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Title: Selection of Candidate Genes for Population Studies


1
Selection of Candidate Genes for Population
Studies
  • Zuo-Feng Zhang, MD, PhD
  • Epidemiology 243 Molecular Epidemiology

2
Gene Selection for Molecular Studies
  • Selection of putative genetic factors is the
    central issue of the molecular epidemiological
    studies even thought the selection of the
    putative risk factors are equally important
    because of the focus of the molecular
    epidemiology is the assessment of
    gene-environment interaction

3
Two Types of Genes
  • High Risk Genes
  • Low Risk Genes

4
Familiar Disease Genes (High Risk Gene)
  • -High penetrance
  • -High AR/RR
  • -Gene frequency low (lt1)
  • -Study setting family
  • -Study type Linkage
  • -PAR low
  • -Role of Environment Modest

5
Example of High Risk Genes
  • Mutations of TP53 gene
  • BRCA1 and BRCA2
  • RB gene mutations

6
Susceptibility Genes (Low Risk Genes)
  • -Low penetrance
  • -Low AR/RR
  • -Gene frequency high (gt1-90)
  • -Study setting population
  • -Study type association
  • -PAR high
  • -Role of Environment critical

7
Approach for High Risk Genes
  • Functional approach (forward genetics) from
    genotype to phenotype
  • Positional approach (reversed genetics) from
    phenotype to genotype

8
Functional Approach An Example
  • From patients with DNA repair defects
  • a cell line is created
  • Add certain fragment of human chromosome
  • Produce a repair component phenotype

9
Positional Approach
  • Linkage analysis
  • Loss of heterozygosity (LOH)
  • Chromosome abnormalities

10
Linkage analysis
  • It is method to identify the disease loci
  • Family based, need sufficient sample size
  • Germline DNA from affected and unaffected
    individuals
  • A genetic mechanism (autosomal dominant/recessive)
  • A set of markers

11
Loss of Heterozygosity (LOH)
  • Need both normal and tumor tissues
  • The loss of signal in targeted tissue (tumor) in
    comparison with normal tissue
  • If LOH consistently observed in a particular
    region, an indication of an important gene is
    indicated in the region.

12
Chromosome Abnormalities
  • Deletion
  • Insertion
  • Microsatellite instability

13
In-depth Approaches to Identify Candidate Genes
  • When above three methods indicate a region in
    chromosome, further work is needed to identify
    particular candidate genes
  • -Mutation screening
  • -restoration of normal phenotype by transfection
    of a normal allele
  • -mouse model of disease by introducing defective
    mutations

14
Approaches for Low Risk Genes
  • Linkage analysis may not be feasible because it
    requires a relatively large sample size (If the
    OR2, 2500 family would be needed)

15
Approaches for Low Risk Genes
  • New techniques will be needed to identify the low
    risk susceptibility genes
  • -Automated micro-array genechips
  • -SNP identification

16
Selection of Putative Genes (1)
  • Inter-individual variation in the trait exist in
    the population
  • -If there is very small variation of the
    phenotype in the population, the rationale to
    examine the genotype is weak.
  • -If there is a very large variation of the
    phenotype, other potential factors need to be
    considered

17
Selection of Putative Genes (2)
  • The gene is involved in the process related to
    carcinogenesis
  • -DNA repair
  • -Chromosome stability
  • -Activities of oncogenes/tumor suppressor genes
  • -cell cycle control/signal tranduction

18
Selection of Putative Genes (3)
  • The trait exhibits an inheritance pattern
    consistent with Mendelian transmission
  • Any phenotype should have a genetic basis

19
Selection of Putative Genes (3)
  • Certain phenotypes such as mutagen sensitivity
    has been reported to be associated with many
    smoking related cancers, however, the precise
    nature of this susceptibility factor remains
    incompletely understand because the genotype
    associated with mutagen sensitivity is still
    unclear.

20
Selection of Putative Genes (4)
  • Gene action exists in relevant organ.
  • -CYP1A1 is largely absent from liver, but
    present in lung
  • -CYP2D6 is expressed in brain
  • -GSTM1 has some expression in lung
  • -GSTP1 is expressed in lung

21
Selection of Putative Genes (5)
  • Gene location and characterization.
  • -Similar gene structure may indicate similar
    function
  • -Most of mutations occur in the coding sequence,
    but mutations in intragenic noncoding may occur
  • -Specific point mutation may indicate specific
    exposures

22
Selection of Putative Genes
  • Polymorphisms and mutation
  • Gene-Gene interactions
  • Animal models
  • Human studies
  • Genotype-phenotype
  • Relation to disease
  • Ethnic variation

23
Selection of Putative Genes
  • Gene-Gene interaction (phase I and phase II).
  • -CYP1A1 and GSTM1 and lung cancer risk, PAH
    (carcinogens)
  • -CYP2A6 and CYP2D6, NNK

24
2-1. BackgroundThe summary of characteristics
and significance of the genes of interest.
25
2-1. Background Theoretical model of
gene-gene/environmental interaction pathway
26
2-1. Background Theoretical model of
gene-gene/environmental interaction pathway
27
2-1. Background Theoretical model of
gene-gene/environmental interaction pathway
GSTM1
28
2-1. Background Theoretical model of
gene-gene/environmental interaction pathway
DNA damage repaired
Defected DNA repair gene
If DNA damage not repaired
If loose cell cycle control
29
DNA damage repaired
Defected DNA repair gene
If DNA damage not repaired
If loose cell cycle control
30
2-1. BackgroundThe summary of epidemiological
literature for the genes of interest
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UCLA Prostate Cancer SPORE Development
ProjectSingle Nucleotide Polymorphisms (SNPs) of
Genes in the DNA Double Strand Break Repair
(DSBR) Pathways and Risk of Prostate Cancer, A
Preliminary Study
  • Zuo-Feng Zhang, MD, PhD
  • Department of EpidemiologyUCLA School of Public
    Health

38
Epidemiological Observations Involvement of DSBR
Pathway Genes in Prostate Cancer Risk
  • The risk of prostate cancer is known to be
    elevated in carriers of germline mutations in
    BRCA2
  • Increased risk of prostate cancer is also
    observed in carriers of BRCA1 and CHEK2
    mutations, and also associated with SNPs of the
    ATM genes
  • Those observations indicate possible involvement
    of DNA DSBR pathway genes

39
Non-homologous Recombination
homologous recombination
BRCA1
BRCA2
Damage recognition cell cycle delay response
(DRCCD )
ATM
CHEK2(RAD53
BRCA1
40
Hypotheses
  • Single Nucleotide Polymorphisms (SNPs) of genes
    in the DNA Double Strand Break Repair (DSBR)
    Pathways may be associated with the
    susceptibility to prostate cancer.
  • We further hypothesize that the SNPs of the DSBR
    may interplay each other and may modify effects
    of environmental factors on the risk of prostate
    cancer.

41
Specific Aim 1
  • To assay Single Nucleotide Polymorphisms (SNPs)
    of genes in double strand break (DSB) repair
    pathway, including genes involved in Homologous
    Recombinational Repair (HRR) RAD51, RAD52,
    RAD54L, NBS1, XRCC2, XRCC3, BRCA1, and BRCA2
    LIG4, and XRCC4 in Non-homologous end-joining
    (NHEJ), ATM, BRCA1, CHEK1, CHEK2 (RAD53), P53,
    and HUS1 in damage recognition cell cycle delay
    response (DRCCD) pathway.

42
Specific Aim 2
  • To evaluate independent effect of SNPs of the DSB
    repair pathway when potential confounding
    factors, such as age, race, and education and to
    assess potential combined effects of SNPs
  • To explore possible effect modifications on
    nutritional factors on the risk of prostate
    cancer.

43
Proposed Experimental Approach
  • This study is based on a case-control study with
    a total of 122 cases with prostate cancer and 135
    healthy controls. All cases and controls were
    interviewed by a research nurse using a standard
    epidemiological questionnaire at MSKCC from 1993
    to 1997.
  • Blood samples and tumor tissue specimens were
    collected.
  • The SNPs will be genotyped in individual DNA
    samples using the SNPlex platform by ABI. The
    UCLA Sequencing and Genotyping Core Facility has
    recently added Applied Biosystems
    high-throughput SNP genotyping assay SNPlex
    to the available services. This assay is
    flexible, robust and highly reproducible.

44
JCCC Genotyping Core ABI SNPlex, a New High
Throughput Approach to Identify SNPs of
Susceptibility Genes
www.genetics.ucla.edu/genotyping
45
Zhang Lab SNP GenotypingPilot Project
  • 75 passed design process
  • 48 SNPs chosen for first pool
  • Whole Genome Amplification of DNA for 3080
    samples
  • 122,496 SNPs since genotyped since January

46
Preliminary Results
  • 99.4 reproducibility by automated scoring.
  • 99.7 reproducibility by manual scoring.
  • 6 SNPs never worked
  • 96 call rate of remaining markers
  • Comparable to results reported by other labs

47
Study Population
48
Progress of the Study
  • Specific Aim 1, we have assayed selected single
    nucleotide polymorphisms (SNPs) of genes in
    double strand break repair (DSBR) pathway,
    including genes BRCA1, NBS1, TP53, APEX1, CHEK1,
    CHEK2, and ATM in 68 cases with prostate cancer
    and 90 healthy male controls using ABI SNPlex
    platform.

49
Progress of the Study
  • Specific Aim 2, we explored independent effect of
    SNPs of the genes mentioned above in the DSBR
    pathway when potential confounding factors, such
    as age, race, and education were controlled.

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Results of Preliminary study
  • The adjusted ORs are
  • 4.6 (95CI 0.6-34.1) for BRCA1 (rs8176109) 5.0
    (95 CI 1.1-22.3) for NBS1 (rs9995)
  • 3.1 (95CI 0.46-21.2) for TP53 (rs2909430)
  • 2.0 (95CI 0.49-8.02) for APEX1 (rs3136820) 2.6
    (95CI 0.58-11.6) for CHEK1 (rs506504)
  • 0.6 (95CI 0.17-2.3) for ATM (rs228591).

52
Future Plan
  • We will continue our proposed specific aims by
    assaying additional SNPs in the DSBR pathway
    genes as well as other pathways including other
    DNA repair pathways, metabolic, inflammatory, and
    cell cycle pathways among prostate cancer cases
    and controls. We will explore the independent
    effect of those SNPs on the risk of prostate
    cancer. We will also add the haplotype tagging
    SNPs of the DSBR pathways in order to identify
    haplotypes associated with prostate cancer risk.
    Those additional studies will have a greater
    impact on the translational research objectives
    of the SPORE.

53
BRCA1 Haplotypes and Risk of Prostate Cancer
54
Translational Potential of the Study
  • Our results with relatively small samples size
    suggest potential involvement of SNPs of the DSBR
    pathway genes in the development of prostate
    cancer.
  • If confirmed by studies with larger sample size,
    SNPs in DSBR pathway genes may be used in
    individual risk assessment, and identification of
    high risk population for intervention and
    chemoprevention

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The Selection Criteria of SNPs
  • functional SNPs if possible
  • amino-acid-changing SNPs
  • SNPs in the functional region of the gene or SNPs
    without amino acid changes that were hypothesized
    to affect the transcription/ translation of the
    protein
  • the rare allele frequency of SNPs must be equal
    to or higher than 5 in the general population

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Proposed Study of Lung Cancer among Non-smokers
61
Motives and Conceptual Framework For Study of
Genetic Susceptibility to Lung Cancer among
Non-smokers
  • About 16 of the male smokers and 10 of female
    smokers will eventually develop lung cancer,
    which suggest exposures to other environmental
    carcinogens and individual genetic susceptibility
    may play an important role among non smoking lung
    cancer.
  • It is suggested that 26 of lung cancer are
    associated with genetic susceptibility
    Lichtenstein P, et al. NEJM, 2000)
  • We hypothesize that the variation of genetic
    susceptibility or single nucleotide polymorphisms
    (SNPs) of genes in inflammation, DNA repair, and
    cell cycle control pathways may be important on
    the development of lung cancer among non-smokers.

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DNA damage repaired
Defected DNA repair gene
If DNA damage not repaired
G0
If loose cell cycle control
64
Issues in genetic association studies
  • Many genes
  • 25,000 genes, many can be candidates
  • Many SNPs
  • 10,000,000 SNPs, ability to predict functional
    SNPs is limited
  • Methods to select SNPs
  • Only functional SNPs in a candidate gene
  • Systematic screen of SNPs in a candidate gene
  • Systematic screen of SNPs in an entire pathway
  • Genomewide screen
  • Systematic screen for all coding changes

65
Selection of SNPs(Genome-wide association
studies)
  • Molecular
  • Higher requirements Affymetrix and Perlegen
  • Analytical
  • Highest requirements Data management, automation
  • Advantages
  • No biological assumptions and can identify novel
    genes/pathways
  • Excellent chance to identify risk alleles
  • Utility in individual risk assessment
  • Disadvantages
  • High costs
  • Concern of multiple tests

66
500K SNP Coverage Median intermarker distance
3.3 kb Mean intermarker distance
5.4 kb Average Heterozygosity
0.30 Average minor allele frequency
0.22 SNPs in genes 196,384 80 of genome within
10kb of a SNP
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LIG SNP and Passive Smoking
69
Figure 1. The effects of SNPs on the Risk of Lung
Cancer among Smokers and Non-smokers
OR
70
Hypothesis
  • The overall hypothesis is that multiple sequence
    variants in the genome are associated with the
    risk of lung cancer among non-smokers.
    Specifically, we hypothesize that a number of
    common nonsmoking lung cancer risk-modifying SNPs
    are in strong LD with the SNPs arrayed on the
    500K GeneChip.

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Specific Aims
  • Aim 1. To perform exploratory tests for
    association between 500K SNPs across the genome
    and lung cancer risk among 200 non-smoking lung
    cancer patients and 200 controls.
  • Aim 2. To perform first stage of confirmatory
    association tests between lung cancer risk and
    more than 1,000 SNPs implicated in Aim 1 among an
    independent set of 600 pairs of cases and
    controls.

75
Specific Aims
  • Aim 3. To perform second stage of confirmatory
    association tests between lung cancer risk and
    more than 500 SNPs that were replicated in Aim 2
    among an additional 600 cases and 600 controls.
    Additional SNPs will also be added from our
    ongoing pathway specific analyses of DNA repair,
    cell cycle regulation, inflammation and metabolic
    pathways based on non-smokers in our lung cancer
    study.
  • Aim 4. To perform fine mapping association
    studies in the flanking regions of each of the
    30-100 SNPs confirmed in Aim 3 among the entire
    1,400 cases and 1,400 controls. The large number
    of cases with non-smoking lung cancer in this
    study population also allows us to identify SNPs
    that are associated with risk of the disease
    among nonsmokers.

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Specific Aims
  • Aim 5. To explore the generalizability of the
    SNPs identified in Specific Aims 1-4 within a
    Chinese population of 600 nonsmoking lung cancer
    cases and 600 nonsmoking controls. The relatively
    homogeneous Chinese population not only allows us
    to further confirm the associations, but also
    improves our ability to finely map the SNPs
    associated with lung cancer risk among
    non-smokers.

77
Discussion Costs
  • Affy 500 k SNP chip 1000/case
  • 2000 x 10002m
  • 1000 x 10001m
  • 500 x 10000.5 M
  • 500 x 3000 (SNP) x 0.15225, 000
  • 500 x 30 (SNP) x 0.15 2,250

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1040 controls, 601 head and neck cancer cases,
and 611 lung cancer cases
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GSTM1 and Lung Cancer among Non-Smokers
1.19 0.69-2.03
GSTM1 Normal
Null Smoking No
No
81
GSTT1 and Lung Cancer among Non-Smokers
1.53 0.83-2.81
GSTT1 Normal Null
Smoking No
No
82
p53 codon 72 and Lung Cancer among non-smokers
0.79 0.32-1.95
p53 A/A or A/P P/P Smoking No
No
83
GSTP1 and Lung Cancer among Non-Smokers
0.69 0.39-1.24
GSTP1 Ile/Ile Any Val
Smoking No
No
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