Monthly Projects and PI Archives
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Monthly Projects and Investigator Archives

Click on the month to go to the featured project and investigator for that particular month and year.

July 2015
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Featured Project of the Month
PMT Group – Pharmacogenomics of Membrane Transporters

Figure. Discovery of functional membrane transporter variants using an integrative pharmacogenomic approach.

The PMT group is highly focused on membrane transporters that play a critical role in drug disposition and response. Using mechanistic studies in cells, knockout mouse, computational models and genetic associations studies in clinical studies, our group has developed a comprehensive functional map of genetic variants in membrane transporters from two major superfamilies, Solute Carrier (SLC) and ATP Binding Cassette (ABC) Superfamily.  Examples of our recent studies include:

  1. Role of organic cation transporters (SLC22A1, SLC22A2, SLC22A3, SLC47A1 and SLC47A2) with metformin disposition and response in human using knockout mouse and clinical resources (PMID: 25920679, 24961373, 23267855, 21956618, 24853734);
  2. Discovery of ABCG2 in allopurinol response using genomewide association study in large clinical cohort (PMID: 25676789);

  3. Role of rare variants in several SLC and ABC transporters, including ABCC4 in tenofovir-associated Fanconi syndrome (PMID: 25485598);

  4. Genetic determinants of paclitaxel-induced peripheral neuropathy using genomewide association study and polygenic modeling (PMID: 22843789, 24513692, 23204130, 24513692);
  5. Homology modeling and structure-based approaches to discover drug and small molecules that interact with membrane transporters (PMID: 23509259, 22932902, 21885739);
  6. Discovery of regulatory elements of membrane transporters (PMID: 21368754, 25275310, 21383772).

In parallel, the PMT Clinical Research group focuses on understanding the underlying genetic differences that influence metformin response,  particularly in African Americans.  Metformin is the first-line therapy to treat Type 2 diabetes.  Though it is effective at lowering HbA1c levels, there is a large degree of inter-individual variation in metformin’s effects on initial glycemic response as well as the time to disease progression, where patients no longer response to metformin monotherapy. Through PGRN III, we have collected DNA samples from 1000 African Americans who have been prescribed metformin and have HbA1c levels at baseline and after treatment. These patients are from Kaiser Permanente Northern California, Kaiser South East and University of Maryland. We are currently analyzing the genomewide association study for metformin response.  In addition, we also model the effect of metformin on disease progression using the collected HbA1c levels over time. 

Meet a PGRN Investigator

Sook Wah Yee
PMT Group

Assistant Adjunct Professor, University of California San Francisco

A member of the PMT group since 2007, Dr. Sook Wah Yee is currently Assistant Adjunct Professor in the Department of Bioengineering and Therapeutic Science at University of California San Francisco.  In collaboration with other PMT investigators, Dr. Yee has made a number of discoveries related to membrane transporters.  Notably, she and her colleagues discovered that ABCG2 (Breast Cancer Resistance Protein, BCRP) is a key transporter involved in the disposition and response to the anti-gout medication, allopurinol.  Genetic variants in this transporter associated with poor response to allopurinol.  Other discoveries include the finding that transporters for the world’s most widely prescribed anti-diabetic drug, metformin, also transport vitamin B1, thiamine.  Sook Wah is actively involved in many collaborative studies to identify membrane transporters that modulate drug response and human traits. She is especially passionate about discovering new roles of membrane transporters in targeting drugs to tissues of interest to treat human diseases. She has participated in studies of genotype-to-phenotype, candidate gene and genome-wide association related to response to metformin and other highly transported drugs. In addition, she also devoted her time within PMT as Project Director, as well as, within the PGRN-RIKEN Network Resource and PGRN-RNASeq. 

ResearchGate Profile: https://www.researchgate.net/profile/Sook_Wah_Yee

 

June 2015
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Featured Project of the Month
PARC Group – Correlations of LCL transcript statin response with in vivo statin response

 

Figure. Treatment of 426 CAP LCLs with 2 uM simvastatin for 24 hours elicits a widespread transcriptional response measured using RNA-seq.

Though statins are effective at lowering plasma LDL-cholesterol levels and cardiovascular disease risk in most people, there is a large degree of inter-individual variation in statin efficacy. In addition, statins cause adverse effects such as new-onset diabetes or myopathy in some patients. We seek to better understand the underlying genetic differences that influence statin response.

Through PARC and the PGRN, we have collected RNA sequencing data from over 400 control- and statin-exposed lymphoblastoid cell lines (LCLs) derived from participants of the Cholesterol and Pharmacogenetics (CAP) 40 mg/day 6-week simvastatin clinical trial, which included individuals of predominantly European or African American ancestry. We are currently using this RNA-seq dataset to identify genes with endogenous or statin-induced changes in expression levels or transcript structure that are correlated with other in vitro and in vivo statin response phenotypes of interest, including plasma lipid levels and glycemic traits. We are also incorporating allelic expression imbalance information into association studies of genetic variation with gene expression and transcript structure changes to identify differential eQTLs and sQTLs, respectively. 

Meet a PGRN Investigator

Elizabeth Theusch
PARC Group

Postdoctoral fellow, Children’s Hospital Oakland Research Institute (CHORI)

Dr. Theusch utilizes her knowledge of statistical genetics, computational biology, pharmacogenomics, and biology to identify candidate genetic modulators of human traits, diseases, and drug responses. She is especially interested in studying how genetic ancestry and sex interact with other genetic determinants of human phenotypes. She is excited about the promise of precision medicine and is passionate about helping people to discover more about their past, present, and future through genetic analysis.

As a member of the PARC team for several years, Dr. Theusch has been involved in many projects related to statin pharmacogenomics and has collaborated with other investigators within and outside of the PGRN. Her main focus within PARC is to analyze RNA-seq data generated from control- and statin-exposed LCLs and the corresponding genetic and phenotype data derived from clinical trial participants to identify candidate genes and pathways that may modulate statin response. In addition to her RNA-seq analyses, she has participated in studies of candidate gene and genome-wide association, ancestral differences in statin response, and splicing.

LinkedIn Profile: https://www.linkedin.com/in/elizabeththeusch


May 2015
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Featured Project of the Month
PEAR Group –  Pharmacogenomic Evaluation of Antihypertensive Responses

 

Hypertension (HTN) is the most common chronic disease for which drugs are prescribed, and the most prevalent risk factor for heart attack, stroke, renal failure and heart failure. Responses to antihypertensive drug therapy exhibit considerable inter-patient variability, contributing to poor rates of HTN control (currently 40% in the US), and frequent nonadherence and dropout from therapy. This project is directed towards the long-term goal of selection of antihypertensive drug therapy based on a patient's genetic make-up. We propose to identify genetic predictors of the antihypertensive and adverse metabolic responses to two preferred and pharmacodynamically contrasting drug classes, beta blocker (atenolol and metoprolol) and thiazide diuretics (HCTZ and chlorthalidone), given initially as monotherapy in uncomplicated hypertensive individuals (Pharmacogenomic Evaluation of Antihypertensive Responses [PEAR] participants), or as combination therapy in complicated, hypertensive heart disease patients (INternational VErapamil Trandolapril SR STudy [INVEST] participants). In addition to DNA (IBC chip and GWAS), RNA (RNA Seq on extreme responders) and untargeted metabolomics data on a subset, high quality phenotype data, including both home, clinic, and for atenolol and HCTZ treated patients, ambulatory measures of blood pressure (BP), and heart rate (HR) response, and lipid, glucose, and uric acid measures of adverse metabolic responses. Additionally we have carefully collected and adjudicated adverse CV outcomes (heart attack, stroke, all-cause death and incident diabetes) in INVEST participants. Representative findings include genetic markers in PRKCA (rs16960228) and GNAS-EDN3 (rs 2273359) associated with blood pressure response to hydrochlorothiazide (PMID 23753411), and in NEDD4L (rs414601) associated with better blood pressure response and improved cardiovascular outcomes.

PMID: 23353631

 

Meet a PGRN Investigator

Rhonda Cooper-DeHoff
PEAR Group
Associate Professor, Department of Pharmacotherapy and Translational Research, College of Pharmacy and Division of Cardiovascular Medicine, College of Medicine, University of Florida

Associate Director for the Center for Pharmacogenomics, College of Pharmacy

Dr. Cooper-DeHoff is Associate Professor in the Department of Pharmacotherapy and Translational Research in the College of Pharmacy and Division of Cardiovascular Medicine in the College of Medicine at the University of Florida. She is also the Associate Director for the Center for Pharmacogenomics in the College of Pharmacy. She is an expert in clinical pharmacology, pharmacogenomics and clinical trial conduct, with particular focus in the area of hypertension and antihypertensive drugs – both blood pressure response and adverse metabolic responses. She has particular expertise in the pharmacogenomics of thiazide diuretics and beta-blockers as well as the study of the interactions between hypertension and diabetes, especially as it related to blood pressure control.  She has had funding and numerous publications in the areas of blood pressure control in patients with heart disease and diabetes, as well as in the response and adverse response and pharmacogenomics associations of antihypertensive drugs.  Currently, she is M-PI of the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) project within the NIH Pharmacogenomics Research Network. She has effectively co-led this collaborative research group, spread over 6 institutions in the US for a decade.  She has serves as the leader of International Consortium of Antihypertensive Pharmacogenomics Studies (ICAPS) since 2012, facilitating and presiding over all consortium activities to date. She also served as the Director of the International Pharmacy Coordinating Center for the INternational VErapamil Trandolapril STudy (INVEST) which was a network of over 800 research sites in 14 countries which enrolled over 22,000 patients, including almost 10,000 Hispanic and African American participants. She served successfully in this capacity for more than ten years.More information regarding Dr. Cooper-DeHoff can be obtained at this

Profile Link: http://pharmacy.ufl.edu/faculty/rhonda-cooper-dehoff/ 


April 2015
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Featured Project of the Month
PPII Group –  Genetic Variation In Aryl Hydrocarbon Receptor (AHR) is Associated with Plasma Kynurenine Levels: A Pharmacometabolomics-informed Pharmacogenomic Study

 

Major Depressive Disorder (MDD) is the most common psychiatric disorder worldwide. It has been estimated that more than 150 million people suffer from MDD, which accounts for a significant level of Disability Adjusted Life Years (DALY). Previous studies demonstrated the importance of kynurenine (KYN) pathway metabolites in the pathogenesis of psychiatric disorders. 5HT and KYN are both metabolites of the amino acid tryptophan (TRP). TRP is converted to 5HT by the enzymatic action of tryptophan hydroxylase (TPH) 1 and 2 while, TRP can also be converted to KYN, by indolamine 2,3 dioxygenase 1, 2 (IDO1 and IDO2) and tryptophan 2, 3 dioxygenase (TDO2). The majority of the TRP is metabolized to KYN and relatively smaller amounts are used to generate 5HT.  The KYN pathway is important in the pathogenesis and drug response in MDD because: a minor increase in KYN production drastically reduces the amount of available TRP to generate 5HT. In addition, one of the downstream metabolites of KYN, quinolinic acid, is an agonist for NMDA receptors. Activation of NMDA receptors is associated with MDD.

The Mayo Clinic PGRN Center has completed an 800-patient SSRI trial in which MDD patients were treated with citalopram or escitalopram for 8 weeks. Blood samples were drawn at baseline, after 4 weeks and after 8 weeks of therapy to measure selected metabolites and blood drug concentrations. DNA was also isolated and used for genome-wide association study (GWAS) genotyping. We then carried out a GWAS for kynurenine concentration. Our studies showed that genomic variation in the aryl hydrocarbon receptor gene (AHR) was associated with baseline plasma KYN levels in MDD patients. In the nucleus, AHR forms a heterodimer with AHR Nuclear Transporter (ARNT), and the AHR/ARNT heterodimer binds to XRE sequences. However, AHR Repressor  (AHRR) competes with AHR to bind ARNT and represses AHR functions. Our studies have shown that single nucleotide polymorphisms (SNPs) in AHR are eQTLs for the AHR gene, and are associated with increased expression of IDO1 and TDO2, enzymes catalyzing the rate-limiting step for KYN biosynthesis. We have also observed that increased IDO1 and TDO2 expression were positively associated with the expression of AHR Repressor (AHRR). Therefore, our data suggests that AHRR protein can bind with the XREs present in IDO1 and TDO2 genes and apparently act as a transcription factor.

Link: http://onlinelibrary.wiley.com/doi/10.1002/cpt.48/epdf

 

Meet a PGRN Investigator

Balmiki Ray
PPII Group
NIH T32 Clinical Pharmacology Fellow at the Mayo Clinic

My research interest is to incorporate different “omics” to predict response to therapies in Major Depressive Disorders (MDD) and other diseases. Presently, Selective Serotonin (5HT) Reuptake Inhibitors (SSRIs) are the most commonly prescribed medicine to treat MDD. SSRIs prevent reuptake of serotonin by the pre-synaptic terminals, resulting in increased concentrations of 5HT in synapses. Even though many patients benefit from SSRI therapy, only 32% patients with MDD achieve complete remission after 14 weeks of SSRI therapy. This emphasizes the importance of “individualized” therapeutic strategies in MDD. The high degree of non-response to SSRI by MDD patients is largely due to phenotypic heterogeneity. Combining different “omics”, as we have at the Mayo Clinic PGRN Center, can delineate novel pathophysiological pathways. This would help us to ‘sub-classify’ patients according to their unique, individual pathophysiology, which could vary greatly within MDD patients. This same approach could be taken to several other neuropsychiatric disorders where lack of therapeutic response (or lack of available therapeutic agents) is a major concern.

LinkedIn Profile: https://www.linkedin.com/pub/balmiki-ray-md/a6/879/397

 

March 2015
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Featured Project of the Month
XGEN Group – Regulatory Polymorphisms in Human DBH Affect Peripheral Gene Expression and Sympathetic Activity

 

Figure: All liver samples with large allelic DBH mRNA expression ratios are heterozygous for rs1611115 (indicated with star).

In this study we have identified two SNPs in the gene dopamine beta hydroxylase (DBH) that interact to lower a carrier’s risk for heart attack. DBH is the rate limiting enzyme in the conversion of dopamine to norepinephrine. These neurotransmitters are vital in the central nervous system, and dopamine’s influence in the brain is well understood. In this case, however, strong genetic effects were seen in the periphery– in liver and lung tissue – and not in the brain. Variation was previously associated with circulating levels of DBH; however, the causal relationships and tissue-specific effects were unresolved. In order to detect the presence of regulatory variants, we use an allelic expression imbalance assay, in which we quantitate the expression of each allele in heterozygous samples. We found that these two SNPs, rs1108580 and rs1611115, had a combined effect on messenger RNA expression. A PheWAS analysis (phenome-wide association study; in collaboration with Marilyn Ritchie and Sarah Pendergrass at Penn State) revealed a potential association with myocardial infarction, which was replicated in additional cohorts. Because these SNPs appear to influence the local production of norepinephrine in several if not all sympathetically innervated organs, we anticipate potential effects of DBH variants on a spectrum of disorders and treatments.

Links:

PMID: 25326128

Two Frequent Genetic Variants Lower Risk for Heart Attack

Researchers identify 2 genetic mutations that interact to lower heart attack risk

Meet a PGRN Investigator

Elizabeth S. Barrie
XGEN Group
Ph.D, Postdoctoral Researcher, The Ohio State University

Dr. Barrie is a postdoctoral researcher in the Center for Pharmacogenomics at The Ohio State University. She has a passion for connecting the basic sciences to clinical research. She is interested in identifying and defining genetic factors affecting dysregulation of the sympathetic nervous system. Resolving the genetics of catecholamine signaling has broad implications in the CNS as well, as dopamine dysregulation is implicated in addiction as well as Parkinson’s, Alzheimer’s, and dementia. As the population ages, there is an increasing burden of these diseases. 

In her studies, she uses human tissue samples for molecular genetic studies to identify which specific variants are important, and then uses existing databases to validate the results clinically. Allelic differences in the expression of mRNA transcripts at a given gene locus, or allelic expression imbalance (AEI), can be measured when a single nucleotide polymorphism (SNP) is heterozygous. Allelic mRNA differences reveal the presence of regulatory variants within this gene locus (acting in cis) since AEI ratio analysis cancels out the influence of trans-acting factors. Using this approach, her research has revealed the presence of frequent regulatory variants in several dopaminergic genes.

Identifying genetic factors that predispose certain individuals to disease may allow earlier intervention and delay disease progression and may also be used to help tailor treatments for these patients. The strength of this approach lies in the identification of the functional polymorphism causing differential expression, enhancing the predictive power of biomarker tests over the use of surrogate genetic markers alone. 

Links:

https://www.linkedin.com/in/ElizabethSBarrie

http://pharmacogenomics.osu.edu

February 2015
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Featured Project of the Month
PHONT Group –  Evaluating the Use of Star Allele Nomenclature with High-Throughput Sequence Data: Implications for Research and Clinical Practice

 

The number of clinically-implemented pharmacogenomics (PGx) tests is growing rapidly. Most PGx genes use a "star allele" nomenclature system to describe known genetic variations, and this system is widely used to represent genotype.  In particular, much of the clinical decision support (CDS) that has been implemented for PGx genes uses star alleles as the basis for recommending a course of action to the provider.  While the robust representation of test results is essential for deriving accurate clinical interpretations and recommendations, the ability of the star allele nomenclature system to represent next-generation sequencing (NGS) results has not been systematically evaluated.  We developed a novel algorithm to evaluate the impact of the star allele nomenclature system when it is used with exome sequencing data.  We catalogued and quantified the errors identified in 5 genes (CYP2C9CYP2C19, CYP3A5, SLCO1B1, and TPMT) from 6503 individuals of European-American or African-American ancestry. Many of the errors we identified could negatively impact research studies and clinical practice.

 

Meet a PGRN Investigator

Robert R. Freimuth
PHONT Group
Assistant Professor of Biomedical Informatics, Department of Health Science Research, Mayo Clinic

Dr. Freimuth works at the interface of biomedical informatics and clinical genomics developing computational methods, tools and infrastructure that facilitate the translation of genomic data to clinical practice.  In particular, he is working on developing standards-based knowledge representation schemas for the pharmacogenomic domain, including gene-drug interactions and clinical recommendations that could be used as part of decision support algorithms.  The goal of his research is to help realize the promise of personalized and precision medicine through the development of interoperable systems that provide caregivers with genomic clinical decision support at the point of care. 

Within the PGRN, Dr. Freimuth is PI of the PGRN Pharmacogenomics Ontology (PHONT) network resource, which aims to create standardized representations for pharmacogenomics data.  He Chairs the Data Standardization Work Group within the PGRN Translational Pharmacogenetics Program and he is co-Chair of the Clinical Pharmacogenetics Implementation Consortium (CPIC) Informatics Work Group.  Dr. Freimuth participates in many other research networks and standards development initiatives, including eMERGE, ClinGen, HL7 Clinical Genomics, W3C Healthcare and Life Sciences, and the ONC Standards & Interoperability Framework.  He recently completed two terms as Chair of the AMIA Genomics and Translational Bioinformatics Working Group, and continues to serve that community through the role of Past-Chair.

Dr. Freimuth is an Assistant Professor of Biomedical Informatics in the Department of Health Sciences Research, Mayo Clinic.  He earned a Ph.D. in Molecular Pharmacology from Mayo Graduate School, where he studied the pharmacogenomics and functional genomics of drug metabolizing genes.  He completed a postdoctoral fellowship in the Division of Molecular Oncology at Washington University, where he developed a bioinformatics pipeline for the annotation of genomic variants.  Prior to his current position, he worked in the Siteman Cancer Center Bioinformatics Core at Washington University as a scientific domain expert for software development projects.

Links:

http://www.mayo.edu/research/faculty/freimuth-robert-r-ph-d/bio-00027248

https://www.linkedin.com/in/robertrfreimuth

 

December 2014
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Featured Project of the Month
XGEN Group –  Long-range enhancer promoter interaction regulate CYP2D6 expression

 

A highly variable and among the most important drug metabolizing cytochrome P450s, CYP2D6 has been extensively studied with respect to pharmacogenetics.  Genetic variants of CYP2D6 are currently used as biomarkers for predicting CYP2D6 metabolizer phenotype.  However, genotype and phenotype are not always consistent, suggesting the presence of hidden variants yet to be discovered.  Using newly developed genomics technologies and guided by data from the ENCODE project, Dr. Wang identified a distal enhancer located over 100kb downstream of the CYP2D6 promoter that increases CYP2D6 transcription. A frequent functional SNP inside this enhancer further increases CYP2D6 expression.  This result leads to a different interpretation of the true activity of several previously identified CYP2D6 variants and may lead to improved CYP2D6 biomarker panel.  Similar approaches can be applied to other genes related to drug therapy. 

Articles:

PMID: 23985325

PMID: 25381333 

 

Meet a PGRN Investigator

Danxin Wang
XGEN Group
Research Scientist, Adjunct Associate Professor, Associate Director
Center for Pharmacogenomics, School of Medicine, The Ohio State University

The focus of my work is to identify and functionally characterize regulatory polymorphisms in genes related to drug therapy.  I have identified and/or functionally characterized regulatory polymorphisms in several clinically important genes, including ABCB1, VKORC1, NAT1, CYP2C9, CYP3A4, and CYP2D6, each with distinct molecular genetics mechanisms.  Recently, I have begun to apply newly developed genomics technologies to identify distal regulatory regions and polymorphisms for pharmacogenetics candidate genes, including CYP2D6 and CYP3A4, two important drug metabolizing enzymes.  The goal is to develop biomarkers for personalized drug therapy while understanding fundamental mechanisms of genomic regulation pathways.

Links:

Center for Pharmacogenomics, School of Medicine, The Ohio State University

XGEN Group

 

November 2014
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Featured Project of the Month
PAAR4Kids Group –   Pharmacogenomics of asparaginase allergy

 

Asparaginase is an enzyme that is not expressed in humans that is a mainstay for the treatment of leukemia and lymphoma. Although its precise mechanism of action is somewhat controversial, it catabolizes asparagine, resulting in asparagine depletion systemically. The drug preparations of asparaginase are isolated from bacteria, and thus a major factor that limits the clinical utility of asparaginase is the development of allergic reactions to the enzyme, often accompanied by neutralizing antibodies and lower systemic activity of asparaginase. We performed genome-wide SNP array analysis of germline DNA in 1870 patients enrolled on leukemia trials at St. Jude Children’s Research Hospital (n = 541) as part of Children’s Oncology Group trials (n= 1,329). We used the SNP array data to impute human leukocyte antigen (HLA) alleles in those patients with leukemia of European ancestry, capitalizing on the Type 1 Diabetes Genetics Consortium (T1DGC) reference panel of 4,871 unrelated individuals of European ancestry, each of whom had HLA type data. Among the 1,870 patients, we imputed 39 unique HLA-DRB1 (Figure) and 15 unique HLA-DQB1 alleles.  We found that both hypersensitivity and anti-asparaginase antibodies were more common among patients with HLA-DRB1*07:01 alleles (P = 7.5 x 10-5, OR = 1.64; P = 1.4 x 10-5, OR = 2.92, respectively). In silico structural modeling revealed that high-risk amino acids, associated with the HLA-DRB1*07:01 alleles, were located within the binding pocket of the HLA protein. Using a sequence-based consensus tool, we predicted the binding affinity of the imputed HLA-DRB1 alleles for putative asparaginase epitopes, and found that allergy was more common among patients whose HLA type predicted high-affinity binding of HLA to asparaginase (P = 3.3 x 10-4, OR = 1.38).[Fernandez et al, Blood] Follow-up studies of more diverse populations using genome-wide exome interrogation confirm the importance of HLA alleles in asparaginase allergy. 

Article:

HLA-DRB1*07:01 is associated with a higher risk of asparaginase allergies.
Fernandez CA, Smith C, Yang W, Daté M, Bashford D, Larsen E, Bowman WP, Liu C, Ramsey LB, Chang T, Turner V, Loh ML, Raetz EA, Winick NJ, Hunger SP, Carroll WL, Onengut-Gumuscu S, Chen WM, Concannon P, Rich SS, Scheet P, Jeha S, Pui CH, Evans WE, Devidas M, Relling MV.

Blood. 2014 Aug 21;124(8):1266-76. doi: 10.1182/blood-2014-03-563742. Epub 2014 Jun 26.
PMID: 24970932

 

Meet a PGRN Investigator

Mignon Loh
PAAR4Kids Group
Professor of Clinical Pediatrics, University of California San Francisco

Dr. Loh is a pediatric hematologist-oncologist whose research focuses on translational studies in childhood leukemia, specifically acute lymphoblastic leukemia (ALL) and juvenile myelomonocytic leukemia (JMML).  The mission of her laboratory is identify novel genetic alterations in primary patient leukemia samples and incorporate them into algorithms for diagnosis, monitoring of disease response, and identification of novel therapeutic approaches.   Related to her work in PAAR4Kids, she is Vice Chair of the Children’s Oncology Group (COG) Biology of ALL Committee. Her COG AALL03B1 study was the largest risk stratification trial in the history of childhood leukemia research, having enrolled over 11,200 children.  AALL03B1 incorporated clinical features, genetics of leukemia blasts, germline genetics, and measures of early treatment response in order to identify the most appropriate therapies for subgroups of patients. The genetic studies started by Dr. Loh continue on with the next generation of COG ALL studies that contribute to PAAR4Kids research. These trials allow for the unbiased study of pharmacogenetic determinants of response and toxicity in thousands of patients.

Recently, she and her colleagues have identified a novel subgroup of patients with a number of kinase fusions or genetic alterations that will activate kinase signaling. Several FDA-approved drugs, such as imatinib or dasatinib, are available for such patients, and the COG is beginning to test these patients for the presence of these lesions. Dr. Loh is involved in designing and conducting clinical trials that will test the effectiveness of genomically-targeted agents added to front-line ALL regimens. Dr. Loh is keenly interested in developmental therapeutics; she served as Study Chair of a Phase I trial to assess the maximally tolerated dose of the JAK inhibitor, ruxolitinib, in children, in order to build upon laboratory observations that support the use of this compound in specific molecular subsets of leukemia. Dr. Loh is also studying phosphosignaling in ALL.  By coupling comprehensive studies on the genomic landscape for ALL with these studies of the functional consequences of genetic lesions on aberrant B-precursor cell signaling, Dr. Loh seeks to identify characteristic signaling that can be further exploited therapeutically.

Links:

http://www.lohlab.com/

http://profiles.ucsf.edu/mignon.loh

http://cancer.ucsf.edu/heroes/mignon-loh.4759

 

October 2014
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Featured Project of the Month
 PAAR Group –  Immunopharmacogenomics

 
Development of new technologies in the genomics field has enabled us to examine millions of genetic variations as well as whole-genome or -exome sequences very rapidly at the very cheap cost.  Taking the advantages of the large-scale SNP typing systems and next generation DNA sequencers, the international collaborative groups including us have been accumulating a huge body of information and successfully identified dozens of germline variations in genes susceptible to various cancers as well as thousands of somatic in various types of human cancer cells.  Although these germline genomic variations or somatic mutations have been very extensively examined in various disease conditions, the immune responses in cancer patients have not been well characterized so far.  Because of the recent successes of various immunotherapies including the antibodies targeting growth-stimulating molecules, those modulating the immunosuppressive molecules (anti CTLA4 antibody, anti-PD1 antibody, and anti-PDL1 antibody), cancer vaccine treatment, and adaptive cell therapy, there is at present no or less skepticisms in the future of immunotherapy as one of the major modalities to treat cancer.  However, in spite that we observed very good response in a subset of patients and very long survivors as the outcome of these immunotherapies, we do not understand well the underlying mechanism what kinds of immune cells contribute to the good clinical responses.  In another words, we cannot figure out clearly why the majority of patients showed no response to the treatment.  In addition, recent studies have implied that the immune response in cancer patients significantly influence to the response to chemotherapy, chemoradiation, or radiation therapy.  Furthermore, it is also very important to characterize immune responses after bone marrow transplantation for the better understanding of the molecular mechanism of GVHD (graft-versus-host disease) as well as that of tumor cell elimination by the donor immune cells.   To address these questions, we attempted to characterize differences or changes in immune cells (T-cell and B-cell repertoire) by deep sequencing of TCR (T cell receptor) and BCR (B cell receptor) with the Ion PGM sequencer, a semi-conductor type of DNA sequencer.  The technology development in DNA sequencing allowed us to obtain 5-6 million reads of TCR or BCR cDNA clones by a single experiment with the sequence read length of 400 bp that is enough to characterize the cDNA sequences covering the V, D (for beta chain), J and 5’ portion of the C region.  By applying this approach, we found the activation of certain T cell populations in patients who suffered from very severe GVHD and also that in patients who received the cancer peptide vaccine treatment.  In addition to cancer research, this approach can be applied for detailed characterization of immune responses in patients with autoimmune diseases, those with severe allergy to various foods and drugs, and those who suffer from acute or chronic rejection after organ transplantations.  

 Article:

 H. Fang, R. Yamaguchi, X. Liu, Y. Daigo, P.Y. Yew, C. Tanikawa, K. Matsuda, S. Imoto, S. Miyano, and Y. Nakamura: Quantitative T Cell Repertoire Analysis by Deep cDNA Sequencing of T Cell Receptor alpha and beta Chains using Next-Generation Sequencing (NGS) OncoImmunology, in press, 2014

Meet a PGRN Investigator

Yusuke Nakamura
PAAR Group

Professor of Medicine, Section of Hematology/Oncology
Professor of Surgery
Deputy Director, Center for Personalized Therapeutics
The University of Chicago

Our laboratory has been focusing on four projects; (1) Molecular characterization of cancer-specific enzymes, such as MELK (maternal embryonic leucine zipper kinase), that are involved in the maintenance of cancer stem cells as well as various methyltransferases that modify histones and non-histone proteins involved in carcinogenic pathways. Using such information, we have begun collaborating with pharmaceutical companies in order to screen for drugs that will target these cancer specific molecules. (2) Genomic sequencing of whole exomes as well as 400 cancer-related genes in a variety of tumors.  We are in the process of sequencing lung and bladder cancer tissues in order to discover somatic mutations which lead to identification of new drug-target molecules. (3) Characterization of the immune responses in patients who were treated with cancer peptide vaccines or those who developed GVHD (Graft-versus-host disease) after bone marrow transplantation through the use of high-throughput sequencing of T cell receptors (immunogenomics or immunopharmacogenomics). (4) Identification of genetic variants that are related to efficacy or adverse reactions of various drugs (pharmacogenomics).

The ultimate goals of our laboratory are to develop novel molecularly-targeted anti-cancer drugs and to establish the personalized treatment of cancer patients whereby they are treated with a targeted drug(s) which is not only effective but also has a minimum risk of adverse reactions. In the past year, we have achieved two very important accomplishments.  One is the identification of di-methylation of heat shock protein 70 (HSP70) at Lys-561 by SETD1A methyltransferase.  Enhanced HSP70 methylation has been detected in various types of human cancer. We found that methylated HSP70 is predominantly localized in the nucleus of cancer cells whereas most of the HSP70 protein is located in the cytoplasm. Nuclear HSP70 directly interacts with aurora kinase B (AURKB) in a methylation-dependent manner, promoting AURKB activity in vitro and in vivo and therefore enhancing the growth of cancer cells.  Our findings demonstrate a critical role of HSP70 methylation in human carcinogenesis.

The second key achievement is the development of a highly potent MELK inhibitor, OTSSP167, with IC50 of 0.41 nM by collaboration with OncoTherapy Science.  We have reported that MELK plays an indispensable role in the maintenance of cancer stem-cell characteristics and invasiveness of cancer cells through the phosphorylation of two MELK substrates, PSMA1 (proteasome subunit alpha type 1) and DBNL (drebrin-like). We have found that the compound suppresses mammosphere formation of breast cancer cells and exhibits significant growth suppression of xenografts derived from human breast, lung, prostate, and pancreas cancer cell lines in mice. This MELK inhibitor is a promising compound which looks to have the ability to suppress the growth of tumor-initiating cells and may therefore be applied in the treatment of a wide range of human cancers.

Google Scholar Citations Link

Lab Link

August 2014
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Featured Project of the Month
NWAP Group –  "Exploring Pathways to Trust: A Tribal Perspective on Data-sharing"

 
Data-sharing policies promoted by the National Institutes of Health (NIH) aim to maximize public benefit derived from genetic studies by increasing research efficiency and the use of a pooled data resource for future studies. Although broad access to data may lead to benefits for populations underrepresented in genetic studies, such as indigenous groups, tribes have ownership interest in their data. The Northwest-Alaska Pharmacogenetic Research Network (NWA-PGRN), a partnership involving tribal organizations and universities conducting basic and translational pharmacogenetic research, convened a meeting in Feb 2012 to discuss the collection, management, and secondary use of research data, and the processes surrounding access to data stored in federal repositories.  Meeting attendees included representatives of the three NWA-PGRN tribal partners, other Northwest tribal organizations, university-based researchers, scholars whose work addresses questions related to tribal human subjects and other research processes, and NIH representatives.  The goal of the meeting was to exchange information and perspectives about data sharing in research involving tribal-university partnerships, and to identify knowledge that would be helpful to tribal authorities, researchers and NIH officials in preparing for discussions about data sharing. 

Outcomes of these discussions showed that data sharing may result in benefits for tribal communities, but the risks must be acknowledged and addressed as part of the research partnership agreement. Tribes have ownership interest in their data and traditions, and past experiences with genetic research have made tribes cautious of broad data-sharing agreements. There is strong support for efficient research processes that expedite the time required to generate benefits from collaborative research despite serious concerns about the potential for harm, but moving forward is dependent on efforts by the scientific community to build and maintain trust. Developing data sharing strategies and protocol may be an appropriate step towards this objective, yet procedures to do so must take into account tribal sovereignty and need for accountability. Tribes may use different mechanisms to ensure appropriate oversight of research – e.g., research review committees, tribally based IRBs, review of draft manuscripts, etc. The key elements are transparency of the data-sharing obligations and options, and the opportunity for tribal authorities to review and approve research involving tribal samples or data.           

There are several specific ways in which accountability could be encouraged by NIH as part of the research process. The NIH could develop mechanisms focused on consultation between researchers, research institutes, and the tribal leadership and community to negotiate data-sharing plans in the context of the study period, or through stand-alone planning grants. The meeting group suggested encouraging NIH and other government funders to include dollars designated for consultation with tribes prior to, and throughout the research period. Grant proposals could also require a dissemination plan that specifies how researchers will provide information back to the community during the project period and after completion of the research, which could take the form of resources for community meetings and travel to public venues for tribal representatives and researchers. The group noted that this step of returning to communities could be combined with a research partnership evaluation component that would benefit the NIH in identifying the elements of collaboration that strengthen trust and facilitate respectful negotiation. The group also felt that tribes should have an opportunity to give input related to, and be involved in, the review process for secondary research uses of tribal data.

In the contemporary era, federal policies favoring scientific discovery and innovations in biotechnology must be moderated by respect for tribal sovereignty. In any tribal-university partnership, it will be necessary to establish a relationship of trust in which tribal laws and cultural interests are given deference, and in which an ethic of respectful negotiation is used to secure the rights of the tribe and the interests of the research community in promoting forms of knowledge that are truly of benefit to all.

Link to article:  http://www.ncbi.nlm.nih.gov/pubmed/24830328

James RD, Tsosie R, Sahota P, Parker M, Sylvester I, Lewis J, Klejka J, Muzquiz L, Olsen P, Whitener R, Burke W. Exploring Pathways to Trust: A Tribal Perspective on Data Sharing. Genetics in Medicine. PMID 24830328.

 

Meet a PGRN Investigator

Rosalina James
NWAP Group
Assistant Professor, Department of Bioethics and Humanities
Center for Genomics and Healthcare Equality
University of Washington

Dr. Rosalina (Rose) James’ interests involve developing capacity for interdisciplinary tribal health research practices and policies. As part of these efforts, she has led a number of activities that exposed American Indians and Alaska Natives and college students to health science careers, community based participatory research (CBPR), and genetics. She currently directs two cores, the Training core and the Indigenous Genomics Alliance core, for the NIH/NHGRI-sponsored Center for Genomics and Healthcare Equality (CGHE) at the University of Washington. Under the latter CGHE core, she co-chairs a working group entitled Advancing Indigenous Research Ethics in Practice and Policy, which aims to establish collaborative processes between local tribal organizations and university research divisions. Her scholarship also includes dissemination of research information to community audiences through diverse peer-reviewed venues, such as publications for the online Genetics Resource Guide for tribal leaders developed through the National Congress of American Indians Policy Research Center. 

Link to full profile:

http://depts.washington.edu/bhdept/facres/rdjames_bio.html

July 2014
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Featured Project of the Month
TPP Group –  "The 1200 Patient Project"

 

“The 1200 Patients Project”, a clinical research effort within the Center for Personalized Therapeutics at The University of Chicago, aims to determine whether and how preemptive pharmacogenomic test information might be incorporated into routine clinical treatment decisions by examining 1200 physician-patient pairs.  The primary key feature of the project is the preemptive nature of the genotyping for all patient participants, eliminating the significant barrier of time delays in the receipt of pharmacogenomic results.  Similar to the TPP, our project aims to have the additional benefit of overcoming other significant barriers to routine pharmacogenomic clinical implementation by studying potential limitations like poor physician knowledge about drug-gene relationships, understanding the level of evidence necessary for associations to have clinical impact, and the desire by physicians for clear guidelines about test result interpretation.

The project is prospectively enrolling and preemptively genotyping (using a custom-designed panel of variants carefully selected and validated for their clinical pharmacogenomic role) 1200 adults receiving outpatient care at The University of Chicago.  Patient-specific results are available to enrolled ‘early adopter’ study physicians (representing a diverse set of medical specialties) through a created research portal, or genomic prescribing system (GPS), which provides instantaneous pharmacogenomic guidance.  Encounter-level data are being collected for thousands of visits.  It is hypothesized that inappropriate or high risk medications will be less likely to be prescribed to genetically at-risk patients when pharmacogenomic results are preemptively known.

Publications Related to the Project:

http://www.ncbi.nlm.nih.gov/pubmed/24616296

http://www.ncbi.nlm.nih.gov/pubmed/22929923

http://www.ncbi.nlm.nih.gov/pubmed/24024891

Additional Link:

http://cpt.uchicago.edu/

Meet a PGRN Investigator

Peter H. O’Donnell
TPP Group
Assistant Professor, Department of Medicine
Associate Director for Clinical Implementation
Center for Personalized Therapeutics
Committee on Clinical Pharmacology and Pharmacogenomics
The University of Chicago

Dr. O'Donnell has an interest in the study of pharmacogenomics and pharmacogenomic clinical implementation, which involves considering each patient's genetic profile when determining therapeutic decisions. Dr. O'Donnell serves as principal investigator of the "1200 Patients Project," a clinical study operated through the Center for Personalized Therapeutics at the University of Chicago. In this role, he leads an initiative exploring the benefit of incorporating broad pharmacogenomic testing into routine clinical practice for patients with any type of disease.

A practicing oncologist specializing in the treatment of genitourinary malignancies, specifically bladder cancer, Dr. O'Donnell leads several additional ongoing research projects. Currently, he is investigating how genetic factors affect chemotherapy drug outcomes -- specifically for patients receiving treatment for bladder cancer.  In particular, he is investigating how pharmacogenomic markers might be used to inform selection of patients who should preferentially receive chemotherapy as part of multimodal treatment for bladder cancer.  He is also exploring the discovery of new pharmacogenomic markers for patients receiving the widely-used chemotherapy drugs cisplatin and capecitabine. 

Link:
http://www.uchospitals.edu/physicians/peter-odonnell.html

June 2014
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Featured Project of the Month
XGEN Group –  RNA-Seq Group: Central Nervous System- XGen subproject 

 

The goal of the CNS-XGen RNA sequencing sub-award is to evaluate the complexity and regulation of RNA expression in the different regions of the human brain, and to assess the effects of chronic nicotine exposure on this gene expression.  The approach is to use deep transcriptome sequencing to analyze RNA transcription in 10 different brain regions in 10 individuals.  Brain tissues from an equal number of smokers and non-smokers have been sequenced.  Recognizing that mRNA expression alone does not reveal the entire complexity  of gene regulation the cDNA libraries are prepared using techniques that capture all expressed RNA transcripts including existing intronic, intergenic and long non-coding regions. We have also begun to prepare and sequence small and microRNA’s in brain tissues and regions from the same individuals.  In addition, DNA from all 10 individuals has been genotyped for ~ 5 million common variants using the Illumina Omni5 + exome bead chip.  Along with quantitation of gene expression, the bioinformatics group is developing algorithms for analysis of splice isoforms, allelic expression and poly adenylation sites from the deep sequencing data. These potential regulatory aspects all contribute to the underlying genetics of regulation of RNA expression and provide credible targets for predictive and or preventative biomarkers and drug targets.  Development of analytic and bioinformatics methods to fully understand and utilize the additional data on non-coding and other regulatory transcripts revealed by this broad transcript detection is a critical next step in fully understanding the underlying genetics of the regulation of brain gene expression.

We have made excellent progress in generating a human brain tissue transcriptome database, in collaboration with the PGRN RNAseq project and the CNS Working Group. Comparison of regional brain expression levels with GWAS associated neurocognitive traits may provide a means of honing in on the most appropriate genes for further investigation in drug targeting and drug development.

1: Smith RM, Webb A, Papp AC, Newman LC, Handelman SK, Suhy A, Mascarenhas R, Oberdick J, Sadee W. Whole transcriptome RNA-Seq allelic expression in human brain. BMC Genomics. 2013 Aug 22;14:571. doi: 10.1186/1471-2164-14-571. PubMed PMID: 23968248; PubMed Central PMCID: PMC3765493.

2: Webb A, Papp AC, Sanford JC, Huang K, Parvin JD, Sadee W. Expression of mRNA transcripts encoding membrane transporters detected with whole transcriptome sequencing of human brain and liver. Pharmacogenet Genomics. 2013 May;23(5):269-78. doi: 10.1097/FPC.0b013e32835ff536. PubMed PMID: 23492907.

3: Geier EG, Chen EC, Webb A, Papp AC, Yee SW, Sadee W, Giacomini KM. Profiling solute carrier transporters in the human blood-brain barrier. Clin Pharmacol Ther. 2013 Dec;94(6):636-9. doi: 10.1038/clpt.2013.175. Epub 2013 Sep 5. PubMed PMID: 24013810; PubMed Central PMCID: PMC3906042.

Meet a PGRN Investigator

Audrey Papp
XGEN Group
Technical Director, Pharmacogenomics Core Laboratory, The OSU College of Medicine, Center for Pharmacogenomics 

Audrey Papp is the Technical Director of the Pharmacogenomics Core Laboratory in the Ohio State University College of Medicine Center for Pharmacogenomics.  She is a research specialist in Pharmacology with expertise in Pharmacogenomics and Molecular Pathology.   Her expertise was instrumental in developing new methods and approaches geared towards discovery of functional genetic biomarkers.  Most recently Audrey played a leading role in implementation of Next Generation Sequencing in the Pharmacogenomics Core Laboratory.  Consequently, the OSU Pharmacogenomics Core Lab has been designated as an Ion Torrent Certified Service Provider, with acknowledged expertise in Exome and RNA sequencing as well as other molecular techniques. The Pharmacogenomics Core Lab is currently using the Life Technologies SOLiD 5500WF, Ion Torrent PGM, and Ion Proton deep sequencing platforms.  

In her career, Audrey has been successful at design and implementation of new concepts and programs in both clinical and research areas. She has been directing operations of The Pharmacogenomics Core Lab since it's inception in 2002.  Audrey has extensive experience with sample acquisition and preparation, assay development, DNA and RNA sequencing, and experimental validation.  She mentors students and fellows, and guides the technical operations of the laboratory.  Because of her experience and scientific contributions, Audrey was granted Principle Investigator status at OSU in 2010.  Previously, she was supervisor of the Clinical Molecular Pathology Laboratory in the Department of Pathology at The Ohio State University Medical Center.  She played a key role in developing the test portfolio, and establishing the Molecular Pathology Laboratory as a CLIA certified lab.   

Audrey’s personal strengths include teaching, conceptual thinking, operations, and management - in essence working with people, and making things work. In addition to participation in both clinical and research aspects of health care, she is a contributing author on over 80 papers.

Links:

From the Advances in Genome Biology and Technology Meeting, Life Technology Workshop, February 2013  “Ion Ampliseq RNA Panels for Biomarker Discoveryhttp://www.youtube.com/watch?v=d2KCBbTqC0s

RNA-SEQ WITHIN REACH.  Live transcriptome sequencing webinars 2013 RNA Sequencing for Biomarker Discovery” webinar with OSU’s Audrey Papp http://find.lifetechnologies.com/sequencing/transcriptomewebinar/lt-ion/webinar-registration-277765-4491HJ.html  Webinar 2

May 2014Back to Top
Featured Project of the Month
PGPop Group –  PharmacoGenomic discovery and replication in very large patient POpulations (PGPop)

 

PharmacoGenomic discovery and replication in very large patient POpulations (PGPop) was conceived as a network resource to provide to PGRN an opportunity to identify large groups of real world patients with known drug exposures and outcomes for pharmacogenomic study in a clinical setting by mining Electronic Health Record (EHR) data.  EHR data can be used for disease or drug-response discovery.  EHR data also allows for the inverse experiment, a hypothesis-free scan of phenotypes associated given genetic variants, called a phenome-wide association study.

Each PGPop node includes a very large collection of patient data, drug exposures, and outcomes, and they share the general characteristic that they include "all comers" rather than more narrowly defined clinical trial populations. Some consortium nodes include large DNA collections in place, while others cover millions of lives and have committed to an infrastructure to collect DNA from patients with identified phenotypes. The participating systems include:

  • BioVU , the Vanderbilt DNA databank that currently links nearly 180,000 de-identified electronic health records (EHR) records with DNA obtained from discarded blood samples
  • The Marshfield Clinic Personalized Medicine Research Project (PMRP) that includes DNA from almost 20,000 individuals coupled to an EHR that extends back to the 1960s
  • The Crimson Project that can provide DNA linked to de-identified medical records to Harvard Partners investigators from over 800,000 patient visits annually.
  • BioBank Japan, a resource that includes DNA and other biospecimens in >300,000 subjects.  Clinical data are collected by medical coordinators at each of the 66 participating hospitals that cover 2% of all Japanese hospital beds (~25,000).
  • The integrated pharmacoepidemiology program of 13 health plans participating in the HMO Research Network Center for Education and Research in Therapeutics (CERT); these plans together cover 11,000,000 lives. 
A recent large-scale PheWAS for genome-phenome discovery: http://www.ncbi.nlm.nih.gov/pubmed/24270849
Meet a PGRN Investigator

Joshua C Denny
PGPop Group
Associate Professor, Departments of Biomedical Informatics and Medicine
Vanderbilt University 

My primary research foci are developing computational methods to identify phenotypes from electronic health records (EHR), performing genomic and pharmacogenomic analyses using EHR-linked genomic data, and creating the resources needed to translate this knowledge into clinical practice.  I have been involved with Vanderbilt’s Pharmacogenomics of Arrhythmia Therapy (PAT) as well as PGPop and Pharmacogenomics of Rheumatoid Arthritis Therapy (PhRAT).  We have used EHR data to identify diseases and drug-response traits for genetic association studies.  At Vanderbilt, I have also been involved with the PREDICT program, which is using pharmacogenetic data embedded within the EHR to guide care using genomic decision support.  We believe use of EHR data is an important tool to rapidly accrue study populations, capture rare severe adverse events, and help elucidate genetic mechanisms.

Full Profile Link

 

 

 

 

 

 

April 2014Back to Top
Featured Project of the Month
BCM-HGSC Group –  Human Genome Sequencing Center 

 
In collaboration with the other two members of the PGRN Deep Sequencing Resource (DSR) and PGRN Network Members, the Baylor College of Medicine’s Human Genome Sequence Center (BCM-HGSC) played a leading role in the design of the PGRN-seq custom capture sequencing platform. The platform targets 84 high-value genes known to be associated with drug efficacy and toxicity in a high-throughput, economic and thorough manner. Working closely with our partners at NimbleGen, solution based hybrid selection capture probes were designed for each gene including every known gene model exon, 2kb upstream and 1 kb downstream as potential regulatory regions and the Affymetrix DMET and Illumina ADME genotyping loci not already accounted for. Multiple rounds of testing across the DSRs using 32 multi-ethnic Coriell trios demonstrated outstanding concordance with variant sites defined by the Thousand Genomes Project. We further tested with 96 samples from the PAPI-2 group and again demonstrated better than 99% percent concordance at previously assayed common variant sites as well as demonstrated the unique utility of the platform by identifying a number of unknown rare sites in this sample set. Using these datasets, we once again worked with NimbleGen to produce a rebalanced version of the platform that was used by the DSRs to sequence a set of Coriell samples for the CDC’s Genetic Testing Reference Materials Coordination Program (GeT-RM).

While PGRN-seq performs very well, a single platform aimed at variant characterization may be inadequate at a few very important loci. The BCM-HGSC is collaborating with the PNAT, PAAR4Kids and NWAP network laboratories on an pilot approach that combines whole region capture and Illumina sequencing with long read regional capture sequencing on the Pacific Biosciences instrument to characterize variants across the difficult 300 kb CYP2A6/CYP2B6 region. Preliminary results look promising and we look forward to expanding the scope of this approach as well as developing further resources aimed at exploring drug-genome phenotypes and translation of these tools to clinical settings.

Meet a PGRN Investigator

Xiang Qin
BCM-HGSC Group
Assistant Professor, Department of Molecular and Human Genetics
Baylor College of Medicine

Dr. Xiang Qin is a faculty member within the Human Genome Sequencing Center at Baylor College of Medicine (BCM-HGSC). Dr. Qin has been actively participating in PGRN projects for the past three years by bringing his extensive bioinformatics and programming skills to bear on numerous challenges encountered in the projects undertaken by the BCM-HGSC Deep Sequencing Resource (DSR), including PGRN-seq and numerous RNA-seq and GWAS-directed resequencing projects.

Dr. Qin’s research interests are aimed at the development of QC and analysis methods and pipelines for drug response-related genomic variant detection and annotation. Dr. Qin is pursuing the developing of analysis methods for gene expression profiling using RNA-seq to identify gene expression patterns that are associated with allele-specific drug response and efficacy. He is also working on multi-“omics” platform data integration methods to identify genomic markers for precision medicine. With each of these efforts, Dr. Qin hopes to advance Baylor’s renowned application of genomics to the practice of medicine.

 

 

 

 

March 2014
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Featured Project of the Month
PGBD Group –  Pharmacogenomics of Bipolar Disorder

 

Bipolar disorder is a common psychiatric disorder characterized by extreme alternation in mood states from the highs of mania to the lows of depression. It is associated with substantial morbidity, loss of productivity and a 17% lifetime suicide risk. Lithium was the first mood stabilizer medication that treated both the highs and lows and more importantly kept patients moods stable and prevented episodes. Subsequent to its introduction in the 1970’s, many anticonvulsants have been shown to also have mood stabilizing properties, but in head to head studies, lithium remains the best in overall effectiveness, particularly in reducing suicide. A subset of bipolar patients have a very robust response to lithium with virtual elimination of symptoms. These patients may have different characteristics and represent a neurochemically and genetically distinct form of illness. Currently there is no way to identify these good responders in advance and patients frequently require numerous medication trials until an effective treatment is identified. These trials can extend for months to years during which time the patient suffers and is exposed to suicide risk. The goal of this project is to identify genes associated with a good response to lithium. This will serve two important goals. It will guide the development of a DNA test panel to predict lithium response. It may also identify genes that predispose to a lithium responsive form of illness, thereby informing regarding the pathways and mechanisms of illness. 700 Bipolar I subjects are being studied at 11 international clinical sites. Each subject is screened and started on lithium as they enter the stabilization phase of the study. During this 4 month period, they are stabilized on lithium and tapered off of other psychotropic medications. They then enter a 2 year long maintenance phase where they are followed at 2 month intervals in order to detect a relapse. The time to relapse can then be used as a quantitative measure of lithium response and compared to genetic variation at a select subset of genes. As the planned sample may be small for genomewide association methods, it is important to select a smaller set of genes to test first. These sets will be derived from an international sister study, the Consortium for Lithium Genetics, ConLiGen, which has used retrospective historical methods of determining response and is currently completing a genomewide association study of 3000 subjects. Another sources of genes to examine is from biological experiments using induced pluripotent stem cells (iPS). In collaboration with Dr. Gage and colleagues at the Salk Institute, iPS cell lines have been established for subjects observed prospectively to be responders or non-responders. These lines were subsequently differentiated into neurons and treated both with and without lithium at clinical concentrations for one week. Gene expression is presently being measured by RNA-seq and genes will be sought that change expression in response to lithium for responders but not non-responders. These genes will then be genotyped or sequenced in the full set of 700 subjects to test for genetic variants associated with response. In this way both biological and genetic information are integrated in order to better identify genes and disease mechanisms.

Journal Articles: PMC3542199, PMC3925336, PMC3349991, PMC3128104, PMC2889682, PMC3748365, PMC3636100

Meet a PGRN Investigator

John R. Kelsoe
PGBD Group
Professor
Director, Laboratory of Psychiatric Genomics Department of Psychiatry
Institute for Genomic Medicine
University of California San Diego

Dr. Kelsoe’s longstanding research focus has been the genetics of bipolar disorder and lithium response. Dr. Kelsoe is presently the director of the Laboratory of Psychiatric Genomics and a member of the UCSD Institute for Genomic Medicine.

Dr. Kelsoe directs the Bipolar Genome Study (BiGS) which is conducting whole genome sequencing studies of bipolar families. He also co-directs the Psychiatric GWAS Consortium for Bipolar Disorder (PGC-BD) which is an international collaborative effort designed to identify genes for bipolar disorder in a sample of over 10,000 patients.

Dr. Kelsoe also directs the Pharmacogenomics of Bipolar Disorder Study (PGBD) which is part of the Pharmacogenomics Research Network. The goal of this study is to identify genetic variants that are associated with good response to lithium. This study includes a prospective clinical trial of lithium over 24 months and gene identification by sequencing and iPS neuronal models.

Project Website

Profile Website

February 2014
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Featured Project of the Month
UW-NEXTGEN Group –  PGRNseq: Targeted Pharmacogenetic Sequencing for Research and Clinical Use

 

Understanding the genetic basis of an individual’s response to therapeutic drugs (pharmacogenetics) is a unique area of research with significant translational impact for medicine. Known genetic variants with effects on important clinical phenotypes, including clopidogrel efficacy and warfarin maintenance dose, highlight the potential translational utility of pharmacogenetic analysis. The emergence of next-generation sequencing offers a promising new tool to explore the links between drug response and genetic variation, both common and rare. To characterize the full spectrum of variation in human populations and to evaluate how these differences are linked to drug responses, the Pharmacogenetics Research Network (PGRN) has developed a new platform, PGRNseq, a low-cost, high-throughput next-generation sequencing platform centered on the custom capture of 84 genes with strong associations to drug phenotypes. Sequence captured from these genes includes both coding regions and 2kb upstream to assess variation within regulatory regions. PGRNseq’s design includes known variants present on other commercially available pharmacogenetic platforms for backwards compatibility with existing datasets. To test the performance and accuracy of this new tool, we sequenced 32 diverse trios from HapMap and 1000Genomes using the PGRNseq platform, as well as 94 patient liver samples. In uniquely mapping regions, we found 99.9% genotype concordance at all overlapping sites with orthogonal datasets from HapMap and 1000Genomes. PGRNseq is currently being deployed by the eMERGE network to generate pharmacogenetic sequencing data for 9000 individuals for deposit into electronic medical records alongside extensive phenotype information. Initial data from the first 300 samples reveals a mean of 182 novel gene-altering variants, including newly-described truncating variants in important pharmacogenes such as CYP2C19 and DPYD. We have also developed a more focused platform targeting all 13 genes with known, actionable pharmacogenetic variation using Molecular Inversion Probes (MIPs), which allow for large-scale variant typing and discovery with a significant cost benefit over traditional capture methods. We are currently testing this new platform on our set of 32 HapMap Trios, and testing both platforms on a new cell-line-based reference panel assembled by the CDC containing rare alleles with known pharmacogenetic effects. 

Link

Meet a PGRN Investigator

Adam Gordon
UW-NEXTGEN Group
Graduate Student, University of Washington, Department of Genome Sciences

Adam Gordon is a graduate student in University of Washington’s Genome Sciences department. During his time in the lab of Dr. Deborah Nickerson, Adam has analyzed thousands of deeply sequenced human exomes in order to characterize rare genetic variation within genes that play a role in drug efficacy and toxicity. As a part of the UW-NGS group, and in conjunction with the other PGRN Deep Sequencing Resources, Adam has helped develop the PGRNseq platform for variation discovery and typing in large patient cohorts. Additionally, he is leading the effort to develop additional pharmacogenetic sequence capture technologies for future large-scale sequencing efforts.


Initially drawn to the fields of evolutionary biology and population genetics, Adam’s research interests have shifted towards understanding the clinical significance of rare genetic variation and developing technologies to assess this variation. As clinical sequencing becomes standard medical care, we will continue to unearth new, unique genetic variants in genes known to play a role in drug efficacy. Through understanding the patterns of variation in these genes, Adam hopes to provide researchers and clinicians a framework for understanding and interpreting new pharmacogenetic variants that can drive treatment and prescription plans for more targeted, effective patient care.

Link to website

January 2014
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Featured Project of the Month
WU-NGS Group – Sequencing Allelic Diversity at the CYP2D6 Gene Locus

 

The CYP2D6 gene encodes an enzyme from the cytochrome P450 pathway that is important in drug metabolism, and thus is of interest for pharmacogenomic studies.   The DNA sequencing of this gene is difficult due to the occurrence of complex rearrangements and a high sequence homology to two CYP2D6 pseudogenes that reside in close proximity in the genome.  These complexities are likely to vary within and across ethnic populations, and in order to better interpret genomic studies, a clearer picture of the structural makeup and diversity of the region is critical.  Most high throughput, cost efficient sequencing methods today yield relatively short sequence reads and read pair distances, thereby complicating read mapping to these complex and repetitive regions.  With a clearer understanding of the allelic diversity and of potential structural arrangements, the use of short read sequencing technology and interpretation of the data will likely be more tenable.  

In order to improve our understanding of this genomic interval, we are sequencing 24 large insert (~40kb) fosmid clones identified from libraries constructed from the genomes of ethnically diverse individuals. 

By isolating these genomic regions in manageable 40kb single haplotype fosmid-sized pieces, and by employing both conventional, long read technologies (ABI 3730 and Pacific Biosciences SMRT Sequencing system) and manual assembly improvement techniques (aka “finishing”), we will unambiguously resolve these regions, and thus better understand the allelic and structural diversity contained in these clones.

The resulting high quality reference sequences are being submitted to NCBI as a community resource, and will be provided as alternate tracks in the NCBI human reference genome sequence.  By isolating these haplotypes, genes and pseudogenes through fosmid clone sequencing, we will enable subsequent elucidation of SNPs to structural variants (copy number) and gene vs. pseudogene copies, which could potentially be exploited in interpretation of the short read sequencing technology. 

The effort to improve, build and represent allelic diversity in the human reference genome is an activity that is part of the Genome Reference Consortium(GRC).   Additionally, we hope to continue efforts similar to this across other allelically diverse and complex regions of the genome, and community input is welcome through the provided link.  

http://www.ncbi.nlm.nih.gov/projects/genome/assembly/grc/

Meet a PGRN Investigator

Robert (Bob) Fulton
WU-NGS Group
Director of Project Development and Management, The Genome Institute at Washington University

Robert (Bob) Fulton is the Director of Project Development and Management at The Genome Institute at Washington University School of Medicine.  His role is to deliver genomic solutions to a broad range of clinical and research questions. Bob joined The Genome Institute (TGI) in 1994, and he has almost 20 years of extensive experience in the generation of DNA sequence and analysis. Throughout his time at TGI, he has led the production-based targeted sequence efforts as well as the sequence improvement (finishing) pipelines responsible for genome sequence refinement.

The skills and expertise he has developed over the years are now applied to the development of sequence-based strategies designed to answer critical questions associated with the use of genomics in the clinical and research environments. As part of this role, he continues to be a leader in the targeted sequence efforts, which includes variant validation, extension, and de novo discovery activities through targeted sequence techniques.

In addition to this, Mr. Fulton is still actively involved in sequence improvement activities. TGI continues to play a significant role in the improvement of the human and mouse genomes. Mr. Fulton is a major leader in the Genome Reference Consortium and TGI maintains one of the only labs in the country dedicated to this effort.

Link to full profile

November 2013
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Featured Project of the Month
PAPI-2 Group –  Proposed Paradigm for Pharmacometabolomic Studies.

While aspirin is a well-established antiplatelet agent, the mechanisms of aspirin resistance remain poorly understood. Metabolomics allows for measurement of hundreds of small molecules in biological samples enabling detailed mapping of pathways involved in drug response. With this in mind we defined the metabolic signature of aspirin exposure in subjects during a short-term aspirin intervention. Many metabolites, including known aspirin catabolites, changed after exposure to aspirin but pathway enrichment analysis identified purine metabolism as significantly affected by drug exposure. Furthermore, purines were associated with aspirin response, and poor responders had higher post-aspirin adenosine and inosine levels than did good responders. Using an approach we’ve coined "pharmacometabolomics-informed pharmacogenomics", we queried genetic variants in purine metabolosim genes for association with platelet aggregation response to aspirin and identified genetic variants in adenosine kinase that were associated with aspirin response. Combining metabolomics and genomics allowed for more comprehensive interrogation of mechanisms of variation in aspirin response.

Link to article

Meet a PGRN Investigator

Laura Yerges-Armstrong
PAPI-2 Group
Assistant Professor, Department of Medicine and Department of Epidemiology & Public Health, Program in Personalized and Genomic Medicine

Dr. Yerges-Armstrong is an epidemiologist whose research focus is the molecular epidemiology of complex diseases.  Throughout her career she has worked on a number of large epidemiological studies of aging and is actively involved in projects from the Amish research program addressing the genetic underpinnings of complex traits. As part of this research, she has worked with a number of consortia efforts including: the Genetics of Liver Disease (GOLD) consortium, the Genetic Factors for Osteoporosis (GEFOS) consortium, the Cohorts of Heart and Aging Research in Genetic Epidemiology (CHARGE) musculoskeletal group, the Reproductive Genetics (ReproGen) consortium and the Study of Underlying Genetic Determinants of Vitamin D and Highly Related Traits (Sunlight) consortium.

Since 2010 Dr. Yerges-Armstrong has been involved with the pharmacogenomics research projects at the University of Maryland.  In addition to genomic investigations, her work has focused on the analysis of metabolomic data in two anti-platelet intervention studies in the Old Order Amish: the Heredity and Phenotype Intervention (HAPI) Heart Study and the Pharmacogenomics of Antipatelet Intervention (PAPI) Study.

Link to full profile

October 2013
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Featured Project of the Month
PharmGKB Group –  The Pharmacogenomics Knowledge Pyramid.

 

The Pharmacogenomics Knowledge Pyramid was prototyped in 2012 in order to illustrate the priorities of PharmGKB.  The foundation of the pyramid is the primary pharmagenomic literature from which pharmacogenomic knowledge is extracted via automated processes or manual curation.  This is the most basic information contained in PharmGKB, serving as the basis for the knowledge found in the other layers of the pyramid. Manually curated literature is annotated and represented in a standardized format, linking genes and variants to drugs and phenotypes. Aggregated annotations form the basis for variant important pharmacogene summaries (VIPs) and drug-centered pathways.  Annotations on specific variant-drug combinations are also grouped together to provide genotype-based summaries.  PharmGKB’s clinical implementation efforts are at top of the pyramid, including genotype-based drug dosing guidelines and data consortia efforts.

Link to PharmGKB

Meet a PGRN Investigator

Teri E. Klein 
PharmGKB Group
Director of PharmGKB

 

Russ B. Altman
PharmGKB Group
Professor of Bioengineering, Genetics, Medicine, and (by courtesy) Computer Science 

Russ Altman and Teri Klein have lead the PharmGKB since its inception in 2000. Initially, Russ served as the PI, and Teri as the Director.  In the past year, Teri has also been appointed as Co-PI, and so the two work closely together supervising all the activities of the PharmGKB:  building the knowledgebase and website, performing basic informatics research relevant to pharmacogenomics and PharmGKB, assembling and participating in data sharing consortia, and working on the CPIC guidelines.   

Before joining Stanford, Teri was on the faculty at UCSF.  She has a BA in Chemistry/Biology from UC Santa Cruz, and PhD in Medical Information Sciences from UCSF.  Before focusing her attention on pharmacogenomics, she had a research program focusing on computational chemistry, the structure of biological molecules important for disease, particularly collagen and genetic diseases associated with mutations in collagen.  She also worked on computational drug docking and structure-function relationships.

Russ has a AB in Biochemistry from Harvard, a PhD in Medical Information Sciences from Stanford, and an MD from Stanford.  He is board-certified in internal medicine.  Before working in pharmacogenomics, he worked on 3D protein structure determination from NMR and other noisy sources of structural information, with a focus on ribosome modeling.  He also worked on natural language processing technologies for complementing high-throughput RNA expression data, and methods for characterizing and recognizing protein active sites. 

The PharmGKB is mostly staffed by professional staff, including curators, developers and technical folks.  The associated research laboratory has students and post-docs working on projects of potential relevance (often on a long time scale...) to pharmacogenomics.  Current projects include:  exome sequencing of high/low dose warfarin patients, NLP to extract gene-drug relationships,  whole genome sequencing of Iranian-descent populations, generating high quality systems pharmacology pathways, predicting the expression of genes in response to drugs, drug design, drug-repurposing, determining druggability, and methods for interpreting underpowered drug-oriented GWAS studies, among others.  Almost all of the projects involve drugs and are dependent on having (or gaining) a molecular understanding of drug response, which provides a powerful unifying theme tying together the PharmGKB and the lab research program.

September 2013
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Featured Project of the Month
P-STAR Group –  Pharmacogenomics of Statin-Induced Myopathy.


Statins are the most commonly prescribed drug in the United States and significantly decrease the risk for cardiovascular disease.  Statin therapy can result in varying degrees of myotoxicity, occurring within 20% or more of treated patients.  These events range from very severe rhabdomyolysis to low-level myalgia, and may be a primary cause of cessation and non-compliance.  In the Bush Lab, Laura Wiley is using BioVU, the Vanderbilt DNA Biobank to examine myopathy events in response to statin therapy with the goal of identifying genetic factors that influence myopathy risk.  The ultimate goal is to both predict patients who are at increased risk of these side effects, and to understand the pharmacodynamics and pharmacokinetics responsible for the muscle toxicity. 

Meet a PGRN Investigator

William S. Bush
P-STAR Group
Assistant Professor, Center for Human Genetics Research, Department of Biomedical Informatics, Vanderbilt University

 

My research interests lie in two inter-related areas:  identifying genetic mechanisms associated with common human phenotypes and phenotype classes, and advancing our understanding of complex relationships among genetic variants in the human genome. 

Human genetic studies now capture much of the common genetic variation in the human genome, and new sequencing technologies will soon affordably capture the entire DNA sequence for all participants of a study.  Exploring this new world of data poses interesting analytical challenges but also presents great opportunity.  We conduct analyses for several complex disease studies, including multiple sclerosis and other autoimmune disorders, and various cancer phenotypes.  Many genetic analyses focus on associating a single variant to a single phenotype.  Working under the hypothesis that complex disorders are likely to have a complex genetic etiology, we examine combinations of genetic variants that are known to influence established biological mechanisms.  We also examine collections of related phenotypes for pleiotropy -- a phenomenon where a genetic variant, gene, or genetic mechanism influences multiple phenotypes. 

Likewise, new technologies have dramatically increased the amount and scale of experimental data available from sequencing and gene expression studies based on human cell lines.  Simultaneously, numerous online repositories have been developed to organize and electronically distribute information on gene function, protein structure and function, metabolic and regulatory pathways, and evolutionary conservation.  Using a combination of bioinformatics, basic statistical approaches, and more advanced data mining and machine learning techniques, we are studying how patterns of genomic variation influence the function of both individual genes and entire biological systems.  These patterns can then be investigated in model systems, or applied to specialized analyses of human genetic data to link functional variation to traits of interest.

August 2013
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Featured Project of the Month

PMT Group –  Genomic characterization of drug induced regulatory elements.

 

Interindividual variation in gene regulatory elements plays a causative role in adverse and ineffective drug reactions. However, our knowledge of the location and function of drug-dependent elements remains poor. To uncover drug-associated elements in a genome-wide manner, we performed ChIP-seq using antibodies against the pregnane X receptor (PXR) and three different enhancer marks (p300, H3K4me1, H3K27ac) on primary human hepatocytes treated with rifampin or vehicle control. We identified 1,297 regions bearing a drug-dependent regulatory signature, exhibiting a conditional enrichment of PXR occupancy as well as all three enhancer marks. These sequences reside near several Phase I & II enzymes, membrane transporters, and overlap pharmacogenomic and liver-related GWAS variants.  Selected rifampin-induced sequences were tested for promoter and enhancer activity, finding several to be activated by rifampin. Nucleotide variants within these drug induced sequences showed differential regulatory activity. These elements are likely to contain many undiscovered causative variants of adverse drug reactions.

PMID: 21368754

PMID: 22630332

Meet a PGRN Investigator

Nadav Ahituv
PMT Group
Associate Professor, University of California San Francisco

The research in my laboratory is focused on understanding the role of regulatory sequences in human biology and disease. We are extremely interested in identifying gene regulatory nucleotide changes that can be associated with pharmacogenomic phenotypes. Working along with Drs. Kathleen M. Giacomini and Deanna L. Kroetz as part of the Pharmacogenetics of Membrane Transporters project, which is part of the NIH Pharmacogenomics Research Network, we are focusing on analyzing nucleotide variation in membrane transporters.

Membrane transporters are of great pharmacogenetic importance, as they are the targets for many commonly used prescribed drugs and have a great influence in absorption, distribution, and elimination of many clinically used drugs. Using computational analyses, ChIP-seq and RNA-seq coupled with high-throughput in vitro and in vivo functional studies we are characterizing how genetic differences in regulatory sequences of these membrane transporters and other drug-associated genes lead to clinical variation in drug response.

Link to lab website

 

 

 

 

 

 

July 2013
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Featured Project of the Month

NWAP Group – Pharmacogenetics in American Indian Populations.


 

A full understanding of genetic variation in American Indian communities is essential if pharmacogenetic testing is to reach its optimal clinical utility in patients from these populations. Through a collaborative partnership with the Confederated Salish and Kootenai Tribes (CSKT) in northwestern Montana, we have resequenced the CYP2D6, CYP3A4, CYP3A5, and CYP2C9 genes. We also compared the frequencies of known variants and haplotypes in the CSKT population to the frequencies in other world populations.

Allele frequencies of the most common variants were CYP2D6*4 and *41 (20.86 and 11.23%, respectively); CYP3A4*1G and *1B (26.81 and 2.20%, respectively); CYP3A5*3 (92.47%); and CYP2C9*2 and *3 (5.17 and 2.69%, respectively). In general, allele frequencies in CYP2D6, CYP2C9 and CYP3A5 were similar to those observed in European Americans; there was, however, a marked divergence at the CYP3A4*1G allele. These results highlight the importance of conducting pharmacogenomic research in American Indian populations to inform drug-dosing protocols.

PMID:23778323

Meet a PGRN Investigator

Erica L. Woodahl 
 NWAP Group
Associate Professor of Pharmaceutics, University of Montana

 Within the NWA-PGRN, my research focuses on pharmacogenomics in American Indian populations. We developed a partnership with the Confederated Salish and Kootenai Tribes (CSKT) in northwestern Montana to explore the interest of the Tribes in pharmacogenomic research.

We use community-based participatory research to identify research priorities, build trust to develop a productive partnership, and adhere to research protocols and procedures required by the Tribes. This includes discussions with providers at Tribal Health, Tribal Council leaders, and members of a community advisory board.

This research includes the identification and characterization of genetic variation in genes that predict drug response and toxicity. We have described allele frequencies among American Indian people that differ from other well-studied world populations. Understanding this variation is an important step towards improving dosage regimens of clinically relevant drugs for the CSKT population.

We have also created digital stories to educate the CSKT community about our pharmacogenetics research project. An example of one of these stories can be found here: http://www.youtube.com/watch?v=Qz5106fwuxc

Link to Profile

Link to NWAP PGRN Page

June 2013
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Featured Project of the Month

PAAR4Kids GroupClinical Implementation of Preemptive Pharmacogenetic Testing.



Preemptive pharmacogenetic tests are being systematically implemented into patient care at St. Jude Children's Research Hospital. Planned with St. Jude's Family Advisory Council, the PG4KDS clinical trial protocol (http://www.stjude.org/pg4kds) has enrolled over 1200 patients from May 2011-April 2013, [PMCID: 3589526] using the Affymetrix DMET array [PMCID: 3516299] supplemented with a copy number assay for CYP2D6. One gene/drug pair at a time is selectively migrated into the electronic medical record (EMR) for all enrolled patients.

Two genes and 8 associated drugs are implemented thus far. Prior to migration of a pharmacogenetic test into the EMR, substantial effort is required to create tables (http://www.pharmgkb.org/page/tppTables) that translate diplotypes into phenotypes (working with the TPP), pharmacogenetic diagnoses (working with PHONT), automated clinical interpretation templates, [PMCID: 3589522] interruptive point-of-care prescribing alerts, and patient and clinician educational tools.

Drug prescribing decisions and actionable phenotypes are prioritized and defined by CPIC (http://www.pharmgkb.org/page/cpic), an effort led by PAAR4Kids and PharmGKB.

Meet a PGRN Investigator

Jun J. Yang
PAAR4Kids Group
Assistant Member, Dept. of Pharm. Sci., St. Jude Children's Research Hospital

Within PAAR4Kids, my research interest is to characterize the genetic basis of inter-individual variability in the susceptibility and treatment response of childhood acute lymphoblastic leukemia (ALL).

Primarily via genome-wide association studies (GWAS) in collaboration with the Children's Oncology Group, we identify genetic variants that contribute to ALL disease risk (J Clin Oncol 30:751) and to treatment outcome (JAMA301:393, Blood 120:4197).

With the overarching goal to reveal novel biology of ALL and to develop more individualized therapy, we also extensively follow up on GWAS hits and functionally characterize molecular mechanisms underlying their associations with leukemogenesis and response to chemotherapy.

We focus on both inherited and acquired genomic variations (also interactions between the two genomes), with a particular emphasis on the genomics of racial disparities in childhood ALL (Nat Genet 43:237).

Full Profile

April 2013
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Featured Project of the Month

PAT GroupSymptomatic Response to Antiarrhythmic Drug Therapy Is Modulated by a Common SNP in AF.


Recent genome-wide association studies have identified three atrial fibrillation (AF) susceptibility loci on chromosomes 4q25 (near PITX2), 16q22 (in ZFHX3) and 1q21 (in KCNN3). These findings suggest that variable mechanisms contribute to AF susceptibility and suggest that response to therapy may also be genotype-dependent. In this study, we tested the hypothesis that response to antiarrhythmic drugs is modulated by the three common AF risk alleles.

While multiple clinical variables failed to predict response to antiarrhythmic drugs, a single SNP (rs10033464) at the 4q25 locus was an independent predictor of successful rhythm control in both the discovery and validation cohorts with an odds ratio 4.7 (see Table 6 from article).
Our results suggest that a common AF susceptibility allele on chromosome 4q25 modulates response to antiarrhythmic drugs and points to a potential role for stratification of therapeutic approaches by genotype.
Link to article

Meet a PGRN Investigator

Dawood Darbar
PAT Group
Associate Professor of Medicine, Vanderbilt University Medical Center

Within PAT, Dr. Darbar¿s research focuses on determining the genomic predictors of variable drug response in atrial fibrillation (AF), the commonest arrhythmia in clinical practice. Recent advances in our understanding of the molecular mechanisms in AF support the hypothesis that variability in response to drug therapy may reflect differences in underlying genetic mechanisms. A key enabling resource for AF studies at the PAT center is the Vanderbilt AF Registry.

This clinical-DNA Registry has proven to be an important source for not only phenotyping large AF pedigrees but also for identifying genetic, molecular and clinical subtypes of AF, laying the basis for rational mechanism-based and directed treatments for this common arrhythmia. Atrio-ventricular nodal blockers exert variable effects and current antiarrhythmic drugs are only moderately effective and are limited by side effects including the potential for proarrhythmia. Thus, one implication of the PAT investigators¿ work is that therapy with current drugs could be improved by identifying predictors of response. Recently, we have reported that common variants (at chr4q25 and in the ¿-adrenergic receptor gene) modulate responses to drug therapies used in AF.
Full Profile

March 2013
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Featured Project of the Month

PAAR GroupIntegration of Cell Line and Clinical Trial Genome-Wide Analyses Supports a Polygenic Architecture of Paclitaxel- Induced Sensory Peripheral Neuropathy.


To assess the utility of cell-based models in cancer pharmacogenomic biomarker discovery, Wheeler et al. compared genome-wide association study results of paclitaxel-induced cytotoxicity in lymphoblastoid cell lines (LCLs) and paclitaxel-induced peripheral neuropathy in breast cancer patients.

Significant overlap between the clinical and LCL studies was observed, confirming a role for the LCL model in the analysis of a subset of genes involved in patient paclitaxel-induced toxicity. One overlap gene, RFX2, was functionally validated in a nerve cell model of paclitaxel response. The enrichment results and functional example imply that cellular models of chemotherapeutic toxicity may capture components of the underlying polygenic architecture of related traits in patients.

Link to article

Meet a PGRN Investigator

Michael Maitland
PAAR Group
Assistant Professor of Medicine and Associate Director, Committee on Clinical Pharmacology and Pharmacogenomics
University of Chicago

Within PAAR, Dr. Maitland¿s research focuses on development and validation of endophenotypes for angiogenesis inhibitors. In cancer patient cohorts, his team has demonstrated reproducible variance in the typical blood pressure elevations caused by some angiogenesis inhibitors. The variance appears to be based on intrinsic differences that might determine therapeutic response to angiogenesis inhibitors. Currently a PAAR team tests the associations among functional gene variants that affect circulatory system function with the blood pressure response to angiogenesis inhibitors.

In collaboration with PAPI-2, his team has screened circulating peptides in cancer patients and then characterized variance in the concentrations of these candidate biomarkers in the Old Order Amish of Lancaster County. The PAPI-2 team conducts quantitative trait GWAS to identify gene variants that might affect response to new cancer therapeutics. The PAAR team then conducts clinical and mechanistic studies to develop these gene variants as pharmacogenomic biomarkers for new anticancer therapeutics. This approach has identified a SNP in KDR that affects pharmacodynamic response to the VEGFR2 inhibitor pazopanib.
Full Profile

February 2013
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Featured Project of the Month

PAPI-2 GroupAspirin Pharmacogenomics: Role of PEAR1 in Personalized Anti-Platelet Therapy.


While aspirin is generally effective at reducing the risk of thrombotic events in patients with cardiovascular disease, significant inter-individual variation in platelet response to aspirin exists. We measured collagen-stimulated platelet aggregation at baseline, after clopidogrel administration, and after clopidogrel and aspirin administration in 565 healthy subjects of the PAPI Study, and conducted a GWAS.

Follow-up studies revealed that rs12041331 in the platelet endothelial aggregation receptor 1 (PEAR1) gene was strongly associated with aspirin response (P=7.66x10-9). In 227 patients undergoing percutaneous coronary intervention, A-allele carriers of rs12041331 were more likely to experience a cardiovascular event or death compared to GG homozygotes (HR=3.18, 95%CI 1.50-6.74, P=0.003). In an independent cohort of aspirin-treated patients with stable coronary artery disease, rs12041331 A-allele carriers had significantly increased risk of myocardial infarction compared to GG homozygotes (OR=2.03, 95%CI 1.01-4.09, P=0.048).

These results suggest that common genetic variation in PEAR1 may be a determinant of platelet response and cardiovascular events in patients on aspirin.

Link to article

Meet a PGRN Investigator

Joshua P. Lewis
PAPI-2 Group
Assistant Professor, Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, Program in Personalized and Genomic Medicine

Cardiovascular disease is the leading causes of death in the United States. The goal of my research is to identify and functionally characterize genes contributing to cardiovascular disease risk in order to ultimately translate genetic discoveries into individualized patient care through pharmacogenomics and/or other clinical approaches.

While dual antiplatelet therapy (DAPT) with aspirin and clopidogrel is the standard of care for improving cardiovascular outcomes in patients with various coronary syndromes, variable inter-individual responses to antiplatelet therapies exist resulting in increased risk of recurrent cardiovascular events in some patients. My research objective is to identify genetic variants through candidate gene studies, genome-wide association analyses, and other "omics" approaches that contribute to differences in platelet response and to functionally elucidate the molecular mechanisms responsible for this variability. Currently, the potential pharmacogenetic effects of platelet endothelial aggregation receptor 1 (PEAR1), paraoxonase 1 (PON1), carboxylesterase 1 (CES1), and ATP-binding cassette sub-family C member 4 (ABCC4) on DAPT effectiveness are currently being investigated.

Full Profile

January 2013
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Featured Project of the Month

PhRAT GroupPolygenic Modeling.


The PGRN Polygenic Modeling project seeks to glean the total contribution to pharmacological traits from genomic data. We are part of a scientific community working toward comprehensive understanding of the genetic architecture of human disease and response phenotypes, and of its implications for improving patient care. The Polygenic Modeling project is led by the PGRN group PhRAT, committed to genomic studies of treatment response in rheumatoid arthritis patients and to electronic health records for biomedical research, and by the PGRN Statistical Analysis Resource.

Polygenic Modeling includes studies of cancer chemotherapy efficacy and toxicity (PGRN groups PMT, PAAR and PAAR4Kids, response to statins (PARC), antihypertensives (PEAR) and clopidogrel (PAPI), and to biologics in autoimmune disease treatment (PhRAT). Recent insights revealed by Polygenic Modeling: In cancer, variants in certain gene pathways contribute to peripheral neuropathy experienced by patients undergoing paclitaxel therapy. In rheumatoid arthritis, response to different anti-TNF biologic therapies varies due largely to independent genes with broadly immune-related functions.

Meet a PGRN Investigator

Eli Stahl, PhD
PhRAT Group
Assistant Professor, Division of Psychiatric Genomics and the Institute for Genomics and Multiscale Biology at Mt Sinai School of Medicine

Eli Ayumi Stahl, PhD, Assistant Professor in the Division of Psychiatric Genomics and the Institute for Genomics and Multiscale Biology at Mt Sinai School of Medicine, is an investigator in the PGRN group PhRAT, the network-wide Polygenic Modeling project, and the PGRN Statistical Analysis Resource.
Eli is actively engaged in understanding the genetic underpinnings of disease risk and treatment response, and their implications for improving patient care. He led a genome-wide association study of rheumatoid arthritis, is currently leading a genomic study of treatment efficacy in rheumatoid arthritis patients, and also participates in studies of bipolar disorder and schizophrenia among others.

Eli¿s recent work on polygenic analysis suggested that predisposition to several common diseases is largely captured by the genomic data typically analyzed in the largest-scale studies. These methods have led to several new results and insights in pharmacogenomics studies through the PGRN Polygenic Modeling project.

December 2012
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Featured Project of the Month

NWAP GroupGene-Environment Interactions in the Vitamin K Cycle in Alaska Native People.


To better understand genetic and environmental factors that modify the warfarin dose-response relationship in Alaska Native people, we are studying blood coagulation in 1000 adult Yup¿ik volunteers living in western Alaska. Specifically, we are interested in learning how their traditional diet might affect the function of the vitamin K cycle and/or platelets. The diet of Yup¿ik people is highly enriched in omega-3 polyunsaturated fatty acids (PUFAs), due to the consumption of cold-water fish and marine mammals. In addition, because of potential challenges in access to foods rich in vitamin K (traditional and commercial) in the population, vitamin K intake may be variable and subject to seasonal changes. Observed variation in different measures of coagulation function and the vitamin K cycle are being evaluated in relation to established biomarkers of PUFA and vitamin K intake, as well as inherited variation in genes involved in the vitamin K cycle and clotting factor synthesis. The goal of the study is to utilize both genomic and environmental biomarkers to better inform clinicians in the safe and efficacious use of warfarin, and potentially other anti-coagulation therapies, in Alaska Native people. Link to publication 1, Link to Publication 2

Meet a PGRN Investigator

Renee F. Robinson, PharmD, MPH
NWAP Group
Senior Researcher - Southcentral Foundation


Research initiatives at Southcentral Foundation (SCF) directly support community involvement, engagement, and participation. As both an officer in the US Public Health Service and a Senior Researcher at SCF, a tribally owned and operated healthcare system serving ~65,000 Alaska Native and American Indian (AN/AI) people in southcentral Alaska, my research agenda/priorities are based on AN/AI community identified needs/concerns.

My goal as a researcher within this unique setting is to identify, establish, and cultivate necessary investigative teams; create partnerships across disciplines and institutions; address the clinical concerns identified by the AN/AI community in a culturally sensitive manner; and help AN/AI researchers, researcher associates, and research assistants develop.

Our current studies within the PGRN network utilize a community-based participatory research framework to better understand the potential role of pharmacogenetics on medication selection, management (e.g. tamoxifen, tacrolimus, and warfarin), dissemination, and utility within the AN/AI community.

Link to Southcentral Foundation.

November 2012
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Featured Project of the Month

PAT GroupAssessment of a pharmacogenomic marker panel in a population identified from electronic medical records.


This study, led by Dr. Crawford¿s graduate student Matt Oetjens as part of a larger team led by Dr. Dan Roden of the Pharmacogenomics of Arrhythmia Therapy (PAT), aims to present an overall assessment of the Illumina pharmacogenetic genotyping product, the ADME Core Panel, and to report allele frequencies of the 184 functional and clinically interesting ADME Core markers in our study population. We genotyped 326 individuals of European-descent in BioVU, the Vanderbilt University Medical Center biorepository linked to de-identified electronic medical records, using the ADME Core Panel. Based on standard quality control metrics, we found the quality of the ADME Core Panel data to be mostly high, with exceptions in the CNVs and markers in certain genes (notably CYP2D6). Results suggest that more than a third (37%) of ADME-targeted dialleleic markers do not have reference allele frequency data in public repositories or the literature, highlighting the need for reference data for these mostly rare variants.

Meet a PGRN Investigator

Dana C. Crawford, Ph.D.
PAT Group
Associate Professor, Molecular Physiology and Biophysics; Investigator, Center for Human Genetics Research

I am Associate Professor in the Department of Molecular Physiology and Biophysics and Investigator in the Center for Human Genetics Research (CHGR).

My expertise is genetic epidemiology and human genetics. My laboratory accesses epidemiologic and clinical collections to characterize common and rare genetic variants associated with human complex traits such as infectious diseases, cardiovascular disease, obesity, type 2 diabetes, cancers, and age-related macular degeneration in diverse populations (African Americans and Mexican Americans). We also are interested in identifying pleiotropy and environmental modifiers of these genetics associations, including pharmacogenomics.

I am PI of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study as part of the larger Population Architecture using Genomics and Epidemiology (PAGE) study as well as co-chair of the electronic Medical Records & Genomics (eMERGE) Genomics Work Group as a co-investigator of the Vanderbilt Genome-Electronic Records (VGER) study and a co-investigator of the Pharmacogenomics of Arrhythmia Therapy in the Pharmacogenomics Research Network (PGRN).
Link to full profile.

September 2012
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Featured Project of the Month

PNAT GroupPharmacogenetics of Nicotine Addiction Treatment.


Figure: Abstinence rates across different DRD1 genotype groups within slow and normal nicotine metabolizers and genotype groups.

PNAT has characterized a biomarker of CYP2A6 activity, the nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine). This ratio reflects both genetic and environmental influences on CYP2A6 activity and nicotine clearance. The NMR is measured in smokers and is an established predictor of therapeutic response. Recently, we conducted NMR-stratified analyses in two randomized clinical trials of smoking abstinence treatments across 13 regions coding for nicotinic acetylcholine receptors and proteins involved in the dopamine reward system. Polymorphisms in DRD1 had significant interactions with increased odds of abstinence within slow metabolizers (OR=3.1-3.5, 95% confidence interval 1.7-6.7).

To facilitate translation of NMR use to clinical practice, PNAT is currently conducting a prospective placebo-controlled multi-center pharmacogenetic (PGx) clinical trial of alternative therapies for smoking cessation treatment in 1,350 smokers. In this trial, randomization to placebo, transdermal nicotine, or varenicline is influenced by an individual¿s¿ measured NMR. This data will serve to determine the cost-effectiveness of using NMR in practice, as well help identify additional sources of genetic variation influencing nicotine clearance and therapeutic response. Link to publication.

Meet a PGRN Investigator

David V. Conti, Ph.D.
PNAT Group
University of Southern California, Zilkha Neurogenetic Institute, Keck School of Medicine, Department of Preventive Medicine, Division of Biostatistics

My research focuses on the intersection between statistical methodology and applied investigations in genetic epidemiology. My past methodological research has used Bayesian hierarchical models for more precise localization of putative disease variants and model selection approaches aimed to determine which SNPs and/or haplotype effects best describe the relation between genetic variation and a trait of interest.

More recent work has focused on the analysis of rare variants utilizing Bayesian uncertanty techniques to determine if regional rare variation in the aggregate is associated with disease and to identify which variants are most likely driving that association.

In my collaborative research in smoking cessation as part of PNAT, we have constructed a smoking behavior risk ontology representing our knowledge of nicotine metabolism and the brain reward system as well as their links to the relevant phenotypes.

This resulting ontology has served to provide priors for interaction analysis in pathways and to guide many of the motivating hypotheses in the applied investigations, including main genetic effects, gene-gender interactions, and gene-biomarker interactions.


Profile Website

August 2012
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Featured Project of the Month

PARC GroupMetabolomics Reveals That Amino Acids Contribute to Variation in Response to Simvastatin Treatment.


Figure. Correlation matrix illustrating clusters of metabolites associated with LDL-cholesterol response to simvastatin.
Statins are widely prescribed for reducing LDL-cholesterol and risk for cardiovascular disease, but there is considerable variation in therapeutic response. In collaboration with investigators in the Metabolomics Research Network, a gas chromatography-time-of-flight mass-spectrometry-based metabolomics platform was used to evaluate global effects of simvastatin (40 mg/day for 6 weeks) on intermediary metabolism in 100 healthy individuals.. The metabolic signature of drug exposure included essential amino acids, lauric acid (p<0.0055, q<0.055), and alpha-tocopherol (p<0.0003, q<0.017). Using the HumanCyc database and pathway enrichment analysis, we observed that the metabolites of drug exposure were enriched for the pathway class amino acid degradation (p<0.0032). Metabolites whose change correlated with LDL-C lowering response included dibasic amino acids which share plasma membrane transporters with arginine, the rate-limiting substrate for nitric oxide synthase, a critical mediator of cardiovascular health. These results indicate that clusters of metabolites involved in pathways not directly connected with cholesterol metabolism may play a role in modulating the response to simvastatin treatment. Link to publication.

Meet a PGRN Investigator

Marisa W. Medina, Ph.D.
PARC Group
Children's Hospital Oakland Research Institute

                         

My primary area of interest is the identification of genetic and molecular determinants underlying variation in cardiovascular disease risk factors, namely elevated plasma LDL cholesterol, as well as inter-individual variation in response to statins, a class of cholesterol lowering drugs.

Specifically, my research has been focused on investigating the role of changes in alternative splicing as a novel mechanism involved in cholesterol regulation. We have demonstrated that multiple genes in the cholesterol biosynthesis and uptake pathways are regulated at the level of alternative splicing in response to changes in intracellular cholesterol content to help maintain cholesterol homeostasis. This regulation appears to be mediated by sterol-induced changes in the expression levels of a set of splicing factors which target these genes. My lab is currently in the process of identifying the specific splicing factors that mediate these changes, as well as gene variants both within these factors as well as their target genes, that modulate this pathway.

For the past seven years, I have also been investigating statin pharmacogenetics within the PARC group. The two major areas I am most involved in are 1) a discovery based aim utilizing lymphoblastoid cell lines derived from participants of a statin clinical trial to integrate in vitro transcriptomic measurements with genome-wide DNA variation, cellular markers of cholesterol metabolism, and in vivo phenotypes of the cell line donors to identify genes and pathways underlying both cellular and clinical variation in statin response, and 2) a hypothesis driven aim to characterize and functionalize novel candidate genes and SNPs associated with variation in statin efficacy using cellular mechanistic studies.


Profile Website

July 2012
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Featured Project of the Month

PHAT GroupGenome-wide Association Analysis in Asthma Subjects Identifies SPATS2L as a Novel Bronchodilator Response Gene.

          
Bronchodilator response (BDR) measures reversibility of airflow obstruction by comparing lung function (i.e. FEV1) before and after administration of short-acting β2-agonists, the most commonly used asthma medications. While the literature on the pharmacogenetic influences on BDR has largely focused on the β2-adrenergic receptor (B2AR), we have previously demonstrated that variation in multiple other candidate genes contributes to BDR. In the present study, a genome-wide association study (GWAS) of BDR was performed with 1,644 non-Hispanic white asthmatic subjects from six independent drug clinical trials Data for 469,884 single nucleotide polymorphisms (SNPs) were tested for association with BDR using an additive model. Replication analyses of primary P-values were conducted in 1051 white subjects from two indpendent asthma cohorts. The lowest overall combined P-value was 9.7E-07 for SNP rs295137, on chromosome 2 near SPATS2L. SPATS2L expression knockdown via siRNA resulted in increased β2-adrenergic receptor levels (Figure). Our results suggest that SPATS2L may be an important regulator of β2-adrenergic receptor down-regulation and that there is promise in gaining a better understanding of the biological mechanisms of differential response to β2-agonists through GWAS. (PLoS Genetics, PubMed Citation Pending)

Meet a PGRN Investigator

Blanca E. Himes, Ph.D.
PHAT Group
Channing Laboratory
Brigham and Women's Hospital and Harvard Medical School

I am an Instructor in Bioinformatics at Harvard Medical School, working primarily at the Channing Laboratory, Brigham and Women's Hospital. The ultimate goal of my research is to better understand the genetics and pharmacogenetics of asthma and related traits. My computational and analytical skills, as well as my background in biomedical sciences, have been instrumental in my research and distinguish my approaches from those of traditional clinician researchers.

I have used probabilistic graphical models to find genetic association networks of asthma exacerbations and bronchodilator response and designed a computational algorithm to search through large datasets of variables that are optimal predictors of a phenotype. This work continues as I am using GWAS data to create improved multi-SNP tests of these traits and asthma. This work is also the basis for my K99 award (K99 HL105663 "Integrative Genomics Approaches to Model the Genetic Architecture of Asthma") in which I seek to identify novel genetic variants that modulate asthma risk and asthma treatment response via the integration of multiple data sources, and to use these variants to create predictive models of asthma and asthma therapy.

The study described in this month's "Project of the Month" is currently in press at PLoS Genetics and incorporates an integration of GWAS data with a tailored siRNA approach targeting the top gene identified through the GWAS. We are generating additional data, including RNASeq data from isoproterenol-stimulated human airway smooth muscle cells and eQTL data from B2AR-transfected lymphoblastoid cells, to continue to refine the genetic and genomic influences on β2-agonist response. By integrating this data, we hope to soon create predictive models of response to β2-agonist therapy in asthma.

June 2012
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Featured Project of the Month

PPII GroupAromatse inhibitors, estrogens and musculoskeletal pain: estrogen-dependent T-cell leukemia 1A (TCL1A) gene-mediated regulation of cytokine expression.

Arthralgia and myalgia are major side effects associated with the aromatase inhibitor (AI) therapy of breast cancer. In a recent GWAS of DNA samples from an AI Clinical Trials, we identified SNPs associated with musculoskeletal pain during adjuvant AI therapy for breast cancer, including one SNP that created an estrogen response element near the 3' end of the T-cell leukemia 1A (TCL1A) gene. In the present study, we set out to determine whether these same SNPs might influence cytokine expression and effect more broadly, and, if so, to explore the mechanism. We observed that E2 - induced SNP-dependent TCL1A expression altered IL-17, IL-17RA, IL-12, IL-12RB2, and IL-1R2 expression as well as NF-KB transcriptional activity. Specifically, variant SNP genotypes were associated with a striking decrease in TCL1A expression after blockade of the estrogen receptor (left Figure panel), and were associated with a striking increase in NF-KB transcriptional activity after blockade of estrogen effect (right Figure panel). These results provide a pharmacogenomic explanation for a clinically important adverse drug reaction and insight into a novel estrogen-dependent mechanism for the modulation of cytokine and cytokine receptor expression. For more see PMID: 22405131.

Meet a PGRN Investigator

Mohan Liu, Ph.D.
PPII Group
Mayo Clinic, Division of Clinical Pharmarcology, Department of Molecular Pharmacology and Experimental Therapeutics

I am an Instructor in Molecular Pharmacology and Experimental Therapeutics at the Mayo Clinic. I joined the Mayo Clinic PPII PGRN Center just as it was initiating a large, genome-wide association (GWA) study of aromatase inhibitor (AI) therapy of breast cancer in collaboration with National Cancer Institute (NCI) and National Cancer Institute of Canada (NCIC) to address a major AI side effect, musculoskeletal pain.

GWAS genotyping was performed in collaboration with Japanese RIKEN Center for Genomic Medicine. This "three-way collaboration" made it possible for me to identify and pursue GWAS "signals" by applying a genomic data-rich panel of 300 lymphoblastoid cell lines (LCLs) for which the Mayo PGRN has 1.3 million SNPs and 54,000 expression array probe sets for each cell line.

This LCL "model system" was developed by PPII Co-PI Liewei Wang, MD-PhD. I used this model system to generate and test pharmacogenomic hypothesis for a series of GWA studies of the endocrine therapy of breast cancer.

The study described in this month's "Project of the Month" was published in the Journal of Clinical Oncology in 2010 and led directly to the present project – which identified a novel, genetically variable estrogen-dependent process for the regulation of cytokine and cytokine receptor expression.

May 2012
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Featured Project of the Month

PHONT GroupPharmacogenomics Ontology (PHONT) Network Resource Standardization of PGRN Data Dictionaries 



The variety of disease phenotypes that are studied in the PGRN, as well as differences in clinical systems in use at each PGRN site, lead to data that is heterogeneous,non-standardized, and institution-specific. We performed a survey of data dictionaries from PGRN research sites with the goal of identifying overlapping and unique data elements among the sites, and proposed standards that establish common semantic meanings and representations for the data. This was accomplished by mapping variables from research sites to data standards that are aligned with national Meaningful Use requirements and/or developed by international standards development organizations. The process of data element harmonization and standardization not only provides a means for representing common and related variables in canonical forms, but also serves to identify gaps in data standards that must be filled to ensure the pharmacogenomic domain is sufficiently covered by those standards. Furthermore, this effort will facilitate the integration of pharmacogenomics data into EMRs and its translation into clinical practice. More...

Meet a PGRN Investigator

Christopher G. Chute, M.D., Dr.P.H.
PHONT Group – Mayo Cinic, Professor of Medical Informatics

Christopher G. Chute, MD DrPH, is an internist, epidemiologist, and biomedical informaticist who became convinced somewhere along his career that large-scale, collaborative biomedical research and discovery required comparable and consistent data representation. Unfortunately, this ultimately means standards, which is the intellectual equivalent of eating your vegetables. However, to make such things palatable, one can always "map" the way one likes to work with ones own data to emergent national and international consensus standards for clinical and biological data representation. Chute is most active in the clinical standards world chairing the ISO Technical Committee (TC215) on health informatics, chairing the International Classification of Disease revision for WHO, and serving on the HL7 Advisory Board and the HHS Health Information Technology Standards Committee. He also leads or co-leads a number of grants related to the PGRN PHONT resource, such as eMERGE, SHARPn, Beacon, NCBO, and Mayo's CTSA Informatics Core, among others. Chute is leading PHONT to make data mapping transparent and painless to PGRN investigators, while ultimately providing value thought EMR interfaces. Profile page

April 2012
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Featured Project of the Month

PEAR Group
Defining genetic variation at chromosome 12q15 and association with antihypertensive response to hydrochlorothiazide

We have recently replicated an association between a SNP on chromosome 12q15 with the antihypertensive response to hydrochlorothiazide (HCTZ) in African Americans. We found that African American patients carrying SNP rs7297610 C/C genotype had a significantly greater 3.4/2.5 mmHg blood pressure decline in response to HCTZ than T allele carriers. We additionally found that gene expression of the nearby gene YEATS4 was significantly down-regulated in patients by HCTZ treatment in those with the C/C genotype, while there was no effect of HCTZ on YEATS4 expression in T carriers. Due to the lack of association in those of European ancestry, both in the original study, and in this PEAR study, and for other reasons, we do not believe rs7297610 is the functional polymorphism. Therefore, in collaboration with the Baylor Human Genome Sequencing Center, and as part of the PGRN Deep Sequencing Resource, we are currently sequencing a 700kb region on chromosome 12q15 in good and poor responders to HCTZ, including both African Americans and Caucasians, in an attempt to discover the functional polymorphism(s). For more see PMID: 22350108.

Meet a PGRN Investigator

Amber L. Beitelshees, PharmD, MPH
PEAR Group
University of Maryland, Baltimore, Division of Endocrinology, Diabetes & Nutrition

My research is aimed at improving outcomes in the treatment and prevention of cardiovascular disease and diabetes.

We are particularly interested in determining how variability in genes involved in lipid and glucose metabolism can be used to predict improved safety and efficacy of the chronic medications used to treat cardiovascular disease.

My lab utilizes genetic epidemiology, clinical pharmacology, and functional genomics to address these questions.


Profile page

March 2012
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Featured Project of the Month

PhRAT Group
Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis

The genetic association of the major histocompatibility complex (MHC) to rheumatoid arthritis risk has commonly been attributed to alleles in HLA-DRB1, though controversy remains about the specific causal variants in HLA-DRB1and the presence of other independent effects elsewhere in the MHC. We used genome-wide SNP data in 5,018 individuals with seropositive rheumatoid arthritis (cases) and 14,974 unaffected controls. We imputed and tested classical alleles and amino acid polymorphisms in HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1 and HLA-DRB1. Conditional and haplotype analyses identified that three amino acid positions (11, 71 and 74) in HLA-DRβ1 and single–amino-acid polymorphisms in HLA-B (at position 9) and HLA-DPβ1 (at position 9). All of these sites are located in peptide-binding grooves, and almost completely explain the MHC association to rheumatoid arthritis risk.

For more see PMID: 22286218 .

Meet a PGRN Investigator

Soumya Raychaudhuri, M.D., Ph.D.
PhRAT Group
Harvard Medical School, Divisions of Genetics and Rheumatology
Brigham and Women's Hospital

I am an Assistant Professor of Medicine at Harvard Medical School within the Divisions of Genetics and Rheumatology at Brigham and Women's Hospital. I completed my graduate work at Stanford University with Russ Altman, and my postdoctoral training at the Broad Institute with Mark Daly.

I am interested in translating the results from human genetic studies into pathways, cell-types, and mechanisms that are critical to disease pathogenesis. My lab has expertise in statistical genetics, bioinformatics, and high-throughput immunology.


Lab page

February 2012
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Featured Project of the Month

XGEN Group
Regulatory variants in the antipsychotics receptor 5-HT2A

We study expression genetics of drug-related genes, discovering frequent regulatory variants in key genes such as CYP3A4, DRD2, and DAT, with robust clinical effects. Post-doc Ryan Smith has now completed analysis of the serotonin 2A receptor (to be published), a critical target of antipsychotics, with clinically relevant polymorphisms yet to be characterized. Measuring the transcriptome profile of 5-HT2A with use of second generation sequencing, Ryan has identified three regulatory variants, resolving an unusual mechanism for a promoter variant. These results enable correct interpretation of numerous clinical association results, with promise of developing a biomarker test. For more information on the method, see PMID: 21289622

Meet a PGRN Investigator

Ryan M. Smith, Ph.D.
XGEN Group
Pharmacogenomics Core Laboratory, The Ohio State University

The central goal of my work is to understand how genetic diversity contributes to human disease, and more globally, complex human behaviors. Starting at the level of the basic genetic code, DNA, and moving upward through layers of building complexity (RNA to protein, to protein networks, to a cell, a tissue, an organ, to complex human behaviors), I search for genetic variants that perturb the entire system, contributing to human disease and affecting treatment outcome. With this approach, I hope to find new avenues to treatment and implement personalized medicine. My 5-HTR2A results are pretty exciting as this receptor gene has resisted previous attempts to resolve the responsible polymorphisms. It is also our first example where deep sequencing offered an approach to solving a long-standing problem.

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