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1.
J Glob Health ; 13: 04151, 2023 Nov 17.
Artigo em Inglês | MEDLINE | ID: mdl-37974435

RESUMO

Background: Suboptimal health status (SHS) is a non-clinical or pre-disease state between optimal/ideal health and disease. While its etiology remains unclear, lifestyle is considered one of the most important risk factors. We aimed to examine the effects of lifestyles on SHS through a nationwide survey in China. Methods: We conducted a cross-sectional survey in 148 cities across China between 20 June and 31 August 2022, on 30 505 participants from rural and urban communities gathered through stratified quota sampling. We measured SHS with the Short-Form Suboptimal Health Status Questionnaire (SHSQ-SF). We gathered information on participants' lifestyles (ie, smoking, alcohol consumption, breakfast habits, weekly food delivery frequency, intermittent fasting, sleep duration and physical activities) through face-to-face interview. We determined the relationship between lifestyle and SHS logistic regression analysis by based on odds ratios (ORs) and 95% confidence intervals (CIs). Results: We included 22 897 participants (female: 13 056, male: 9841), 12 108 (52.88%) of whom reported exposure to SHS. After adjusting for demographic characteristics, individuals who currently smoked (OR = 1.165; 95% CI = 1.058-1.283) and those who drank alcohol (OR = 1.483; 95% CI = 1.377.1.596) were at a higher risk of SHS than those who have never done either. In a dose-response way, takeaway food consumption was associated with a higher risk of SHS, while increased frequency of breakfast and mild-intensity exercise conversely reduced said risk. Individuals with shorter sleep duration had a higher risk of SHS when compared to those who slept for more than seven hours per day. Conclusions: We observed a relatively high prevalence of SHS across China, highlighting the importance of lifestyle in health promotion. Specifically, adopting healthy dietary habits, engaging in regular physical activity, and ensuring high-quality sleep are key in preventing SHS. Registration: Chinese Clinical Trial Registry (ChiCTR2200061046).


Assuntos
Promoção da Saúde , Estilo de Vida , Humanos , Masculino , Feminino , Estudos Transversais , Nível de Saúde , China/epidemiologia
2.
Brief Bioinform ; 24(2)2023 03 19.
Artigo em Inglês | MEDLINE | ID: mdl-36917170

RESUMO

Metagenomic sequencing (mNGS) is a powerful diagnostic tool to detect causative pathogens in clinical microbiological testing owing to its unbiasedness and substantially reduced costs. Rapid and accurate classification of metagenomic sequences is a critical procedure for pathogen identification in dry-lab step of mNGS test. However, clinical practices of the testing technology are hampered by the challenge of classifying sequences within a clinically relevant timeframe. Here, we present GPMeta, a novel GPU-accelerated approach to ultrarapid pathogen identification from complex mNGS data, allowing users to bypass this limitation. Using mock microbial community datasets and public real metagenomic sequencing datasets from clinical samples, we show that GPMeta has not only higher accuracy but also significantly higher speed than existing state-of-the-art tools such as Bowtie2, Bwa, Kraken2 and Centrifuge. Furthermore, GPMeta offers GPMetaC clustering algorithm, a statistical model for clustering and rescoring ambiguous alignments to improve the discrimination of highly homologous sequences from microbial genomes with average nucleotide identity >95%. GPMetaC exhibits higher precision and recall rate than others. GPMeta underlines its key role in the development of the mNGS test in infectious diseases that require rapid turnaround times. Further study will discern how to best and easily integrate GPMeta into routine clinical practices. GPMeta is freely accessible to non-commercial users at https://github.com/Bgi-LUSH/GPMeta.


Assuntos
Metagenoma , Microbiota , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Metagenômica/métodos , Sensibilidade e Especificidade
3.
Hum Mutat ; 42(12): 1567-1575, 2021 12.
Artigo em Inglês | MEDLINE | ID: mdl-34428318

RESUMO

The American College of Medical Genetics and Genomics, and the Association for Molecular Pathology (ACMG/AMP) have proposed a set of evidence-based guidelines to support sequence variant interpretation. The ClinGen hearing loss expert panel (HL-EP) introduced further specifications into the ACMG/AMP framework for genetic hearing loss. This study developed a tool named Variant Interpretation Platform for genetic Hearing Loss (VIP-HL), aiming to semi-automate the HL ACMG/AMP rules. VIP-HL aggregates information from external databases to automate 13 out of 24 ACMG/AMP rules specified by HL-EP, namely PVS1, PS1, PM1, PM2, PM4, PM5, PP3, BA1, BS1, BS2, BP3, BP4, and BP7. We benchmarked VIP-HL using 50 variants in which 82 rules were activated by the ClinGen HL-EP. VIP-HL concordantly activated 93% (76/82) rules, significantly higher than that of by InterVar (48%; 39/82). VIP-HL is an integrated online tool for reliable automated variant classification in hearing loss genes. It assists curators in variant interpretation and provides a platform for users to share classifications with each other. VIP-HL is available with a user-friendly web interface at http://hearing.genetics.bgi.com/.


Assuntos
Genoma Humano , Perda Auditiva , Humanos , Testes Genéticos , Variação Genética , Perda Auditiva/diagnóstico , Perda Auditiva/genética , Estados Unidos
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