The genetics of type 2 diabetes: what have we learned from GWAS?

Abstract

Type 2 diabetes mellitus has been at the forefront of human diseases and phenotypes studied by new genetic analyses. Thanks to genome-wide association studies, we have made substantial progress in elucidating the genetic basis of type 2 diabetes. This review summarizes the concept, history, and recent discoveries produced by genome-wide association studies for type 2 diabetes and glycemic traits, with a focus on the key notions we have gleaned from these efforts. Genome-wide association findings have illustrated novel pathways, pointed toward fundamental biology, confirmed prior epidemiological observations, drawn attention to the role of β-cell dysfunction in type 2 diabetes, explained ~10% of disease heritability, tempered our expectations with regard to their use in clinical prediction, and provided possible targets for pharmacotherapy and pharmacogenetic clinical trials. We can apply these lessons to future investigation so as to improve our understanding of the genetic basis of type 2 diabetes.

Figure 1. Frequency of genetic variation and disease susceptibility

Figure adapted from references , A portion of “missing heritability” may be explained by low frequency variants with intermediate penetrance. The low risk-allele frequencies make the variants undetectable by current GWAS arrays. Resequencing technology and new-generation arrays may help identify these low-frequency variants; larger sample sizes may be needed to detect significant signals. The effort can be further strengthened by applying prior biological and epidemiological data to select associations.

Figure 2. Schematic of a typical GWAS design

The general design of GWAS starts with a stage 1 (discovery) cohort. The top SNPs are promoted to the stage 2 (replication) cohort based on 1) a significance threshold that is usually dictated by pragmatic considerations, 2) whether there is prior knowledge of association between the disease the variant, and 3) whether an association is biologically plausible. The successfully replicated SNPs are meta-analyzed in the combined stage 1 and stage 2 cohorts. The SNPs that reach levels of genome-wide significance (P=5×10⁻⁸) are explored further using the functional analysis techniques listed.

Figure 3. Quantile-Quantile Plots for HOMA-B and HOMA-IR in a large meta-analysis

Figure adapted from reference. The quantile-quantile (QQ) plot illustrates the observed P values in the distribution versus those that were expected under the null hypothesis of no association. The null distribution is depicted by the red diagonal line. The entire distribution of P values is in black, the exclusion of the ten newly discovered loci (DGKB-TMEM195, ADCY5, MADD, ADRA2A, FADS1, CRY2, SLC2A2, GLIS3, PROX1, C2CD4B) in green, and the exclusion of the four genome-wide significant fasting glucose-associated loci reported previously (GCK, GCKR, G6PC2 and MTNR1B) in blue. The HOMA-B P values have a larger deviation from expected compared to HOMA-IR and therefore genetic associations with HOMA-B are more likely to be detected than with HOMA-IR.