4 posts tagged with "OpenGWAS"

Genome-wide association studies have mapped thousands of genetic associations, but interpreting what those associations mean biologically remains a central challenge. In a new medRxiv preprint, Andrew Elmore, Aimee Hanson, Genevieve Leyden and colleagues introduce the Human Genotype-Phenotype Map (GPMap), an open resource for tracing shared genetic signals across complex traits and molecular measurements.

Figure: GPMap processing pipeline, from GWAS summary statistics through imputation, fine-mapping, colocalisation and views by trait, gene, variant and tissue. Source: Elmore et al., medRxiv, 2026, Fig. 1 (CC BY-ND 4.0).

Side‑effects are one of the main reasons people stop taking antipsychotic medicines — even when the drugs are helping with symptoms. But when someone reports “I’ve gained weight” or “my blood pressure has changed”, it’s often hard to know whether the drug truly caused it, which biological target is responsible, and whether that target is the one we wanted to hit in the first place.

In work led by Andrew Elmore, published in PLOS Genetics, we combine pharmacology (what receptors a drug binds) with human genetics (natural experiments) to map side‑effects back to specific receptors.

The IEU GWAS Database​

The MRC Integrative Epidemiology Unit (MRC IEU) at the University of Bristol hosts the IEU GWAS Database, one of the world’s largest open collections of Genome Wide Associate Study data. As of April 2019, the database contains over 250 billion genetic association records from more than 20,000 analysis of human traits.

Previously we had successfully run GWAS on almost all of the UKBiobank traits (https://ieup4.blogs.bristol.ac.uk/2018/10/01/ukb_gwas/). Our next job was to make these searchable at scale. This post explains how we have done this and how you can access the data.