MendelVar: gene prioritization at GWAS loci using phenotypic enrichment of Mendelian disease genes

Abstract

Gene prioritisation at GWAS loci necessities careful assembly and examination of different types of molecular evidence to arrive at a set of plausible candidates. In many human traits, common small-effect mutations may subtly dysregulate the function of the very same genes which are impacted by rare, large-effect mutations causing Mendelian disease of similar phenotype. However, information on gene-Mendelian disease associations, rare pathogenic mutations driving the disease, and the disease phenotype ontology is dispersed across many data sources and does not integrate easily with enrichment analysis.MendelVar is a new webserver facilitating transfer of knowledge from Mendelian disease research into interpretation of genetic associations from GWAS of complex traits.MendelVar allows querying of pre-defined or LD-determined genomic intervals against a comprehensive integrated database to find overlap with genes linked to Mendelian disease. Next, MendelVar looks for enrichment of any Human Phenotype Ontology, DiseaseOntology and other ontology/pathway terms associated with identified Mendelian genes. In addition, MendelVar provides a list of all overlapping pathogenic and likely pathogenic variants for Mendelian disease sourced from ClinVar. Inclusion of information obtained from MendelVar in post-GWAS gene annotation pipelinescan strengthen the case for causal importance of some genes. Moreover, as genes with Mendelian disease evidence may make for more successful drug targets, this may be particularly useful in drug discovery pipelines. Taking GWAS summary statistics for malepattern baldness, intelligence and atopic dermatitis, we demonstrate the use of MendelVar in prioritizing candidate genes at these loci which are linked to relevant enriched ontology terms. MendelVar is freely available at https

Genome-wide association studies identify 137 loci for DNA methylation biomarkers of ageing

“…In order to characterise the potential overlap of Mendelian disease genes and associated pathways with our findings, a series of enrichment analyses were conducted (Methods) [31].…”

“…The potential role of Mendelian disease genes and associated pathways in influencing the epigenetic clock was investigated with MendelVar [31], independently for each marker phenotype. We did not limit our analysis to any particular phenotype class amongst the Mendelian disease genes but looked for enrichment of any disease processes found to be strongly linked to genes in the GWAS loci.…”

The Musculoskeletal Knowledge Portal: Making Omics Data Useful to the Broader Scientific Community

“…( 36 ) Data from these valuable resources will be added to the MSK‐KP in the coming year. Leveraging other functional databases: Databases from the Zebrafish Information Network (ZFIN), ( 44 ) Online Mendelian Inheritance in Man (OMIM), ( 45 ) and International Skeletal Dysplasia Society Nosology of Skeletal Disorders ( 46 ) can also be mined to identify candidate genes, that when knocked out, result in musculoskeletal disease. ( 47 ) Candidate genes can be further analyzed using gene set enrichment analysis ( 38 ) to identify genes that cluster with defined anabolic signaling pathways that may be of therapeutic relevance.…”

Linking common and rare disease genetics through gene regulatory networks

“…Over the years, many pathway-enrichment methods have been developed that can identify which biological pathways are enriched for common diseases [8][9][10] as well as highlighting their most likely cellular context(s) 11,12 . In addition, several methods can prioritize individual genes within GWAS susceptibility loci by studying how they are functionally related to genes in other susceptibility loci 8,[13][14][15][16] . However, these methods confine themselves to genes in GWAS loci, potentially missing relevant trans-regulated upor downstream effects.…”