Identification of New Modulators and Inhibitors of Palmitoyl-Protein Thioesterase 1 for CLN1 Batten Disease and Cancer.

Palmitoyl-protein thioesterase 1 (PPT1) is an understudied enzyme that is gaining attention due to its role in the depalmitoylation of several proteins involved in neurodegenerative diseases and cancer. PPT1 is overexpressed in several cancers, specifically cholangiocarcinoma and esophageal cancers. Inhibitors of PPT1 lead to cell death and have been shown to enhance the killing of tumor cells alongside known chemotherapeutics. PPT1 is hence a viable target for anticancer drug development. Furthermore, mutations in PPT1 cause a lysosomal storage disorder called infantile neuronal ceroid lipofuscinosis (CLN1 disease). Molecules that can inhibit, stabilize, or modulate the activity of this target are needed to address these diseases. We used PPT1 enzymatic assays to identify molecules that were subsequently tested by using differential scanning fluorimetry and microscale thermophoresis. Selected compounds were also tested in neuroblastoma cell lines. The resulting PPT1 screening data was used for building machine learning models to help select additional compounds for testing. We discovered two of the most potent PPT1 inhibitors reported to date, orlistat (IC50 178.8 nM) and palmostatin B (IC50 11.8 nM). When tested in HepG2 cells, it was found that these molecules had decreased activity, indicating that they were likely not penetrating the cells. The combination of in vitro enzymatic and biophysical assays enabled the identification of several molecules that can bind or inhibit PPT1 and may aid in the discovery of modulators or chaperones. The molecules identified could be used as a starting point for further optimization as treatments for other potential therapeutic applications outside CLN1 disease, such as cancer and neurological diseases.

Pharmacogenomic Analyses Implicate B Cell Developmental Status and MKL1 as Determinants of Sensitivity toward Anti-CD20 Monoclonal Antibody Therapy.

Monoclonal antibody (mAb) therapy directed against CD20 is an important tool in the treatment of B cell disorders. However, variable patient response and acquired resistance remain important clinical challenges. To identify genetic factors that may influence sensitivity to treatment, the cytotoxic activity of three CD20 mAbs: rituximab; ofatumumab; and obinutuzumab, were screened in high-throughput assays using 680 ethnically diverse lymphoblastoid cell lines (LCLs) followed by a pharmacogenomic assessment. GWAS analysis identified several novel gene candidates. The most significant SNP, rs58600101, in the gene MKL1 displayed ethnic stratification, with the variant being significantly more prevalent in the African cohort and resulting in reduced transcript levels as measured by qPCR. Functional validation of MKL1 by shRNA-mediated knockdown of MKL1 resulted in a more resistant phenotype. Gene expression analysis identified the developmentally associated TGFB1I1 as the most significant gene associated with sensitivity. qPCR among a panel of sensitive and resistant LCLs revealed immunoglobulin class-switching as well as differences in the expression of B cell activation markers. Flow cytometry showed heterogeneity within some cell lines relative to surface Ig isotype with a shift to more IgG+ cells among the resistant lines. Pretreatment with prednisolone could partly reverse the resistant phenotype. Results suggest that the efficacy of anti-CD20 mAb therapy may be influenced by B cell developmental status as well as polymorphism in the MKL1 gene. A clinical benefit may be achieved by pretreatment with corticosteroids such as prednisolone followed by mAb therapy.

RYK Gene Expression Associated with Drug Response Variation of Temozolomide and Clinical Outcomes in Glioma Patients.

Temozolomide (TMZ) chemotherapy is an important tool in the treatment of glioma brain tumors. However, variable patient response and chemo-resistance remain exceptionally challenging. Our previous genome-wide association study (GWAS) identified a suggestively significant association of SNP rs4470517 in the RYK (receptor-like kinase) gene with TMZ drug response. Functional validation of RYK using lymphocytes and glioma cell lines resulted in gene expression analysis indicating differences in expression status between genotypes of the cell lines and TMZ dose response. We conducted univariate and multivariate Cox regression analyses using publicly available TCGA and GEO datasets to investigate the impact of RYK gene expression status on glioma patient overall (OS) and progression-free survival (PFS). Our results indicated that in IDH mutant gliomas, RYK expression and tumor grade were significant predictors of survival. In IDH wildtype glioblastomas (GBM), MGMT status was the only significant predictor. Despite this result, we revealed a potential benefit of RYK expression in IDH wildtype GBM patients. We found that a combination of RYK expression and MGMT status could serve as an additional biomarker for improved survival. Overall, our findings suggest that RYK expression may serve as an important prognostic or predictor of TMZ response and survival for glioma patients.

MKX-AS1 Gene Expression Associated with Variation in Drug Response to Oxaliplatin and Clinical Outcomes in Colorectal Cancer Patients.

Oxaliplatin (OXAL) is a commonly used chemotherapy for treating colorectal cancer (CRC). A recent genome wide association study (GWAS) showed that a genetic variant (rs11006706) in the lncRNA gene MKX-AS1 and partnered sense gene MKX could impact the response of genetically varied cell lines to OXAL treatment. This study found that the expression levels of MKX-AS1 and MKX in lymphocytes (LCLs) and CRC cell lines differed between the rs11006706 genotypes, indicating that this gene pair could play a role in OXAL response. Further analysis of patient survival data from the Cancer Genome Atlas (TCGA) and other sources showed that patients with high MKX-AS1 expression status had significantly worse overall survival (HR = 3.2; 95%CI = (1.17-9); p = 0.024) compared to cases with low MKX-AS1 expression status. Alternatively, high MKX expression status had significantly better overall survival (HR = 0.22; 95%CI = (0.07-0.7); p = 0.01) compared to cases with low MKX expression status. These results suggest an association between MKX-AS1 and MKX expression status that could be useful as a prognostic marker of response to OXAL and potential patient outcomes in CRC.

Discovery of a Potent and Selective Naphthyridine-Based Chemical Probe for Casein Kinase 2.

Naphthyridine-based inhibitors were synthesized to yield a potent and cell-active inhibitor of casein kinase 2 (CK2). Compound 2 selectively inhibits CK2α and CK2α' when profiled broadly, thereby making it an exquisitely selective chemical probe for CK2. A negative control that is structurally related but lacks a key hinge-binding nitrogen (7) was designed on the basis of structural studies. Compound 7 does not bind CK2α or CK2α' in cells and demonstrates excellent kinome-wide selectivity. Differential anticancer activity was observed when compound 2 was profiled alongside a structurally distinct CK2 chemical probe: SGC-CK2-1. This naphthyridine-based chemical probe (2) represents one of the best available small molecule tools with which to interrogate biology mediated by CK2.

Discovery of potent Plasmodium falciparum protein kinase 6 (PfPK6) inhibitors with a type II inhibitor pharmacophore.

Malaria is a devastating disease that causes significant global morbidity and mortality. The rise of drug resistance against artemisinin-based combination therapy demonstrates the necessity to develop alternative antimalarials with novel mechanisms of action. We report the discovery of Ki8751 as an inhibitor of essential kinase PfPK6. 79 derivatives were designed, synthesized and evaluated for PfPK6 inhibition and antiplasmodial activity. Using group efficiency analyses, we established the importance of key groups on the scaffold consistent with a type II inhibitor pharmacophore. We highlight modifications on the tail group that contribute to antiplasmodial activity, cumulating in the discovery of compound 67, a PfPK6 inhibitor (IC50 = 13 nM) active against the P. falciparum blood stage (EC50 = 160 nM), and compound 79, a PfPK6 inhibitor (IC50 < 5 nM) with dual-stage antiplasmodial activity against P. falciparum blood stage (EC50 = 39 nM) and against P. berghei liver stage (EC50 = 220 nM).

Multi-omic profiling reveals the ataxia protein sacsin is required for integrin trafficking and synaptic organization.

Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a childhood-onset cerebellar ataxia caused by mutations in SACS, which encodes the protein sacsin. Cellular ARSACS phenotypes include mitochondrial dysfunction, intermediate filament disorganization, and progressive death of cerebellar Purkinje neurons. It is unclear why the loss of sacsin causes these deficits or why they manifest as cerebellar ataxia. Here, we perform multi-omic profiling in sacsin knockout (KO) cells and identify alterations in microtubule dynamics and mislocalization of focal adhesion (FA) proteins, including multiple integrins. Deficits in FA structure, signaling, and function can be rescued by targeting PTEN, a negative regulator of FA signaling. ARSACS mice possess mislocalization of ITGA1 in Purkinje neurons and synaptic disorganization in the deep cerebellar nucleus (DCN). The sacsin interactome reveals that sacsin regulates interactions between cytoskeletal and synaptic adhesion proteins. Our findings suggest that disrupted trafficking of synaptic adhesion proteins is a causal molecular deficit in ARSACS.

Multiple approaches to repurposing drugs for neuroblastoma.

Neuroblastoma (NB) is the second leading extracranial solid tumor of early childhood with about two-thirds of cases presenting before the age of 5, and accounts for roughly 15 percent of all pediatric cancer fatalities in the United States. Treatments against NB are lacking, resulting in a low survival rate in high-risk patients. A repurposing approach using already approved or clinical stage compounds can be used for diseases for which the patient population is small, and the commercial market limited. We have used Bayesian machine learning, in vitro cell assays, and combination analysis to identify molecules with potential use for NB. We demonstrated that pyronaridine (SH-SY5Y IC50 1.70 µM, SK-N-AS IC50 3.45 µM), BAY 11-7082 (SH-SY5Y IC50 0.85 µM, SK-N-AS IC50 1.23 µM), niclosamide (SH-SY5Y IC50 0.87 µM, SK-N-AS IC50 2.33 µM) and fingolimod (SH-SY5Y IC50 4.71 µM, SK-N-AS IC50 6.11 µM) showed cytotoxicity against NB. As several of the molecules are approved drugs in the US or elsewhere, they may be repurposed more readily for NB treatment. Pyronaridine was also tested in combinations in SH-SY5Y cells and demonstrated an antagonistic effect with either etoposide or crizotinib. Whereas when crizotinib and etoposide were combined with each other they had a synergistic effect in these cells. We have also described several analogs of pyronaridine to explore the structure-activity relationship against cell lines. We describe multiple molecules demonstrating cytotoxicity against NB and the further evaluation of these molecules and combinations using other NB cells lines and in vivo models will be important in the future to assess translational potential.

Identification of Novel 2,4,5-Trisubstituted Pyrimidines as Potent Dual Inhibitors of Plasmodial PfGSK3/PfPK6 with Activity against Blood Stage Parasites In Vitro.

Essential plasmodial kinases PfGSK3 and PfPK6 are considered novel drug targets to combat rising resistance to traditional antimalarial therapy. Herein, we report the discovery of IKK16 as a dual PfGSK3/PfPK6 inhibitor active against blood stage Pf3D7 parasites. To establish structure-activity relationships for PfPK6 and PfGSK3, 52 analogues were synthesized and assessed for the inhibition of PfGSK3 and PfPK6, with potent inhibitors further assessed for activity against blood and liver stage parasites. This culminated in the discovery of dual PfGSK3/PfPK6 inhibitors 23d (PfGSK3/PfPK6 IC50 = 172/11 nM) and 23e (PfGSK3/PfPK6 IC50 = 97/8 nM) with antiplasmodial activity (23d Pf3D7 EC50 = 552 ± 37 nM and 23e Pf3D7 EC50 = 1400 ± 13 nM). However, both compounds exhibited significant promiscuity when tested in a panel of human kinase targets. Our results demonstrate that dual PfPK6/PfGSK3 inhibitors with antiplasmodial activity can be identified and can set the stage for further optimization efforts.

High-throughput screening and genome-wide analyses of 44 anticancer drugs in the 1000 Genomes cell lines reveals an association of the NQO1 gene with the response of multiple anticancer drugs.

Cancer patients exhibit a broad range of inter-individual variability in response and toxicity to widely used anticancer drugs, and genetic variation is a major contributor to this variability. To identify new genes that influence the response of 44 FDA-approved anticancer drug treatments widely used to treat various types of cancer, we conducted high-throughput screening and genome-wide association mapping using 680 lymphoblastoid cell lines from the 1000 Genomes Project. The drug treatments considered in this study represent nine drug classes widely used in the treatment of cancer in addition to the paclitaxel + epirubicin combination therapy commonly used for breast cancer patients. Our genome-wide association study (GWAS) found several significant and suggestive associations. We prioritized consistent associations for functional follow-up using gene-expression analyses. The NAD(P)H quinone dehydrogenase 1 (NQO1) gene was found to be associated with the dose-response of arsenic trioxide, erlotinib, trametinib, and a combination treatment of paclitaxel + epirubicin. NQO1 has previously been shown as a biomarker of epirubicin response, but our results reveal novel associations with these additional treatments. Baseline gene expression of NQO1 was positively correlated with response for 43 of the 44 treatments surveyed. By interrogating the functional mechanisms of this association, the results demonstrate differences in both baseline and drug-exposed induction.

Race and smoking status associated with paclitaxel drug response in patient-derived lymphoblastoid cell lines.

The use of ex-vivo model systems to provide a level of forecasting for in-vivo characteristics remains an important need for cancer therapeutics. The use of lymphoblastoid cell lines (LCLs) is an attractive approach for pharmacogenomics and toxicogenomics, due to their scalability, efficiency, and cost-effectiveness. There is little data on the impact of demographic or clinical covariates on LCL response to chemotherapy. Paclitaxel sensitivity was determined in LCLs from 93 breast cancer patients from the University of North Carolina Lineberger Comprehensive Cancer Center Breast Cancer Database to test for potential associations and/or confounders in paclitaxel dose-response assays. Measures of paclitaxel cell viability were associated with patient data included treatment regimens, cancer status, demographic and environmental variables, and clinical outcomes. We used multivariate analysis of variance to identify the in-vivo variables associated with ex-vivo dose-response. In this unique dataset that includes both in-vivo and ex-vivo data from breast cancer patients, race (P = 0.0049) and smoking status (P = 0.0050) were found to be significantly associated with ex-vivo dose-response in LCLs. Racial differences in clinical dose-response have been previously described, but the smoking association has not been reported. Our results indicate that in-vivo smoking status can influence ex-vivo dose-response in LCLs, and more precise measures of covariates may allow for more precise forecasting of clinical effect. In addition, understanding the mechanism by which exposure to smoking in-vivo effects ex-vivo dose-response in LCLs may open up new avenues in the quest for better therapeutic prediction.

Synergistic drug combinations and machine learning for drug repurposing in chordoma.

Chordoma is a devastating rare cancer that affects one in a million people. With a mean-survival of just 6 years and no approved medicines, the primary treatments are surgery and radiation. In order to speed new medicines to chordoma patients, a drug repurposing strategy represents an attractive approach. Drugs that have already advanced through human clinical safety trials have the potential to be approved more quickly than de novo discovered medicines on new targets. We have taken two strategies to enable this: (1) generated and validated machine learning models of chordoma inhibition and screened compounds of interest in vitro. (2) Tested combinations of approved kinase inhibitors already being individually evaluated for chordoma. Several published studies of compounds screened against chordoma cell lines were used to generate Bayesian Machine learning models which were then used to score compounds selected from the NIH NCATS industry-provided assets. Out of these compounds, the mTOR inhibitor AZD2014, was the most potent against chordoma cell lines (IC50 0.35 µM U-CH1 and 0.61 µM U-CH2). Several studies have shown the importance of the mTOR signaling pathway in chordoma and suggest it as a promising avenue for targeted therapy. Additionally, two currently FDA approved drugs, afatinib and palbociclib (EGFR and CDK4/6 inhibitors, respectively) demonstrated synergy in vitro (CI50 = 0.43) while AZD2014 and afatanib also showed synergy (CI50 = 0.41) against a chordoma cell in vitro. These findings may be of interest clinically, and this in vitro- and in silico approach could also be applied to other rare cancers.

Synergistic Chemotherapy Drug Response Is a Genetic Trait in Lymphoblastoid Cell Lines.

Lymphoblastoid cell lines (LCLs) are a highly successful model for evaluating the genetic etiology of cancer drug response, but applications using this model have typically focused on single drugs. Combination therapy is quite common in modern chemotherapy treatment since drugs often work synergistically, and it is an important progression in the use of the LCL model to expand work for drug combinations. In the present work, we demonstrate that synergy occurs and can be quantified in LCLs across a range of clinically important drug combinations. Lymphoblastoid cell lines have been commonly employed in association mapping in cancer pharmacogenomics, but it is so far untested as to whether synergistic effects have a genetic etiology. Here we use cell lines from extended pedigrees to demonstrate that there is a substantial heritable component to synergistic drug response. Additionally, we perform linkage mapping in these pedigrees to identify putative regions linked to this important phenotype. This demonstration supports the premise of expanding the use of the LCL model to perform association mapping for combination therapies.

Design of a Cyclin G Associated Kinase (GAK)/Epidermal Growth Factor Receptor (EGFR) Inhibitor Set to Interrogate the Relationship of EGFR and GAK in Chordoma.

We describe the design of a set of inhibitors to investigate the relationship between cyclin G associated kinase (GAK) and epidermal growth factor receptor (EGFR) in chordoma bone cancers. These compounds were characterized both in vitro and using in cell target engagement assays. The most potent chordoma inhibitors were further characterized in a kinome-wide screen demonstrating narrow spectrum profiles. While we observed a direct correlation between EGFR and antiproliferative effects on chordoma, GAK inhibition appeared to have only a limited effect.

The influence of Neanderthal alleles on cytotoxic response.

Various studies have shown that people of Eurasian origin contain traces of DNA inherited from interbreeding with Neanderthals. Recent studies have demonstrated that these Neanderthal variants influence a range of clinically important traits and diseases. Thus, understanding the genetic factors responsible for the variability in individual response to drug or chemical exposure is a key goal of pharmacogenomics and toxicogenomics, as dose responses are clinically and epidemiologically important traits. It is well established that ethnic and racial differences are important in dose response traits, but to our knowledge the influence of Neanderthal ancestry on response to xenobiotics is unknown. Towards this aim, we examined if Neanderthal ancestry plays a role in cytotoxic response to anti-cancer drugs and toxic environmental chemicals. We identified common Neanderthal variants in lymphoblastoid cell lines (LCLs) derived from the globally diverse 1000 Genomes Project and Caucasian cell lines from the Children's Hospital of Oakland Research Institute. We analyzed the effects of these Neanderthal alleles on cytotoxic response to 29 anti-cancer drugs and 179 environmental chemicals at varying concentrations using genome-wide data. We identified and replicated single nucleotide polymorphisms (SNPs) from these association results, including a SNP in the SNORD-113 cluster. Our results also show that the Neanderthal alleles cumulatively lead to increased sensitivity to both the anti-cancer drugs and the environmental chemicals. Our results demonstrate the influence of Neanderthal ancestry-informative markers on cytotoxic response. These results could be important in identifying biomarkers for personalized medicine or in dissecting the underlying etiology of dose response traits.

Genetic Variants in CPA6 and PRPF31 Are Associated With Variation in Response to Metformin in Individuals With Type 2 Diabetes.

Metformin is the first-line treatment for type 2 diabetes (T2D). Although widely prescribed, the glucose-lowering mechanism for metformin is incompletely understood. Here, we used a genome-wide association approach in a diverse group of individuals with T2D from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial to identify common and rare variants associated with HbA1c response to metformin treatment and followed up these findings in four replication cohorts. Common variants in PRPF31 and CPA6 were associated with worse and better metformin response, respectively (P < 5 × 10-6), and meta-analysis in independent cohorts displayed similar associations with metformin response (P = 1.2 × 10-8 and P = 0.005, respectively). Previous studies have shown that PRPF31(+/-) knockout mice have increased total body fat (P = 1.78 × 10-6) and increased fasted circulating glucose (P = 5.73 × 10-6). Furthermore, rare variants in STAT3 associated with worse metformin response (q <0.1). STAT3 is a ubiquitously expressed pleiotropic transcriptional activator that participates in the regulation of metabolism and feeding behavior. Here, we provide novel evidence for associations of common and rare variants in PRPF31, CPA6, and STAT3 with metformin response that may provide insight into mechanisms important for metformin efficacy in T2D.

Genetic Variants in HSD17B3, SMAD3, and IPO11 Impact Circulating Lipids in Response to Fenofibrate in Individuals With Type 2 Diabetes.

Individuals with type 2 diabetes (T2D) and dyslipidemia are at an increased risk of cardiovascular disease. Fibrates are a class of drugs prescribed to treat dyslipidemia, but variation in response has been observed. To evaluate common and rare genetic variants that impact lipid responses to fenofibrate in statin-treated patients with T2D, we examined lipid changes in response to fenofibrate therapy using a genomewide association study (GWAS). Associations were followed-up using gene expression studies in mice. Common variants in SMAD3 and IPO11 were marginally associated with lipid changes in black subjects (P < 5 × 10-6 ). Rare variant and gene expression changes were assessed using a false discovery rate approach. AKR7A3 and HSD17B13 were associated with lipid changes in white subjects (q < 0.2). Mice fed fenofibrate displayed reductions in Hsd17b13 gene expression (q < 0.1). Associations of variants in SMAD3, IPO11, and HSD17B13, with gene expression changes in mice indicate that transforming growth factor-beta (TGF-ß) and NRF2 signaling pathways may influence fenofibrate effects on dyslipidemia in patients with T2D.

Common and rare genetic markers of lipid variation in subjects with type 2 diabetes from the ACCORD clinical trial.

BACKGROUND: Individuals with type 2 diabetes are at an increased risk of cardiovascular disease. Alterations in circulating lipid levels, total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides (TG) are heritable risk factors for cardiovascular disease. Here we conduct a genome-wide association study (GWAS) of common and rare variants to investigate associations with baseline lipid levels in 7,844 individuals with type 2 diabetes from the ACCORD clinical trial. METHODS: DNA extracted from stored blood samples from ACCORD participants were genotyped using the Affymetrix Axiom Biobank 1 Genotyping Array. After quality control and genotype imputation, association of common genetic variants (CV), defined as minor allele frequency (MAF) ≥ 3%, with baseline levels of TC, LDL, HDL, and TG was tested using a linear model. Rare variant (RV) associations (MAF < 3%) were conducted using a suite of methods that collapse multiple RV within individual genes. RESULTS: Many statistically significant CV (p < 1 × 10-8) replicate findings in large meta-analyses in non-diabetic subjects. RV analyses also confirmed findings in other studies, whereas significant RV associations with CNOT2, HPN-AS1, and SIRPD appear to be novel (q < 0.1). DISCUSSION: Here we present findings for the largest GWAS of lipid levels in people with type 2 diabetes to date. We identified 17 statistically significant (p < 1 × 10-8) associations of CV with lipid levels in 11 genes or chromosomal regions, all of which were previously identified in meta-analyses of mostly non-diabetic cohorts. We also identified 13 associations in 11 genes based on RV, several of which represent novel findings.

Incorporating Concomitant Medications into Genome-Wide Analyses for the Study of Complex Disease and Drug Response.

Given the high costs of conducting a drug-response trial, researchers are now aiming to use retrospective analyses to conduct genome-wide association studies (GWAS) to identify underlying genetic contributions to drug-response variation. To prevent confounding results from a GWAS to investigate drug response, it is necessary to account for concomitant medications, defined as any medication taken concurrently with the primary medication being investigated. We use data from the Action to Control Cardiovascular Disease (ACCORD) trial in order to implement a novel scoring procedure for incorporating concomitant medication information into a linear regression model in preparation for GWAS. In order to accomplish this, two primary medications were selected: thiazolidinediones and metformin because of the wide-spread use of these medications and large sample sizes available within the ACCORD trial. A third medication, fenofibrate, along with a known confounding medication, statin, were chosen as a proof-of-principle for the scoring procedure. Previous studies have identified SNP rs7412 as being associated with statin response. Here we hypothesize that including the score for statin as a covariate in the GWAS model will correct for confounding of statin and yield a change in association at rs7412. The response of the confounded signal was successfully diminished from p = 3.19 × 10-7 to p = 1.76 × 10-5, by accounting for statin using the scoring procedure presented here. This approach provides the ability for researchers to account for concomitant medications in complex trial designs where monotherapy treatment regimens are not available.

Evaluating the role of admixture in cancer therapy via in vitro drug response and multivariate genome-wide associations.

AIM: We investigate the role of ethnicity and admixture in drug response across a broad group of chemotherapeutic drugs. Also, we generate hypotheses on the genetic variants driving differential drug response through multivariate genome-wide association studies. METHODS: Immortalized lymphoblastoid cell lines from 589 individuals (Hispanic or non-Hispanic/Caucasian) were used to investigate dose-response for 28 chemotherapeutic compounds. Univariate and multivariate statistical models were used to elucidate associations between genetic variants and differential drug response as well as the role of ethnicity in drug potency and efficacy. RESULTS & CONCLUSION: For many drugs, the variability in drug response appears to correlate with self-reported race and estimates of genetic ancestry. Additionally, multivariate genome-wide association analyses offered interesting hypotheses governing these differential responses.