Race and Ethnicity in Genetic Epidemiology

1. Race and Ethnicity in Genetic Epidemiology Neil Risch

2. 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.”

3. 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 doesn’t 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.”

4. 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.”

5. Does Race/Ethnicity Matter? • Eric Lander (Nova Interview): • “The genetic difference between any two people, whether it’s 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.

6. Does Race/Ethnicity Matter? • Eric Lander (continued): • “So race is not a very helpful category to a geneticist, because it’s focusing on a fairly small number of genes that describe appearance. But if we’re talking about the 30,000 genes that run the human symphony, that’s a tapestry that weaves through every population. That’s why geneticists really don’t 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.”

7. Does Race/Ethnicity Matter? • Haga and Venter (Science;July, 2003): • “We are concerned that applying antiquated labels to the analysis and interpretation of scientific data could result in misleading and biologically meaningless conclusions.”

8. 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.”

9. What is the evidence regarding genetic structure and race?

10. 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

12. 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

14. 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

19. 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)

21. 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

22. 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

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

24. 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

26. Genetic Cluster Analysis4 Clusters

27. Genetic Cluster AnalysisEast Asians Alone

28. GCA Classification versus SIRE • Concordant: 3,631 • Discordant: 5 • Discordance Rate: .0014

29. 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

30. SELF-IDENTIFIED RACE ETHNICITIES

31. 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

32. Multidimensional Scaling( using Reynolds Distance) South-Asians are with Hispanics

33. Multidimensional Scaling

34. 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

35. 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

36. 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

37. 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

38. 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.

39. 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.

40. 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.

41. 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).

42. African Ancestry in African Americans

43. Ancestry in Mexican Americans from Starr County, Texas

44. 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?)

45. 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

46. Admixture Analysis – Blood Pressure and BMI • For blood pressure and BMI, performed linear regression on estimated African IA for the African Americans (n=1424) and on African IA and Caucasian IA for the Mexican Americans (n=1122), adjusted for age, age2, sex and field center. BMI was included as a covariate for blood pressure

47. African IA in hypertensives versus normotensives

48. Results of ANOVA of African IA

49. Linear Regression on African IA in African Americans

50. Regression in Mexican Americans on African and Caucasian IA