AbstractBackgroundAlzheimer’s disease (AD) demonstrates heterogeneity across domains of cognitive impairment, atrophy, and pathological accumulation. This has led to speculations that AD may comprise several disease subtypes. AD is under substantial genetic influence, thus searching for genetic clustering may provide insight towards the origins of this phenotypic variability.MethodGenotyping data from 2,739 AD cases and 5,478 age and sex‐matched controls from the UK Biobank were used as the discovery data. A principal components analysis (PCA) was applied to AD‐associated variants (p<0.05 in the IGAPS2 GWAS of AD) to assess disease‐relevant structure. A novel biclustering algorithm was then applied to find disease‐specific genetic signatures of AD. This algorithm searches for subsets of subjects and variants that are present in cases, but importantly, not in controls. Pathway analysis was used to characterize the biological pathways implicated by disease‐relevant and specific clustering. Data from 476 AD cases and 591 controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were used to test replication of clusters.ResultPCA revealed 3 distinct clusters. Each cluster contained a mix of cases and controls but these clusters only became apparent when restricting to AD‐associated variants, suggesting disease‐relevant structure. Examining clusters separately, we found 2 significant disease‐specific biclusters comprising sets of variants found more frequently in a subset of AD cases than in controls. When projecting ADNI data on UK Biobank principal components, there was almost perfect overlap of disease‐relevant clusters. Disease‐specific biclusters significantly replicated (p<0.05) across a range of parameter choices.ConclusionThese findings demonstrate a hierarchy of heterogeneity for AD genetic risk. At the first level, the three disease‐relevant clusters may indicate that different pathways are more vulnerable for different groups of individuals, but additional risk factors or insults are required to substantially increase risk for AD. At the next level, individuals assigned to the biclusters may represent subtypes of AD with different genetic signatures that significantly increase risk for AD. Replication in ADNI demonstrates that this hierarchical structure is a generalizable aspect of AD genetic risk. More broadly, this study illustrates an approach that can be extended to investigate genetic heterogeneity of other complex diseases.