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Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with complex traits and diseases. However, elucidating the causal genes underlying GWAS hits remains challenging. We applied the summary data-based Mendelian randomization (SMR) method to 28 GWAS summary datasets to identify genes whose expression levels were associated with traits and diseases due to pleiotropy or causality (the expression level of a gene and the trait are affected by the same causal variant at a locus). We identified 71 genes, of which 17 are novel associations (no GWAS hit within 1 Mb distance of the genes). We integrated all the results in an online database ( http://www.cnsgenomics/shiny/SMRdb/ ), providing important resources to prioritize genes for further follow-up, for example in functional studies.

Original publication




Journal article


Genome Med

Publication Date





Complex traits, Expression quantitative trait loci (eQTL), Genome-wide association studies (GWAS), Summary data-based Mendelian randomization (SMR), Alzheimer Disease, Autism Spectrum Disorder, Coronary Artery Disease, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Inflammatory Bowel Diseases, Models, Statistical, Phenotype, Quantitative Trait Loci, Quantitative Trait, Heritable