Pharmacogenetic Perturbations in Humans as a Tool to Generate Mechanistic Insight

  1. Jose C. Florez
  1. Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts
  2. Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
  3. Department of Medicine, Harvard Medical School, Boston, Massachusetts
  1. Corresponding author: Jose C. Florez, jcflorez{at}partners.org.

The field of human genetics has witnessed tremendous acceleration in the last decade, driven in part by the advent of genome-wide association studies (GWAS) (1,2). However, novel insights have not kept pace. In most cases, the specific DNA sequences that cause the molecular changes leading to type 2 diabetes (T2D) have not been identified, and robust signals of association are often initially opaque with regard to a plausible functional mechanism (3,4). Thus, although GWAS constitute a powerful approach to rapidly and systematically uncover associations that may open new windows into T2D pathophysiology, they do not circumvent the need to refine the associated loci to find the precise “causal” DNA sequences—causal in the sense that altering these sequences would eliminate the clinical phenotype (5,6).

We therefore need complementary strategies that both identify the genes of interest within each associated region and illuminate their function. The integration of physiological and pharmacogenetic information with genetic discoveries can provide such a path. By perturbing a live human with a drug that targets a given gene and assessing the response to this perturbation, one may be able to “close the loop” and demonstrate that the gene is indeed involved in producing the phenotype of interest. In a reciprocal fashion, drugs that modulate a specific limb of the glucose homeostatic system (e.g., insulin secretion, central or peripheral insulin sensitivity), if shown to elicit differential responses depending on genotype, may serve to prioritize genes in a given associated region.

The article by ‘t Hart et al. (7) in this issue illustrates this approach. The authors used the Metabochip to identify genetic variants that influence glucagon-like peptide-1 (GLP-1)–induced insulin secretion in 232 nondiabetic participants from two separate Dutch and German cohorts who were treated with a hyperglycemic clamp. The Metabochip is …

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