@article{mcdonough_warren_jack_motsinger‐reif_armstrong_bis_house_singh_el rouby_gong_et al._2021, title={Adverse Cardiovascular Outcomes and Antihypertensive Treatment: A Genome‐Wide Interaction Meta‐Analysis in the International Consortium for Antihypertensive Pharmacogenomics Studies}, volume={110}, ISSN={0009-9236 1532-6535}, url={http://dx.doi.org/10.1002/cpt.2355}, DOI={10.1002/cpt.2355}, abstractNote={We sought to identify genome‐wide variants influencing antihypertensive drug response and adverse cardiovascular outcomes, utilizing data from four randomized controlled trials in the International Consortium for Antihypertensive Pharmacogenomics Studies (ICAPS). Genome‐wide antihypertensive drug‐single nucleotide polymorphism (SNP) interaction tests for four drug classes (β‐blockers, n = 9,195; calcium channel blockers (CCBs), n = 10,511; thiazide/thiazide‐like diuretics, n = 3,516; ACE‐inhibitors/ARBs, n = 2,559) and cardiovascular outcomes (incident myocardial infarction, stroke, or death) were analyzed among patients with hypertension of European ancestry. Top SNPs from the meta‐analyses were tested for replication of cardiovascular outcomes in an independent Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) study (n = 21,267), blood pressure (BP) response in independent ICAPS studies (n = 1,552), and ethnic validation in African Americans from the Genetics of Hypertension Associated Treatment study (GenHAT; n = 5,115). One signal reached genome‐wide significance in the β‐blocker‐SNP interaction analysis (rs139945292, Interaction P = 1.56 × 10−8). rs139945292 was validated through BP response to β‐blockers, with the T‐allele associated with less BP reduction (systolic BP response P = 6 × 10−4, Beta = 3.09, diastolic BP response P = 5 × 10−3, Beta = 1.53). The T‐allele was also associated with increased adverse cardiovascular risk within the β‐blocker treated patients’ subgroup (P = 2.35 × 10−4, odds ratio = 1.57, 95% confidence interval = 1.23–1.99). The locus showed nominal replication in CHARGE, and consistent directional trends in β‐blocker treated African Americans. rs139945292 is an expression quantitative trait locus for the 50 kb upstream gene NTM (neurotrimin). No SNPs attained genome‐wide significance for any other drugs classes. Top SNPs were located near CALB1 (CCB), FLJ367777 (ACE‐inhibitor), and CES5AP1 (thiazide). The NTM region is associated with increased risk for adverse cardiovascular outcomes and less BP reduction in β‐blocker treated patients. Further investigation into this region is warranted.}, number={3}, journal={Clinical Pharmacology & Therapeutics}, publisher={Wiley}, author={McDonough, Caitrin W. and Warren, Helen R. and Jack, John R. and Motsinger‐Reif, Alison A. and Armstrong, Nicole D. and Bis, Joshua C. and House, John S. and Singh, Sonal and El Rouby, Nihal M. and Gong, Yan and et al.}, year={2021}, month={Aug}, pages={723–732} }
 @article{lynch_ruterbories_jack_motsinger-reif_hanel_2020, title={The influence of packed cell volume versus plasma proteins on thromboelastographic variables in canine blood}, volume={30}, ISSN={["1476-4431"]}, url={https://doi.org/10.1111/vec.12979}, DOI={10.1111/vec.12979}, abstractNote={Abstract}, number={4}, journal={JOURNAL OF VETERINARY EMERGENCY AND CRITICAL CARE}, author={Lynch, Alex M. and Ruterbories, Laura and Jack, John and Motsinger-Reif, Alison A. and Hanel, Rita}, year={2020}, month={Jul}, pages={418–425} }
 @article{roell_havener_reif_jack_mcleod_wiltshire_motsinger-reif_2019, title={Synergistic Chemotherapy Drug Response Is a Genetic Trait in Lymphoblastoid Cell Lines}, volume={10}, ISSN={["1664-8021"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85074258240&partnerID=MN8TOARS}, DOI={10.3389/fgene.2019.00829}, abstractNote={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.}, journal={FRONTIERS IN GENETICS}, author={Roell, Kyle R. and Havener, Tammy M. and Reif, David M. and Jack, John and McLeod, Howard L. and Wiltshire, Tim and Motsinger-Reif, Alison A.}, year={2019}, month={Oct} }
 @article{jack_small_brown_havener_mcleod_motsinger-reif_richards_2018, title={Gene expression and linkage analysis implicate as a mediator of rituximab resistance}, volume={18}, ISSN={["1473-1150"]}, DOI={10.1038/tpj.2017.41}, abstractNote={Elucidating resistance mechanisms for therapeutic monoclonal antibodies (MAbs) is challenging, because they are difficult to study in non-human models. We therefore developed a strategy to genetically map in vitro drug sensitivity, identifying genes that alter responsiveness to rituximab, a therapeutic anti-CD20 MAb that provides significant benefit to patients with B-cell malignancies. We discovered novel loci with genome-wide mapping analyses and functionally validated one of these genes, CBLB, which causes rituximab resistance when knocked down in lymphoma cells. This study demonstrates the utility of genome-wide mapping to discover novel biological mechanisms of potential clinical advantage.}, number={3}, journal={PHARMACOGENOMICS JOURNAL}, author={Jack, J. and Small, G. W. and Brown, C. C. and Havener, T. M. and McLeod, H. L. and Motsinger-Reif, A. A. and Richards, K. L.}, year={2018}, month={May}, pages={467–473} }
 @article{akhtari_havener_fukudo_jack_mcleod_wiltshire_motsinger-reif_2018, title={The influence of Neanderthal alleles on cytotoxic response}, volume={6}, ISSN={["2167-8359"]}, DOI={10.7717/peerj.5691}, abstractNote={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.}, journal={PEERJ}, author={Akhtari, Farida S. and Havener, Tammy M. and Fukudo, Masahide and Jack, John R. and McLeod, Howard L. and Wiltshire, Tim and Motsinger-Reif, Alison A.}, year={2018}, month={Oct} }
 @article{rotroff_marvel_jack_havener_doria_shah_mychaleckyi_mcleod_buse_wagner_et al._2017, title={Common genetic variants in neurobeachin (nbea) are associated with metformin drug response in individuals with type 2 diabetes in the accord clinical trial}, volume={101}, number={S1}, journal={Clinical Pharmacology & Therapeutics}, author={Rotroff, D. M. and Marvel, S. W. and Jack, J. R. and Havener, T. M. and Doria, A. and Shah, H. S. and Mychaleckyi, J. C. and McLeod, H. L. and Buse, J. B. and Wagner, M. J. and et al.}, year={2017}, pages={S9–9} }
 @article{toledo_arnold_kastenmuller_chang_baillie_han_thambisetty_tenenbaum_suhre_thompson_et al._2017, title={Metabolic network failures in Alzheimer's disease: A biochemical road map}, volume={13}, number={9}, journal={Alzheimers & Dementia}, author={Toledo, J. B. and Arnold, M. and Kastenmuller, G. and Chang, R. and Baillie, R. A. and Han, X. L. and Thambisetty, M. and Tenenbaum, J. D. and Suhre, K. and Thompson, J. W. and et al.}, year={2017}, pages={965–984} }
 @article{jackson_long_he_motsinger-reif_mcleod_jack_2016, title={A comparison of DMET Plus microarray and genome-wide technologies by assessing population substructure}, volume={26}, ISSN={["1744-6880"]}, DOI={10.1097/fpc.0000000000000200}, abstractNote={Objective The capacity of the Affymetrix drug metabolism enzymes and transporters (DMET) Plus pharmacogenomics genotyping chip to estimate population substructure and cryptic relatedness was evaluated. The results were compared with estimates using genome-wide HapMap data for the same individuals. Methods For 301 unrelated individuals, spanning three continental populations and one admixed population, genotypic data were collected using the Affymetrix DMET Plus microarray. Genome-wide data on these individuals were obtained from HapMap release 3. Population substructure was assessed using Eigenstrat and ADMIXTURE software for both platforms. Cryptic relatedness was explored by inbreeding coefficient estimation. Nonparametric tests were used to determine correlations of the analytical results of the two genotyping platforms. Results Principal components analysis identified population substructure for both datasets, with 15.8 and 16.6% of the total variance explained in the first two principal components for DMET Plus and HapMap data, respectively. ADMIXTURE results correctly identified four subpopulations within each dataset. Nonparametric rank correlations indicated significant associations between analyses with an average &rgr;=0.7272 (P<10–16) across the three continental populations and &rgr;=0.4888 for the admixed population. Concordance correlation coefficients (average &rgr;c=0.9693 across all four subpopulations) strongly indicate concordance between ADMIXTURE results. Inbreeding coefficients were slightly inflated (16 individuals>0.15) using DMET Plus data and no cryptic relatedness was indicated using HapMap data. The inflated inbreeding estimation could be because of the limited number of markers provided by DMET as a random sample of 1832 markers from HapMap also yielded inflated estimates of cryptic relatedness (39 individuals>0.15). Furthermore, use of single nucleotide polymorphisms located in genes involved in metabolism and transport may have different allele frequencies in subpopulations than single nucleotide polymorphisms sampled from the whole genome. Conclusion The DMET Plus pharmacogenomics genotyping chip is effective in quantifying population substructure across the three continental populations and inferring the presence of an admixed population. On the basis of our results, these microarrays offer sufficient depth for covariate adjustment of population substructure in genomic association studies.}, number={4}, journal={PHARMACOGENETICS AND GENOMICS}, author={Jackson, Jami N. and Long, Kevin M. and He, Yijing and Motsinger-Reif, Alison A. and McLeod, Howard L. and Jack, John}, year={2016}, month={Apr}, pages={147–153} }
 @article{shah_setzer_jack_houck_judson_knudsen_liu_martin_reif_richard_et al._2016, title={Using ToxCast (TM) data to reconstruct dynamic cell state trajectories and estimate toxicological points of departure}, volume={124}, number={7}, journal={Environmental Health Perspectives}, author={Shah, I. and Setzer, R. W. and Jack, J. and Houck, K. A. and Judson, R. S. and Knudsen, T. B. and Liu, J. and Martin, M. T. and Reif, D. M. and Richard, A. M. and et al.}, year={2016}, pages={910–919} }
 @article{jack_havener_mcleod_motsinger-reif_foster_2015, title={Evaluating the role of admixture in cancer therapy via in vitro drug response and multivariate genome-wide associations}, volume={16}, ISSN={["1744-8042"]}, DOI={10.2217/pgs.15.85}, abstractNote={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.}, number={13}, journal={PHARMACOGENOMICS}, author={Jack, John and Havener, Tammy M. and McLeod, Howard L. and Motsinger-Reif, Alison A. and Foster, Matthew}, year={2015}, pages={1451–1463} }
 @article{abdo_xia_brown_kosyk_huang_sakamuru_zhou_jack_gallins_xia_et al._2015, title={Population-Based in Vitro Hazard and Concentration-Response Assessment of Chemicals: The 1000 Genomes High-Throughput Screening Study}, volume={123}, ISSN={["1552-9924"]}, DOI={10.1289/ehp.1408775}, abstractNote={Background: Understanding of human variation in toxicity to environmental chemicals remains limited, so human health risk assessments still largely rely on a generic 10-fold factor (10½ each for toxicokinetics and toxicodynamics) to account for sensitive individuals or subpopulations. Objectives: We tested a hypothesis that population-wide in vitro cytotoxicity screening can rapidly inform both the magnitude of and molecular causes for interindividual toxicodynamic variability. Methods: We used 1,086 lymphoblastoid cell lines from the 1000 Genomes Project, representing nine populations from five continents, to assess variation in cytotoxic response to 179 chemicals. Analysis included assessments of population variation and heritability, and genome-wide association mapping, with attention to phenotypic relevance to human exposures. Results: For about half the tested compounds, cytotoxic response in the 1% most “sensitive” individual occurred at concentrations within a factor of 10½ (i.e., approximately 3) of that in the median individual; however, for some compounds, this factor was > 10. Genetic mapping suggested important roles for variation in membrane and transmembrane genes, with a number of chemicals showing association with SNP rs13120371 in the solute carrier SLC7A11, previously implicated in chemoresistance. Conclusions: This experimental approach fills critical gaps unaddressed by recent large-scale toxicity testing programs, providing quantitative, experimentally based estimates of human toxicodynamic variability, and also testable hypotheses about mechanisms contributing to interindividual variation. Citation: Abdo N, Xia M, Brown CC, Kosyk O, Huang R, Sakamuru S, Zhou YH, Jack JR, Gallins P, Xia K, Li Y, Chiu WA, Motsinger-Reif AA, Austin CP, Tice RR, Rusyn I, Wright FA. 2015. Population-based in vitro hazard and concentration–response assessment of chemicals: the 1000 Genomes high-throughput screening study. Environ Health Perspect 123:458–466; http://dx.doi.org/10.1289/ehp.1408775}, number={5}, journal={ENVIRONMENTAL HEALTH PERSPECTIVES}, author={Abdo, Nour and Xia, Menghang and Brown, Chad C. and Kosyk, Oksana and Huang, Ruili and Sakamuru, Srilatha and Zhou, Yi-Hui and Jack, John R. and Gallins, Paul and Xia, Kai and et al.}, year={2015}, month={May}, pages={458–466} }
 @article{che_jack_motsinger-reif_brown_2014, title={An adaptive permutation approach for genome-wide association study: Evaluation and recommendations for use}, volume={7}, journal={Biodata Mining}, author={Che, R. L. and Jack, J. R. and Motsinger-Reif, A. A. and Brown, C. C.}, year={2014} }
 @article{hertz_roy_jack_motsinger-reif_drobish_clark_carey_dees_mcleod_2014, title={Genetic heterogeneity beyond CYP2C8*3 does not explain differential sensitivity to paclitaxel-induced neuropathy}, volume={145}, ISSN={["1573-7217"]}, DOI={10.1007/s10549-014-2910-1}, abstractNote={The development of paclitaxel-induced peripheral neuropathy (PIPN) is influenced by drug exposure and patient genetics. The purpose of this analysis was to expand on a previous reported association of CYP2C8*3 and PIPN risk by investigating additional polymorphisms in CYP2C8 and in hundreds of other genes potentially relevant to paclitaxel pharmacokinetics. Clinical data was collected prospectively in an observational registry of newly diagnosed breast cancer patients. Patients treated with paclitaxel-containing regimens were genotyped using the Affymetrix DMET™ Plus chip. Patients who carried the CYP2C8*2, *3, or *4 variant were collapsed into a low-metabolizer CYP2C8 phenotype for association with PIPN. Separately, all SNPs that surpassed quality control were assessed individually and as a composite of genetic ancestry for associations with PIPN. 412 paclitaxel-treated patients and 564 genetic markers were included in the analysis. The risk of PIPN was significantly greater in the CYP2C8 low-metabolizer group (HR = 1.722, p = 0.018); however, the influences of the *2 and *4 SNPs were not independently significant (*2: p = 0.847, *4: p = 0.408). One intronic SNP in ABCG1 (rs492338) surpassed the exploratory significance threshold for an association with PIPN in the Caucasian cohort (p = 0.0008) but not in the non-Caucasian replication group (p = 0.54). Substantial genetic variability was observed within self-reported racial groups but this genetic variability was not associated with risk of grade 2+ PIPN. The pharmacogenetic heterogeneity within a cohort of breast cancer patients is dramatic, though we did not find evidence that this heterogeneity directly influences the risk of PIPN beyond the contribution of CYP2C8*3.}, number={1}, journal={BREAST CANCER RESEARCH AND TREATMENT}, author={Hertz, Daniel L. and Roy, Siddharth and Jack, John and Motsinger-Reif, Alison A. and Drobish, Amy and Clark, L. Scott and Carey, Lisa A. and Dees, E. Claire and McLeod, Howard L.}, year={2014}, month={May}, pages={245–254} }
 @article{brown_havener_medina_jack_krauss_mcleod_motsinger-reif_2014, title={Genome-wide association and pharmacological profiling of 29 anticancer agents using lymphoblastoid cell lines}, volume={15}, ISSN={["1744-8042"]}, DOI={10.2217/pgs.13.213}, abstractNote={ Aim: Association mapping with lymphoblastoid cell lines (LCLs) is a promising approach in pharmacogenomics research, and in the current study we utilized LCLs to perform association mapping for 29 chemotherapy drugs. Materials & methods: Currently, we use LCLs to perform genome-wide association mapping of the cytotoxic response of 520 European–Americans to 29 different anticancer drugs; the largest LCL study to date. A novel association approach using a multivariate analysis of covariance design was employed with the software program MAGWAS, testing for differences in the dose–response profiles between genotypes without making assumptions about the response curve or the biologic mode of association. Additionally, by classifying 25 of the 29 drugs into eight families according to structural and mechanistic relationships, MAGWAS was used to test for associations that were shared across each drug family. Finally, a unique algorithm using multivariate responses and multiple linear regressions across pairs of response curves was used for unsupervised clustering of drugs. Results: Among the single-drug studies, suggestive associations were obtained for 18 loci, 12 within/near genes. Three of these, MED12L, CHN2 and MGMT, have been previously implicated in cancer pharmacogenomics. The drug family associations resulted in four additional suggestive loci (three contained within/near genes). One of these genes, HDAC4, associated with the DNA alkylating agents, shows possible clinical interactions with temozolomide. For the drug clustering analysis, 18 of 25 drugs clustered into the appropriate family. Conclusion: This study demonstrates the utility of LCLs in identifying genes that have clinical importance in drug response and for assigning unclassified agents to specific drug families, and proposes new candidate genes for follow-up in a large number of chemotherapy drugs. }, number={2}, journal={PHARMACOGENOMICS}, author={Brown, Chad C. and Havener, Tammy M. and Medina, Marisa W. and Jack, John R. and Krauss, Ronald M. and McLeod, Howard L. and Motsinger-Reif, Alison A.}, year={2014}, month={Feb}, pages={137–146} }
 @article{jack_rotroff_motsinger-reif_2014, title={Lymphoblastoid Cell Lines Models of Drug Response: Successes and Lessons from this Pharmacogenomic Model}, volume={14}, ISSN={["1875-5666"]}, DOI={10.2174/1566524014666140811113946}, abstractNote={A new standard for medicine is emerging that aims to improve individual drug responses through studying associations with genetic variations. This field, pharmacogenomics, is undergoing a rapid expansion due to a variety of technological advancements that are enabling higher throughput with reductions in cost. Here we review the advantages, limitations, and opportunities for using lymphoblastoid cell lines (LCL) as a model system for human pharmacogenomic studies. There are a wide range of publicly available resources with genome-wide data available for LCLs from both related and unrelated populations, removing the cost of genotyping the data for drug response studies. Furthermore, in contrast to human clinical trials or in vivo model systems, with high-throughput in vitro screening technologies, pharmacogenomics studies can easily be scaled to accommodate large sample sizes. An important component to leveraging genome-wide data in LCL models is association mapping. Several methods are discussed herein, and include multivariate concentration response modeling, issues with multiple testing, and successful examples of the 'triangle model' to identify candidate variants. Once candidate gene variants have been determined, their biological roles can be elucidated using pathway analyses and functionally confirmed using siRNA knockdown experiments. The wealth of genomics data being produced using related and unrelated populations is creating many exciting opportunities leading to new insights into the genetic contribution and heritability of drug response.}, number={7}, journal={CURRENT MOLECULAR MEDICINE}, author={Jack, J. and Rotroff, D. and Motsinger-Reif, A.}, year={2014}, pages={833–840} }
 @article{huang_massouras_inoue_peiffer_ramia_tarone_turlapati_zichner_zhu_lyman_et al._2014, title={Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines}, volume={24}, number={7}, journal={Genome Research}, author={Huang, W. and Massouras, A. and Inoue, Y. and Peiffer, J. and Ramia, M. and Tarone, A. M. and Turlapati, L. and Zichner, T. and Zhu, D. H. and Lyman, R. F. and et al.}, year={2014}, pages={1193–1208} }
 @article{rotroff_jack_campbell_clark_motsinger-reif_2014, title={PGxClean: a quality control GUI for the Affymetrix DMET chip and other candidate gene studies with non-biallelic alleles}, volume={7}, journal={Biodata Mining}, author={Rotroff, D. and Jack, J. and Campbell, N. and Clark, S. and Motsinger-Reif, A. A.}, year={2014} }
 @article{jack_motsinger-reif_koutros_alavanja_beane freeman_hoppin_2014, title={Single-Nucleotide Polymorphism Data Support the General Unrelatedness of the Males in the Agricultural Health Study}, volume={23}, ISSN={1055-9965 1538-7755}, url={http://dx.doi.org/10.1158/1055-9965.EPI-14-0276}, DOI={10.1158/1055-9965.epi-14-0276}, abstractNote={Abstract}, number={10}, journal={Cancer Epidemiology Biomarkers & Prevention}, publisher={American Association for Cancer Research (AACR)}, author={Jack, J. R. and Motsinger-Reif, A. A. and Koutros, S. and Alavanja, M. C. and Beane Freeman, L. E. and Hoppin, J. A.}, year={2014}, month={Jul}, pages={2192–2195} }