Papel dos níveis séricos de vitamina D e das variantes genéticas envolvidas na sua rota metabólica na hepatite C crônica

Introdução: Nos últimos anos têm-se demonstrado que a vitamina D desempenha um papel crucial em muitas doenças agudas e crônicas, não só afetando as condições ósseas, mas também aumentando o risco de fraturas, doenças auto-imunes e câncer. A influência da vitamina D nas doenças do fígado tem sido amplamente discutida já que esta sofre metabolismo hepático. Indivíduos com doenças hepáticas, e em especial com hepatite C crônica, apresentam maior prevalência de deficiência de vitamina D. Objetivos: Avaliar, em duas amostras distintas, a influência dos níveis séricos de vitamina D e/ou dos polimorfismos envolvidos na sua rota metabólica na progressão da doença hepática crônica causada pelo vírus C. Métodos: A primeira amostra consistiu de um estudo transversal com 132 pacientes com hepatite C crônica genótipo 1 do Hospital de Clínicas de Porto Alegre (HCPA). Foi avaliada a influência de níveis séricos de vitamina D e dos polimorfismos rs7041 e rs4588 do gene GC no grau de fibrose hepática (escore METAVIR). As genotipagens foram feitas com ensaio TaqMan e as análises estatísticas foram realizadas no programa SPSS v.20.0. A segunda amostra consistiu da análise de dados extraídos da plataforma dbGaP. Foram investigados 681 pacientes com hepatite C crônica da coorte americana HALT-C, acompanhados pelo período quatro anos. Avaliou-se a relação de 40 polimorfismos dos genes DHCR7, GC, CYP2R1, CYP24A1, CYP27B1, VDR, SMAD3 e TGFB1 nos seguintes desfechos: piora da fibrose hepática; descompensação hepática (escore Child Pugh-Turcotte>7, ascite, encefalopatia hepática, peritonite bacteriana espontânea e/ou sangramento de varizes gastroesofágicas); desenvolvimento de carcinoma hepatocelular e morte do fígado. Os polimorfismos que não se encontravam disponíveis no banco de dados foram imputados com o programa Mach-Admix 2.0.203 e as análises foram no programa Plink 1.07 e foi realizada correção de Bonferroni. Nesta amostra, resultados com P 7, ascites, spontaneous bacterial peritonitis, and/or encephalopathy); development of hepatocellular carcinoma; and liver death. Polymorphisms not available in dbGaP data were imputed using Mach-Admix 2.0.203 software and analyses were performed in Plink v.1.07 and a Bonferroni’s correction was performed. Results with P<0.05 were considered as having tendency towards association. Results: In HCPA sample low serum vitamin D, as well as severe vitamin D deficiency, were more frequent among patients with intermediate/severe fibrosis (METAVIR 3 and 4). Although rs7041 and rs4588 4 polymorphisms and its haplotypes presented association with serum levels of vitamin D, they were not associated with severity of liver fibrosis. In sample two, eleven polymorphisms presented tendency towards association (P<0.05) with the studied outcomes: four SNPs in DHCR7 with hepatic decompensation (rs4944957, rs12800438, rs3829251 and rs4945008); two in GC with worsening of fibrosis and liver death (rs7041 and rs222020); two in CYP2R1 with ascites or hepatocellular carcinoma (rs7116978 and rs1562902); two in VDR with gastric/esophageal bleeding and hepatocellular carcinoma (rs4516035 and rs2239186); and one in SMAD3 with worsening of fibrosis and encephalopathy (rs2118610). Only one polymorphism, rs1800469 in TGFB1, showed statistical significance with hepatic decompensation after Bonferroni’s correction (P<0.05/40). Conclusions: Our results demonstrated that low serum vitamin D has association with fibrosis progression in chronic hepatitis C genotype 1. Also, the eleven polymorphisms with tendency towards association indicate that genetic variants in vitamin D pathway possess weak or none relation with progression of chronic hepatitis C, deserving future analyses. Finally, polymorphism rs1800469 in TGFB1 demonstrated potential utility to help identify patients with higher odds of hepatic decompesantion

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