Genetics of complex human disease traits.Daniel T. O’Connor, M.D.Department of Medicine.Nopm-252. First year curriculum in human genetics.Wed Apr 1, 2009.CMME-2047.

PURPOSE.In the next two hours, we plan to cover the role of heredity and genes in

very common, non-Mendelian traits that are frequently seen by primary carephysicians. We will illustrate how we establish the role of heredity on any trait,and then methods to position the particular genes that influence such a trait.

WHAT IS A “COMPLEX TRAIT”?

Trait = phenotype.

Disease causation/etiology/origin:The old conundrum of: “Nature (heredity) versus nurture (environment)”.How to solve this riddle: Family/pedigree or twin studies (see below).

Frequency.Most (>95%) of the disease encountered in internal medicine, family

medicine, pediatrics, neurology, or psychiatry is complex, and its origin is not wellunderstood. Not clearly completely hereditary (Mendelian) or environmental.Read: Hypertension, coronary artery disease, arrhythmia, stroke, aneurysm,asthma, COPD, diabetes, obesity, schizophrenia, bipolar disorder . . .

Multifactorial: Genes, environment, gene-by-environment interactions.

Non-Mendelian.Mendelian: Gene ‡ Trait (1:1; high penetrance ~100%).Non-Mendelian: Only partial penetrance. Some people with the gene do not

get the trait. Some people who do not have the gene still get the trait.

Bimodality: Hallmark of a major gene effect on a quantitative trait.

Bimodality: Hallmark of a major gene effect on a quantitative trait.

Polygenic Traits

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Complex Trait Model

Disease Phenotype

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Marker Gene1

Individualenvironment

Polygenicbackground

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Linkage

Linkagedisequilibrium

Mode ofinheritance Linkage

Association

APPROACHES TO COMPLEX TRAITS.

(Genetic) epidemiology.Demographics (age, sex, ethnicity, geography, fam hx).“Risk” (susceptibility) factors (see above).

Relative risk (RR): Given a risk factor, what is the increase in traitprevalence?

Estimator of RR: Odds ratio (OR). Given a risk factor, OR = (have trait/donot have trait).

OR +/- confidence interval (+/-95% CI) versus reference (no risk) =1.No risk: RR or OR = 1.OR +/- CI >>1 ‡ Risk (susceptibility) factor.OR +/- CI <<1 ‡ Protective factor.Test by χ2 (2x2 contingen cytabl ).e

CHGA genetic variation: Risk factor for hypertensive ESRD in blacks

J Am Soc Nephrol. 2008 Mar;19(3):600-14.Chromogranin A polymorphisms are associated with hypertensive renal disease.Salem RM, Cadman PE, Chen Y, Rao F, Wen G, Hamilton BA, Rana BK, Smith DW, Stridsberg M, Ward HJ, Mahata M, Mahata SK, Bowden DW, Hicks PJ, Freedman BI, Schork NJ, O'Connor DT.

Estimator of RR: Odds ratio (OR).Given a risk factor, OR = (have trait/do not have trait).

“Intermediate” (risk) traits (phenotypes).Intermediate in time and mechanism.Bridging genotype and ultimate, late disease trait.Ideally: Greater h2, earlier penetrance.If biochemical assays: “Biomarkers”.

“Intermediate” in

time and causality

Mec

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Cardiorenal disease trait(later life)

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Gene(fixed at conception)

Twins: window into heritability (h2) of any phenotype

Monozygotic (MZ, identical) twins: Billy and Benny . . .VP = VG + VE

h2 = VG/VP = 2(RMZ - RDZ)Source: Guinness Book of World Records.

Total mole count for MZ and DZ twins

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MZ twins - 153 pairs, r = 0.94 DZ twins - 199 pairs, r = 0.60

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Cardiac output

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Baroreflex up

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Heritability (h2) of traits in human twin pairs

Heritability (h

2), mean +/- SEM

Trait

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Physiological Biochemical

Family studies (twin pairs, pedigrees). Fam hx as a risk factor. In 1st degree relatives: Parents, siblings. Heritability (h2): Fraction of trait variance accounted for by genetic variance. VP = VG + VE

h2 = VG/VP

Estimate h2 from twin pair (or pedigree) studies:Type of twin pair Allele sharing across the genome.MZ = monozygotic = identical. 100%DZ = dizygotic = fraternal ~50% (on average), like any sib pair

Quick-and-dirty algorithm:h2 = VG/VP = 2(RMZ – RDZ)

West J Med. 1984 Dec;141(6):799-806. Understanding genetic and environmental risk factors in susceptible persons. Williams RR.

Family history as a risk factor for complex traits.

Familyhistory

(Genetic) “linkage”: Co-segregation of marker and trait.Versus independent segregation: Different chromosome, or far apart on same

chromosome.Thus, marker and trait loci are within ~50 cM of “genetic” distance.

cM: Just count the meiotic recombinants versus non-recombinantscM = (Recombinant meioses / Total meioses)*(100)

Lower cM means closer (marker and trait loci)Calibration. cM (genetic/meiotic distance) vs Mb (physical distance):

1 cM = ~1 Mb (actually ~0.5-2.0).Markers to span the genome for linkage:

3000 cM/50 cM = 60 fully informative (heterozygosity) markers in theoryIn practice:

~400-800 highly informative markers (multiallelic microsatellites) ~2000-10,000 less informative markers (biallelic SNPs)

Linkage = Meiotic co-segregation

A2A4

A3A4

A1A3

A1A2

A2A3

A1A2 A1A4 A3A4 A3A2

Marker allele A1

cosegregates withdominant disease

Linkage Markers…

Thomas Hunt Morgan – discoverer of linkage

Idiosyncratic features of genetic linkage (= meiotic co-segregation).

Units.Metric = meiotic recombination (~50 meioses/generation).Units of genetic distance = recombination during meiosis (cM).cM = (recombinant meioses/total meioses)*100 E.g.: [8/(8+86)]*100 =(8/94)*100

= 8.5 cM1 cM ~ 1 Mb Range ~0.5-2.0 Varies by species, sex, chromosomal region (meiotic “hot spots”)

Significance.“LOD” scores.LOD = Log10 of the odds ratio for linkageOdds ratio: Co-segregation (marker and trait)

NotSignificant: LOD >3.0 (i.e., odds ratio > 1000/1) Why 3.0? ~50 “linkage groups” (meiotic breaks/generation), target =0.05. 1/50*1/20=1/1000.

Genetic linkage: Meiotic recombination distance in cM

cM = (recombinant meioses/total meioses)*100[8/(8+86)]*100 =(8/94)*100

= 8.5 cM

Mahata SK, Kozak CA, Szpirer J, Szpirer C, Modi WS, Gerdes HH, Huttner WB, O'Connor DT.Dispersion of chromogranin/secretogranin secretory protein family loci in mammalian genomes. Genomics. 1996 Apr 1;33(1):135-9.

1 cM ~ 1 MbRange ~0.5-2.0Varies by species, sex, chromosomal region (meiotic “hot spots”)

Mouse SBP crosses: “Genome scan” linkage.

Wright FA, O'Connor DT, Roberts E, Kutey G, Berry CC, Yoneda LU, Timberlake D, Schlager G. Genome scan for blood pressure loci in mice. Hypertension. 1999 Oct;34(4 Pt 1):625-30.

LOD score: Log10 of the OR for linkage (marker, trait).Log10 (non-recombinants / total meioses).“Significant” LOD > 3 (i.e., OR > 1000).Why? ~50 linkage groups (meiotic breaks/generation), target =0.05 .

1/50*1/20=1/10 00.Quantitativ e trai , t no -n parametric:

Regressi . on Pl :otY = (Trai t difference)2 withi n eac h si b pai r of DZtwi n pair.X = Allele s share d IB (D identica l bydescen ), 0t ‡ 1‡ 2.

Linkage is about loci, not particular alleles!Terminology: “QTL” (Quantitative Trait Locus). LOD >3 peak for that trait.Problems:

Need families based on probands (but relatives may not be available).Ideal for Mendelian disorders, but limited success for complex traits.Meiosis yields very large chromosomal sharing blocks by first-degree

relatives, but this can give rise to low spatial resolution of involved genes (verybroad LOD peaks).

J Clin Invest. 1996 May 1;97(9):2111-8. Quantitative trait locus mapping of human blood pressure to a genetic region at or near the lipoprotein lipase gene locus on chromosome 8p22. Wu DA, Bu X, Warden CH, Shen DD, Jeng CY, Sheu WH, Fuh MM, Katsuya T, Dzau VJ, Reaven GM, Lusis AJ, Rotter JI, Chen YD.

Genetic linkage: What the data (marker, trait) look like.

J Clin Invest. 1996 May 1;97(9):2111-8. Quantitative trait locus mapping of human blood pressure to a genetic region at or near the lipoprotein lipase gene locus on chromosome 8p22. Wu DA, Bu X, Warden CH, Shen DD, Jeng CY, Sheu WH, Fuh MM, Katsuya T, Dzau VJ, Reaven GM, Lusis AJ, Rotter JI, Chen YD.

Genetic linkage: What the data (marker, trait) look like.

(Allelic) association: Marker ‡ Trait.• “Candidate” gen : e Specifi c prio r hypothes is fo r on e gen (e e. .,g

hemoglobi n ‡ thalassemia).Firs , t systemat ic polymorphi smdiscove ry(b y resequencing).Define haplotyp /e L D (linka ge disequilibrium) blocks.

Blo ~cks 3-50 k bpi n unrelate d individuals. Origi n is ancestr almeioticrecombinati . on Var y in length b y ethnicit .y

Assa y SN (Ps orSNP haplotypes) i n phenotyp ed individuals.Haplotypes: Infe r fr omindividua l diploi d genotyp es b y probability.Dichotomou s trai : t Disea se case s versu s controls. Analyz e byχ2 on

3x2 continge ncytabl :e 3 (diploi d genoty peclasse ; s . ., e g A/A, A/ , /G G G) x2(cas /e control) contingen cy tables.

Continuou s trai : t Analyz e by ANOVA, wi th genoty pe (diploi d genotypeclasses; e. ., g A/A, A/ , /G G G) a s independe ntvariabl .e

Associatio n derive s effect s ofparticula r alleles, no t jus t loci.Advanta : ge Unrel atedindividua ls (d o not needfamilies).Problems:

Populatio n stratificati (on artifactua l associatio n a s a resul t o f allelefrequency difference s acro ss populations).

The catecholamine biosynthetic pathway.

T Flatmark. Regulation of catecholamine biosynthesis. Acta Physiol Scand 168:1-17, 2000.

Figure 8: TH haplotypes in vivo

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Tyrosine hydroxylase promoter haplotype 2: Pleiotropy.Coordinate effects on both catecholamine excretion

and stress blood pressure response in twins

Change in DBP during cold stress, mmHg

Norpinephrine excretion, ng/gm

Haplotype 2n=2 copies(n=32 individuals)

Haplotype 2n=1 copy(n=164 individuals)

Haplotype 2n=0 copies(n=131 individuals)

Norepinephrine h2=49.6+/-6.7%, p=0.0001*

Haplotype 2 on norepinephrine: p=0.0125*, 4.06% variation explained

Δ DBP h2=32+/-8%, =0.0003*p

2 Haplotype onΔ : DBP =0.0004*p , 3.73% variation explained

: Pleiotropy bivariate likelihood ratio test

χ2=14.2, =0.0002*p

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Tyrosine hydroxylase regulatory polymorphism:Interaction of genotype and sex to affect DBP

Male DBPFemale DBP

DBP, mmHg(mean +/- SEM)

Tyrosine hydroxylase (TH) promoter C-824T diploid genotype

78.3+/-1.5

(n=234)

2-way ANOVA:(Covariates: age, BMI)Overall F=12.4, p<0.001*Genotype F=1.30, p=0.273Sex F=31.6, p<0.001*Genotype * Sex F=3.14, p=0.044*C-824T explains 3.4% of DBP varianceAlleles: C=61%, T=39%

HWE: χ2=0.54, =0.46p

74.9+/-1.5( =233)n

82.8+/-1.3( =285)n

74.9+/-1.2( =329)n

85.3+/-2.6( =75)n

73.2+/-2.1( =110)n

: Males alone =3.12, Genotype F =0.045*p

:Females alone =0.015, =0.985Genotype F p

Figure 7: Intermediate phenotypes

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Gene

Biochemical trait

Physiological trait

Disease trait

Hypertension: “Intermediate” phenotypes and candidate genes.

Tyrosine hydroxylase C-824T

Catecholamines

Baroreceptor function Stress blood pressure

Hypertension

• GWAS (Genome Wide Association Study). Hypothesis: Commondisease/Common Variant.

Markers to span the genome for association:~3.3 Gbp (1 Gbp = 109 bp) genome / 500K SNPs = ~6000 bp (~6 kbp).The only variants spaced this closely (i.e., the common) are SNPs.Spacing based on HapMap <www.hapmap.org> and LD (linkage

disequilibrium) blocks.HapMap: 270 people world-wide typed at ~4 million SNPs across the

genome.Within an LD block, SNPs are highly correlated (r2 ~0.6-1.0).Try to “tag” each LD block across the genome.

Advantage: Unrelated individuals (do not need families).Problems:

Population stratification (artifactual association as a result of allelefrequency differences across populations).

Statistical challenges to GWAS: Many LD blocks tested, modifiedtarget p=5x10-7.

Solution: Replication in an independent sample, for joint (multiplicative,∩) probability.

pter qter5’ 3’

Chromosome

Paternal

Maternal

T C A G

C T G A

Haplotype: Ordered array of alleles along a single chromosome. Biallelic SNPs (single nucleotide polymorphisms). Typically “transitions”:

Purine Purine (G A)Pyrimidine Pyrimidine (C T)

5’ 3’

Paternal

Maternal

T A C G T A C G

C G T C C G T A

“Linkage disequilibrium” (LD): Local, marker-on-marker locus Equilibrium = randomness (no correlation, r2=0) Disequilibrium = non-random (correlated, r2>0) Marker-on-trait locus: Mapping tool

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r2

BiallelicSNPs

In population genetics, linkage disequilibrium is the non-random association of alleles at two or more loci. Linkage disequilibrium describes a situation in which some combinations of alleles or genetic markers occur more or less frequently in a population than would be expected from a random formation of haplotypes from alleles based on their frequencies. Non-random associations between polymorphisms at different loci are measured by the degree of linkage disequilibrium (LD). The level of linkage disequilibrium is influenced by a number of factors including the rate of meiotic recombination (crossovers) and the rate of mutation.

Linkage disequilibrium (LD). Marker trait Marker marker

HapMap: View variation patterns

Triangle plot shows LD values using r2 or

D’/LOD scores in one or more HapMap

population

The International HapMap Project(Identification of SNPs that ‘tag’ haplotypes within blocks)

Daly, M.J., Rioux, J.D., Schaffner, S.F., Hudson, T.J. and Lander, E.S. (2001). High-resolution haplotype structure in the human genome. Nature Genet. 29: 229-232.

Linkage disequilibrium (LD) “blocks” on human chromosome 14q32 100 kbp displayed, from <www.HapMap.org>

3 short-range (~30 kbp) LD blocks

No long-range (~100 kbp) LD

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Region of the genome around around SNP rs9941339 in CDH13 (T-cadherin = novel adiponectin receptor) on 16q24 associated with intra MZ pair differences in HDL cholesterol (GWAS in n=1662 MZ pairs). Black points represent SNPs genotyped in the study and gray points represent SNPs whose genotypes were imputed. In middle panel, red line shows the fine-scale recombination rate (centimorgans per Mb) estimated from Phase II HapMap and the black line shows the cumulative genetic distance (in cM). Association p=8.5x10^-8.

Gene-by-Environment (GxE) interaction probed by MZ twin intra-pair trait differences:HDL-cholesterol effect of T-cadherin (CDH13, novel adiponectin receptor)

genetic variation revealed by dense, genome-wide profiling in 1662 MZ pairs

p=8.5x10-8

100 kbp

• Common disease / Rare variant hypothesis.Or, accumulation of excess rare variants: Non-synonymous (amino acid

replacement) cSNPs.Technology: Extensive re-sequencing in large numbers of cases vs

controls. Typically resequence a “pathway” in population trait extreme individuals(boost statistical power).

Analyses: Summed χ2, cases versus controls. Computational assessmentof amino acid change functionality (SIFT, PolyPhen). Ultimately functionalstudies.

Qu ic k T ime ™ a n d a d e c o mp re s s o ra re n e e d e d to s e e th is p ic tu re .

Qu ic k T ime ™ a n d a d e c o mp re s s o ra re n e e d e d to s e e th is p ic tu re .

Qu ic k T ime ™ a n d a d e c o mp re s s o ra re n e e d e d to s e e th is p ic tu re .

Accumulation of deleterious rare amino acid substitution variants at extremes of human body mass index (BMI)

Ahituv N, Kavaslar N, Schackwitz W, Ustaszewska A, Martin J, Hebert S, Doelle H, Ersoy B, Kryukov G, Schmidt S, Yosef N, Ruppin E, Sharan R, Vaisse C, Sunyaev S, Dent R, Cohen J, McPherson R, Pennacchio LA. Medical sequencing at the extremes of human body mass. Am J Hum Genet. 2007 Apr;80(4):779-91.

• “Drilling down to the “QTN” (Quantitative Trait Nucleotide)”.Problem: Even after successful allelic association, the lower limit of

resolution is the LD block (~3-50 kbp). So where, within that LD block, is thecausative variant?

Solution: Studies of the putative responsible variant in a system outside ofthe human organism: in vitro (test-tube enzymology), in cella (transfection intocultured cells), or in vivo (transgenic mice).

Drilling down to the “QTN” (“Quantitative Trait Nucleotide”)

• Haplotype “block” is the lower limit of resolution of marker-on-trait mapping.

• Switch to studies of associated variants: – In cella. E.g., transfected/expressed variants.– In vitro. E.g., kinetic properties of variants.– In vivo: transgenic mice (BAC haplotype

variant expression on knockout background).

Positional candidate genetic loci.

“Positional candidate” locus

Wong C, Mahapatra NR, Chitbangonsyn S, Mahboubi P, Mahata M, Mahata SK, O'Connor DT. The angiotensin II receptor (Agtr1a): functional regulatory polymorphisms in a locus genetically linked to blood pressure variation in the mouse. Physiol Genomics. 2003 Jun 24;14(1):83-93.

“Positional candidate” locus

Wong C, Mahapatra NR, Chitbangonsyn S, Mahboubi P, Mahata M, Mahata SK, O'Connor DT. The angiotensin II receptor (Agtr1a): functional regulatory polymorphisms in a locus genetically linked to blood pressure variation in the mouse. Physiol Genomics. 2003 Jun 24;14(1):83-93.

“Positional candidate” locus

Wong C, Mahapatra NR, Chitbangonsyn S, Mahboubi P, Mahata M, Mahata SK, O'Connor DT. The angiotensin II receptor (Agtr1a): functional regulatory polymorphisms in a locus genetically linked to blood pressure variation in the mouse. Physiol Genomics. 2003 Jun 24;14(1):83-93.

Wild-type

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Firefly luciferaseenzymatic activity assay

Transfection

Celllysis

Promoter variant characterization

Wong C, Mahapatra NR, Chitbangonsyn S, Mahboubi P, Mahata M, Mahata SK, O'Connor DT. The angiotensin II receptor (Agtr1a): functional regulatory polymorphisms in a locus genetically linked to blood pressure variation in the mouse. Physiol Genomics. 2003 Jun 24;14(1):83-93.

“Positional candidate” locus

• “Risk” allele (gene) versus “modifier” allele (gene).Risk allele: Allele that increases risk/susceptibility for disease, in

longitudinal studies.Example: CFTR (Cl- channel) ΔF508 ‡ Cystic fibrosis.

Modifier allele: Allele that influences course of the disease, once thatdisease has occurred.

Example: KCNMB1 Glu65Lys ‡ Rapid progression of renaldysfunction.

Exposure

Dz

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Rapid decline

Initiation(case/control study)

Outcome(longitudinal study)

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Genomics in Dz risk: Two kinds of Gene-by-Environment interactions.

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Figure 3A

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Overall: p<0.001KCNMB1: p=0.030Covariate: Pro_cr p<0.001; Mb_GFR p<0.001; BP goal p=0.196; Drug p=0.065Permutation test: p=0.017Alleles: E=95%, K=5%. HWE: p=0.552

E/E E/K+K/K KCNMB1 E65K genotype

KCNMB1 Glu65Lys effect on rate of GFR declinein hypertensive nephrosclerosis (NIDDK AASK)

KCNMB1 Glu65Lys predicts long-term loss of renal functionin hypertensive nephrosclerosis (NIDDK AASK)

E/K+K/K

E/K+K/K censored

E/E

E/E censored

Log rank p=0.0190Event: ESRD requiring dialysis or doubling of serum creatinine

Months after enrollment

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Figure 3B

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VOCC BK

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VOCC BK

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1 subunit 1 subunit

Contracted mesangialor smooth muscle cell

Relaxed mesangialor smooth muscle cell

K+ K+

: Ca2+ ions

: Inhibition

KCNMB1 Glu65Lys: Hypothesis for effect on GFR

Figure 4Higher fluxLower flux

Wild-type Variant

WHAT HAVE WE LEARNED?• “Complex” trait definition.• Risk (susceptibility) factors.• “Intermediate” (risk) traits (phenotypes).• Family/twin studies and heritability.• Genetic linkage: Co-segregation of marker and trait.• Allelic association: Marker ‡ trait.

• “Candidate” gene.• GWAS (Genome Wide Association Study). Hypothesis: Common disease/Common Variant.• Common disease / Rare variant hypothesis.• “Drilling down to the “QTN” (Quantitative Trait Nucleotide)”.• “Risk” allele (gene) versus “modifier” allele (gene).

SAMPLE QUESTIONS.The idea has been to develop a feeling for concepts, rather than details. The

responses I would make are indicated by “*” or “‡ ”.

Which of these phenotyped datasets would allow you to establish heritability (h2)of a trait? Pick all that are correct.

Twin pairs *Nuclear families (parents, siblings, children) *Extended pedigrees (including second degree relatives) *Random sample of the US urban population taken from Chicago, Illinois.Probands from a case/control study of asthma.

Which of the following data on families and disease would allow estimation ofheritability? Pick one.

Street and city address with zip code.Trait measurements in MZ and DZ twin pairs. *

Match the gene-finding method with the type of information discovered.Method Information

Linkage ‡ LociAssociation ‡ Alleles

What biological process gives rise to haplotype (LD) blocks? (Pick one).Meiotic recombination *X-irradiationCosmic raysSite-directed mutagenesis

Which of the following epidemiologic parameters can help to estimate whether heredity influencesa trait? Pick one.

Familial relative risk, estimated by odds ratio *Family incomeFederal and state income tax returnsCollege tuition payments

If you wished to scroll through the entire genome searching for an allelic association to a complextrait in cases versus controls, how many SNP genotypes would you need to type, in order tocapture the correlated LD blocks across the genome? Pick one.

5K50K500K *5 million