Complement factor H gene (CFH) polymorphisms C-257T, G257A and haplotypes are associated with protection against severe dengue phenotype, possible related with high CFH expression.

Four genetic polymorphisms located at the promoter (C-257T) and coding regions of CFH gene (exon 2 G257A, exon 14 A2089G and exon 19 G2881T) were investigated in 121 dengue patients (DENV-3) in order to assess the relationship between allele/haplotypes variants and clinical outcomes. A statistical value was found between the CFH-257T allele (TT/TC genotypes) and reduced susceptibility to severe dengue (SD). Statistical associations indicate that individuals bearing a T allele presented significantly higher protein levels in plasma. The -257T variant is located within a NF-κB binding site, suggesting that this variant might have effect on the ability of the CFH gene to respond to signals via the NF-κB pathway. The G257A allelic variant showed significant protection against severe dengue. When CFH haplotypes effect was considered, the ancestral CG/CG promoter-exon 2 SNP genotype showed significant risk to SD either in a general comparison (ancestral × all variant genotypes), as well as in individual genotypes comparison (ancestral × each variant genotype), where the most prevalent effect was observed in the CG/CG × CA/TG comparison. These findings support the involvement of -257T, 257A allele variants and haplotypes on severe dengue phenotype protection, related with high basal CFH expression.

Lentivírus em caprinos leiteiros do semiárido paraibano: prevalência de anticorpos, fatores de risco e detecção molecular / Lentivirus in dairy goats from the semiarid region of Paraiba state: seroprevalence, risk factors and molecular detection

Os objetivos do presente trabalho foram determinar a prevalência de caprinos leiteiros soropositivos para a infecção por Lentivirus de pequenos ruminantes no semiárido do Estado da Paraíba, Nordeste do Brasil, identificar fatores de risco associados à prevalência de rebanhos positivos, e realizar a detecção molecular do agente. Foram utilizadas 1047 cabras leiteiras de 110 propriedades selecionadas aleatoriamente no Município de Monteiro, Estado da Paraíba, no período de março de 2009 a dezembro de 2011. Para o diagnóstico da infecção por Lentivirus, foi utilizado o teste de imunodifusão em gel de ágar (AGID). Um ano após foi realizada nova sorologia, e PCR em tempo real foi aplicada em amostras de sangue e leite de 48 cabras procedentes de quatro propriedades com animais soropositivos. As prevalências de propriedades positivas e de animais soropositivos na AGID foram 44,6% (IC 95% = 35,1% - 54,3%) e 8,1% (IC 95% = 5,6% - 16,8%), respectivamente. Realizar corte e desinfecção de umbigo (odds ratio = 2,44; p = 0,048) e condições de aglomeração de animais (odds ratio = 3,45; p = 0,048) foram associadas com a prevalência de propriedades positivas. Um ano após a realização do inquérito sorológico, foi verificada a permanência de animais infectados, detectados por PCR em tempo real a partir de amostras de sangue e leite. A PCR em tempo real das amostras de leucócitos circulantes apresentou boa performance, com sensibilidade de 100%, especificidade de 92,86%, concordância de 93,75% e indicador Kappa de 0,765. Sugere-se que seja realizado um trabalho de educação sanitária junto aos produtores sobre medidas de prevenção com o objetivo de reduzir a disseminação da infecção nos rebanhos.

The aims of this study were to determine the seroprevalence of infection by ruminants Lentivirus in dairy goats in the semiarid of the Paraiba State, Northeastern Brazil, to identify risk factors associated with the herd-level prevalence and to perform molecular detection of the agent. A total of 1,047 dairy goats from 110 herds were randomly selected from the county of Monteiro, Paraiba State, and serum samples were collected from March 2009 to December 2011. For the diagnosis of Lentivirus infection, the agar gel immunodiffusion test (AGID) was used. One year after that a new serology was performed and the real-time PCR assay was applied in blood and milk samples from 48 goats from four herds with seropositive animals. Prevalence of positive herds and seropositive animals at AGID were 44.6% (95% CI=35.1-54.3%) and 8.1% (95% CI =5.6-16.8%), respectively. Umbilical cord cutting and disinfection (odds ratio = 2.44; p = 0.048) and conditions of animal agglomeration (odds ratio=3.45; p=0.048) were associated with herd-level prevalence. One year after the serological profile, the permanence of infected animals detected by real-time PCR in blood and milk samples was verified. Real-time PCR using white blood cells had a good performance, with sensitivity of 100%, specificity of 92.86%, concordance of 93.75% and Kappa index of 0.765. It was suggested to teach sanitary measures to the herd owners in order to encourage them to adopt prevention measures aiming to reduce the spread of the infection in the herds.

Classification of dengue fever patients based on gene expression data using support vector machines.

BACKGROUND: Symptomatic infection by dengue virus (DENV) can range from dengue fever (DF) to dengue haemorrhagic fever (DHF), however, the determinants of DF or DHF progression are not completely understood. It is hypothesised that host innate immune response factors are involved in modulating the disease outcome and the expression levels of genes involved in this response could be used as early prognostic markers for disease severity. METHODOLOGY/PRINCIPAL FINDINGS: mRNA expression levels of genes involved in DENV innate immune responses were measured using quantitative real time PCR (qPCR). Here, we present a novel application of the support vector machines (SVM) algorithm to analyze the expression pattern of 12 genes in peripheral blood mononuclear cells (PBMCs) of 28 dengue patients (13 DHF and 15 DF) during acute viral infection. The SVM model was trained using gene expression data of these genes and achieved the highest accuracy of approximately 85% with leave-one-out cross-validation. Through selective removal of gene expression data from the SVM model, we have identified seven genes (MYD88, TLR7, TLR3, MDA5, IRF3, IFN-alpha and CLEC5A) that may be central in differentiating DF patients from DHF, with MYD88 and TLR7 observed to be the most important. Though the individual removal of expression data of five other genes had no impact on the overall accuracy, a significant combined role was observed when the SVM model of the two main genes (MYD88 and TLR7) was re-trained to include the five genes, increasing the overall accuracy to approximately 96%. CONCLUSIONS/SIGNIFICANCE: Here, we present a novel use of the SVM algorithm to classify DF and DHF patients, as well as to elucidate the significance of the various genes involved. It was observed that seven genes are critical in classifying DF and DHF patients: TLR3, MDA5, IRF3, IFN-alpha, CLEC5A, and the two most important MYD88 and TLR7. While these preliminary results are promising, further experimental investigation is necessary to validate their specific roles in dengue disease.