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An international study using genetic data from nearly 2.8 million people identified 127 Alzheimer’s disease risk loci, including 48 newly identified loci. Its analyses suggest that commonly used methods may have underestimated the contribution of common genetic variants, while findings also point to immune and neuronal processes; the results do not establish new treatments or settle how much of the observed risk is genetic.
An international research team has identified 127 genetic loci associated with Alzheimer’s disease, including 48 not previously reported, in an analysis drawing on data from nearly 2.8 million people. Published in Nature, the study also suggests that some earlier methods may have underestimated the contribution of common genetic variants to Alzheimer’s risk, while linking genetic signals to immune activity and neurons in the brain.
The researchers combined summary genetic data from 30 cohorts, including people diagnosed with Alzheimer’s, people whose parent had Alzheimer’s or dementia, and control participants. The overall data set included 109,479 people with Alzheimer’s, 74,141 proxy cases, 2,131,799 controls and 499,708 proxy controls. Proxy cases were participants reporting a parent’s diagnosis; they were not themselves counted as Alzheimer’s cases in that part of the analysis. The study reported an effective sample size of 416,493.
The multi-ancestry analysis found 118 significant loci; a further nine were identified in analysis restricted to European ancestry, producing 127 overall. The researchers also prioritized genes and biological pathways. Among the findings were associations involving microglia, the brain’s immune cells, and several neuronal populations. The analyses highlighted pathways related to immune activation, lipid binding, amyloid processing and cell adhesion.
The team examined five potential drug targets—RRM2B, SYK, KEAP1, CACNA1S and AXL—but did not test them as treatments in this study. The source report notes that previous experimental work had promising findings for some targets, while interventions involving CACNA1S and AXL did not improve outcomes in the cited human and mouse studies. A genetic association or target nomination is not evidence that a drug acting on it will safely or effectively prevent or treat Alzheimer’s.
What the New Genetic Map Adds
The results expand the number of identified Alzheimer’s risk loci and offer researchers a broader set of genetic signals to investigate. The study’s central point about inherited risk is methodological: estimates based on common genetic variants can depend on how researchers analyze and combine data. The authors used SBayesRC to estimate SNP-based heritability and compared its estimates with those from linkage disequilibrium score regression, as well as simulations using UK Biobank data. The reported findings suggest that some existing approaches may miss part of the genetic signal; they do not mean that genes determine an individual’s outcome.
The findings also reinforce interest in processes beyond amyloid alone, including microglial immune activity and neuronal biology. That may help guide future work on disease mechanisms and risk prediction. However, the study does not demonstrate that changing these processes will improve symptoms, slow disease, or prevent Alzheimer’s. Its potential relevance is in identifying research directions, not providing a treatment recommendation.
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Earlier Estimates and Study Design
Twin studies have estimated that 60% to 80% of Alzheimer’s susceptibility is heritable. That estimate describes variation in susceptibility across a population and should not be interpreted as the percentage of a particular person’s disease caused by genes. Earlier genome-wide association studies had identified about 80 risk loci, while estimates based on common single-nucleotide polymorphisms suggested those variants accounted for about 5% of disease liability. These figures measure related but not identical aspects of genetic contribution.
The new analysis included participants grouped by European, African, East Asian, admixed American and South Asian ancestry. Yet about 91% of the effective sample size was European ancestry. The researchers said ancestry-specific results were less precise in groups with smaller samples. Cases were identified through clinical diagnoses or health-record codes; some cohorts included unspecified dementia codes. Those design choices matter when interpreting both the number of loci and how well findings may apply across populations.
The study used several methods to prioritize genes, including fine-mapping, gene-based analyses, molecular data and Mendelian randomization. The researchers also evaluated polygenic scores in independent clinical and biobank cohorts. Such scores combine many genetic variants to estimate relative risk, but their predictive performance can vary across populations and does not itself diagnose disease.
“The analyses identified 118 significant loci in the multi-ancestry analysis and nine additional loci in the European-ancestry-only analysis, giving 127 loci overall; 48 were newly identified.”
— The study authors, as summarized in the News-Medical report
Limits of the Genetic Findings
The study does not establish that its newly identified loci cause Alzheimer’s, nor does it show that targeting the nominated genes would benefit patients. Some genetic signals may operate through mechanisms not yet understood. The authors also reported that, after adjustment for average differences in gene expression across cell types, the microglial association remained significant while neuronal associations became only nominally significant. Whether the observed neuronal expression patterns contribute to disease or result from neurodegeneration remains unresolved.
Representation is another limitation: the effective sample was heavily weighted toward European ancestry, and smaller samples produced less precise results for other groups. The available report does not provide enough detail to determine how much the revised heritability estimates differ numerically from previous estimates, or how well any resulting risk predictions would work in routine clinical care. The size of the genetic contribution remains a question of estimation, not a single settled percentage applicable to every person.
Testing Signals in Future Research
Further studies will need to replicate the associations in larger and more balanced ancestry groups, clarify how prioritized genes affect brain cells, and test whether the proposed biological mechanisms are relevant to disease progression. Researchers would also need separate experimental and clinical evidence before any of the named targets could be considered useful treatments. The current study’s drug-target analysis is a starting point for investigation, not a report of a clinical trial.
For risk prediction, the next question is whether polygenic scores can be validated in independent populations and shown to add useful information beyond existing clinical factors. The study evaluated scores in independent cohorts, but the source material does not establish that they are ready for routine use. Until further validation, the results are best understood as research findings about population-level risk and disease biology, not individual medical guidance.
Key Questions
What did the study find?
Researchers reported 127 Alzheimer’s-associated genetic loci, including 48 newly identified loci, and connected genetic signals with immune and neuronal processes. The findings come from genetic analyses, not treatment tests.
Does this mean genes cause 60% to 80% of an individual’s Alzheimer’s disease?
No. The 60% to 80% figure cited from twin studies is an estimate of heritability within populations. It is not a calculation of how much of one person’s disease is caused by genes.
Did the researchers identify a new Alzheimer’s treatment?
No. The study nominated potential targets, including SYK and AXL, but did not test them as treatments. A genetic finding does not establish that targeting a gene will help patients.
How broadly do the results apply across ancestry groups?
The study included several ancestry groups, but about 91% of the effective sample size was European ancestry. The authors said results were less precise in groups with smaller samples, so more representative studies are needed.
Source: news-medical.net
