Human Genetics and Gene Mapping of Complex Traits

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1 Human Genetics and Gene Mapping of Comple Traits Advanced Genetics, Spring 205 Human Genetics Series Tuesday 4/07/5 Nancy L. Saccone,

2 What is different aout Human Genetics (recall from Cristina Strong's lectures) Can study comple ehaviors and cognition, neurgenetics Etensive sequence variation leads to common/comple disease. Common disease, common variant hypothesis 2. Large # of small-effect variants 3. Large # of large-effect rare variants 4. Como of genotypic, environmental, epigenetic interactions Imprinting uniquely mammalian Trinucleotide repeat diseases "anticipation Greg Gison, Nature Rev Genet 202 Clinical impact

3 Testing for interactions GG (epistasis), GE Question: Does the effect of st variale on the outcome differ for different values of the 2 nd variale?

4 GE interaction eample not in humans Cooper and Zuek, rat strains: "maze dull" and "maze right" - selectively red ased on maze performance. Then, two environments: - normal la rearing - "enriched" environment (e.g. playthings, open space)

5 Animal models Cooper and Zuek, 958: mean numer of learning errors normal maze dull maze right enriched as presented in Rowe, 2003

6 Other possile outcomes Another way to get a GE interaction: cross-over normal maze dull maze right enriched

7 Possile outcomes Here's what we might see if there were main effects only (no GE interaction) normal maze dull maze right enriched

8 Possile outcomes another possiility: if no GE interaction AND no main effect of environment normal maze dull maze right enriched

9 Testing for interactions Traditional approach is to use a product term in the regression model Eample (case-control logistic regression analysis) Let P = proaility of eing a case Let = SNP genotype (additive coding) 2 = se (0=male, =female) P ln - P = + 22 To test for interaction etween and 2, i.e. does the SNP effect differ in men vs women: ln P = ( ) - P 2 Is there significant evidence that 3 is different from 0?

10 Eample: = SNP genotype, 2 = se Full model with interaction: Odds Ratio for SNP when 2 = 0 (male) Odds Ratio for SNP when 2 = (female) ] [ e P P [...] 0 [...] 0 0, [...] 0, [...] 0 0 ) /( ) /( e e e e e P P P P OR male [...] [...] 0, [...], [...] 0 0 ) /( ) /( e e e e e P P P P OR female

11 Genomic Imprinting Occurs in mammals (insects, plants) Departure from classical Mendelian genetics: Maternally and paternally inherited alleles are distinguished Epression of allele depends on parent of origin Can e tissue specific Called maternally imprinted if maternal allele is inactive Paternally imprinted if paternal allele is inactive Eample of epigenetics (study of inherited factors that are independent of the DNA sequence itself)

12 Imprinting can generate non-mendelian patterns Trait manifests only when allele is inherited from the mother: Trait manifests only when allele is inherited from the father: Dots indicate non-epressing carriers From Weiss, Genetic variation and human disease, 993 / Hall, 990a, ASHG

13 Genomic Imprinting and Human Disease Prader-Willi Syndrome and Angelman Syndrome (see Joe Dougherty s lecture) Beckwith-Wiedemann Syndrome IGF2 gene normally is imprinted in humans, with the maternal allele silenced Improper activation of the maternal allele leads to BWS Symptoms: overgrowth, increased risk of cancer

14 From Hartl, Essential Genetics 6 th Ed. Genomic Imprinting and Human Disease Prader-Willi Syndrome and Angelman Syndrome

15 Moving from GWAS to post-gwas: Genetics, clinical impact and personalized medicine Priorities for Personalized Medicine Report of the President s Council of Advisors on Science and Technology Septemer 2008 Eecutive Summary Personalized medicine refers to the tailoring of medical treatment to the individual characteristics of each patient. It does not literally mean the creation of drugs or medical devices that are unique to a patient, ut rather the aility to classify individuals into supopulations that differ in their susceptiility to a particular disease or their response to a specific treatment. Preventive or therapeutic interventions can then e concentrated on those who will enefit, sparing epense and side effects for those who will not.

16 Moving from GWAS to post-gwas: Genetics, clinical impact and personalized medicine 20: Green and Guyer (NHGRI), Nature 20: Base pairs to edside not just ench to edside 205: President Oama announced $25 million Precision Medicine Initiative Ojectives: Cancer treatment Voluntary national research cohort (compare with UK research facilitated y nationalized healthcare) Privacy protection Modernizing regulatory landscape Pulic-private partnerships Fact sheet at

17 Improving the effectiveness of healthcare: e.g. genomics to guide personalized medicine E D. Green and M.S. Guyer Nature 20

18 Pharmacologic Treatment Costs/Challenges Side effects Adherence Use restrictions Cost Benefits Efficacy Genomics can guide personalized medicine

19 Smoking cessation pharmacotherapy as an eample But first, some history.

20 2003 The dramatic reduction in smoking [in the US] has een one of the most important recent pulic health successes. The potent effect of pervasive societal changes on [smoking] ehavior will far outweigh any possile enefits of identification of risk genes for individual smokers

21 2006 Genetics studies should e acknowledged as currently unlikely to lead to improved lung cancer prevention compared with the proven, non genetic-ased strategies for smoking cessation

22 Current smoking rates (CDC data) Year % of US adults who were current smokers % % % % % What we have is not enough: Increased social pressure Policy changes Heightened awareness of health consequences Availale pharmacotherapy (e.g. nicotine replacement, others)

23 CHRNA5 predicts cessation success and response to medication Pharmacogenetics and Genomics: Feruary Volume 23 - Issue 2 - p Nicotinic acetylcholine receptor variation and response to smoking cessation therapies Bergen, Andrew W. a ; Javitz, Harold S. a ; Krasnow, Ruth a ; Nishita, Denise a ; Michel, Martha a ; Conti, David V. ; Liu, Jinghua ; Lee, Won ; Edlund, Christopher K. ; Hall, Sharon c ; Kwok, Pui-Yan d ; Benowitz, Neal L. e ; Baker, Timothy B. f ; Tyndale, Rachel F. h ; Lerman, Caryn g ; Swan, Gary E. a

24 Study Design University of Wisconsin TTURC N=073, European Ancestry All sujects received intensive ehavioral counseling Pharmacotherapy arms (NRT, upropion, como) and placeo arm Cessation Astinence at 60 days Time to relapse over 60 days Chen, Baker et al, Am J Psychiatry 202 CHRNA5 haplotype rs Functional amino acid change in CHRNA5 rs CHRNA5 mrna levels in rain and lung Haplotype of 2 variants H (GC, 20.8%) (high risk for dependence) H2 (GT, 43.7%) H3 (AC, 35.5%), low risk for dependence

25 CHRNA5 Predicts Cessation & Response to Medication Astinence 00% Smokers with CHRNA5 low risk 90% Smokers with CHRNA5 high risk 80% 70% 60% 50% 40% 30% Placeo + Counseling Counseling alone Counseling Medication + Medication Counseling 20% 0% 0% Chen, Baker et al, Am J Psychiatry 202 H H2 H3 H: LOW RISK H2 H3: HIGH RISK

26 Numer Needed to Treat (NNT) Varies y Genetic Status Astinence 00% 90% NNT > 000 NNT = 4 NNT: Numer of patients to treat for to enefit 80% 70% 60% 50% 40% 30% Placeo + Counseling Counseling alone Counseling Medication + Medication Counseling 20% 0% 0% H H2 H3 H: LOW RISK H2 H3: HIGH RISK Chen, Baker et al, Am J Psychiatry 202

27 In smokers with high genetic risk, NNT for cessation medication compares very well to current evidence-ased clinical treatments Disorder Treatment Numer needed to treat (NNT) Duodenal Ulcer H Pylori Antiiotics 2 COPD Anticholinergic 6 Stroke Alteplase Hypercholesterolemia Statins Nicotine Dependence NRT 4 in CHRNA5 high risk gp 000 in CHRNA5 low risk gp UpToDate, 203

28 Summary Human gene mapping for comple diseases/traits: Linkage (e.g. Model-ased or model-free analyses in families) Association (e.g. allele/genotype frequency differences unrelated cases-controls; linear and logistic regression; effect size) Genome-wide association studies Linkage disequilirium (LD) Power when tested SNP is in LD with causal SNP Genetic imputation GG and GE interactions Visualizing interactions vs main effects Testing with a product term Imprinting Genomics and personalized medicine (e.g genotype-y treatment interactions)