Our new paper is out! We revisit the genetic architecture of Alzheimer´s disease (AD) and introduce a novel meta-analytic method for the integration of direct and proxy genome-wide association studies using family history of disease. journals.plos.org/plosgenetics/a… 1/10

Recent meta-analyses combining direct case-control GWAS and GWAS of family history of disease (GWAX) indicate very low common variant SNP heritability of AD compared to twin-based heritability estimates. 2/10

Scrutinizing common approaches for estimating SNP heritability from GWAX we found dramatic downwardly biased estimates of SNP heritability, and we introduce a novel multivariate method to recover unbiased estimates of heritability and individual SNP effects 3/10

Via simulation we show that our method outperforms conventional meta-analytic approaches combining GWAS and GWAX summary data for the recovery of SNP heritability and individual SNP effects across a range of conditions. 4/10

We apply our method to investigate the genetic architecture of AD using GWAX from UK Biobank and direct case-control GWAS from the IGAP and estimate the liability scale common variant SNP heritability of Clinical AD outside of APOE region at ~7–11%. 5/10

Using prevalence rates from epidemiological and molecular imaging data we project that common variants distributed outside of the APOE region may account for approximately 23% of variation in liability for AD pathology. 6/10

Our local analysis of heritability estimates that ~90% of common variant SNP heritability of AD exists outside the APOE region, indicating a continuous accumulation of heritability across the genome with a pronounced discontinuity at the APOE locus. 7/10

Altogether our results suggest the genetic risk of AD is characterized by core pathways (APOE) superimposed upon a diffuse but highly polygenic background that accumulates continuously across the entirety of the genome. 8/10

Our novel multivariate method is implemented in Genomic SEM. A tutorial for the method can be found here: github.com/GenomicSEM/Gen…. I will be happy to provide guidance to anyone interested in applying the method 9/10

Huge thanks to the amazing team that made this study possible @Andrew_Grotz riccardomarioni @michelnivard Elliot Tucker-Drob 10/10