Genetic Heterogeneity of Self-Reported Ancestry Groups in an Admixed Brazilian Population

Abstract

Population stratification is the main source of spurious results and poor reproducibility in genetic association findings. Population heterogeneity can be controlled for by grouping individuals in ethnic clusters; however, in admixed populations, there is evidence that such proxies do not provide efficient stratification control. The aim of this study was to evaluate the relation of self-reported with genetic ancestry and the statistical risk of grouping an admixed sample based on self-reported ancestry.
A questionnaire that included an item on self-reported ancestry was completed by 189 female volunteers from an admixed Brazilian population. Individual genetic ancestry was then determined by genotyping ancestry informative markers.
Self-reported ancestry was classified as white, intermediate, and black. The mean difference among self-reported groups was significant for European and African, but not Amerindian, genetic ancestry. Pairwise fixation index analysis revealed a significant difference among groups. However, the increase in the chance of type 1 error was estimated to be 14%.
Self-reporting of ancestry was not an appropriate methodology to cluster groups in a Brazilian population, due to high variance at the individual level. Ancestry informative markers are more useful for quantitative measurement of biological ancestry.

Full text

Original Article
Genetic Heterogeneity of Self-Reported Ancestry Groups
in an Admixed Brazilian Population
Tulio C Lins1,*, Rodrigo G Vieira1,*, Breno S Abreu1, Paulo Gentil2,
Ricardo Moreno-Lima2, Ricardo J Oliveira2, and Rinaldo W Pereira1,2
1Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília, Brasília, DF, Brazil
2Programa de Pós-Graduação em Educação Física, Universidade Católica de Brasília, Taguatinga, DF, Brazil
Received November 4, 2010; accepted January 28, 2011; released online April 16, 2011
ABSTRACT
Background: Population stratification is the main source of spurious results and poor reproducibility in genetic
association findings. Population heterogeneity can be controlled for by grouping individuals in ethnic clusters;
however, in admixed populations, there is evidence that such proxies do not provide efficient stratification control.
The aim of this study was to evaluate the relation of self-reported with genetic ancestry and the statistical risk of
grouping an admixed sample based on self-reported ancestry.
Methods: A questionnaire that included an item on self-reported ancestry was completed by 189 female volunteers
from an admixed Brazilian population. Individual genetic ancestry was then determined by genotyping ancestry
informative markers.
Results: Self-reported ancestry was classified as white, intermediate, and black. The mean difference among self-
reported groups was significant for European and African, but not Amerindian, genetic ancestry. Pairwise fixation
index analysis revealed a significant difference among groups. However, the increase in the chance of type 1 error
was estimated to be 14%.
Conclusions: Self-reporting of ancestry was not an appropriate methodology to cluster groups in a Brazilian
population, due to high variance at the individual level. Ancestry informative markers are more useful for quantitative
measurement of biological ancestry.
Key words: ethnicity; population structure; ancestry; admixture
INTRODUCTION
The genetic structure of human populations is relevant in
epidemiologic studies and can be used as a tool for collecting
parental ancestry information in an admixed population.
Although the biogeography of some groups is culturally and
genetically fixed, other groups have experienced substantial
recent admixture with ancestors from widely divergent
regions. That is the case in the Brazilian population, which
is genetically characterized by differing degrees of admixture
of 3 parental populations (European, African, and Native
American).1,2
The debate on how genetic studies should be controlled
for population stratification has encompassed several
methodologies, including self-reported ethnicity and genetic
ancestry markers.3–8Self-reported ancestry has been described
as a method that is highly correlated with genetic population
structure in well defined, stratified ethnic groups, such as
Europeans, Africans, and Asians.7–9However, in cases of
admixed populations, both self-reported ancestry and anthro-
pometric traits used as proxies, such as skin pigmentation, are
believed to be unreliable methods of determining ancestry,3–5,8
which suggests that molecular markers based on genetic
clustering should be used to reduce the potential inaccuracies
of population stratification.3,6,10
Many association studies have classified ethnic groups by
means of subjective assessment by the interviewer, evaluation
of anthropometric traits, genealogical examination, and self-
reported ancestry.11–15 However, the recent use of molecular
markers to determine genetic ancestry has revealed wide
genetic heterogeneity in admixed Brazilians.5,16–22 One
problem in performing association studies of admixed popu-
lations that are assessed solely by self-reported ancestry as a
proxy of ethnic group is the possibility of spurious association
Address for correspondence. Rinaldo Wellerson Pereira, Programa de Pós-Graduação em Ciências Genômicas e Biotecnologia, Universidade Católica de Brasília,
Brasília, DF, Brazil, SGAN 916 Módulo B, “Bloco C”2°Andar, Sala S-220 –Brasília –DF, Brazil, CEP 70790-160 (e-mail: rinaldo.pereira@catolica.edu.br).
*These authors contributed equally to this work.
Copyright © 2011 by the Japan Epidemiological Association
J Epidemiol 2011
doi:10.2188/jea.JE20100164
Advance Publication by J-STAGEAdvance Publication by J-STAGE
JE20100164-1

with false-positive or false-negative results.5–7,23–26 Thus, the
aim of this study was to evaluate the relation of self-reported
with genetic ancestry and the statistical risk of grouping an
admixed sample by using self-reported ancestry.
METHODS
Population sample
Samples were obtained from 189 postmenopausal women
(age, 67.77 ± 5.22 years) who had volunteered as part of a
healthcare program developed by the Universidade Católica
de Brasília, located in the Center-West Region of Brazil
(Taguatinga, DF, Brazil). The volunteers answered a lifestyle
questionnaire that included a multiple-choice question on self-
reported ancestry, based on the method used by the Brazilian
Institute of Geography and Statistics (IBGE) national census
survey.27 All sampled individuals signed an informed consent
form, and the research protocol was approved by the
University Ethical Committee.
Assessment of individual genetic ancestry
For assessment of individual genetic ancestry, we selected 13
Ancestry Informative Markers (AIMs) that have differential
allele frequencies among European, African, and Amerindian
parental populations28–30 (Table 1). The potential infor-
mativeness of most of these SNPs was evaluated in a
Brazilian population sample,21 and a modified method was
applied to the use of the current markers. Briefly, genotypic
data were obtained by optimized PCR to coamplify DNA
fragments in 2 multiplex panels of ancestry informative
markers. Later, the PCR-amplified products were purified
in an enzymatic treatment with exonuclease I (ExoI) and
shrimp alkaline phosphatase (SAP) enzymes to eliminate
nonincorporated dNTPs and primers. Finally, the
minisequencing reaction was performed using the SNaPshot
Multiplex minisequencing kit reaction mix (Applied
Biosystems, Foster City, USA), and the products were
analyzed on the ABI 3130 XL Genetic Analyzer (Applied
Biosystems) in an ABI 3700 POP-6 polymer. Genotypes
were called using GeneScan Analysis Software, version 3.7
(Applied Biosystems) and Genotyper version 3.7 (Applied
Biosystems). The detailed optimized multiplex single-base
extension protocol, with reactant concentration and PCR
thermocycling conditions, has been reported elsewhere.21,31–33
Statistical analysis
Allelic frequencies were obtained by direct counting, along
with pairwise population Fixation index (FST) analysis, which
was performed using GenAlex software.34 The FST measures
population differentiation based on the heterozygosity of
genetic polymorphism data is calculated using the formula,
FST =(H
T−HS)×H
T
−1, where HTis the expected hetero-
zygosity in the total population and HSis the observed
heterozygosity in a subpopulation.35 The fixation index
can range from 0.0 (no differentiation) to 1.0 (complete
differentiation) and theoretically varies from little (0.0 to 0.05)
to moderate (0.05 to 0.15), great (0.15 to 0.25), or very great
genetic differentiation (>0.25).
Estimation of individual genomic ancestry was performed
using an algorithm based on maximum likelihood estimation
(MLE). Briefly, the log likelihood function is maximized
for the admixture parameter of up to 3 parental populations
using a priori known allele frequencies and estimates the
individual ancestry probability from a predetermined number
of analyzed genotypes of an admixed individual. The
MLE approach was implemented in the software program
IAE3CI; the detailed statistics have been described
elsewhere.36,37
Basic descriptive statistics and 1-way analysis of variance
(ANOVA) with the post-hoc Games-Howell test to adjust for
unequal variances were used to determine the relation between
genetic ancestry distribution and self-reported ancestry
groups. A Pvalue of 0.05 or lower was considered
statistically significant. Statistical analysis was performed
using SPSS software version 13 (SPSS Inc., Chicago, IL,
USA).
Table 1. Allelic frequencies and information on 13 ancestry informative markers for parental populations and studied samples
Locusref Position Allele EUR AMR AFR White Intermediate Black
CRH (rs3176921)30 8q13.1 G 0.073 0.017 0.682 0.435 0.395 0.767
CYP3A4 (rs2740574)29 7q22.1 G 0.958 0.959 0.198 0.485 0.654 0.771
FyNull (rs2814778)30 1q23.2 C 0.002 0.000 0.999 0.101 0.237 0.548
LPL (rs285)30 8p21.3 G 0.508 0.558 0.029 0.519 0.513 0.226
OCA2 (rs1800404)30 15q13.1 G 0.254 0.552 0.885 0.370 0.528 0.717
rs112903830 15q13 C 0.224 0.983 0.995 0.671 0.808 0.871
rs142665430 15q21 C 0.010 0.930 0.970 0.096 0.276 0.758
rs148064230 6q23 C 0.994 0.621 0.106 0.788 0.679 0.435
AT3 (rs3138521)28 1q25 Insertion 0.282 0.061 0.858 0.354 0.304 0.597
rs73655630 7p15 C 0.244 0.018 0.939 0.242 0.313 0.519
rs376864130 2p13 G 0.923 1.000 0.010 0.715 0.725 0.577
rs187153430 5p15.2 G 0.019 0.000 0.960 0.029 0.049 0.250
rs476680730 12q24.2 A 0.622 0.948 0.030 0.559 0.542 0.429
European (EUR), African (AFR) and Native American (AMR).
Genetic Heterogeneity of Self-Reported Ancestry Groups2
J Epidemiol 2011

RESULTS
A total of 192 participants completed the study, but only 3
were of self-reported Amerindian ancestry. Due to the lack
of statistical power, these 3 women were not considered in
the analysis, and 189 participants remained for study, as
previously described. The questionnaire responses indicated
that the sampled population had similar prevalences (41.8%)
for 2 groups, white and intermediate (ie, any sort of
admixture). Blacks represented 16.4% of the sample. No
individual reported Asian descent in the present research.
Allelic frequency for the 13 genotyped SNPs is described
in Table 1, along with the frequencies of the parental
populations. Using Wright’s scale of genetic differentiation,
FST analysis revealed little difference between the white and
intermediate groups (FST = 0.022), a moderate difference
between the intermediate and black groups (FST = 0.138),
and great differentiation between the black and white groups
(FST = 0.225); all P-values were significant.
The genetic ancestry of each self-reported ancestry category
and the total sample was estimated (Table 2). The range of
individual ancestry for the 3 parental genomes within each
self-reported ancestry category is depicted in a box plot
(Figure). The 3 self-reported categories had overlapping
ranges for each parental ancestry. For example, with regard
to European ancestry, there were individuals in all 3 self-
reported categories within the range of 0.41 to 0.78 for the
ancestry proportion. For African ancestry, this overlap ranged
from 0.19 to 0.48, and for Amerindian ancestry the range was
from 0 to 0.42 (Figure). For instance, an individual in the
black group had 78% European ancestry and 22% African
ancestry (sample 181; Figure).
One-way ANOVA for comparison of means in conjunction
with the Games-Howell post-hoc test revealed significant mean
Table 2. Genetic ancestry estimates among self-reported ancestry groups, by skin color
Self-reported ancestry
European African Amerindian
AV±SD VAR AV±SD VAR AV±SD VAR
White (n= 79) 0.738 ± 0.135 0.018 0.172 ± 0.134 0.018 0.090 ± 0.120 0.014
Intermediate (n= 79) 0.615 ± 0.140 0.020 0.256 ± 0.142 0.020 0.129 ± 0.168 0.029
Black (n= 31) 0.387 ± 0.164 0.027 0.472 ± 0.158 0.025 0.141 ± 0.189 0.035
Total (n= 189) 0.629 ± 0.187 0.035 0.254 ± 0.174 0.031 0.117 ± 0.155 0.024
Average values (AV), standard deviations (SD), and variance (VAR).
BlackIntermediateWhite
Self-reported ancestry groups
1.0
0.8
0.6
0.4
0.2
0.0
178
165
97
181
180
97
AMR
AFR
EUR
Genetic ancestry proportions
Figure. Boxplot of genetic ancestry estimates of European (EUR), African (AFR), and Amerindian (AMR) proportions
among the 3 self-reported groups. *outliers.
Lins TC, et al. 3
J Epidemiol 2011

differences among self-reported groups for European and
African ancestries, but not for Amerindian ancestry (Table 3).
Although significant, the confidence interval showed that, for
European and African ancestries, the average range of the
boundary limits was 0.14, which indicates that the probability
of spurious findings (type 1 error) arising simply by chance
was 14% higher; the usual result is 5% (P= 0.05).
DISCUSSION
The Federal District is a modern urban center and the capitol
of Brazil. It has a population of migrants from several regions
of Brazil. The 2007 National Household Sample Survey
reported a distribution of self-reported ancestry in the Federal
District that was very similar to that of the present study,
differing only in the prevalence of blacks.27 The inferred
ancestry estimated here is comparable to those of other
published studies of the Center-West Brazilian population,17,21
with only slight differences in European and African ancestry
proportions, which were probably due to sampling issues.
In this study, the statistical power of the 13 AIM panel
might have been insufficient to accurately assess ancestry in
an admixed population.38 However, when the population
ancestry estimates, standard deviations, and variances of the
present study were compared with those of a different sample
of Center-West Brazil that was assessed using a set of 28
ancestry markers,21 the values did not statistically differ
between samples (P= 0.49), especially with regard to
individuals of Amerindian ancestry (0.118 ± 0.149, variance
0.022, in the earlier sample).21
Allelic frequency and F-statistic estimates significantly
differed among groups. It is noteworthy that the differences in
allelic frequencies between the corresponding ancestry-related
populations (ie, European versus white Brazilians and African
versus black Brazilians) were remarkably divergent. This was
the case for CYP3A4 in EUR-white (δ= 0.473) and for
rs1871534 in AFR-black (δ= 0.710), which highlights the
admixture among these groups. The proportions of genetic
ancestries in the intermediate group were similar to those
of the total sample and differed only in variance. Therefore,
the range amplitude and variance of ancestry at an individual
level were too large for self-reported ancestry to be considered
a suitable proxy for homogenic clustering, although the
differences in their means were statistically significant.
In addition, we observed an overlap in the range of genetic
ancestry values among groups, which suggests that individuals
with the same proportions of admixture could include
themselves in any ethnic category. The confidence interval
revealed that the risk of this occurring simply by chance was
14%, considering the European and African ancestry
estimates. It is worth mentioning that the group self-reported
as black had a proportion of non-African ancestry exceeding
53%. In previous studies of the Brazilian population, African
ancestry did not exceed non-African ancestry, but a large
proportion was observed in a sample of the rural community of
the Southeastern Brazilian state of Minas Gerais (48% non-
African ancestry)5and in an urban population sample from Rio
de Janeiro (49% non-African ancestry).39 The intermediate
group described here had estimates closer to those of the white
group, as was the case for the urban population of Rio de
Janeiro.39 Alternatively, in a study of a sample from a rural
community,5the intermediate group was closer to blacks,
revealing an important issue, namely, that groups with equal
self-reported proportions can have different genetic ancestry
Table 3. Comparisons of genetic ancestry among groups, by self-reported skin color. The mean difference was considered
significant at P≤0.05
Dependent
variable (i) Group (j) Group Mean difference
(i −j) Standard error P-value
95% Confidence interval
Lower bound Upper bound
EUR
White Intermediate 0.122 0.022 <0.001 0.070 0.174
Black 0.351 0.033 <0.001 0.271 0.432
Intermediate White −0.122 0.022 <0.001 −0.174 −0.070
Black 0.229 0.034 <0.001 0.148 0.310
Black White −0.351 0.033 <0.001 −0.432 −0.271
Intermediate −0.229 0.034 <0.001 −0.310 −0.148
AFR
White Intermediate −0.078 0.022 0.001 −0.130 −0.026
Black −0.300 0.032 <0.001 −0.377 −0.222
Intermediate White 0.078 0.022 0.001 0.026 0.130
Black −0.221 0.033 <0.001 −0.300 −0.143
Black White 0.300 0.032 <0.001 0.222 0.377
Intermediate 0.221 0.033 <0.001 0.143 0.300
AMR
White Intermediate −0.041 0.023 0.187 −0.097 0.014
Black −0.051 0.037 0.349 −0.141 0.038
Intermediate White 0.041 0.023 0.187 −0.014 0.097
Black −0.010 0.039 0.964 −0.105 0.084
Black White 0.051 0.037 0.349 −0.038 0.141
Intermediate 0.010 0.039 0.964 −0.084 0.105
European (EUR), African (AFR), and Native American (AMR) proportions.
Genetic Heterogeneity of Self-Reported Ancestry Groups4
J Epidemiol 2011

profiles, especially if the samples are from communities with
different levels of urbanization. Those features were also
demonstrated in other Brazilian population samples that
assessed ancestry by using maternal (mtDNA) and paternal
(Y-chromosome) molecular markers.20,22,40
A related study of Puerto Ricans who self-classified
ancestry/color groups found statistically significant
differences in genetic ancestry among 3 groups (blanco,
trigueño, and negro).41 The results of that study can be
compared with the categories in the present study. An
overlapping range in ancestry estimates was also reported,
in which the distribution of African ancestry overlapped
across 12% for all 3 color categories (range of ancestry
estimates: 0.27–0.35). In the present sample, this range was
considerably higher (0.19–0.48), which encompassed 48% of
the sample. For European ancestry, the overlap accounted for
63% of the sample in a range between 0.41–0.78, while for
Amerindian ancestry, 95% of individuals were in the
overlapping range (0.0–0.42) for all 3 categories.
The reliability of self-classification can be poor, even
among a proband and siblings,4in which the family history
would be assumed to be more reliable. In the same way,
interviewers might misclassify an individual for whom they
do not know the ancestral family history. Indeed, different
interviewers have classified the same individual into different
groups.23,42 These examples illustrate how self-identified
ethnicity might not be sufficiently accurate for use in
biomedical research, as it is primarily a sociocultural
construct.42 Considerable variation exists because ethnicity
is essentially constructed under social circumstances
that consider many cultural traditions.1,42,43 In admixed
populations, individuals might feel that they belong to a
certain ethnic group for cultural reasons or beliefs; however,
their genealogy might consist of an unknown admixture.1,2
Although our sample comprised only women, we did not
evaluate such effects on self-declared ancestry, as it may
have more sociological than biological meaning.42,43 From a
sociological and anthropological point, a person’s biological
ancestry might have no relationship to their self-identification
with a cultural group, but such ancestry might be of great
importance in clinical research.
In conclusion, determination of ethnicity based on self-
reported ancestry is vulnerable to misclassification and should
be avoided in scientific research. Therefore, the concept of
ethnic group and self-declared ancestry are not synonymous in
biomedical research and must be replaced with scientific
measurements that have biological meaning, such as
individual ancestry estimated by DNA markers.5,24,44 Several
strategies can be effective in controlling heterogeneity
equivalence. For example, individual ancestry estimates can
be used to match admixed case-control groups.45 They can
also be used in cross-sectional studies as covariates to adjust
for a population stratification effect.24,31,33 The use of ancestry
informative markers to estimate individual ancestry is an
effective and reliable solution to correct the effects of
heterogeneity.
ACKNOWLEDGMENTS
This work was supported by the National Council for Scientific
and Technological Development (CNPq), the Brazilian
National Graduate Committee (CAPES), and Pro-Dean of
Graduate Research of the Universidade Católica de Brasília
(UCB-PRPGP). We are thankful to all who directly or indirectly
collaborated in this work, in particular the project volunteers.
Conflicts of interest: None declared.
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