Mark McCarthy, MD
Senior Director and Staff Scientist, Human Genetics
Genentech
Now we have 400+ Signals for Type 2 Diabetes Risk, What on Earth are we Going to Do with Them?
Individual risk of common complex diseases such as type 2 diabetes is influenced by the impact of variation at many hundreds (even thousands) of genetic risk loci, in combination with a wide range of exposures experienced over the life course. A deeper understanding of these factors, and the mechanisms through which they influence disease risk and development, is a prerequisite if we are to develop more effective strategies for prevention and treatment.
Over the past decade, there has been substantial progress along these lines. In the case of type 2 diabetes, large-scale collaborative efforts have identified almost 500 independent associations. However, merely cataloguing the location of these signals along the genome is a sterile exercise, unless these discoveries can be used to stimulate biological discovery and translational opportunity.
By intersecting genetic data with epigenomic data from relevant cell types and tissues, we now know, for a growing number of these signals: which specific genetic variant is responsible; which regulatory element active is disturbed, and in which tissue or cell type; which downstream effector gene mediates the causal effect; and which pathophysiological process is consequently perturbed. Over 100 genes at these loci (and their encoded proteins) have been implicated in type 2 diabetes pathogenesis (with varying degrees of confidence) through a combination of genetic, genomic and molecular approaches, and it is becoming possible to use these to define networks and pathways mediating predisposition. Each of these provides an opportunity to identify novel points for therapeutic intervention.
These studies have provided a clear description of the genetic architecture of the disease, and a sound framework for thinking about risk stratification, target validation and biomarker discovery. There have been successes in using genetics to highlight which of the many claimed associations with potentially modifiable environmental exposures are directly causal, and therefore might represent promising avenues for preventative intervention. In the years to come, we will see ever-wider application of polygenic risk scores to improve individual prediction of diabetes risk, and to capture clinical and phenotypic heterogeneity within type 2 diabetes that influences clinically-relevant outcomes such as complication risk and therapeutic response.
