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Genetics for Epidemiologists Lecture 2: Measurement of Genetic Exposures National Human Genome Research Institute National Institutes of Health U.S. Department.

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Presentation on theme: "Genetics for Epidemiologists Lecture 2: Measurement of Genetic Exposures National Human Genome Research Institute National Institutes of Health U.S. Department."— Presentation transcript:

1 Genetics for Epidemiologists Lecture 2: Measurement of Genetic Exposures National Human Genome Research Institute National Institutes of Health U.S. Department of Health and Human Services National Institutes of Health National Human Genome Research Institute Teri A. Manolio, M.D., Ph.D. Director, Office of Population Genomics and Senior Advisor to the Director, NHGRI, for Population Genomics

2 Topics to be Covered Measuring genetic variation –Blood group markers –Restriction-fragment length polymorphisms –Variable number of tandem repeats (VNTRs, minisatellites and microsatellites) –Single nucleotide polymorphisms (SNPs) Linkage disequilibrium (LD) Familial resemblance and family history

3 Larson, G. The Complete Far Side

4 Measuring Genetic Variation: Blood Group and Enzymatic Markers Am J Med Genet 1984; 19: RBC COMT activity measured in 5 large families with hypertension (total 518 individuals) Associations tested with 25 genetic markers: ABO, Rh, K, MNS, P, Fy, Jk, PGD, ADA, ACP1, PGM1, HBB, GPT, C3, HPA, TF, GC, OR, GM, KM, BF, ESD, GLO1, Le Lod score of 1.27 and estimated recombination fraction of 0.1 found for phosphogluconate dehydrogenase (PGD)

5 Restriction Fragment Length Polymorphisms (RFLPs) Am J Hum Genet 1980; 32: Define polymorphic marker loci that can be detected as differences in length of DNA fragments after digestion with DNA sequence- specific endonucleases Establish linkage relationships using pedigree analysis

6 Restriction Fragment Length Polymorphisms (RFLPs) Am J Hum Genet 1980; 32: Since the RFLPs are being used simply as genetic markers, any trait… segregating in a pedigree can be mapped. Such a procedure would not require any knowledge of the biochemical nature of the trait or of the nature of the alterations in the DNA responsible for the trait.

7 RFLPs Used to Map Neurofibromatosis Science 1987; 236: Linkage analysis of 15 Utah kindreds showed that a gene responsible for von Recklinghausen neurofibromatosis (NF) is located near the centromere on chromosome 17

8 RFLPs Used to Map Neurofibromatosis Science 1987; 236: Cosegration of NF with the A2 (1.9 kb) allele and not A1 (2.4kb) in each of four affected offspring.

9 Variable Numbers of Tandem Repeats (VNTRs): Minisatellites Repetition in tandem of a short (6- to 100-bp) motif spanning 0.5 kb to several kb –Opened the way to DNA fingerprinting for individual identification –Provided the first highly polymorphic, multiallelic markers for linkage studies –Associated with many interesting features of human genome biology and evolution Well-known minisatellite is 5.5kb, kringle IV repeat in apolipoprotein(a) and plasminogen Vernaud G and Denoued F, Genome Res 2000; 10:

10 Kringle-IV Encoding Sequences of Human apo(a) cDNA ApoA1 Alleles Lackner et al, Hum Mol Genet 1993; 2:

11 Correlations of ApoA Molecular Weight with Lp(a) Levels and Number of Kringle-IV Repeats Gavish et al, J Clin Invest 1989; 84:

12 Simple Sequence Repeats (also “VNTRs”): Microsatellites Most are di-, tri-, and tetra-nucleotide repeats repeated times Most are highly polymorphic making them enormously useful for mapping and linkage Marshfield and similar maps placed ~400 microsatellites across genome, provided primers for analysis Could be highly automated: NHLBI and CIDR large-scale genotyping services Repetition in tandem of a short (2- to 6-bp) motif from 5-5,000 times

13 Multipoint LOD Scores for Long-term SBP and DBP on Chromosome 17 Levy et al, Hypertension 2000;36:

14 Larson, G. The Complete Far Side

15 GAAATAATTAATGTTTTCCTTCCTTCTCCTATTTTGTCCTTTACTTCAATTTATTTATTTATTATTAATATTATTATTTTTTGAG ACGGAGTTT C/A CTCTTGTTGCCAACCTGGAGTGCAGTGGCGTGATCTCAGCTCACTGCACACTCCGCTTTCCTGGTT TCAAGCGATTCTCCTGCCTCAGCCTCCTGAGTAGCTGGGACTACAGTCACACACCACCACGCCCGGCTAATTTTTGTA TTTTTAGTAGAGTTGGGGTTTCACCATGTTGGCCAGACTGGTCTCGAACTCCTGACCTTGTGATCCGCCAGCCTCTGC CTCCCAAAGAGCTGGGATTACAGGCGTGAGCCACCGCGCTCGGCCCTTTGCATCAATTTCTACAGCTTGTTTTCTTTG CCTGGACTTTACAAGTCTTACCTTGTTCTGC C/T TCAGATATTTGTGTGGTCTCATTCTGGTGTGCCAGTAGCTAAAAAT CCATGATTTGCTCTCATCCCACTCCTGTTGTTCATCTCCTCTTATCTGGGGTCAC A/C TATCTCTTCGTGATTGCATTCT GATCCCCAGTACTTAGCATGTGCGTAACAACTCTGCCTCTGCTTTCCCAGGCTGTTGATGGGGTGCTGTTCATGCCTCA GAAAAATGCATTGTAAGTTAAATTATTAAAGATTTTAAATATAGGAAAAAAGTAAGCAAACATAAGGAACAAAAAGGAA AGAACATGTATTCTAATCCATTATTTATTATACAATTAAGAAATTTGGAAACTTTAGATTACACTGCTTTTAGAGATGGAGA TGTAGTAAGTCTTTTACTCTTTACAAAATACATGTGTTAGCAATTTTGGGAAGAATAGTAACTCACCCGAACAGT G/T AA TGTGAATATGTCACTTACTAGAGGAAAGAAGGCACTTGAAAAACATCTCTAAACCGTATAAAAACAATTACATCATAATG ATGAAAACCCAAGGAATTTTTTTAGAAAACATTACCAGGGCTAATAACAAAGTAGAGCCACATGTCATTTATCTTCCCTT TGTGTCTGTGTGAGAATTCTAGAGTTATATTTGTACATAGCATGGAAAAATGAGAGGCTAGTTTATCAACTAGTTCATTTT TAAAAGTCTAACACATCCTAGGTATAGGTGAACTGTCCTCCTGCCAATGTATTGCACATTTGTGCCCAGATCCAGCATA GGGTATGTTTGCCATTTACAAACGTTTATGTCTTAAGAGAGGAAATATGAAGAGCAAAACAGTGCATGCTGGAGAGAG AAAGCTGATACAAATATAAA T/G AAACAATAATTGGAAAAATTGAGAAACTACTCATTTTCTAAATTACTCATGTATTTTC CTAGAATTTAAGTCTTTTAATTTTTGATAAATCCCAATGTGAGACAAGATAAGTATTAGTGATGGTATGAGTAATTAATATC TGTTATATAATATTCATTTTCATAGTGGAAGAAATAAAATAAAGGTTGTGATGATTGTTGATTATTTTTTCTAGAGGGGTTG TCAGGGAAAGAAATTGCTTTTT SNPs 1 / 300 bases ~ 10 million across genome Single Nucleotide Polymorphisms (SNPs)

16 Christensen and Murray, N Engl J Med 2007; 356: Mapping the Relationships Among SNPs

17 Chromosome 9p21 Region Associated with MI Samani N et al, N Engl J Med 2007; 357:

18 Boston Provi- dence New York Phila- delphia Balti- more Providence 59 New York Philadelphia Baltimore Washington Distances Among East Coast Cities

19 Boston Provi- dence New York Phila- delphia Balti- more Providence 59 New York Philadelphia Baltimore Washington Distances Among East Coast Cities < > 400

20 Boston Provi- dence New York Phila- delphia Balti- more Providence 59 New York Philadelphia Baltimore Washington Distances Among East Coast Cities < > 400

21 Distances Among East Coast Cities Boston Provi- dence New York Phila- delphia Balti- more Wash- ington

22 Distances Among East Coast Cities Boston Provi- dence New York Phila- delphia Balti- more Wash- ington

23 One Tag SNP May Serve as Proxy for Many CAGATCGCTGGATGAATCGCATCTGTAAGCAT CGGATTGCTGCATGGATCGCATCTGTAAGCAC CAGATCGCTGGATGAATCGCATCTGTAAGCAT CAGATCGCTGGATGAATCCCATCAGTACGCAT CGGATTGCTGCATGGATCCCATCAGTACGCAT CGGATTGCTGCATGGATCCCATCAGTACGCAC SNP2 ↓ SNP3 ↓ SNP4 ↓ SNP5 ↓ SNP6 ↓ SNP1 ↓ Block 1Block 2 SNP7 ↓ SNP8 ↓

24 One Tag SNP May Serve as Proxy for Many CAGATCGCTGGATGAATCGCATCTGTAAGCAT CGGATTGCTGCATGGATCGCATCTGTAAGCAC CAGATCGCTGGATGAATCGCATCTGTAAGCAT CAGATCGCTGGATGAATCCCATCAGTACGCAT CGGATTGCTGCATGGATCCCATCAGTACGCAT CGGATTGCTGCATGGATCCCATCAGTACGCAC % SNP2 ↓ SNP3 ↓ SNP4 ↓ SNP5 ↓ SNP6 ↓ SNP1 ↓ Block 1Block 2 SNP7 ↓ SNP8 ↓

25 One Tag SNP May Serve as Proxy for Many CAGATCGCTGGATGAATCGCATCTGTAAGCAT CGGATTGCTGCATGGATCGCATCTGTAAGCAC CAGATCGCTGGATGAATCGCATCTGTAAGCAT CAGATCGCTGGATGAATCCCATCAGTACGCAT CGGATTGCTGCATGGATCCCATCAGTACGCAT CGGATTGCTGCATGGATCCCATCAGTACGCAC % SNP3 ↓ SNP5 ↓ SNP6 ↓ Block 1Block 2 SNP7 ↓ SNP8 ↓

26 One Tag SNP May Serve as Proxy for Many CAGATCGCTGGATGAATCGCATCTGTAAGCAT CGGATTGCTGCATGGATCGCATCTGTAAGCAC CAGATCGCTGGATGAATCGCATCTGTAAGCAT CAGATCGCTGGATGAATCCCATCAGTACGCAT CGGATTGCTGCATGGATCCCATCAGTACGCAT CGGATTGCTGCATGGATCCCATCAGTACGCAC % SNP3 ↓ SNP6 ↓ Block 1Block 2 SNP8 ↓

27 One Tag SNP May Serve as Proxy for Many GTT 35% CTC 30% GTT 10% GAT 8% CAT 7% CAC 6% other haplotypes 4% Block 1Block 2FrequencySingleton

28 Pair-Wise Linkage Disequilibrium (LD) Measures For a discussion and comparison of these LD measures, see Devlin B, Risch N, Genomics 1995; 29: NameSymbolDefinition "Lewontin's D"Dp AB p ab – p Ab p aB "D prime"D'D / max (D) Correlation ("r-squared") r2r2 D 2 / p A p a p B p b Courtesy K. Jacobs, NCI

29 Two Measures of LD: D' and r 2 D' varies from 0 (complete equilibrium) to 1 (complete disequilibrium) When D' = 0, typing one SNP provides no information on the other SNP D' does not adequately account for allele frequencies; r 2 is correlation between SNPs, is preferred measure When r 2 = 1, two SNPs are in perfect LD; allele frequencies are identical for both SNPs, and typing one SNP provides complete information on the other

30 What can LD do for me? Knowledge of patterns of LD can be quite useful in the design and analysis of genetic data Design: –Estimation of theoretical power to detect associations –Evaluation of degree of completeness of sampling of genetic variants –Choice of most informative genetic variants to genotype Sample size increases by ~1/r 2 to achieve same power to detect association with SNP2 as SNP1 Courtesy K. Jacobs, NCI

31 Association Signal for Coronary Artery Disease on Chromosome 9 Samani N et al, N Engl J Med 2007; 357:

32 Region of Chromosome 1 Showing Strong Association with Inflammatory Bowel Disease Duerr R et al. Science 2006; 314:

33 Grant et al, Nat Genet 2006; 38: LD Patterns in TCF7L2 Association Region

34 International HapMap Consortium, Nature 2005; 437: LD in Three HapMap Populations

35 A HapMap for More Efficient Association Studies: Goals Use just the density of SNPs needed to find associations between SNPs and diseases Do not miss chromosomal regions with disease association Produce a tool to assist in finding genes affecting health and disease Ancestral populations differ in their degree of LD; recent African ancestry populations are older and have shorter stretches of LD, need more SNPs for complete genome coverage

36 SNPs as Gateway to Genome-Wide Association (GWA) Studies SNPs much more numerous than other markers and easier to assay Genome-wide studies attempt to capture majority of genomic variation (10M SNPs!) Variation inherited in groups, or blocks, so not all 10 million points have to be tested Blocks are shorter (so need to test more points) the less closely people are related SNP technology allows studies in unrelated persons, assuming 5kb – 10kb lengths in common (300,000 – 1,000,000 markers)

37 International HapMap Consortium, Nature 2005; 437:

38 International HapMap Consortium, Nature 2007; 449:

39 Progress in Genotyping Technology Nb of SNPs Cost per genotype (Cents, USD) ABI TaqMan ABI SNPlex Illumina Golden Gate Illumina Infinium/Sentrix Affymetrix 100K/500K Perlegen Affymetrix MegAllele Affymetrix 10K Courtesy S. Chanock, NCI

40 Affymetrix 500K Illumina 317K Illumina 550K Illumina 650Y Continued Progress in Genotyping Technology Courtesy S. Gabriel, Broad/MIT July 2005Oct 2006 Cost per person (USD)

41 Year Number of SNPs Cost/SNPCost/Study Cost of a Genome-Wide Association Study in 2,000 People

42 Year Number of SNPs Cost/SNPCost/Study 2001 Cost of a Genome-Wide Association Study in 2,000 People

43 Year Number of SNPs Cost/SNPCost/Study ,000,000 Cost of a Genome-Wide Association Study in 2,000 People

44 Year Number of SNPs Cost/SNPCost/Study ,000,000$1.00 Cost of a Genome-Wide Association Study in 2,000 People

45 Year Number of SNPs Cost/SNPCost/Study ,000,000$1.00$20 billion Cost of a Genome-Wide Association Study in 2,000 People

46 Year Number of SNPs Cost/SNPCost/Study ,000,000$1.00$20 billion 2008 Cost of a Genome-Wide Association Study in 2,000 People

47 Year Number of SNPs Cost/SNPCost/Study ,000,000$1.00$20 billion 20081,000,000 Cost of a Genome-Wide Association Study in 2,000 People

48 Year Number of SNPs Cost/SNPCost/Study ,000,000$1.00$20 billion 20081,000, ¢ Cost of a Genome-Wide Association Study in 2,000 People

49 Year Number of SNPs Cost/SNPCost/Study ,000,000$1.00$20 billion 20081,000, ¢$1 million Cost of a Genome-Wide Association Study in 2,000 People

50 Coverage (% SNPs tagged at r 2 > 0.8) of Commercial Genotyping Platforms Manolio et al, J Clin Invest 2008; 118: HapMap population sample Platform YRICEUCHB+JPT Affymetrix GeneChip 500K Affymetrix SNP Array Illumina HumanHap Illumina HumanHap Illumina HumanHap650Y Perlegen 600K479284

51 Following the Polymorphism Literature Sometimes named for: –amino acid change (AGT M235T) –nucleotide sequence (AGTR1 A1166C) –promoter (AGT -6 G/A) –restriction enzyme site (XbaI, PvuII, HindIII) –gene product (APOE*e2) –legacy system (DRB1*0104) –reference SNP (rs709932) or submitted SNP (ss ) Good sources for information: OMIM, HUGO, dbSNP, UCSC Genome Browser Courtesy S. Chanock, NCI

52 Other Genomic Technologies Sequencing: measure variation at every point in gene or candidate region in dozens to hundreds of people to find functional variants Gene expression: measure changes in mRNA (transcribed) in cases and controls or in response to stimulation Epigenetics: measure DNA methylation or histone deacetylation that turns genes on and off

53 Sidney Harris,

54 Summary Points: Genotyping Methods Unbelievably rapid progress from small number of blood group markers to >10M SNPs, CNVs, structural variants, sequence variants Technology will continue to change and will be challenge to keep up with; difficult to know when ready to apply to population studies SNPs are currently the dominant technology (more to come in Lecture 4) Quality control is a major issue

55 Familial Resemblance?

56 Evidence for Genetic Influence on Disease or Trait from Family Data Familial resemblance: trait more similar among related than unrelated persons Familial clustering: risk of disease in relative of case > risk in relative of non-case or of general population; (sibling relative risk, Risch's λ S ) Distributions of continuous trait: mixtures of distributions or commingling analysis

57 Sibling Relative Risk of Living to Age 90 Centenarians vs. Those Dying at Age 73 Perls TT et al, Lancet 1998; 351:1560.

58 Large Representative Pedigree Showing 69 Patients with Atrial Fibrillation Arnar et al, Europ Heart J 2006; 27:

59 Strength of Extensive Genealogies Common diseases do not show Mendelian inheritance patterns Affected siblings infrequent in common diseases, but many patients may have more distant relatives with same disease Degree of Relatives Risk Ratio [95% CI]P-Value [1.67,1.88]< [1.27,1.44]< [1.14,1.23]< [1.06,1.13]< [1.02,1.07]< Arnar et al, Europ Heart J 2006; 27:

60 Familial Correlations Phenotypic resemblance among relatives estimated by regression of one relative’s value (offspring), on that of another (parent): Y o = μ + β [(Y m + Y f )/2] + ε Twice parent-offspring correlation is estimate of heritability If trait under genetic control, expect trait correlations among closer relatives to be greater than those among more distant relatives

61 Familial Correlations of Sex-Specific LV Mass, Multiply-Adjusted Relative PairPairs (n)CorrelationExpected Spouse Parent-offspring Sibling 1, Avuncular after Post W et al, Hypertension 1997; 30:

62 Assessing Familial and Genetic Nature of a Phenotypic Trait: Heritability Often designated as H, h 2, or σ 2 G /σ 2 P Proportion of total inter-individual variation in the trait (σ 2 P ) or phenotypic variation, attributable to genetic variation (σ 2 G ) Population- and environment-specific parameter Its value, high or low, does not indicate role of genes in any specific individual Does allow one to predict expected degree of familial aggregation of a trait Traits with high heritability should prove fruitful in identifying trait-related genes

63 Genetic Basis of Familial Clustering of Plasma ACE Activity RelativeNMean (u/L) Major Gene Effect Mean (u/L)% Variance Fathers Mothers Siblings Cambien F, et. al., Am J Hum Genet 1988; 43:

64 Estimated Heritability Explained by GWA Findings to Date Estimated GWA σ 2 G Estimated Total σ 2 G Reference Height3%90% Weedon Nat Genet 2008 T2DMλ s = 1.07λ s = 3.5 Zeggini/Scott Science 2007 CRP? 10.5%30-50% Reiner/Ridker Nat Genet 2008 ~1.3 ORλ s = 4-11 Liu PLoS Genet 2008 NHGRI GWA Catalog,

65 Hardy-Weinberg Equilibrium Occurrence of two alleles of a SNP in the same individual are two independent events Ideal conditions: –random mating - no selection (equal survival) –no migration - no mutation –no inbreeding - large population sizes –gene frequencies equal in males and females)… If alleles A and a of SNP rs1234 have frequencies p and 1-p, expected frequencies of the three genotypes are: After G. Thomas, NCI Freq AA = p 2 Freq Aa = 2p(1-p)Freq aa = (1-p) 2

66 Summary Points: Familial Clustering Indicator of possible genetic influence May over-estimate genetic component due to poor assessment and adjustment for shared environment Methods include twin studies, parent-offspring correlation, “relative” relative risk, % variance explained Current genes for complex disease explain only tiny fraction of total heritability

67 Larson, G. The Complete Far Side

68

69 Basic Definitions: Loci, Genes, Alleles Locus: Place on a chromosome where a specific gene or set of markers resides Quantitative trait locus (QTL): a genetic factor believed to influence a quantitative trait such as blood pressure, lipoprotein levels, etc. Gene: Contiguous piece of DNA that can contain information to make or modify ‘expression’ of specific protein(s) Allele: A variant form of a DNA sequence at a particular locus on a chromosome Candidate gene: Gene believed to influence expression of complex phenotypes due to known biologic properties of their products After S. Chanock, NCI

70 Basic Definitions: Parts of a Gene Exon: a DNA sequence that usually specifies the sequence of amino acids in translation Intron: an intervening DNA sequence removed from mRNA after transcription and thus does not encode protein in translation Splice site: Junction of intron and exon Promoter: region of DNA to which an RNA polymerase binds and initiates transcription - the promoter regulates gene expression by controlling the amount of mRNA transcribed Polymorphism: Variation in the sequence of DNA among individuals After S. Chanock, NCI

71 SNPs and Function: We know so little… Majority are “silent” –No known functional change Some alter gene expression/regulation –Promoter/enhancer/silencer –mRNA stability –Small RNAs Some alter function of gene product –Change sequence of protein Courtesy S. Chanock, NCI

72 SNPs within Genes Coding SNPs (cSNPs) Synonymous: no change in amino acid previously termed “silent” but….. Can alter mRNA stability DRD2 (Duan et al 2002) Can alter speed of translation and protein folding MDR1 (Gottesman et al 2007) Nonsynonymous: changes amino acid (codon) conservative and radical Nonsense: insertion of stop codon Frameshift (insertion/deletion): Disrupts codon sequence, rare but disruptive After S. Chanock, NCI

73 SNPs Outside Genes Majority distributed throughout genome are “silent” (excellent as markers) Alter transcription –Promoter, enhancer, silencer Regulate expression –Locus control region, mRNA stability Most are assumed to be ‘silent hitchhikers’ –No function by predictive models or analysis Courtesy S. Chanock, NCI

74 Sample Collection and Processing Obtaining samples for DNA preparation –whole blood, buffy coat –sputum –buccal cells –serum, urine –pathology specimens –placenta, excreta, other Purifying and quantifying DNA Transformed lymphocytes Whole genome amplification (WGA) ‘Barcode’ individual DNAs (QC) After S. Chanock, NCI


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