Evaluating human genetic support for hypothesized metabolic disease genes

Abstract

We investigate the extent to which human genetic data are incorporated into studies that hypothesize novel links between genes and metabolic disease. To lower the barriers to using genetic data, we present an approach to enable researchers to evaluate human genetic support for experimentally determined hypotheses.

Figure 1.. Human Genetic Evidence (HuGE) guidelines.

To use our proposed HuGE guidelines to evaluate genetic support for a gene, we independently evaluate evidence from common variant associations (leftmost column) and rare variant gene-level associations (bottom row). Evidence from common variant associations, which can be obtained from any one of several public resources described in the main text, falls into one of five tiers. The lowest tier (“No evidence”) applies to genes not within 100kb of a genome-wide significant (p<5×10⁻⁸) association. If a gene is within 100kb of an association, we then identify the strongest association (i.e. with the lowest p-value) in the region and use it to determine the tier: “Causal coding variant” applies to genes that harbor a coding variant with the strongest association in the region, “Nearest gene” applies to genes that are the closest among genes in the region to the strongest association, “Coding variant” applies to genes that harbor a coding variant that does not have the strongest association, and “GWAS locus” applies to all other genes within 100kb of an association. The “GWAS locus” tier assumes that seven genes lie within 100kb of the association (the average value across the genome); for loci with more or fewer genes near the association, the support could be more accurately calculated according to the actual number of genes near the association. Evidence from rare variant gene-level associations, also available from multiple public resources, falls into one of five tiers determined by the association p-value: “Exome-wide” (p<2.5×10⁻⁶), “Strong” (p<1×10⁻³), “Nominal” (p<0.05), “Weak” (p<0.1), and “No evidence” (p>0.1). We combine the two sources of evidence to yield the values in the cell corresponding to the relevant row and column. The cells show qualitative descriptions of evidence strength and the estimated probability (rounded to nearest 5%) that the gene is involved in disease under conservative (no supporting experimental evidence, left of bar) and optimistic (supporting experimental evidence, right of bar) scenarios. Both the qualitative and the quantitative values follow by applying rules from Bayesian statistics together with literature estimates of evidence strength as described in the main text. Further information regarding these derivations is available on the common metabolic diseases knowledge portal (CMDKP). Document S1 includes step-by-step instructions for using the CMDKP or other public resources to evaluate HuGE scores, and an automated tool implementing them for 341 common metabolic diseases can be found on the CMDKP (https://hugeamp.org/hugecalculator.html).