Loss-of-function CYP2C9 variants: finding the correct clinical role for Type 2 diabetes pharmacogenetic testing

eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants

BACKGROUND

We explored premature stop-gain variants to test the hypothesis that variants, which are likely to have a consequence on protein structure and function, will reveal important insights with respect to the phenotypes associated with them. We performed a phenome-wide association study (PheWAS) exploring the association between a selected list of functional stop-gain genetic variants (variation resulting in truncated proteins or in nonsense-mediated decay) and an extensive group of diagnoses to identify novel associations and uncover potential pleiotropy.

RESULTS

In this study, we selected 25 stop-gain variants: 5 stop-gain variants with previously reported phenotypic associations, and a set of 20 putative stop-gain variants identified using dbSNP. For the PheWAS, we used data from the electronic MEdical Records and GEnomics (eMERGE) Network across 9 sites with a total of 41,057 unrelated patients. We divided all these samples into two datasets by equal proportion of eMERGE site, sex, race, and genotyping platform. We calculated single effect associations between these 25 stop-gain variants and ICD-9 defined case-control diagnoses. We also performed stratified analyses for samples of European and African ancestry. Associations were adjusted for sex, site, genotyping platform and the first three principal components to account for global ancestry. We identified previously known associations, such as variants in LPL associated with hyperglyceridemia indicating that our approach was robust. We also found a total of three significant associations with p < 0.01 in both datasets, with the most significant replicating result being LPL SNP rs328 and ICD-9 code 272.1 "Disorder of Lipoid metabolism" (pdiscovery = 2.59x10-6, preplicating = 2.7x10-4). The other two significant replicated associations identified by this study are: variant rs1137617 in KCNH2 gene associated with ICD-9 code category 244 "Acquired Hypothyroidism" (pdiscovery = 5.31x103, preplicating = 1.15x10-3) and variant rs12060879 in DPT gene associated with ICD-9 code category 996 "Complications peculiar to certain specified procedures" (pdiscovery = 8.65x103, preplicating = 4.16x10-3).

CONCLUSION

In conclusion, this PheWAS revealed novel associations of stop-gained variants with interesting phenotypes (ICD-9 codes) along with pleiotropic effects.

Investigating the Role of Plasma Glucose Concentration as a Phenotypic Marker for CYP2C9 Genetic Variants, in the Diabetic Population of Gujarat

The present study was aimed to investigate the role of plasma glucose concentration as a phenotypic marker and to study the frequency distribution of CYP2C9 genetic variants in Gujarat state diabetic population. One hundred and nine unrelated diabetes mellitus patients treated with sulfonylureas were genotyped for CYP2C9*2 and CYP2C9*3 alleles. Their pre- and posttreatment postprandial blood glucose levels were recorded and mean glucose drop per milligram of drug values were calculated and further used as an index for phenotypic correlation. The frequencies of CYP2C9*1, CYP2C9*2 and CYP2C9*3 alleles in the Gujarat state diabetic population were 0.84, 0.07 and 0.09, respectively. The distribution of CYP2C9*1/*1, CYP2C9*1/*2, CYP2C9*1/*3, CYP2C9*2/*2, CYP2C9*2/*3 and CYP2C9*3/*3 genotypes were 0.73, 0.08, 0.13, 0.0, 0.06 and 0.0, respectively. Patients with CYP2C9*1/*2 genotype did not show any significant difference in the mean glucose drop per milligram of drug values when compared with wild-type patients in glipizide-treatment group. Patients with CYP2C9*1/*3 genotype showed greater mean glucose drop per milligram of drug values than patients with CYP2C9*1/*1 wild-type genotype for both glipizide and glimepiride while patients with CYP2C9*2/*3 genotype showed greater drop than patients with CYP2C9*1/*1 genotype only in the glipizide-treatment group. The presence of CYP2C9*3 allele significantly affected plasma glucose drop per milligram of drug values in patients taking glipizide and glimepiride, while effects of CYP2C9*2 allele were insignificant. Further studies are needed to confirm the effects of CYP2C9*2 allele on plasma glucose drop per milligram of drug values. However, plasma glucose concentration is a complex physiological marker that cannot be used to establish perfect genotype-phenotype correlation. Hence studies exploring robust phenotypic markers must be initiated.