3 research outputs found

    Immunological evaluation of young unvaccinated patients with Turner syndrome after COVID-19

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    Objectives: The X-chromosome contains the largest number of immune-related genes, which play a major role in COVID-19 symptomatology and susceptibility. Here, we had a unique opportunity to investigate, for the first time, COVID-19 outcomes in six unvaccinated young Brazilian patients with Turner syndrome (TS; 45, X0), including one case of critical illness in a child aged 10 years, to evaluate their immune response according to their genetic profile. Methods: A serological analysis of humoral immune response against SARS-CoV-2, phenotypic characterization of antiviral responses in peripheral blood mononuclear cells after stimuli, and the production of cytotoxic cytokines of T lymphocytes and natural killer cells were performed in blood samples collected from the patients with TS during the convalescence period. Whole exome sequencing was also performed. Results: Our volunteers with TS showed a delayed or insufficient humoral immune response to SARS-CoV-2 (particularly immunoglobulin G) and a decrease in interferon-γ production by cluster of differentiation (CD)4+ and CD8+ T lymphocytes after stimulation with toll-like receptors 7/8 agonists. In contrast, we observed a higher cytotoxic activity in the volunteers with TS than the volunteers without TS after phorbol myristate acetate/ionomycin stimulation, particularly granzyme B and perforin by CD8+ and natural killer cells. Interestingly, two volunteers with TS carry rare genetic variants in genes that regulate type I and III interferon immunity. Conclusion: Following previous reports in the literature for other conditions, our data showed that patients with TS may have an impaired immune response against SARS-CoV-2. Furthermore, other medical conditions associated with TS could make them more vulnerable to COVID-19

    Table_1_Follow-up of young adult monozygotic twins after simultaneous critical coronavirus disease 2019: A case report.pdf

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    BackgroundThe influence of the host genome on coronavirus disease 2019 (COVID-19) susceptibility and severity is supported by reports on monozygotic (MZ) twins where both were infected simultaneously with similar disease outcomes, including several who died due to the SARS-CoV-2 infection within days apart. However, successive exposures to pathogens throughout life along with other environmental factors make the immune response unique for each individual, even among MZ twins.Case presentation and methodsHere we report a case of a young adult monozygotic twin pair, who caught attention since both presented simultaneously severe COVID-19 with the need for oxygen support despite age and good health conditions. One of the twins, who spent more time hospitalized, reported symptoms of long-COVID even 7 months after infection. Immune cell profile and specific responses to SARS-CoV-2 were evaluated as well as whole exome sequencing.ConclusionAlthough the MZ twin brothers shared the same genetic mutations which may be associated with their increased risk of developing severe COVID-19, their clinical progression was different, reinforcing the role of both immune response and genetics in the COVID-19 presentation and course. Besides, post-COVID syndrome was observed in one of them, corroborating an association between the duration of hospitalization and the occurrence of long-COVID symptoms.</p

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

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    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
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