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UNIVERSITY OF CALIFORNIA, SAN DIEGO The Cholinesterases: A Study in Pharmacogenomics A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Biomedical Sciences by Anne Marie Valle Committee in charge: Professor Palmer Taylor, Chair Professor Philip Bourne Professor Mark A. Lawson Professor Daniel T. O’Connor Professor Nicholas J. Schork 2008 Copyright Anne Marie Valle, 2008 All Rights Reserved This Dissertation of Anne Marie Valle is approved, and it is acceptable in quality and form for publication in microfilm: Chair University of California, San Diego 2008 iii To my family: my mother Connie, my husband George, my beautiful children Alethea, Krista, Tammy, Georgie and Carly my wonderful grandchildren Ashley, Kevin, Kristopher, Ezra, Fernando, Diego, Julia, and last but not least Gavin iv TABLE OF CONTENTS Signature Page………………………………..………………………………….……….iii Dedication………………………………………………………………..………….……iv Table of Contents……………………………………………………………….................v List of Abreviations……………………………………………………………………...vii List of Figures……………………………………………………………………….........xi List of Tables and Schemes……………………………………………..………………xiii Acknowledgements…………………………………………………………………........xv Vita and Publications…………………………………………………………………..xviii Abstract of Dissertation……………………………………………………………..…...xx Chapter I Introduction to the Fields of Pharmacogenetics/Pharmacogenomics, Twin Studies, Cholinergic Control of Cardiovascular Function, and the Cholinesterases……………………………………………………………1 A. Pharmacogenetics/Pharmacogenomics and the Promise of Personalized Medicine..….……………………………………………………………...1 B. Twin Studies….………………………………………………………..9 C. Cholinergic Control of Cardiovascular Function.……………..……..13 D. The Cholinesterases.............................................................................22 E. Dissertation Overview………………………………………………..38 Chapter II Butyrylcholinesterase: Association with the Metabolic Syndrome and Identification of Two Gene Loci Affecting Activity…….………………40 A. Abstract………………………………………………………………40 B. Introduction…………………………………………………………..41 C. Participants and Methods…………………………………………….42 D. Results………………………………………………………………..47 E. Discussion…………………………………………………………….54 F. Acknowledgements…………………………………………………...58 v Chapter III A Pharmacogenomic Study: Investigating Naturally Occurring Variations in the Acetylcholinesterase Gene …..........................................................60 A. Abstract………………………………………………………………60 B. Introduction…………………………………………………………..61 C. Material and Methods………………………………………………...63 D. Results………………………………………………………………..75 E. Discussion…………………………………………………………...115 F. Acknowledgements………………………………………………….118 Chapter IV Summary and Closing Remarks……..……………………………….....119 A. The Butyrylcholinesterase Story……………………………………120 B. The Acetylcholinesterase Story……………………………………..125 C. Closing Remarks……………………………………………………126 References …………………………………………………………………………..127 vi LIST OF ABBREVIATIONS 2-PAM pyridinium aldoxime ACh acetylcholine AChE acetylcholinesterase ADR adverse drug response ANOVA analysis of variance ANS autonomic nervous system AV atrioventricular BChE butyrylcholinesterase BMI body mass index BP blood pressure BSA bovine serum albumin cDNA complementary deoxyribonucleic acid CI confidence interval CV cardiovascular ChE cholinesterase CMV cytomegalovirus CNS central nervous system CYP cytochrome P450 CVLM caudal ventrolateral medulla DMEM Dulbecco’s modified Eagles medium DNA deoxyribonucleic acid DTNB 5,5’-dithio-bis(2-nitrobenzoic acid vii DZ dizygotic EPI epinephrine FBS fetal bovine serum G6PD glucose-6-phosphate-dehydrogenase gDNA genomic deoxyribonucleic acid HEK human embryonic kidney HR heart rate HTN hypertension LOD logarithm of odds mAChR muscarinic acetylcholine receptor mRNA messenger ribonucleic acid MZ monozygotic NAT2 N-acetyltransferase-2 nAChR nicotinic acetylcholine receptor NCBI National Center for Biotechnology Information NE norepinephrine NTS nucleus of the solitary tract OMIM Online Mendelian Inheritance in Man OP organophosphates PAS peripheral anionic site PCR polymerase chain reaction PDB Protein Data Bank viii PTC phenylthiocarbamide QTL quantitative trait loci RVLM rostral ventrolateral medulla SA sinoarterial SD standard deviation SNP single nucleotide polymorphism SpDMB (Sp)-3,3dimethylbutyl methylphosphonothiocholine SOLAR Sequential Oligogenic Linkage Analysis Routines TDT transmission disequilibrium test TPMT thiopurine s-metyl transferase UTR untranslated region VMC vasomotor center wt wildtype Amino Acid Residues Ala or A alanine Arg or R arginine Asn or N asparagines Asp or D aspartate Cys or C cysteine Glu or E glutamate Gln or Q glutamine Gly or G glycine ix His or H histidine Ile or I isoleucine Lys or K lysine Leu or L leucine Met or M methionine Phe or F phenylalanine Pro or P proline Ser or S serine Thr or T threonine Trp or W tryptophan Tyr or Y tyrosine Val or V valine x LIST OF FIGURES Chapter I Figure I.1 Contribution of Twins to the Study of Complex Traits and Diseases…...11 Figure I.2 Sympathetic and Parasympathetic Neurotransmitters…………………...14 Figure I.3 Sympathetic and Parasympathetic Regulation of Cardiac Function……..16 Figure I.4 AChE and BChE Gene Structures………………………………………..23 Figure I.5 hAChE and hBChE Crystal Structures…………………………………..27 Figure I.6 Conformation of ChE Proteins with Bound BW284c51…………………28 Figure I.7 ChEs Activity Curves……………………………………………………29 Figure I.8 AChE Inhibition and Reactivation……………………………………….37 Chapter II Figure II.1 Cumulative Sum of Deviations from Overall Mean……………………..48 Figure II.2 Results of Linkage Analysis for the Detection of Loci Affecting Plasma Cholinesterase…………..………………………………………………..53 Chapter III Figure III.1 Frequency Distribution of Cholinesterase Activity……………………...77 Figure III.2 Linear Regression Graphs of MZ and DZ Twin Pairs…………………...78 Figure III.3 SNP Discovery: SNPs Found in the Unrelated Panel Mapped to the AChE gene………………………………………………………………………80 Figure III.4 cSNPs Modeled on mAChE Crystal Structure…………………………..91 Figure III.5 Comparison of wtT547 and D134H Gene Expression…………………..95 Figure III.6 D134H Temperature Sensitivity………………………………………....95 Figure III.7 pS Curves: A = wtT547 B = R3Q C = D134H D = H322N…………..98 Figure III.8 Comparison of pS Curves for wtT547 AChE and Mutants……………...99 Figure III.9 Exponential Decay Curves from Stability Assays……………………...102 xi Figure III.10 Human AChE Structure………………………………………………...104 Figure III.11 Compensating Double Mutant (D134H/R136Q)……………………….105 Figure III.12 Protein Expression Normalized to the wtT547…………………………107 Figure III.13 D134H/R136Q pS Curve (Top Panel) and Summary of pS Curves (Bottom Panel)…………………………………………………………………...108 Figure III.14 Half-Life (t50) Parameter Normalized to the wtT547…………………..109 Figure III.15 Paraoxon Inhibition Curves for wtT547 and D134H Proteins………….112 Figure III.16 Oxime-Assisted Reactivation Curves for the wtT547 and D134H Proteins …...……………………………………………………………………...114 Chapter IV Figure IV.1 Ideogram of Genes Located Around GATA12G02…………………….122 xii LIST OF TABLES AND SCHEMES Chapter I Table I.1 Key Discoveries of the 1950s……………………………………………..4 Table I.2 Genetic Basis of Variability in Drug Response…………………………...8 Table I.3 Twin Studies and Their Applications……………………………………12 Table I.4 In vivo Studies Implicating a Role for the Cholinergic Control of Cardiovascular Function…………………………………………………20 Chapter II Table II.1 Effects of Method Variation, Sex and Sex-Specific Age Variation on Plasma Cholinesterase Activity…………………………………………..47 Table II.2 Correlation between Plasma Cholinesterase Activity (adjustment for method variation) and Variables Related to Cardiovascular Risk……….50 Table II.3 Pairwise Similarity of Twin Plasma Cholinesterase and Models for Fitting Data………………………………………………………………………51 Chapter III Table III.1 Mutagenesis Primers with Corresponding Template Sequence……….....70 Table III.2 Correlation Analysis of Cholinesterase Enzymatic Activity…………….81 Table III.3 SNP Results: Resequencing of AChE in the Unrelated Panel…………..82 Table III.4 Minor Allelic Frequencies in the Unrelated Panel (Contig NT_007933.13 Reverse Complement)…………………………………………………....84 Table III.5 Haplotype Reconstruction using the Nonsynonymous cSNPs…………..85 Table III.6 Haplotype (HAP) Reconstruction using SNPs 5, 8, 9, 12, 16…………...86 Table III.7A Heritability and Association Study (Complete Twin Panel)…………….88 Table III.7B Heritability and Association Study (Eur-Am Panel)………………….....89 Table III.8 Vector pcDNA3 + hAChE cDNA (7224 bp)…………………………....93 Table III.9 Kinetic Parameters for wtT547 and Mutant Protein Enzymes................100 Table III.10 Relative Stability of the Mutant Protein Enzymes……………………...110 xiii Chapter IV Table IV.1 Links to Identified Genes around GATA126G02 on the UCSC Genome Browser…………………………………………………………………123 LIST OF SCHEMES Chapter I Scheme I.1 Scheme and Equation I.1………………………………………………...31 Scheme I.2 Scheme and Equation I.2………………………………………………...32 Chapter III Scheme III.1 Scheme and Equation III.1……………………………………………....96 Scheme III.2 Scheme and Equation III.2……………………………………………...111 Scheme III.3 Scheme and Equation III.3……………………………………………...113 xiv ACKNOWLEDGEMENTS First and foremost I would like to give my thanks and gratitude to my mentor and dissertation chair Dr. Palmer Taylor not only for accepting me into his lab but most importantly, for having the patience and understanding to help me surmount my learning curve and lack of confidence. I feel very fortunate to have worked
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    CANCER GENOMICS & PROTEOMICS 11 : 1-12 (2014) Genome-wide Transcriptional Sequencing Identifies Novel Mutations in Metabolic Genes in Human Hepatocellular Carcinoma DAOUD M. MEERZAMAN 1,2 , CHUNHUA YAN 1, QING-RONG CHEN 1, MICHAEL N. EDMONSON 1, CARL F. SCHAEFER 1, ROBERT J. CLIFFORD 2, BARBARA K. DUNN 3, LI DONG 2, RICHARD P. FINNEY 1, CONSTANCE M. CULTRARO 2, YING HU1, ZHIHUI YANG 2, CU V. NGUYEN 1, JENNY M. KELLEY 2, SHUANG CAI 2, HONGEN ZHANG 2, JINGHUI ZHANG 1,4 , REBECCA WILSON 2, LAUREN MESSMER 2, YOUNG-HWA CHUNG 5, JEONG A. KIM 5, NEUNG HWA PARK 6, MYUNG-SOO LYU 6, IL HAN SONG 7, GEORGE KOMATSOULIS 1 and KENNETH H. BUETOW 1,2 1Center for Bioinformatics and Information Technology, National Cancer Institute, Rockville, MD, U.S.A.; 2Laboratory of Population Genetics, National Cancer Institute, National Cancer Institute, Bethesda, MD, U.S.A.; 3Basic Prevention Science Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, U.S.A; 4Department of Biotechnology/Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, U.S.A.; 5Department of Internal Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea; 6Department of Internal Medicine, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan, Korea; 7Department of Internal Medicine, College of Medicine, Dankook University, Cheon-An, Korea Abstract . We report on next-generation transcriptome Worldwide, liver cancer is the fifth most common cancer and sequencing results of three human hepatocellular carcinoma the third most common cause of cancer-related mortality (1). tumor/tumor-adjacent pairs.
  • Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene

    Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene

    Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.