epistasis

Sackton TB & Hartl DL 2016 Genotypic context and epistasis in individuals and populations. Cell 166:279-287.

• in human genetics, direct studies are rarely possible
• inferences about physiological epistasis instead rely on estimates of statistical epistasis in populations
• this is problematical
• the failure to detect statistical epistasis does not imply that physiological epistasis is absent or unimportant

• physiological epistasis is likely to be pervasive
• this inference is often misleading when extrapolated to statistical epistasis
• there is an asymmetry in their implications
• high levels of statistical epistasis always imply substantial physiological epistasis
• physiological epistasis can be pervasive and still result in negligible levels of statistical epistasis

• in their contribution to the genetic variance, many of the effects of physiological epistasis are allocated to the additive and dominance components of variation and do not contribute to statistical epistasis

• does statistical epistasis account for missing ("phantom") heritability?
• why does it matter whether statistical epistasis is or is not a significant part of the genetic variance?
• it matters because of the assumption that tracing the sources of genetic variation will reveal metabolic and regulatory networks for complex diseases to improve disease risk prediction and also highlight new drug targets for prevention or therapeutic intervention
• for most complex diseases, the genetic risk factors result in a modest (10%–50%) increase in risk
• in the aggregate they account for only part (typically <50%) of the phenotypic variation attributable to the additive effects of genes
• the top 40 gene contributing to variation in adult human height account for <10% of the heritability
• a total of 697 genetic factors with statistically significant effects on adult height explain only ~20% the heritability

• among the hypotheses put forward to account for the missing heritability are
• lack of sufficiently powerful statistical methods to detect causal variants
• common variants with effects too small to detect with typical sample sizes
• rare variants with large effects
• dominance
• physiological epistasis
• tandem repeat polymorphisms
• epigenetic effects

• when all genetic factors are taken into account, including those whose effects do not reach statistical significance, then a high proportion of the heritability for complex traits and diseases can be explained
• hundreds or thousands of genetic factors of small effect might therefore contribute to complex traits and diseases
• Yang and colleagues (2015) used genetic relationship matrices stratified by minor allele frequency and linkage disequilibrium to impute about 17 million causal variants affecting adult height and body mass index among 44,126 unrelated individuals
• taking into account the likely overestimate of heritability based on family studies, the imputed genetic factors accounted for 80%–90% of heritability for adult height and 70%–90% of heritability for body mass index
• some 25%–50% of the genetic variation in these traits could be attributed to common variants