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Application of Genetic Tools to Clinical and Translational Research. Thomas A. Pearson, MD, PhD University of Rochester School of Medicine Visiting Scientist, NHGRI. TAProots Vineyard Keuka Lake, NY. Concord Grapes. One year old French hybrid grapes. Vanessa Seedless Grapes.

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Application of genetic tools to clinical and translational research l.jpg

Application of Genetic Tools to Clinical and Translational Research

Thomas A. Pearson, MD, PhD

University of Rochester

School of Medicine

Visiting Scientist, NHGRI


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TAProots Vineyard Research Keuka Lake, NY


Concord grapes l.jpg
Concord Grapes Research




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Lecture 8. Application of Genetic Tools to Clinical and Translational Research

  • Examine the basis for inferring that gene variants are causal for a disease.

  • Consider the use of genetic tools in personalized medicine

    a. Genetic Screening/susceptibility assessment

    b. Pharmacogenomics

  • Discuss the application of genetic tools to future observational and experiential studies.


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Contributions of GWAS to Basic Science Translational Research

Genome structure and function

Exons, introns Regulatory elements

Novel mechanisms of disease

Proteins as therapeutics

Drug targets

  • Mass screening of small molecule inhibitors


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U.S. Surgeon General’s Translational ResearchCriteria for Causal Association

  • Temporal relationship

  • Strength of the association

  • Dose-response relationship

  • Replication of findings

  • Biologic plausibility

  • Consideration of alternate explanations

  • Cessation of exposure

  • Consistency with other knowledge

  • Specificity of the association

* Report of the Advisory Committee to the Surgeon General, 1964




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GWAS AssociationDemonstrating Risk Per Allele for Breast Cancer*

*Easton, DF, et al. Nature 2997; 447: 1087-1093



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Possible Explanations of Heterogeneity of Results in Genetic Association Studies

  • Biologic mechanisms

    • Genetic heterogeneity

    • Gene-gene interactions

    • Gene-environment interactions

  • Spurious mechanisms

    • Selection bias

    • Information bias

    • Publication biasConfounding (population stratification)

    • Cohort, age, period (secular effects

    • Type I error


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Structure of Human Genes: Association StudiesPotential Sites of Gene Variation

  • Exons

  • Introns

  • Regulatory Elements

    • Promoters

    • PolyA Tail

    • Enhanceers

    • Silencers

    • Locus Control Regions


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GWAS to Identify Novel Breast Cancer Susceptibility Loci* Association Studies

  • Known breast cancer loci explain <25% of familial risk.

  • Two stage study of 4398 cases and 4316 controls with replication of 30 SNP’s in 21,860 cases and 22,578 controls.

  • 227,876 SNP’s genotyped.

  • 5 novel loci related to breast cancer at P<I0-7 explain an additional 3.6% of familial risk.

  • 1792 additional SNP’s associated at P<.05 with 1343 expected, suggesting many additional susceptibility alleles exist.

Easton DF, et al. Nature 2007; 447: 1087-1093



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Intervention in Children with Hutchinson-Gilford Progeria Syndrome*

  • Rare disorder of accelerated aging with death from cardiovascular disease by age 13 years.

  • Defect is a glycine GGC to glycine GGT in codon 608 of exon 11 of lamin A gene.

    • Activates a cryptic splice donor to produce an abnormal protein, Lamin A.

    • Lamin A or progerin cannot release from farnesyl-cysteine tether site on the nuclear membrane and alters transcription.

  • Farnesyl transferase inhibition prevents anchoring of progerin in fibroblasts and in transgenic mouse models.

  • Open label clinical trial of inhibition of farnesyl transferase with ABT 100 is underway.

*Merideth MA, et. al. NEJM 2008; 358: 592-604


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GWAS Identifies Gene Variant rs4430796 Which Confers Risk for Prostate Cancer and Protection from Type 2 Diabetes*

*Gundmundsson J, et al. Nat Gen 7/1/07


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Personalized Medicine for Prostate Cancer and Protection from Type 2 Diabetes*

“At its most basic, personalized medicine refers to using information about a person’s genetic make-up to tailor strategies for detection, treatment, and prevention of disease”

Francis Collins,

Director, NHGRI

7/17/05


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Screening of Family Members of Patients Admitted with Coronary Heart Disease

  • 5620 consecutive patients admitted to 53 randomly selected hospitals for MI, coronary bypass or angioplasty, or unstable angina.

  • Medical record review of discharge plans.

    • 37/5620 (0.7%) identified plan to screen first degree relatives.

  • Follow-up 6 months after discharge

    • 16% of children screened for risk factors.

    • Little variance based on risk or risk factors of proband.

Swanson JR, Pearson TA. Am J Prev Med 2001; 20:50-55


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Larson, G. Coronary Heart DiseaseThe Complete Far Side. 2003.


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The U.S. Surgeon General’s Family History Initiative Coronary Heart Disease

  • My Family Health Portrait

    • Web-based tool to collect and organize family history information

      https://familyhistory.hhs.gov

    • Printout for sharing with healthcare providers

  • National Family History Day (Thanksgiving)

    • Encourage Americans to talk about and write down health problems running in their family


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Some Conditions for Which Newborn Screening Has Been Implemented

Nussbaum R. Thompson and Thompson’s Medical Genetics, 2007


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Criteria for an Effective Screening Program Implemented

Analytic Validity

Clinical Validity

Clinical Utility

1. Condition is frequent to justify cost

2. Detection would otherwise not occur at early enough stage

3. Early treatment prevents morbidity

4. Treatment is available

5. Families and personnel available to perform screening, inform about results, and institute treatment.


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Barriers to Application of Genetic Markers to Clinical Preventive Medicine*

  • Lack of information on how the prevalence and risk contribution of markers varies across population groups.

  • Limited data on how the inheritance of multiple markers affects an individual’s risk

  • Little information on how most genetic risk factors interact with environmental factors

  • Few studies on common diseases that test the effect of interventions on genetic risk factors

Faero WG, Guttmarker AE, Collins FS. JAMA 2008; 299


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Cost – Effectiveness Trial of New Biomarker Test Preventive Medicine*Patients at Risk For Disease

Randomization

New Test

Usual Care

High Risk

Low Risk

Treatment

No Treatment

Treatment

No Treatment

Outcome Measures: Clinical Events, Costs, etc.


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Commercial Direct-to-Consumer Genomic Testing* Preventive Medicine*

*Offit K. JAMA 2008, 299; 1353-4


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Larson, G. Preventive Medicine*The Complete Far Side. 2003.


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BRCA1 and BRCA2: Preventive Medicine*Estimated Lifetime Risk of Cancer*

Antoniou, et al. ASHG 2003; 72: 1117


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BRCA 1&2 Testing* Preventive Medicine*

  • Current testing does not identify all genetic risk and explains relatively little of total incidence.

  • Recommend testing affected relative: if positive, offer to unaffected relatives.

  • Costs: BRCA 1/2 sequencing ($3200), supplemental testing ($650), test for single known mutation ($350).

  • Preventive options for BRCA 1/2+ women

    • Prophylactic surgery

    • Tamoxifen (may be effective only in BRCA 2)

    • Early breast screening or breast MRI

Burke W, Jackson Laboratory 7/26/08


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Delivery of Genomic Medicine for Common Chronic Diseases: A Systematic Review

Scheuner MT, et al. JAMA 2008; 299: 1320-1334


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GINA: The Genetic Information Non-Discrimination Act 2007-2008

  • Prohibits health insurers from requesting or requiring genetic information of an individual or their family members or using it for decisions on coverage, rates, etc.

    • Includes participation in research that includes genetic services

  • Prohibits employers from requesting or requiring information or using it in decisions regarding hiring, firing, or terms of employment


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Pharmacogenetics 2007-2008: The study of differences in drug response due to allelic variation in genes affecting drug metabolism, efficacy, and toxicity.

  • Drug metabolism under genetic control

    • Hydroxylation

    • Conjugation

      • Glucuronidation

      • Acetylation

      • Methylation

  • Phenotypes of drug metabolism

    Normal metabolizers

    Poor metabolizers

    Ultrafast metabolizers


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Frequency of Slow-Acelylator Phenotype Affecting Isoniazid Metabolism

BurroughsVJ, et al., cited in Nussbaum R,

Thompson and Thompson’s Genetic Medicine, 2007



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Policy for Sharing of Data Obtained in NIH Supported and Conducted GWAS (NOT-OD-07-088)

Goal:

To make available the genotype and phenotype datasets as rapidly as possible to a wide range of scientific investigators.

Components:

Data repository (NCBI, dbGAP)

Data submission and protection

Data access

Publication

Intellectual property


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Investigators Requesting and Receiving GWAS Data Conducted GWAS (NOT-OD-07-088)

  • Submit a description of proposed research project

  • Submit a data access request, co-signed by Institutional Official

  • Protect data confidentiality

  • Ensure data security measures are in place

  • Notify appropriate Data Access Committee of policy violations, if any

  • Submit annual reports on research findings


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Conclusions Conducted GWAS (NOT-OD-07-088)

  • Evidence for the causal association of gene polymorphisms in common chronic diseases is still in formative stages

  • Application of products of genomics research such as susceptibility assessment and pharmacogenomics holds promise but barriers persist

    • Technologies are currently being marketed to consumers

    • Survey evidence suggesting low level of genetic knowledge in consumers and low levels of skills in providers

  • Genome research has been a boom for basic scientists; clinical investigators should ready themselves to participate in this developing field


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    Sample Collection Conducted GWAS (NOT-OD-07-088)and Processing

    • Obtaining samples for DNA preparation

      • Blood

      • Buccal cells

      • Serum

      • Pathology specimens

      • Other?

    • Purifyign and quantifying DNA

    • Whole genome amplification (WGA)

    • Trace individual DNAs (QC)

    Courtesy S. Chanock, NCi


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