This meta-analysis examined genetic data and diagnoses of Alzheimer disease and related dementias within the VA Million Veterans Program. The population included participants of European ancestry, Hispanic ancestry, and African ancestry. The authors compared their findings against existing GWAS results to identify new dementia-associated loci. Secondary outcomes included eQTL effects and differential gene expression.
In the European ancestry meta-analysis, the study identified 17 loci. The African ancestry meta-analysis identified 4 loci, while the Hispanic ancestry meta-analysis identified 3 loci. When combining European ancestry GWAS loci with consortium results, the total reached 72 loci. A cross-ancestry meta-analysis identified 62 lead loci. Additionally, 26 genes or regions surpassed genome-wide significance.
The authors note that adverse events, serious adverse events, discontinuations, and tolerability were not reported. The study does not describe a specific intervention or comparator beyond the genetic analysis framework. Practice relevance suggests that these new loci present potential new targets for dementia treatment. Future large-scale genetic analyses will enhance understanding of genetic risk and improve prediction.
The evidence is observational and genetic in nature. The authors caution that these findings represent potential targets rather than established clinical interventions. No safety data were available to assess tolerability or adverse outcomes associated with these genetic markers.
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Introduction Biobank-scale cohorts of individuals with genetic data and diagnoses of Alzheimers disease and related dementias (ADRD) have facilitated the discovery of several additional risk loci via meta-analysis, with existing cohorts assembled specifically for ADRD genetic discovery. Cross-ancestry meta-analyses have further elucidated the overall genetic architecture of these dementias. Here, we include for the first time the European ancestry (EA) and Hispanic ancestry (HA) subset of the VA Million Veterans Program (MVP) along with the African ancestry (AA) MVP participants in a meta-analysis with a large-scale EA and AA meta-analysis. Methods Independent genome-wide association studies (GWASs) were conducted in MVP participants using four phenotypes derived from electronic medical records and surveys: ADRD, prescriptions for common dementia medications, and self-reported maternal and paternal history of dementia (dementia by proxy). These GWASs were repeated in the EA, AA, and HA ancestry groups. MVP ancestry-specific and cross-ancestry meta-analyses were conducted. These were then meta-analyzed with existing GWAS results. Functionality of the peak variants was explored using brain-derived gene expression data and co-localization analysis. Results Apart from the APOE region, 17, 4, and 3 GWS loci were observed in the MVP EA, AA, and HA meta-analyses, respectively. When we meta-analyzed these with consortium results, we observed 72 loci in the EA GWAS and 62 lead loci in the cross-ancestry meta-analysis. While most of these loci were known, 26 genes/regions were identified containing variants surpassing genome-wide significance for the first time: 7 EA specific, 12 in the cross-ancestry meta-analysis, and 7 driven by AA and HA cohorts. Several of these are members of pathways containing established ADRD risk genes, and several of the peak SNPs showed evidence for eQTL effects on their respective genes. Several of the novel SNPs showed significant eQTL effects in brain-derived mRNA-seq experiments, and the novel gene PAX7 was significantly differentially expressed in ADRD cases and controls. Discussion MVP represents a large and unique primarily male cohort comprised of US Veterans from a range of backgrounds with a unique set of environmental exposures. The results generated here demonstrate the utility of biobank-level cohorts for AD genetic discovery, and the inclusion of MVP data in our study enabled an increase of underrepresented ancestry groups relative to prior cross-ancestry GWASs. The new AD risk loci identified present potential new targets for dementia treatment, and future large-scale genetic analyses will enhance what is known about AD genetic risk and improve genetic risk prediction.