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ABSTRACT Background and Aims CircRNAs and autophagy are closely involved in the physiological and pathological processes of ovarian cancer; however, their exact mechanisms are still undetermined. This investigation aimed to elucidate the function and associated pathways of circFAM188A, which modulates proliferation, autophagy, and invasion in ovarian cancer (EOC). Methods The expression of circFAM188A in the tissues of EOC patients was assessed via RT‐PCR. To elucidate proliferation, invasion, and autophagy in the tumor cells, Transwell, 5‐ethynyl‐2′‐deoxyuridine (EdU), and mRFP‐GFP‐LC3 reporter assays were conducted. The binding sites between circ‐FAM188A and the miR‐670‐3p, miR‐670‐3p and YY1 were predicted using bioinformatics and verified by dual‐luciferase reporter assays. Pulldown assays demonstrated binding between ULK1 and circ‐FAM188A. ULK1 was found to be crucial in the initial stage of autophagy. Moreover, an in vivo xenograft model was established by subcutaneous injection of nude mice with EOC cells. Result Expression of circ‐FAM188A was increased in EOC tissues relative to normal ovarian tissues and circ‐FAM188A overexpression promoted proliferation, invasion, and autophagy; these effects were reversed by circ‐FAM188A silencing. miR‐670‐3p and circ‐FAM188A co‐localized in the cytoplasm. circ‐FAM188A enhanced YY1 expression by sponging miR‐670‐3p and was also shown to interact with ULK1. Conclusion It is thus suggested that circ‐FAM188A modulates autophagy by sponging miR‐670‐3p as well as interacting with ULK1.

Abstract. Background:. While type 2 diabetes mellitus (T2DM) is considered a putative causal risk factor for coronary artery disease (CAD), the intrinsic link underlying T2DM and CAD is not fully understood. We aimed to highlight the importance of integrated care targeting both diseases by investigating the phenotypic and genetic relationships between T2DM and CAD. Methods:. We evaluated phenotypic associations using data from the United Kingdom Biobank (N = 472,050). We investigated genetic relationships by leveraging genomic data conducted in European ancestry for T2DM, with and without adjustment for body mass index (BMI) (T2DM: Ncase/Ncontrol = 74,124/824,006; T2DM adjusted for BMI [T2DMadjBMI]: Ncase/Ncontrol = 50,409/523,897) and for CAD (Ncase/Ncontrol = 181,522/984,168). We performed additional analyses using genomic data conducted in multiancestry individuals for T2DM (Ncase/Ncontrol = 180,834/1,159,055). Results:. Observational analysis suggested a bidirectional relationship between T2DM and CAD (T2DM→CAD: hazard ratio [HR] = 2.12, 95% confidence interval [CI]: 2.01–2.24; CAD→T2DM: HR = 1.72, 95% CI: 1.63–1.81). A positive overall genetic correlation between T2DM and CAD was observed (rg = 0.39, P = 1.43 × 10–75), which was largely independent of BMI (T2DMadjBMI–CAD: rg = 0.31, P = 1.20 × 10–36). This was corroborated by six local signals, among which 9p21.3 showed the strongest genetic correlation. Cross-trait meta-analysis replicated 101 previously reported loci and discovered six novel pleiotropic loci. Mendelian randomization analysis supported a bidirectional causal relationship (T2DM→CAD: odds ratio [OR] = 1.13, 95% CI: 1.11–1.16; CAD→T2DM: OR = 1.12, 95% CI: 1.07–1.18), which was confirmed in multiancestry individuals (T2DM→CAD: OR = 1.13, 95% CI: 1.10–1.16; CAD→T2DM: OR = 1.08, 95% CI: 1.04–1.13). This bidirectional relationship was significantly mediated by systolic blood pressure and intake of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, with mediation proportions of 54.1% (95% CI: 24.9–83.4%) and 90.4% (95% CI: 29.3–151.5%), respectively. Conclusion:. Our observational and genetic analyses demonstrated an intrinsic bidirectional relationship between T2DM and CAD and clarified the biological mechanisms underlying this relationship.

Background Pneumoconiosis mostly combines pulmonary and cardiovascular diseases, among which pulmonary heart disease (PHD) is of major concern due to its significant impact on the survival of pneumoconiosis patients. White cell count (WCC), red cell distribution width (RDW) and platelet parameters are thought to affect inflammatory responses and may be predictors of various cardiovascular diseases. However, very few studies have focused on PHD.Objectives To examine the relationship between baseline complete blood count parameters (WCC, RDW, platelet parameters) and the risk of incident PHD in pneumoconiosis patients.Design A retrospective cohort study.Setting This was a single-centre, retrospective cohort study that used data from an Occupational Disease Hospital, Chengdu, Sichuan.Participants A total of 946 pneumoconiosis patients from January 2012 to November 2021 were included in the study. Female patients and patients who had PHD, coronary heart disease, hypertensive heart disease, cardiomyopathy, heart failure, oncological disease, multiple organ dysfunction, AIDS at baseline and follow-up time of less than 6 months were also excluded.Outcome measures We identified PHD according to the patient’s discharge diagnosis. We constructed Cox proportional hazard regression models to assess the HR of incident PHD in pneumoconiosis, as well as 95% CIs.Results In the multiple Cox proportional hazard regression analysis, platelet count (PLT) and plateletcrit (PCT) above the median at baseline were associated with an increased risk of PHD in pneumoconiosis with adjusted HR of 1.52 (95% CI 1.09 to 2.12) and 1.42 (95% CI 1.02 to 1.99), respectively.Conclusion Higher baseline PLT and PCT are associated with a higher risk of PHD in pneumoconiosis.

BackgroundThe incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses.Methods and findingsWe searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian-Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices.ConclusionsIn this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking.

BackgroundThe relationship between type 2 diabetes mellitus (T2DM) and gallstone disease (GSD) have been incompletely understood. We aimed to investigate their phenotypic and genetic associations and evaluate the biological mechanisms underlying these associations.MethodsWe first evaluated the phenotypic association between T2DM and GSD using data from the UK Biobank (n>450,000) using a prospective observational design. We then conducted genetic analyses using summary statistics from a meta-analysis of genome-wide association studies of T2DM, with and without adjusting for body mass index (BMI) (Ncase=74,124, Ncontrol=824,006; T2DMadjBMI: Ncase=50,409, Ncontrol=523,897) and GSD (Ncase=43,639, Ncontrol=506,798).ResultsA unidirectional phenotypic association was observed, where individuals with T2DM exhibited a higher GSD risk (hazard ratio (HR)=1.39, P