Local genetic covariance analysis with lipid traits identifies novel loci for early-onset Alzheimer’s Disease

The genetic component of early-onset Alzheimer disease (EOAD), accounting for ~10% of all Alzheimer’s disease (AD) cases, is largely unexplained. Recent studies suggest that EOAD may be enriched for variants acting in the lipid pathway. The current study examines the shared genetic heritability between EOAD and the lipid pathway using genome-wide multi-trait genetic covariance analyses. Summary statistics were obtained from the GWAS meta-analyses of EOAD by the Alzheimer’s Disease Genetics Consortium (n=19,668) and five blood lipid traits by the Global Lipids Genetics Consortium (n=1,320,016). The significant results were compared between the EOAD and lipids GWAS and genetic covariance analyses were performed via SUPERGNOVA. Genes in linkage disequilibrium (LD) with top EOAD hits in identified regions of covariance with lipid traits were scored and ranked for causality by combining evidence from gene-based analysis, AD-risk scores incorporating transcriptomic and proteomic evidence, eQTL data, eQTL colocalization analyses, DNA methylation data, and single-cell RNA sequencing analyses. Direct comparison of GWAS results showed 5 loci overlapping between EOAD and at least one lipid trait harboring APOE, TREM2, MS4A4E, LILRA5, and LRRC25. Local genetic covariance analyses identified 3 regions of covariance between EOAD and at least one lipid trait. Gene prioritization nominated 3 likely causative genes at these loci: ANKDD1B, CUZD1, and MS4A64.The current study identified genetic covariance between EOAD and lipids, providing further evidence of shared genetic architecture and mechanistic pathways between the two traits.Author summary: Most individuals develop Alzheimer’s disease late in life, but approximately 10% of patients develop the disease before the age of 65 – these cases are known as early-onset Alzheimer’s disease (EOAD). Relatively little is known about the genes that contribute to non-autosomal dominant EOAD, but it is believed that some contributing genetic variants may be acting in the lipid pathway. We examined the genetic correlation between EOAD and five different lipid traits (total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and triglycerides) and identified three genomic regions that showed genetic overlap between EOAD and at least one of the five lipid traits. We used a novel gene prioritization approach that combined evidence from multiple sources to nominate three specific candidate genes in these regions: ANKDD1B, CUZD1, and MS4A64, all of which have been associated with lipid-related disorders and/or Alzheimer’s disease. Identification of mechanistic pathways shared between EOAD and lipid traits provides novel insights into the underlying etiology of these disorders and informs development of improved screening, prevention, and treatment strategies.