Polycystic ovary syndrome (PCOS) is a common metabolic disorder in women. To identify causative genes, we conducted a genome-wide association study (GWAS) of PCOS in Han Chinese. The discovery set included 744 PCOS cases and 895 controls; subsequent replications involved two independent cohorts (2,840 PCOS cases and 5,012 controls from northern Han Chinese; 498 cases and 780 controls from southern and central Han Chinese). We identified strong evidence of associations between PCOS and three loci: 2p16.3 (rs13405728; combined P-value by meta-analysis P(meta) = 7.55 × 10⁻²¹, odds ratio (OR) 0.71); 2p21 (rs13429458, P(meta) = 1.73 × 10⁻²³, OR 0.67); and 9q33.3 (rs2479106, P(meta) = 8.12 × 10⁻¹⁹, OR 1.34). These findings provide new insight into the pathogenesis of PCOS. Follow-up studies of the candidate genes in these regions are recommended.

Following a previous genome-wide association study (GWAS 1) including 744 cases and 895 controls, we analyzed genome-wide association data from a new cohort of Han Chinese (GWAS 2) with 1,510 polycystic ovary syndrome (PCOS) cases and 2,016 controls. We followed up significantly associated signals identified in the combined results of GWAS 1 and 2 in a total of 8,226 cases and 7,578 controls. In addition to confirming the three loci we previously reported, we identify eight new PCOS association signals at P < 5 × 10(-8): 9q22.32, 11q22.1, 12q13.2, 12q14.3, 16q12.1, 19p13.3, 20q13.2 and a second independent signal at 2p16.3 (the FSHR gene). These PCOS association signals show evidence of enrichment for candidate genes related to insulin signaling, sexual hormone function and type 2 diabetes (T2D). Other candidate genes were related to calcium signaling and endocytosis. Our findings provide new insight and direction for discovering the biological mechanisms of PCOS.

Registered in the Chinese Clinical Trial Registry (ChiCTR-ONB-15007464).

Background Only few pathogens that cause lower respiratory tract infections (LRTIs) can be identified due to limitations of traditional microbiological methods and the complexity of the oropharyngeal normal flora. Metagenomic next-generation sequencing (mNGS) has the potential to solve this problem. Methods This prospective observational study sequentially enrolled 93 patients with LRTI and 69 patients without LRTI who visited Peking University People’s Hospital in 2019. Pathogens in bronchoalveolar lavage fluid (BALF) specimens were detected using mNGS (DNA and RNA) and traditional microbiological assays. Human transcriptomes were compared between LRTI and non-LRTI, bacterial and viral LRTI, and tuberculosis and nontuberculosis groups. Results Among 93 patients with LRTI, 20%, 35%, and 65% of cases were detected as definite or probable pathogens by culture, all microbiological tests, and mNGS, respectively. Our in-house BALF mNGS platform had an approximately 2-working-day turnaround time and detected more viruses and fungi than the other methods. Taking the composite reference standard as a gold standard, it had a sensitivity of 66.7%, specificity of 75.4%, positive-predictive value of 78.5%, and negative-predictive value of 62.7%. LRTI-, viral LRTI–, and tuberculosis-related differentially expressed genes were respectively related to immunity responses to infection, viral transcription and response to interferon-γ pathways, and perforin 1 and T-cell receptor B variable 9. Conclusions Metagenomic DNA and RNA-seq can identify a wide range of LRTI pathogens, with improved sensitivity for viruses and fungi. Our in-host platform is likely feasible in the clinic. Host transcriptome data are expected to be useful for the diagnosis of LRTIs.

Aims/Introduction: This study aimed to evaluate the association between time in range (TIR) obtained from continuous glucose monitoring and the prevalence and degree of painful diabetic neuropathy. Materials and Methods: A total of 364 individuals with diabetic peripheral neuropathy were enrolled in this study. Sensor-based flash glucose monitoring systems were used to monitor the participants' glucose levels, and the glycemic variability metrics were calculated, including the TIR, glucose coefficient of variation, standard deviation and the mean amplitude of glycemic excursions. The participants were asked to record any form of pain during the 2 weeks of monitoring, and score the pain every day on a numerical rating scale. Based on the numerical rating scale, the patients were divided into the pain-free group, mild pain group and moderate/severe pain group. Results: Overall, 51.92% (189/364) of the participants were diagnosed with painful diabetic neuropathy. Compared with the pain-free group, the level of TIR decreased significantly in the mild pain and moderate/severe pain groups (P < 0.05). The prevalence of mild pain and moderate/severe pain decreased with increasing TIR quartiles (all P < 0.05). Multiple linear regression analysis showed that TIR was significantly negatively correlated with the numerical rating scale score after adjustment for glycated hemoglobin, glycemic variability indicators and other risk factors (P < 0.05). Logistic regression analysis showed that a decreasing level of TIR was significantly associated with an increasing risk of any pain and moderate/severe pain (P < 0.05). Conclusions: TIR is correlated with painful diabetic neuropathy and is underscored as a valuable clinical evaluation measure.