Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference.

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings

Improving genomic diagnosis of rare pediatric disease in the UK and Ireland

This is the author accepted manuscriptBackground: Pediatric disorders include a range of highly penetrant, genetically heterogeneous conditions amenable to genome-wide diagnostic approaches. Finding a molecular diagnosis is challenging but can have lifelong benefits. Methods: The Deciphering Developmental Disorders (DDD) study recruited >13,500 families with severe, likely monogenic, difficult-to-diagnose developmental disorders from 24 regional genetics services around the UK and Ireland. We collected standardised phenotype data and performed exome sequencing and microarray analysis to investigate novel genetic causes. We developed an iterative variant analysis pipeline, reporting candidate variants to clinical teams for validation, diagnostic interpretation and communication to families. We performed multiple regression analyses evaluating factors affecting probability of diagnosis. Results: We reported ~1 candidate variant per parent-offspring trio and ~2.5 variants per singleton proband. Using clinical and computational approaches to variant classification, we achieved a diagnosis in ~41% (5502 probands), of whom ~76% have a pathogenic de novo variant. Another ~22% have variants of uncertain significance in genes robustly linked with monogenic developmental disorders. Recruitment as a parent-offspring trio had the largest impact on chance of diagnosis (OR=4.70). Probands who were extremely premature (OR=0.39), had in-utero exposure to antiepileptic medications (OR=0.44), or whose mothers had diabetes (OR=0.52) were less likely to be diagnosed, as were those of African ancestry (OR=0.51). Conclusions: The DDD study shows multimodal analysis of genome-wide data has good diagnostic power, even after prior attempts at diagnosis.Health Innovation Challenge FundWellcome Sanger InstituteWellcome Trus