Race, Ethnicity & Ancestry in Genetic Research

17 Pages·2011·0.29 MB·English

HUGOJ
DOI10.1007/s11568-011-9154-5
RESEARCH ARTICLE
The use of race, ethnicity and ancestry in human genetic research
Sarah E. Ali-Khan • Tomasz Krakowski •
Rabia Tahir • Abdallah S. Daar
Received:4February2011/Revised:27April2011/Accepted:17June2011
(cid:2)TheAuthor(s)2011.ThisarticleispublishedwithopenaccessatSpringerlink.com
Abstract Post-Human Genome Project progress has with some of the recommendations/guidelines for the use
enabled a new wave of population genetic research, and of race/ethnicity over time, while showing that important
intensifiedcontroversyovertheuseofrace/ethnicityinthis shortfallsstillremain:noarticleusing‘race’,‘ethnicity’or
work. At the same time, the development of methods for ‘ancestry’ defined or discussed the meaning of these con-
inferring genetic ancestry offers more empirical means of cepts in context; a third of articles still do not provide a
assigning group labels. Here, we provide a systematic rationalefortheiruse,withthoseusing‘ancestry’beingthe
analysisoftheuseofrace/ethnicityandancestryincurrent least likely to do so. Further, no article discussed potential
genetic research. We base our analysis on key published socio-ethical implications of the reported research. As
recommendations for the use and reporting of race/eth- such, there remains a clear imperative for highlighting the
nicity which advise that researchers: explain why the importance of consistent and comprehensive reporting on
terms/categories were used and how they were measured, human populations to the genetics/genomics community
carefully define them, and apply them consistently. We globally, to generate explicit guidelines for the uses of
studied 170 population genetic research articles from high ancestry and genetic ancestry, and importantly, to ensure
impact journals, published 2008–2009. A comparative that guidelines are followed.
perspective was obtained by aligning study metrics with
similar research from articles published 2001–2004. Our Keywords Race(cid:2)Ethnicity(cid:2)Ancestry(cid:2)Geneticancestry
analysis indicates a marked improvement in compliance inference (cid:2) Terminology (cid:2) Genetic research
S.E.Ali-Khan(&)(cid:2)T.Krakowski(cid:2)R.Tahir(cid:2)A.S.Daar Introduction
McLaughlin-RotmanCentreforGlobalHealth,University
HealthNetworkandUniversityofToronto,101CollegeSt,Suite The completion of the Human Genome Project over a
406,Toronto,ONM5G1L7,Canada
decade ago has led to intensified studies of genetic varia-
e-mail:[email protected];[email protected]
tioninhumanpopulations.Muchofthisworkusesspecific
A.S.Daar
population identities to categorize groups, for example
e-mail:[email protected]
Caucasian, Korean, South Asian and Yoruban, and in
A.S.Daar addition often uses the generic terminology ‘race’ and
DepartmentofPublicHealthSciencesandofSurgery, ‘ethnicity’ to refer to them. The validity of using socially-
UniversityofToronto,Toronto,ONM5S1A8,Canada
visible groups inbiomedical research has been an ongoing
controversy.However,thereisnowresurgentinterestinthe
A.S.Daar
McLaughlinCentreforMolecularMedicine,UniversityHealth subject (Burchard et al. 2003; Cooper et al. 2003; Duster
NetworkandUniversityofToronto,Toronto,ONM5S1A1, 2005; Risch et al. 2002; Schwartz 2001; Stevens 2003),
Canada
because technology advances are increasing opportunities
to clarify the relationship between social identity, genetic
A.S.Daar
GrandChallengesCanada,http://www.grandchallenges.ca diversity and health, and to move beyond old prejudices
123
HUGOJ
about human difference (Ali-Khan and Daar 2010; Edito- Working Group 2005; Rivara and Finberg 2001; Sankar
rial 2004a; Rotimi 2004). Accordingly, in the last 2 years andCho2002;Winker2004);(3)describehowparticipants
several multidisciplinary groups including our own, have were assigned to the research populations (Anonymous
convened to examine these issues afresh (Caulfield et al. 2005;Editorial2004b;Lee etal.2008;RaceEthnicityand
2009, Lee et al. 2008). Genetics Working Group 2005; Sankar and Cho 2002;
A fundamental difficulty raised by the use of socially- Winker2004);and(4)describethelimitationsofthestudy
visible population labels—whether they are referred to as with respect to the populations to which the research
‘races’, ethnicities, nationalities, or by other language—is findings can be generalized (Anonymous 2003; Anony-
that their meanings and parameters are context-dependent mous 2005; Davis et al. 2001; Ioannidis et al. 2004;
(Kressin et al. 2003; Rotimi 2004), and have powerful Osborne and Feit 1992). Various of these have been
ramifications beyond the domain of science (Bamshad and endorsed by biomedical journals, and by the International
Olson 2003; Clayton 2002; Gould 1981; Lewontin 1995; Council of Medical Journal Editors http://www.icmje.org/
Provine 1973). Lack of clarity and consistency in the journals.html#S (for review, see Caulfield et al. 2009).
description of research populations and inadequate justifi- However,studiesassessingcomplianceingeneticresearch
cationfortheirusehasbeenapersistentsourceofconcern published over 2001–2004 (Editorial 2004b; Sankar et al.
in biomedical research (Bhopal 1997; Clayton 2002; Col- 2007; Shanawani et al. 2006); indicated that guidelines
lins 2004; Comstock et al. 2004; Editorial 2004b; Lee were not widely followed.
2004; Sankar and Cho 2002), and can have adverse sci- Since those data were collected, the advent of high-
entific and social consequences, particularly in the context resolution genome-wide genotyping is allowing more
ofgeneticsresearch.Assuch,failuretodefineagrouplabel empiricaldescriptionofindividualsandpopulations,bythe
or describe how membership was ascertained makes it inference of genetic or ‘biogeographical’ ancestry (Bam-
difficulttoknowwhoexactlyisbeingstudied,challenging shad et al. 2004; Li et al. 2008; Novembre et al. 2008;
the reproducibility of research findings and limiting por- Rosenberg et al. 2002; Royal et al. 2010; Shriver et al.
tability to other geneticists, disciplines, and the clinic 2004; Via et al. 2009). Used to determine and quantify
(Brown2007;Editorial2004b;Sankaretal.2007).Further, genetic background, this technology can augment or
suchambiguitycanencourageracial/ethnicstereotypesand supersedetheuseofproxymethods,suchasself-identified
over-simplifications that stymie, rather than promote, race/ethnicity, physical appearance, language-spoken, or
understanding of genetic diversity (Bamshad et al. 2004; ancestry based on geographical origin, to stratify research
Race Ethnicity and Genetics Working Group 2005). participants and maximize their relative genetic homoge-
Likewise, failing to explain why a particular population neity. Thus, some have suggested the use of ‘ancestry’
wasstudiedwithrespecttotheresearchquestioncanimply ratherthanrace/ethnicitytodescribegroupdifferencesand
thatsocialidentityisthebasisforanyobservedphenotypic genetic variation, because of its more objective basis, and
differences. Such interpretations may divert from further perceived distance from negative connotations associated
studytoidentifytrueunderlyingmechanisms(Sankaretal. with‘race’(Ali-KhanandDaar2010;Bamshadetal.2004;
2004), and have dangerous clinical consequences by Race Ethnicity and Genetics Working Group 2005; Smart
encouraging reliance on social identity for prescription or et al. 2006).Ourstudyhadtwogoals; (1) toassess current
prognosis (Braun et al. 2007; Geiger 2003; Lee 2005). compliance with recommendations for the use of race and
Ongoing concern has prompted journal editors, profes- ethnicity—or more broadly social identity—in genetic
sional societies and expert commentators to repeatedly research; and (2) to examine the use of ‘ancestry’ as a
offer guidelines for the use and reporting of race and eth- genericterminologytodescribestudypopulations,andalso
nicityingeneticresearch.Thesehavelargelyconvergedon in the sense of ‘genetic ancestry’ by the use of empirical
four key points; (1) define the race and ethnicity, or more genomic methods to categorize research groupings.
broadly the population terms, used in the context of the Authors who previously examined the use of race and
study (Anonymous 2005; Burchard et al. 2003; Cooper ethnicity in genetic research considered all specific popu-
et al. 2003; Editorial 2004b; Iverson et al. 1998; Kaplan lationidentifiersusedinthecontextofhumansas‘raceand
and Bennett 2003; Race Ethnicity and Genetics Working ethnicity’ terms (Sankar et al. 2007; Shanawani et al.
Group 2005; Sankar and Cho 2002; Winker 2004); (2) 2006).Wedonotdisagreewiththis,butforthepurposesof
explain how the terms or categories relate to the research the second part of our analysis we went beyond previous
hypothesis,orwhytheparticularpopulationwaschosenfor analyses,sub-dividingourdatabythegenericterminology
studybytheresearchers(Anonymous2005;Editorial1996, used to refer to the specific named study populations in
Editorial 2004a; International Council of Medical Journal articles,inordertocomparearticleswhichusedthegeneric
Editors 2010; Iverson et al. 1998; Kaplan and Bennett terms ‘race and/or ethnicity’, with those using ‘ancestry’,
2003; Lee et al. 2008; Race Ethnicity and Genetics or‘other’terms.Inaddition,wenotethatwedidnotdefine
123
HUGOJ
race or ethnicity or ancestry for the purposes of this work, Ancestry Group’. Likewise, each of these terms captures
but rather kept the study open-ended with the goal of all the specific groups classified to these geographic
observing how these terms are currently put to use by regions. For example ‘American Continental Ancestry
authors.Inthisvein,weaddthatthegoalofthisstudywas Group’includes;‘IndiansCentralAmerica’;‘IndiansNorth
not to assess which of these terms should be used by America’, ‘Indians South America’; and ‘Inuits’; and
authors. However, we agree with previous commentators likewise, when expanded each of these terms captures a
that the study of DNA within the context of socially- range of specific population identifiers. For example ‘Inu-
identified groups in no way justifies the definition of sub- its’ corresponds to; ‘Inuit’; ‘Inupiat(s)’; ‘Eskimo(s)’;
groupsofindividualsasbiologicallydistinctraces(Collins ‘Kalaallit(s)’;and‘Aleut(s)’(see:http://www.ncbi.nlm.nih.
2010). gov/mesh).
Wedecidedtodirectoursampletowardarticlesthatare
most likely to reflect the state of the art in the field of
Materials and methods genetic research, and to be of high quality. Our rationale
was that such articles may be most likely to have wider
Study design scientific and social influence, by serving as models and
hypothesis generators for other researchers, and by infil-
In this work we undertook a systematic analysis of scien- trating the non-geneticist community by being reported in
tific articles reporting genetic research in the context of the popular press. To capture articles most likely to be of
human populations. Our analysis was divided into two thistype,weidentifiedaconveniencesampleof10leading
parts.Inthefirstpart,toevaluatehowuseandreportingof population-based geneticists, genetic epidemiologists and
this research has changed over time we assessed selected genome scientists based in the United States and Canada,
metrics adapted from previous studies (Sankar et al. 2007; andaskedthemtoratethetop5mostinfluentialjournalsin
Shanawani et al. 2006). We also asked new questions to which to publish their work. We then limited our article
examine the use of ‘ancestry’ to describe populations, the collection to the top 6 highest ranked journals from this
use of genotyping data to assign ancestry and thus verify survey. These were; the American Journal of Human
research group membership, and whether discussion of Genetics;HumanGenetics;Nature;NatureGenetics;PLoS
socialandethicalimplicationsofthereportedresearchwas Genetics; and Science (N = 197) (search completed Feb-
included in articles. In the second part of the study, to ruary2010)(seeTable 1).Wenotethatthreeofthesehave
assess differences between articles using different generic published policy on the use and reporting of race and
terminology to refer to study populations we sub-divided ethnicity(Brown2007;Editorial2004a,b).However,none
the data by articles using; (1) race and/or ethnicity; are listed as explicitly endorsing the ICMJE’s Uniform
(2)ancestry;and(3)otherterminology.Wethencompared Requirements for manuscripts submitted to biomedical
the metrics obtained in part one of the study across these journals (see http://www.icmje.org/journals.html#S).
sub-divisionsofthedata.Wealsocollectedqualitativedata
with respect to how ‘ancestry’ was used in articles.
Table1 Samplesetcharacteristics,N(%)
Totalsample N=170
Sample selection
Yearofpublication
WeconductedaPubmedsearchstrategytoobtainasample
2008 N=93(54.7%)
ofjournalarticlesforanalysis.Weusedthekeywords(race
2009 N=77(45.3%)
OR ethnicity OR ancestry) and the genetic terms (poly-
Journalofpublication(2008impactfactor)
morphism OR CNV OR SNP), with the limits; humans,
AmericanJournalofHumanGenetics(10.153) N=41(24.1%)
English, and publication dates between January 1st 2008
Humangenetics(4.042) N=38(22.4%)
and December 31st 2009 (N = 3536). The use of ‘race’,
Nature(31.434) N=13(7.6%)
‘ethnicity’ and ‘ancestry’ in Pubmed captures articles in
NatureGenetics(30.259) N=40(23.5%)
which these words occur in the text, articles that use these
PLoSGenetics(8.883) N=32(18.8%)
as words as MeSH headings, and the hierarchy of terms
Science(28.103) N=6(3.5%)
occurring under these headings. For example, ‘race’, is a
Articlegeneralfieldofinterest
synonym for the MeSH heading ‘Continental Population
Populationgenetics N=26(15.2%)
Groups’, which includes; ‘American Continental Ancestry
Medical N=127(74.7%)
Group’; ‘American Native Continental Ancestry Group’;
Methods N=9(5.3%)
‘Asian Continental Ancestry Group’; ‘European ‘Conti-
Non-medical N=8(4.7%)
nental Ancestry Group’; and ‘Oceanic Continental
123
HUGOJ
The abstracts and MeSH information for each article we collected qualitative data for further analysis, by
were then reviewed to exclude all but original research recording the text content as well. We also noted the
articlesfromthesample—news,comments,letters,reviews country of the institution of the first author, how the
and meta-analyses were removed. Finally, the entire arti- researchwasfunded,whetherornotinformedconsentwas
clesweredownloadedandreviewedindetailtoverifyeach reportedfortheresearchpopulationsinvolved,andwhether
described original research studying human genetic varia- or not a conflict of interest statement was provided.
tion using human tissue samples or human subjects. This
process yielded a final study sample of 170 articles for Basic features Each article was analysed with respect to
analysis. three basic features providing fundamental information
aboutthestudyitreported.Eachcodewasscoredasayes/
Data analysis novariable.(1)hypothesiswasdefinedasthepresenceofa
foundingideaorassumptionstatedasthestartingpointfor
Part one investigation. Text identified for this code included for-
mally stated hypotheses, and more general research ques-
The study articles were saved as PDFs, and printed out, tions, goals or aims. In each case the text had to state or
readandexaminedbyhandtoextractdata.Inaddition,the imply that the idea provided the basis for the study; (2)
full Medline format information on each article was limitations were statements that described the factors that
uploaded to a Refworks database, and the data from our restrictedthegeneralizabilityofstudyfindings.Statements
analysis were recorded in customized fields. To enable hadtobeexplicitandrelatedtostudydesigntobecodedas
comparison to previous study on articles published from limitations.Hypothesisandlimitationsarestandardaspects
2001 to 2004 (Sankar et al. 2007, Shanawani et al. 2006), of scientific research articles. Inclusion of a specific
the coding and analytical framework we used was adapted hypothesis is important as this is where readers might
principallyfromSankaretal.(2007),andwithreferenceto expect to find an explanation for how identifying a study
the analysis by Shanawani et al. (2006). Sankar’s group population as a specific race, ethnicity or ancestry group
developed content codes to analyze how the research relates to the study premise or research question. A limi-
populations were described, and the main components and tations statement offers the opportunity to explain how
structureofscientificarticles.Inadditiontousingthese,we widely the findings can be applied to populations beyond
developedadditionalcodestoassesstheuseofancestry,of the study sample that might be associated with the race,
empirical genomic methods to measure ancestry, or assign ethnicity or ancestry terms used in the study. Note that
or verify membership in research populations, and the some articles were not included in the limitations analysis
discussion of ethical and social aspects in articles. An because we judged their analysis to not require such a
initial set of codes was tested by SEA, RT and TK. These qualification; and (3) sample origin was defined not as the
codesweresubjectedtoseveralroundsofconsensuscoding geographical region from which the samples were
(Jenkins et al. 2005; Sankar et al. 2007) and discussion obtained, but where and how the researchers acquired the
amongst all the authors. When interpretation and concep- tissue samples or genetic data, for example—whether they
tual issues were resolved, and the codes were deemed to were obtained from a tissue or databank, collected at a
adequatelycapturerelevantarticlefeatures,acodingguide hospital, or were already in researchers’ possession.
was generated listing coding rules, definitions and exam-
ples. The final study analysis was carried out by SEA. Reason for using populations To examine authors’
explanations for why research was conducted using race
Coding and ethnicity or ancestry terms, articles were classified
based on three features that have been recommended by
The analysis codes evaluated four main areas: (1) basic expert commentary, journals, and professional societies
article features; (2) reasons researchers gave for how and (Ali-Khan and Daar 2010; American Academy of Pediat-
why they used named populations in the study design; (3) rics: Committee on Pediatric Research 2000; American
theroleofthenamedpopulationsintheresearchdesignor Anthropological Association 2000; Bamshad et al. 2004;
the description of the research; (4) use of empirical geno- Editorial 1996; International Council of Medical Journal
mic means to assign or verify membership in the research Editors 2010; Lee et al. 2008; Race Ethnicity and Genet-
populations; and (5) discussion of social or ethical impli- ics Working Group 2005; Rivara and Finberg 2001;
cations of human genetic research. We analyzed each Winker2004),andsee,http://www.icmje.org/urm_full.pdf.
article bylookingfortextcorresponding tothese codes,or (1) Why populations was used to label text that gave
piecesofinformation,asdescribedbelowandscoredthem reasons for pursuing the research question by using a
as a yes/no variable. Additionally, for many of the codes, population so identified; (2) Why this population was used
123
HUGOJ
to code reasons provided for studying the particular group genomically, defining parameters for group exclu-
population(s) in question. Reasons could be practical sion or inclusion, this was also coded as yes.
(e.g. because the sample was available) or theoretical
(e.g. because the condition of interest was known to occur The role of named populations in genetic research To
frequently in a particular group); (3) Basis for assigning examine the various ways that articles used race and eth-
population term was defined as the method by which nicity, or ancestry, text was labelled that referred to the
membershipinthestudypopulationwasdetermined,orthe following5codes:(1)Labelforstudypopulationonlywas
population label was assigned to research participants. For applied to text where race, ethnicity, ancestry or other
example, self-reported by subjects, taken from existing populations terms were used to label the study population
records,assumedbecauseofthegeographicalregionwhere only, and not as a research variable; (2) Independent and;
subjects were recruited, or assigned based on genomic (3) Dependent were applied respectively when race, eth-
inference. If an article provided any of these means it was nicity, ancestry or other population terms were employed
coded yes. Thus, a yes/no variable and how, as qualitative asindependentordependentvariablesintheresearchbeing
data, was collected. reported; (4) DNA with label indicated where authors had
labelled DNA—for example, alleles, chromosomes, hap-
Useofgenotypingdatatoinfergeneticancestry Tobegin lotypes, or mutations—with a race, ethnicity or ancestry
to evaluate the nature and the degree to which high reso- term,asin‘MexicanandCaucasianTallele(Plaisieretal.
lution genome-wide genotyping—or genetic ancestry test- 2009) Codes (1–4) could co-occur, but codes (2) (Inde-
ing—is being used to assess the genetic background or pendent) and (3) Dependent) were mutually exclusive.
ancestry of research participants or samples, we labelled
textthatdescribedsuch methodologies.Onlystudiesusing Social and ethical implications related to human popula-
these approaches as part of their process of assigning or tion genetic research We looked for statements discuss-
verifying the membership of participants or samples to ing social or ethical implications of population-based
researchgroupings,ortoassessforpopulationstratification genetic research. Such content had to discuss implications
were coded as ‘yes’. The use of such methods to analyse arising from the genetic research being reported—e.g. text
thegeneticstructureofpopulationsasthemaingoalofthe relating to the potential for study results to stigmatize the
reported research were coded ‘no’. Both a yes/no variable research population. We coded these as a yes/no variable,
and how, as qualitative data, was collected. and if found, the issues discussed were recorded as quali-
tative data.
Definesraceand/orethnicity,orancestryterms Toassess
the degree to which authors defined and described the Categorization of articles by general field of interest We
terms and identities used to refer to research populations also categorized the articles by their general field of
we labelled text according to the following codes interest; ‘population genetics’ was defined as including
(1) Defines generic ‘race’, ‘ethnicity’ or ‘ancestry’ was population genetic and studies examining inter or intra-
applied when text explicitly defined race, ethnicity or population genetic structure, genetic anthropology, and
ancestry as a genetic, social or biological concept, or pro- whole genome sequencing articles; ‘medical’ included
vided a reference to information that did so. Further, we diseaseandpharmacogenomics-relatedarticles;‘methods’,
began to assess the comprehensiveness of research popu- reported new methodologies or analytical approaches in
lation definitions. We based our criteria on those recom- geneticresearch;and‘non-medical’wasdefinedasarticles
mended by commentators who underlined the importance reporting studies of non-medical-related phenotypes, for
of thorough, and multi-dimensional description of popu- example height or hair colour. For the purposes of this
lations (Bamshad et al. 2004, Editorial 2004b). Thus, we analysis these categories were exclusive.
applied(2)Definesspecificraceorethnicity,ancestryterm
(or population identifier) to articles only when they pro- Part two
vided all of the following information; (1) the identifier or
name of the research population; (2) the geographical Generic terminology used to refer to research popula-
location where the participants were recruited or the tions We recorded all the generic terminology used to
community where they were resident; (3) their ‘racial’, describe the research populations in each study, and the
ethnic, or geographical ancestral origin; and (4) specified specific research population names or identifiers. If an
howthislabelwasassigned(forexample,byself-report,by article referred to the research populations by ‘race’ or
genomic ancestry inference, based on multiple generations ‘ethnicity/ethnic’ anywhere in the main article body or
of the participants’ family etc.). In addition, if text, or a supplementarymaterialswecodedthearticleas‘raceand/
figure (e.g. a principal components plot) described the orethnicity’.Likewise,ifanarticlereferredtopopulations
123
HUGOJ
asancestriesorancestrygroups (butnotrace orethnicity), Part one—compliance with recommendations
it was coded ‘ancestry’. Articles using only a specific for the use and reporting of populations in genetic
population identifier such as whites, African Americans, research
Han Chinese etc., or that described populations using any
other terminology such as origin, descent, etc. were coded Basic article features
‘other’. We also recorded examples where the generic
terms ‘race and ethnicity’ were used synonymously with We were able to identify a clearly stated hypothesis or
‘ancestry’, or that used them in a conceptually distinct research questions in almost every article in our sample
fashion, and collected qualitative data regarding the use (99.4%, N = 169) (Table 2). Likewise, most papers
and application of ‘ancestry’ in articles. describedtheoriginoftheirresearchsamples.Fewerarticles
We note that for the purposes of this analysis and con- describedthelimitationsoftheirstudieswithrespecttothe
sistent with others (Sankar et al. 2007; Shanawani et al. populations investigated (52.4%, N = 87). Most of these
2006), we did not distinguish conceptually between race limitations statements were not extensive, but rather com-
andethnicity.Despitesomecommentatorsofferingdistinct prisedofasentenceinthearticlediscussionstatingthatthe
definitionsofthese(Editorial2004b;Harrison1995;Kalow studyfindingsshouldbevalidatedorfurtherinvestigatedin
2001;Wood2001),itappearsthatinpracticetheyaremost diverse populations, or in other ‘racial’, ethnic or ancestry
often used interchangeably (Condit 2007; Oppenheimer groups(seeforexample,Ganeshetal.2009).
2001; Sankar and Cho 2002). Thus, in this work, we con-
sidered them together as one category. Reason for using populations
Supplementary and additional data About two thirds of articles explained why they chose to
study labelled populations (65.9%, N = 112), or why they
Many articles provided additional supplementary infor- chose to study the particular populations featured in the
mation or methods online. These were downloaded, research (68.8%, N = 117) (Table 2). Most of these
examinedforrelevantinformation,andcodedaspartofthe explanations were based on the phenotype or condition
analysis for each article. Some referred readers to previ- under study being of high prevalence in the study popu-
ously published literature for details about research pro- lation, or the fact that this group was understudied in
cedures or the study population. These articles were also comparisontoothers,forexample‘Becauseneuroblastoma
downloaded, examined and relevant statements were used in the United States is demographically a disease of Cau-
asthebasisforassigningthecodestotheoriginalarticle.If casiansofEuropeandescent,welimitedourinitialanalyses
thesearticlesdidnotprovidetherelevantdetailsbutinturn to this racial group to minimize phenotypic variabil-
referenced another paper, we scored the article as ‘no’ for ity’(Diskin et al. 2009). A key scientific consideration in
the code in question. selecting samples for association studies is that they be
drawn from the most genetically homogeneous population
Statistical analyses possible—thus striving to avoid spurious associations
resultingfrompopulationstratification(CardonandPalmer
Aftersub-dividingthedatabythegenericterminologyused 2003; Marchini et al. 2004). However, few articles (4.7%,
torefertothestudypopulationsinarticles,asin(1)raceand/ N = 9),specificallylinkedthisnotiontotheuseoflabelled
orethnicity;(2)ancestry;and(3)other.Wethencompared populations in their study, or to the particular population
frequenciesofindividualcodesacrosstheresultingsubsets investigated. Of the articles that did not explain why they
ofthedata,assessingthesignificanceofanydifferencesvia chose to study labelled populations, all but one were
the chi-square statistic. Statistical tests were performed association studies or other analyses to identify a trait’s
usingSigmaStatstatisticalsoftware(Version3.5). geneticbasis.Inmanyofthesearticlespopulations/samples
were ostensibly used because of their availability to
researchers, although this was not explicitly stated.
Results Mostarticlesalsoprovidedsomebasisforhowthepop-
ulation label was assigned to research participants (88.2%,
Sample set characteristics N = 150).Mostindicatedthatthiswasbyself-reportedrace,
ethnicity, geographical origin or ancestry, and/or was
We reviewed and analyzed 170 research articles published determinedbasedonthegeographicalregionwherepartic-
in2008and2009reportinggeneticresearchinthecontextof ipants were recruited or resided, and/or was assigned or
human groups. Basic characteristics and categorization by verified using genomic data (see following section).
thearticles’generalfieldofinterestareshowninTable 1. Assigning population labels on the basis of more than one
123
HUGOJ
Table2 Samplesetcoding
Variablescoded N=170(%)
frequencies,N(%)
Basicfeatures
Hypothesis 169(99.4%)
Limitations 87(52.4%)
Sampleorigin 163(95.9%)
Reasonforusingpopulation
Whypopulations 112(65.9%)
Whythispopulation 117(68.8%)
Basisforassigningpopulationlabel 150(88.2%)
Useofgenotypingdatatoinfergeneticancestry 88(51.8%)
SNPgenotypesorancestryinformativemarkers(AIMs)used 20(23.3%)
toinferancestryproportionsofindividualparticipants’DNAsamples
Genotypedatausedtoassessthegenetichomogeneityofpopulationbyprincipal 36(41.9%)
componentsclusteranalysis,Samplesoutlyingfrompopulationclustersofinterest
excludedfromfurtheranalysis
Textbrieflystatesthatpotentialpopulationstratificationwasexaminedintheresearch 32(36.4%)
populations,butnofurtherdetailsareprovided
Definesgeneric‘raceandethnicity’or‘ancestry’ 0(0%)
Definesspecificpopulationlabel/describespopulationgroup 102(60.0%)
Waysofusingpopulationsinresearch
Labelforstudypopulationonly 78(45.9%)
Independentvariable 87(51.2%)
Dependentvariable 1(0.59%)
DNAwithalabel 23(13.5%)
Discussessocialandethicalimplications 0(0%)
generation of the research participants’ family has been of study populations, by principal components cluster
recommended(Tangetal.2005).However,only18articles analysis, sometimes in comparison to HapMap reference
(10.6%)inoursampledescribedusingsuchapproaches. populations. Samples outlying from population clusters of
interest were excluded from further analysis (41.9%,
Use of genotyping data to infer genetic ancestry N = 36),seeforexample,(Yamaguchi-Kabataetal.2008);
(3)textbrieflystatesthatpotentialpopulationstratification
Justoverhalfthearticles(51.8%,N = 88)describedusing was examined in the research populations, but no further
genomic data to assess the genetic ancestry of research details are provided. These articles simply state that popu-
participantstoassignorverifytheresearchgroupings,and/ lationgeneticstructurewasnotevident,orthatitwasfound
or to guard against population stratification (Cardon and andcorrected(36.4%,N = 32).Articlesfeaturingthislatter
Palmer 2003; Marchini et al. 2004) (Table 2). This is wording(3),werenotcoded‘yes’asprovidingthebasisfor
important because such approaches can substantiate the assigning the population label, because no details were
genetic similarity of individuals stratified using proxy providedastohowsampleswereincludedorexcludedfrom
methods, and provides another element to the description theresearchgroups.Likewise,suchtextwasnotcoded‘yes’,
of research populations. asconstituting agenomic description ofthe population for
Most of these determinations were described in the thesamereason(seesectionbelow).Thus,geneticancestry
methods section of articles where statistical analyses or testing was described in a variety of ways, and at varying
quality control issues were described, and fell into three levelsofdetailbyauthors.
broad categories; (1) genome-wide SNP genotypes or
ancestryinformativemarkers(AIMs)wereusedtoinferthe Defining race or ethnicity, and ancestry
ancestry proportions of individual participants’ DNA sam-
ples.Thosewhoseancestrypercentagesfellbelowaspeci- No article in our sample set specifically defined the
fied cut-off were excluded from further analysis (23.3%, meaning of the generic terms ‘race’, ‘ethnicity’ or
N = 20),seeforexample,(Trevinoetal.2009);(2)genome- ‘ancestry’ in the research reported (Table 2). This was
wideSNPdatawasusedtoassessthegenetichomogeneity surprisingtousgiventhehighpercentageofarticleswhich
123
HUGOJ
explained the basis for how they assigned the population Social and ethical implications
labelused(88.2%).Further,weexpectedthatarticlesusing
terms of race, ethnicity or ancestry to categorize their No articles mentioned or discussed social or ethical impli-
research samples, or that used groups so labelled as inde- cationsarisingfromgeneticresearchingeneral,orfromthe
pendent research variables (51.2%, see section below), researchbeingreported(Table 2).Ontheonehandthiswas
wouldalsodiscussordefinethemeaningoftheseconcepts not really surprising given that geneticists and social sci-
in the context of their study. Although no article provided entists have not traditionally collaborated, despite calls for
explicit definitions, several studies whose goal was to interdisciplinary perspectives (Ali-Khan and Daar 2010;
analyze genetic substructure in populations, did begin to Bonhametal.2005;Condit2007;Leeetal.2008;Viaetal.
outline a distinction between population identifiers/names 2009).Conversely,giventhatauthorsfrombothdisciplines
orself-identifiedethnicity,andancestry,whichwasframed have engaged these issues (Bamshad et al. 2004;Burchard
in terms of genetic background (see for example, Li et al. etal.2003;Caulfieldetal.2009;Cooperetal.2003;Duster
2008; Reich et al. 2009; Tishkoff et al. 2009). 2005;Leeetal.2008;Rotimi2004),weanticipatedfinding
Acriticalcomponentofmanyrecommendationshasbeen somediscussion,howevercursory,inarticles.
touseasspecificpopulationlabelsaspossible,tocarefully
define their meanings (Bamshad et al. 2004; Kaplan and Comparison of current data with previous studies
Bennett 2003; Sankar and Cho 2002), providing as much
informationonthepopulation‘asiscompatiblewithethical To begin to get perspective on how researchers’ reporting
review boardrequirements’(Editorial2004b).Forthe pur- haschangedoverthecourseofthepastdecade,wecompared
poseofthisstudy,weconsideredadefinitiontoinclude(1) our findings with a previous study which analyzed genetic
the name or population identity of the group; (2) the geo- researcharticlespublishedover2001–2004,andwithwhich
graphicalregionofrecruitmentorthecommunityinwhich we specifically aligned part of our study methodology and
theresearchparticipantresides;(3)theirethnicidentityand analysis (Table 3). We found marked increases in the
or/thegeographicaloriginoftheirancestors;and(3)aspe- numbersofarticlesprovidinghypothesisstatementsforthe
cific indication of how the latter was determined. To be research reported (30% in the earlier study, compared to
scoredyes,anarticleneededtoprovideallofthisinforma- 99.4%ofarticlesinourdataset,P =\0.001),andlikewise
tion. More than half the articles in our dataset defined the describing the origin of their research samples (62.4%
specific population identifier used according to these compared to 95.9%, P =\0.001). Compared to earlier in
parameters (60%, N = 102). Of these, 54.9% (N = 56) the decade, more authors described the limitations of their
included a genomic description (i.e. groups (1) and (2) researchfindingswithrespecttothe population-based data
described in the previous section). Of articles that did not reported (22.7% compared to 52.4%, P =\0.001). How-
‘define’the population, many notedthe geographical loca- ever,stillonlyabouthalfthearticlesprovidedlimitations.
tionofrecruitmentorresidence,and/ortherace/ethnicity,or There were substantial increases in the proportion of
ancestryofparticipantsorsamples,butnothowtheselatter articles(1)explainingwhysamples/participantsinthestudy
categorizations were determined. For example, they might weregroupedbyraceandethnicity,orancestrylabels(10.9%
state that ‘all subjects were of full Japanese ancestry’ compared to 66.5%, P =\0.001); and (2) justifying why
(Yasuda et al. 2008), but not explain precisely what this these particular population groups were studied (11.2%
meantincontext,orhowitwasdetermined. comparedto68.2%,P =\0.001).Incontrast,therewasno
changeovertimeinarticlesdefiningthegenericterms‘race’,
Ways of using labelled populations in genetic research ‘ethnicity’, or ‘ancestry’ in the context of their study—no
articles in either dataset defined these terms. This was sur-
Abouthalfofthearticles(51.7%,N = 88)usedthenamed prising given the intensification of population studies using
populations as either dependent or independent variables thesetermsinthelast10 years,andthecontinuedscrutinyof
(Table 2). The remainder used population identifiers only measurement, communication and identity issues over this
tolabeltheirstudypopulations,butnottotestahypothesis time(Caulfieldetal.2009;Clayton2002;FosterandSharp
related to the named group. A number of papers (13.5%, 2004; Lee et al. 2008; Rotimi 2004). It also suggests that
N = 23) labelled DNA by population. In most of these researchersconsiderthemeaningsofthesetermsself-evident.
cases the population identifier was used to label the infer-
red ancestral identity of DNA sections in admixture map- Part two: cross-comparison of articles using different
ping or similar studies, see for example (Hancock et al. terminologies—race and ethnicity, ancestry or other
2009).Afewarticlesusedwordingsuchas‘ethnic-specific
locus’ (Lei et al. 2009) or an ‘Asian mitochondrial DNA We recorded the generic terminology used to refer to
haplotype’ (Keyser et al. 2009). research populations in each article. Most described the
123
HUGOJ
Table3 Comparisonofcurrentdatawithearlierstudy
Sankaretal.(2007) Currentstudy
Dataderivedfrom 2001–2004 2008–2009
articlesfrom
publicationyears
#Articles 330 170
Sampleselection Medlinesearchstrategy:raceandethnicity,geneticsand Pubmedsearchstrategy:(raceORethnicityORancestry)
criteria populationkeywords;ANDpublicationinoneof3 AND(SNPORpolymorphismORCNV)keywords;
journaltypesamples(genetics,clinical,andgeneral); ANDpublicationinoneofsixleadingjournalsforthe
mainlyhighimpactjournals publicationofhumangeneticresearch;mainlyhigh
impactjournals
Variablescoded
Basicfeatures Pvaluebychisq
Hypothesis 99(30%) 169(99.4%) \0.001*
Limitations 75(22.70%) 87(52.4%) \0.001*
Sampleorigin 206(62.40%) 163(95.9%) \0.001*
Reasonforusingpopulations
Whypopulations 36(10.90%) 113(66.5%) \0.001*
Whythispopulation 37(11.20%) 116(68.2%) \0.001*
Definesgeneric‘raceandethnicity’or‘ancestry’ 0% 0% N/A
Waysofusingpopulationsinresearch
Labelforstudypopulationonly 76(23%) 82(48.2%) \0.001*
Independentvariable 154(46.70%) 87(51.2%) 0.389
Dependentvariable 16(4.80%) 1(0.59%) 0.026*
DNAwithalabel 35(10.60%) 23(13.5%) 0.412
*Indicatesstatisticallysignificantdifference,P\0.05
studiedpopulationsasracesorethnicities(N = 80,47.1%) To assess potential differences in the way researchers
(Table 4).Forexample,‘The67populationsanalyzedinthis use ‘race and/or ethnicity’, compared to ‘ancestry’ or
study represent 41 ethnic nationalities living in China and ‘other’ kinds of terminology to describe research popula-
other eastern Asian regions’ (Shi et al. 2009), and ‘All tions or samples, we sub-divided our data by the generic
geneticassociationanalyseswerestratifiedbyself-identified terminology used, and analyzed the frequency of our
race (white vs. African American)…’(Rasmussen-Torvik researchcodesandcategorizationsacrossthesesub-groups
etal.2009).Only4articles(2.4%)usedraceonlyasater- (Table 4). For the basic article features, there was no sig-
minology,therestused‘race/ethnicity’,orethnicityonly,to nificant difference between terminology sub-groups.
describepopulations. ‘Ancestry’or‘ancestry groups’were However, articles using race and/or ethnicity were signif-
usedin22.4%ofarticles(N = 38),forexample,‘Riskallele icantly more likely to provide a justification for why the
frequenciesofrs12970134arehigheramongindividualsof research studied populations so labeled (75.0%, N = 60)
Indian Asian ancestry than those of European ancestry’ comparedtothoseusingancestry(44.7%,N = 17)orother
(Chambersetal.2008).Theremainderofarticlesreferredto terminology (69.2%, N = 36) (P = 0.004). Articles using
populationsonlybyaspecificpopulationidentifierorname race and/or ethnicity were also significantly more likely to
suchas‘EuropeanAmerican’,‘Hadza’or‘Japanese’,orby report medical-related research (P =\0.001). Consistent
using various descriptors—most often origin, descent and with these findings, during our analysis we noted that
derived, for example ‘this difference is maintained in medical–related articles often investigated health dispari-
American childrenof Japanese descentresident inthe US’ ties between groups framed in terms of race or ethnicity,
(Burgneretal.2009)(seeTable 5foralistoftermsandways and rationalized the study of their research populations on
of describing populations compiled from our sample set). this basis. On the other hand, articles using ancestry were
We cannot comment on how the relative use of these ter- less likely to provide a justification for the use of this
minologies has changed over time, as previous studies did terminology to label populations, or why particular popu-
notexaminethisparameter. lations were studied (Table 4).
123
HUGOJ
Table4 Presenceofcodedarticlefeaturesbygenericterminologyused
Totalsampleset,N=170 Raceandethnicity Ancestry OtherN=52 Pvalue
N=80(47.1%) N=38(22.4%) (30.6%) bychisq
Variablescoded
Basicfeatures
Hypothesis 79(98.8%) 38(100%) 52(100%) 0.568
Limitations 43(55.1%) 16(45.7%) 28(53.8%) 0.319
Sampleorigin 75(93.8%) 37(97.4%) 51(98.1%) 0.413
Reasonforusingpopulation
Whypopulations 60(75.0%) 17(44.7%) 36(69.2%) 0.004*
Whythispopulation 55(68.8%) 23(60.5%) 38(73.1%) 0.372
Basisforassigningpopulationlabel 71(88.8%) 35(92.1%) 44(84.6%) 0.542
Useofempiricalgenomicmethods 44(55.0%) 25(65.8%) 19(36.5%) 0.017*
Definesgeneric‘raceandethnicity’or‘ancestry’ 0(0%) 0(0%) 0(0%)
Definesspecificpopulationlabel 51(63.8%) 24(63.2%) 27(51.9%) 0.361
Waysofusingpopulationsinresearch
Labelforstudypopulationonly 34(43.0%) 21(56.8%) 27(51.9%) 0.352
Independentvariable 46(58.2%) 17(45.9%) 24(46.2%) 0.296
Dependentvariable 0(0%) 0(0%) 1(1.9%) 0.319
DNAwithalabel 14(17.5%) 3(7.9%) 6(11.5%) 0.319
Generalarticlefieldofinterest
Populationgenetics 10(12.5%) 1(2.6%) 15(28.8%) 0.002*
Medical 68(85%) 32(84.2%) 27(51.9%) \0.001*
Methods 1(1.3%) 2(5.3%) 6(11.5%) 0.036*
Non-medical 1(1.3%) 3(7.9%) 4(7.7%) 0.134
Pvaluebychisqforterminology \0.001* \0.001* \0.001*
usedwithinfieldofinterest
*Indicatesstatisticallysignificantdifference,P\0.05
Finally,wehypothesizedthatarticlesusing‘ancestry’to residence or self-identified ethnicity to assign group
label populations would be more likely to use genotyping membership. Conversely, case–control studies aiming to
data to assess the genetic background of their research identify new genetic variants and striving to minimize
groups, in order to assign the population label. Indeed, population stratification, most often analyzed genotyping
there was a significant relationship between the use of data or inferred genetic ancestry to stratify samples.
‘ancestry’ and of empirical genomic methods (65.8%),
compared to‘race andethnicity’ (55.0%), orarticles using Uses of ancestry in our sample set
‘other’ ways of referring to their research populations or
samples(36.5%)(P = 0.017)(Table 4).Theimportanceof Tofurtherunderstandhow‘ancestry’isbeingbyemployed
controlling for population stratification through the inresearchpractice,wecataloguedhowthetermwasused
assessment of genetic ancestry has been a key consider- by authors in articles. We found the terms ‘ancestry’ or
ation in the context of genetic association studies (Cardon ‘ancestry group’ were used in three main ways. Most
and Palmer 2003; Marchini et al. 2004). Consistent with commonly, they were used, as described above, to refer to
this, medical (53.3%) and non-medical-related articles the geographical origin of populations, for example ‘indi-
(62.5%) in our sample set—of which 41.5% and 50.0%, viduals of European ancestry’, or the line of heritage or
respectively reported genome-wide association studies— descent of a group, for example, ‘Ashkenazi Jewish
were more likely to use genomic methods, while popula- ancestry’ (Bronstein et al. 2008). In particular, ancestry
tion-related articles were less likely to (23.1%) was often used to describe populations/individuals for
(P = 0.006) (Table 6). Again this was consistent with our whom the geographic origin of their predecessors is dif-
observations that population genetics type articles—which ferent from their current place of residence (for example
often mapped genetic substructure across populations— African Americans, or European Americans). ‘Ancestry’,
mostlyreliedonlanguage-spoken,geographicallocationof ‘geographicancestry’or‘biogeographicancestry’wasalso
123