Missing heritability of common diseases and treatments outside the protein-coding exome

Abstract

Genetic factors strongly influence risk of common human diseases and treatment outcomes but the causative variants remain largely unknown; this gap has been called the ‘missing heritability’. We propose several hypotheses that in combination have the potential to narrow the gap. First, given a multi-stage path from wellness to disease, we propose that common variants under positive evolutionary selection represent normal variation and gate the transition between wellness and an ‘off-well’ state, revealing adaptations to changing environmental conditions. In contrast, genome-wide association studies (GWAS) focus on deleterious variants conveying disease risk, accelerating the path from off-well to illness and finally specific diseases, while common ‘normal’ variants remain hidden in the noise. Second, epistasis (dynamic gene-gene interactions) likely assumes a central role in adaptations and evolution; yet, GWAS analyses currently are poorly designed to reveal epistasis. As gene regulation is germane to adaptation, we propose that epistasis among common normal regulatory variants, or between common variants and less frequent deleterious variants, can have strong protective or deleterious phenotypic effects. These gene-gene interactions can be highly sensitive to environmental stimuli and could account for large differences in drug response between individuals. Residing largely outside the protein-coding exome, common regulatory variants affect either transcription of coding and non-coding RNAs (regulatory SNPs, or rSNPs) or RNA functions and processing (structural RNA SNPs, or srSNPs). Third, with the vast majority of causative variants yet to be discovered, GWAS rely on surrogate markers, a confounding factor aggravated by the presence of more than one causative variant per gene and by epistasis. We propose that the confluence of these factors may be responsible to large extent for the observed heritability gap.

A review of genome-wide association studies for multiple sclerosis: classical and hypothesis-driven approaches

“…At that, HLA-DRB1*15:01 alone explains about 20 % of heritability (Lill 2014). There are several explanations of this "missing heritability" (Manolio et al 2009;Sadee et al 2014) in complex diseases, of which MS is a typical example.…”

“…However, we apparently are at the initial stage of this process. Recent estimations based on sibling studies (Sadee et al 2014) suggest that the MS risk loci identified to date explain only about 27 % of its total heritability (Lill 2014). At that, HLA-DRB1*15:01 alone explains about 20 % of heritability (Lill 2014).…”

“…It is useful to keep in mind when interpreting GWAS results that many adaptive frequent variations, remaining in the noise of GWAS results, are in gene-gene interactions and can turn deleterious under unfavorable conditions (Sadee et al 2014). Recently, novel approaches to GWAS analysis have been proposed.…”

Resolving the etiology of atopic disorders by using genetic analysis of racial ancestry

“…186 One source of this “missing heritability” (discrepancy between the predicted and observed genetic risk) could be rare or structural variants that contribute to disease risk but were not covered in early GWAS (newer GWAS platforms have a greater representation of these variants). Another reason for missing heritability could be gene-gene and gene-environment interactions.…”

Genetic Variation Determines PPARγ Function and Anti-diabetic Drug Response In Vivo

“…Current genome-wide association studies (GWAS) reveal a large gap between known causal genes and the observed heritability of common diseases and treatment outcomes (Sadee et al, 2014). Another limitation of GWAS is that each locus nominates a large group of SNPs in linkage disequilibrium, such that causal and neutral variants cannot easily be distinguished.…”