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5/20/2013 1 + Familial Breast Cancer SEARCHING THE GENES SEARCHING THE GENES Samuel J. Haryono +
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Page 1: Samuel J. Haryono - Unandpasca.fk.unand.ac.id/wp...dr.-Samuel-Haryono-GWAS2.pdf · 5/20/2013 2 + Issues in HSBOC Spectrum of mutation testing in familial breast cancer Variant of

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Familial Breast CancerSEARCHING THE GENESSEARCHING THE GENES

Samuel J. Haryono

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+Issues in HSBOC Spectrum of mutation testing in familial breast cancer

Variant of BRCA vs mutation of BRCA

Clinical guideline and management for carrier

BRCA mutation with TNBC

Recurrent mutation in Indonesia

Penetrance , sporadic and modifier genes

Sanger HRM NGS Sanger, HRM, NGS

Options of preventive, risk assessment, genetic counselling

SAMANDA ( Syndrome-Adopted Mutation-Assessment-Need-Data-Analysis) risk calculation for Indonesian specific FBC

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+• 1866 Paul Brocapedigree in BCvarian mutation of BRCA1RRM =risk reduction mastectomy

in Asia is less:brca2, ER+, lower penetrans less penetrans, less evidence,

is it appropriate action / option?

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GWAS(Genome-Wide Association Study)

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Introduction

+Development in genomic era

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Not100% Identical!!

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+Development in genomic era

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+SNPSingle Nucleotide Polymorphism

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10 million SNPs

+Development in genomic era

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+LingkageSNPs

+International Hapmap Consortium

The International HapMapConsortium.2005. A haplotype map of the human genome. Nature.437:1299-1320

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+Development in genomic era

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+DNA Microarray

Collection of microscopic pDNA spots attached to a solid surface

Genome-Wide 5.0 Chip (Affymetrix)

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+Development in genomic era

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GWAS (Genome-Wide Association Study)

+GWAS

- Whole Genome Association Studies (WGAS)( )

- Correlation between variant vs traits

- Variant (e.g SNP) genotype

- Trait (major disease in this case : breast cancer) phenotype

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+Published Genome-Wide Associations through

07/2012Published GWA at p≤5X10-8 for 18 trait

categories

NHGRI GWA Catalogwww.genome.gov/GWAStudieswww.ebi.ac.uk/fgpt/gwas/

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+Association Study

Cohort

Case Control

Cross-Sectional

Case-control Cohort Cross-Sectional

Exposure Past Present Present

Disease Present Future Present

+Case-Control

Present

(Breast Cancer +) (Breast Cancer -)

Genotype Analysis

past

SNP (marker)SNP (marker)

GENE

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Methods

+Multistage design

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+Sample Preparation

50 Cases

50 Control

DNA Isolation (Roche)

DNA quantity check ([DNA]= 100-200 ng/μl

DNA quantity check (A260/A280 = 1.7-1.8)

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+Microarray

Affymetrix©y

Genome-Wide SNP array 5.0

+Sample Preparation(Whole Genome Sampling Assay)

Kennedy GC et al. 2003. Large-scale genotyping of complex DNA. Nat Biotechnol. 21:1233-7.

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+Signal Measurement

Kennedy GC et al. 2003. Large-scale genotyping of complex DNA. Nat Biotechnol. 21:1233-7.

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Data Analysis

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+

Preliminary Analysis

+Flowchart

Signal from Chip Genotype

genotyping

Sample (100)

SNP(400k)

SNP & Sample Filtering( )

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+Flowchart

GenotypeSignal from

Chipgenotyping

Sample (less than 100)

SNP(less than

400k)

HaplotypeSNPs Tag

+Genotyping

Signal from Chip Genotype

genotyping

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+Genotyping(BRLMM-P)

Software :Software :Genotyping Console 4.0 (Affymetrix)

Affymetrix.2007. BRLMM-P: a genotype calling method for the SNP 5.0 array. Technical Report.

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Genome-Wide Associated Study Associated Study (GWAS) on hereditary susceptibility breast cancer in Indonesia-Samuel J Haryono-

+ SNP summary (1)

Page 29: Samuel J. Haryono - Unandpasca.fk.unand.ac.id/wp...dr.-Samuel-Haryono-GWAS2.pdf · 5/20/2013 2 + Issues in HSBOC Spectrum of mutation testing in familial breast cancer Variant of

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+ SNP summary (2)

+ List of SNPs per-sample and its genotype

Probe set ID Allele genotyping

confidence Allelegenotype

contrast strength Sequence genotyping

dbSNP rs ID Chromosomal position

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+

Sample & SNP Filtering

+Sample (100)

SNP & Sample Filtering

SNP

(400k)

Sample (less than 100)

SNP(less than

400k)

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+Sample Filtering

1. SNP Call Rate

Fraction of called SNPs per sample over the total number of SNPs in the datasheet

Missing genotype data

Software :Genotyping Console 4.0 (Affymetrix)

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Sample (100)

SNP(400k)

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+Sample Filtering

Include SNP

Exclude SNP

100%

+SNP Filtering

1. per-SNP Call Rate

S S ( f )Remove SNP per-SNP call rate (sometimes referred to as completeness) less than some threshold. Commonly-used value for the per-SNP call rate threshold range from 90-95%.

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+

Sample (100)

SNP(400k)

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2. HWE (Hardy-Weinberg Equilibrium) p-value

SNP Filtering

Remove SNPs significantly out of Hardy Weinberg Equilibrium in cases and/or control. A p-value threshold in the range of 10-7 is commonly used.

Allele frequency vs Genotype frequency

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+SNP Filtering

3. MAF (Minor Allele Frequency)

Frequency at which the less common allele occurs in a given population.

Conside removing SNPs with minor allele frequency (MAF) less than certain threshold (for example 1%)

+ Chromosom SNPs

before afterChromosome 1 35402 28355

Chromosome 2 36786 29725

Chromosome 3 30222 24737

Chromosome 4 28628 22909

Chromosome 5 28572 23634

Chromosome 6 27954 23387Chromosome 6 27954 23387

Chromosome 7 22816 18931

Chromosome 8 24498 19891

Chromosome 9 20139 16663

Chromosome 10 25170 20540

Chromosome 11 23092 18861

Chromosome 12 21960 18079

Chromosome 13 17054 13720

Chromosome 14 13950 11415

Chromosome 15 12703 10387

Chromosome 16 13464 10724

Exlude SNPs

(18.68%)

81.32%

Chromosome 16 13464 10724

Chromosome 17 9872 7940

Chromosome 18 13236 10639

Chromosome 19 5475 4635

Chromosome 20 11043 8905

Chromosome 21 6268 5167

Chromosome 22 5334 4303

Chromosome X 9778 6974

total 443416 360521

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+Haplotype Analysis

Haplotype block p yp Pairwise tagging

Linkage Disequilibrium measurement r2

SNPs tags

+Linkage Disequilibrium

r2 provides information on the corelation of two loci

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+Haplotype Block

+

Software : Haploview 4.2

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+

Software : Haploview 4.2

+

Association Study

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+Population stratification

Marchini J, et al. 2004. The effects of human population structure on large genetic association studies. Nat Genet. 36:512-7

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+Manhattan Plot

Wang K, et al. 2009. Common genetic variants on 5p14.1

i t ith ti associate with autism spectrum disorders. Nature. 459:528-533

+

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+Acknowledgement

Samuel HaryonoAlthaf SetyawanIGB DatasenaWahyu Budi SantosaAdrian SalimRaymond MulyarahardjaMulyarahardjaDismas A. ChaspuriUti Nilam SariKartika Sari

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Thank You


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