a care facility was required with associated total dependence for basic activities of daily living. Noted by family before transfer to the long-term care facility were episodic possible hallucinations. It was challenging to know if what was described was misinterpretation of objects in view or a true hallucination. During this time, she developed muscle rigidity, motor apraxias, worsening perceptual, and language skills and became dependent for all activities of daily livings. At the fourth year of treatment, occasional myoclonus was noted. She was a 1 person assist for walking because of increased risk of falls. After 1 year in the care home, she was admitted to the acute care hospital in respiratory distress. CT brain imaging during that admission revealed marked generalized global cortical atrophy and marked hippocampal atrophy ( Fig. 2 ). She died at age 63 of pneumonia. An autopsy was performed confirming the cause of death and her diagnosis of AD, showing numerous plaques and tangles with congophilic amyloid angiopathy. In addition, there was prominent Lewy Body pathology noted in the amygdala.

Three years before her death informed consent was obtained from the patient and family to perform medical genetic testing for EOAD. The standard panel offered by the laboratory was selected and included PSEN1 , PSEN2 , APP, and apoE analysis. Tests related to genes related to frontotemporal dementia were not requested based on clinical presentation and clinical judgement. This was carried out with blood samples and not cerebrospinal fluid because of patient, family, and health provider preference. The results revealed a novel PSEN2 mutation with an adenosine replacing cytosine at nucleotide position 665, codon 222 [amino acid substation of lysine for threonine at position 221 (L221T)]. This PSEN2 variant was noted to be novel to the laboratory’s database, noting that models predicted that this variant is likely pathogenic. The other notable potentially significant genetic finding is the apoliprotein E genotype was Є 3/4 .

β-amyloid (Aβ) is a 38 to 43 amino acid peptide that aggregates in AD forming toxic soluble oligomers and insoluble amyloid fibrils which form plaques. Aβ is produced by the cleavage of the APP first by an α-secretase, which produces a 99 amino acid C-terminal fragment of APP, and then at a variable “gamma” position by the γ-secretase which releases the Aβ peptide itself. It is this second γ-cleavage which determines the length and therefore the pathogenicity of the Aβ peptides, with 42 amino acid form of Aβ having a high propensity to aggregate and being more toxic.

The γ-secretase is composed of at least 4 proteins, mAph1, PEN2, nicastrin, and presenilin . Of these proteins, presenilin has 2 distinct isoforms ( PSEN1 and PSEN2 ), which contain the catalytic site responsible for the γ-cleavage. PSEN mutants are the most common genetic cause of AD with 247 mutations described in PSEN1 and 48 mutations described in PSEN2 (Alzgene database; www.alzforum.org/mutations ). PSEN2 mutations are reported to be associated with AD of both early onset and variable age onset as well as with other neurodegenerative disorders such as Lewy Body dementia, frontotemporal dementia, Parkinson dementia, and posterior cortical atrophy. 2–4 In addition, PSEN2 has associations with breast cancer and dilated cardiomyopathy. 3

PSEN2 mutants are believed to alter the γ-secretase cleavage of APP increasing the relative amount of the more toxic Aβ42. The mean age of onset in PSEN2 mutations, is 55.3 years but the range of onset is surprisingly wide, spanning 39 to 83 years. Over 52% of cases are over 60 years. All cases have extensive amyloid plaque and neurofibrillary tangles, and many have extensive alpha-synuclein pathology as well. 5

In considering the novelty of this reported PSEN2 mutation, a literature search of Medline, the Alzgene genetic database of PSEN2 and the Alzheimer Disease and Frontotemporal Dementia Mutation Databases (AD&FTMD) were completed ( www.molgen.vib-ua.be/ADMutations ). The mutation presented here (L221T) has never been described before.

Although this mutation has not been described, we believe that it is highly likely to be pathogenic. This mutation is not conservative, as it replaces a lysine residue which is positively charged with threonine which is an uncharged polar, hydrophilic amino acid. The mutation itself occurs in a small cytoplasmic loop between transmembrane domain 4 and 5, which is conserved in the PSEN1 gene, and in PSEN2 is highly conserved across vertebrates, including birds and zebrafish all the way to Caenorhabditis elegans , but differs in Drosophila melanogaster (fruit fly) ( Fig. 3 ). We examined this mutation using several computer algorithms which examine the likelihood that a mutation will not be tolerated. Both SIFT ( http://sift.bii.a-star.edu.sg ) and PolyPhen-2.2.2 (HumVar) ( www.bork.embl-heidelberg.de/PolyPhen ) predicts that this variant is pathogenic. Interestingly, it is noted that PSEN1 mutations after amino acid 200 develop amyloid angiopathy. 5,7

This patient also had an additional risk factor for AD, being a heterozygote for the apoЄ4 allele. Among other mechanisms, its presence reduces clearance of Aβ42 from the brain and increases glial activation. 8 Although the apoЄ4 allele is known to lower the age of onset of dementia in late onset AD, it has not been clearly shown to influence age of onset of EOAD in a limited case series. 9 It should be noted that heterozygote state may have contributed to an acceleration of her course given the known metabolism of apoЄ4 and its association with accelerated cerebral amyloid and known reduction in age of onset. 10

Given that there is no definite family history of autosomal dominant early onset dementia, it is likely that her PSEN2 mutation was a new random event. With the unusually wide age of onset it is conceivable that one of her parents could still harbor this PSEN2 mutation. The patient’s father, however, is currently 87 and living independently at the time of writing this manuscript, making him highly unlikely to be an EOAD carrier. Nonpaternity is an alternate explanation for the lack of known first-degree relative with EOAD; however, this is deemed unlikely by the family member who provided the supplemental history. Her mother died at age 79, so she could conceivably carry our mutation but we do not have access to this genetic material. Without extensive testing of many family members it would be impossible to speculate about autosomal recessive form of gene expression. In addition, the genetic testing requested was limited to presenilins , APP, and apoE mutations. Danish heritage may add Familial Danish dementia as a remote consideration; however, Familial Danish dementia has a much different clinical presentation with long tract signs, cerebellar dysfunction, onset in the fourth decade as well as hearing loss and cataracts at a young age. 11 This disease has high autosomal dominant penetration which also makes it less likely in the patient’s context. This specific gene (chromosome 13) was not tested. The autopsy findings do not support this possibility. There are reports of Familial AD pedigrees in Germany, including a Volga pedigree with PSEN141I mutation in exon 5, but this is clearly separate from our mutation which is in exon 7. Our mutation was also not observed in a recent cohort of 23 German individuals with EOAD which underwent whole genome sequencing, but did find 2 carriers of the Volga pedigree. It is also possible that both the PSEN2 mutation and the ApoE genotype contributed to her disease and early onset presentation. This case illustrates the multiple pathology types which occur in individuals bearing PSEN2 mutations, and highlights the later ages in which patients can present with PSEN2 mutations. 12

ACKNOWLEDGMENT

The authors acknowledge Gwyneth Duhn, RN, BNSc, MSc, for her support of this paper.

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Case study unlocks clues to rare resilience to Alzheimer’s disease

Aging Biology Alzheimer's Disease Clinical Research

From NIH Director’s Blog

Biomedical breakthroughs most often involve slow and steady research in studies involving large numbers of people. But sometimes careful study of even just one truly remarkable person can lead the way to fascinating discoveries with far-reaching implications.

An NIH-funded case study published recently in the journal  Nature Medicine  falls into this far-reaching category [1]. The report highlights the world’s second person known to have an extreme resilience to a rare genetic form of early onset Alzheimer’s disease. These latest findings in a single man follow a 2019 report of a woman with similar resilience to developing symptoms of Alzheimer’s, despite having the same strong genetic predisposition for the disease [2].

The new findings raise important new ideas about the series of steps that may lead to Alzheimer’s and its dementia. They’re also pointing the way to key parts of the brain for cognitive resilience — and potentially new treatment targets — that may one day help to delay or even stop progression of Alzheimer’s.

The man in question is a member of a well-studied extended family from the country of Colombia. This group of related individuals, or kindred, is the largest in the world with a genetic variant called the “Paisa” mutation (or  Presenilin-1 E280A ). This Paisa variant follows an autosomal dominant pattern of inheritance, meaning that those with a single altered copy of the rare variant passed down from one parent usually develop mild cognitive impairment around the age of 44. They typically advance to full-blown dementia around the age of 50 and rarely live past the age of 60. This contrasts with the  most common form of Alzheimer’s , which usually begins after age 65.

The new findings come from a team led by  Yakeel Quiroz , Massachusetts General Hospital, Boston; Joseph Arboleda-Velasquez, Massachusetts Eye and Ear, Boston; Diego Sepulveda-Falla, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; and Francisco Lopera, University of Antioquia, Medellín, Colombia. Lopera  first identified this family  more than 30 years ago and has been studying them ever since.

In the new case report, the researchers identified a Colombian man who’d been married with two children and retired from his job as a mechanic in his early 60s. Despite carrying the Paisa mutation, his first cognitive assessment at age 67 showed he was cognitively intact, having limited difficulties with verbal learning skills or language. It wasn’t until he turned 70 that he was diagnosed with mild cognitive impairment — more than 20 years later than the expected age for this family — showing some decline in short-term memory and verbal fluency.

At age 73, he enrolled in the  Colombia-Boston biomarker research study (COLBOS ). This study is a collaborative project between the University of Antioquia and Massachusetts General Hospital involving approximately 6,000 individuals from the Paisa kindred. About 1,500 of those in the study carry the mutation that sets them up for early Alzheimer’s. As a member of the COLBOS study, the man underwent thorough neuroimaging tests to look for amyloid plaques and tau tangles, both of which are hallmarks of Alzheimer’s.

While this man died at age 74 with Alzheimer’s, the big question is: How did he stave off dementia for so long despite his poor genetic odds? The COLBOS study earlier identified a woman with a similar resilience to Alzheimer’s, which they traced to two copies of a rare, protective genetic variant called Christchurch. This variant affects a gene called apolipoprotein E ( APOE3 ), which is well known for its influence on Alzheimer’s risk. However, the man didn’t carry this same protective variant.

The researchers still thought they’d find an answer in his genome and kept looking. While they found several variants of possible interest, they zeroed in on a single gene variant that they’ve named  Reelin-COLBOS . What helped them to narrow their search down to this variant is the man also had a sister with the Paisa mutation who only progressed to advanced dementia at age 72. It turned out, in addition to the Paisa variant, the siblings also shared an altered copy of the newly discovered  Reelin-COLBOS  variant.

This  Reelin-COLBOS  gene is known to encode a protein that controls signals to chemically modify  tau proteins , which form tangles that build up over time in the Alzheimer’s brain and have been linked to memory loss.  Reelin  is also functionally related to  APOE , the gene that was altered in the woman with extreme Alzheimer’s protection.  Reelin  and  APOE  both interact with common protein receptors in neurons. Together, the findings add to evidence that signaling pathways influencing tau play an important role in Alzheimer’s pathology and protection.

The neuroimaging exams conducted when the man was age 73 have offered further intriguing clues. They showed that his brain had extensive amyloid plaques. He also had tau tangles in some parts of his brain. But one brain region, called the entorhinal cortex, was notable for having a very minimal amount of those hallmark tau tangles.

The entorhinal cortex is a hub for memory, navigation, and the perception of time. Its degeneration also leads to cognitive impairment and dementia. Studies of the newly identified  Reelin-COLBOS  variant in Alzheimer’s mouse models also help to confirm that the variant offers its protection by diminishing the pathological modifications of tau.

Overall, the findings in this one individual and his sister highlight the Reelin pathway and brain region as promising targets for future study and development of Alzheimer’s treatments. Quiroz and her colleagues report that they are actively exploring treatment approaches inspired by the Christchurch and  Reelin-COLBOS  discoveries.

Of course, there’s surely more to discover from continued study of these few individuals and others like them. Other as yet undescribed genetic and environmental factors are likely at play. But the current findings certainly offer some encouraging news for those at risk for Alzheimer’s — and a reminder of how much can be learned from careful study of remarkable individuals.

References:

[1] Lopera F, et al.  Resilience to autosomal dominant Alzheimer’s disease in a Reelin-COLBOS heterozygous man . Nat Med. 2023. Epub May 15. doi: 10.1038/s41591-023-02318-3.

[2] Arboleda-Velasquez JF, et. al. Resistance to autosomal dominant Alzheimer’s disease in an APOE3 Christchurch homozygote: A case report . Nat Med. 2019. Epub Nov. 4. doi: 10.1038/s41591-019-0611-3.

NIH Support: National Institute on Aging; National Eye Institute; National Institute of Neurological Disorders and Stroke; Office of the Director

This research was supported in part by NIA grant R01AG054671.

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An official website of the National Institutes of Health

The Mysterious Case of The Youngest Person Ever Diagnosed With Alzheimer's

In 2023, neurologists at a memory clinic in China diagnosed a 19-year-old with what they believed to be Alzheimer's disease , making him the youngest person ever to be diagnosed with the condition in the world.

The male teenager began experiencing memory decline around age 17, and the cognitive losses only worsened over the years.

Imaging of the patient's brain showed shrinkage in the hippocampus, which is involved in memory, and his cerebrospinal fluid hinted at common markers of this most common form of dementia .

Alzheimer's disease (AD) is often thought of as an old person's ailment, and yet early-onset cases, which include patients under the age of 65, account for up to 10 percent of all diagnoses.

Almost all patients under 30 years of age can have their Alzheimer's explained by pathological gene mutations, putting them into the category of familial Alzheimer's disease ( FAD ). The younger a person is when they receive a diagnosis, the more likely it is the result of a faulty gene they've inherited.

Yet researchers at the Capital Medical University in Beijing couldn't find any of the usual mutations responsible for the early onset of memory loss, nor any suspect genes when they performed a genome-wide search.

Before this diagnosis in China, the youngest patient with Alzheimer's was 21 years old. They carried the PSEN1 gene mutation , which causes abnormal proteins to build up in the brain, forming clumps of toxic plaques, a common feature of Alzheimer's.

Cases like the one in China pose something of a mystery. None of the 19-year-old's family had a history of Alzheimer's or dementia, making it hard to categorize as FAD, yet the teenager had no other diseases, infections, or head trauma that could explain his sudden cognitive decline either.

Two years before being referred to the memory clinic, the teenage patient began struggling to focus in class. Reading also became difficult and his short-term memory declined. Oftentimes, he couldn't remember events from the day before, and he was always misplacing his belongings.

Ultimately, the cognitive decline became so bad, the young man was unable to finish high school, although he could still live independently.

A year after being referred to the memory clinic, he showed losses in immediate recall, short-delay recall after three minutes, and long-delay recall after 30 minutes.

The patient's full-scale memory score was 82 percent lower than that of peers his own age, while his immediate memory score was 87 percent lower.

Long-term follow-up is needed to support the young man's diagnosis, but his medical team said at the time the patient was "altering our understanding of the typical age of onset of AD."

"The patient had very early-onset AD with no clear pathogenic mutations," neurologist Jianping Jia and colleagues wrote in their study , "which suggests that its pathogenesis still needs to be explored."

The case study, published in February 2023, just goes to show that Alzheimer's doesn't follow a single pathway, and is much more complex than we thought, emerging via numerous avenues with varying effects.

In a statement to the South China Morning Post, the neurologists who described the patient's case argued that future studies should focus on early-onset cases to further improve our understanding of memory loss.

"Exploring the mysteries of young people with Alzheimer's disease may become one of the most challenging scientific questions of the future," they said .

The study was published in the Journal of Alzheimer's Disease .

An earlier version of this article was published in February 2023.

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The brain that defied alzheimer’s.

Genetic mutation found that could shed light on mechanism for disease resistance, lead to new therapies

Neil Osterweil

MGH News and Public Affairs

Illustration by Roy Scott

Aliria Rosa Piedrahita de Villegas should have developed Alzheimer’s disease in her 40s and died from the disease in her 60s because of a rare genetic mutation.

Instead, she lived dementia-free into her 70s, and now her brain is yielding important clues about the pathology of dementia and possible treatments for Alzheimer’s disease.

As researchers at Massachusetts General Hospital and other centers first described in 2019, the woman, from Medellin, Colombia, was a member of an extended family with a mutation in a gene labeled PSEN1. The PSEN1 E280A mutation is autosomal dominant, meaning that only a single copy of the gene is required to cause disease. Carriers of the mutation typically exhibit symptoms of Alzheimer’s in their 40s or 50s, and die from the disease soon after, but this woman did not begin to show signs of Alzheimer’s until her early 70s. She died in 2020 from metastatic melanoma at the age of 77.

The key difference in the Colombian woman’s ability to fend off the disease for three decades appeared to be that in addition to having the PSEN1 E280A mutation, she was also a carrier of both copies of a mutation known as APOE3 Christchurch.

“This exceptional case is an experiment designed by nature that teaches us a way to prevent Alzheimer’s: let’s observe, learn, and imitate nature.” Francisco Lopera, director of the Neuroscience Group of Antioquia in Medellín, Colombia.

The APOE family of genes control production of apolipoproteins, which transport lipids (fats) in blood and other bodily fluids. The APOE2 variant is known to be protective against Alzheimer’s dementia, while the APOE4 variant is linked to an increased risk for the disease.

APOE3, the most common variant, is not typically associated with either reduced or increased risk for Alzheimer’s.

“This is a ground-breaking case for Alzheimer’s disease and has already opened new paths for treatment and prevention, which we’re currently pursuing with some collaborators. This work is now bringing light into some of the mechanisms of resistance to Alzheimer’s disease” says investigator Yakeel T. Quiroz

Quiroz is director of the Multicultural Alzheimer Prevention Program (MAPP ) at Mass General, an associate professor of psychology at Harvard Medical School, and Paul B. and Sandra M. Edgerley MGH Research Scholar 2020-2025 .

As Quiroz and colleagues now report in the neuropathology journal Acta Neuropathologica , the woman did, in fact, have pathologic features of Alzheimer’s disease in her brain, but not in regions of the brain where the hallmarks of Alzheimer’s are typically found.

“This patient gave us a window into many competing forces — abnormal protein accumulation, inflammation, lipid metabolism, homeostatic mechanisms — that either promote or protect against disease progression, and begin to explain why some brain regions were spared while others were not,” says Justin Sanchez, co-first author, and an investigator at MGH Neurology.

Researchers identified in Aliria’s brain a distinct pattern of abnormal aggregation or “clumping” of tau, a protein known to be altered in Alzheimer’s disease and other neurologic disorders.

In this case, the tau pathology largely spared the frontal cortex, which is important for judgment and other “executive” functions, and the hippocampus, which is important for memory and learning. Instead, the tau pathology involved the occipital cortex, the area of the brain at the back of the head that controls visual perception.

The occipital cortex was the only major brain region to exhibit typical Alzheimer’s features, such as chronic inflammation of protective brain cells called microglia, and reduced levels of APOE expression.

“Thus, the Christchurch variant may impact the distribution of tau pathology, modulates age at onset, severity, progression, and clinical presentation of [autosomal dominant Alzheimer’s disease], suggesting possible therapeutic strategies,” the researchers write.

“It is seldom that we have nice surprises while studying familial Alzheimer’s disease brains. This case showed an amazingly clear protected phenotype. I am sure our molecular and pathologic findings will at least suggest some avenues of research and elicit hope for a successful treatment against this disorder.” says co-first author Diego Sepulveda-Falla, research lead at University Medical Center Hamburg-Eppendorf in Hamburg, Germany.

“This exceptional case is an experiment designed by nature that teaches us a way to prevent Alzheimer’s: let’s observe, learn, and imitate nature,” concludes Francisco Lopera, director of the Neuroscience Group of Antioquia in Medellín, Colombia. Lopera is a co-senior author and the neurologist who discovered this family and has been following them for the last 30 years.

Quiroz is a co-senior author of the report, along with Kenneth S. Kosik, University of California, Santa Barbara; Lopera, and Sepulveda-Falla. Sanchez contributed equally to the study.

The study was supported by grants from the National Institutes of Health, MGH Executive Committee on Research (MGH Research Scholar Award), Alzheimer’s Association, the Deutsche Forschungsgemeinschaft, Universidad de Antioquia, the Werner Otto Stiftung, and the Gernam Federal Ministiry of Education and Research.

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Case Study Unlocks Clues to Rare Resilience to Alzheimer’s Disease

Posted on May 30th, 2023 by Lawrence Tabak, D.D.S., Ph.D.

A brain is covered with a protective shield decorated with DNA and labeled Reelin-COLBOS

An NIH-funded case study published recently in the journal Nature Medicine falls into this far-reaching category [1]. The report highlights the world’s second person known to have an extreme resilience to a rare genetic form of early onset Alzheimer’s disease. These latest findings in a single man follow a 2019 report of a woman with similar resilience to developing symptoms of Alzheimer’s despite having the same strong genetic predisposition for the disease [2].

The new findings raise important new ideas about the series of steps that may lead to Alzheimer’s and its dementia. They’re also pointing the way to key parts of the brain for cognitive resilience—and potentially new treatment targets—that may one day help to delay or even stop progression of Alzheimer’s.

The man in question is a member of a well-studied extended family from the country of Colombia. This group of related individuals, or kindred, is the largest in the world with a genetic variant called the “Paisa” mutation (or Presenilin-1 E280A ). This Paisa variant follows an autosomal dominant pattern of inheritance, meaning that those with a single altered copy of the rare variant passed down from one parent usually develop mild cognitive impairment around the age of 44. They typically advance to full-blown dementia around the age of 50 and rarely live past the age of 60. This contrasts with the most common form of Alzheimer’s , which usually begins after age 65.

The new findings come from a team led by Yakeel Quiroz , Massachusetts General Hospital, Boston; Joseph Arboleda-Velasquez, Massachusetts Eye and Ear, Boston; Diego Sepulveda-Falla, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; and Francisco Lopera, University of Antioquia, Medellín, Colombia. Lopera first identified this family more than 30 years ago and has been studying them ever since.

In the new case report, the researchers identified a Colombian man who’d been married with two children and retired from his job as a mechanic in his early 60s. Despite carrying the Paisa mutation, his first cognitive assessment at age 67 showed he was cognitively intact, having limited difficulties with verbal learning skills or language. It wasn’t until he turned 70 that he was diagnosed with mild cognitive impairment—more than 20 years later than the expected age for this family—showing some decline in short-term memory and verbal fluency.

At age 73, he enrolled in the Colombia-Boston biomarker research study (COLBOS ). This study is a collaborative project between the University of Antioquia and Massachusetts General Hospital involving approximately 6,000 individuals from the Paisa kindred. About 1,500 of those in the study carry the mutation that sets them up for early Alzheimer’s. As a member of the COLBOS study, the man underwent thorough neuroimaging tests to look for amyloid plaques and tau tangles, both of which are hallmarks of Alzheimer’s.

While this man died at age 74 with Alzheimer’s, the big question is: how did he stave off dementia for so long despite his poor genetic odds? The COLBOS study earlier identified a woman with a similar resilience to Alzheimer’s, which they traced to two copies of a rare, protective genetic variant called Christchurch. This variant affects a gene called apolipoprotein E ( APOE3 ), which is well known for its influence on Alzheimer’s risk. However, the man didn’t carry this same protective variant.

The researchers still thought they’d find an answer in his genome and kept looking. While they found several variants of possible interest, they zeroed in on a single gene variant that they’ve named Reelin-COLBOS . What helped them to narrow it down to this variant is the man also had a sister with the Paisa mutation who only progressed to advanced dementia at age 72. It turned out, in addition to the Paisa variant, the siblings also shared an altered copy of the newly discovered Reelin-COLBOS variant.

This Reelin-COLBOS gene is known to encode a protein that controls signals to chemically modify tau proteins , which form tangles that build up over time in the Alzheimer’s brain and have been linked to memory loss. Reelin is also functionally related to APOE , the gene that was altered in the woman with extreme Alzheimer’s protection. Reelin and APOE both interact with common protein receptors in neurons. Together, the findings add to evidence that signaling pathways influencing tau play an important role in Alzheimer’s pathology and protection.

The entorhinal cortex is a hub for memory, navigation, and the perception of time. Its degeneration also leads to cognitive impairment and dementia. Studies of the newly identified Reelin-COLBOS variant in Alzheimer’s mouse models also help to confirm that the variant offers its protection by diminishing the pathological modifications of tau.

Of course, there’s surely more to discover from continued study of these few individuals and others like them. Other as yet undescribed genetic and environmental factors are likely at play. But the current findings certainly offer some encouraging news for those at risk for Alzheimer’s disease—and a reminder of how much can be learned from careful study of remarkable individuals.

References :

[1] Resilience to autosomal dominant Alzheimer’s disease in a Reelin-COLBOS heterozygous man . Lopera F, Marino C, Chandrahas AS, O’Hare M, Reiman EM, Sepulveda-Falla D, Arboleda-Velasquez JF, Quiroz YT, et al. Nat Med. 2023 May;29(5):1243-1252.

[2] Resistance to autosomal dominant Alzheimer’s disease in an APOE3 Christchurch homozygote: a case report . Arboleda-Velasquez JF, Lopera F, O’Hare M, Delgado-Tirado S, Tariot PN, Johnson KA, Reiman EM, Quiroz YT et al. Nat Med. 2019 Nov;25(11):1680-1683.

Alzheimer’s Disease & Related Dementias (National Institute on Aging/NIH)

“ NIH Support Spurs Alzheimer’s Research in Colombia ,” Global Health Matters, January/February 2014, Fogarty International Center/NIS

“ COLBOS Study Reveals Mysteries of Alzheimer’s Disease ,” NIH Record, August 19, 2022.

Yakeel Quiroz (Massachusetts General Hospital, Harvard Medical School, Boston)

Joseph Arboleda-Velasquez (Massachusetts Eye and Ear, Harvard Medical School, Boston)

Diego Sepulveda-Falla Lab (University Medical Center Hamburg-Eppendorf, Hamburg, Germany)

Francisco Lopera (University of Antioquia, Medellín, Colombia)

NIH Support: National Institute on Aging; National Eye Institute; National Institute of Neurological Disorders and Stroke; Office of the Director

One Comment

The entorhinal cortex is a hub for memory, navigation, and the perception of time. Also pheromone reception. 100mg of healthy adult male facial skin surface lipid pheromone that is normally passed in kissing, allows laughing, singing, and real joy again in an Alzheimer’s patient. The pheromone, the grease on your nose, is always in sight whenever your silly eyes are open. It halts the progression of Alzheimer’s Disease, also FT dementia, Tourette’s, Parry-Romberg, epilepsy, …

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Early onset Alzheimer's disease - a case study

Affiliations.

1 Katedra i Zakład Podstawowych Nauk Medycznych, Wydział Nauk o Zdrowiu w Bytomiu, Śląski Uniwersytet Medyczny w Katowicach.
2 Katedra i Klinika Neurologii, Wydział Lekarski z Oddziałem Lekarsko-Dentystycznym w Zabrzu, Śląski Uniwersytet Medyczny w Katowicach.
3 Górnośląskie Centrum Rehabilitacji Repty, Tarnowskie Góry.
4 Faculty of Public Health in Bytom, Medical University of Silesia in Katowice.
5 Instytut Psychologii, Wyższa Szkoła Humanitas w Sosnowcu.
PMID: 34365482
DOI: 10.12740/PP/OnlineFirst/114122

Dementia syndromes constitute problem not only for the elderly. Early-onset dementia (EOD) starts below the age of 65 years. It accounts for 4-10% of all cases of dementia. EOD has significant psychosocial consequences because it affects people in their most productive years of life, with numerous family, professional and social responsibilities. There are many diseases that have been identified as the cause of the EOD. Among them, the most common are Alzheimer's disease, vascular dementia, fronto-temporal dementia, Lewy body dementia, traumatic brain injury, alcohol related dementia, Huntington's disease, Parkinson's disease, mixed dementia, Creutzfeldt-Jakob disease and Down's syndrome. Most studies have demonstrated Alzheimer's disease as the most common etiology of EOD. The article presents the case of a 33-year-old patient hospitalized in the Department of Neurology in Zabrze, with cognitive dysfunction, speech disordersand featuresof Parkinson's extrapyramidal syndrome that have been progressing for about 15 months. The MR of the head revealed cortical and subcortical atrophy, especially in parietal and temporal lobes. The cerebrospinal fluid examination showed decreased level of β-amyloid and significantly elevated level of H-tau. The patient was diagnosed with early-onset Alzheimer's disease, which was confirmed by genetic testing - the sequence change was identified in the gene for presenilin 1 in a heterozygous system.

Keywords: Alzheimer’s disease; dementia; early-onset dementia.

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Case of early-onset Alzheimer’s disease with atypical manifestation

Limin Sun ,

https://doi.org/ 10.1136/gpsych-2020-100283

Short-term memory decline is the typical clinical manifestation of Alzheimer’s disease (AD). However, early-onset AD usually has atypical symptoms and may get misdiagnosed. In the present case study, we reported a patient who experienced symptoms of memory loss with progressive non-fluent aphasia accompanied by gradual social withdrawal. He did not meet the diagnostic criteria of AD based on the clinical manifestation and brain MRI. However, his cerebrospinal fluid examination showed a decreased level of beta-amyloid 42, and increased total tau and phosphorylated tau. Massive amyloid β-protein deposition by 11C-Pittsburgh positron emission tomography confirmed the diagnosis of frontal variant AD. This case indicated that early-onset AD may have progressive non-fluent aphasia as the core manifestation. The combination of individual and precision diagnosis would be beneficial for similar cases.

Introduction
Clinical report and methods

Early-onset Alzheimer’s disease (EOAD), which comprises 5% of Alzheimer’s disease (AD), shows a 1.6-year average delay in diagnosis compared with late-onset AD. 1 2 The clinical phenotype of atypical EOAD is heterogeneous, and primary progressive aphasia (PPA) is rarely the initial manifestation of related dementia syndromes. Compared with the progressive non-fluent aphasia (PNFA) related to the language variant phenotype of frontotemporal lobar degeneration (FTLD), molecular imaging studies in patients with primary progressive aphasia suggest the pathological basis of AD. 3 Neurodegeneration uaually starts in a specific neural anatomic networks. The clinical phenotype of PPA can usually infer the type of protein degeneration, which can be used to infer gene mutation. With the development of biomarkers such as genetics, molecular biology, neuroimaging and positron emission tomography (PET), accurate diagnosis can be gradually achieved. In this case study, we describe an AD patient with PNFA as the first symptom.

The patient was a 63-year-old married man, a right-handed businessman, native of Shanghai, with 12 years of school education. He has memory loss and non-fluent speech for 7 years combined with personality changes for 5 years. The patient recovered from hepatitis A 32 years ago and has well-controlled hypertension for 30 years.

The patient’s caregiver described that the patient showed forgetfulness and developed poor pronunciation at the age of 56. His short-term memory has gradually declined as noticed that he repeatedly gave money to customers while selling clothes. He frequently forgot where he parked his bicycle, and it was hard for him to speak a full sentence; his language was vague and short. He was impatient when being asked to repeat a word. Over time, he could only say some single syllables. He evolved into fully aphasia gradually, and his personality also changed gradually. At the age of 59, he could not recognise himself in the mirror and he often hid his shoes because he was worried that they would be stolen. Therefore, his wife had accompanied him to see a neurologist. The physical and neurological examination revealed no remarkable signs. His brain MRI showed mild atrophy in the bilateral frontal lobe ( figure 1A at the age of 59). Fluorodeoxyglucose positron emission tomography (FDG-PET) revealed that glucose metabolism in the bilateral frontal and parietal lobe was declined, and the left side was significant ( figure 1B at the age of 59). The Mini-Mental State Examination (MMSE) score was 18 out of 30 (18/30). At that point, he was diagnosed with cognitive impairment and treated with rivastigmine. After the treatment, his memory improved slightly. In 2017, the neurologist gave him quetiapine and donepezil due to developing visual hallucinations and irritability. The second brain MRI scan revealed increased frontal and temporal atrophy compared with the first one ( figure 1C at the age of 61). The FDG-PET revealed that the cerebral cortical glucose metabolism was further reduced, especially the bilateral frontal and parietal lobes were obvious ( figure 1D at the age of 61).

Brain imaging and cognitive score of the patient. (A) The patient’s MRI in May 2015 revealed mild atrophy of the bilateral frontal lobe (at the age of 59). (B) The patient’s FDG-PET in May 2015 revealed that glucose metabolism in the bilateral frontal and parietal lobe was reduced, and the left side was significant (at the age of 59). (C) The patient’s MRI in July 2017 (2 years after the first scan), revealed more atrophy of the bilateral frontal lobe and temporal lobe atrophy occurred (at the age of 61). (D) The patient’s FDG-PET in August 2017 revealed that the cerebral cortical glucose metabolism was reduced more, bilateral frontal and parietal lobes obvious in particular (at the age of 61). (E) The patient’s third MRI in May 2019 (2 years after the second scan) revealed atrophy of the whole cerebral cortex with bilateral frontal lobes, temporal lobe and hippocampus more affected (at the age of 63). (F) The patient’s 11C-PIB PET in May 2019 revealed saliently amyloid deposition in diffuse cortical areas, particularly in the bilateral frontal, parietal, temporal cortices and posterior cingulated gyrus (at the age of 63). (G) Mini-Mental State Examination (MMSE) of the patient. MMSE in May 2015 revealed a total score was 18/30 (at the age of 59). MMSE in May and December 2019 revealed a total score were 3/30 and 2/30; the results showed severe impairments in language and other cognitive areas (at the age of 63). 11C-PIB PET, 11C-Pittsburgh compound B positron emission tomography; FDG-PET, fluorodeoxyglucose positron emission tomography.

In May 2019, the patient’s symptoms aggravated further, which included bad temper, crying often and being more difficult to be looked after. His wife brought him to seek help from a psychiatrist, and he was admitted into the Department of Geriatric Psychiatry of Shanghai Mental Health Center. He underwent routine laboratory tests to exclude non-neurodegenerative and dementia. His neurological examination showed gait abnormality, negative Babinski’s sign, muscular tension hyperactivity, knee jerk reflex hyperactivity and a weak positive right palmar jaw reflex. The MMSE score was 3/30. The patient exhibited severe impairments in orientation (2/10), attention and calculation (1/5), recall (0/6), language (0/8) and visual construction (0/1). The Montreal Cognitive Assessment score was 0 (0/30), which was significantly lower than it was in 2015( figure 1G ). The third brain MRI demonstrated atrophy of the cerebral cortex, especially in the bilateral frontal lobes and hippocampus. The medial temporal lobe atrophy scale was at grade 3 ( figure 1E at the age of 63).

In addition, we tested three pathogenic genes for early-onset AD including amyloid precursor protein, presenilin-1, presenilin-2 genes related to neurocognitive disorders, but no mutation was found. Apolipoprotein E (APOE) genotyping showed APOE ε3/ε3 type. In order to reach a definite diagnosis, the patient underwent 11C-Pittsburgh compound B positron emission tomography (11C-PIB PET) and cerebrospinal fluid (CSF) examination. 11C-PIB PET revealed noticeable amyloid deposition in diffuse cortical areas, particularly in the bilateral frontal, parietal, temporal cortices and posterior cingulated gyrus ( figure 1F at the age of 63). The measured CSF biomarkers showed decreased amyloid β-protein (Aβ) 42 (462 pg/ml; cut-off >562 pg/ml), increased total tau (754 pg/ml; cut-off <370 pg/ml) and increased phosphorylated tau (87.40 pg/ml; cut-off <66.26 pg/ml). Eventually, the diagnosis of frontal variant EOAD was reconfirmed considering the early onset of dementia, the slow progression of symptoms, the absence of focal neurological damage signs and the exclusion of other systemic or brain diseases that could cause dementia. Due to the gastrointestinal adverse reactions of the patient, rivastigmine was suspended. We used memantine 10 mg b.i.d. and donepezil 5 mg q.d. to improve cognition and to control psychobehavioural symptoms and vortioxetine 10 mg q.d. to improve mood. After the treatment and follow-up for 7 months, the patient’s behaviour and mood was improvved significally, and his language expression improved slightly ( figure 1G at the age of 63).

The initial clinical manifestations of the patient included short-term memory decline, poor pronunciation and personality changes at an early stage, followed by behavioural and psychological symptoms of dementia, including hallucinations, delusions of theft, gradual decline in self-care as well as depression. The patient’s brain MRI initially showed mild atrophy of the bilateral frontal lobe. With the progress of the disease, more severe atrophy of the cerebral cortex, temporal lobe and hippocampus appeared besides the further atrophy of the bilateral frontal lobe. The atypical manifestation such as early aphasia, frontal lobe atrophy and personality changes can mislead clinicians in diagnosing frontotemporal lobar degeneration. This is the main reason leading to the misdiagnosis of this patient, which should be taken as a lesson or future reference for clinicians.

According to the current classification schemes, the clinical symptoms were in line with PNFA, which are halting speech by speech sound errors with spared content word comprehension and atrophy of the left frontal lobe. 4 PNFA is one of the primary progressive aphasias. 4 This patient met the diagnostic criteria of frontotemporal dementia, consistent with the early personality changes and cognitive abnormalities. 5 In the past 7 years, the patient’s speech fluency and cognitive function decreased continuously and rapidly. The clinical manifestations could not be explained by typical AD. The CSF phosphorylated tau was slightly higher, and no gene mutations associated with AD were found, which further made it harder to reach the diagnosis. However, the 11C-PIB PET showed heavy and extensive Aβ-amyloid depositions and provided definite pathological evidence of AD. A retrospective study found PNFA with 13%– 31% of cases might have the pathology of AD. 6 The patient met the research diagnostic AT(N) framework of AD, with A: (11C-PIB PET revealed amyloid depositions, CSF Aβ42 decreased), T: (CSF phosphorylated microtubule-associated protein tau increased) and N: (cortical atrophy on MRI, glucose hypometabolism in the bilateral frontal parietal lobe and CSF total microtubule-associated protein tau increased). 7 We use the AD pathological markers as the gold standard to exclude other types of dementia and reach an earlier and more accurate diagnosis. It’s worth pointing out that the patient might have mixed neuropathology. Santos-Santos 6 found that 75% of PNFA or PPA cases may have mixed pathological changes of FTLD and AD. This poses a new challenge for clinicians, suggesting that verified, reliable and accessible biomarkers for diagnosis of FTLD should be developed urgently. Otherwise, the comorbid pathological cases would only be accurately diagnosed after autopsy.

After reaching a clear diagnosis, and according to the China guidelines for the diagnosis and treatment of dementia and cognitive impairment in 2018 and the guidelines for the diagnosis and treatment of AD, 8 the patient was treated with cholinesterase inhibitors and excitatory amino acid receptor antagonists to enhance cognition, and antidepressants were given to relieve his mood. After the treatment, the patient’s symptoms were improved, and his mood was stable. Additionally, the biopsychosocial medical model has become more and more accepted. We should treat the patients with medication and non-drug intervention for patients and their caregivers. Spouses and caregivers of patients with early-onset dementia bear a greater burden and higher depression rates. 9 The speech impairments of this patient appeared early. He was emotionally unstable, grumpy and easy to be tearful, which was alleviated when his wife comforted him. Two weeks later, he was released from the hospital and continued to receive comprehensive rehabilitation treatments. Anyway, providing individualised psychosocial support for patients and their caregivers is very important for improving symptoms and quality of life. 10

Some of PNFAs are due to the underlying pathology of AD, which is more common in EOAD. In the present case, neither clinical examination nor MRI could definitively differentiate FTLD from EOAD. According to AT(N) research framework, we could eventually confirm the neuropathy diagnosis of AD or frontal-variant AD (fvAD), but the previous misdiagnoses were significant. FvAD can lead to social withdrawal and depression. These patients should benefit from accurate diagnosis, medication treatment and individualised psychosocial intervention.

Lin Zhu obtained a bachelor’s degree in clinical medicine from Shanghai Jiao Tong University School of Medicine, Shanghai, China in 2006. She is currently working as an attending doctor and psychotherapist at the Neurorehabilitation Department of Shanghai Third Rehabilitation Hospital. After completing clinical training, she started a two-year master program and was certified by the Institute of Psychology of the Chinese Academy of Sciences. In addition, she has also been trained and actively involved in clinical neurological research for half year in the Department of Geriatric Psychiatry of Shanghai Mental Health Center, Shanghai, China. Her main research interest includes the rehabilitation of elderly with psychiatric disorders.

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A new Alzheimer's study suggests where you live can affect the odds of a diagnosis

Juliana Kim

Medical instruments are pictured at the Actors Fund's Al Hirschfeld Free Health Clinic on March 23, 2011, in New York City. Researchers found that the odds of getting a formal dementia diagnosis in the U.S. differed based on location. Spencer Platt/Getty Images hide caption

In the United States, it's estimated that about 7 million people are living with Alzheimer's disease and related dementias. But the number of people with a formal diagnosis is far less than that. Now, a new study suggests the likelihood of getting a formal diagnosis may depend on where a person lives.

Researchers at the University of Michigan and Dartmouth College found that diagnosis rates vastly differ across the country and those different rates could not simply be explained by dementia risk factors, like if an area has more cases of hypertension, obesity and diabetes.

The reasons behind the disparity aren't clear, but researchers speculate that stigma as well as access to primary care or behavioral neurological specialists may impact the odds of getting a formal diagnosis.

"We tell anecdotes about how hard it is to get a diagnosis and maybe it is harder in some places. It's not just your imagination. It actually is different from place to place," said Julie Bynum, the study's lead author and a geriatrician at the University of Michigan Medical School.

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Those differences may have potential consequences. That's because a formal diagnosis of Alzheimer's opens up access to treatments that may slow down the brain changes associated with the disease. Without that formal diagnosis, patients also would not be eligible for clinical trials or insurance coverage for certain medications. Even in cases of dementia where treatment is not an option, a diagnosis can also help in the planning for a patient's care.

The findings , published last week in the journal Alzheimer's & Dementia , emerged from two main questions: What percent of older adults are being diagnosed with dementia across communities in the U.S.? And is the percent we see different from what we would expect?

To answer these questions, researchers used Medicare and demographics data to create two maps. The first displayed the percentage of people receiving a formal diagnosis in each hospital referral region (HRR), which divides the country into 306 areas based on where people are likely to seek treatment. The second estimated what the percentage should be in each HRR based on health risk factors and race.

What they discovered was that the two maps were vastly different, with parts of the Great Plains and Southwest seeing less diagnosis than expected. For example, a person in Wichita Falls, Texas, may have twice the likelihood of getting a diagnosis than a person living in Minot, N.D.

'Providers Don't Even Listen': Barriers To Alzheimer's Care When You're Not White

"Even within a group of people who are all 80, depending on where you live, you might be twice as likely to actually get a diagnosis," Bynum said.

It's difficult to say for certain if an area is under-diagnosing, because researchers compared each HRR to the national diagnosis average instead of the actual number of cases in each community, she added.

But the findings shed new light on why dementia diagnosis is more prevalent in some areas than others — and that it does not simply have to do with an individual's risk factors alone, but also access to health care resources and education on the disease.

Erin Abner, an epidemiologist at the University of Kentucky who was not involved in the study, said the results were not surprising and that there are many barriers to diagnosis.

"Where we live is a powerful influence on our brain health," she said. "It is very difficult for adults in many parts of the country to access behavioral neurological specialist care — in many cases waiting lists to be seen are months or even years long."

For some, language and cultural differences can also impact access to care .

Diagnosing Alzheimer's can be a long process that includes cognitive and neuropsychological assessments, as well as tests showing the presence of amyloid plaques in the brain. Bynum hopes the findings will help draw attention to the role that health care systems have on diagnosis rates and finding people who may be living with dementia under the radar.

"This other component of what the health care system and our public health system might do in informing and educating populations, that's also relevant and important," Bynum said. "And in some ways, we can fix that."

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A new era for alzheimer’s disease may be around the corner.

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A woman, suffering from Alzheimer's disease, looks at an old picture on March 18, 2011 in a ... [+] retirement house in Angervilliers, eastern France. AFP PHOTO / SEBASTIEN BOZON (Photo credit should read SEBASTIEN BOZON/AFP via Getty Images)

The recent FDA approval of Eli Lilly’s new immunotherapy for slowing the cognitive decline of early Alzheimer’s marked another step forward in the push to develop effective therapies for this notoriously difficult disease.

After two decades of no new Alzheimer’s drugs, the FDA has approved both this new drug, donanemab , and another immunotherapy called lecanemab in the past couple of years, offering the first glimmers of hope to the more than six million Americans who live with the disease. (In Europe, where I live, that number is estimated to be nearly eight million people .)

Both therapies attempt to clear toxic amyloid proteins from the brain through injectable monoclonal antibodies that are administered via regular infusions. Lecanemab is the most intensive, needing infusions every two weeks, while donanemab infusions are required monthly.

Dr Howard Fillit, co-founder and chief science officer of the Alzheimer’s Drug Discovery Foundation (ADDF) described the latest approval as “a very significant moment for the Alzheimer’s field,” but also cautioned that neither therapy is a panacea. A clinical trial showed that donanemab can slow the rate of cognitive decline by 35 percent over 18 months, with both drugs seemingly delaying disease progression rather than halting it altogether.

“While this class of drugs is only modestly effective, slowing cognitive decline by around 30%, they provide around six months of stability where the patient’s disease does not progress any further,” says Fillit. “It allows patients more time where they can remember their loved ones, which I believe is meaningful for a uniformly fatal disease like this one.”

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But right now, not all regulators are convinced by the benefits of these treatments, compared with the risks. In late July, European regulators rejected lecanemab, describing its benefits as ‘small’, while highlighting cases of brain swelling and bleeding within the treatment group. In Eli Lilly’s TRAILBLAZER-ALZ 2 trial of donanemab, more than a third of the treated group experienced brain bleeds while three patients died as a consequence of receiving the drug.

Now with a third antibody-based drug, Remternetug, also in clinical trials , there are questions surrounding whether such immunotherapies might be more effective if they were administered earlier in the disease course, perhaps even before the onset of symptoms.

In the future, testing this hypothesis in trials might be more feasible as the rise of these drugs has been accompanied by a parallel rise in blood tests that screen for molecular signals which mirror the accumulation of disease-causing proteins in the brain.

Two years ago, the National Institute on Aging funded a study which demonstrated that measuring certain amyloid biomarkers in blood plasma can predict the amount of amyloid in the brain, while some have suggested that tau, another toxic protein which forms tangles in the brains of Alzheimer’s patients, may be more closely linked to cognitive decline. A newly published study in the journal JAMA also described that testing for a tau-related biomarker in the blood, ptau-217, could detect whether a person has Alzheimer’s disease with 90% accuracy, better than cognitive assessments and CT scans.

Amyloid-removing immunotherapies are just one of the many approaches being explored for Alzheimer’s, and other treatment possibilities are likely to emerge.

“These drugs [lecanemab and donanemab] are the building blocks for the next generation of care and offer some reprieve as researchers work to develop more efficacious therapeutics targeting the underlying biology of the disease,” says Fillit.

Vaccines and the Biology of Aging

Fillit describes a general renewed sense of optimism within the field of Alzheimer’s drug development with ‘neuro-curious’ venture capitalists reaching out to his organization to learn more about emerging research.

One of the most active areas of investigation is Alzheimer’s vaccines, which attempt to trigger the immune system to produce its own antibodies against a multitude of disease-causing proteins in the brain.

The biotech company Prothena is currently developing a first-in-class vaccine that attempts to simultaneously target both amyloid and tau, while AC Immune and Alzinova have their own vaccine candidates in the pipeline. These efforts represent a considerable resurgence after the first Alzheimer’s vaccine was abandoned in the early 2000s due to reports of brain inflammation .

Kristina Torfgård, who worked on Alzinova’s candidate as the company’s former CEO, says that much has been learned from that early failure. The new, second generation vaccines take a much more nuanced approach.

“It is generally agreed that the peptide beta amyloid drives Alzheimer’s, but there are both non-toxic and toxic forms of this peptide,” she says. “The most toxic form is typically referred to as an oligomer, but if you are not specifically targeting this form, your vaccine is not likely to work because there will be so many off-target reactions to inert beta amyloid.”

In Alzinova’s case, Torfgård says that the immunogen in their vaccine candidate looks to generate antibodies against amyloid oligomers. While current trials are targeting Alzheimer’s patients with mild cognitive impairment, it is also possible that eventually such vaccines could be administered at a much earlier stage.

“With success, we could ultimately contemplate a preventative approach for individuals that do not currently have Alzheimer’s and evaluate the potential to slow or prevent transition to presymptomatic disease,” says Gene Kinney, president and CEO of Prothena. “Diagnostic advances will continue to be important with this.”

While the concept of Alzheimer’s vaccines against amyloid or tau has been on the radar for some time, a recent review paper found that 75% of the drugs in the pipeline are targeting pathways guided by the biology of aging.

“We now know that aging is the leading risk factor for Alzheimer’s, but Alzheimer’s is not a normal part of aging,” says Fillit. “With decades of learnings on how the dysfunctional processes caused by the biology of aging culminates in the disease, we have several novel pathways including inflammation, epigenetic and vascular and mitochondrial dysfunction, that researchers are looking to translate into new drugs.”

The brain uses 20% of the body’s energy supply, and aging research indicates that glucose metabolism breaks down with age, so some drugmakers are looking to slow cognitive decline by targeting this metabolic dysfunction. Fillit highlights how Novo Nordisk is currently investigating whether their GLP-1 drug semaglutide can help maintain the brain’s glucose metabolic rate.

Ultimately, Torfgård and Fillit both predict that as with other chronic diseases, such as cancer and hypertension, a cocktail of different treatment options will be required to address both the symptoms and various underlying causes of Alzheimer’s.

“With a disease this complex, we will need several drugs that can be used in combination with one another,” says Fillit. “Biomarker advances will allow physicians to personalize treatments based on each patient’s individual biomarker profile. The field’s current research may also open the door to disease prevention, as our ultimate goal is to slow the progression of the disease or to prevent its onset altogether.”

Thank you to David Cox for additional research and reporting on this article.

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Molecule restores cognition and memory in Alzheimer’s disease mouse study

Person in lab coat, surgical mask and gloves holds a film up to a light and looks at images of brain scans on it

In a new study, a molecule identified and synthesized by UCLA Health researchers was shown to restore cognitive functions in mice with symptoms of Alzheimer’s disease by effectively jump-starting the brain’s memory circuitry.

If proven to have similar effects in humans, the candidate compound would be novel among Alzheimer’s disease treatments in its ability to revitalize memory and cognition, study authors said.

“There is really nothing like this on the market or experimentally that has been shown to do this,” said study lead author Dr. Istvan Mody, the Tony Coelho Professor of Neurology and distinguished professor of physiology at UCLA Health.

The molecule, DDL-920, works differently from recent FDA-approved drugs for Alzheimer’s disease such as lecanemab and aducanumab, which remove harmful plaque that accumulates in the brains of Alzheimer’s disease patients. While removing this plaque has been shown to slow the rate of cognitive decline, it does not restore the memory or remedy cognitive impairments.

“They leave behind a brain that is maybe plaqueless, but all the pathological alterations in the circuits and the mechanisms in the neurons are not corrected,” Mody said.

In the study, published in the journal The Proceedings of the National Academy of Sciences, UCLA researchers led by Dr. Istvan Mody and Dr. Varghese John, a professor of neurology and director of the Drug Discovery Laboratory (DDL) at the Mary S. Easton Center for Alzheimer's Disease Research and Care at UCLA sought to find a compound that could figuratively flip the switch back on in the brain’s memory circuitry.

Similar to a traffic signal, the brain fires off electric signals at different rhythms to start and stop various functions. Gamma oscillations are some of the highest-frequency rhythms and have been shown to orchestrate brain circuits underlying cognitive processes and working memory – the type of memory used to remember a phone number. Patients with early Alzheimer’s disease symptoms such as mild cognitive impairment have been shown to have reduced gamma oscillations, Mody said.

Other studies attempted to use neuromodulation techniques to stimulate gamma oscillations to restore memory. Auditory, visual or transcranial magnetic stimulation at a frequency of 40 hertz – similar to the frequency of a cat’s purr – worked to dissolve plaques in the brain but again did not show notable cognitive enhancements, Mody said.

In this latest study, Mody and his team sought to tackle the problem from a different perspective. If they could not jump-start these memory circuits using external tools, perhaps there was a way to trigger these electrical rhythms from the inside using a molecule.

Specifically, they needed a compound to target certain fast-firing neurons, known as the parvalbumin interneurons, that are critical in generating gamma oscillations and therefore memory and cognitive functions. However, certain chemical receptors in these neurons that respond to the chemical messenger known as Gamma-aminobutyric acid, or GABA, work like brake pedals to reduce the gamma oscillations entrained by these neurons.

Mody, John and their team identified the compound DDL-920 to antagonize these receptors, allowing the neurons to sustain more powerful gamma oscillations.

To test whether this would result in improved memory and cognition, researchers used mice that were genetically modified to have symptoms of Alzheimer’s disease.

Both these Alzheimer’s disease-model mice and wild-type mice underwent baseline cognitive testing in a Barnes maze – a circular platform surrounded by visual clues and containing one escape hole. The maze is used to measure how well rodents can learn and remember the location of the escape hole.

After the initial tests, researchers orally administered DDL-920 to the Alzheimer’s model mice twice daily for two weeks. Following treatment, the Alzheimer’s disease-model mice were able to recall the escape hole in the maze at similar rates as the wild-type mice. Additionally, the treated mice did not display any abnormal behavior, hyperactivity or other visible side effects over the two-week period.

Mody said that while the treatment was effective in mice, much more work would be needed to determine if the treatment would be safe and effective in humans. Should it ultimately prove to be effective, the drug could have implications for treatments of other diseases and health conditions that have diminished gamma oscillations, such as depression, schizophrenia and autism spectrum disorder, Mody said.

“We are very enthusiastic about that because of the novelty and the mechanism of action that has not been tackled in the past,” Mody said.

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Case Study: A Precision Medicine Approach to Multifactorial Dementia and Alzheimer’s Disease

Mary kay ross.

a Brain Health and Research Institute, Seattle, WA, USA

b Washington University School of Medicine, St. Louis, MO, USA

Kristine L. Lokken

c Department of Psychiatry and Behavioral Neurobiology, University of Alabama-Birmingham, Birmingham, AL, USA

Dale E. Bredesen

d Department of Molecular and Medical Pharmacology, UCLA, Los Angeles, CA, USA

Jared C. Roach

e Institute for Systems Biology, 401 Terry Ave N, Seattle, WA, USA, 98109

Cory C. Funk

Nathan price, noa rappaport, james r. heath.

We report a case of a patient with mixed dementia successfully treated with a personalized multimodal therapy. Monotherapeutics are inadequate for the treatment of Alzheimer’s disease (AD) and mixed dementia; therefore, we approach treatment through an adaptive personalized multimodal program. Many multimodal programs are pre-determined, and thus may not address the underlying contributors to cognitive decline in each particular individual. The combination of a targeted, personalized, precision medicine approach using a multimodal program promises advantages over monotherapies and untargeted multimodal therapies for multifactorial dementia. In this case study, we describe successful treatment for a patient diagnosed with AD, using a multimodal, programmatic, precision medicine intervention encompassing therapies targeting multiple dementia diastheses. We describe specific interventions used in this case that are derived from a comprehensive protocol for AD precision medicine. After treatment, our patient demonstrated improvements in quantitative neuropsychological testing, volumetric neuroimaging, PET scans, and serum chemistries, accompanied by symptomatic improvement over a 3.5-year period. This case outcome supports the need for rigorous trials of comprehensive, targeted combination therapies to stabilize, restore, and prevent cognitive decline in individuals with potentially many underlying causes of such decline and dementia. Our multimodal therapy included personalized treatments to address each potential perturbation to neuroplasticity. In particular, neuroinflammation and metabolic subsystems influence cognitive function and hippocampal volume. In this patient with a primary biliary cholangitis (PBC) multimorbidity component, we introduced a personalized diet that helped reduce liver inflammation. Together, all these components of multimodal therapy showed a sustained functional and cognitive benefit. Multimodal therapies may have systemwide benefits on all dementias, particularly in the context of multimorbidity. Furthermore, these therapies provide generalized health benefits, as many of the factors – such as inflammation – that impact cognitive function also impact other systems.

INTRODUCTION

Recently, there has been increased interest in multimodal interventions for reducing the risk of Alzheimer’s Disease (AD). For example, the World Health Organization [ 1 ] published guidelines to reduce risk for cognitive decline and dementia that emphasize multimodal interventions. Reported lifestyle interventions include increased cognitive, physical, and social activity for reducing risk of cognitive decline [ 2 – 4 ]. Combination therapies and multimodal approaches have produced therapeutic success for chronic illnesses such as cancers, HIV, and cardiovascular disease. These initial successes demonstrate that targeted, multimodal approaches to AD deserve further and more detailed study.

In this paper, we present a single case study with full details of the clinical course and outcome. We describe a successful treatment response for a patient with previously diagnosed AD using a precison medicine, multimodal intervention with specific focus on treating potential contributors such as steroid hormone deficiency, thyroid deficiency, kidney function, liver function, vascular health, tick-borne infections, mercury toxicity, and mycotoxins. Each of these may independently contribute in this individual as an underlying driver of cognitive decline and the AD disease process. In presenting this case, we take a step towards filling a paucity in the literature for methods to evaluate and treat cognitive symptoms secondary to biotoxicity. Treating multimodal disease with potentially synergistic targeted interventions towards each disease modality should be a paradigm for the future of personalized medical treatment of many chronic diseases, particularly those that affect aging individuals.

CASE PRESENTATION

Background information.

A 78-year-old, left-handed retired female physician presented with a one-year history of severe, progressive memory loss, such that her significant other described her memory for recent events as “disastrous.” She described a lifelong mild dyslexia, and amnesia for many events of her early childhood and adolescence. She noted an awareness of mild cognitive problems for approximately 20 years, but these worsened in the year prior to evaluation. She also noted poor recall for movies that she had watched and books that she had read. She noted problems with name recall, and often called her pets by the wrong name. She noticed increased susceptibility to stress and fatigue which seemed to worsen when her son died a tragic death in 2001. At presentation, she reported leading an active life, enjoying golfing, hiking, birding, and gardening. She worked in private practice as a psychiatrist until she retired at the age of 75. She has always been actively involved in many civic associations, and remains active in political circles. She has a family history of dementia and memory issues: her mother developed dementia secondary to hydrocephalus, and her sister developed memory problems but died from an aneurysm at the age of 80. She reported exposure to mold in her partner’s home. She also stated that she has several dogs that she sleeps with in her bed. She lives in New York, does not use tick spray on the dogs, and reports an average of 10 tick bites per year. She had a remote history of Bell’s palsy on the left side of unknown etiology. Her past medical history is also significant for Raynaud’s syndrome, elevated gamma-glutamyl transpeptidase secondary to primary biliary cholangitis (PBC), and elevated mercury. She had elevated inflammatory markers suggesting exposure to biotoxins. She was diagnosed with early AD by her neurologist in 2016. In particular, a fluorodeoxyglucose-positron emission tomography (FDG-PET) scan revealed decreased glucose utilization in the anterior superior precuneus bilaterally and the anterolateral left temporal lobe which is consistent with the earliest manifestations of AD. Her neurologist recommended treatment with donepezil and memantine. She refused both because she had read about their minimal effects on decline and because she had read about anecdotal successes with programmatic treatment.

Mulitmodal Interventions for Alzheimer’s Disease

Recently, there has been increased interest in multimodal interventions for reducing the risk of Alzheimer’s Disease (AD). The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) was the first randomized controlled trial (RCT) demonstrating a beneficial effect of a 2-year multidomain intervention (using nutrition, physical activity, and cognitive training) on cognitive performance in older adults who were at risk for dementia based on vascular parameters [ 2 ]. World Health Organization guidelines include multimodal interventions [ 1 ]. Many others have reported success with lifestyle intervention (increased cognitive, physical, and social activity) in reducing risk of cognitive decline among individuals with mild cognitive impairment (MCI), and with aerobic exercise in improving executive function in those with early stage-cognitive impairment [ 5 , 6 ].

A recent publication by Isaacson et al. [ 7 ] provided further support for the application of multimodal lifestyle interventions to improve cognition and reduce AD and cardiovascular risk scores in patients at risk for AD. The authors used a personalized medicine approach when considering treatment options for patients. They found that multidomain interventions reduced AD and cardiovascular risk scores. In addition, in those seeking prevention, both high and low levels of compliance were associated with improved cognition with individualized multidomain interventions. Patients already exhibiting early cognitive impairment (MCI) showed improved cognition only with high levels of compliance with the individualized multidomain interventions, and cognition declined for those in the low compliance group. Anecdotal sustained improvements have been reported in over 100 patients with AD or MCI using a personalized, precision medicine approach that addresses presumptive contributors to cognitive decline, such as insulin resistance, systemic inflammation, and pathogens [ 8 ], although these are often not reported with detailed descriptions of the interventions and clinical course for each patient. Combination therapies and multimodal approaches have produced therapeutic success for chronic illnesses such as cancer, HIV, and cardiovascular disease [ 3 ]. Because of the complex nature of AD, with many potential and variable contributors, the initial success in prevention trials, and the anecdotal success with cognitive improvement in MCI and AD, a targeted, multimodal approach deserves further detailed study and documentation.

Individuals may vary due to genetics, environment, and lifestyle. Our precision medicine approach considers individual variability by utilizing an extensive evaluation including detailed medical history, lifestyle variables, blood biomarkers, neuroimaging with volumetrics, and quantitative neurocognitive assessments. Practitioners utilizing this approach can further examine whether patients with cognitive issues harbor a significant burden of toxicity contributing to their cognitive decline. Possible multimodal lifestyle interventions for cognitive decline in AD include diet, nutrition, exercise, mindfulness, and stress management. In addition to the effects of lifestyle, epidemiological and pathological studies suggest that there are numerous other underlying drivers such as environmental toxins and chronic infections. Environmental toxins may include mercury from seafood and amalgam fillings or biotoxins such as mycotoxins from mold exposure. Chronic infections could include herpes, gingival disease, COVID-19, or tick born disease such as Lyme disease [ 9 – 11 ]. The recent COVID-19 pandemic has raised the possibility of long-term cognitive effects given the neuroinvasive potential of this novel coronavirus [ 12 ]. Furthermore, pandemic stressors may worsen cognitive issues [ 13 ].

One study showed an 8% increase in hippocampal volume over a 12-week period with a multifaceted lifestyle program [ 14 ]. Additional literature has noted the influence of lifestyle-related factors such as obesity on brain atrophy, and the beneficial effects of physical activity and diet on gray matter volume [ 15 , 16 ]. Physical activity itself has also been linked with reduced burden of amyloid on PET scans [ 17 ]. A systematic review of multiple lifestyle factors including alcohol use and smoking suggested that fMRI also reflects both positive and negative influences of these factors on the physiologic changes reflected by this modality [ 18 ]. A randomized clinical trial of physical activity in 24 elderly women (75–83 years old) assigned either to 3 months of biweekly 90-min sessions focused on aerobic exercise, strength training, and physical therapy versus rest showed that the intervention group had improved glucose metabolism [ 19 ]. This parallels a larger randomized study showing improved hippocampal volumes in a physical activity group versus a passive stretching group on volumetric MR quantification [ 20 ]. A recent Canadian study suggested that a screening imaging program for dementia based in part by modifiable risk factors was financially manageable [ 21 ].

We recommended multimodal interventions for the treatment of this patient. These were personalized, and in addition to diet and exercise interventions, included hormone replacement, DMSA therapy for posisble heavy metal toxicity, Lyme therapy for posisble Borrelia infection, and cognitive training.

DMSA Therapy.

DMSA has a half life of 4 hours and it is important to keep the drug at a steady state so that the bound metals do not become reabsorbed and deposit in other tissues of the body. It is important to note that the order in which treatment progressed was very slow and chelation of heavy metals was actually one of the last therapies. The patient was treated in a progressive order that the chelation of heavy metals was one of the last things she was treated for in an effort to ensure that her gut health was good and that she was stronger and able to handle the chelation of mercury. With a history of PBC there was concern about her ability to sustain good liver detoxification. She was very sensitive to DMSA and noted a decrease in her cognition when she took a dose for provocation. While on chelation she was given herbs that enhance liver detoxification along with a rigorous nutrient regimen. The chelation protocol is: (1) Low Dose DMSA 10 mg/kg is the dose to be taken every 4 hours around the clock for 4 days drinking at least 8 ounces of water with each dose; (2) 10 days off between each 4 day treatment cycle, and (3) during the holiday between oral chelation we recommended patients replenish minerals and nutrients that have been removed with chelation.

Lyme Therapy.

Given dementia symptoms and the patients serologies, medications used for treatment of Lyme are: (1) Cefdinir 300 mg bid; (2) Azithromycin 500 mg qd; and (3) the Byron White herbal regimen.

Cognitive Training.

This patient engages in cognitive training using BrainHQ by Posit Science [ 22 ]. When she first embarked on this program she was unable to do BrainHQ and found it very frusterating. She initially was able to do a brain training program Elevate. She has since graduated to the BrainHQ and is now in the 94 th percentile. She states that she uses her BrainHQ score to help let her know how her cognition is going and it alarms her to any new problems. She is currently using BrainHQ 45 minutes per day.

Baseline Neurological and Cognitive Assessments

The patient underwent memory testing at the age of 65 while attending Canyon Ranch Health Resort. Testing consisted of the Wechsler Memory Scale-III (WMS-III). Results indicated that her Working Memory Index (WMI) was in the average range of ability (WMS-III WMI=108, 70 th percentile); however, her Immediate Memory Index (89, 23 rd percentile), Delayed Memory Index (88, 21 st percentile), and her General Memory Index (88, 21 st percentile) were all in the low average range of ability (see Table 1 ). Interpretation by the health resort clinical psychologist was that her memory was poorer than expected based on her vocation of medical doctor. It was therefore recommended that she undergo more extensive neuropsychological testing.

Hippocampal Volume Measurements. From 2016 to 2019 overall hippocampal volume increased 3%. Timepoints: 1 = 2016; 2 = 2017; 3 = 2019.

Timepoint	Left Hippocampus Volume (ml)	Left Hippocampus Vol/mTIV ratio	Left Hippocampus NR Index	Left Hippocampus Z-score	Left Hippocampus %
1	3.86	0.199	0.804	0.054	52.17
2	3.76	0.191	−1.28	−0.087	46.55
3	4.06	0.211	4.91	0.33	63.03

Timepoint	Right Hippocampus Volume (ml)	Right Hippocampus Vol/mTIV ratio	Right Hippocampus NR Index	Right Hippocampus Z-score	Right Hippocampus %
1	4.05	0.208	2.76	0.187	57.41
2	3.99	0.203	1.41	0.095	53.79
3	4.09	0.213	4.52	0.306	62.03

Timepoint	Hippocampus Volume (ml)	Hippocampus Vol/mTIV ratio
1	7.91	0.41
2	7.75	0.39
3	8.15	0.42

However, the patient did not seek further assistance for her memory complaints for several years due to actually forgetting. Her cognitive problems continued to progress insidiously, with an acceleration in cognitive decline starting at approximately age 74. She noted that she was starting to mix up the names of people and pets and that she was starting to have difficulty with navigating spaces, such as having difficulty finding her way back to her table at a restaurant after using the bathroom. An acquaintance encouraged her to look into integrative approaches to brain health, and she began a multimodal program under the supervision of Dr. Ross at what is now the BHRI clinic. She initiated the multimodal program in January 2017 at age 75.

Prior to starting the program, she saw a neurologist in order to obtain confirmatory diagnostic testing. She scored a 28/30 on the MMSE at the initial neurology evaluation in 9/2016. Her neurological exam was normal. She underwent an MRI of the brain in 9/2016 that revealed mild biparietal atrophy with hippocampal cysts on the right side. MRI also revealed a few scattered small foci of hyperintensity in the bilateral hemispheric white matter and paramedian pons, and evidence of a partially empty sella with flattening of the pituitary gland. Volumetric analysis revealed decreased hippocampal volume bilaterally. FDG-PET conducted in 9/2016 indicated mildly decreased FDG activity in the anterior superior precuneus bilaterally as well as in the anterolateral left temporal lobe. The findings were thought to represent early AD pathology and she was referred for neuropsychological testing.

A full neuropsychological evaluation was conducted in 11/2016. She reported to the evaluating neuropsychologist that her overall energy and cognitive problems had improved somewhat over the past few months with the lifestyle changes. Even so, her neuropsychological performances revealed impairments in reaction time, visual organization/constructional skills, and learning/recognition of unstructured information, within the context of estimated high average baseline intellectual capacity. She struggled on the testing with the intial learning of a word list and did not appear to benefit from repetition of the list. In fact, she reported that the words were “dropping out” following the learning trials. Her learning slope was in the borderline-impaired range (7 th percentile). Recognition performance was also notable for a remarkably high number of false positive errors. Learning improved when the verbal material was presented in a contextual format of a story. Reaction time on a computerized measure was slowed, and her approach to drawing a complex geometric figure was disorganized and poorly planned, resulting in inaccuracies in the placement and spacing of the figure details. She performed in the borderline-impaired range on this task (2 nd -5 th percentile). This constellation of findings was felt to be most compatible with early AD.

Clinical Course

A multimodal program was prepared for this patient tailoring the appropriate neutraceuticals and medications to fit this patient’s specific needs. Labs and biomarkers were evaluataed and targeted neutraceuticals were used to optimize levels of hormones, vitamins, glucose, and insulin. Her history of tick bites and Bell’s palsy prompted a workup that revealed a positive Western blot IgM for Lyme disease. She was placed on oral antibiotics and an herbal regimen for 3 months. Her thyroid and sex hormones were suboptimal, so she was placed on bioidentical hormone therapy as well as natural thyroid replacement. She was tested for heavy metals using a pre- and post-provocation test (Doctors Data) that revealed elevated mercury. She initially went to an integrative practice in New York for IV glutathione while she underwent oral chelation [ 23 ]. She was placed on an oral chelation protocol using DMSA. The patient was hospitalized with ehrilichiosis and received IV antibiotics; she states that she noticed an increase in her energy following the antibiotics. She had a home sleep study in 2020 and was found to have moderate sleep apnea. She began CPAP, and now reports even better energy and subjective cognitive function. She also trains her cognitive function with BrainHQ. She also uses a Vielight Gamma, Oura Ring, and MUSE Headband. She meets with a neuro physical therapist via Zoom twice weekly for excise sessions that are coupled with dual tasking. She feels that exercising with dual tasking has contributed greatly to her cognitive rehabilitation. We measured system-wide clinical markers and followed their longitudinal trajectory ( Figure 1 ). The average date of the inflection point towards a positive trend in these markers was in May 2017 five months after start of therapy, suggesting a synergistic and cumulative impact of multimodal interventions within months of commencing therapy.

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Trajectories of select clinical chemistries. Hippocampal volume measurements are shown for comparison. Orange line; upper bound of reference. Blue line; lower bound of reference. Multimodal treatment of the entire individual results in subtle changes that impact many physiological subsystems. Although these impacts often change trajectories only within traditional reference ranges, the cumulative effect on well being may be pronounced.

Neuroimaging

The patient’s MRI of the brain on 9/2016 showed a quantified hippocampal volume of 16th percentile on NeuroQuant. Her FDG-PET scan was qualitatively interpreted as having low metabolism in the anterior precuneus and anterolateral temporal lobes. This report also noted a qualitative description of “mild biparietal atrophy.” Neuroquant, the software program that measures these volumes initially has been shown to underestimate hippocampal volume [ 24 ] compared to another FDA-cleared program called Neuroreader, which is also utilized for MRI brain structural quantification [ 25 ]. While each software program compares brain volumes to a normal database, they utilize different databases. It has been published with Neuroreader that its normal database comes from the Alzheimer’s Disease Neuroimaging Initiative Database (ADNI), a well validated and well published research cohort [ 25 ]. It should be noted therefore that while the intial Neuroquant analysis suggested a hippocampal volume at 16 th percentile, the Neuroreader analysis for that same scan showed a more normal value of 54 th percentile. It should also be noted that while the intial FDG PET scan suggested AD based on the parietal hypometabolism, there was no medial temporal lobe hypometabolism reported, although as noted above, there was hypometabolism noted in the precuneus.

The visually interpreted mild biparietal atrophy on the MRI from 2016 was not supported by the quantitative result from Neuroreader, showing a normal parietal lobe volume of 49 th percentile. This discrepancy highlights the need for quantitative evaluations of atrophy, which are usually more accurate than visual evaluations [ 26 ]. Longitudinal evalutions are also key in determining suggestive evidence of AD, since progressive atrophy is noted in conjunction with neurodegenerative disease [ 27 ].

With respect to these longitudinal evaluations, the 2017 brain MRI scan showed a reduction in hippocampal volumes compared to 2016, and this was observed with Neuroquant, as well, although, again, with a lower percentile from that scan at 11 th percentile compared to the still normal hippocampal volume percentile on Neuroreader of 50 th percentile. Additionally, as with the 2016 scan, none of the patient’s brain volumes were found to be abnormally low. It should also be noted that while the Neuroquant percentiles of 11 th or 16 th percentile may be considered abnormally low, the Neuroquant software program uses a 5 th percentile cutoff to determine abnormally low volume,s while Neuroreader uses a 25 th percentile threshold. Overall, the patient’s hippocampal volume from 2016 to 2017 declined on Neuroreader by 3%, which is an abnormal rate of atrophy, as it should normally be declining by only 0.5% per year. Such enhanced rate of decline is a poor prognostic feature in Alzheimer’s patients and in the the risk for conversion from MCI to AD [ 27 ]. However, from 2017 to 2019 the patient’s hippocampal volume to mTIV ratio showed an increase by 8% to the 62nd percentile – up considerably from the 50 th percentile in 2017 ( Table 1 ). Previous publications have shown that the hippocampus is neuroplastic enough to increase in volume when exposed to multimodal personalized treatment programs and lifestyle changes. The volumes for other brain regions, as with 2017 and 2016 studies, were found to be in the normal range. The summary of changes in hippocampal volumes are shown in Figure 2 .

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Hippocampal volume changes in the patient from 2016 to 2019. The hippocampal volume decreased from 2016 to 2017 (red line) and then increased between 2017 and 2019 (green line). Volumes were determined with Neuroreader software.

Longitudinal Biomarker Analyses

For each biomarker, we fit a quadratic regression to all longitudinal values. To compute the inflection point (typically the nadir) for each trajectory, we computed the vertex of the parabola resulting from the quadratic regression. In some cases, such as monotonically increasing values (e.g., Vitamin D) we did not compute an inflection point. For the following analytes dates of inflection are: GGT 11/4/16, BUN 7/3/17, alkaline phosphate 12/9/16, homocysteine 9/12/17, ALT 5/15/17, bilirubin 12/21/17. The average inflection date is May 23, 2017. These inflection points group together at approximately the same time (late 2016 through 2017) which is consistent with the timing of full impact of the multimodal intervention.

Improvements in Cognition and Function

As noted above, the patient’s presentation, pattern of cognitive decline, chronicity and progression, neuropsychological testing, MRI volumetrics, and FDG-PET scan results were compatible with a diagnosis of early AD. She has undergone treatment from 2016 to the present. From 2016 until 2020, the patient noted marked subjective improvements in memory. She noted that she was able to remember her golf strokes and those of her friends once again. She no longer failed to feed the parking meters and did not leave her car in the road while still running. Her significant other noted that her memory improved from “disastrous” to “just plain lousy” and ultimately to “normal.”

In the later part of 2019 this patient was able to fly from New York to Seattle unaccompanied and navigated the entire trip on her own with no problem; a patient dignosed with AD in 2016 would most likely not be traveling across the country alone 3 years later. These marked subjective changes were accompanied by objective changes. She consistently used BrainHQ cognitive training; her position in the reference range provided by BrainHQ improved from 9 th to 97 th percentile. Her Montreal Cognitive Assessment (MoCA) was 23 in 10/2017, was stable at 23 in 12/18 and improved to 26 in 11/2019. Her hippocampal volume increased from 50 th to 62 nd percentile, a volume increase of 8%; a positive change this large over this period of time was seen in only 3% of reference AD participants in ADNI [ 28 , 25 ]. Her FDG-PET scan also showed improvement. Her initial FDG-PET revealed mildly decreased FDG activity in the anterior superior precuneus bilaterally as well as in the anterolateral left temporal lobe. The remainder of the brain parenchyma had normal ativity. An interpretation could be that the mild biparietal and hippocampal volume loss with concordant subtle FDG hypometabolism represented the earliest imaging manifestations of underlying AD pathology in her case [ 14 ]. The repeat FDG-PET, which was conducted on the same machine, revealed mild patchy hypometabolism of the superior parietal and anterior temporal lobes along with the superior parietal volume loss which was unchanged from the previous measurement. These findings suggested that age-related changes could account for mild cognitive impairment.

The patient underwent follow-up neuropsychological testing in 11/2019 at the age of 78, after following multimodal treatment recommendations for over three years. Results were compared with her memory testing conducted in 12/2006 at the age of 65 and full neuropsychological testing conducted on 11/2016 at the age of 75 ( Table 2 ).

Neuropsychological Test Performances.

Test	2006	Year 2016	2019	Change from 2016–2019

Immediate Memory (IM) Stories (scaled score)	9	13	12	−1
Recall IM (percent)	41	57	68	11%
Delayed Memory (DM) Stories (scaled score)	9	13	11	−2
Recall DM (percent)	30	46	51	5%
Delayed Retention (percent)	ND	67.7	83	15%
Recognition (percent)	ND	83	86	3%
CVLT-II LDFR (scaled score)	ND	7	9	2
CVLT-II LDCR (scaled score)	ND	7	9	2
Visual Immediate (IM) (scaled score)	7	6	13	7
Visual Delayed Memory DM (scaled score)	13	10	14	4

DigSpan (scaled score)	ND	11	12	1
Coding (scaled score)	ND	9	11	2
Trails A (scaled score)	ND	8	9	1
Rey Copy (scaled score)	ND	4	8	4
Phonemic Fluency (scaled score)	ND	10	9	−1
Semantic Fluency (scaled score)	ND	11	9	−2
Trails B (scaled score)	ND	11	10	−1
WCST (scaled score)	ND	8	8	0

Her estimated intellectual function was stable over time. In 11/2019, she obtained an estimated Full-Scale IQ of 122 which corresponds with the 93 rd percentile and the superior range of functioning. This was considered commensurate with her performance of an estimated Full-Scale IQ of 117 (87 th percentile, high average range) at the 2016 neuropsychological evaluation.

In 11/2019, she scored a 26/30 on the MoCA and a perfect score of 58/58 on the WMS-IV Brief Cognitive Status Evaluation. Her performance on the MoCA showed improvement at this 2019 timepoint in comparison with scores of 23/30 in 2/2017, 23/30 on 10/2017 and 23/30 in 12/2018. Her performance on tests of basic attention, working memory, and processing speed were in the average range (WAIS-IV Digit Span, 75 th percentile; WAIS-IV Coding, 63 rd percentile; Trailmaking Test – Part A, 58 th percentile). These performances reflected slight improvements in comparison to her 2016 evaluation. Performances on measures of both phonemic and semantic verbal fluency were slightly declined in comparison to her 2016 evaluation. She performed at the 32 nd percentile on a test of semantic verbal fluency at the 2019 evaluation, in comparison to the 63 rd percentile although both performances were in the average range of ability. She performed in the low average range on a test of phonemic verbal fluency (FAS, 21 st percentile) at the 2019 evaluation, which was slightly lower than her 2016 performance (39 th percentile).

In terms of visuospatial skills, she had significant difficulty with copying the cube on the MoCA at past evaluations but was able to complete the task with full credit given at the most recent evaluation in 2019. She performed in the average range when copying a complex figure (Rey Complex Figure Test – Copy, 32/36 which is >16 th percentile), reflecting marked improvement in her performance in comparison to the 2016 evaluation (Rey Complex Figure Test – Copy, 24/36 which is 2 nd -5 th percentile) ( Figure 3 ). Her performance on the WAIS-IV Block Design subtest was in the average range (37 th percentile) and consistent with her 2016 performance (50 th percentile).

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Organization and detail of Rey figure drawing from 2017 to 2019.

Executive functions were stable over time. She performed in the upper end of the average range on a task of mental flexibility (Trailmaking B Test, 68 th percentile) in 2019 and this was consistent with her 2016 performance (70 th percentile). She easily completed a problem-solving task, achieving all 6 of 6 categories on the Wisconsin Card Sorting Test, with error responses all in the average range. This was also consistent with her 2016 performances. Her ability to learn and immediately recall a complex line drawing was in the high average range for both immediate (86 th percentile) and delayed (92 nd percentile) memory. Although the recall portion of this test was not given at her 2016 evaluation, her performance was in the average range on a similar visual memory task.

Her performance on a verbal list learning task was generally consistent with her performance at the 2016 evaluation. She did improve to learn and recall one additional word, moving her performance to the average range (30 th percentile) at the 2019 evaluation in comparison to her low average (16 th percentile) performance at the 2016 evaluation for short delayed cued recall and long delayed cued recall. Her performance was stable on a story memory task. At the 2019 evaluation, she performed in the average range for learning and memory of auditory information and she was able to retain 83 percent of what she initially learned after a 30-minute delay.

Her most recent cognitive testing indicated generally intact cognitive function across most neurocognitive skills. Her neuropsychological profile indicates general stability over time, with some possible restoration of cognitive function in visuospatial skills, auditory learning and memory, nonverbal memory, and processing speed. Given her high level of intellectual capacity, it is likely that performances in the average range may actually indicate a change in cognition relative to her true abilities. Minor weaknesses continued to be observed in the learning, free recall, and recognition of unstructured information (e.g. word list) and also in phonemic verbal fluency.

Overall, from 2017 to 2019 she manifested measured improvement of cognitive function in visuospatial skills, auditory learning and memory, nonverbal memory, and processing speed, with stability in executive functioning and in other areas of cognition. Stability in cognitive function over a period of 2–3 years for a person diagnosed with early AD is a clinical success. Most patients experience cognitive decline, especially in learning and memory. This patient demonostrated improvements across a variety of cognitive skills.

Given the need for effective AD treatments, it is instructive to identify patients who show improvement or long-term stability, and then evaluate connections between treatments and outcomes. Since AD is a complex multimodal chronic illness, it is essential to evaluate numerous potential contributing factors. Here, we present a case study of multimodal therapy for multimorbid dementia. The patient demonstrated improvements in symptoms, neuropsychological assessments, and brain imaging. An advantage of multimodal intervention is that the health and homeostasis of diverse physiological subsystems can be addressed concurrently. Since many of these subsystems contribute, possibly incrementally, possibly synergistically, or possibly substantially to cognitive function, they all need to be considered. Where appropriate, those that are disease-perturbed should be addressed. In particular, interventions in this individual addressed two key subsystems that influence cognition: neuroinflammation and metabolism. Neuroinflammation appeared to be induced by Borrelia burgdorferi , Ehrlichiosis and heavy metal toxicity – as well as suboptimal nutrient and hormone levels. There is evidence that chronic infection with Borrelia burdorferi such as neuroborreliosis can play a role in the development of AD [ 29 – 31 ]. Our multimodal therapy included personalized treatments to address each of these potentially underlying neuroinflammatory causes. Liver and other metabolic subsystems also influence cognitive function and hippocampal volume [ 32 ]. We introduced a personalized diet that helped reduce liver inflammation due to PBC evidenced by a sustained drop in GGT ( Figure 1 ). Together, all these components of multimodal therapy showed a sustained functional and cognitive benefit. Furthermore, multimodal therpaies may have systemwide benefits as many of the factors – such as inflammation – that impact cognitive function also impact other systems [ 33 ]. Therefore multimodal therapies are particularly appropriate for individuals with multimorbidities.

To some extent, multimodal intervention can be likened to pulling an airplane out of a dive. There may not be an immediate shift from decreasing function to increasing function. Because many factors are changing, one expects a time delay between when one starts to intervene and the lowest point of the curve. Furthermore, one does not necessarily expect all the inflections of all possible assays at exactly the same time, as each physiologic subsystem has distinct dynamics. However, with a comprehensive multimodal program, we do expect them roughly the same time, as we see in these data ( Figure 1 ).

It is essential to take a detailed history and listen to the patient and family members recount the events leading up to the patient’s illness. It is imperative when faced with a patient like this that we consider their entire “exposozome” including their daily living environment. We should consider factors such as mold, in-home toxins, biotoxin exposure, heavy metals, diet, stress management, hormone balance and lifestyle. We believe that an approach of first identifying the many potential contributors to cognitive decline and then applying a personalized, precision medicine approach is essential to designing effective treatments for AD. Such an approach is quite distinct from the typical single drug-centric approach that pre-determines a treatment that is unrelated to the potential etiologic contributors. Chronic illness as it relates to AD is a continuum that starts decades earlier. Cases such as this one suggest that many of these factors can be systematically addressed and reversed. As this is expanded and tested in clinical trials, this represents an exciting approach to 21 st -century medicine and the treatment of chronic disease with a new lens. The COCOA and PREVENTION trials are examples of trials using this approach [ 34 , 35 ].

This case also highlights differences between multiple defintions of “Alzheimer’s disease” in use spanning research and clinical contexts. The Alzheimer’s Association and National Institute of Aging provide a fairly clear framework for the definition of AD to be used in a research context [ 36 ]. This framework requires the documentation of molecular (e.g., amyloid) pathology. We do not know if the patient in this case study has such molecular pathology and cannot definitely classify this patient using the NIA-AA framework. In clinical practice, AD is often diagnosed presumptively, without assays for molecular markers [ 37 ]. The absence of testing for such markers is not always due to diagnostic malpractice; in some cases these tests are not available, are too expensive, are too invasive, would not impace care, or are otherwise contraindicated. Compared to some other diseases, such as infectious diseases, the clinical utility of a confident and precise diagnosis of AD is less. These other diseases have more clearly understood causal pathologies that clearly point to particular monotherapies. One advantage of a personalized multimodal approach for dementia is that it is robust to imprecision in diagnosis and nascent understandings of causalities. Treating multiple possible causes of dementia, personalized based on clinical and molecular evidence, and responding dynamically based on patient response can lead to clinical benefit even in complex cases of mixed dementia.

We have presented a single case example. In our experience, this patient is representative of many whose manifestations and pathophysiology are complex. Each patient has a slightly different presentation and combination of drivers of dementia, but treatments and outcomes via this precison medicine approach share more similarities than differences. The improvement observed in this patient underlines the need for clinical trials to test treatment protocols such as the one described here. The treatment program for this person may provide a guidepost for preventing or reversing the cognitive impairment of others with dementia.

Acknowledgement

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database ( adni.loni.usc.edu ). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at adni.loni.usc.edu .

Funding Statement

Providence St. Joseph Health provided generous funding for the Alzheimer’s Translational Pillar (ATP) at ISB. Analysis was supported by NIH U01AG046139, RF1AG057443, U01AG061359, & R01AG062514.

Conflicts of Interest

The authors have no conflicts of interest to declare.

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Published: 21 August 2024

Serum proteomics reveal APOE-ε4 -dependent and APOE-ε4 -independent protein signatures in Alzheimer’s disease

Elisabet A. Frick 1 ,
Valur Emilsson ORCID: orcid.org/0000-0001-9982-0524 1 , 2 ,
Thorarinn Jonmundsson ORCID: orcid.org/0000-0001-9158-0087 2 ,
Anna E. Steindorsdottir ORCID: orcid.org/0000-0002-2386-5934 2 ,
Erik C. B. Johnson ORCID: orcid.org/0000-0002-0604-2944 3 , 4 ,
Raquel Puerta ORCID: orcid.org/0000-0002-1191-5893 5 ,
Eric B. Dammer ORCID: orcid.org/0000-0003-2947-7606 3 , 6 ,
Anantharaman Shantaraman ORCID: orcid.org/0000-0003-1384-941X 3 , 6 ,
Amanda Cano 5 , 7 ,
Mercè Boada ORCID: orcid.org/0000-0003-2617-3009 5 , 7 ,
Sergi Valero 5 , 7 ,
Pablo García-González ORCID: orcid.org/0000-0003-0125-5403 5 , 7 ,
Elias F. Gudmundsson ORCID: orcid.org/0000-0002-7661-4872 1 ,
Alexander Gudjonsson 1 ,
Rebecca Pitts ORCID: orcid.org/0000-0003-4733-414X 8 ,
Xiazi Qiu ORCID: orcid.org/0000-0002-8397-2168 8 ,
Nancy Finkel 8 ,
Joseph J. Loureiro ORCID: orcid.org/0000-0001-7222-9160 8 ,
Anthony P. Orth ORCID: orcid.org/0009-0005-9865-0494 9 ,
Nicholas T. Seyfried ORCID: orcid.org/0000-0002-4507-624X 3 , 4 , 6 ,
Allan I. Levey ORCID: orcid.org/0000-0002-3153-502X 3 , 4 ,
Agustin Ruiz ORCID: orcid.org/0000-0003-2633-2495 5 , 7 ,
Thor Aspelund ORCID: orcid.org/0000-0002-7998-5433 1 , 2 ,
Lori L. Jennings ORCID: orcid.org/0000-0001-5130-8417 8 ,
Lenore J. Launer ORCID: orcid.org/0000-0002-3238-7612 10 ,
Valborg Gudmundsdottir ORCID: orcid.org/0000-0002-7459-1603 1 , 2 &
Vilmundur Gudnason ORCID: orcid.org/0000-0001-5696-0084 1 , 2

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Alzheimer's disease
Functional genomics

A deeper understanding of the molecular processes underlying late-onset Alzheimer’s disease (LOAD) could aid in biomarker and drug target discovery. Using high-throughput serum proteomics in the prospective population-based Age, Gene/Environment Susceptibility–Reykjavik Study (AGES) cohort of 5,127 older Icelandic adults (mean age, 76.6 ± 5.6 years), we identified 303 proteins associated with incident LOAD over a median follow-up of 12.8 years. Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status, were implicated in neuronal processes and overlapped with LOAD protein signatures in brain and cerebrospinal fluid. We identified 17 proteins whose associations with LOAD were strongly dependent on APOE- ε 4 carrier status, with mostly consistent associations in cerebrospinal fluid. Remarkably, four of these proteins (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE- ε 4 yet upregulated due to LOAD, a finding replicated in external cohorts and possibly reflecting a response to disease onset. These findings highlight dysregulated pathways at the preclinical stages of LOAD, including those both independent of and dependent on APOE- ε 4 status.

Unbiased proteomics and multivariable regularized regression techniques identify SMOC1, NOG, APCS, and NTN1 in an Alzheimer’s disease brain proteomic signature

CSF proteome profiling across the Alzheimer’s disease spectrum reflects the multifactorial nature of the disease and identifies specific biomarker panels

Plasma proteomic profiles predict future dementia in healthy adults

Alzheimer’s disease (AD) is the most common cause of dementia, accounting for up to 80% of all dementia cases 1 , of which late-onset Alzheimer’s disease (LOAD) is most common 2 . As of 2022, approximately 55 million individuals worldwide had dementia, representing one out of nine people aged 65 years or older 3 . Although promising advances have been made in amyloid-targeting therapeutic options for early-stage LOAD 4 , 5 , they still have limited benefit, and identification of additional risk pathways that can be used for early detection and intervention is highly needed. To meet these demands, a variety of biologically relevant circulating molecules have been broadly associated with LOAD risk. The proteome in particular has the potential to reveal circulating markers of disease-related molecular pathways from different tissues, and studies assessing the circulating proteomic signatures between older adults without dementia and individuals suffering from LOAD have been described 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 . Modest sample sizes, low-throughput proteomics and lack of longitudinal information have, however, been limiting factors in these studies. A recent large-scale longitudinal study identified promising blood-based markers for all-cause incident dementia, although it is unknown how specific the results are to LOAD 17 . Information on the global circulating proteomic profile preceding the onset of LOAD, and how well it reflects AD-related processes in brain and cerebrospinal fluid (CSF), is, thus, scarce.

AD has a considerable genetic component, and both common 18 and rare risk variants have been identified 19 , of which the strongest effects are conferred by variants in the well-known APOE (apolipoprotein E) gene. Approximately 25% of the general population carries the APOE-ε4 variant, whereas it is present in over 50% of AD cases 20 , 21 . The APOE-ε4 allele increases the risk of LOAD by three-fold in heterozygous carriers and by up to 12-fold in homozygous carriers 22 . Although the link between the ε4 allele and LOAD has been extensively researched, light has yet to be shed on the precise mechanism by which the APOE gene affects LOAD onset and/or progression. Importantly, recent large-scale proteogenomic studies have consistently established the APOE locus as a protein-regulatory hotspot, regulating levels of hundreds of proteins in both circulation 23 , 24 , 25 , 26 and CSF 27 , 28 . However, it remains unknown to what extent these proteins relate to LOAD and if they can provide new information on the mechanisms through which APOE-ε4 mediates its risk. Identifying LOAD-associated circulatory proteins and whether their association is APOE-ε4 dependent or independent is crucial for the understanding of AD more generally as well as for gaining insight into potential pathways suitable for targeting in personalized treatment.

The current study tests the hypotheses that specific proteomic signatures in the circulation precede LOAD diagnosis and can reflect dysregulated biological pathways in the brain and CSF. Furthermore, we expect that some of these protein signatures may be affected by the APOE- ε 4 genotype and can, thus, provide molecular readout of pathways directly affected by APOE- ε 4 . To address these hypotheses, we used a high-throughput aptamer-based platform to characterize 4,137 serum proteins in 5,294 participants of the population-based Age, Gene/Environment Susceptibility–Reykjavik Study (AGES) 29 to identify protein signatures of incident LOAD (events occurring during follow-up) and prevalent LOAD, taking an unbiased, longitudinal and cross-sectional approach to the discovery of potential biomarkers for LOAD (Fig. 1 ). Considering the protein-regulatory influence of APOE and how it may impact the way that serum proteins are associated with LOAD, we disentangled the LOAD protein signature into APOE- ε 4 -dependent and APOE- ε 4 -independent components, by identifying proteins whose LOAD association is largely attenuated upon conditioning on APOE- ε 4 carrier status. We compared the serum protein signature of LOAD to those observed in CSF and brain and, finally, used genetic variation as anchors to determine the potential causal direction between serum proteins and disease state.

a , Overview of the AGES cohort and study participants. Prevalent non-AD dementia cases were excluded from the analysis. b , Overview of the aptamers tested and their associations with LOAD. Serum measurements of 4,782 aptamers were tested for associations with prevalent and incident LOAD status, using logistic and Cox proportional hazards regression models, respectively. From the proteins associated with incident LOAD, sets of 140 proteins with an APOE-ε4 -independent association and 17 proteins with an APOE-ε4 -dependent association were defined. The APOE-ε4 -dependent proteins were further expanded to first-degree PPI partners. All sets of proteins were subjected to functional enrichment analysis and bidirectional MR analysis. c , Overview of the replication cohorts used in the study, which include proteins measured in the circulation (ACE) as well as in brain and CSF (Emory). This figure was created with BioRender.

The AGES study cohort

This prospective population-based study was based on 5,127 participants free of dementia at baseline, after the exclusion of 163 individuals with prevalent non-AD dementia and 167 individuals with prevalent LOAD. During a potential follow-up of 12.8 years (median using reverse Kaplan–Meier, 95% confidence interval (CI): 12.6–13.2), 655 individuals were diagnosed with incident LOAD, with the last individual being diagnosed 16 years from baseline. Of those, 115 were diagnosed at the AGES 5-year follow-up study visit, whereas the remaining cases were based on clinical diagnosis of LOAD from linked records ( Methods ). Participants with incident LOAD were older at entry, were more likely to carry an APOE-ε4 allele, had lower body mass index (BMI) and had lower education levels compared to healthy individuals (Supplementary Table 1 ). See Fig. 1 for the study overview.

Serum protein profile of incident LOAD in AGES

To investigate the LOAD-associated circulatory proteomic patterns that occur before disease onset, we used Cox proportional hazards (Cox PH) models and found 320 aptamers (303 proteins) to be significantly (false discovery rate (FDR) < 0.05) associated with incident LOAD diagnosis after adjusting for age and sex (model 1), with hazard ratios (HRs) ranging from 0.78 for TBCA to 1.47 for NTN1 per standard deviation increase of protein levels (Fig. 2a and Supplementary Table 2 ). To account for variability related to APOE- ε 4 carrier status, we adjusted for the genotype in an additional model (model 2; Supplementary Table 2 ), which resulted in 140 significant aptamers (130 unique proteins, HR: 0.79 (CD4)–1.25 (CGA/FSHB), FDR < 0.05) (Fig. 2b ), all of which overlapped with model 1 (Fig. 2c ). When comparing the two models, 43% of the serum proteins remained significant after APOE-ε4 adjustment, indicating that their LOAD association is independent of the APOE-ε4 genotype (Table 1 and Supplementary Table 2 ). Adjusting for additional AD risk factors and estimated glomerular filtration rate (eGFR) ( Methods ) retained 38 significant LOAD-associated aptamers (35 proteins, HR: 0.80 (CD4)–1.26 (SMOC1), FDR < 0.05) (model 3; Supplementary Table 2 ), which may reflect specific processes affecting risk of LOAD that are not captured by currently established risk factors.

a , b , Volcano plots showing the protein association profile for incident LOAD with the HR for incident LOAD from the Cox PH models ( x axis) and −log 10 of Benjamini–Hochberg FDRs ( y axis) across two models: without APOE- ε 4 adjustment (model 1) ( a ) and with APOE- ε 4 adjustment (model 2) ( b ). c , Venn diagram for the overlap between models 1 and 2 for incident LOAD. d , e , Enrichment of top GO terms from GSEA analysis for incident LOAD (model 1) shown as a dot plot stratified by ontology ( d ) and gene-concept network ( e ). f , g , Comparison of effect sizes (HR) from Cox PH models for incident LOAD between the AGES and the ACE ( n = 719) cohorts for all proteins reaching nominal significance ( P < 0.05) in the Cox PH in ACE for model 1 ( f ) and model 2 ( g ). Protein associations with Benjamini–Hochberg FDR < 0.05 are denoted in red. BP, biological process; CC, cellular component; MF, molecular function.

As HR variability can arise with lengthy follow-up time, secondary analyses were implemented with a 10-year follow-up cutoff, which revealed mostly overlapping results (Supplementary Note 1 , Supplementary Tables 3 and 4 and Supplementary Fig. 1 ). We did, however, detect protein associations specific to the shorter follow-up time, which potentially reflect processes that take place closer to the LOAD diagnosis. As there may be further differences in proteomic profiles depending on whether protein sampling occurred before or after LOAD diagnosis, we additionally considered the protein profile of 167 AGES participants with prevalent LOAD at baseline (Supplementary Note 2 , Supplementary Fig. 2a–c and Supplementary Tables 5 – 7 ). Interestingly, many of the proteins associated with increased risk of incident LOAD showed the opposite direction of effect for prevalent LOAD although generally not statistically significant (Supplementary Fig. 2d ). These contrasting results suggest an important temporal element in the LOAD-associated proteome. In total, 346 aptamers (329 unique proteins) were associated with LOAD when all outcomes (incident and prevalent LOAD), follow-up times and models were considered (Supplementary Tables 2 , 3 and 5 ).

To evaluate which biological processes are reflected by the overall incident LOAD-associated protein signature in AGES, we performed a gene set enrichment analysis (GSEA). The strongest enrichment for protein associations in model 1 was observed for Gene Ontology (GO) terms related to axon development and neuron morphogenesis (Fig. 2d,e and Supplementary Table 8 ). The proteins driving the enrichment included neural cell adhesion molecules 1 and 2 (NCAM1 and NCAM2), netrin 1 (NTN1), contactin 1 (CNTN1), neuropilin 1 (NRP1), fibronectin leucine-rich transmembrane protein 2 (FLRT2), matrix metallopeptidase 2 (MMP2) and cell adhesion molecule L1-like (CHL1). GSEA of the protein profiles of model 2, where APOE- ε 4 carrier status was adjusted for, showed similar enrichment results (Supplementary Table 8 ), demonstrating that these terms were mainly driven by the APOE- ε 4 -independent component of the LOAD-associated protein profile (Supplementary Note 3 ). No tissue-elevated gene expression was significantly enriched among the LOAD-associated proteins, except for adipose tissue (Supplementary Table 8 ). Nevertheless, seven (35%) of the top 20 APOE-ε4- independent LOAD-associated proteins had elevated expression in brain or choroid plexus compared to other tissues (Table 1 ).

Proteins with APOE-ε4 -dependent association with incident LOAD

As previously mentioned, 43% of the protein associations with incident LOAD were independent of APOE- ε 4 . Of the remaining 57% that were affected by APOE-ε4 adjustment, we identified 17 proteins whose associations with incident LOAD were particularly strongly affected by APOE- ε 4 carrier status (Table 2 , Fig. 3a , Supplementary Fig. 3 and Supplementary Table 2 ). These proteins, hereafter referred to as APOE-ε4 -dependent proteins, were defined as proteins significantly (FDR < 0.05) associated with incident LOAD in model 1 but whose nominal significance was attenuated ( P > 0.05) or whose direction of effect changed upon APOE- ε 4 adjustment in model 2. These APOE-ε4 -dependent proteins included those with the strongest associations with LOAD before adjusting for the APOE- ε 4 allele (Fig. 2a ). The levels of the APOE protein (targeted by four aptamers) were not significantly associated with incident or prevalent LOAD (FDR > 0.19 for all models, both outcomes). However, lower levels were observed in prevalent LOAD at a nominal significance ( P < 0.05) that was unaffected by adjustment for APOE-ε4 carrier status (Supplementary Table 9 ). Figure 3b shows the intra-correlations among the 17 APOE-ε4 -dependent proteins. All the 17 APOE-ε4 -dependent proteins were strongly regulated by the APOE- ε 4 allele (Fig. 3c , Table 2 , Supplementary Fig. 4 and Supplementary Table 10 ), with the ε 4 allele increasing the levels of five of the proteins and decreasing the levels of the other 12. Accordingly, we observed that increased levels of the five APOE-ε4 upregulated proteins and decreased levels of the 12 APOE-ε4 downregulated proteins were also associated with higher risk of LOAD, yielding an HR above and below 1, respectively (Fig. 3d ). As per definition, most of the APOE-ε4 -dependent proteins lost significance upon APOE-ε4 adjustment, yet, interestingly, the direction of effect inverted for five proteins after APOE-ε4 adjustment (ARL2, IRF6, NEFL, S100A13 and TBCA) (Fig. 3e ). A previous study using the Simoa assay (Quanterix) reported increased NEFL levels in APOE-ε4 compared to APOE-ε3 carriers 30 , whereas we observed the opposite. We, thus, compared NEFL measurements from SOMAscan and the Simoa assay in a subset of AGES and observed differences in the associations with both APOE-ε4 and LOAD, indicating that they potentially measure different NEFL species 31 (Supplementary Note 4 and Supplementary Fig. 5 ).

a , Spaghetti plot showing the statistical significance as Benjamini–Hochberg FDR of protein associations with incident LOAD across the three Cox PH models, highlighting a set of 17 unique proteins (green) whose association with incident LOAD is attenuated upon APOE- ε 4 adjustment. The horizontal lines indicate Benjamini–Hochberg FDR < 0.05 (dashed) and P < 0.05 (dot-dashed). The total number of significantly associated proteins (FDR < 0.05) for each model is shown above. b , Pairwise Pearson’s correlation among the 17 APOE-ε4 -dependent proteins. c , Forest plot showing the effect (beta coefficient) of the APOE genotype on the 17 APOE-ε4 -dependent proteins in AGES. The beta coefficients indicate the change in protein levels per ε4 allele count and are shown with 95% CIs. d , e , Forest plots showing the HR for incident LOAD per standard deviation increase in level for each of the 17 APOE-ε4 -dependent proteins in AGES without APOE- ε 4 adjustment (model 1) ( d ) and with APOE- ε 4 adjustment (model 2) ( e ). The LOAD HRs are shown with 95% CIs. Proteins that change direction of effect between the two models are highlighted in red. f – h , Replication analyses for c – e were performed in the ACE cohort ( n = 719) in the same manner as in the AGES cohort. FAM159B (in gray) was not measured in the ACE SOMAscan assay.

The HR conferred by APOE-ε4 for incident LOAD in the AGES cohort was 2.1 (Cox PH P = 1.23 × 10 −27 ) per copy of the ε4 allele. To evaluate if any of the 17 APOE-ε4 -dependent proteins might mediate the effect of APOE - ε4 on incident LOAD, we performed a regression-based mediation analysis. The overall proportion of the effect mediated was non-significant (estimate = −0.05, P = 1; Supplementary Fig. 6a ), thus suggesting that these proteins do not mediate the LOAD risk conferred by APOE-ε4 . However, although not direct mediators, the 17 proteins could be blood-based readouts of a true mediator within tissue-specific pathological processes occurring before LOAD diagnosis. We additionally considered the change in HR for APOE-ε4 on risk of incident LOAD when adjusting for individual LOAD-associated proteins and found that adjustment for most proteins resulted in a minor effect decrease (Supplementary Fig. 6b ). Intriguingly, however, the adjustment for four APOE-ε4 -dependent proteins (NEFL, ARL2, TBCA and S100A13) caused an increase of approximately 10% in APOE-ε4 effect size (Supplementary Fig. 6b,c ). Thus, the effect of APOE-ε4 on LOAD is partly masked by secondary opposing associations between these proteins and LOAD, which are further explored below. Although the 17 APOE-ε4 -dependent proteins were not significantly enriched for tissue-elevated gene expression (Supplementary Table 8 ), we observed that four (LRRN1, FAM159B, NEFL and HBQ1) had elevated gene expression in brain compared to other tissues, and one (TMCC3) clustered with oligodendrocyte-related genes (Table 2 ). Of the remaining APOE-ε4 -dependent proteins, eight were ubiquitously expressed, including in brain tissue, and four were elevated in other tissues. We did not detect any significantly enriched molecular signatures or GO terms for the 17 APOE-ε4 -dependent proteins (Supplementary Table 8 ). However, a network analysis of measured and inferred physical protein–protein interactions (PPIs) 32 revealed that the APOE-ε4 -dependent proteins interact directly with proteins involved in microtubule and centromeric functions, neuronal response and development, neuroinflammation and AD (Extended Data Fig. 1 , Supplementary Tables 11 – 13 and Supplementary Note 5 ).

Given the well-established relationship between APOE and cholesterol 33 , we explored the potential effect of serum lipid levels on the association between LOAD and the 17 APOE-ε4 -dependent proteins (Supplementary Table 14 , Supplementary Figs. 7 and 8 and Supplementary Note 6 ). Our findings suggest that, although many of the APOE-ε4 -dependent proteins are associated with cholesterol levels, it is not the driver of their link to LOAD.

Finally, given the observed APOE-ε4 -dependent and APOE-ε4 -independent proteomic associations with LOAD in the full cohort, we additionally investigated if any proteins were differentially associated with LOAD within APOE-ε4 carriers versus non-carriers by stratification via an interaction analysis. We found differential associations between the strata for several proteins, potentially suggesting that different pathways vary in their contribution to the development of LOAD depending on APOE-ε4 carrier status (Supplementary Note 7 and Supplementary Table 15 ).

External validation of protein associations with LOAD

We evaluated the protein associations with incident LOAD from our APOE-ε4 -dependent/independent analyses in an external cohort, the Alzheimer Center Barcelona (ACE) ( n = 1,341), with SOMAscan platform (v4.1-7K) measurements from plasma of individuals who were referred to the center. The longitudinal component of ACE consists of individuals who had been diagnosed with mild cognitive impairment (MCI) at the center and had been followed up. A total of 719 participants had follow-up information and 266 converted to LOAD over a median follow-up of 3.14 years (reverse Kaplan–Meier, 95% CI: 3.04–3.28) (Supplementary Table 16 ). Despite the fundamentally different cohorts, with AGES being population based and using the V3-5K SOMAscan platform and ACE based on individuals with established symptoms and the v4.1-7K SOMAscan platform, we replicated 36 protein associations with LOAD at nominal significance ( P < 0.05) in the smaller ACE cohort (Table 3 , Supplementary Table 10 and Fig. 2f,g ). Of those, 30 proteins were nominally significant in model 1, with 97% being directionally consistent with the observations in AGES (Fig. 2f ). In model 2, 21 proteins were nominally significant, 86% of which were directionally consistent (Fig. 2g ). After multiple testing correction, seven proteins remained statistically significant (FDR < 0.05), all of which were directionally consistent (Table 3 , Supplementary Table 10 and Fig. 2f,g ). Six were statistically significant (FDR < 0.05) in model 1 (NEFL, LRRN1, TBCA, CTF1, C1orf56 and TIMP4) and one in model 2 (S100A13) (Supplementary Table 10 ). Of all 332 tested aptamers, 213 (64%) were directionally consistent regardless of significance in model 1 (two-sided exact binomial test P = 2.0 × 10 −5 ), and 202 (61%) were directionally consistent in model 2 (two-sided exact binomial test P = 0.002), demonstrating an enrichment for consistency in direction of effect. The protein associations replicated in the ACE cohort are of particular interest as they represent potentially clinically relevant candidates for LOAD that are consistent in two different contexts: in both a general population and a clinically derived symptomatic sample set. However, our results suggest that many of the proteins that associate with long-term LOAD risk are not strongly associated with the conversion from MCI to AD, which is further into the AD trajectory and may also explain the limited overlap between the proteins associated with prevalent and incident LOAD in AGES.

Validation of reversed association conditional on APOE-ε4

Specifically considering the APOE-ε4 -dependent proteins, the association between the APOE- ε 4 allele and the proteins was replicated for 13 of 17 proteins in the ACE cohort (Fig. 3f and Supplementary Fig. 4b ). Furthermore, the change in direction of effect for incident LOAD upon APOE- ε 4 adjustment was replicated in the ACE cohort for four of five proteins (ARL2, NEFL, S100A13 and TBCA) (Fig. 3g,h and Supplementary Table 10 ), with even larger effects observed in the ACE cohort compared to AGES in the APOE- ε 4 adjusted model and three proteins (ARL2, S100A13 and TBCA) becoming statistically significant ( P < 0.05). Thus, the attenuation of the primary LOAD associations for these proteins upon APOE- ε 4 adjustment meet the criteria of APOE- ε 4 dependence ( Methods ). No significant interaction between these proteins and APOE- ε 4 carrier status on AD risk was observed in either the AGES or ACE cohorts. Taken together, our results show that these proteins are strongly downregulated by APOE- ε 4 and, consequently, show an inverse relationship with incident LOAD; but when adjusting for the APOE-ε4 allele, their association with LOAD is still significant but reversed, suggesting a secondary non- APOE-ε4- mediated process affecting these same proteins in relation to LOAD in the opposite direction that is more strongly observed in a cohort of individuals with MCI than in the population-based AGES cohort.

Potential causal associations between proteins and LOAD

The proteins associated with LOAD could include proteins causally related to the disease or proteins whose serum level changes reflect a response to prodromal or genetic liability to LOAD. To test this hypothesis, we performed a bidirectional two-sample Mendelian randomization (MR) analysis, including the targets of all 346 aptamers associated with LOAD in our study. Genetic variant associations for serum protein levels were obtained from a catalog of cis -protein quantitative trait loci (pQTLs) from AGES 23 , whereas variant associations with LOAD were extracted from a recent GWAS of 39,106 clinically diagnosed LOAD cases, 46,828 proxy-LOAD and dementia cases and 401,577 controls of European ancestry 18 . In total, 117 (34%) of the LOAD-associated serum aptamers had cis -pQTLs that were suitable as genetic instruments and were included in the protein-LOAD MR analysis (Supplementary Table 17 ).

In the forward MR analysis, two proteins—integrin binding sialoprotein (IBSP) and amyloid precursor protein (APP)—had support for causality (Supplementary Table 18 ). IBSP had a risk-increasing effect for LOAD in both the causal analysis (odds ratio (OR) = 1.26, FDR = 0.03) and observational analysis (incident LOAD full follow-up, HR = 1.13, FDR = 0.04). APP had a protective effect for LOAD in both the causal analysis (OR = 0.76, FDR = 0.03) and the observational analysis (incident LOAD full follow-up, HR = 0.88, FDR = 0.047). Notably, although not statistically significant, we observed suggestive support for a protective effect of genetically determined serum levels of acetylcholinesterase (ACHE; OR = 0.92, P = 0.061), a target of clinically used therapeutic agent for dementia 34 (Supplementary Table 18 and Supplementary Fig. 9 ). In a forward MR analysis of the APOE - ε4 -dependent protein interaction partners, two proteins, APP and MAPK3, had support for causality (Supplementary Table 13 and Supplementary Note 5 ).

As most of the observational protein associations in the current study were detected for incident LOAD and, thus, reflect changes that take place before the onset of clinically diagnosed disease, it is unlikely that their levels and effects are direct downstream consequences of the disease after it reaches a clinical stage. However, they may reflect a response to a prodromal stage of the disease. We, therefore, performed a reverse MR to test if the observed changes in serum protein levels are likely to occur downstream of the genetic liability to LOAD, which may capture processes both at the prodromal and clinical stage. The APOE locus is likely to have a dominant pleiotropic effect in the reverse MR analysis (Supplementary Table 19 , Supplementary Fig. 10 and Supplementary Note 8 ), as it has a disproportionately strong effect on LOAD risk compared to all other common genetic variants while also being a well-established pQTL trans -hotspot, affecting circulating levels of up to hundreds of proteins 23 , 24 , 25 , 26 . We, therefore, performed the primary reverse MR analysis using only LOAD-associated genetic variants outside of the APOE locus as instruments. We found two proteins (S100A13 and ARL2) that were significantly (FDR < 0.05) increased by LOAD or its genetic liability (Supplementary Table 19 and Supplementary Figs. 10 and 11 ). Interestingly, both were among the 17 previously identified APOE - ε4 -dependent LOAD proteins, together with two additional proteins that were nominally significant in the reverse MR (TBCA, P = 4.4 × 10 −4 , FDR = 0.051 and IRF6, P = 7.9 × 10 −4 , FDR = 0.055). Thus, intriguingly, these findings suggest that these four proteins are upregulated by LOAD, in contrast to the observed APOE-ε4 downregulation of the same proteins (Fig. 4 ). This supports our findings of competing biological effects described above (Fig. 3e and Supplementary Fig. 6 ), and, collectively, our results indicate that simultaneous opposing effects of APOE-ε4 on the one hand and LOAD on the other result in differential regulation of these proteins in serum (Fig. 4b ).

a , Comparison of HRs for incident LOAD with and without APOE- ε 4 adjustment in the observational analysis (Cox PH) ( n = 5,127), the effects of APOE- ε 4 on protein levels in AGES ( n = 5,332) and reverse MR ORs (excluding the APOE locus) shown for the four APOE-ε4 -dependent proteins that change direction of effect in both observational and causal analyses when APOE is accounted for. All effects are shown with 95% CIs. b , c , Visual summaries of the observed data. b , Mediation diagrams showing three possible hypotheses that could explain the relationship among APOE-ε4 , LOAD and the four proteins shown in a . Our analyses do not support the hypothesis that LOAD mediates the effect of APOE- ε 4 on proteins (hypothesis 1) or the other way around (hypothesis 2). However, our results from both the observational and causal analyses support the hypothesis that two mechanisms are at play that affect the same proteins in the opposite direction (hypothesis 3). c , The APOE- ε 4 genotype leads to increased risk of LOAD by its effects in brain tissue. The same genotype results in a downregulation of serum levels of four proteins that are consequently themselves negatively associated with incident LOAD. Additionally, other non- APOE LOAD risk variants lead to upregulation of the same proteins in the reverse MR analysis, possibly reflecting a response to LOAD or its genetic liability. This figure was created with BioRender.

We performed a replication analysis of the effect of APOE- ε 4 on protein levels and the reverse MR results for these four proteins using published protein GWAS summary statistics from two recent studies 24 , 35 . In the external datasets, the downregulation of all four proteins by APOE- ε 4 (as determined by the rs429358 C allele) was replicated (Supplementary Fig. 12 ). In the reverse MR analysis (excluding the APOE locus), the upregulation of protein levels by LOAD liability observed in AGES was also detected for two proteins (S100A13 and TBCA) in both validation cohorts, reaching significance ( P < 0.05) in the study by Ferkingstad et al. 35 (Supplementary Fig. 12 and Supplementary Table 20 ). Although the two proteins changed direction in a similar manner as in AGES, the effect size was considerably smaller in the validation cohorts. Notably, however, individuals in these two cohorts are much younger than those in AGES, with mean ages of 55 years and 48 years for the Ferkingstad et al. 35 and Sun et al. 24 studies, respectively, compared to 76 years in AGES. Therefore, we conducted an age-stratified reverse MR analysis in AGES that showed a strong age-dependent effect, with a much larger effect of LOAD genetic liability on protein levels in individuals over 80 years of age compared to those younger than 80 years (Supplementary Fig. 12 ). The effect size in AGES individuals younger than 80 years was in line with the effect observed in the validation cohorts. Thus, if the upregulation of these proteins reflects a response to prodromal or preclinical LOAD, an older cohort may be needed to detect an association of the same degree as we found in AGES. However, the observed support in the validation cohorts for the discordant effects of APOE versus non- APOE LOAD-associated genetic variants on the same serum proteins strongly implicates these proteins as directly relevant to LOAD, potentially as readouts of biological processes that are both disrupted by APOE-ε4 and modulated in the opposite manner as a response to genetic predisposition to LOAD or the disease onset in general.

Together, these results indicate that LOAD or its general genetic liability causally affects the levels of some APOE-ε4 -dependent proteins, but this effect is simultaneously masked by the strong effects of the APOE locus in the other direction (Fig. 4a ). These outcomes strengthen the results described above, showing that the levels of these four proteins are strongly downregulated in APOE- ε 4 carriers, and lower levels of these proteins are, therefore, associated with increased risk of LOAD in an APOE-ε4 -dependent manner (Fig. 4b ). Simultaneously, the reverse MR analysis shows that the collective effect of the other non- APOE LOAD risk variants is to upregulate the serum levels of these same proteins, possibly reflecting a response mechanism to LOAD pathogenesis (Fig. 4c ). Again, this is in line with the observational analysis, where all four proteins changed direction of effect when adjusting for APOE-ε4 (Figs. 3d,e,g,h and 4a ).

Overlap with the AD brain and CSF proteome

To evaluate to what extent our LOAD-associated serum proteins reflect the proteomic profile of AD in relevant tissues, we queried data from recent proteomic studies of AD in CSF 36 and brain 37 , which also describe tissue-specific co-regulatory modules. We observed that, of our LOAD-associated serum proteins, 51 were also associated with AD in brain as measured by mass spectrometry (MS), with 32 (63%) being directionally consistent (Fig. 5a,b and Supplementary Tables 21 and 22 ). Higher directional consistency was observed within the APOE-ε4 -independent protein group, or 15 (71%) of 21 proteins associated with AD in brain tissue. Additionally, 60 proteins were directly associated with AD in CSF as measured with SOMAscan (7K) (Fig. 5a ), with 46 (77%) being directionally consistent (Fig. 5b ). The proportion of directionally consistent associations between serum and CSF was higher in both the APOE-ε4 -independent and APOE-ε4 -dependent protein groups, or 88% (22 of 25 and seven of eight for APOE-ε4 -independent and APOE-ε4 -dependent proteins, respectively) (Fig. 5b and Supplementary Table 21 ). However, directional inconsistency between plasma and CSF AD proteomic profiles was reported previously in a similar comparison 38 . Fourteen proteins overlapped among all three tissues in the context of AD (Fig. 5a and Supplementary Table 21 ). Many of these proteins have established links or are highly relevant to LOAD, such as spondin 1 (SPON1), involved in the processing of APP 39 ; secreted modular calcium-binding protein 1 (SMOC1), previously proposed as a biomarker of LOAD in postmortem brains and CSF 40 ; NTN1, an interactor of APP and regulator of amyloid beta (Aβ) production 41 ; NEFL, previously proposed as a plasma biomarker for LOAD and axon injury 42 , 43 ; and Von Willebrand factor (VWF), known for its role in blood clotting and associations with LOAD 44 (Supplementary Table 21 ). Notably, some of the APOE-ε4 -dependent proteins were associated with AD across all three tissues, such as TBCA and TP53I11.

a , Venn diagram showing the overlap of AD-associated proteins in serum, brain and CSF. b , Comparison of the effect sizes for AD-associated proteins that overlap between serum and brain (top) and serum and CSF (bottom). The proteins are stratified based on the APOE-ε4 dependence in AGES for incident LOAD. The effect size in AGES is shown for incident LOAD model 1 (Cox PH), except for proteins that were uniquely identified using the shorter 10-year follow-up (Cox PH) or prevalent LOAD (logistic regression), in which case the respective effect size from the significant association is shown. c – e , Heatmap showing the enrichment (two-sided Fisher’s test) of AD-associated proteins by tissue type ( x axis) in the AGES serum protein modules ( c ), Emory CSF protein modules ( d ) and Emory brain protein modules ( e ) ( y axis). Modules that are enriched for AD associations in more than one tissue are highlighted with red squares.

We previously described the co-regulatory structure of the serum proteome, which can broadly be defined as 27 modules of correlated proteins 25 (Supplementary Table 23 ). In the current study, we found that, among the 346 aptamers (329 proteins) associated with LOAD (prevalent or incident, any model), five serum protein modules (M27, M3, M11, M2 and M24) were overrepresented (Fig. 5c and Supplementary Table 24 ). In particular, the 140 APOE-ε4- independent proteins were specifically overrepresented in module M27, enriched for proteins involved in neuron development and the extracellular matrix (ECM), and in module M3, associated with growth factor signaling pathways (Supplementary Table 24 ). By contrast, the 17 APOE-ε4- dependent proteins were specifically enriched in protein module M11 (Supplementary Table 24 ), which is strongly enriched for lipoprotein-related pathways and is under strong genetic control of the APOE locus 25 . Serum modules M27, M24 and M11 were all enriched for AD associations in CSF (Fig. 5c ). We next sought to understand to what extent our LOAD-associated proteins identified in serum might reflect AD protein signatures in CSF and brain tissue. Among the LOAD-associated proteins measured in serum, we found the APOE-ε4 -dependent and APOE-ε4 -independent proteins to be enriched in different CSF modules, most of which were also linked to AD (Fig. 5d and Supplementary Table 24 ). In brain tissue, the serum APOE-ε4- independent LOAD proteins were particularly enriched in brain module M42 (Matrisome), which is enriched for ECM proteins 37 (Fig. 5e and Supplementary Table 24 ). Strikingly, M42 was strongly enriched for the AD proteomic profiles of all three tissues (Fig. 5e and Supplementary Table 24 ). Interestingly, members of this module (SMOC1, SPON1, NTN1, GPNMB and APP), with some of the strongest association with AD in brain (Fig. 5b and Supplementary Table 24 ), overlapped with some of the strongest associations in serum to incident LOAD in our study (Fig. 2a,b and Supplementary Table 2 ).

This module has furthermore been demonstrated to be correlated with Aβ deposition in the brain, and some of its protein constituents (for example, MDK, NTN1 and SMOC1) have been shown to co-localize with and bind to Aβ 37 . Additionally, the APOE locus regulates M42 levels in the brain (mod-QTL), and, although the APOE protein is a member of module M42, this regulation was found to not be solely driven through the levels of the APOE protein itself 37 . Our results simultaneously show that other members of the module, such as SPON1 and SMOC1, exhibit an APOE-ε4 -independent association to incident LOAD in serum. Interestingly, these same two proteins are increased in CSF 30 years before symptom onset in autosomal dominant early-onset AD 45 . In summary, we demonstrate significant overlaps in LOAD-associated protein expression across blood, CSF and brain on both an individual protein level and on a protein module level.

We describe a comprehensive mapping of the serum protein profile of LOAD that provides insight into processes that are independent of or dependent on the genetic control of APOE - ε 4 (Supplementary Fig. 13 ). We identified 329 proteins in total that differed in the incident or prevalent LOAD cases compared to non-LOAD participants in a population-based cohort with long-term follow-up. Among these, we identified a grouping of proteins based on their primary LOAD association being statistically independent of (140 proteins), or dependent on (17 proteins) APOE - ε 4 carrier status. Many of the APOE-ε4 -independent proteins are implicated in neuronal pathways and are shared with the LOAD-associated CSF and brain proteome. The 17 APOE-ε4 -dependent proteins overlap with AD-associated protein modules in CSF and interact directly with protein partners involved in LOAD, including APP. Another key finding is that, among these 17 proteins, four proteins (ARL2, S100A13, TBCA and IRF6) change LOAD-associated direction of effect both observationally and genetically when taking APOE- ε 4 carrier status into account. Notably, we replicated this directional change both observationally for three proteins (ARL2, S100A13 and TBCA) and genetically for two proteins (S100A13 and TBCA) in external cohorts. Collectively, our results suggest that, although their primary association with LOAD reflects the risk conferred by APOE - ε 4 , there exists a secondary causal effect of LOAD itself on the protein levels in the reverse direction as supported by the MR analysis, possibly reflecting a response to the disease onset.

Previous studies identifying proteins associated with LOAD were limited to cross-sectional cohorts or were based on all-cause dementia 6 , 17 , 46 , 47 . Here, we extend those findings by distinguishing LOAD cases from other types of dementia based on a clinical diagnosis criterion in a prospective cohort study to identify LOAD-specific serum protein signatures preceding clinical onset. A recent study of UK Biobank participants using the Olink platform identified several proteins associated with incident dementia, including AD 48 . Their top AD-associated proteins differed from those prioritized in the current study; thus, future work is required to determine how proteomic platform and cohort differences, such as age, influence protein associations with LOAD, both of which we found to directly affect the results in our extended analyses of NEFL (Supplementary Note 4 ). Furthermore, our comparative approach of statistical models with and without APOE- ε 4 adjustment provides a compartmentalized view of the LOAD serum protein profile and demonstrates how protein effects can differ depending on genetic confounders, which are imperative to take into consideration. We found that the proteins associated with incident LOAD in our study, in particular those independently of APOE- ε 4 , such as GPNMB, NTN1, SMOC1 and SPON1, overlap with the proteomic profile of LOAD in CSF 38 and brain 37 ; are enriched for neuronal pathways; and have been functionally implicated with LOAD (Table 1 ), which may reflect an altered abundance of neuronal proteins in the circulation during the prodromal stage of LOAD. These overlaps that we found across independent cohorts and different proteomics technologies suggest that the serum levels of some proteins have a direct link to the biological systems involved in LOAD pathogenesis and may even provide a peripheral readout of neurodegenerative processes before clinical diagnosis of LOAD. In particular, the proteins that show directionally consistent effect sizes suggest exceptional AD-specific robustness as the measurements vary by tissue, methodology and populations.

We identified 17 proteins with a particularly strong APOE-ε4 -dependent association with incident LOAD, of which eight were also associated with prevalent AD in CSF. The association between APOE- ε 4 and circulating levels of these proteins was reported by our group 23 , 25 , 26 and others 49 , but their direct association with incident LOAD has, to our knowledge, not been previously described. Interestingly, we previously observed multiple independent genetic signals in the APOE–APOC1–APOC1P1 region affecting these same proteins to a varying degree, some of which co-localize with GWAS signals for LOAD 23 , which necessitate further investigation for better understanding of the complex regulatory effects in this genetic region that converge on the same set of proteins. The proteins with an APOE-ε4 -dependent association with LOAD may point directly to the processes through which APOE- ε 4 mediates its risk and provide a readout of the pathogenic process in the circulation for the approximately 50% of patients with LOAD worldwide carrying the variant 20 , 21 . Although our data do not provide information on the tissue origin of the APOE-ε4 -dependent proteins, some exhibit brain-elevated gene expression 50 or have been associated with LOAD at the transcriptomic or protein level in brain tissue or CSF (Table 2 ). At the genetic level, a lookup in the GWAS catalog 50 shows that an intron variant in the IRF6 gene has a suggestive GWAS association with LOAD via APOE-ε4 carrier status interaction 51 . In addition, variants in the TMCC3 gene have been linked to LOAD 52 , educational attainment 53 and caudate volume change rate 54 , and variants in the TBCA gene have been suggestively associated with reaction time 55 and PHF-tau levels 56 . Collectively, the gene expression patterns for these proteins in the brain, interactions with proteins involved in neuronal processes and suggestive associations between genetic markers in or near these genes and brain-related outcomes suggest that these APOE-ε4 -dependent proteins may reflect brain-specific processes affected by APOE- ε 4 carrier status that affect the risk of developing LOAD. Notably, the association patterns for ARL2, S100A13 and TBCA suggest the presence of a pathway that is downregulated by APOE-ε4 already in midlife, given the consistent effect of APOE-ε4 on the same proteins in younger cohorts, but upregulated at the onset of LOAD, as supported by the larger observed effects in the APOE- ε 4 adjusted analysis in the ACE cohort of individuals who are closer to diagnosis on the AD trajectory than those in AGES. Additional studies are required to expand on these interpretations and dissect the complex mechanisms at playages to determine if the modulation of the process represented by these proteins has therapeutic potential.

Conflicting results have been observed for the relationship between serum or plasma levels of the APOE protein and LOAD 57 . Although serum levels of the APOE protein, as measured by the SOMAscan platform, were not strongly associated with LOAD in AGES, our results support a relationship between lower APOE levels and prevalent LOAD. We furthermore observed conflicting results in the association between APOE- ε4 and NEFL compared to a previous study 30 . Our results comparing different methods for measuring NEFL in AGES (Supplementary Note 4 ) highlight the importance of considering proteomic platforms and their potential differences in protein species detection, as noted by Budelier et al. 31 and others 58 .

Two proteins, IBSP and APP, were identified to potentially have a causal role in LOAD. IBSP was previously associated with plasma Aβ and incident dementia 59 , and APP is the precursor protein for Aβ 60 . Based on the MR analysis for the third of LOAD-associated proteins that could be tested, most do not appear to be causal in and of themselves, but their association with incident LOAD may still reflect changes that occur years before the onset of LOAD that could be of interest to target before irreversible damage accumulates.

A major strength of our study is the high-quality data from a prospective longitudinal population-based cohort study with detailed follow-up, broad coverage of circulating proteins and a comprehensive comparison to the AD proteome in CSF and brain. The limitations of our study include that our results are based on a Northern European cohort and cannot necessarily be transferred directly to other populations or ethnicities. Additionally, although we partly replicated our overall findings in an external cohort, a greater replication proportion could be anticipated in a more comparable cohort as discussed above. The ACE cohort consists of clinically referred individuals with MCI and proteomic measurements performed on a different version of the SOMAscan platform (version 4.1 versus version 3 in AGES). Additionally, different normalization procedures were applied by SomaLogic for the two SOMAscan versions, which may have an effect on the LOAD associations 47 . Regardless of these differences, we did replicate most of the APOE-ε4 -dependent LOAD associations, including the APOE-ε4 -dependent change in effect for ARL2, S100A13 and TBCA. We could not test all LOAD-associated proteins for causality, including most of the APOE-ε4 -dependent proteins, due to lack of significant cis -pQTLs for two-thirds of the proteins; thus, we cannot exclude the possibility that some could be causal but missed by our analysis. Finally, although a clinical LOAD diagnosis criterion was used for classifying cases, it is possible that some individuals were misclassified, and some of our findings may, thus, reflect processes related to dementia in general. As a result, it is critical to validate these findings in individuals with established Aβ and tau deposits as well as in experimental settings.

The proteins highlighted in this study and the mechanisms they point to may be used as a source of biomarkers or therapeutic targets that can be modulated for the prevention or treatment of LOAD. This large prospective cohort study, using both a longitudinal and a cross-sectional design, represents a unified and comprehensive reference analysis with which past and future serum protein biomarkers and drug targets can be considered, compared and evaluated.

AGES study population

Participants aged 66–96 years were from the AGES cohort. AGES is a single-center prospective population-based study of deeply phenotyped individuals ( n = 5,764; mean age, 76.6 ± 5.6 years; 58% women) and survivors of the 40-year-long prospective Reykjavik study, an epidemiologic study aimed to understand aging in the context of gene/environment interaction by focusing on four biologic systems: vascular, neurocognitive (including sensory), musculoskeletal and body composition/metabolism 29 . The AGES study was approved by the Nation Bioethics Committee in Iceland (approval number VSN-00-063), by the National Institute on Aging Intramural Institutional Review Board and by the Data Protection Authority in Iceland. All participants provided informed consent for their participation in the study and did not receive compensation.

Of the AGES participants, 3,411 attended a 5-year follow-up visit, and all participants were followed up for incident dementia through medical and nursing home reports (Resident Assessment Instrument (RAI)) and death certificates. The follow-up time was up to 16.9 years, with the last individual being diagnosed 16 years from baseline. LOAD diagnosis at AGES baseline and follow-up visits was carried out using a three-step procedure as previously described 29 . In brief, cognitive assessment was carried out on all participants. Neuropsychological testing was performed on individuals with suspected dementia. Individuals remaining suspect for dementia underwent further neurologic and proxy examinations in the second diagnosis step. Third, a panel comprising a neurologist, a geriatrician, a neuroradiologist and a neuropsychologist assessed the positive-scoring participants according to international guidelines and gave a dementia diagnosis. Diagnoses for all-cause dementia and LOAD from nursing home reports were based on intake examinations upon entry or standardized procedures carried out in all Icelandic nursing homes 61 . Diagnosis of LOAD was established according to National Institute of Neurological and Communicative Diseases and Stroke–Alzheimerʼs Disease and Related Disorders Association (NINCDS-ADRDA) criteria or according to International Classification of Diseases, 10th revision (ICD-10) code F00 criteria. The participants diagnosed at baseline were defined as prevalent LOAD cases, whereas individuals diagnosed with LOAD during the follow-up period (either at the AGESII follow-up visit or through linked records) were defined as incident LOAD cases. All prevalent non-AD dementia cases ( n = 163) were excluded from analyses.

Age, sex, education and lifestyle variables were assessed using questionnaires at baseline. Education was categorized as primary, secondary, college or university degree. Smoking was characterized as current, former or never smoker. APOE genotyping was assessed using microplate array diagonal gel electrophoresis (MADGE) 62 . BMI and hypertension were assessed at baseline. BMI was calculated as weight (kg) divided by height squared (m 2 ), and hypertension was defined as antihypertensive treatment or blood pressure (BP) > 140/90 mmHg. Type 2 diabetes was defined from self-reported diabetes, diabetes medication use or fasting plasma glucose ≥7 mmol L −1 . Serum creatinine was measured using a Roche Hitachi 912 instrument, and eGFR was derived with the four-variable MDRD study equation 63 .

Proteomic measurements

The proteomic measurements in AGES were described in detail elsewhere 26 , 64 and were available for 5,457 participants. In brief, a custom version of the SOMAscan platform (Novartis V3-5K) was applied based on SOMAmer protein profiling technology 65 , 66 including 4,782 aptamers that bind to 4,137 human proteins. Serum was prepared using a standardized protocol 67 from blood samples collected after an overnight fast by the same personnel who were specifically trained in protocols for sample collection and handling. Special care was taken to minimize the time between blood draw and sample centrifugation. Bench time was minimized at all times, and samples were stored in 0.5-ml aliquots at −80 °C under constant surveillance. Serum samples that had not been previously thawed were used for the protein measurements. All samples were randomized and run as a single set at SomaLogic, Inc., blinded to any phenotypic outcomes. Hybridization controls were used to adjust for systematic variability in detection, and calibrator samples of three dilution sets (40%, 1% and 0.005%) were included so that the degree of fluorescence was a quantitative reflection of protein concentration. All aptamers that passed quality control had median intra-assay and inter-assay coefficient of variation (CV) < 5%. Finally, intra-plate median signal normalization was applied to individual samples by SomaLogic instead of normalization to an external reference of healthy individuals, as is done for later versions of the SOMAscan platform ( https://somalogic.com/wp-content/uploads/2022/07/SL00000048_Rev-3_2022-01_-Data-Standardization-and-File-Specification-Technical-Note-v2.pdf ).

Of the 37 APOE-ε4 -independent and APOE-ε4 -dependent proteins highlighted in Tables 1 and 2 , respectively, orthogonal MS verified the specificity of eight aptamers (seven proteins) in previous studies 25 . Twelve additional aptamers were profiled (CD4 (3143_3_1), BRD4 (10043_31_3), SPON1 (5496_49_3), SMOC1 (13118_5_3), LRRN1 (11293_14_3), S100A13 (7223_60_3), CTF1 (13732_79_3), ARL2 (12587_65_3), C1orf56 (5744_12_3), MSN (5009_11_1), IRF6 (9999_1_3) and NEFL (10082_251_3)), and two additional aptamers (C1orf56 (5744_12_3) and MSN (5009_11_1)) were confirmed (Table 2 ) with SOMAmer pulldown mass spectrometry (SP-MS) using patient serum samples (>65 years) purchased from BioIVT. The new confirmations’ methodology is consistent with previous publications 25 , but the instrumentation was updated. Data-dependent analysis was performed on an Orbitrap Eclipse operated in positive ionization mode, with electrospray voltage of 1,500 V and ion transfer tube temperature of 275 °C applied. Full MS scans with quadrupole isolation were acquired in the Orbitrap mass analyzer using a scan range of 375–1,500 m / z , standard AGC target and automatic maximum injection time. Data-dependent scans were acquired in the Orbitrap with a 0.7- m / z quadrupole isolation window, 50,000 resolution, 50% normalized AGC target, 200-ms maximum injection time and 38% HCD collision energy over a 2-s cycle time. Dynamic exclusion of 45 s relative to ±10 p.p.m. reference mass tolerance was applied. The peptides were eluted with Aurora Ultimate 25 cm × 75 µm ID, 1.7 µm C18 nano columns over a 90-min gradient on the Vanquish Neo UHPLC system (Thermo Fisher Scientific). Raw data files were processed in Proteome Discoverer version 2.5 with SequestHT database search using a canonical human FASTA database (20,528 sequences, updated 8 April 2022).

The proteomic measurements for NEFL in a subset of AGES using the Simoa assay from Quanterix were described elsewhere 68 .

ACE Alzheimer Center Barcelona was founded in 1995 and has collected and analyzed roughly 18,000 genetic samples, diagnosed over 8,000 patients and participated in nearly 150 clinical trials to date. For more details, visit https://www.fundacioace.com/en . The syndromic diagnosis of all individuals of the ACE cohort was established by a multidisciplinary group of neurologists, neuropsychologists and social workers. Healthy controls (HCs), including individuals with a diagnosis of subjective cognitive decline (SCD), were assigned a Clinical Dementia Rating (CDR) of 0, and individuals with MCI were assigned a CDR of 0.5. For MCI diagnoses, the classification of López et al. and Petersen’s criteria were used 69 , 70 , 71 , 72 . The 2011 National Institute on Aging and Alzheimer’s Association (NIA-AA) guidelines were used for AD diagnosis 73 . All ACE clinical protocols were previously published 74 , 75 , 76 . All ACE cohort participants provided written informed consent for their participation in the study and did not receive compensation 74 . Paired plasma and CSF samples 77 , following consensus recommendations, were stored at −80 °C. A subset of the ACE cohort was analyzed with the SOMAscan 7K proteomic platform 78 ( n = 1,370) (SomaLogic, Inc.). The proteomic data underwent standard quality control procedures at SomaLogic and were median normalized to reference using the adaptive normalization by maximum likelihood (ANML) method ( https://somalogic.com/wp-content/uploads/2022/07/SL00000048_Rev-3_2022-01_-Data-Standardization-and-File-Specification-Technical-Note-v2.pdf ). Additionally, APOE genotyping was assessed using TaqMan genotyping assays for rs429358 and rs7412 single-nucleotide polymorphisms (SNPs) (Thermo Fisher Scientific). Genotypes were furthermore extracted from the Axiom 815K Spanish Biobank Array (Thermo Fisher Scientific) performed by the Spanish National Center for Genotyping (CeGen).

Statistics and reproducibility

Protein measurement data were Box-Cox transformed and then centered and scaled. Extreme outliers (>4.3 s.d.) were excluded as previously described 64 . The assumption of normal distribution for the transformed protein measurements was visually inspected but not formally tested. Sample size was not predetermined by any statistical method but, rather, by available data. The associations of serum protein profiles with prevalent AD ( n = 167) were examined cross-sectionally by logistic regression at baseline. The associations of serum protein profiles with incident LOAD ( n = 655) were examined longitudinally using Cox proportional hazards models after excluding all participants with prevalent dementia. Participants who died or were diagnosed with incident non-AD dementia were censored at date of death or diagnosis. To account for HR variability that may arise with lengthy follow-up periods, a secondary analysis using a 10-year follow-up cutoff of incident LOAD was performed ( n LOAD = 432). All individuals who had not experienced an event by the end of the 10-year follow-up were considered as not having an event. These individuals were not excluded from the analysis and were, thus, treated as ‘healthy’ controls. To compare the fits of the two follow-up times and to test for time dependence of the coefficients, we used ANOVA and the ‘survsplit’ function from the ‘survival’ R package 79 . For both prevalent and incident LOAD, we examined three covariate-adjusted models. The primary model (model 1) included the covariates sex and age. Model 2 included as an additional covariate the APOE- ε 4 allele count (ε2/ε4 genotypes excluded). The third model (model 3) included additional adjustment for cardiovascular and lifestyle risk factors (BMI, type 2 diabetes, education, hypertension and smoking history) that have been associated with risk of LOAD 80 and kidney function (eGFR) that may influence circulating protein levels. When performing the APOE -ε4 stratification analysis via interaction for incident LOAD, we added an interaction term between each aptamer and APOE-ε4 carrier status (no, not carrying ε4; yes, either ε34 or ε44) in model 2. We then used the ‘glht’ function from the ‘multcomp’ package (version 1.4.20) to obtain a recalculated HR and P value per strata. We extracted the effect sizes and P values for the interaction term directly from the summary of the Cox model. To assess the associations between APOE genotype (0, 1 or 2 copies of APOE - ε4 ) and the LOAD-associated proteins, a multiple linear regression was performed adjusting for sex and age, where the beta coefficient indicates the change in protein levels per ε4 allele count. Benjamini–Hochberg FDR was used to account for multiple hypothesis testing. ACE SomaLogic proteomics data were similarly Box-Cox transformed, and association analysis was performed in the same manner as in AGES. Mediation analysis was conducted using the ‘cmest’ function from the ‘CMAverse’ (version 0.1.0) R package with APOE - ε4 as exposure, incident LOAD as outcome and the 17 APOE-ε4 -dependent proteins as potential mediators. The proportion mediated was calculated with direct counterfactual imputation estimation and 95% CIs based on 1,000 bootstrap repetitions.

APOE- ε 4 dependence criteria of the proteins were defined as serum proteins that met FDR significance of less than 0.05 in association with incident LOAD in model 1, thus unadjusted for the APOE- ε 4 allele, but whose nominal significance was abolished upon APOE- ε 4 correction in model 2 ( P > 0.05). Serum proteins that remained nominally significantly associated with incident LOAD ( P < 0.05) upon APOE- ε 4 correction but changed direction of effect were also considered to meet the APOE-ε4 dependence criteria, as a reversal of the effect indicates that the primary association is driven by APOE- ε 4 .

Functional enrichment analyses were performed using overrepresentation analysis (ORA) and GSEA using the R packages ‘clusterProfiler’ and ‘fgsea’ 81 , 82 . The association significance cutoff for inclusion in ORA was FDR < 0.05. Background for both methods was specified as all proteins tested from the analysis leading up to enrichment testing. The investigated gene sets were the following: GO, Human Phenotype Ontology, KEGG, Wikipathways, Reactome, Pathway Interaction Database (PID), microRNA targets (MIRDB and Legacy), transcription factor targets (GTRD and Legacy), ImmuneSigDB and the vaccine response gene set 83 . Finally, we included tissue gene expression signatures via the same methods (ORA and GSEA) using data from GTEx 84 and the Human Protein Atlas 85 , where gene expression patterns across tissues were categorized in the same manner as described by Uhlen et al. 85 , and tissue-elevated expression was considered as gene expression in any of the categories ‘tissue-specific’, ’tissue-enriched’ or ‘group-enriched’. minGSSize was set at 2 when investigating the LOAD-associated serum proteins directly. Before running the GSEA, the average effect size from the appropriate observational analysis was computed for each protein detected by multiple aptamers to eliminate duplicates from the protein list. Duplicate protein annotations were removed before executing the ORA. The effect sizes from the observational analyses were used for GSEA ranking. For the PPI network analysis, PPIs from InWeb 32 ( n = 14,448, after Entrez ID filtering) were used to obtain the first-degree interaction partners of the APOE-ε4 -dependent proteins. For GSEA of the APOE-ε4 -dependent protein interaction partners, minGSSize was set to 15, and maxGSSize was set to 500. Gene expression patterns based on a consensus dataset combining GTEx and Human Protein Atlas gene expression data were obtained from the Human Protein Atlas (version 23) for the top LOAD-associated proteins (Tables 1 and 2 ) as well as single-cell sequencing cluster membership 85 . Analyses were conducted using R versions 4.2.1. and 4.2.3.

Protein comparisons across serum, CSF and brain

To compare protein modules and AD associations across tissues, protein modules and protein associations with AD were obtained from brain 37 and CSF 36 . The brain data, from the Banner Sun Health Research Institute 86 and ROSMAP 87 , included tandem mass tag (TMT)-MS-based quantitative proteomics for 106 controls, 200 asymptomatic AD cases and 182 AD cases. The CSF samples were collected under the auspices of the Emory Goizueta Alzheimer’s Disease Research Center (ADRC) and the Emory Healthy Brain Study (EHBS) 36 . The cohort consisted of 140 healthy controls and 160 patients with AD as defined by the National Institute on Aging research framework 73 . Protein measurements were performed using TMT-MS and SOMAScan (7K). Only SomaLogic protein measurements were included in the comparison between CSF and serum, which were median normalized. Proteins were matched on SomaLogic aptamer ID when possible but otherwise by Entrez gene symbol. Overlaps between modules and AD-associated (FDR < 0.05) proteins across tissues were evaluated with Fisher’s exact test.

A two-sample bidirectional MR analysis was performed, first, to evaluate the potential causal effects of serum protein levels on AD (forward MR) and, second, to evaluate the potential causal effects of AD or its genetic liability on serum protein levels (reverse MR). All aptamers significantly (FDR < 0.05) associated with LOAD (incident or prevalent) were included in the MR analyses, or a total of 346 unique aptamers (Supplementary Tables 2 , 3 and 5 ), of which 320 aptamers were significant in the full follow-up incident LOAD analysis (models 1–3); 106 aptamers were significant in the 10-year follow-up incident LOAD analysis (models 1–3); and 10 aptamers were significant in the prevalent LOAD analysis (models 1–3). Genetic instruments for serum protein levels were obtained from a GWAS of serum protein levels in AGES 23 and defined as follows. All variants within a 1-Mb (±500-kb) cis -window for the protein-encoding gene were obtained for a given aptamer. A cis -window-wide significance level Pb = 0.05/N, where N equals the number of SNPs within a given cis -window, was computed, and variants within the cis -window for each aptamer were clumped ( r 2 ≥ 0.2, P ≥ Pb). All aptamers included in the MR analysis had instruments with F -statistic > 10 (Supplementary Table 17 ). The effect of the genetic instruments for serum protein levels on LOAD risk was obtained from a GWAS of 39,106 clinically diagnosed LOAD cases, 46,828 proxy-LOAD and dementia cases and 401,577 controls of European ancestry 18 . Genetic instruments for the serum protein levels not found in the LOAD GWAS dataset were replaced by proxy SNPs ( r 2 > 0.8) when possible, to maximize SNP coverage. Genetic instruments for LOAD in the reverse causation MR analysis were obtained from the same LOAD GWAS 18 , where genome-wide significant variants were extracted ( P < 5 × 10 −8 ) and clumped at a more stringent linkage disequilibrium (LD) threshold ( r 2 ≥ 0.01) than for the protein instruments to limit overrepresentation of SNPs from any given locus across the genome. In the reverse causation MR analysis, cis- variants (±500 kb) for the given protein were excluded from the analysis to avoid including pleiotropic instruments affecting the outcome (protein levels) through other mechanisms than the exposure (LOAD). The primary reverse causation MR analysis was performed excluding any variants in the APOE locus (chr19:45,048,858–45,733,201, genome build GRCh37). Causal estimate in the forward MR for each protein was obtained by the generalized weighted least squares (GWLS) method 88 , which accounts for correlation between instruments. Causality for proteins with single cis -acting variants was assessed with the Wald ratio estimator. For the reverse MR analysis, the inverse variance weighted method was applied due to a more stringent LD filtering of the instruments. Instrument heterogeneity was evaluated with Cochran’s Q test and horizontal pleiotropy with the MR Eggerʼs test using the ‘TwoSampleMR’ R package.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

Data from AGES are available through collaboration ([email protected]) under a data usage agreement with the Icelandic Heart Association. Data from the ACE cohort are available at the Global Neurodegeneration Proteomics Consortium ( https://www.neuroproteome.org/ ) via the Alzheimer Disease Data Initiative portal or by direct request to ACE Alzheimer Center Barcelona (contact: [email protected]). GWAS summary statistics were obtained from the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession numbers GCST90027158 , GCST90243133 , GCST90242506 and GCST90241568 ), the Global Lipids Genetics Consortium ( https://csg.sph.umich.edu/willer/public/glgc-lipids2021/ ) and deCode Genetics ( https://www.decode.com/summarydata/ ). Tissue specificity information was obtained from Human Protein Atlas version 23 ( https://v23.proteinatlas.org/ ). The MS-based validation data for aptamers included on the custom SOMAscan panel used in this study are available from ProteomeXchange via the PRIDE partner repository ( https://www.ebi.ac.uk/pride/ ) 89 under accession numbers PXD008819 – PXD008823 and PXD054671 , and from the PASSEL repository ( https://peptideatlas.org/passel/ ) under accession number PASS01145 . All other data supporting the conclusions of this study are presented in the main text and are freely available as a supplement to this manuscript.

Code availability

Statistical analyses were performed in R ( https://www.r-project.org/ ). The code used in this study will be made available by the corresponding author, V. Gudmundsdottir, upon reasonable request.

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Acknowledgements

The authors acknowledge the contribution of the Icelandic Heart Association (IHA) staff to AGES-Reykjavik as well as the involvement of all study participants. National Institute on Aging (NIA) contracts N01-AG-12100 and HHSN271201200022C (for V. Gudnason) and Althingi (the Icelandic Parliament) financed the AGES-Reykjavik study. IHA and Novartis have collaborated on proteomics research since 2012. This study was also funded by NIA grants 1R01AG065596-01A1 (to V. Gudnason), 1K08AG068604 (to E.J.) and P30AG066511 and U01AG061357 (to A.I.L.) and Icelandic Research Fund grant 206692-051 (to V. Gudmundsdottir). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Genome Research @ Ace Alzheimer Center Barcelona (GR@ACE) project is supported by Grifols SA, Fundación bancaria ‘La Caixa’, Ace Alzheimer Center Barcelona and CIBERNED. Additional support was received from the ADAPTED and MOPEAD projects (European Union/EFPIA Innovative Medicines Initiative Joint (grant numbers 115975 and 115985, respectively)), from the HARPONE project, from the Agency for Innovation and Entrepreneurship (VLAIO) grant number PR067/21 and from Janssen. A.C. received support from the National Institute of Health Carlos III under the Sara Borrell grant (CD22/00125). The funders had no control over the publication.

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Elisabet A. Frick, Valur Emilsson, Elias F. Gudmundsson, Alexander Gudjonsson, Thor Aspelund, Valborg Gudmundsdottir & Vilmundur Gudnason

Faculty of Medicine, University of Iceland, Reykjavik, Iceland

Valur Emilsson, Thorarinn Jonmundsson, Anna E. Steindorsdottir, Thor Aspelund, Valborg Gudmundsdottir & Vilmundur Gudnason

Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA

Erik C. B. Johnson, Eric B. Dammer, Anantharaman Shantaraman, Nicholas T. Seyfried & Allan I. Levey

Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA

Erik C. B. Johnson, Nicholas T. Seyfried & Allan I. Levey

Research Center and Memory Clinic. Ace Alzheimer Center Barcelona – Universitat Internacional de Catalunya, Barcelona, Barcelona, Spain

Raquel Puerta, Amanda Cano, Mercè Boada, Sergi Valero, Pablo García-González & Agustin Ruiz

Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA

Eric B. Dammer, Anantharaman Shantaraman & Nicholas T. Seyfried

CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain

Amanda Cano, Mercè Boada, Sergi Valero, Pablo García-González & Agustin Ruiz

Novartis, Cambridge, MA, USA

Rebecca Pitts, Xiazi Qiu, Nancy Finkel, Joseph J. Loureiro & Lori L. Jennings

Novartis, San Diego, CA, USA

Anthony P. Orth

Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA

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Contributions

Conceptualization: E.A.F., V. Gudmundsdottir., V.E. and V. Gudnason. Formal analysis: E.A.F., V. Gudmundsdottir, T.J., A.E.S., E.F.G., A.G., T.A., E.B.D. and A.S. Resources: V. Gudnason, V.E., A.I.L., A.R., A.P.O., J.J.L., L.L.J., N.T.S., E.C.B.J. and L.J.L. Data curation: R.P., A.C., M.B., P.G.-G., S.V., V. Gudmundsdottir, T.A. and E.F.G. Writing original draft: E.A.F. and V. Gudmundsdottir. Writing review and editing: all authors Visualization: E.A.F. and V. Gudmundsdottir. Supervision: V. Gudmundsdottir and V. Gudnason. Funding acquisition: V. Gudnason and L.J.L.

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Correspondence to Valborg Gudmundsdottir or Vilmundur Gudnason .

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R.P., X.Q., N.F., L.L.J., A.P.O. and J.J.L. are employees and stockholders of Novartis. N.T.S. and A.I.L. are co-founders of Emtherapro. No other potential conflicts of interest relevant to this article were reported.

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Extended data

Extended data fig. 1 functional enrichment analysis of apoe-ε4 -dependent protein-protein interaction partners..

a ) A scheme of the PPI partners selection, where first degree partners of the APOE-ε4- dependent proteins were extracted from the InWeb database. b-c ) Enrichment of selected GO terms for the PPI partner proteins shown as b ) dotplot and c ) gene-concept network. d-e ) Enrichment of top seven unique Wikipathways shown as d ) dotplot and e ) gene-concept network. BP, biological process; CC, cellular component; MF, molecular function.

Supplementary information

Supplementary information.

Supplementary Notes 1–8, Supplementary Figs. 1–13, Supplementary Table 25 and Supplementary References.

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Frick, E.A., Emilsson, V., Jonmundsson, T. et al. Serum proteomics reveal APOE-ε4 -dependent and APOE-ε4 -independent protein signatures in Alzheimer’s disease. Nat Aging (2024). https://doi.org/10.1038/s43587-024-00693-1

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DOI : https://doi.org/10.1038/s43587-024-00693-1

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Cancer drug could treat early-stage Alzheimer’s disease, study shows

Researchers discovered that by blocking a specific enzyme called indoleamine-2,3-dioxygenase 1, or IDO1 for short, they could rescue memory and brain function in models that mimic Alzheimer’s disease. Pictured from right to left: Melanie Reynolds, Penn State’s Dorothy Foehr Huck and J. Lloyd Huck Early Career Chair in Biochemistry and Molecular Biology, Praveena Prasad, doctoral candidate at Penn State, Brenita Jenkins, lab manager and research scientist at Penn State.

Credit: Michelle Bixby/Penn State

UNIVERSITY PARK, Pa. — A type of drug developed for treating cancer holds promise as a new treatment for neurodegenerative diseases such as Alzheimer’s, according to a recent study by researchers at Penn State, Stanford University and an international team of collaborators.

The researchers discovered that by blocking a specific enzyme called indoleamine-2,3-dioxygenase 1, or IDO1 for short, they could rescue memory and brain function in models that mimic Alzheimer’s disease. The findings, published today (Aug. 22) in the journal Science, suggest that IDO1 inhibitors currently being developed as a treatment for many types of cancer, including melanoma, leukemia and breast cancer, could be repurposed to treat the early stages of neurodegenerative diseases — a first for the chronic conditions that lack preventative treatments.

“We’re showing that there is high potential for IDO1 inhibitors, which are already within the repertoire of drugs being developed for cancer treatments, to target and treat Alzheimer's,” said Melanie McReynolds , the Dorothy Foehr Huck and J. Lloyd Huck Early Career Chair in Biochemistry and Molecular Biology at Penn State and co-author on the paper. “In the broader context of aging, neurological decline is one of the biggest co-factors of being unable to age healthier. The benefits of understanding and treating metabolic decline in neurological disorders will impact not just those who are diagnosed, but our families, our society, our entire economy.”

Alzheimer’s disease is the most common type of dementia, an umbrella term that refers to all age-associated neurodegenerative disorders, McReynolds explained. In 2023, as many as 6.7 million Americans were living with Alzheimer’s disease, according to the Centers for Disease Control and Prevention , and its prevalence is expected to triple by 2060.

“Inhibiting this enzyme, particularly with compounds that have been previously investigated in human clinical trials for cancer, could be a big step forward in finding ways to protect our brains from the damage caused by aging and neurodegeneration,” said Katrin Andreasson , the Edward F. and Irene Pimley Professor of Neurology and Neurological Sciences at the Stanford University School of Medicine and the study’s senior author.

Alzheimer’s disease affects the parts of the brain that control thought, memory and language, the result of progressive and irreversible loss of synapses and neural circuitry. As the disease progresses, symptoms can increase from mild memory loss to losing the ability to communicate and respond to the environment. Current treatments for the disease are focused on managing symptoms and slowing progression, through targeting the build-up of amyloid and tau plaques in the brain, but there are no approved treatments for combating the onset of the disease, McReynolds said.

“Scientists have been targeting the downstream effects of what we identify as an issue with the way the brain powers itself,” said Praveena Prasad , doctoral student at Penn State and co-author on the paper. “The therapies that are currently available are working to remove peptides that are likely the result of a bigger issue we can target before those peptides can start forming plaques. We’re demonstrating that by targeting the brain’s metabolism, we can not only slow, but reverse the progression of this disease.”

Using preclinical models — in vitro cellular models with amyloid and tau proteins, in vivo mouse models and in vitro human cells from Alzheimer’s patients — the researchers demonstrated that stopping IDO1 helps restore healthy glucose metabolism in astrocytes, the star-shaped brain cells that provide metabolic support to neurons.

IDO1 is an enzyme that breaks down tryptophan, the same molecule in turkey that can make you sleepy, into a compound called kynurenine. The body’s production of kynurenine is the first part of a chain reaction known as the kynurenine pathway, or KP, which plays a critical role in how the body provides cellular energy to the brain. The researchers found that when IDO1 generated too much kynurenine, it reduced glucose metabolism in astrocytes that was required to power neurons. With IDO1 suppressed, metabolic support for neurons increased and restored their ability to function.

The researchers conducted the study in several models of Alzheimer’s pathology, namely amyloid or tau accumulation and found that the protective effects of blocking IDO1 cut across these two different pathologies. Their findings suggest that IDO1 may also be relevant in diseases with other types of pathology, such as Parkinson’s disease dementia as well as the broad spectrum of progressive neurodegenerative disorders known as tauopathies, explained Paras Minhas, current resident at Memorial Sloan Kettering Cancer Center who earned a combined medical and doctoral degree in neuroscience at Stanford School of Medicine and is first author on the paper

“The brain is very dependent on glucose to fuel many processes, so losing the ability to effectively use glucose for metabolism and energy production can trigger metabolic decline and, in particular, cognitive decline,” Minhas said. “Through this collaboration we were able to visualize precisely how the brain’s metabolism is impacted with neurodegeneration.”

The other Penn State author is lab manager Brenita Jenkins. Other co-authors are Amira Latif-Hernandez, Aarooran S. Durairaj, Qian Wang, Siddhita D. Mhatre, Travis Conley, Hannah Ennerfelt, Yoo Jin Jung, Edward N. Wilson, Frank M. Longo, Takeshi Uenaka and Marius Wernig of Stanford University; Jeffrey R. Jones, Ryan Goodman, Traci Newmeyer, Kelly Heard, Austin Kang and Fred H. Gage of The Salk Institute for Biological Studies; Yuki Sugiura and Makoto Suematsu of Keio University; Ling Liu and Joshua D. Rabinowitz of Princeton University; Erik M. Ullian of the University of California San Francisco; Geidy E. Serrano and Thomas G. Beach of the Banner Sun Health Research Institute.

The Howard Hughes Medical Institute Hanna H. Gray Fellows Program Faculty Phase and the Burroughs Welcome Fund PDEP Transition to Faculty funded the Penn State aspects of this work.

10.1126/science.abm6131

Method of Research

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Article title.

Restoring hippocampal glucose metabolism rescues cognition across Alzheimer's disease pathologies

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22-Aug-2024

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