PubMed · 6968982
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1980. Retirement patterns for self-employed workers.. https://pubmed.ncbi.nlm.nih.gov/6968982/
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The association between Human Pegivirus 1 (HPgV-1, Pegivirus hominis, family Hepaciviridae) with disease etiology remains unclear, yet this virus is widely distributed among people exposed to contaminated blood. This study aimed to identify the prevalence and characterize HPgV-1 genomes obtained from acute febrile patients (n = 92 from 2019) and from blood donors (n = 633 from 2022) sampled in Mato Grosso, Brazil. The serum samples were tested by RT-qPCR for a conserved 5' UTR region of HPgV-1. Nucleic acid of 28 positive samples was converted to ds-cDNA, purified and sequenced with an Illumina NextSeq platform. The prevalence of HPgV-1 among acute febrile patients was 4.35% (4/92), who were mostly female (3/4; 75.00%) mean 28.86 (12-67) years-old; whereas among blood donors it was 3.79% (24/633), which were predominantly male (16/24; 66.67%), aged 30-45 years-old (13/24; 54.17%). Eight HPgV-1 genomic sequences (7,708-9,248) were recovered; two belong to subgenotype 2a and clustered with strains from United States, Brazil, France and Japan, while the remaining six genomes from subgenotype 2b grouped with strains from Pará, Brazil and abroad. HPgV-1 detection in acute febrile patients and in healthy blood donors highlights the necessity to investigate the epidemiological aspects of this infection, as well as the possible impact to public health in Midwestern Brazil.
BACKGROUND: Asthma is a heterogeneous disease influenced by genetic and environmental factors. Fine particulate matter (PM2.5) exacerbates asthma, likely through oxidative stress pathways, but whether genetic variation modifies this effect remains unclear. METHODS: We analysed data on 948 adults with asthma from the Severe Asthma Research Program (SARP), linking ZIP-code-level PM2.5 exposure with whole-genome sequencing data. We tested 4337 single nucleotide polymorphisms (SNPs) in 120 oxidative stress pathway genes for gene-environment (GxE) interactions with PM2.5 on lung function (forced expiratory volume in 1 s [FEV1] % predicted) using weighted linear regression. Gene expression data from bronchial epithelial cells (n = 170) were used to assess cis-expression quantitative trait loci (eQTLs). FINDINGS: Higher PM2.5 exposure was associated with lower FEV1% predicted (β per μg/m3 = -0.7, p = 0.01). We identified 20 SNPs across seven genes (OXSR1, PXDN, TPO, LRRK2, APP, MSRA, MSRB2) with significant GxE interactions after multiple-testing correction. Five SNPs were also eQTLs, linking PM2.5-modified gene expression to lung function. Minor alleles in OXSR1 and PXDN were associated with reduced gene expression and worsened FEV1% under high PM2.5 exposure. Conversely, TPO variants were associated with higher baseline expression and lower lung function, but under increasing PM2.5 exposure, minor allele carriers showed suppressed TPO expression and improved FEV1%. INTERPRETATION: This study identified 20 SNPs in oxidative stress pathway genes that modify the effect of PM2.5 on lung function in asthma. These findings highlight the importance of integrating environmental context in genetic studies and suggest potential therapeutic targets for pollution-sensitive asthma phenotypes. FUNDING: Supported by NIH grants.
BACKGROUND: Densitometric screening for osteoporosis in postmenopausal women has not been demonstrated cost-effective. We have tried to identify clinical factors for screening previous to densitometry avoiding unnecessary explorations. PATIENTS AND METHODS SETTING: outpatient clinics of a menopausal unit in a 450-bed general hospital. Cross-sectional study, in two steps, of two groups of 140 and 284 women attending for physiological menopause. A clinical questionnaire, physical data and lumbar densitometry (Hologic QDR 1000) were obtained classifying the cases as "normal" or "low bone mass" (osteopenia or osteoporosis) according with the WHO criteria. In the first group a logistic regression analysis was done to identify predictive factors for abnormal densitometry, then validated in the second group. Sensitivity, specificity, predictive values (PV) and classification ability of clinical factors were analyzed. RESULTS: Four factors were independent predictors of abnormal densitometry: age > 51 (odds ratio [OR] = 6.64; 95% CI, 2.36-18.7); body weight < 70 kg (OR = 4.32; 95% CI, 1.71-10.09); years of fertility < 32 (OR = 3.77; 95% CI, 1.36-10.04), and number of live births > 2 (OR = 3.47; 95% CI, 1.27-9.53). Presence of one factor offers: sensitivity 91.9%; specificity 15%; positive PV 66.6%, and negative PV 50%, whereas the presence of two factors offers: sensitivity 62.7%; specificity 70%; positive PV 79.9%, and negative PV 50.3%. Clinical screening allows, when two factors are present, to avoid a 35.5% of densitometries and the false-negative cases represent 18%. CONCLUSIONS: Detection of bone-risk clinical factors (abnormal densitometry) yields a screening, previous to densitometry, that avoids at least one third of explorations in women with physiological menopause, improving the efficiency of the test.