A large multi-ancestry genetic study published in Nature identified 127 genetic risk loci associated with Alzheimer’s disease (AD), including 48 previously unreported loci, providing new insights into the genetic architecture, underlying biological mechanisms, and potential therapeutic targets of the disease.
The study combined genetic summary data from 30 cohorts, comprising 109,479 individuals with AD, 74,141 proxy cases, 2,131,799 controls, and 499,708 proxy controls. Proxy cases were defined as individuals whose mother or father had been diagnosed with AD or dementia, excluding participants with AD themselves. The effective sample size was 416,493, with participants representing European, African, East Asian, admixed American, and South Asian ancestries. European ancestry accounted for approximately 91% of the effective sample size.
Genome-wide association studies (GWAS) were conducted separately across ancestry groups, followed by inverse-variance-weighted fixed-effect meta-analysis. Gene prioritization involved fine-mapping, gene-based analyses, quantitative trait locus colocalization, and Mendelian randomization. Polygenic scores (PGSs) were also developed to assess genetic risk prediction across independent clinical and biobank cohorts.
The analysis identified 118 significant loci in the multi-ancestry analysis and nine additional loci in the European-ancestry analysis, bringing the total to 127, including 48 novel loci. Further investigation identified 17 genes among the novel loci that interacted with drugs not approved for AD. Five potential therapeutic targets were highlighted: RRM2B, SYK, KEAP1, CACNA1S, and AXL. SYK and AXL were associated with immune responses to amyloid-beta, while earlier experimental studies reported promising findings involving RRM2B, SYK, and KEAP1. However, these targets were not evaluated as treatments in the present study. QPCT was also prioritized at a previously established locus, linking genetic findings to amyloid-beta modification targeted by donanemab.
Gene-set analyses identified 72 significantly associated gene sets, predominantly involving lipid binding, immune activation, amyloid catabolism, and cell adhesion. Additional pathways included EphrinB reverse signaling, glutathione metabolism, RAS signaling, sphingolipid metabolism, and synaptic endocytosis.
Cell-type analyses demonstrated significant enrichment of AD-associated genetic signals in microglia, particularly genes involved in inflammatory responses and phagocytosis. Several implicated genes included INPP5D, SYK, BLNK, HAVCR2, PICALM, AXL, FCER1G, and PLCG2. Enrichment was also observed in three neuronal populations, suggesting potential neuronal dysregulation. However, these associations became less significant after adjustment for differences in gene expression across cell types, leaving the contribution of neuronal changes to disease development uncertain. Additional analyses suggested that increased astrocytic expression of KIF21B and reduced oligodendrocytic expression of MAF might contribute to AD susceptibility.
Genetic overlap with other neurodegenerative conditions, including Parkinson’s disease and amyotrophic lateral sclerosis (ALS), was also observed. At the UBE2V1–SPATA2 locus, colocalization analysis suggested a shared causal genetic variant associated with AD and ALS.
Heritability estimates using SBayesRC indicated that common genetic variants accounted for approximately 16% of AD liability in European ancestry, compared with 6% estimated using linkage disequilibrium score regression. Estimates were 13% in East Asian and 10% in African ancestry, although differences between ancestry groups were not statistically established. The multi-ancestry PGS explained an average of 12.8% of liability variance in European cohorts beyond baseline models, reaching 16.9% in one clinical cohort. Among European participants aged 65 years or older in the UK Biobank, observed AD prevalence was seven times higher in the highest PGS decile than in the lowest decile. However, predictive performance was weaker in non-European populations.
The findings expand the understanding of AD genetics, highlighting the central contribution of microglial activity and pathways involving immunity, lipid metabolism, and amyloid processing. Although PGSs improved genetic risk prediction, particularly in European-ancestry populations, their clinical applicability remains to be established. Limited representation of non-European populations and potential diagnostic inaccuracies associated with parental proxy reports underscore the need for larger, more diverse genetic studies to improve the accuracy, generalizability, and equity of AD risk assessment.
Reference
- Uffelmann E, Wightman DP, Bahrami S, Shadrin AA, Fominykh V, Ojima T, et al. Alzheimer’s disease genetics converges on microglial and neuronal dysregulation. Nature. 2026 Oct 28. doi:10.1038/s41586-026-11206-y.