Amerindian (but not African or European) ancestry is significantly associated with diurnal preference within an admixed Brazilian population

Significant questions remain unanswered regarding the genetic versus environmental contributions to racial/ethnic differences in sleep and circadian rhythms. We addressed this question by investigating the association between diurnal preference, using the morningness–eveningness questionnaire (MEQ), and genetic ancestry within the Baependi Heart Study cohort, a highly admixed Brazilian population based in a rural town. Analysis was performed using measures of ancestry, using the Admixture program, and MEQ from 1,453 individuals. We found an association between the degree of Amerindian (but not European of African) ancestry and morningness, equating to 0.16 units for each additional percent of Amerindian ancestry, after adjustment for age, sex, education, and residential zone. To our knowledge, this is the first published report identifying an association between genetic ancestry and MEQ, and above all, the first one based on ancestral contributions within individuals living in the same community. This previously unknown ancestral dimension of diurnal preference suggests a stratification between racial/ethnic groups in an as yet unknown number of genetic polymorphisms

Cohort profile : the Baependi Heart Study-a family-based, highly admixed cohort study in a rural Brazilian town

PURPOSE: Cardiovascular disease (CVD) is a major challenge to global health. The same epidemiological transition scenario is replayed as countries develop, but with variations based on environment, culture and ethnic mixture. The Baependi Heart Study was set up in 2005 to develop a longitudinal family-based cohort study that reflects on some of the genetic and lifestyle-related peculiarities of the Brazilian populations, in order to evaluate genetic and environmental influences on CVD risk factor traits. PARTICIPANTS: Probands were recruited in Baependi, a small rural town in the state of Minas Gerais, Brazil, following by first-degree and then increasingly more distant relatives. The first follow-up wave took place in 2010, and the second in 2016. At baseline, the study evaluated 1691 individuals across 95 families. Cross-sectional data have been collected for 2239 participants. FINDINGS TO DATE: Environmental and lifestyle factors and measures relevant to cardiovascular health have been reported. Having expanded beyond cardiovascular health outcomes, the phenotype datasets now include genetics, biochemistry, anthropometry, mental health, sleep and circadian rhythms. Many of these have yielded heritability estimates, and a shared genetic background of anxiety and depression has recently been published. In spite of universal access to electricity, the population has been found to be strongly shifted towards morningness compared with metropolitan areas. FUTURE PLANS: A new follow-up, marking 10 years of the study, is ongoing in 2016, in which data are collected as in 2010 (with the exception of the neuropsychiatric protocol). In addition to this, a novel questionnaire package collecting information about intelligence, personality and spirituality is being planned. The data set on circadian rhythms and sleep will be amended through additional questionnaires, actimetry, home sleep EEG recording and dim light melatonin onset (DLMO) analysis. Finally, the anthropometric measures will be expanded by adding three-dimensional facial photography, voice recording and anatomical brain MRI

Growth hormone insensitivity with immune dysfunction caused by a STAT5B mutation in the south of Brazil: evidence for a founder effect

ABSTRACT Homozygous STAT5B mutations causing growth hormone insensitivity with immune dysfunction were described in 10 patients since 2003, including two Brazilian brothers from the south of Brazil. Our objectives were to evaluate the prevalence of their STAT5B mutation in this region and to analyze the presence of a founder effect. We obtained DNA samples from 1,205 local inhabitants, 48 relatives of the homozygous patients and four individuals of another affected family. Genotyping for STAT5B c.424_427del mutation and for two polymorphic markers around it was done through fragment analysis technique. We also determined Y-chromosome and mtDNA haplotypes and genomic ancestry in heterozygous carriers. We identified seven families with STAT5B c.424_427del mutation, with 33 heterozygous individuals. The minor allelic frequency of this mutation was 0.29% in this population (confidence interval 95% 0.08-0.5%), which is significantly higher than the frequency of other pathogenic STAT5B allele variants observed in public databases (p < 0.001). All heterozygous carriers had the same haplotype present in the homozygous patients, found in only 9.4% of non-carriers (p < 0.001), supporting the existence of a founder effect. The Y-chromosome haplotype, mtDNA and genomic ancestry analysis indicated a European origin of this mutation. Our results provide compelling evidence for a founder effect of STAT5B c.424_427del mutation

Origin and dynamics of admixture in Brazilians and its effect on the pattern of deleterious mutations.

While South Americans are underrepresented in human genomic diversity studies, Brazil has been a classical model for population genetics studies on admixture. We present the results of the EPIGEN Brazil Initiative, the most comprehensive up-to-date genomic analysis of any Latin-American population. A population-based genome-wide analysis of 6,487 individuals was performed in the context of worldwide genomic diversity to elucidate how ancestry, kinship, and inbreeding interact in three populations with different histories from the Northeast (African ancestry: 50%), Southeast, and South (both with European ancestry >70%) of Brazil. We showed that ancestry-positive assortative mating permeated Brazilian history. We traced European ancestry in the Southeast/South to a wider European/Middle Eastern region with respect to the Northeast, where ancestry seems restricted to Iberia. By developing an approximate Bayesian computation framework, we infer more recent European immigration to the Southeast/South than to the Northeast. Also, the observed low Native-American ancestry (6-8%) was mostly introduced in different regions of Brazil soon after the European Conquest. We broadened our understanding of the African diaspora, the major destination of which was Brazil, by revealing that Brazilians display two within-Africa ancestry components: one associated with non-Bantu/western Africans (more evident in the Northeast and African Americans) and one associated with Bantu/eastern Africans (more present in the Southeast/South). Furthermore, the whole-genome analysis of 30 individuals (42-fold deep coverage) shows that continental admixture rather than local post-Columbian history is the main and complex determinant of the individual amount of deleterious genotypes

Origin and dynamics of admixture in Brazilians and its effect on the pattern of deleterious mutations

Submitted by Nuzia Santos ([email protected]) on 2016-02-19T13:11:37Z No. of bitstreams: 1 Origin and dynamics of admixture in Brazilians and its effect on the pattern of deleterious mutations..pdf: 501572 bytes, checksum: 45f5ed2fc0a7c2cb73e047a75457edae (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2016-02-19T13:37:09Z (GMT) No. of bitstreams: 1 Origin and dynamics of admixture in Brazilians and its effect on the pattern of deleterious mutations..pdf: 501572 bytes, checksum: 45f5ed2fc0a7c2cb73e047a75457edae (MD5)Made available in DSpace on 2016-02-19T13:37:09Z (GMT). No. of bitstreams: 1 Origin and dynamics of admixture in Brazilians and its effect on the pattern of deleterious mutations..pdf: 501572 bytes, checksum: 45f5ed2fc0a7c2cb73e047a75457edae (MD5) Previous issue date: 2015Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade de São Paulo. Instituto do Coração. São Paulo, SP, BrasilUniversidade Federal de Pelotas. Programa de Pós-Graduação em Epidemiologia. Pelotas, RS, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade de São Paulo. Instituto do Coração. São Paulo, SP, BrasilUniversidade de São Paulo. Instituto do Coração. São Paulo, SP, BrasilUniversidade Federal da Bahia. Instituto de Matemática. Departamento de Estatística. Salvador, Bahia, BrasilUniversidade Federal da Bahia. Instituto de Ciências da Saúde. Departamento de Ciências da Biointeração. Salvador, Bahia, BrasilUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, BrasilUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, BrasilUniversity of Leicester. Department of Genetics. Leicester, United KingdomWashington University School of Medicine. Department of Molecular Microbiology. St. Louis, MO/University of California. Department of Medicine. San Diego, CAAsociación Benéfica Proyectos en Informática, Salud, Medicina y Agricultura. Biomedical Research Unit. Lima, PeruUniversidade Federal de Santa Catarina. Embriologia e Genética. Departamento de Biologia Celular. Florianópolis, SC, BrasilUniversidade Federal de Minas Gerais. Departamento de Estatística. Belo Horizonte, MG, BrasilUniversità di Ferrara. Dipartimento di Scienze della Vita e Biotecnologie. Ferrara, ItalyJohns Hopkins University. International Health. Bloomberg School of Public Health. Baltimore, MD, USA/Universidade Peruana Cayetano Heredia. Laboratorio de Investigación de Enfermedades Infecciosas. Lima, PeruUniversity of Toronto. Center for Addiction and Mental Health. Department of Psychiatry and Neuroscience Section. Toronto, ON, CanadaUniversidade Federal de Santa Catarina. Embriologia e Genética. Departamento de Biologia Celular. Florianópolis, SC, BrasilUniversidade Federal de Santa Catarina. Embriologia e Genética. Departamento de Biologia Celular. Florianópolis, SC, BrasilInnsbruck Medical University. Molecular and Clinical Pharmacology. Department of Medical Genetics. Division of Genetic Epidemiology. Innsbruck, AustriaFrederick National Laboratory for Cancer Research. Leidos Biomedical Research. Cancer Genomics Research Laboratory. Frederick, MDLondon School of Hygiene and Tropical Medicine. Faculty of Epidemiology. Department of Infectious Disease Epidemiology. London, United KingdomUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, BrasilFundação Oswaldo Cruz. Instituto de Pesquisa Rene Rachou. Belo Horizonte, MG, BrasilUniversidade de São Paulo. Instituto do Coração. São Paulo, SP, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, BrasilUniversidade Federal da Bahia. Instituto de Ciências da Saúde. Departamento de Ciências da Biointeração. Salvador, BA, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Laboratório de Computação Científica. Belo Horizonte, MG, Brasil.Universidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Rene Rachou. Belo Horizonte, MG, Brasil.Universidade Federal de Pelotas. Programa de Pós-Graduação em Epidemiologia. Pelotas, RS, Brasil.Universidade Federal de Rio Grande do Sul. Centro Nacional de Supercomputação. Porto Alegre, RS, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Rene Rachou. Grupo de Genômica e Biologia Computacional. Belo Horizonte, MG, Brasil.Universidade Federal de Pelotas. Programa de Pós-Graduação em Epidemiologia. Pelotas, RS, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Rene Rachou. Belo Horizonte, MG, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Rene Rachou. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Laboratório de Computação Científica. Belo Horizonte, MG, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, Brasil.Universidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, Brasil.While South Americans are underrepresented in human genomic diversity studies, Brazil has been a classical model for population genetics studies on admixture.We present the results of the EPIGEN Brazil Initiative, the most comprehensive up-to-date genomic analysis of any Latin-American population. A population-based genomewide analysis of 6,487 individuals was performed in the context of worldwide genomic diversity to elucidate how ancestry, kinship, and inbreeding interact in three populations with different histories from the Northeast (African ancestry: 50%), Southeast, and South (both with European ancestry >70%) of Brazil. We showed that ancestry-positive assortative mating permeated Brazilian history. We traced European ancestry in the Southeast/South to a wider European/Middle Eastern region with respect to the Northeast, where ancestry seems restricted to Iberia. By developing an approximate Bayesian computation framework, we infer more recent European immigration to the Southeast/South than to the Northeast. Also, the observed low Native-American ancestry (6–8%) was mostly introduced in different regions of Brazil soon after the European Conquest. We broadened our understanding of the African diaspora, the major destination of which was Brazil, by revealing that Brazilians display two within-Africa ancestry components: one associated with non-Bantu/western Africans (more evident in the Northeast and African Americans) and one associated with Bantu/eastern Africans (more present in the Southeast/South). Furthermore, the whole-genome analysis of 30 individuals (42-fold deep coverage) shows that continental admixture rather than local post-Columbian history is the main and complex determinant of the individual amount of deleterious genotypes