Race and Ethnicity in Genetic Epidemiology

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Race and Ethnicity in Genetic Epidemiology

• Neil Risch

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Does Race/Ethnicity Matter?

• Editorial, New England Journal of Medicine
• Race is biologically meaningless.
• Nature Genetics Editorial
• Commonly used ethnic labels are both
  insufficient and inaccurate representations of
  inferred genetic clusters.
• Genetic data show that any two individuals
  within a particular population are as different
  genetically as any two people selected from any
  two populations in the world.

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Does Race/Ethnicity Matter?

• Jack Kemp
• The human genome project shows there is no
  genetic way to tell the races apart. For
  scientific purposes, race doesnt exist.
• President Bill Clinton
• All the schoolchildren will soon be learning in
  their biology classes that all the people in the
  world all the people in the world, in terms of
  their genetic makeup, scientifically, are 99.9
  the same. The Serbs, the Albanians, the Irish,
  the Latins, the Asians.

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Does Race/Ethnicity Matter?

• J. Craig Venter
• It is disturbing to see reputable scientists and
  physicians even categorizing things in terms of
  race there is no basis in the genetic code for
  race.

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Does Race/Ethnicity Matter?

• Eric Lander (Nova Interview)
• The genetic difference between any two people,
  whether its a Sumo wrestler or a Sports
  Illustrated bathing suit model one tenth of a
  percent. Those two, and any two people on this
  planet, are 99.9 identical at the DNA level.

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Does Race/Ethnicity Matter?

• Eric Lander (continued)
• So race is not a very helpful category to a
  geneticist, because its focusing on a fairly
  small number of genes that describe appearance.
  But if were talking about the 30,000 genes that
  run the human symphony, thats a tapestry that
  weaves through every population. Thats why
  geneticists really dont think race is a terribly
  helpful concept.
• But then to define all the human variation on
  top of it, we sequenced millions and millions of
  DNA segments from a worldwide sample of 24
  people Pacific Islanders, Asians, Africans,
  Americans.

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Does Race/Ethnicity Matter?

• Haga and Venter (ScienceJuly, 2003)
• We are concerned that applying antiquated labels
  to the analysis and interpretation of scientific
  data could result in misleading and biologically
  meaningless conclusions.

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Does Race/Ethnicity Matter?

• Shields et al (Am Psychol, 2005)
• The authors examine the history of racial
  categories, current research practices, and
  arguments for and against using race variables in
  genetic analyses. The authors argue that the
  sociopolitical constructs appropriate for
  monitoring health disparities are not appropriate
  for use in genetic studies investigating the
  etiology of complex diseases.

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What is the evidence regarding genetic structure
and race?
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Results from Population Genetics Studies

• Bowcock et al, Nature, 1994
• 30 microsatellite loci
• 14 populations, 148 subjects
• African - CAR pygmy, Zaire pygmy, Lisongo
• Caucasian Northern European, Italians
• Oceania Melanesian, New Guinean, Australian
• East Asia Chinese, Japanese, Cambodian
• Americas Maya, Surui, Karatiana

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Calafell et al, Eur J Hum Genet, 1998

• 45 microsatellite loci
• 10 populations, 504 subjects
• African CAR pygmy, Zaire pygmy
• Caucasian Dane, Druze
• Oceania Melanesian (Nasioi)
• East Asia Chinese, Japanese, Yakut
• Americas Maya, Surui

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Unpublished data (Collaboration with Ken and Judy
Kidd)

• 49 SNPs in 14 Loci
• 33 populations, 1716 subjects
• African Biaka, Mbuti, Yoruba, Ibo, Hausa,
  Ethiopia, African American
• Caucasian Yemen, Druze, Samaritan, Adygei,
  Russia, Finn, Dane, Irish, European American
• Oceania Nasioi, Micronesian
• East Asia SF Chinese, Taiwan Chinese, Hakka,
  Ami, Atayal, Japanese, Cambodian, Yakut
• Americas Cheyenne, AZ Pima, MX Pima, Maya,
  Ticuna, Surui, Karitiana

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What is the evidence regarding genetic structure
and race?

• How much correlation is there between
  self-identified race/ethnicity (SIRE) and genetic
  structure in the human population?
• Results from the Family Blood Pressure Program
  (FBPP)

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FBPP

• Study of genetic and environmental determinants
  of hypertension in families
• Four networks, 15 field centers (collection
  sites), four major race/ethnicity groups
  Caucasian (CAU), African American (AFR), East
  Asian (Chinese, Japanese) (EAS), Hispanic
  (Mexican American) (HIS)
• Our analysis includes one subject per family

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FBPP

• Total of 3,636 individuals included (one per
  family)
• CAU 1349, 6 sites
• AFR 1308, 4 sites
• HIS 412, 1 site
• EAS 567 (407 CHI, 160 JAP), 5 sites
• 18 SIRE-site combinations total

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FBPP

• Genome Screen STR markers, all typed at the NHLBI
  sponsored Mammalian Genotyping Service,
  Marshfield, Wisconsin (James Weber)
• Total number of markers included 366.

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Analysis

• Genetic Distances (Reynolds,1983 Nei, 1978)
  between all pairs of SIRE-sites (18x17/2 153
  comparisons)
• Multidimensional scaling (MDS) for two
  dimensional depiction of genetic distances
• Branching tree relating 18 SIRE-sites
• Genetic Cluster Analysis (GCA) using STRUCTURE on
  all 3,636 subjects (326 markers), comparison with
  SIRE

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Genetic Cluster Analysis4 Clusters
Cluster A Cluster B Cluster C Cluster D
CAU 1348 0 0 1
AFR 3 0 1305 0
HIS 1 0 0 411
CHI 0 407 0 0
JAP 0 160 0 0
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Genetic Cluster AnalysisEast Asians Alone
Cluster A Cluster B
CHI 405 2
JAP 4 156
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GCA Classification versus SIRE

• Concordant 3,631
• Discordant 5
• Discordance Rate .0014

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Reynolds-Stanford-Kaiser Cardiovascular Disease
Project

• Investigators
• Stanford Tom Quertermous, Mark Hlatky, Steve
  Fortmann, Rick Myers, Richard Olshen, Neil Risch
• Kaiser Alan Go, Carlos Iribarren, Malini
  Chandra, Phenius Lathon
• Analysis by Analabha Basu

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SELF-IDENTIFIED RACE ETHNICITIES
White (Caucasoid) 2281
Black (African-American) 438
Hispanic 197
Indian-Pakistani (South-Asian) 55
Asian/ Asian-American (East-Asian) 223
Native Hawaiian or Other Pacific Islander 9
American-Indian/Native American 2
Mixed-Hispanic 326
Mixed-Other 138
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Overview of Genetic data

• 467 Markers (SNPs)
• 452 Autosomal Markers 15 X-chromosomal Markers
• 77 Candidate Genes
• 73 on Autosomal Chromosomes 4 on X-chromosome

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Multidimensional Scaling ( using Reynolds
Distance)

• South-Asians are with Hispanics

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Multidimensional Scaling
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Structure with 4 ancestral populations

• Self-Identified Inferred
  Clusters Number of
• Population 1 2
  3 4 Individuals
• Caucasian 0.943 0.004 0.004
  0.050 265
• African-American 0.011 0.989 0.000
  0.000 183
• Hispanic 0.138 0.000 0.000
  0.862 181
• South-Asian 0.287 0.000 0.006
  0.706 55
• East-Asian 0.014 0.000 0.981
  0.005 215

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Structure with 5 ancestral populations

• Self-Identified Inferred
  Clusters Number of
• Population 1 2
  3 4 5 Individuals
• Caucasoid 0.858 0.027 0.108
  0.004 0.004 265
• African-American 0.011 0.000 0.000 0.000
  0.989 183
• Hispanic 0.126 0.742 0.132
  0.000 0.000 181
• South-Asian 0.046 0.018 0.935
  0.000 0.000 55
• East-Asian 0.014 0.005 0.000
  0.981 0.000 215

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Analysis of Group Differences

• SIRE and GCA give nearly identical results with
  enough genetic markers
• Important environmental/social/cultural
  differences also exist between SIRE groups
• High correlation between SIRE and GCA leads to
  strong confounding between genetic and
  non-genetic factors when examining group
  differences in prevalence of diseases or traits

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Analysis of Group Differences

• Ignoring the SIRE/GCA relationship (and avoiding
  SIRE, using GCA only) runs the risk of false
  inference of genetic explanations for group
  differences
• Distinguishing between genetic and non-genetic
  sources of group differences best examined within
  a single admixed group, but depends on variation
  in admixture levels, and is still possibly
  subject to residual correlation and confounding

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Analysis of Individuals Admixture Analysis

• Even though the four ethnic groups were easily
  separable based on genetic markers, African
  Americans and Latino Americans typically have
  ancestry from multiple continents. Using the
  same genetic markers, it is possible to estimate
  for each individual the proportions of ancestry,
  or individual ancestry (IA) from each
  continental/ancestral group.

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Analysis of Individuals Admixture Analysis

• African Americans and Latino Americans typically
  have ancestry from multiple continents. Using
  genetic markers, it is possible to estimate for
  each individual the proportions of ancestry, or
  individual ancestry (IA) from each
  continental/ancestral group.

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Admixture AnalysisFBPP

• Estimation of ancestry requires genotypes of
  individuals representing the original indigenous
  ancestors. For our analyses, we included 1,378
  unrelated Caucasians from the FBPP, 127 unrelated
  sub-Saharan Africans and 50 Native Americans from
  the World Diversity Panel.

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Admixture Analysis - FBPP

• These various data sources shared 284
  microsatellite markers from the Marshfield
  Screening Set 10, where all subjects were
  genotyped.
• IA estimates were obtained from the genetic
  cluster analysis program Structure (Pritchard et
  al).

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African Ancestry in African Americans
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Ancestry in Mexican Americans from Starr County,
Texas
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Admixture Analysis

• Distinguishing between genetic and non-genetic
  sources of group differences can be examined
  within a single admixed population.
• Depends on variation in admixture levels within
  that population
• Examine correlation of individual ancestry (IA)
  with trait of interest (e.g. does blood pressure
  correlate with African ancestry?)

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Admixture Analysis - FBPP

• 3,207 African Americans representing 1,801
  sibships from 4 recruitment sites
• 1,506 Mexican Americans representing 453 sibships
  from 1 recruitment site
• Estimated IA and its correlation with blood
  pressure, hypertension, and BMI

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Admixture Analysis Blood Pressure and BMI

• For blood pressure and BMI, performed linear
  regression on estimated African IA for the
  African Americans (n1424) and on African IA and
  Caucasian IA for the Mexican Americans (n1122),
  adjusted for age, age2, sex and field center.
  BMI was included as a covariate for blood pressure

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African IA in hypertensives versus normotensives
Site Group Hypertensive Hypertensive Normotensive Normotensive Delta P value
Number Mean (sd) Number Mean (sd)
Maywd Afr. Amer. 49 .863 (.097) 141 .867 (.092) -.004 .805
Jackson Afr. Amer. 223 .851 (.123) 37 .827 (.113) .024 .264
Forsyth Afr. Amer. 144 .845 (.114) 47 .820 (.139) .025 .225
Birming Afr. Amer. 351 .881 (.086) 34 .860 (.102) .021 .170
Starr Mex. Amer. 101 .043 (.029) 161 .043 (.030) .000 .89
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Results of ANOVA of African IA
Factor df Sum of Sq. Mean Sq. F value P value
Site 3 .271 .093 8.269 .00002
Hyper-tension 1 .035 .035 3.185 .075
Resid. 1021 11.148 .011
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Linear Regression on African IA in African
Americans
b(IA) SBP b(IA) DBP b(IA) MAP b(IA) BMI
5.4 (4.5) 3.0 (3.1) 6.2 (3.3) 4.0 (2.0)
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Regression in Mexican Americans on African and
Caucasian IA
Outcome b(IA) African b(IA) Caucasian
SBP 9.5 (21.6) -8.9 (5.8)
DBP 18.9 (10.0) -1.0 (2.6)
MAP 15.6 (12.6) -3.9 (3.3)
BMI 3.9 (6.0) 4.3 (1.7)
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Admixture Analysis

• Caveat Still possibly subject to residual
  correlation and confounding
• For example, within African Americans,
  discrimination may be related to both skin
  pigment and adverse health outcomes
• Skin pigment is likely to be genetically
  correlated with degree of European versus African
  ancestry

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Admixture Mapping

• As opposed to ancestry estimates based on the
  entire genome, which may be confounded with
  non-genetic factors, ancestry at specific genetic
  locations are less likely to be so confounded
• The power of the method depends on how large the
  effect of an allele is on the trait, and the
  difference in the frequency of that allele
  between ancestral groups

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Admixture Analysis

• If only a small number of genes contribute to
  ethnic difference, global estimate may be only
  poorly correlated with those specific locations
• Therefore, locus-specific analysis might be more
  informative (admixture mapping)

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Admixture Mapping

• If the admixture occurred recently in history
  (e.g. over the past 10 generations), then the
  ancestry excess will extend over large segments
  of the chromosome
• Thus, markers in the vicinity of the trait locus
  will also show excess ancestry from the
  population with the higher allele frequency

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Admixture Mapping in FBPP

• Estimated locus-specific African ancestry for
  hypertensives from 3 networks separately also a
  pooled group of cases based on more stringent
  criteria performed similar analysis on controls
  (normotensives)

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Red Line Marker Information
Black Line Genome-wide Z scores
Cases
Controls
Distribution of Z Scores
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Table 2 Marker locations associated with the largest excess of African ancestry in hypertensive subjects for each individual network Table 2 Marker locations associated with the largest excess of African ancestry in hypertensive subjects for each individual network Table 2 Marker locations associated with the largest excess of African ancestry in hypertensive subjects for each individual network Table 2 Marker locations associated with the largest excess of African ancestry in hypertensive subjects for each individual network

Network and marker Location (cM) Excess African ancestry Z score

GenNet
GATA184A08 6q24.1 (146) 0.021 3.08
D6S2436 6q25.1 (155) 0.021 3.08
D21S1437 21q21 (13) 0.017 2.55
GENOA
GATA184A08 6q24.1 (146) 0.011 4.23
D6S2436 6q25.1 (155) 0.010 3.01
HyperGEN
GATA184A08 6q24.1 (146) 0.017 4.69
D6S2436 6q25.1 (155) 0.011 2.91
D21S1437 21q21 (13) 0.011 2.88
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Lessons from Asthma

• Data from Esteban Burchard and colleagues.
• Example of complex interplay between ancestry and
  environmental factors

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Lifetime Asthma Prevalence in US
Lara et al, 2006
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Genetics of Asthma in Latino Americans (GALA)

• Esteban Burchard, PI
• Study of Mexican and Puerto Rican asthmatics from
  Mexico, Puerto Rico and the US.

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Genetics of Asthma in Latino Americans (GALA)

• Estimated African, European and Native American
  ancestry in Puerto Ricans with ancestry
  informative markers (AIMS)
• Examined relationship of ancestry and
  socio-economic status (SES) on asthma risk
• Found an interaction between ancestry, SES and
  asthma risk

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Ancestry-Socioeconomic Status Interaction Risk
of Asthma
In lower SES category, Puerto Ricans patients
with asthma had less African and more European
ancestry compared to healthy controls, whereas in
upper SES category, patients with asthma had
more African and less European ancestry compared
to healthy controls
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Conclusion

• Epidemiologic and genetic studies in admixed
  populations (e.g. African Americans and Latinos)
  offers unique opportunities to unravel complex
  genetic and environmental contributors to disease

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Two Examples of Ethnic-Specific Alleles in
Pharmacogenetics

• Irinotecan (Camptosar) and colon cancer
• Carbamazepine and Stevens-Johnson Syndrome

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Irinotecan and Colon Cancer

• Extreme side effects in some patients
• Severe diarrhea, neutropenia
• Recommended reduced starting dosage
• Metabolized by uridine diphosphate
  glucuronosyltransferase isoform 1A1 (UGT1A1)
• Homozygotes/compound heterozygotes for deficiency
  alleles at greatly increased risk for side effects

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Frequency of UGT1A1 Deficiency Genotypes by
Ethnic Group
Blacks Whites Asians Pac Isls
28/28 20 15 1 lt0.1
6/6 6/28 lt0.1 lt0.1 5.5 ?
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Stevens-Johnson Syndrome and Carbamazepine
(Tegretol)

• Carbamazepine most common cause of SJS in Asians
• HLA B1502 a major risk factor in Han Chinese
• Relative Risk estimated at 2,500 (Chung et al,
  Nature 2004)
• B1502 carrier frequency about 8 in Chinese,
  very rare or non-existent in other racial groups
• May explain greater proportion of SJS due to
  carbamazepine in Asians than other groups