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An international study drawing on genetic data from nearly 2.8 million people identified 127 Alzheimer’s disease risk loci, including 48 not previously reported. The researchers also found evidence linking genetic risk to microglia and neurons, and argue that a method used to estimate genetic contribution may have produced lower estimates than another approach. The findings do not establish new treatments or show that genetic risk can yet be predicted equally well across ancestry groups.
Researchers analyzing genetic data from nearly 2.8 million people identified 127 loci associated with Alzheimer’s disease, including 48 not previously reported, and found that one commonly used method may have underestimated how much common genetic variants contribute to risk. The international study, published in Nature, also linked Alzheimer’s-associated genes to immune activity in microglia and to neuronal processes, but it does not establish that the newly highlighted genes are causes of disease or proven treatment targets.
The researchers combined data from 30 cohorts, including 109,479 people diagnosed with Alzheimer’s, 74,141 proxy cases, 2,131,799 controls and 499,708 proxy controls. Proxy cases were people whose mother or father was reported to have Alzheimer’s or dementia; they were not themselves counted as diagnosed cases in that analysis. The study’s effective sample size was 416,493, a separate measure used in genetic analyses.
The multi-ancestry analysis found 118 significant risk loci; a European-ancestry-only analysis added nine, for 127 overall. Forty-eight were new to the study’s findings. The team also identified 72 significant gene sets, with results clustering around lipid binding, immune activation, amyloid processing and cell adhesion. These are statistical associations and biological clues, not proof that every implicated pathway drives disease.
For the heritability question, the researchers used SBayesRC to estimate the contribution of common genetic variants and compared its results with estimates from linkage disequilibrium score regression, or LDSC. The study’s simulations using UK Biobank data examined differences between the methods. The report says those differences suggest earlier SNP-based estimates may have been too low; it does not mean that genes explain all Alzheimer’s risk or that a person’s future can be predicted from genetic data alone.
What the New Risk Loci Add
The results expand the map researchers can use to investigate inherited Alzheimer’s risk and the biology associated with it. The study’s cell analyses found enrichment of genetic associations among genes preferentially expressed in microglia, immune cells in the brain. Inflammatory microglial states had the strongest association, although no individual state met the study’s threshold for statistical significance.
The findings could help guide follow-up work on disease mechanisms and risk prediction. The researchers also highlighted five possible drug targets—RRM2B, SYK, KEAP1, CACNA1S and AXL—but the study did not test these as Alzheimer’s treatments. Some prior experimental work had reported promising results for certain targets, while interventions involving CACNA1S and AXL had not improved outcomes in the cited human and mouse studies. These are research leads, not treatment recommendations.
A clearer account of genetic contribution may also affect how future studies interpret risk. However, heritability is a population-level estimate, not the proportion of an individual’s disease caused by genes. Alzheimer’s risk reflects multiple factors, and this study does not provide a clinical test or change current care.
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Earlier Estimates and Study Design
Previous twin studies have estimated that 60% to 80% of Alzheimer’s susceptibility is heritable. Earlier genome-wide association studies had identified about 80 risk loci, while estimates based on common single-nucleotide polymorphisms suggested those variants accounted for roughly 5% of disease liability. Those figures describe different methods and measures; they should not be treated as interchangeable estimates of an individual’s risk.
Researchers conducted genetic analyses within ancestry groups, adjusted for factors including age and sex, and combined results using a statistical meta-analysis. Although participants represented European, African, East Asian, admixed American and South Asian ancestry groups, about 91% of the effective sample was of European ancestry. The authors report that results for groups with smaller samples were less precise, limiting how confidently the findings can be applied across populations.
Beyond identifying loci, the team used several approaches to prioritize genes and pathways, including fine-mapping, gene-based analyses and comparisons with molecular data. They also examined genes associated with changes in different brain cell types. Such analyses can narrow down candidates for further testing, but they do not by themselves establish the sequence of events that leads to Alzheimer’s.
“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 report
Limits on Risk and Cell Findings
The study does not show that the 48 newly identified loci directly cause Alzheimer’s, nor does it establish that the proposed drug targets will work in patients. The five targets were prioritized through genetic and database analyses; they were not tested as treatments in this research.
The direction of some cell findings is also unsettled. Genes underexpressed in three neuronal populations showed enrichment, but the researchers could not determine whether those expression differences contribute to Alzheimer’s or arise after neurodegeneration begins. After adjustment for average differences in gene expression across cell types, the neuronal associations became only nominally significant, while the microglial association remained significant.
It is also unclear how well the findings will translate to populations underrepresented in the dataset. The study included several ancestry groups, but the large European share and smaller, less precise subgroup results limit firm conclusions about differences in genetic risk across populations. The report does not provide a new validated clinical prediction tool or a revised individual-risk estimate.
Further Testing of Genetic Leads
The immediate next step is replication and follow-up research: scientists will need to test whether the newly associated loci and prioritized genes affect Alzheimer’s biology, and determine how those effects operate in relevant brain cells. Candidate targets will require experimental and clinical evaluation before they can be considered treatments.
Further studies with larger and more balanced ancestry representation could clarify how consistently the associations appear across populations and improve the precision of risk analyses. Researchers will also need to assess whether the heritability estimates produced by different methods hold up in additional datasets. The present findings identify directions for that work, but no new clinical guidance or treatment change is announced.
Key Questions
What did the study find?
It identified 127 Alzheimer’s-associated genetic loci, including 48 not previously reported in the study’s analysis, and found genetic associations involving microglia and other biological processes.
Does this mean genes explain most Alzheimer’s cases?
No. The study compares estimates of genetic contribution, including the contribution of common variants. Heritability is a population-level measure and does not mean genes explain a fixed share of any one person’s disease.
Are the highlighted genes new treatments?
No. RRM2B, SYK, KEAP1, CACNA1S and AXL were identified as possible research targets, but the study did not test them as treatments. Further research would be needed to establish whether targeting them is safe or effective.
How representative was the genetic dataset?
The study included participants of European, African, East Asian, admixed American and South Asian ancestry, but about 91% of the effective sample was European ancestry. The authors said results were less precise for groups with smaller samples.
Source: news-medical.net
