Genetic parameters and association between agronomic traits in special-grain common bean (Phaseolus vulgaris L.) genotypes

Estimates of genetic parameters allow to determine the genetic variability present in a population, and constitute one of the initial steps in a breeding program. The objectives of this study were to estimate genetic parameters and identify agronomic traits directly and indirectly correlated with the grain yield (GY), as well as to estimate their direct and indirect effects on the yield of special-grain common bean genotypes. The experiment was carried out in the harvest 2016/2017, in complete blocks design with three repetitions. The traits evaluated were: days to flowering, days to maturity, first pod height, plant height, number of pods per plant, number of grains per pod, mass of hundred grain, and grain yield. Data were subjected to analysis of variance, and genetic parameters were estimated followed by phenotypic and genotypic correlations. Phenotypic and genotypic correlations were split into direct and indirect effects by path analysis. The population under study showed to be promising for breeding considering the most traits. There is a positive direct effect of days to maturity on grain yield. The traits days to maturity and mass of hundred grains can be used in the indirect selection aiming at higher grain yield. Highlights There is genetic variability in the population under study, indicating that the population is promising for the selection of agronomic traits. Based on genetic parameters, correlations and path analysis, the selection for days to maturity can provide genetic gains for yield at early cycles. Direct selection for days to maturity should be carried out aiming at higher yield. Indirect selection for days to maturity and mass of hundred grains can be used aiming at yield gains in special-grain common bean.Estimates of genetic parameters allow to determine the genetic variability present in a population, and constitute one of the initial steps in a breeding program. The objectives of this study were to estimate genetic parameters and identify agronomic traits directly and indirectly correlated with the grain yield (GY), as well as to estimate their direct and indirect effects on the yield of special-grain common bean genotypes. The experiment was carried out in the harvest 2016/2017, in complete blocks design with three repetitions. The traits evaluated were: days to flowering, days to maturity, first pod height, plant height, number of pods per plant, number of grains per pod, mass of hundred grain, and grain yield. Data were subjected to analysis of variance, and genetic parameters were estimated followed by phenotypic and genotypic correlations. Phenotypic and genotypic correlations were split into direct and indirect effects by path analysis. The population under study showed to be promising for breeding considering the most traits. There is a positive direct effect of days to maturity on grain yield. The traits days to maturity and mass of hundred grains can be used in the indirect selection aiming at higher grain yield. Highlights There is genetic variability in the population under study, indicating that the population is promising for the selection of agronomic traits. Based on genetic parameters, correlations and path analysis, the selection for days to maturity can provide genetic gains for yield at early cycles. Direct selection for days to maturity should be carried out aiming at higher yield. Indirect selection for days to maturity and mass of hundred grains can be used aiming at yield gains in special-grain common bean

Polymorphisms in the MBL2 gene are associated with the plasma levels of MBL and the cytokines IL-6 and TNF-α in severe COVID-19

IntroductionMannose-binding lectin (MBL) promotes opsonization, favoring phagocytosis and activation of the complement system in response to different microorganisms, and may influence the synthesis of inflammatory cytokines. This study investigated the association of MBL2 gene polymorphisms with the plasma levels of MBL and inflammatory cytokines in COVID-19.MethodsBlood samples from 385 individuals (208 with acute COVID-19 and 117 post-COVID-19) were subjected to real-time PCR genotyping. Plasma measurements of MBL and cytokines were performed by enzyme-linked immunosorbent assay and flow cytometry, respectively.ResultsThe frequencies of the polymorphic MBL2 genotype (OO) and allele (O) were higher in patients with severe COVID-19 (p< 0.05). The polymorphic genotypes (AO and OO) were associated with lower MBL levels (p< 0.05). IL-6 and TNF-α were higher in patients with low MBL and severe COVID-19 (p< 0.05). No association of polymorphisms, MBL levels, or cytokine levels with long COVID was observed.DiscussionThe results suggest that, besides MBL2 polymorphisms promoting a reduction in MBL levels and therefore in its function, they may also contribute to the development of a more intense inflammatory process responsible for the severity of COVID-19

I Diretriz brasileira de cardio-oncologia pediátrica da Sociedade Brasileira de Cardiologia

Sociedade Brasileira de Oncologia PediátricaUniversidade Federal de São Paulo (UNIFESP) Instituto de Oncologia Pediátrica GRAACCUniversidade Federal de São Paulo (UNIFESP)Universidade de São Paulo Faculdade de Medicina Instituto do Coração do Hospital das ClínicasUniversidade Federal do Rio Grande do Sul Hospital de Clínicas de Porto AlegreInstituto Materno-Infantil de PernambucoHospital de Base de BrasíliaUniversidade de Pernambuco Hospital Universitário Oswaldo CruzHospital A.C. CamargoHospital do CoraçãoSociedade Brasileira de Cardiologia Departamento de Cardiopatias Congênitas e Cardiologia PediátricaInstituto Nacional de CâncerHospital Pequeno PríncipeSanta Casa de Misericórdia de São PauloInstituto do Câncer do Estado de São PauloUniversidade Federal de São Paulo (UNIFESP) Departamento de PatologiaHospital Infantil Joana de GusmãoUNIFESP, Instituto de Oncologia Pediátrica GRAACCUNIFESP, Depto. de PatologiaSciEL

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

BACKGROUND: Measurement of changes in health across locations is useful to compare and contrast changing epidemiological patterns against health system performance and identify specific needs for resource allocation in research, policy development, and programme decision making. Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we drew from two widely used summary measures to monitor such changes in population health: disability-adjusted life-years (DALYs) and healthy life expectancy (HALE). We used these measures to track trends and benchmark progress compared with expected trends on the basis of the Socio-demographic Index (SDI). METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2016. We calculated DALYs by summing years of life lost and years of life lived with disability for each location, age group, sex, and year. We estimated HALE using age-specific death rates and years of life lived with disability per capita. We explored how DALYs and HALE differed from expected trends when compared with the SDI: the geometric mean of income per person, educational attainment in the population older than age 15 years, and total fertility rate. FINDINGS: The highest globally observed HALE at birth for both women and men was in Singapore, at 75·2 years (95% uncertainty interval 71·9-78·6) for females and 72·0 years (68·8-75·1) for males. The lowest for females was in the Central African Republic (45·6 years [42·0-49·5]) and for males was in Lesotho (41·5 years [39·0-44·0]). From 1990 to 2016, global HALE increased by an average of 6·24 years (5·97-6·48) for both sexes combined. Global HALE increased by 6·04 years (5·74-6·27) for males and 6·49 years (6·08-6·77) for females, whereas HALE at age 65 years increased by 1·78 years (1·61-1·93) for males and 1·96 years (1·69-2·13) for females. Total global DALYs remained largely unchanged from 1990 to 2016 (-2·3% [-5·9 to 0·9]), with decreases in communicable, maternal, neonatal, and nutritional (CMNN) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). The exemplars, calculated as the five lowest ratios of observed to expected age-standardised DALY rates in 2016, were Nicaragua, Costa Rica, the Maldives, Peru, and Israel. The leading three causes of DALYs globally were ischaemic heart disease, cerebrovascular disease, and lower respiratory infections, comprising 16·1% of all DALYs. Total DALYs and age-standardised DALY rates due to most CMNN causes decreased from 1990 to 2016. Conversely, the total DALY burden rose for most NCDs; however, age-standardised DALY rates due to NCDs declined globally. INTERPRETATION: At a global level, DALYs and HALE continue to show improvements. At the same time, we observe that many populations are facing growing functional health loss. Rising SDI was associated with increases in cumulative years of life lived with disability and decreases in CMNN DALYs offset by increased NCD DALYs. Relative compression of morbidity highlights the importance of continued health interventions, which has changed in most locations in pace with the gross domestic product per person, education, and family planning. The analysis of DALYs and HALE and their relationship to SDI represents a robust framework with which to benchmark location-specific health performance. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform health policies, health system improvement initiatives, targeted prevention efforts, and development assistance for health, including financial and research investments for all countries, regardless of their level of sociodemographic development. The presence of countries that substantially outperform others suggests the need for increased scrutiny for proven examples of best practices, which can help to extend gains, whereas the presence of underperforming countries suggests the need for devotion of extra attention to health systems that need more robust support. FUNDING: Bill & Melinda Gates Foundation

Polymorphisms in the MBL2 gene are associated with the plasma levels of MBL and the cytokines IL-6 and TNF-α in severe COVID-19

National Council for Scientific and Technological Development (CNPQ #401235/2020-3); Fundação Amazônia de Amparo a Estudos e Pesquisa do Pará (FAPESPA #005/2020 and #006/2020), Secretaria de Estado de Ciência, Tecnologia e Educação Profissional e Tecnológica (#09/ 2021) and Universidade Federal do Pará (PAPQ/2022)Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Ministério da Saúde. Secretaria de Ciência, Tecnologia, Inovação e Insumos Estratégicos. Instituto Evandro Chagas. Programa de Pós-Graduação em Virologia. Ananindeua, PA, Brasil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Ministério da Saúde. Secretaria de Ciência, Tecnologia, Inovação e Insumos Estratégicos. Instituto Evandro Chagas. Programa de Pós-Graduação em Virologia. Ananindeua, PA, Brasil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Pesquisa Básica em Malária, Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Pesquisa Básica em Malária, Ananindeua, PA, Brasil / Federal University of Pará. Institute of Medical Sciences. School of Medicine. Belém, PA, Brazil.Belém Adventist Hospital. Belém, PA, Brazil.Belém Adventist Hospital. Belém, PA, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil / Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil / Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Ciência, Tecnologia, Inovação e Insumos Estratégicos. Instituto Evandro Chagas. Programa de Pós-Graduação em Virologia. Ananindeua, PA, Brasil / Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil.Ministério da Saúde. Secretaria de Ciência, Tecnologia, Inovação e Insumos Estratégicos. Instituto Evandro Chagas. Programa de Pós-Graduação em Virologia. Ananindeua, PA, Brasil / Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.University of the State of Pará. Center of Biological and Health Sciences. Belém, PA, Brazil.University of the State of Pará. Center of Biological and Health Sciences. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Laboratory of Genetics of Complex Diseases. Belém, PA, Brazil.Federal University of Pará. Institute of Biological Sciences. Laboratory of Virology. Belém, PA, Brazil / Federal University of Pará. Institute of Biological Sciences. Graduate Program in Biology of Infectious and Parasitic Agents. Belém, PA, Brazil.Introduction: Mannose-binding lectin (MBL) promotes opsonization, favoring phagocytosis and activation of the complement system in response to different microorganisms, and may influence the synthesis of inflammatory cytokines. This study investigated the association of MBL2 gene polymorphisms with the plasma levels of MBL and inflammatory cytokines in COVID-19. Methods: Blood samples from 385 individuals (208 with acute COVID-19 and 117 post-COVID-19) were subjected to real-time PCR genotyping. Plasma measurements of MBL and cytokines were performed by enzyme-linked immunosorbent assay and flow cytometry, respectively. Results: The frequencies of the polymorphic MBL2 genotype (OO) and allele (O) were higher in patients with severe COVID-19 (p< 0.05). The polymorphic genotypes (AO and OO) were associated with lower MBL levels (p< 0.05). IL-6 and TNF-α were higher in patients with low MBL and severe COVID-19 (p< 0.05). No association of polymorphisms, MBL levels, or cytokine levels with long COVID was observed. Discussion: The results suggest that, besides MBL2 polymorphisms promoting a reduction in MBL levels and therefore in its function, they may also contribute to the development of a more intense inflammatory process responsible for the severity of COVID-19

Association of polymorphisms of IL-6 pathway genes (IL6, IL6R and IL6ST) with COVID-19 severity in an amazonian population

Amazon Foundation for Research Support (FAPESPA)—#005/2020; The Coordination for the Improvement of Higher Education Personnel (CAPES), National Council for Scientific and Technological Development (CNPQ)—#401235/2020-3.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil / Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil.Hospital Adventista de Belém. Belém, PA, Brazil.Hospital Adventista de Belém, Belém, PA, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Imunologia. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde e Ambiente. Instituto Evandro Chagas. Laboratório de Pesquisas Básicas em Malária. Ananindeua, PA, Brasil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, BrazilUniversidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.Universidade Federal do Pará. Programa de Pós-Graduação em Biologia de Agentes Infecciosos e Parasitários. Belém, PA, Brazil / Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Virologia. Belém, PA, Brazil.Universidade Federal do Pará. Instituto de Ciências Biológicas. Laboratório de Genética de Doenças Complexas. Belém, PA, Brazil.Interleukin-6 has been recognized as a major role player in COVID-19 severity, being an important regulator of the cytokine storm. Hence, the evaluation of the influence of polymorphisms in key genes of the IL-6 pathway, namely IL6, IL6R, and IL6ST, may provide valuable prognostic/predictive markers for COVID-19. The present cross-sectional study genotyped three SNPs (rs1800795, rs2228145, and rs7730934) at IL6. IL6R and IL6ST genes, respectively, in 227 COVID-19 patients (132 hospitalized and 95 non-hospitalized). Genotype frequencies were compared between these groups. As a control group, published data on gene and genotype frequencies were gathered from published studies before the pandemic started. Our major results point to an association of the IL6 C allele with COVID-19 severity. Moreover, IL-6 plasmatic levels were higher among IL6 CC genotype carriers. Additionally, the frequency of symptoms was higher at IL6 CC and IL6R CC genotypes. In conclusion, the data suggest an important role of IL6 C allele and IL6R CC genotype on COVID-19 severity, in agreement with indirect evidence from the literature about the association of these genotypes with mortality rates, pneumonia, and heightening of protein plasmatic levels pro-inflammatory driven effects