ESPE Yearbook of Paediatric Endocrinology

Brief summary: Using data on 4964 type 1 diabetes (T1D) cases and 7497 controls, this study assessed whether the effect of common genetic variants (SNPs) on risk of T1D is mediated through trans-effects on the expression of core genes. Nine putative core genes were identified, all implicated in immune system regulation. In addition, four T1D-associated genomic regions were identified as master regulators that have trans-effects on gene expression.

The ‘omnigenic’ model has been proposed as a framework to understand the polygenic architecture of complex traits revealed by genome-wide association studies (GWAS) (1).

This hypothesis postulates that the polygenic effects of common SNPs trait are mediated through weak trans-effects (i.e. effects on other distant genomic locations) on the expression of a relatively sparse set of effector (‘core’) genes, which in turn have a direct effect on the outcome complex disease or trait. In the context of T1D, previous genetic studies have mainly focused on the impact of common variants (SNPs) on genes located nearby, known as cis-effects.

These authors tested whether the ‘omnigenic’ hypothesis applies to T1D, using a large case-control dataset including people with T1D from the Scottish Diabetes Research Network Type 1 Bioresource and individuals without diabetes from the Generation Scotland study. Published T1D GWAS summary statistics were used to calculate aggregated (excluding the HLA region) trans-scores for gene expression in blood. This identified nine candidate genes as putative core genes for T1D: seven of them are involved in the induction and activity of T regulatory cells (FOXP3, CTLA4, STAT1, CD247, IL10RA, MEOX1, CD5) and two (CD1E, LGALS3BP) are involved in the innate and acquired immune response to lipids. Of note, most of these genes were not detected by the conventional T1D GWAS analysis.

These findings support a new genetic analytical approach to identify the genetic drivers of T1D susceptibility and it could be applied also to other diseases. As the authors discuss, replication of the results is needed and a wider application of this approach will require availability of more comprehensive summary-level results from large GWAS of gene expression in various tissues as well as measurements of genetic effects on splicing variants and post-transcriptional modifications.

References: 1. Boyle EA, Li YI, Pritchard JK. An expanded view of complex traits: From polygenic to omnigenic. Cell. 2017;169(7):1177–1186.