ObjectiveTo assess the accuracy of sweat conductivity among newborns and very young infants.DesignProspective, population-based, diagnostic test accuracy study.SettingPublic Statewide Newborn Screening Programme where the incidence rate of cystic fibrosis (CF) is ≈1:11 000.PatientsNewborns and very young infants with positive two-tiered immunoreactive trypsinogen.InterventionsSweat conductivity and sweat chloride were performed simultaneously, on the same day and facility by independent technicians, with the cut-off values of 80 mmol/L and 60 mmol/L, respectively.Main outcome measuresSensitivity, specificity, positive and negative predictive values (PPV and NPV), overall accuracy, positive and negative likelihood ratios (+LR, -LR) and post (sweat conductivity (SC)) test probability were calculated to assess SC performance.Results1193 participants were included, 68 with and 1108 without CF, and 17 with intermediate values. The mean (SD) age was 48 (19.2) days, ranging from 15 to 90 days. SC yielded sensitivity of 98.5% (95% CI 95.7 to 100), specificity of 99.9% (95% CI 99.7 to 100), PPV of 98.5% (95% CI 95.7 to 100) and NPV of 99.9% (95% CI 99.7 to 100), overall accuracy of 99.8% (95% CI 99.6 to 100), +LR of 1091.7 (95% CI 153.8 to 7744.9) and -LR of 0.01 (95% CI 0.00 to 0.10). After a positive and negative sweat conductivity result, the patient’s probability of CF increases around 350 times and drops to virtually zero, respectively.ConclusionSweat conductivity had excellent accuracy in ruling in or ruling out CF after positive two-tiered immunoreactive trypsinogen among newborns and very young infants.

Objective The prevalence of biotinidase deficiency and the frequency of biotinidase gene variants in Brazil are not documented. We aimed to determine the incidence of partial and profound biotinidase deficiency in the state of Minas Gerais, Brazil, and to calculate the frequency of biotinidase gene variants in the newborn screening program of Minas Gerais. Methods Neonates (1,168,385) were screened from May 2013 to June 2018. Those detected with abnormal biotinidase activity based on semi-quantitative assays underwent confirmatory serum tests. The biotinidase gene was sequenced in all confirmed cases. Results The combined incidence of partial and profound biotinidase deficiency was estimated at 1:13,909 live births (95% confidence limit 1:11,235–1:17,217), much higher than the incidence rates reported in other populations worldwide. The most frequent biotinidase gene variants were p.D444H (allele frequency, 0.016), haplotype c.1330G>C;c.511G>A (p.D444H;A171T), p.D543E, c.310-15delT (intronic), p.V199M, and p.H485Q. Together these accounted for 74.6% of the alleles analysed. Conclusion Newborn screening for biotinidase deficiency, which revealed a higher incidence in Minas Gerais, is feasible and plays a critical role in the early identification of affected neonates and prevention of symptoms and irreversible sequelae. Biotinidase gene sequencing is a useful tool to confirm the diagnosis, and also provides valuable information about genetic variability among different populations.

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Pesticides constitute a category of chemical products intended specifically for the control and mitigation of pests. With their constant increase in use, the risk to human health and the environment has increased proportionally due to occupational and environmental exposure to these compounds. The use of these chemicals is associated with several toxic effects related to acute and chronic toxicity, such as infertility, hormonal disorders and cancer. The present work aimed to study the metabolic profile of individuals occupationally exposed to pesticides, using a metabolomics tool to identify potential new biomarkers. Metabolomics analysis was carried out on plasma and urine samples from individuals exposed and non-exposed occupationally, using liquid chromatography coupled with mass spectrometry (UPLC-MS). Non-targeted metabolomics analysis, using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) or partial least squares discriminant orthogonal analysis (OPLS-DA), demonstrated good separation of the samples and identified 21 discriminating metabolites in plasma and 17 in urine. The analysis of the ROC curve indicated the compounds with the greatest potential for biomarkers. Comprehensive analysis of the metabolic pathways influenced by exposure to pesticides revealed alterations, mainly in lipid and amino acid metabolism. This study indicates that the use of metabolomics provides important information about complex biological responses.

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