The Genomic Ancestry of Individuals from Different Geographical Regions of Brazil Is More Uniform Than Expected

Based on pre-DNA racial/color methodology, clinical and pharmacological trials have traditionally considered the different geographical regions of Brazil as being very heterogeneous. We wished to ascertain how such diversity of regional color categories correlated with ancestry. Using a panel of 40 validated ancestry-informative insertion-deletion DNA polymorphisms we estimated individually the European, African and Amerindian ancestry components of 934 self-categorized White, Brown or Black Brazilians from the four most populous regions of the Country. We unraveled great ancestral diversity between and within the different regions. Especially, color categories in the northern part of Brazil diverged significantly in their ancestry proportions from their counterparts in the southern part of the Country, indicating that diverse regional semantics were being used in the self-classification as White, Brown or Black. To circumvent these regional subjective differences in color perception, we estimated the general ancestry proportions of each of the four regions in a form independent of color considerations. For that, we multiplied the proportions of a given ancestry in a given color category by the official census information about the proportion of that color category in the specific region, to arrive at a “total ancestry” estimate. Once such a calculation was performed, there emerged a much higher level of uniformity than previously expected. In all regions studied, the European ancestry was predominant, with proportions ranging from 60.6% in the Northeast to 77.7% in the South. We propose that the immigration of six million Europeans to Brazil in the 19th and 20th centuries - a phenomenon described and intended as the “whitening of Brazil” - is in large part responsible for dissipating previous ancestry dissimilarities that reflected region-specific population histories. These findings, of both clinical and sociological importance for Brazil, should also be relevant to other countries with ancestrally admixed populations

Avaliação dos efeitos citogenéticos da exposição ocupacional a pesticidas em agentes sanitários vinculados à Prefeitura de Belo Horizonte.

Exportado OPUSMade available in DSpace on 2019-08-13T13:07:23Z (GMT). No. of bitstreams: 1 dissertacao_fernanda_de_souza_gomes_kehdy___c_pia.pdf: 523605 bytes, checksum: 176cefdbfe2b42a2437567aa699495fb (MD5) Previous issue date: 23Agentes sanitários responsáveis pela aplicação de pesticidas para o controle de vetores de doenças constituem uma população ocupacionalmente exposta a genotóxicos potenciais. Sendo assim, o objetivo deste estudo foi determinar a relação entre a exposição ocupacional a pesticidas e a presença de danos citogenéticos. Foram selecionados 59 homens (29 agentes sanitários e 30 indivíduos controle) com idade entre 18-57 anos que viviam e trabalhavam na mesma região em Belo Horizonte (Brasil). Através do Teste do Micronúcleo (MN) em linfócitos periféricos, as freqüências de micronúcleos (MN), células binucleadas micronucleadas (CBMN), pontes nucleoplasmáticas (PN), células apoptóticas (APOP), células necróticas (NECR) e índice de divisão nuclear (IDN) foram determinados. A análise de covariância (ANCOVA) revelou freqüências médias significativamente maiores (p<0,05) de MN (15,81 ± 1,31 vs. 4,71 ± 0,42), CBMN (15,10 ± 1,22 vs. 4,62 ± 0,44), PN (4,59 ± 0,76 vs. 1,00 ± 0,34), NECR (12,07 ± 1,45 vs. 5,17 ± 0,70) no grupo exposto, em relação aos indivíduos controle respectivamente. Não houve diferença significativa entre as freqüências de APOP entre os grupos exposto e controle, enquanto o IDN foi significativamente menor (p<0,05) nos expostos (1,49 ± 0,02 vs. 1,61 ± 0,02). Houve relação direta da idade dos indivíduos e as freqüências de MN e CBMN. Não foi observada influência do tempo de exposição ou dos hábitos de fumar e ingerir bebidas alcoólicas sobre os parâmetros citogenéticos analisados. De acordo com estes resultados, a exposição ocupacional à pesticidas mostrou efeito genotóxico e citotóxico nos linfócitos dos agentes sanitários

Genomic ancestry and ethnoracial self-classification based on 5,871 community-dwelling Brazilians (The Epigen Initiative)

Barreto, Mauricio Lima “Documento produzido em parceria ou por autor vinculado à Fiocruz, mas não consta à informação no documento”. Cibele C. Cesar1, Jackson S. Conceição2, Gustavo N.O. Costa2, Nubia Esteban3, Rosemeire L. Fiaccone2, Camila A. Figueiredo2, Josélia O.A. Firmo4, Andrea R.V.R. Horimoto3, Thiago P. Leal5, Moara Machado5, Wagner C.S. Magalhães5, Isabel Oliveira de Oliveira3, Sérgio V. Peixoto4, Maíra R. Rodrigues, Hadassa C. Santos3 & Thiago M. Silva2 1Universidade Federal de MinasGerais, Instituto de Ciências Exatas, Belo Horizonte, Brazil, 2Universidade Federal da Bahia, Instituto de Saúde Coletiva, Salvador, Brazil, 3Universidade de São Paulo, Instituto do Coração, São Paulo, Brazil, 4Fundação Oswaldo Cruz, Instituto de Pesquisas Rene Rachou, Belo Horizonte, Brazil, 5Universidade Federal de Minas Gerais, Instituto de Ciências Biológicas, Belo Horizonte, BrazilSubmitted by Ana Maria Fiscina Sampaio ([email protected]) on 2017-08-01T13:53:30Z No. of bitstreams: 1 Costa MFL Genomic ancestry....pdf: 480721 bytes, checksum: 23b31e00169b8c01cc95b6c11b0343b1 (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2017-08-01T14:24:30Z (GMT) No. of bitstreams: 1 Costa MFL Genomic ancestry....pdf: 480721 bytes, checksum: 23b31e00169b8c01cc95b6c11b0343b1 (MD5)Made available in DSpace on 2017-08-01T14:24:30Z (GMT). No. of bitstreams: 1 Costa MFL Genomic ancestry....pdf: 480721 bytes, checksum: 23b31e00169b8c01cc95b6c11b0343b1 (MD5) Previous issue date: 2015Department of Science and Technology (DECIT,Ministry of Health) and National Fund for Scientific and Technological Development (FNDCT, Ministry of Science and Technology), Funding of Studies and Projects (FINEP, Ministry of Science and Technology, Brazil), Coordination of Improvement of Higher Education Personnel (CAPES, Ministry of Education, Brazil). MFLC, MLB, BLH, ACP, CGV, ETS, CBC, JOAF and SVP are supported by the Brazilian National Research Council (CNPq).Fundação Oswaldo Cruz. Instituto de Pesquisas Rene Rachou. Belo Horizonte, MG, BrasilLondon School of Hygiene and Tropical Medicine. Department of Infectious Disease Epidemiology. London, UKUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, BrasilUniversidade Federal de Pelotas. Programa de Pós Graduação em Epidemiologia. Pelotas, RS, BrasilFundação Oswaldo Cruz. Instituto de Pesquisas Rene Rachou. Belo Horizonte, MG, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, BrasilUniversidade de São Paulo. Instituto doCoração. São Paulo, SP, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, BrasilUniversidade Federal de Pelotas. Programa de Pós Graduação em Epidemiologia. Pelotas, RS, BrasilUniversidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Belo Horizonte, MG, BrasilMúltipla – ver em NotasBrazil never had segregation laws defining membership of an ethnoracial group. Thus, the composition of the Brazilian population is mixed, and its ethnoracial classification is complex. Previous studies showed conflicting results on the correlation between genome ancestry and ethnoracial classification in Brazilians. We used 370,539 Single Nucleotide Polymorphisms to quantify this correlation in 5,851 community-dwelling individuals in the South (Pelotas), Southeast (Bambui) and Northeast (Salvador) Brazil. European ancestry was predominant in Pelotas and Bambui (median = 85.3% and 83.8%, respectively). African ancestry was highest in Salvador (median = 50.5%). The strength of the association between the phenotype and median proportion of African ancestry varied largely across populations, with pseudo R(2) values of 0.50 in Pelotas, 0.22 in Bambui and 0.13 in Salvador. The continuous proportion of African genomic ancestry showed a significant S-shape positive association with self-reported Blacks in the three sites, and the reverse trend was found for self reported Whites, with most consistent classifications in the extremes of the high and low proportion of African ancestry. In self-classified Mixed individuals, the predicted probability of having African ancestry was bell-shaped. Our results support the view that ethnoracial self-classification is affected by both genome ancestry and non-biological factors

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.