Convergence of Genetic Findings for Nicotine Dependence, Lung Cancer and COPD

Laura Jean Bierut, MDWashington 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, MDWashington 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

InitiationFirst puff – First cigarette

Smoker100 cigarettes lifetime

Nicotine Dependence

Never Use

Does everyone who uses nicotine become addicted?

U.S. Population Screening andNicotine Dependence

Screened53,742

InitiatedSmoking27,372

Smoked 100+Cigarettes

15,881

NicotineDependence

7,028

SomeSymptoms

5,596

NoSymptoms

3,05119.2%

44.3%

35.2%58.0%

50.9%

Collaborative Genetic Study of Nicotine Dependence

Novel Gene in Dependence

• nicotinic receptor gene cluster is involved in the development of nicotine dependence.

• How did we get there?

NICSNP ProjectNICSNP 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 AddictionPrincipal Investigator: Pamela Madden (R01 DA 012854)

• Genes for Smoking in Related and Unrelated IndividualsPrincipal Investigator: Ovide Pomerleau (R01 DA 017640)

• Pharmacokinetics of Nicotine in TwinsPrincipal Investigator: Gary Swan (R01 DA 011170)

NIDA Phenotypic Repository John Rice

Perlegen Sciences Dennis Ballinger

Fagerström Test for Nicotine Dependence

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.

Questions Response Options Score

1. How soon after you wake up do you smoke your first cigarette?

Within 5 minutes6-30 minutes

31-60 minutesAfter 60 minutes

3210

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.?

YesNo

10

3. Which cigarette would you hate most to give up? The first one in the morningAll others

10

4. How many cigarettes per day do you smoke? 10 or less11-2021-30

31 or more

0123

5. Do you smoke more frequently during the first hours after waking than during the rest of the day?

YesNo

10

6. Do you smoke if you are so ill that you are in bed most of the day?

YesNo

10

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

rs16969968Saccone et al., 2007

SNPs highly correlated with rs16969968

Findings for Nicotine Dependence

rs16969968Saccone et al., 2007Bierut et al., 2008Sherva et al., 2008Weiss et al., 2008Stevens et al., 2008

rs1051730Saccone et al., 2007Thorgeirsson et al., 2008Amos et al., 2008Spitz et al., 2008

rs1317286Berrettini et al., 2008

Results from Candidate Gene Study

Saccone et al., 2007

The correlation between rs16969968 and rs578776 is < 0.2.

There are two distinct findings in the nicotinic gene cluster associated with nicotine dependence.

Genetic Association and the Nicotinic Receptors - Chromosome 15

rs578776Saccone et al., 2007

Genetic Association and the Nicotinic Receptors - Chromosome 15

rs578776Saccone et al., 2007Bierut et al., 2008Weiss et al., 2008Stevens et al., 2008

rs6495308Berrettini et al.,2008

Nature Genetics, 2008

Nature, 2008

Nature, 2008

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*

PLOS Genetics, 2009

SNPs highly correlated with rs16969968

Findings for Nicotine Dependence, Lung Cancer, COPD

rs16969968Saccone et al., 2007Bierut et al., 2008Sherva et al., 2008Weiss et al., 2008Stevens et al., 2008 rs1051730

Saccone et al., 2007Thorgeirsson et al., 2008Amos et al., 2008Hung et al., 2008Thorgeirsson et al., 2008Liu et al., 2008Pillai et al., 2009

rs1317286Berrettini et al., 2008

rs8034191Amos et al., 2008Hung et al., 2008Liu et al., 2008Pillai et al., 2009

SNPs highly correlated with rs578776Findings for Nicotine Dependence and Lung Cancer

rs578776Saccone et al., 2007Bierut et al., 2008Weiss et al., 2008Stevens et al., 2008Hung et al., 2008Liu et al., 2008

rs6495308Berrettini 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

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 thehorizontal lines.

Biologic Psychiatry

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

Number of Genes genes

Number of Studies

Genes reported associated with schizophrenia

Number of Genes genes

Number of Studies

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 Reis-

Merikangas

Risch, N. et al. JAMA 2009;301:2462-2471.

Logistic Regression Analyses of Risk of Depression for 14 Studies

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.

(n=673) (n=179) (n=664) (n=218) (n=190) (n=58)

parental monitoring

rs16969968=GG (Reference)

rs16969968=GA (OR=1.17)

rs16969968=AA (OR=2.11***)

* p<.05, ** p<.01, *** P<.001 compared to the reference group (GG & higher quartiles)

Average odds ratio for specific genotype

***** ***

***

Gene and Parental Monitoring Interplay

Chen et al., 2009

Gene and Peer Smoking Interplay

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 1 2 3 4 5 6 7 8

G/G

A/G

A/A

95% C.I.

Pre

dict

ed P

roba

bilit

y o

f Nic

otin

e D

epen

denc

e*

Number of Smoking Peers

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 1 2 3 4 5 6 7 8

G/G

A/G

A/A

95% C.I.

Pre

dict

ed P

roba

bilit

y o

f Nic

otin

e D

epen

denc

e*

Number of Smoking Peers

Johnson et al., in review

rs16969968

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 CurvesPower and Effect Size by prevalence of comorbid disorder, given sample size N=2689

Prepared by Hong Xian

Sample Size CurvesRequired 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

European American Subjects

Eligible Subjects 706 2,473

Donated blood for genetic study of Nicotine Dependence

50471% of eligible

1,41557% of eligible

p<0.0001 for difference in participation rates between European Americans and African Americans (χ2 test)

African American Subjects Participate in Genetic Studies

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.

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 1 of 646 8 of 32,442 4 of 646 58 of 32,442 1 of 646 7 of 32,442

Scotland 2 of 211 0 of 229 2 of 211 0 of 229 1 of 211 0 of 229

Germany 1 of 195 0 of 192 3 of 195 0 of 192 1 of 195 0 of 192

England 0 of 105 0 of 96 1 of 105 0 of 96 0 of 105 0 of 96

Italy 0 of 85 0 of 91 0 of 85 0 of 91 0 of 85 0 of 91

Finland 0 of 191 0 of 200 0 of 191 1 of 200 0 of 191 0 of 200

Total 4 of 1,433 8 of 33,250 10 of 1,433 59 of 33,250 3 of 1,433 7 of 33,250

OR 8.68 (1.02, 49.76)

3.90 (1.42, 9.37)

8.94 (0.79, 58.15)

P-value 0.024 0.007 0.040

Nominal association of deletions at 1q21.1, 15q11.2 and 15q13.3 with schizophrenia and related psychoses in the phase I sample

From Stefansson et al. (2008) Large recurrent microdeletions associated with schizophrenia. Nature 455: 232-236.

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.

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 Remission- The Final Step

Initiation

Cigarette Use

Nicotine Dependence

Cessation and Remission

Phenotypic and genetic data are available to qualified investigatorsthrough the NIDA Genetics Consortium and dbGaP.