Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities
Authors: Tilahun Abebe
Tesfaye B Mersha
Journal: Human Genomics (2015)
Discipline: MOLECULAR BIOLOGY & GENETICS
Keywords: limitations; self-reported; race; ethnicity; genetic ancestry
Affiliations: Division of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA. ., Department of Biology, University of Northern Iowa, Cedar Falls, IA, USA. .

Abstract:  This review explores the limitations of self-reported race, ethnicity, and genetic ancestry in biomedical research. Various terminologies are used to classify human differences in genomic research including race, ethnicity, and ancestry. Although race and ethnicity are related, race refers to a person's physical appearance, such as skin color and eye color. Ethnicity, on the other hand, refers to communality in cultural heritage, language, social practice, traditions, and geopolitical factors. Genetic ancestry inferred using ancestry informative markers (AIMs) is based on genetic/genomic data. Phenotype-based race/ethnicity information and data computed using AIMs often disagree. For example, self-reporting African Americans can have drastically different levels of African or European ancestry. Genetic analysis of individual ancestry shows that some self-identified African Americans have up to 99% of European ancestry, whereas some self-identified European Americans have substantial admixture from African ancestry. Similarly, African ancestry in the Latino population varies between 3% in Mexican Americans to 16% in Puerto Ricans. The implication of this is that, in African American or Latino populations, self-reported ancestry may not be as accurate as direct assessment of individual genomic information in predicting treatment outcomes. To better understand human genetic variation in the context of health disparities, we suggest using "ancestry" (or biogeographical ancestry) to describe actual genetic variation, "race" to describe health disparity in societies characterized by racial categories, and "ethnicity" to describe traditions, lifestyle, diet, and values. We also suggest using ancestry informative markers for precise characterization of individuals' biological ancestry. Understanding the sources of human genetic variation and the causes of health disparities could lead to interventions that would improve the health of all individuals. 

Retracted: No

PubPeer comments:
 The article states in the Abstract: Genetic analysis of individual ancestry shows that some self-identified African Americans have up to 99% of European ancestry And sources this claim further in the article: To illustrate, in a recent study, 9 of the 1,247 self-reported African Americans were found to have 100% European ancestry [69]. [69] does not support such claim, was not recent and does not contain  247 anywhere. However, I was able to find the following in [Kodaman et al. (2013)] (which is not cited): The 1300 self-reported African-Americans had a mean proportion of 0.92 African ancestry and the 1247 self-reported European Americans a mean African ancestry of 0.01. Nine of the self-reported African Americans were found to have greater than 0.88 proportion European ancestry, suggesting incorrect classification. The journal drafted a correction, which simply replaced [69] reference with Kodaman, failing to correct factual discrepancies. That prompted me to check the rest of the article and identify a number of other missing or misinterpreted references. To those the journal responded: We discussed your editorial suggestions in detail with the Editor-in-Chief and the authors and decided **not to take any further actions** as the content of the article and the conclusions drawn are not wrong and would not change the science or message. Those issues are: 1) Kodaman (2013) reports  1300 ; tMersha (2015) quotes  1247 . tKodaman: 88%; tMersha: 99% and 100%. 2) Kodaman does not support the claim  that some self-identified African Americans have up to 99% of European ancestry or that the 9 individuals in question had any European ancestry at all. The paper explicitly suggests some sort of error in those cases, but does not investigate it any further. tKodaman s study is done under the *assumption* of two clusters, European and African American. So those 9 exceptional cases could, for example, have 100% Native American or 100% South Asian ancestry. 3) Kodaman does not support the claim that  Phenotype-based race ethnicity information and data computed using AIMs often disagree. tWhile the title of the Kodaman s article might be misleading, the article is concerned with minimization of number of AIMs SNPs while maintaining the accuracy characteristic of a larger number of AIMs. It does not address the accuracy of self-reported race beyond a single sentence. tHowever, 9 1300 0.007 seems to me very accurate. Surely much more accurate than typical correlations between ancestry and diseases. tIn the words of researchers who do address the accuracy of self-reported race ([Tang, 2005] ): t Genetic cluster analysis of the microsatellite markers produced four major clusters, which showed **near-perfect** correspondence with the four self-reported race ethnicity categories. Of 3,636 subjects of varying race ethnicity, only 5 (0.14%) showed genetic cluster membership different from their self-identified race ethnicity. 4) t Similarly, some self-identified European Americans have substantial admixture from African ancestry [70]. tThe actual admixture results for European Americans from [70] are: t0.7%u00b10.9% African ancestry, t96.1%u00b11.6% European ancestry, t3.2%u00b11.6% Native American ancestry. tOr, in the words of the authors, *low*. 5) No reference or methodology is given for Table 1. Presumably it has been computed under the assumption of two clusters, and the 99% maximum for  European ancestry among African Americans is due to a single outlier with likely 60% Native American ancestry (NA20314, EUR=0.40, NAT=0.59) per [Martin (2016)] , Figure S1. 6) t On average, any two randomly selected humans have 99.9% identical DNA [2]. tAlthough a common (over)estimate at the time, I couldn t find it in [2] at first glance. 7) t Thus, the overrepresentation of rare causal variants in certain population could explain the observed differences in disease prevalence, including asthma [6]. tBut [6] does not mention asthma, it s about Tourette Syndrome. 8) t There are two potential reasons why some variants are relatively common in one population but absent (or nearly so) in another: a) a recent emergence of a variant that has not yet had time to spread to other populations and b) natural selection in a specific local environment. tNo reference given. There is no reason to expect a recent mutation to spread to other populations over time. Also fails to acknowledge genetic drift and the founder effect. 9) t An example of the first scenario is a SNP that causes hereditary hemochromatosis, which is common in Europe but very rare elsewhere. tNo reference given. 10) t This phenomenon is referred to as the u201cHispanic Paradoxu201d [21]. t[21] does not contain the word  paradox . Looking at the Wikipedia [article] , that paradox doesn t seem to refer to differences within Hispanics. 11) t The prevalence of HLA-B*5701 variant in the Masai group in Kenya is 13.6%; the frequency of the same allele was zero among the Yoruba in Nigeria and 5.8% among European ancestry. tNo reference given. 12) t Studies have shown that the u201cEveu201d for Cuban population is about 38.8% African, 34.5% Native Americans, and 26.7% Europeans. tThat is not correct. Those are the proportions of mtDNA haplotypes within the modern population [33], not within a single ancestor. 13) t However, the same can be said to the CEU population where recent high-density SNP studies showed population gradient including linkage disequilibrium discrepancies across the Northu2013south and even within Finland (Eastu2013west) [55]. tAt first glance, [55] does not seem to describe differences within Finland. 14) t Almost all genetic studies, including many of the identified variants (e.g., asthma) and pharmacogenetic studies have been primarily performed in cohorts of European descent [79]. t[79] does not seem to make claims about proportions in all genetic studies. It reads: t We identified **three** genome-wide association studies of warfarin dose requirement and one of acenocoumarol. All previous studies were done in either European or Asian populations. ... To identify previous studies testing genetic variation associated with warfarin dose requirements in African Americans, we did another search of PubMed with the same date criteria and no language restrictions, but used the search terms u201cwarfarinu201d and u201cAfrican Americanu201d. We identified **five** studies, all of which used a candidate-gene approach. 15) t A good example that illustrates this phenomenon is the recent studies that showed education and socioeconomic factors, but not genetic ancestry, were associated with blood pressure and cancer among African Americans in the US, respectively [91,92]. t[91] does not support that claim. It is a reply to the letter to the editor about preterm delivery and says: t However, as indicated by decades of research and the recent Institute of Medicine report that **sociodemographic risk factors cannot fully explain** the striking and persistent racial disparity in PTD, PTD is likely a complex disease that is influenced by multiple genetic and environmental factors and their interactions. Given the promise of admixture mapping in other diseases with prominent racial disparity, our study represents a novel approach to search for other possible causes of PTD **beyond sociocultural factors**. t[92] does not seem to support that claim either. It is a psychology paper that does not contain  genetic or  ancestry . 16) t Furthermore, analysis showed that education was significantly associated with blood pressure in African Americans, but not in European American, suggesting that improved access to education in African American communities may help to reduce racial inequalities in health. tNo reference given. 17) t Meanwhile, African populations ... are grossly underrepresented in the genomic studies that inform pharmaceutical guidance [95]. t[95] does not support the claim. 18) t This concern extends to the momentous debate about the development of u2018race-targetedu2019 drugs, such as BiDil (approved by the US Food and Drug Administration (FDA) to treat heart failure in admixed African Americans), based on subgroup analyses without any adjustment for potential confounders in samples [94]. tLooks like a wrong reference. 19) t A study by Lee [100] showed that warfarin dosing algorithms that are based on u2018raceu2019 terms for well-defined ethnic groups are not applicable to the heterogeneous admixed population. t[100] does not contain  warfarin . 20) Missing word  more : t Genetic ancestry can describe genetic relatedness accurately than race and ethnicity tOther typos: t X-lined t much small t andY-DNA t Recent advance ... allow t 106. Race E, Genetics Working G. ,