AbstractBackgroundCase‐control genome‐wide association studies (GWAS) have identified loci associated with risk for Alzheimer disease (AD), but they require very large sample sizes and identify variants with small effect sizes. GWAS of informative endophenotypes for disease have more power to identify novel variants and provide information about biological mechanisms. By analyzing data from 1,269 individuals, we previously identified risk variants for AD that were associated with CSF levels of tau and p‐tau, including a novel variant associated with AD risk. Recent technological developments have led to new assays in plasma for Aβ, p‐tau and NFL with high predictive power. However, no GWAS have been performed using these plasma biomarkers as quantitative trait.MethodPlasma Aβ and NFL were obtained from 882 individuals from the Knight‐ADRC, plasma Aß from 160 individuals from the Human Connectome Project, and plasma Aß, NFL, tau and p‐tau from 1,694 individuals from ADNI. GWAS and sequencing data is also available from these samples. We performed linear regression to determine single nucleotide polymorphisms (SNPs) associated with these plasma AD biomarkers. SKAT‐O was used to perform gene‐based analyses including rare non‐synonymous variants. GCTA and LDSC was used to determine the proportion of biomarker variability explained by genetic variants. We used colocalization to determine if the loci associated with plasma biomarker levels are also associated with AD risk, onset or progression. Mendelian randomization and LDSC was used to determine the overlap in the genetic architecture of plasma AD biomarkers with other traits, including cardiovascular and inflammation‐related traits.ResultThis represents the largest GWAS for plasma AD biomarkers measured with the novel and more powerful assays. We found several genome‐wide significant hits, including APOE. Additional analyses are ongoing.ConclusionPrevious studies using CSF biomarker levels as quantitative traits identified novel genes implicated in AD risk, onset and progression. This current study using plasma biomarker levels as quantitative traits can be critical to identification of novel genes that impact AD and more accurate interpretation of plasma biomarker levels.