Cathy Schaefer

The NIH Pharmacogenetics Research Network (PGRN) is a collaborative group of investigators with a wide range of research interests, but all attempting to correlate drug response with genetic variation. Several research groups concentrate on drugs used to treat specific medical disorders (asthma, depression, cardiovascular disease, addiction of nicotine, and cancer), whereas others are focused on specific groups of proteins that interact with drugs (membrane transporters and phase II drug-metabolizing enzymes). The diverse scientific information is stored and annotated in a publicly accessible knowledge base, the Pharmacogenetics and Pharmacogenomics Knowledge base (PharmGKB). This report highlights selected achievements and scientific approaches as well as hypotheses about future directions of each of the groups within the PGRN. Seven major topics are included: informatics (PharmGKB), cardiovascular, pulmonary, addiction, cancer, transport, and metabolism.

This study examined the relation between maternal prepregnant body mass index (BMI) and development of schizophrenia and schizophrenia spectrum disorders in adult offspring from the Prenatal Determinants of Schizophrenia Study. The study drew on a previously studied cohort of births occurring between 1959 and 1967 to women enrolled in a prepaid health plan. Computerized treatment registries were used to identify possible cases of schizophrenia and spectrum disorders in adult offspring belonging to the health plan from 1981 to 1997. Diagnostic interviews and medical record reviews resulted in diagnosis of 63 cases of schizophrenia and spectrum disorders; these cases and 6,570 unrelated and unaffected cohort members whose mothers also had prepregnancy measures of BMI comprised the sample for analyses. High (> or = 30.0), compared with average (20.0-26.9), maternal prepregnant BMI (kg/m2) was significantly associated with schizophrenia and spectrum disorders in the adult offspring (relative risk [RR] = 2.9; 95% confidence interval [CI] 1.3-6.6), independently of maternal age, parity, race, education, or cigarette smoking during pregnancy. Low (< or = 19.9) maternal BMI was not associated with schizophrenia and spectrum disorders (RR = 1.2; 95% CI 0.64-2.2). Future studies of this cohort will examine factors that may help explain the relationship of high maternal prepregnant BMI with schizophrenia, including nutritional and metabolic factors, toxic exposures, and obstetrical complications.

Objective: We conducted the first GWAS in pediatric MS and tested previously established adult MS-associated candidate genes for association. Background: Up to 10[percnt] of MS patients have symptoms before age 18 (i.e. pediatric-onset MS). Similar to adults, both genetic and environmental risk factors have been implicated. In addition to HLA-DRB1*15:01, results from GWAS in adults with MS have identified ~110 non-MHC MS variants. Methods: All subjects had whole genome profiles (Illumina or Affymetrix chips). Genotype imputation and very rigorous quality control criteria were applied. SHAPEIT2 for phasing was followed by IMPUTE2 (1000 Genomes Phase 3 integrated variant set, October, 2014). Each individual was characterized for genetic ancestry using MDS (PLINK) and STRUCTURE analysis; cases and controls were closely matched on genetic ancestry. Results: We assembled samples from 732 MS cases with onset <18 years (70[percnt] female, mean age of onset 13.9 (+/- 3.5) years, 46[percnt] non-white) and 27,187 controls for genetic studies. Results from whites-only analysis (394 cases, 10,875 controls) showed HLA-DRB1*1501 was strongly associated with MS (OR=2.62, 95[percnt] CI: 2.23-3.07, p=2.1x10-32). Further, 36 of 110 non-MHC SNPs (33[percnt]) were significant (p<0.05); rs2744148 (chr 16), rs3007421 (chr 1) and rs1800693 (chr 12) demonstrated strongest evidence of association with pediatric MS, with larger effects compared to adults: OR=2.94, 95[percnt] CI: 2.41-3.57, p=5.2 x10-27; OR=2.46, 95[percnt] CI: 2.02-2.98, p=3.0 x 10-19; and OR=1.74, 95[percnt] CI: 1.51-2.01, p=4.7 x 10-14, respectively. A weighted genetic risk score (wGRS, 110 variants) was strongly associated with pediatric MS (2.0 x 10-16). Results from GWAS showed at least three genomic regions harbored SNPs with p<10-7. Fine mapping and trans-ethnic meta-analyses are underway. Conclusions: Variants within genes involved in adult MS are also risk factors in children and suggest that similar biological processes are present in both groups. Genetic effects may be stronger in pediatric MS overall.

Objective:We utilized Mendelian randomization to estimate the causal relationship between increasing body mass index (BMI) and pediatric MS susceptibility using a weighted BMI genetic risk score (BMI GRS). Background:Childhood and adolescent obesity are associated with a two-fold increased risk of pediatric and adult-onset MS. However, the relationship between obesity and MS may be confounded by lifestyle and/or socioeconomic factors that have not been appropriately adjusted for in previous studies. Methods:The BMI GRS incorporates the cumulative effect of 97 variants associated with BMI identified from the largest genome-wide association study (GWAS), to date (Locke et al, 2015). A split-sample instrumental variable (IV) analysis was used by summing all risk alleles multiplied by the estimated effect of each risk allele on the phenotype derived from the GWAS. Participants included non-Hispanic white pediatric MS cases and controls from over 15 sites across the U.S. (total sample size: 394 MS cases, 10,875 controls). Results:A significant association between BMI GRS and pediatric MS was demonstrated (causal odds ratio [OR] = 1.20, 95[percnt] CI 1.06, 1.36; p=0.004) after adjusting for sex, ancestry, HLA-DRB1*15:01 (the strongest genetic predictor of MS) and a weighted genetic risk score comprised of 110 non-HLA MS risk variants. Evidence of interaction between BMI GRS and HLA-DRB1*15:01 was also present (p-interaction=0.04); individuals carrying 1-2 DRB1* 15:01 risk alleles demonstrated a stronger association (OR=1.39, 95[percnt] CI 1.16, 1.37) compared to non-carriers (OR=1.05, 95[percnt] CI 0.88, 1.26). Conclusions:For the first time, we provide evidence supporting increased BMI is causally associated with pediatric MS and interacts with HLA-DRB1*15:01 status. Further, pediatric MS risk conferred by obesity may involve predisposing genetic factors for increased BMI, suggesting that specific inflammatory mechanisms involved in the obesity pathway may mediate disease onset.