Post-GWAS knowledge gap: the how, where, and when

Abstract

Genetic risk for complex diseases very rarely reflects only Mendelian-inherited phenotypes where single-gene mutations can be followed in families by linkage analysis. More commonly, a large set of low-penetrance, small effect-size variants combine to confer risk; they are normally revealed in genome-wide association studies (GWAS), which compare large population groups. Whereas Mendelian inheritance points toward disease mechanisms arising from the mutated genes, in the case of GWAS signals, the effector proteins and even general risk mechanism are mostly unknown. Instead, the utility of GWAS currently lies primarily in predictive and diagnostic information. Although an amazing body of GWAS-based knowledge now exists, we advocate for more funding towards the exploration of the fundamental biology in post-GWAS studies; this research will bring us closer to causality and risk gene identification. Using Parkinson's Disease as an example, we ask, how, where, and when do risk loci contribute to disease?

Keywords: Genomics; Neurological disorders.

Fig. 1. The research gap between familial and GWAS Parkinson’s genes.

As a proxy for research effort, PubMed was queried for publications that include the words, “Parkinson’s” or “neurodegeneration” and the standard gene abbreviation (protein and full names were ignored) in the title or abstract. The total number of studies was divided by the number of years since the gene was first formally linked to PD. The most recent PD meta-analysis reported relevant genes based on multiple criteria, those which are both nearest to the risk signal and supported by mendelian randomization. eQTL data are listed as “GWAS nearest & nominated”, the remainder as “GWAS other”. Genes which were reported in the 2012, 2014, or 2017 but not in the 2019 PD meta-analysis are titled “Previous GWAS”. Mean, 25th, and 75th percentiles are shown.