Faculty Bibliography

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE-PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of "precision medicine." The February 2015 eMERGE-PGx data release includes sequence-derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation-Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

We previously reported that tacrolimus (TAC) trough blood concentrations for African American (AA) kidney allograft recipients were lower than those observed in white patients. Subtherapeutic TAC troughs may be associated with acute rejection (AR) and AR-associated allograft failure. This variation in TAC troughs is due, in part, to differences in the frequency of the cytochrome P450 CYP3A5*3 allele (rs776746, expresses nonfunctional enzyme) between white and AA recipients; however, even after accounting for this variant, variability in AA-associated troughs is significant. We conducted a genomewide association study of TAC troughs in AA kidney allograft recipients to search for additional genetic variation. We identified two additional CYP3A5 variants in AA recipients independently associated with TAC troughs: CYP3A5*6 (rs10264272) and CYP3A5*7 (rs41303343). All three variants and clinical factors account for 53.9% of the observed variance in troughs, with 19.8% of the variance coming from demographic and clinical factors including recipient age, glomerular filtration rate, anticytomegalovirus drug use, simultaneous pancreas-kidney transplant and antibody induction. There was no evidence of common genetic variants in AA recipients significantly influencing TAC troughs aside from the CYP3A gene. These results reveal that additional and possibly rare functional variants exist that account for the additional variation.

Gallbladder disease (GBD) has an overall prevalence of 10-40% depending on factors such as age, gender, population, obesity and diabetes, and represents a major economic burden. Although gallstones are composed of cholesterol by-products and are associated with obesity, presumed causal pathways remain unproven, although BMI reduction is typically recommended. We performed genetic studies to discover candidate genes and define pathways involved in GBD. We genotyped 15,241 women of European ancestry from three cohorts, including 3216 with GBD, using the Human cardiovascular disease (HumanCVD) BeadChip containing up to ~ 53,000 single-nucleotide polymorphisms (SNPs). Effect sizes with P-values for development of GBD were generated. We identify two new loci associated with GBD, GCKR rs1260326:T>C (P = 5.88 × 10(-7), ß = -0.146) and TTC39B rs686030:C>A (P = 6.95 x 10(-7), ß = 0.271) and detect four independent SNP effects in ABCG8 rs4953023:G>A (P=7.41 × 10(-47), ß = 0.734), ABCG8 rs4299376:G(>)T (P = 2.40 × 10(-18), ß = 0.278), ABCG5 rs6544718:T>C (P = 2.08 × 10(-14), ß = 0.044) and ABCG5 rs6720173:G>C (P = 3.81 × 10(-12), ß(=)0.262) in conditional analyses taking genotypes of rs4953023:G>A as a covariate. We also delineate the risk effects among many genotypes known to influence lipids. These data, from the largest GBD genetic study to date, show that specific, mainly hepatocyte-centred, components of lipid metabolism are important to GBD risk in women. We discuss the potential pharmaceutical implications of our findings.

BACKGROUND:We investigated causal effect of completed growth, measured by adult height, on coronary heart disease (CHD), stroke and cardiovascular traits, using instrumental variable (IV) Mendelian randomization meta-analysis. METHODS:We developed an allele score based on 69 single nucleotide polymorphisms (SNPs) associated with adult height, identified by the IBCCardioChip, and used it for IV analysis against cardiovascular risk factors and events in 21 studies and 60 028 participants. IV analysis on CHD was supplemented by summary data from 180 height-SNPs from the GIANT consortium and their corresponding CHD estimates derived from CARDIoGRAMplusC4D. RESULTS:IV estimates from IBCCardioChip and GIANT-CARDIoGRAMplusC4D showed that a 6.5-cm increase in height reduced the odds of CHD by 10% [odds ratios 0.90; 95% confidence intervals (CIs): 0.78 to 1.03 and 0.85 to 0.95, respectively],which agrees with the estimate from the Emerging Risk Factors Collaboration (hazard ratio 0.93; 95% CI: 0.91 to 0.94). IV analysis revealed no association with stroke (odds ratio 0.97; 95% CI: 0.79 to 1.19). IV analysis showed that a 6.5-cm increase in height resulted in lower levels of body mass index ( P  < 0.001), triglycerides ( P  < 0.001), non high-density (non-HDL) cholesterol ( P  < 0.001), C-reactive protein ( P  = 0.042), and systolic blood pressure ( P  = 0.064) and higher levels of forced expiratory volume in 1 s and forced vital capacity ( P  < 0.001 for both). CONCLUSIONS:Taller individuals have a lower risk of CHD with potential explanations being that taller people have a better lung function and lower levels of body mass index, cholesterol and blood pressure.

BACKGROUND:Preeclampsia is a hypertensive complication of pregnancy characterized by novel onset of hypertension after 20 weeks gestation, accompanied by proteinuria. Epidemiological evidence suggests that genetic susceptibility exists for preeclampsia; however, whether preeclampsia is the result of underlying genetic risk for essential hypertension has yet to be investigated. Based on the hypertensive state that is characteristic of preeclampsia, we aimed to determine if established genetic risk scores (GRSs) for hypertension and blood pressure are associated with preeclampsia. METHODS:Subjects consisted of 162 preeclamptic cases and 108 normotensive pregnant controls, all of Iowa residence. Subjects' DNA was extracted from buccal swab samples and genotyped on the Affymetrix Genome-wide Human SNP Array 6.0 (Affymetrix, Santa Clara, CA). Missing genotypes were imputed using MaCH and Minimac software. GRSs were calculated for hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) using established genetic risk loci for each outcome. Regression analyses were performed to determine the association between GRS and risk of preeclampsia. These analyses were replicated in an independent US population of 516 cases and 1,097 controls of European ancestry. RESULTS:GRSs for hypertension, SBP, DBP, and MAP were not significantly associated with risk for preeclampsia (P > 0.189). The results of the replication analysis also yielded nonsignificant associations. CONCLUSIONS:GRSs for hypertension and blood pressure are not associated with preeclampsia, suggesting that an underlying predisposition to essential hypertension is not on the causal pathway of preeclampsia.

BACKGROUND:Anorexia nervosa (AN) is a complex psychiatric disease with a moderate to strong genetic contribution. In addition to conventional genome wide association (GWA) studies, researchers have been using machine learning methods in conjunction with genomic data to predict risk of diseases in which genetics play an important role. METHODS:In this study, we collected whole genome genotyping data on 3940 AN cases and 9266 controls from the Genetic Consortium for Anorexia Nervosa (GCAN), the Wellcome Trust Case Control Consortium 3 (WTCCC3), Price Foundation Collaborative Group and the Children's Hospital of Philadelphia (CHOP), and applied machine learning methods for predicting AN disease risk. The prediction performance is measured by area under the receiver operating characteristic curve (AUC), indicating how well the model distinguishes cases from unaffected control subjects. RESULTS:Logistic regression model with the lasso penalty technique generated an AUC of 0.693, while Support Vector Machines and Gradient Boosted Trees reached AUC's of 0.691 and 0.623, respectively. Using different sample sizes, our results suggest that larger datasets are required to optimize the machine learning models and achieve higher AUC values. CONCLUSIONS:To our knowledge, this is the first attempt to assess AN risk based on genome wide genotype level data. Future integration of genomic, environmental and family-based information is likely to improve the AN risk evaluation process, eventually benefitting AN patients and families in the clinical setting.

BACKGROUND:Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Many genetic and environmental risk factors including atherogenic dyslipidemia contribute towards the development of CAD. Functionally relevant mutations in the dyslipidemia-related genes and enzymes involved in the reverse cholesterol transport system are associated with CAD and contribute to increased susceptibility of myocardial infarction (MI). METHOD/METHODS:Blood samples from 990 angiographically confirmed Saudi CAD patients with at least one event of myocardial infarction were collected between 2012 and 2014. A total of 618 Saudi controls with no history or family history of CAD participated in the study. Four polymorphisms, rs2230806, rs2066715 (ABCA1), rs5882, and rs708272 (CETP), were genotyped using TaqMan Assay. RESULTS:CETP rs5882 (OR = 1.45, P < 0.005) and ABCA1 rs2230806 (OR = 1.42, P = 0.017) polymorphisms were associated with increased risk of CAD. However, rs708272 polymorphism showed protective effect (B1 vs. B2: OR = 0.80, P = 0.003 and B2B2 vs. B1B1: OR = 0.68, P = 0.012) while the ABCA1 variant rs2066715 was not associated. CONCLUSION/CONCLUSIONS:This study is the first to report the association of these polymorphisms with CAD in the population of the Eastern Province of Saudi Arabia. The rs5882 polymorphism (CETP) showed a significant association and therefore could be a promising marker for CAD risk estimation while the rs708272 polymorphism had a protective effect from CAD.

AIM:To find new genetic loci associated with statin response, and to investigate the association of a genetic risk score (GRS) with this outcome. PATIENTS & METHODS:In a discovery meta-analysis (five studies, 1991 individuals), we investigated the effects of approximately 50000 single nucleotide polymorphisms on statin response, following up associations with p < 1 × 10(-4) (three independent studies, 5314 individuals). We further assessed the effect of a GRS based on SNPs in ABCG2, LPA and APOE. RESULTS:No new SNPs were found associated with statin response. The GRS was associated with reduced statin response: 0.0394 mmol/l per allele (95% CI: 0.0171-0.0617, p = 5.37 × 10(-4)). CONCLUSION:The GRS was associated with statin response, but the small effect size (˜2% of the average low-density lipoprotein cholesterol reduction) limits applicability.