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

  • Faculdade de Ciências e Educação Sena Aires

Abstract and Figures

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.
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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
Background: Population stratication is the main source of spurious results and poor reproducibility in genetic
association ndings. 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 efcient stratication 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 classied as white, intermediate, and black. The mean difference among self-
reported groups was signicant for European and African, but not Amerindian, genetic ancestry. Pairwise xation
index analysis revealed a signicant 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
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 xed, 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
The debate on how genetic studies should be controlled
for population stratication has encompassed several
methodologies, including self-reported ethnicity and genetic
ancestry markers.38Self-reported ancestry has been described
as a method that is highly correlated with genetic population
structure in well dened, stratied ethnic groups, such as
Europeans, Africans, and Asians.79However, 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,35,8
which suggests that molecular markers based on genetic
clustering should be used to reduce the potential inaccuracies
of population stratication.3,6,10
Many association studies have classied ethnic groups by
means of subjective assessment by the interviewer, evaluation
of anthropometric traits, genealogical examination, and self-
reported ancestry.1115 However, the recent use of molecular
markers to determine genetic ancestry has revealed wide
genetic heterogeneity in admixed Brazilians.5,1622 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 C2°Andar, Sala S-220 Brasília DF, Brazil, CEP 70790-160 (e-mail:
*These authors contributed equally to this work.
Copyright © 2011 by the Japan Epidemiological Association
J Epidemiol 2011
Advance Publication by J-STAGEAdvance Publication by J-STAGE
with false-positive or false-negative results.57,2326 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.
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 populations2830 (Table 1). The potential infor-
mativeness of most of these SNPs was evaluated in a
Brazilian population sample,21 and a modied method was
applied to the use of the current markers. Briey, genotypic
data were obtained by optimized PCR to coamplify DNA
fragments in 2 multiplex panels of ancestry informative
markers. Later, the PCR-amplied products were puried
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.21,3133
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,
1, where HTis the expected hetero-
zygosity in the total population and HSis the observed
heterozygosity in a subpopulation.35 The xation 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). Briey, 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
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 signicant. Statistical analysis was performed
using SPSS software version 13 (SPSS Inc., Chicago, IL,
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
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 Wrights 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 signicant.
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 signicant mean
Table 2. Genetic ancestry estimates among self-reported ancestry groups, by skin color
Self-reported ancestry
European African Amerindian
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).
Self-reported ancestry groups
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 signicant, the condence 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 ndings (type 1 error) arising simply by chance
was 14% higher; the usual result is 5% (P= 0.05).
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 insufcient 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 signicantly
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 signicant.
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 condence 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
signicant at P0.05
variable (i) Group (j) Group Mean difference
(i j) Standard error P-value
95% Condence interval
Lower bound Upper bound
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
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
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
proles, 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-classied
ancestry/color groups found statistically signicant
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: 0.270.35). In the present sample, this range was
considerably higher (0.190.48), which encompassed 48% of
the sample. For European ancestry, the overlap accounted for
63% of the sample in a range between 0.410.78, while for
Amerindian ancestry, 95% of individuals were in the
overlapping range (0.00.42) for all 3 categories.
The reliability of self-classication 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 classied the same individual into different
groups.23,42 These examples illustrate how self-identied
ethnicity might not be sufciently 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 persons biological
ancestry might have no relationship to their self-identication
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 misclassication and should
be avoided in scientic research. Therefore, the concept of
ethnic group and self-declared ancestry are not synonymous in
biomedical research and must be replaced with scientic
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 stratication 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
This work was supported by the National Council for Scientic
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.
Conicts of interest: None declared.
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Genetic Heterogeneity of Self-Reported Ancestry Groups6
J Epidemiol 2011
... In addition, each region of Brazil experienced colonization from different nations and this is reflected in the ethnical differences between these populations [10]. Recent studies have shown a weak correlation between skin color and self-declared ethnicity with genetic ancestry determined by DNA markers [11] [12]. ...
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Background: HPV infection represents an important etiologic factor for Oropharyngeal Squamous Cell Carcinoma (OPSCC). The different ethnic backgrounds could be related to different susceptibility to Human Papilloma-virus (HPV). The aim of our study was to assess the whole of genetic ancestry in HPV status in OPSCC patients. Methods: We conducted a cross-sectional study on patients with OPSCC admitted to the Barretos Cancer Hospital, Brazil from 2014 to 2019. Of these, DNA extraction was performed on 40 patients and genetic ancestry was assessed using a specific panel of 46 informative ancestry markers. Results: We observed a predominance of European ancestry (63%), followed by African (18%), Amerindian (9%) and Asian (8%) both in the OPSCC HPV-positive and HPV-negative group. We did not find any statistically significant differences between the HPV-positive and HPV-negative OPSCC groups in relation to European (p = 0.499), African (p = 0.448), Asian (p = 0.275) or Amerindian (p = 0.836) ancestry. Conclusions: We found a predominance of European ancestry, both in the HPV-positive and HPV-negative groups. In our study, we did not find statistically significant differences between HPV-positive or HPV-negative groups in relation to ancestry.
... Several studies had showed that Latin-American self-reported as whites present variable levels of African and/or Native American genetic ancestry. For example, in a female population from Brasilia, the percentage of African ancestry in self-reported whites was 17.2% (Lins et al., 2011). Another explanation may be that the Campinas population self-reported as white presents a greater European contribution from populations with higher α-thalassemia frequencies, as South-Italians (Weatherall and Clegg, 2001). ...
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Alpha thalassemia is the most common genetic disorder across the world, being the α-3.7 deletion the most frequent mutation. In order to analyze the spectrum and origin of alpha thalassemia mutations in Uruguay, we obtained a sample of 168 unrelated outpatients with normal hemoglobin levels with microcytosis and hypochromia from two cities: Montevideo and Salto. The presence of α-thalassemia mutations was investigated by gap-PCR, restriction endonucleases analysis and HBA2 and HBA1 genes sequencing, whereas the alpha-MRE haplotypes were investigated by sequencing. We found 55 individuals (32.7%) with α-thalassemia mutations, 51(30.4%) carrying the -α3.7 deletion, one with the -α4.2 deletion and three having the rare punctual mutation HBA2:c.-59C>T. Regarding alpha-MRE analysis, we observed a significant higher frequency of haplotype D, characteristic of African populations, in the sample with the -α3.7 deletion. These results show that α-thalassemia mutations are an important determinant of microcytosis and hypochromia in Uruguayan patients with microcytosis and hypochromia without anemia, mainly due to the -α3.7 deletion. The alpha-MRE haplotypes and the α-thalassemia mutations spectrum suggest a predominant, but not exclusive, African origin of these mutations in Uruguay.
... Furthermore, eight countries out of the 22 propose a separate category for 'explicitly' admixed individuals of African descent ('Mulata/o', 'Creole' or 'Mixed'), two countries have a separate 'Brown' category, and three countries gather some or all these labels under the broader 'Afro-descendant' category. In this complex categorization patchwork, population geneticists showed that self-perception of ancestry and self-reported identities overlapping national census categories are often at odds with individuals' genomic ancestries and admixture patterns (47)(48)(49). This is due to the fact that self-constructed cultural identities emerge from multiple familial and societal experiences superimposing self-perceived phenotypic features. ...
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During the Trans-Atlantic Slave Trade (TAST), around twelve million Africans were enslaved and forcibly moved from Africa to the Americas and Europe, durably influencing the genetic and cultural landscape of a large part of humanity since the 15th century. Following historians, archaeologists, and anthropologists, population geneticists have, since the 1950’s mainly, extensively investigated the genetic diversity of populations on both sides of the Atlantic. These studies shed new lights into the largely unknown genetic origins of numerous enslaved-African descendant communities in the Americas, by inferring their genetic relationships with extant African, European, and Native American populations. Furthermore, exploring genome-wide data with novel statistical and bioinformatics methods, population geneticists have been increasingly able to infer the last 500 years of admixture histories of these populations. These inferences have highlighted the diversity of histories experienced by enslaved-African descendants, and the complex influences of socio-economic, political, and historical contexts on human genetic diversity patterns during and after the slave trade. Finally, the recent advances of paleogenomics unveiled crucial aspects of the life and health of the first generation of enslaved Africans in the Americas. Altogether, human population genetics approaches in the genomic and paleogenomic era need to be coupled with history, archaeology, anthropology, and demography in interdisciplinary research, to reconstruct the multifaceted and largely unknown history of the TAST and its influence on human biological and cultural diversities today. Here, we review anthropological genomics studies published over the past 15 years and focusing on the history of enslaved-African descendant populations in the Americas.
... The poor correlation between selfidentified categories and genetic ancestry is even more apparent for the REDS and Salvador cohorts, both of which have a high proportion of individuals in the "Black" and "Mixed" categories ( Table 1), and in which most of the variation in genetic ancestry is not captured by the IBGE categories (r 2 = 0.31). Our finding of a weak correlation between IBGE categories and genetic ancestry is consistent with previous studies of admixed Brazilians (18,41), and suggests that the higher the admixture proportion, the lower the correlation between them. This suggests that there may be important differences between the influence of IBGE categories and of genetic ancestry on the chances of finding a match in REDOME, and it is this question we address in subsequent next sections. ...
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A match of HLA loci between patients and donors is critical for successful hematopoietic stem cell transplantation. However, the extreme polymorphism of HLA loci-an outcome of millions of years of natural selection-reduces the chances that two individuals will carry identical combinations of multilocus HLA genotypes. Further, HLA variability is not homogeneously distributed throughout the world: African populations on average have greater variability than non-Africans, reducing the chances that two unrelated African individuals are HLA identical. Here, we explore how self-identification (often equated with "ethnicity" or "race") and genetic ancestry are related to the chances of finding HLA compatible donors in a large sample from Brazil, a highly admixed country. We query REDOME, Brazil's Bone Marrow Registry, and investigate how different criteria for identifying ancestry influence the chances of finding a match. We find that individuals who self-identify as "Black" and "Mixed" on average have lower chances of finding matches than those who self-identify as "White" (up to 57% reduction). We next show that an individual's African genetic ancestry, estimated using molecular markers and quantified as the proportion of an individual's genome that traces its ancestry to Africa, is strongly associated with reduced chances of finding a match (up to 60% reduction). Finally, we document that the strongest reduction in chances of finding a match is associated with having an MHC region of exclusively African ancestry (up to 75% reduction). We apply our findings to a specific condition, for which there is a clinical indication for transplantation: sickle-cell disease. We show that the increased African ancestry in patients with this disease leads to reduced chances of finding a match, when compared to the remainder of the sample, without the condition. Our results underscore the influence of ancestry on chances of finding compatible HLA matches, and indicate that efforts guided to increasing the African component of registries are necessary.
... See Salzano et al. (1977) for a seminal study in the field;Lins et al. (2010) andHenn et al. (2011) are more a more recent studies making similar claims. 5 In fact, migration and trading of individuals between groups seems to be quite frequent among such societies. ...
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This paper describes using current literature and research a problem that has plagued social scientists for centuries, see that of „moral sentiments?. Human beings are inherently social by nature and hold certain regard for others? opinions (esteem preferences) as well as for others generally (altruism). It is argued in the article that such preferences may in fact be consistent with a core rational human agent. It is furthermore argued that the lack of regard for such preferences in social sciences research (and particularly within the domain of economics) severely weakens models and theories in the respective disciplines. A few potential avenues for including social preferences writ large into social science (read: economic) modeling are outlined.
... Following HLA data processing, comparisons between both populations included in this study began by stratifying individuals in BM and RJ populations based on self-declared ethnicity to minimize the effects of admixture on individuals, even though ethnicity is not a perfect ancestry estimator [25]. The results showed similar allele diversity in both cities when compensating for the effect of the smaller sample size in BM on the number of alleles found, indicating a similar admixture to that of RJ. ...
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Human leukocyte antigen (HLA) genes can exhibit extensive variations in frequency, especially in highly admixed populations, such as that of Brazil. In this study, we demonstrated NGS‐based HLA typing in our laboratory using an Illumina HiSeq 2500 sequencing platform and downstream analysis. We herein describe and compare the allele and haplotype frequencies of the populations in Barra Mansa (BM) and Rio de Janeiro (RJ), using the acquired genetic data. Sequences encompassing 7 HLA loci (HLA‐A, HLA‐B, HLA‐C, HLA‐DRB1, HLA‐DQB1, HLA‐DPA1, and HLA‐DPB1) were amplified from a total of 1435 bone marrow samples donated by volunteers recruited in BM (37.56%) and RJ (62.44%) using polymerase chain reactions, and were sequenced using 5 distinct HiSeq 2500 runs. Alleles were analysed to generate 2‐locus haplotypes and extended haplotypes encompassing more than 2 loci. The most frequent haplotype was A*01:01:01 ~ C*07:01:01 ~ B*08:01:01 ~ DRB1*03:01:01 ~ DQB1*02:01:01 ~ DPA1*01:03:01 ~ DPB1*04:01:01 in both populations. The populations of BM and RJ exhibited a significant difference in genetic composition (p = 0.03) but not in genetic variance (p = 0.45). However, some groups of subjects, classified based on self‐declared ethnicity particularly Branca and Preta, displayed significant genetic variance (p < 0.05). In conclusion, these genetic data indicate no differences in HLA loci between the populations of these two cities, but were informative with respect to variations in ancestry composition. This article is protected by copyright. All rights reserved.
Direct‐to‐consumer genetic ancestry tests measure biogeographic ancestry (BGA), which refers to an individual's ancestral origin in relation to major population groups. There is growing concern that biogeographic information exaggerates both false beliefs about racial genetic differences and, ultimately, racial bias. Across three studies (N = 1317), we find that biogeographic information impacts racial categorization and beliefs about both genetic racial essentialism (i.e., the extent to which people believe that race is genetically derived) and biological race differences. Specifically, we find people are more likely to categorize Black/White biracial targets as Black and believe that a target is more biologically different from White people (e.g., has thicker skin) as the target's percent sub‐Saharan African biogeographic ancestry (ABGA) increases (Studies 1 and 2). We also find that people misrepresent BGA as “race genes,” such that they perceive Black/White biracial targets with more ABGA as sharing more genes with Black people, which then predicts greater Black racial categorization of the target and increased beliefs that the target is susceptible to certain physical and mental illnesses (Study 2). Notably, BGA remains a predictor of these outcomes even when people know the target's specific racial ancestry, that is, their exact number of Black grandparents (Study 2). Finally, we find that exposing people to the idea that race is genetically derived, compared to biologically derived, exaggerates beliefs that genes determine both human life (genetic essentialism) and racial categories (genetic racial essentialism; Study 3). We discuss implications for studying psychological essentialism, racial bias, and racial health disparities.
Introduction and objectives: Little is known about primary biliary cholangitis (PBC) in non-whites. The purpose of this study was to evaluate clinical features and outcomes of PBC in a highly admixed population. Material and methods: The Brazilian Cholestasis Study Group multicentre database was reviewed to assess demographics, clinical features and treatment outcomes of Brazilian patients with PBC. Results: 562 patients (95% females, mean age 51±11 years) with PBC were included. Concurrent autoimmune diseases and overlap with autoimmune hepatitis (AIH) occurred, respectively, in 18.9% and 14%. After a mean follow-up was 6.2±5.3 years, 32% had cirrhosis, 7% underwent liver transplantation and 3% died of liver-related causes. 96% were treated with ursodeoxycholic acid (UDCA) and 12% required add-on therapy with fibrates, either bezafibrate, fenofibrate or ciprofibrate. Response to UDCA and to UDCA/fibrates therapy varied from 39%-67% and 42-61%, respectively, according to different validated criteria. Advanced histological stages and non-adherence to treatment were associated with primary non-response to UDCA, while lower baseline alkaline phosphatase (ALP) and aspartate aminotransferase (AST) levels correlated with better responses to both UDCA and UDCA/fibrates. Conclusions: Clinical features of PBC in highly admixed Brazilians were similar to those reported in Caucasians and Asians, but with inferior rates of overlap syndrome with AIH. Response to UDCA was lower than expected and inversely associated with histological stage and baseline AST and ALP levels. Most of patients benefited from add-on fibrates, including ciprofibrate. A huge heterogeneity in response to UDCA therapy according to available international criteria was observed and reinforces the need of global standardization.
Aims: To evaluate the relationship between self-reported colour-race, genomic ancestry, and metabolic syndrome in an admixed Brazilian population with type 1 diabetes. Methods: We included 1640 participants with type 1 diabetes. The proportions of European, African and Amerindian genomic ancestries were determined by 46 ancestry informative markers insertion deletion sets. Two different sets of analyses were performed to determine whether self-reported colour-race and genomic ancestry were predictors of metabolic syndrome. Results: Metabolic syndrome was identified in 29.8% of participants. In the first model, the factors associated with metabolic syndrome were: female gender (odds ratio 1.95, P<0.001); diabetes duration (odds ratio 1.04, P<0.001); family history of type 2 diabetes (odds ratio 1.36, P=0.019); and acanthosis nigricans (odds ratio 5.93, P<0.001). Colour-race was not a predictive factor for metabolic syndrome. In the second model, colour-race was replaced by European genomic ancestry. The associated factors were: female gender (odds ratio 1.95, P<0.001); diabetes duration (odds ratio 1.04, P<0.001); family history of type 2 diabetes (odds ratio 1.39, P=0.011); and acanthosis nigricans (odds ratio 6.12, P<0.001). Physical exercise (≥3 times a week) was a protective factor (odds ratio 0.77, P=0.041), and European genomic ancestry was not associated with metabolic syndrome but showed an odds ratio of 1.79 (P=0.05). Conclusions: Although a higher level of European genomic ancestry was observed among participants with metabolic syndrome in the univariate analysis, this association did not persist after multivariable adjustments. Further prospective studies in other highly admixed populations remain necessary to better evaluate whether the European ancestral component modulates the development of metabolic syndrome in type 1 diabetes.
Many studies have shown that the LDB2 gene plays a regulatory role in retinal development and the cell cycle, but its biological role remains unclear. In this study, a 31-bp indel in the LDB2 gene was found for the first time on the basis of 2797 individuals from 10 different breeds, which led to different genotypes among individuals (II, ID and DD). Among these genotypes, DD was the most dominant. Association analysis of an F2 resource population crossed with the Gushi (GS) chicken and Anka chicken showed that the DD genotype conferred a significantly greater semi-evisceration weight (SEW, 1108.665g±6.263), evisceration weight (EW, 927.455g±5.424), carcass weight (CW, 1197.306g±6.443), breast muscle weight (BMW, 71.05g±0.574), and leg muscle weight (LMW, 100.303g±0.677) than the ID genotype (SEW, 1059.079g±16.86; EW, 879.459g±14.446; CW, 1141.821g±17.176; BMW, 67.164g±1.523; and LMW, 96.163g±1.823). In addition, LDB2 gene expression in different breeds was significantly higher in the breast muscles and leg muscles than in other tissues. The expression level in the breast muscle differed significantly among stages of GS chicken development, with the highest expression observed at 6 weeks. The expression levels in the pectoral muscles differed significantly among Ross 308 genotypes. In summary, we studied the relationships between a 31-bp indel in the LDB2 gene and economic traits in chickens. The indel was significantly correlated with multiple growth and carcass traits in the F2 resource population and affected the expression of the LDB2 gene in muscle tissue. In short, our study revealed that the LDB2 gene 31-bp indel can be used as a potential genetic marker for molecular breeding.
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There are hereditary differences among human beings. Some of these differences have geographical correlates. Some genetic variants that produce physical or behavioral deficits occur significantly more often in some areas, or in some ethnic groups, than in others. However, none of these facts provides any intellectual support for the race concept, for racial classifications, or for social hierarchies based on ethnic‐group membership. The geographical element of the race concept is important in theory but is widely ignored in practice since it does not conform well to the facts of current human phenotype distribution. Much of the literature on supposed racial differences involves such geographically meaningless exercises as studying differences among "races" by subdividing a sample of North Americans. If races are defined as geographically delimited conspecific populations characterized by distinctive regional phenotypes, then human races do not exist now and have not existed for centuries
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Cytochrome P450 (CYP) is a superfamily of enzymes involved in the metabolism of endogenous compounds and xenobiotics. CYP2A6 catalyzes the oxidation of nicotine and the activation of carcinogens such as aflatoxin B1 and nitrosamines. CYP2E1 metabolizes ethanol and other low-molecular weight compounds and can also activate nitrosamines. The CYP2A6 and CYP2E1 genes are polymorphic, altering their catalytic activities and susceptibility to cancer and other diseases. A number of polymorphisms described are ethnic-dependent. In the present study, we determined the genotype and allele frequencies of the main CYP2A6 and CYP2E1 polymorphisms in a group of 289 volunteers recruited at the Central Laboratory of Hospital Universitário Pedro Ernesto. They had been residing in the city of Rio de Janeiro for at least 6 months and were divided into two groups according to skin color (white and non-white). The alleles were determined by allele specific PCR (CYP2A6) or by PCR-RFLP (CYP2E1). The frequencies of the CYP2A6*1B and CYP2A6*2 alleles were 0.29 and 0.02 for white individuals and 0.24 and 0.01 for non-white individuals, respectively. The CYP2A6*5 allele was not found in the population studied. Regarding the CYP2E1*5B allele, we found a frequency of 0.07 in white individuals, which was statistically different (P < 0.05) from that present in non-white individuals (0.03). CYP2E1*6 allele frequency was the same (0.08) in both groups. The frequencies of CYP2A6*1B, CYP2A6*2 and CYP2E1*6 alleles in Brazilians are similar to those found in Caucasians and African-Americans, but the frequency of the CYP2E1*5B allele is higher in Brazilians.
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Two hundred and three individuals classified as white were tested for 11 single nucleotide polymorphisms plus two insertion/deletions in their Y-chromosomes. A subset of these individuals (n = 172) was also screened for sequences in the first hypervariable segment of their mitochondrial DNA (mtDNA). In addition, complementary studies were done for 11 of the 13 markers indicated above in 54 of 107 black subjects previously investigated in this southern Brazilian population. The prevalence of Y-chromosome haplogroups among whites was similar to that found in the Azores (Portugal) or Spain, but not to that of other European countries. About half of the European or African mtDNA haplogroups of these individuals were related to their places of origin, but not their Amerindian counterparts. Persons classified in these two categories of skin color and related morphological traits showed distinct genomic ancestries through the country. These findings emphasize the need to consider in Brazil, despite some general trends, a notable heterogeneity in the pattern of admixture dynamics within and between populations/groups.
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The role of race in human genetics and biomedical research is among the most contested issues in science. Much debate centers on the relative importance of genetic versus sociocultural factors in explaining racial inequalities in health. However, few studies integrate genetic and sociocultural data to test competing explanations directly. We draw on ethnographic, epidemiologic, and genetic data collected in Southeastern Puerto Rico to isolate two distinct variables for which race is often used as a proxy: genetic ancestry versus social classification. We show that color, an aspect of social classification based on the culturally defined meaning of race in Puerto Rico, better predicts blood pressure than does a genetic-based estimate of continental ancestry. We also find that incorporating sociocultural variables reveals a new and significant association between a candidate gene polymorphism for hypertension (alpha(2C) adrenergic receptor deletion) and blood pressure. This study addresses the recognized need to measure both genetic and sociocultural factors in research on racial inequalities in health. Our preliminary results provide the most direct evidence to date that previously reported associations between genetic ancestry and health may be attributable to sociocultural factors related to race and racism, rather than to functional genetic differences between racially defined groups. Our results also imply that including sociocultural variables in future research may improve our ability to detect significant allele-phenotype associations. Thus, measuring sociocultural factors related to race may both empower future genetic association studies and help to clarify the biological consequences of social inequalities.
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Ancestry informative SNPs can be useful to estimate individual and population biogeographical ancestry. Brazilian population is characterized by a genetic background of three parental populations (European, African, and Brazilian Native Amerindians) with a wide degree and diverse patterns of admixture. In this work we analyzed the information content of 28 ancestry-informative SNPs into multiplexed panels using three parental population sources (African, Amerindian, and European) to infer the genetic admixture in an urban sample of the five Brazilian geopolitical regions. The SNPs assigned apart the parental populations from each other and thus can be applied for ancestry estimation in a three hybrid admixed population. Data was used to infer genetic ancestry in Brazilians with an admixture model. Pairwise estimates of F(st) among the five Brazilian geopolitical regions suggested little genetic differentiation only between the South and the remaining regions. Estimates of ancestry results are consistent with the heterogeneous genetic profile of Brazilian population, with a major contribution of European ancestry (0.771) followed by African (0.143) and Amerindian contributions (0.085). The described multiplexed SNP panels can be useful tool for bioanthropological studies but it can be mainly valuable to control for spurious results in genetic association studies in admixed populations.
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The current study investigated the association between vitamin-D-receptor (VDR) genotypes with bone-mineral density (BMD) and its interaction with physical activity level (PAL). Individuals in a sample of 192 volunteers (67.84 +/- 5.23 years) underwent BMD evaluation and were genotyped for VDR ApaI, BsmI, FokI, and TaqI polymorphisms. Haplotypes were reconstructed through expectation-maximization algorithm, and regression-based haplotype-specific association tests were performed with studied phenotypes. None of the polymorphisms were associated with BMD at any site; however, haplotype was associated with femoral-neck and Ward's-triangle BMD. Interaction between PAL and VDR genotypes was significant for the FokI polymorphism at femoral-neck and Ward's-triangle BMD. The FokI T/T genotype was associated with higher BMD in active women. It was concluded that VDR haplotypes, but not genotypes, are associated with femoral-neck and Ward's-triangle BMD in postmenopausal women. Moreover, the results suggest that VDR FokI polymorphism might be a potential determinant of BMD response to physical activity.
The ethnic and geographic distributions of several common chronic diseases show distinct patterns that are consistent with the distribution of genes and genetic admixture. For example, diabetes and gallbladder disease occur most frequently among Amerindians, while those genetically admixed with them (such as Mexican-Americans) have intermediate rates, and lowest rates are found among Whites and Blacks. Because there will be heterogeneity from individual to individual in ancestral affinity within an admixed population, a method is developed for estimating each person's admixture probability. Results confirm that there is substantial heterogeneity of individual admixture among Mexican-Americans in Starr County, Texas, with a mean value indicating that 65% of genes in this population are Caucasian derived and 35% Amerindian derived. The individual estimates are shown to be unrelated to the probability of being diabetic and only marginally related to gallbladder disease, with those having the most Amerindian affinity being at increased risk. These results are a consequence of the independent assortment of loci and indicate that unless the markers employed are related (including linkage) to the disease of interest, the method will have limited utility. Individual admixture estimates will be useful, however, for examining aspects of population structure and will find increased utility for predicting disease and examining disease associations as more and more of the genome is represented by markers, a very probable prospect with the abundance of DNA polymorphism being identified by restriction enzymes.
GENALEX is a user-friendly cross-platform package that runs within Microsoft Excel, enabling population genetic analyses of codominant, haploid and binary data. Allele frequency-based analyses include heterozygosity, F statistics, Nei&apos;s genetic distance, population assignment, probabilities of identity and pairwise relatedness. Distance-based calculations include AMOVA, principal coordinates analysis (PCA), Mantel tests, multivariate and 2D spatial autocorrelation and TWOGENER. More than 20 different graphs summarize data and aid exploration. Sequence and genotype data can be imported from automated sequencers, and exported to other software. Initially designed as tool for teaching, GENALEX 6 now offers features for researchers as well. Documentation and the program are available at
Brazilian Quilombos are Afro-derived communities founded mainly by fugitive slaves between the 16(th) and 19(th) centuries; they can be recognized today by ancestral and cultural characteristics. Each of these remnant communities, however, has its own particular history, which includes the migration of non-African derived people. The present work presents a proposal for the origin of the male founder in Brazilian quilombos based on Y-haplogroup distribution. Y haplogroups, based on 16 binary markers (92R7, SRY2627, SRY4064, SRY10831.1 and .2, M2, M3, M09, M34, M60, M89, M213, M216, P2, P3 and YAP), were analysed for 98 DNA samples from genetically unrelated men from three rural Brazilian Afro-derived communities-Mocambo, Rio das Rãs and Kalunga-in order to estimate male geographic origin. Data indicated significant differences among these communities. A high frequency of non-African haplogroups was observed in all communities. This observation suggested an admixture process that has occurred over generations and directional mating between European males and African female slaves that must have occurred on farms before the slaves escaped. This means that the admixture occurred before the slaves escaped and the foundation of the quilombo.
To provide a resource for assessing continental ancestry in a wide variety of genetic studies, we identified, validated, and characterized a set of 128 ancestry informative markers (AIMs). The markers were chosen for informativeness, genome-wide distribution, and genotype reproducibility on two platforms (TaqMan assays and Illumina arrays). We analyzed genotyping data from 825 subjects with diverse ancestry, including European, East Asian, Amerindian, African, South Asian, Mexican, and Puerto Rican. A comprehensive set of 128 AIMs and subsets as small as 24 AIMs are shown to be useful tools for ascertaining the origin of subjects from particular continents, and to correct for population stratification in admixed population sample sets. Our findings provide general guidelines for the application of specific AIM subsets as a resource for wide application. We conclude that investigators can use TaqMan assays for the selected AIMs as a simple and cost efficient tool to control for differences in continental ancestry when conducting association studies in ethnically diverse populations.