Heritability jointly explained by host genotype and microbiome: will improve traits prediction?

As we observe the th anniversary of the publication by Robertson that formalized the notion of 'heritability', geneticists remain puzzled by the problem of missing/hidden heritability, where heritability estimates from genome-wide association studies (GWASs) fall short of that from twin-based studies. Many possible explanations have been offered for this discrepancy, including existence of genetic variants poorly captured by existing arrays, dominance, epistasis and unaccounted-for environmental factors; albeit these remain controversial. We believe a substantial part of this problem could be solved or better understood by incorporating the host's microbiota information in the GWAS model for heritability estimation and may also increase human traits prediction for clinical utility. This is because, despite empirical observations such as (i) the intimate role of the microbiome in many complex human phenotypes, (ii) the overlap between genetic variants associated with both microbiome attributes and complex diseases and (iii) the existence of heritable bacterial taxa, current GWAS models for heritability estimate do not take into account the contributory role of the microbiome. Furthermore, heritability estimate from twin-based studies does not discern microbiome component of the observed total phenotypic variance. Here, we summarize the concept of heritability in GWAS and microbiome-wide association studies, focusing on its estimation, from a statistical genetics perspective. We then discuss a possible statistical method to incorporate the microbiome in the estimation of heritability in host GWAS.

Automated summary

Geneticists are puzzled by the problem of missing/hidden heritability, and propose that incorporating host microbiota information into GWAS models could offer a solution. Current GWAS models do not take into account the contributory role of the microbiome in heritability estimate, despite empirical observations indicating its relevance in complex human phenotypes.