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Convergence of Genetic Findings for Nicotine Dependence, Lung Cancer and COPD Laura Jean Bierut, MD Washington University Financial Disclosure • Patent on genetic variants that predict addiction – “Markers of Addiction”. • Consultant for Pfizer in 2008 for genetic studies for smoking cessation. • Funding of studies is through the National Institutes of Health Genetic Studies of Complex Diseases A Retelling of the Emperor’s New Clothes Laura Jean Bierut, MD Washington University Table of Contents Chapter 1: What is the utility of linkage analysis in complex diseases? Chapter 2: How to interpret all the previous genetic findings? Chapter 3: What have we learned from Genome Wide Association Studies of schizophrenia, bipolar disorder, depression, alcoholism and autism? Do we have any findings? Chapter 4: What is the best phenotype to study? Chapter 5: What does gene environment interaction really mean? Chapter 6: What is the power to detect gene environment interaction? Chapter 7: Should we move into studying diverse populations? Chapter 8: Don’t get me started Chapter 9: The Happy Ending Prologue Model of Nicotine Dependence A many step process Never Use Initiation First puff – First cigarette Does everyone who uses nicotine become addicted? Smoker 100 cigarettes lifetime Nicotine Dependence U.S. Population Screening and Nicotine Dependence No Symptoms 3,051 Screened 53,742 50.9% 19.2% Initiated Smoking 27,372 58.0% Smoked 100+ Cigarettes 15,881 35.2% Some Symptoms 5,596 44.3% Collaborative Genetic Study of Nicotine Dependence Nicotine Dependence 7,028 Novel Gene in Dependence • a5-a3-b4 nicotinic receptor gene cluster is involved in the development of nicotine dependence. • How did we get there? NICSNP Project NICSNP is a large scale genome wide association study and candidate gene study of nicotine dependence. • Collaborative Genetic Study of Nicotine Dependence Principal Investigator: Laura Jean Bierut (P01 CA 089392) • The Genetics of Vulnerability to Nicotine Addiction Principal Investigator: Pamela Madden (R01 DA 012854) • Genes for Smoking in Related and Unrelated Individuals Principal Investigator: Ovide Pomerleau (R01 DA 017640) • Pharmacokinetics of Nicotine in Twins Principal Investigator: Gary Swan (R01 DA 011170) NIDA Phenotypic Repository John Rice Perlegen Sciences Dennis Ballinger Fagerström Test for Nicotine Dependence Questions Response Options Score Within 5 minutes 6-30 minutes 31-60 minutes After 60 minutes 3 2 1 0 Yes No 1 0 The first one in the morning All others 1 0 4. How many cigarettes per day do you smoke? 10 or less 11-20 21-30 31 or more 0 1 2 3 5. Do you smoke more frequently during the first hours after waking than during the rest of the day? Yes No 1 0 6. Do you smoke if you are so ill that you are in bed most of the day? Yes No 1 0 1. How soon after you wake up do you smoke your first cigarette? 2. Do you find it difficult to refrain from smoking in places where it is forbidden, e.g., in church, at the library, in cinema, etc.? 3. Which cigarette would you hate most to give up? Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO. (1991). The Fagerstrom Test For Nicotine Dependence: A revision of the Fagerström Tolerance Questionnaire. British Journal of Addiction 86:1119-1127. Case and Control Phenotype Definition • Case: Nicotine dependent defined by a Fagerström Test for Nicotine Dependence (FTND) > 4 • Control: Individual who has smoked 100 or more cigarettes and never had any symptoms of nicotine dependence (Lifetime FTND = 0). Heatherton et al., 1991 Results from Candidate Gene Study Saccone et al., 2007 Results from Candidate Gene Study Saccone et al., 2007 SNPs highly correlated with rs16969968 Findings for Nicotine Dependence rs16969968 Saccone et al., 2007 SNPs highly correlated with rs16969968 Findings for Nicotine Dependence rs16969968 Saccone et al., 2007 rs1317286 Bierut et al., 2008 Berrettini et al., 2008 Sherva et al., 2008 Weiss et al., 2008 Stevens et al., 2008 rs1051730 Saccone et al., 2007 Thorgeirsson et al., 2008 Amos et al., 2008 Spitz et al., 2008 Results from Candidate Gene Study The correlation between rs16969968 and rs578776 is < 0.2. There are two distinct findings in the nicotinic gene cluster associated with nicotine dependence. Saccone et al., 2007 Genetic Association and the Nicotinic Receptors - Chromosome 15 rs578776 Saccone et al., 2007 Genetic Association and the Nicotinic Receptors - Chromosome 15 rs578776 Saccone et al., 2007 Bierut et al., 2008 Weiss et al., 2008 Stevens et al., 2008 rs6495308 Berrettini et al.,2008 Nature, 2008 Nature, 2008 Nature Genetics, 2008 PLOS Genetics, 2009 A Genome-Wide Association Study in Chronic Obstructive Pulmonary Disease (COPD): Identification of Two Major Susceptibility Loci Sreekumar G. Pillai1*, Dongliang Ge2., Guohua Zhu1., Xiangyang Kong1., Kevin V. Shianna2, Anna C. Need2, Sheng Feng2, Craig P. Hersh3, Per Bakke4, Amund Gulsvik4, Andreas Ruppert5, Karin C. Lødrup Carlsen6, Allen Roses2,7, Wayne Anderson1, ICGN Investigators, Stephen I. Rennard8, David A. Lomas9, Edwin K. Silverman3, David B. Goldstein2* SNPs highly correlated with rs16969968 Findings for Nicotine Dependence, Lung Cancer, COPD rs16969968 rs8034191 Amos et al., 2008 Hung et al., 2008 Liu et al., 2008 Pillai et al., 2009 Saccone et al., 2007 Bierut et al., 2008 Sherva et al., 2008 Weiss et al., 2008 Stevens et al., 2008 rs1317286 Berrettini et al., 2008 rs1051730 Saccone et al., 2007 Thorgeirsson et al., 2008 Amos et al., 2008 Hung et al., 2008 Thorgeirsson et al., 2008 Liu et al., 2008 Pillai et al., 2009 SNPs highly correlated with rs578776 Findings for Nicotine Dependence and Lung Cancer rs578776 Saccone et al., 2007 Bierut et al., 2008 Weiss et al., 2008 Stevens et al., 2008 Hung et al., 2008 Liu et al., 2008 rs6495308 Berrettini et al.,2008 Genetic Association Data for Nicotine Dependence and Lung Cancer Prologue - The Smoke is Clearing • There are at least two distinct genetic variants on chromosome 15 associated with nicotine dependence and smoking quantity. • These same variants are associated with lung cancer and COPD. • Is the mechanism of action related to a change in protein structure and expression? • Big Question: Is the association with lung cancer and COPD only an indirect effect through smoking or both an indirect and direct effect? Chapter 1 • What is the utility of linkage analysis in complex diseases? Linkage Analysis Biologic Psychiatry Genome search meta-analysis results for all independent genome scans on smoking behavior (3404 families with 10,235 genotyped subjects). Significance levels corresponding to nominal (p < 0.05), suggestive (p < 0.0085), and genome wide (p < 0.00042) significance are shown by the horizontal lines. Meta-analysis of 32 Genome-wide Linkage Studies of Schizophrenia NYM Ng, DF Levinson, SV Faraone, BK Suarez, LE Delisi, T Arinami, B Riley, T Paunio, AE Pulver, Irmansyah, PA Holmans, M Escamilla, DB Wildenauer, NM Williams, C Laurent, BJ Mowry, et al Mol Psychiatry. 2009 Aug;14(8):774-85. Meta-Analysis of 23 Type 2 Diabetes Linkage Studies from the International Type 2 Diabetes Linkage Analysis Consortium Weihua Guan, Anna Pluzhnokov, Nancy J. Cox, Michael Boehnke for the International Type 2 Diabetes Linkage Analysis Consortium Human Heredity 2008;66(1):35-49. TCF7L2 Science 1996 Linkage analysis has little power to localize genetic regions for complex diseases • Linkage analysis is great to localize genetic regions for Mendelian disorders such as rare illnesses that are transmitted in families. • There is very limited power for linkage analysis to detect genetic regions that are associated with complex illnesses. Chapter 2 • How to interpret all the previous genetic findings? 2005 – Time Zero • 2005 was the start of new generation genetic studies with genome wide association studies. Complement Factor H Polymorphism in Age-Related Macular Degeneration Robert J. Klein, Caroline Zeiss, Emily Y. Chew, Jen-Yue Tsai, Richard S. Sackler, Chad Haynes, Alice K. Henning, John Paul SanGiovanni, Shrikant M. Mane, Susan T. Mayne, Michael B. Bracken, Frederick L. Ferris, Jurg Ott, Colin Barnstable, Josephine Hoh Science, 2005 April 15;308(5720):362-4 Genes reported associated with diabetes mellitus type 2 140 120 100 80 60 When an association is strong and robust, it is quickly replicated in various studies and across numerous populations. 40 20 0 1 18 35 52 69 86 103 120 137 154 171 188 205 222 239 256 273 290 307 324 341 358 375 392 409 426 443 460 477 494 511 528 545 562 579 596 613 Number of Studies 625 genes reported as associated with diabetes mellitus type 2 since 2000. All the top genes were identified in genome wide association studies. Number of Genes genes Genes reported associated with schizophrenia 200 180 160 140 120 100 80 60 40 20 0 1 20 39 58 77 96 115 134 153 172 191 210 229 248 267 286 305 324 343 362 381 400 419 438 457 476 495 514 533 552 571 590 609 628 647 666 685 704 723 742 761 Number of Studies 777 genes reported as associated with schizophrenia since 2000. None of the top genes were identified in genome wide association studies. Number of Genes genes Influence of Life Stress on Depression: Moderation by a Polymorphism in the 5-HTT Gene Avshalom Caspi, Karen Sugden, Terrie E. Moffitt, Alan Taylor, Ian W. Craig, HonaLee Harrington, Joseph McClay, Jonathan Mill, Judy Martin, Antony Braithwaite, Richie Poulton Interaction Between the Serotonin Transporter Gene (5-HTTLPR), Stressful Life Vents, and Risk of Depression: A Meta-Analysis Neil Risch; Richard Herrel; Thomas Lehner; Kung-Yee Liang; Lindon Eaves; Josephine Hohn; Andrea Griem; Maria Kovacs; Jurg Ott; Kathleen ReisMerikangas Logistic Regression Analyses of Risk of Depression for 14 Studies Risch, N. et al. JAMA 2009;301:2462-2471. 2005 – Time Zero • The new paradigm of genetic studies with large scale genome wide association studies has led to an explosion of genetic findings related to illnesses. • Findings for complex diseases prior to GWAS studies are suspect. Chapter 3 • What have we learned from Genome Wide Association Studies of schizophrenia, bipolar disorder, depression, alcoholism and autism? • Do we have any findings? Don’t let the p values fool you • The number of genetic variants tested is in the range of 500,000 to 1 million. • P values at 10-5, 10-6 are common. A p value of 10-7 is starting to be interesting. Negative results are also a finding. Genetic effects are modest • Genetic risks for complex diseases are modest. • A genetic risk (OR) of 1.3 is large. • Most genetic risks are in the 1.1 to 1.2 range or less. This is true for most complex diseases in medicine. Alcoholism, schizophrenia, bipolar disorder, lung cancer, diabetes mellitus (type II). What do modest genetic effects mean? • Many genes are involved in disease, which is consistent with genetic risk in the 1.1 range. • If there are rare variants associated with disease, they must be very strong for us to detect them. • No one gene will predict disease. • Prediction of disease will remain difficult. Chapter 4 • What is the best phenotype to study? Best phenotype is one that is associated with genetic variants • P value ~ sample size and genetic risk. • To improve the p value you can – – Increase the sample size – Increase the genetic effect Does complex phenotyping help? • Given that the genetic effect is modest, we will need very large sample sizes to detect an effect. (What is large? 50,000 individuals) • If large sample sizes are needed, then the phenotyping must be simple and standardized. • If there are complex phenotypes with complex measurements, then the genetic effect must be very large to compensate for the smaller studied population. Chen et al., under review Chapter 5 • What does gene environment interaction really mean? Gene Environment Interaction • Genetic effect may differ in varying environments. • Common environmental variables include – parental monitoring, peer smoking, childhood sexual abuse, other childhood adversity. Gene and Parental Monitoring Interplay 16.00 14.00 rs16969968=GG (Reference) rs16969968=GA (OR=1.17) rs16969968=AA (OR=2.11***) 12.00 Odds Ratio 10.00 7.75 8.00 6.00 *** * p<.05, ** p<.01, *** P<.001 compared to the reference group (GG & higher quartiles) Average odds ratio for specific genotype 4.00 *** ** 2.02 1.71 2.00 *** 1.81 1.17 1.00 0.00 higher quartiles (n=673) lowest quartile (n=179) higher quartiles (n=664) lowest quartile (n=218) parental monitoring higher quartiles (n=190) lowest quartile (n=58) Chen et al., 2009 Predicted Probability of Nicotine Dependence* Gene and Peer Smoking Interplay 0.8 0.7 0.6 G/G A/G A/A 95% C.I. 0.5 0.4 0.3 rs16969968 0.2 0.1 0 1 2 3 4 5 6 7 8 Number of Smoking Peers Johnson et al., in review Gene Environment Conundrum • Environmental risk reduction is universal. • Common environmental variables – parental monitoring, peer smoking, childhood sexual abuse, other childhood adversity. • Will we say “It’s ok not to monitor your child. He won’t smoke.” Chapter 6 • What is the power to detect gene environment interaction? Chapter 6 • What is the power to detect gene environment interaction? • Subtitle – If you thought the power was poor to detect a main effect, then wait till you test power to identify an interaction. Power Curves Power and Effect Size by prevalence of comorbid disorder, given sample size N=2689 Prepared by Hong Xian Sample Size Curves Required Sample Size and Effect Size for 80% Power, by prevalence of comorbid disorder Prepared by Hong Xian Chapter 7 • Should we move into studying diverse populations? National Center for Biotechnology Information (NCBI) database for Genotypes and Phenotypes (dbGaP) – 22 U.S. genetic studies (59,000 subjects) – 6 largest studies (diabetes, lupus, macular degeneration, age-related eye diseases) • 33,000 subjects • 180 African Americans (0.5%) – 5,600 African Americans in 4 psychiatric studies African American Subjects Participate in Genetic Studies African American Subjects Eligible Subjects Donated blood for genetic study of Nicotine Dependence 706 European American Subjects 2,473 504 1,415 71% of eligible 57% of eligible p<0.0001 for difference in participation rates between European Americans and African Americans (χ2 test) Hartz et al., in review Differences in populations • There are clearly differences between populations in frequency of genetic variants and prevalence of disease. • Genetic variants act the same way in different populations. (Ioannidis et al., 2004) Diverse Populations • The promise of personalized medicine and genetic treatment is not there for minority populations. • Scientifically, diversity is good. Chapter 8 – Don’t get me started Three ways to validate a finding • Replication • Replication • Replication • Replication means same phenotype and same variant in the same direction. Nominal association of deletions at 1q21.1, 15q11.2 and 15q13.3 with schizophrenia and related psychoses in the phase I sample Chromosome 1: 144.94-146.29 (Mb) Chromosome 15: 20.31-20.78 (Mb) Chromosome 15: 28.72-30.30 (Mb) Locus Cases Controls Cases Controls Cases Controls Iceland Scotland Germany England Italy Finland Total OR 1 of 646 2 of 211 1 of 195 0 of 105 0 of 85 0 of 191 4 of 1,433 8 of 32,442 0 of 229 0 of 192 0 of 96 0 of 91 0 of 200 8 of 33,250 8.68 (1.02, 49.76) 0.024 4 of 646 2 of 211 3 of 195 1 of 105 0 of 85 0 of 191 10 of 1,433 58 of 32,442 0 of 229 0 of 192 0 of 96 0 of 91 1 of 200 59 of 33,250 3.90 (1.42, 9.37) 0.007 1 of 646 1 of 211 1 of 195 0 of 105 0 of 85 0 of 191 3 of 1,433 7 of 32,442 0 of 229 0 of 192 0 of 96 0 of 91 0 of 200 7 of 33,250 8.94 (0.79, 58.15) 0.040 P-value Three deletions show nominal association with schizophrenia and related psychoses in the first sample of 1,433 patients and 33,250 controls. These deletions are large: the 1q21 deletion spans approximately 1.38 Mb, the one on 15q11.2 approximately 0.47Mb and the one on 15q13.3 approximately 1.57 Mb. P-values (uncorrected for the 66 tests) are from the exact Cochran–Mantel–Haenszel test and are two-sided. Coordinates are based on Build 36 assembly of the human genome. 95% confidence intervals are given within brackets. From Stefansson et al. (2008) Large recurrent microdeletions associated with schizophrenia. Nature 455: 232-236. And the rest • There are no findings for psychiatric genetics. • Deidentified genome wide association studies. • Sample sizes less than 1,000 people for genetic studies using disease status. Chapter 9 – The Happy Ending Mokdad et al., 2004 Mokdad et al., 2004 Mokdad et al., 2004 US Cigarette Use vs. Lung Cancer Deaths, 1900-2005 Cessation and RemissionThe Final Step Initiation Cigarette Use Nicotine Dependence Cessation and Remission Phenotypic and genetic data are available to qualified investigators through the NIDA Genetics Consortium and dbGaP.