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Aims: To investigate the association of methylation risk score (MRS) and its interactions with environmental factors with type 2 diabetes mellitus (T2DM) risk. Methods: We conducted a nested case–control study with 241 onset cases and 241 matched controls. Conditional logistic regression models were employed to identify risk CpG sites. Simple and weighted MRSs were constructed based on the methylation levels of ATP‐binding cassette G1 gene, fat mass and obesity associated gene, potassium voltage‐gated channel member 1 gene, and thioredoxin‐interacting protein gene previously associated with T2DM to estimate the association of MRS with T2DM risk. Stratified analyses were used to investigate interactions between MRS and environmental factors. Results: A total of 10 CpG loci were identified from the aforementioned genes to calculate MRS. After controlling for potential confounding factors, taking tertile 1 as reference, the odds ratios (ORs) and 95% confidence intervals (CIs) for T2DM of tertile 3 was 2.39 (1.36–4.20) for simple MRS and 2.59 (1.45–4.63) for weighted MRS. With per SD score increment in MRS, the OR (95% CI) was 1.66 (1.29–2.14) and 1.60 (1.24–2.08) for simple and weighted MRSs, respectively. J‐curved associations were observed between both simple and weighted MRSs and T2DM risks. Additionally, multiplication interactions for smoking and hypertension with simple MRS on the risk of T2DM were found, similarly for smoking and obesity with weighted MRS on the risk of T2DM (all Pinteraction <.05). Conclusion: Elevated simple and weighted MRSs were associated with increased risk of T2DM. Environmental risk factors may influence the association between MRS and T2DM. [ABSTRACT FROM AUTHOR]

Background: Proliferation, metabolism, tumor occurrence and development in gliomas are greatly influenced by RNA modifications. However, no research has integrated the four RNA methylation regulators of m6A, m1A, m5C and m7G in gliomas to analyze their relationship with glioma prognosis and intratumoral heterogeneity. Methods: Based on three in‐house single‐cell RNA‐sequencing (scRNA‐seq) data, the glioma heterogeneity and characteristics of m6A/m1A/m5C/m7G‐related regulators were elucidated. Based on publicly available bulk RNA‐sequencing (RNA‐seq) data, a risk‐score system for predicting the overall survival (OS) for gliomas was established by three machine learning methods and multivariate Cox regression analysis, and validated in an independent cohort. Results: Seven cell types were identified in gliomas by three scRNA‐seq data, and 22 m6A/m1A/m5C/m7G‐related regulators among the marker genes of different cell subtypes were discovered. Three m6A/m1A/m5C/m7G‐related regulators were selected to construct prognostic risk‐score model, including EIFA, NSUN6 and TET1. The high‐risk patients showed higher immune checkpoint expression, higher tumor microenvironment scores, as well as higher tumor mutation burden and poorer prognosis compared with low‐risk patients. Additionally, the area under the curve values of the risk score and nomogram were 0.833 and 0.922 for 3 year survival and 0.759 and 0.885 for 5 year survival for gliomas. EIF3A was significantly highly expressed in glioma tissues in our in‐house RNA‐sequencing data (p < 0.05). Conclusion: These findings may contribute to further understanding of the role of m6A/m1A/m5C/m7G‐related regulators in gliomas, and provide novel and reliable biomarkers for gliomas prognosis and treatment. [ABSTRACT FROM AUTHOR]

Background: This study used a bidirectional 2-sample Mendelian randomization study to investigate the potential causal links between mtDNA copy number and cardiometabolic disease (obesity, hypertension, hyperlipidaemia, type 2 diabetes [T2DM], coronary artery disease [CAD], stroke, ischemic stroke, and heart failure). Methods: Genetic associations with mtDNA copy number were obtained from a genome-wide association study (GWAS) summary statistics from the UK biobank (n = 395,718) and cardio-metabolic disease were from largest available GWAS summary statistics. Inverse variance weighting (IVW) was conducted, with weighted median, MR-Egger, and MR-PRESSO as sensitivity analyses. We repeated this in the opposite direction using instruments for cardio-metabolic disease. Results: Genetically predicted mtDNA copy number was not associated with risk of obesity (P = 0.148), hypertension (P = 0.515), dyslipidemia (P = 0.684), T2DM (P = 0.631), CAD (P = 0.199), stroke (P = 0.314), ischemic stroke (P = 0.633), and heart failure (P = 0.708). Regarding the reverse directions, we only found that genetically predicted dyslipidemia was associated with decreased levels of mtDNA copy number in the IVW analysis (β= − 0.060, 95% CI − 0.044 to − 0.076; P = 2.416e−14) and there was suggestive of evidence for a potential causal association between CAD and mtDNA copy number (β= − 0.021, 95% CI − 0.003 to − 0.039; P = 0.025). Sensitivity and replication analyses showed the stable findings. Conclusions: Findings of this Mendelian randomization study did not support a causal effect of mtDNA copy number in the development of cardiometabolic disease, but found dyslipidemia and CAD can lead to reduced mtDNA copy number. These findings have implications for mtDNA copy number as a biomarker of dyslipidemia and CAD in clinical practice. [ABSTRACT FROM AUTHOR]

Background: It's still controversial whether Helicobacter pylori (H. pylori) eradication can reverse atrophic gastritis (AG) and intestinal metaplasia (IM). Therefore, we performed a meta‐analysis to estimate the effect of H. pylori eradication on AG and IM. Methods: We searched the PubMed, Web of Science and EMBASE datasets through April 2023 for epidemiological studies, which provided mean glandular atrophy (GA) or IM score before and after H. pylori eradication, or provided ORs, RRs or HRs and 95% CIs for the association of AG or IM with H. pylori eradication. Weighted mean difference (WMD) and pooled ORs and 95%CIs were used to estimate the effect of H. pylori eradication on AG and IM. Results: Twenty articles with a total of 5242 participants were included in this meta‐analysis. H. pylori eradication significantly decreased GA score in the antrum (WMD −0.36; 95% CI: −0.52, −0.19, p < 0.01), GA score in the corpus (WMD −0.35; 95% CI: −0.52, −0.19, p < 0.01), IM score in the antrum (WMD −0.16; 95% CI: −0.26, −0.07, p < 0.01) and IM score in the corpus (WMD −0.20; 95% CI: −0.37, −0.04, p = 0.01). H. pylori eradication significantly improved AG (pooled OR 2.96; 95% CI: 1.70, 5.14, p < 0.01) and IM (pooled OR 2.41; 95% CI: 1.24, 4.70, p < 0.01). The association remained significant in the subgroup analyses by study design, sites of lesions, regions and follow‐up time. Although Publication bias was observed for AG, the association remained significant after trim‐and‐fill adjustment. Conclusions: H. pylori eradication could significantly improve AG and IM at early stage. [ABSTRACT FROM AUTHOR]

Context Mitochondrial DNA (mtDNA) plays a key role in diabetes mellitus and metabolic syndrome (MetS). An increasing number of studies have reported the association between mtDNA copy number (mtDNA-CN) and the risk of diabetes mellitus and MetS; however, the associations remain conflicted and a systematic review and meta-analysis on the association between mtDNA-CN and diabetes mellitus and MetS is lacking. Objective We aimed to investigate the association of mtDNA-CN and diabetes mellitus and MetS using a systematic review and meta-analysis of observational studies. Methods PubMed, EMBASE, and Web of Science were searched up to December 15, 2022. Random-effect models were used to summarize the relative risks (RRs) and 95% CIs. Results A total of 19 articles were included in the systematic review and 6 articles (12 studies) in the meta-analysis involving 21 714 patients with diabetes (318 870 participants) and 5031 MetS (15 040 participants). Compared to the highest mtDNA-CN, the summary RR (95% CIs) for the lowest mtDNA-CN were 1.06 (95% CI, 1.01-1.12; I2 = 79.4%; n = 8) for diabetes (prospective study: 1.11 (1.02-1.21); I2 = 22.6%; n = 4; case-control: 1.27 (0.66-2.43); I2 = 81.8%; n = 2; cross-sectional: 1.01 (0.99-1.03); I2 = 74.7%; n = 2), and 1.03 (0.99-1.07; I2 = 70.6%; n = 4) for MetS (prospective: 2.87 (1.51-5.48); I2 = 0; n = 2; cross-sectional: 1.02 (1.01-1.04); I2 = 0; n = 2). Conclusion Decreased mtDNA-CN was associated with increased risk of diabetes mellitus and MetS when limited to prospective studies. More longitudinal studies are warranted. [ABSTRACT FROM AUTHOR]

We aimed to investigate the association of metabolic obesity phenotypes with all-cause mortality risk in a rural Chinese population. This prospective cohort study enrolled 15 704 Chinese adults (38·86 % men) with a median age of 51·00 (interquartile range: 41·00–60·00) at baseline (2007–2008) and followed up during 2013–2014. Obesity was defined by waist circumference (WC: ≥ 90 cm for men and ≥ 80 cm for women) or waist-to-height ratio (WHtR: ≥ 0·5). The hazard ratio (HR) and 95 % CI for the risk of all-cause mortality related to metabolic obesity phenotypes were calculated using the Cox hazards regression model. During a median follow-up of 6·01 years, 864 deaths were identified. When obesity was defined by WC, the prevalence of participants with metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically unhealthy obesity (MUO) at baseline was 12·12 %, 2·80 %, 41·93 % and 43·15 %, respectively. After adjusting for age, sex, alcohol drinking, smoking, physical activity and education, the risk of all-cause mortality was higher with both MUNO (HR = 1·20, 95 % CI 1·14, 1·26) and MUO (HR = 1·20, 95 % CI 1·13, 1·27) v. MHNO, but the risk was not statistically significant with MHO (HR = 0·99, 95 % CI 0·89, 1·10). This result remained consistent when stratified by sex. Defining obesity by WHtR gave similar results. MHO does not suggest a greater risk of all-cause mortality compared to MHNO, but participants with metabolic abnormality, with or without obesity, have a higher risk of all-cause mortality. These results should be cautiously interpreted as the representation of MHO is small. [ABSTRACT FROM AUTHOR]