Off-label use of azithromycin, hydroxychloroquine, and ivermectin (the “COVID kit”) has been suggested for COVID-19 treatment in Brazil without clinical or scientific evidence of efficacy. These drugs have known adverse drug reactions (ADR). This study aimed to analyze if the sales of drugs in the “COVID kit” are correlated to the reported number of ADR after the COVID-19 pandemic began. Data was obtained from the Brazilian Health Regulatory Agency (Anvisa) website on reported sales and ADRs for azithromycin, hydroxychloroquine, and ivermectin for all Brazilian states. The period from March 2019 to February 2020 (before the pandemic) was compared to that from March 2020 to February 2021 (during the pandemic). Trend adjustment was performed for time series data and cross-correlation analysis to investigate correlation between sales and ADR within the same month (lag 0) and in the following months (lag 1 and lag 2). Spearman’s correlation coefficient was used to assess the magnitude of the correlations. After the pandemic onset, sales of all investigated drugs increased significantly (69.75% for azithromycin, 10,856,481.39% for hydroxychloroquine, and 12,291,129.32% for ivermectin). ADR levels of all medications but azithromycin were zero before the pandemic, but increased after its onset. Cross-correlation analysis was significant in lag 1 for all drugs nationwide. Spearman’s correlation was moderate for azithromycin and hydroxychloroquine but absent for ivermectin. Data must be interpreted cautiously since no active search for ADR was performed. Our results show that the increased and indiscriminate use of ”COVID kit“ during the pandemic correlates to an increased occurrence of ADRs.

Background In this study, the prevalence of different types of mucopolysaccharidoses (MPS) was estimated based on data from the exome aggregation consortium (ExAC) and the genome aggregation database (gnomAD). The population-based allele frequencies were used to identify potential disease-causing variants on each gene related to MPS I to IX (except MPS II). Methods We evaluated the canonical transcripts and excluded homozygous, intronic, 3′, and 5′ UTR variants. Frameshift and in-frame insertions and deletions were evaluated using the SIFT Indel tool. Splice variants were evaluated using SpliceAI and Human Splice Finder 3.0 (HSF). Loss-of-function single nucleotide variants in coding regions were classified as potentially pathogenic, while synonymous variants outside the exon–intron boundaries were deemed non-pathogenic. Missense variants were evaluated by five in silico prediction tools, and only those predicted to be damaging by at least three different algorithms were considered disease-causing. Results The combined frequencies of selected variants (ranged from 127 in GNS to 259 in IDUA) were used to calculate prevalence based on Hardy–Weinberg's equilibrium. The maximum estimated prevalence ranged from 0.46 per 100,000 for MPSIIID to 7.1 per 100,000 for MPS I. Overall, the estimated prevalence of all types of MPS was higher than what has been published in the literature. This difference may be due to misdiagnoses and/or underdiagnoses, especially of the attenuated forms of MPS. However, overestimation of the number of disease-causing variants by in silico predictors cannot be ruled out. Even so, the disease prevalences are similar to those reported in diagnosis-based prevalence studies. Conclusion We report on an approach to estimate the prevalence of different types of MPS based on publicly available population-based genomic data, which may help health systems to be better prepared to deal with these conditions and provide support to initiatives on diagnosis and management of MPS.

Mucopolysaccharidosis type I (MPS I) is an autosomal recessive disease characterized by the deficiency of alpha-L-iduronidase (IDUA), an enzyme involved in glycosaminoglycan degradation. More than 200 disease-causing variants have been reported and characterized in the IDUA gene. It also has several variants of unknown significance (VUS) and literature conflicting interpretations of pathogenicity. This study evaluated 586 variants obtained from the literature review, five population databases, in addition to dbSNP, Human Genome Mutation Database (HGMD), and ClinVar. For the variants described in the literature, two datasets were created based on the strength of the criteria. The stricter criteria subset had 108 variants with expression study, analysis of healthy controls, and/or complete gene sequence. The less stringent criteria subset had additional 52 variants found in the literature review, HGMD or ClinVar, and dbSNP with an allele frequency higher than 0.001. The other 426 variants were considered VUS. The two strength criteria datasets were used to evaluate 33 programs plus a conservation score. BayesDel (addAF and noAF), PON-P2 (genome and protein), and ClinPred algorithms showed the best sensitivity, specificity, accuracy, and kappa value for both criteria subsets. The VUS were evaluated with these five algorithms. Based on the results, 122 variants had total consensus among the five predictors, with 57 classified as predicted deleterious and 65 as predicted neutral. For variants not included in PON-P2, 88 variants were considered deleterious and 92 neutral by all other predictors. The remaining 124 did not obtain a consensus among predictors.