Alzheimer’s Disease (AD) GWAS was conducted in 9,168 subjects (2,903 cases; 6,265 controls) of African ancestry.

Participants were diagnosed for AD according to the National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association criteria. Age at onset for AD patients and age at examination or death for healthy controls was available for most datasets. When not available, other information was used instead, such as age at diagnosis or age at ascertainment. To restrict the analyses to cases with late-onset AD, individuals with age <60 years at symptom onset, last examination, or death were excluded.

Genome-wide single-variant association analyses of common and rare variants were performed individually on 17 independent datasets using SNPTEST. One of these datasets include 705 individuals from West Africa (sampled from Ibadan, Nigeria).

Each dataset was independently phased and imputed to the African Genome Resource (AGR) reference panel.

Age, sex, and population stratification (as determined by the first three principal components (PCs) calculated individually on each dataset) were entered as covariates in Model 1; APOEe4 allele dosage (coded as 0,1,2) was entered as an additional covariate in Model 2. Logistic regression was used for case-control datasets and generalized estimating equations (GEE) as implemented in GWAF were used for family-based datasets (i.e., MIRAGE). Associations with extreme beta coefficients (|β| > 5) were filtered out. Within-study results were subsequently meta-analyzed with METAL employing an inverse-variance based model with genomic control.