Predictors of High Cardiovascular Risk Among Nonobese Patients with Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease in a Chinese Population.

Purpose: This study aims to investigate cardiovascular risk factors in nonobese patients with type 2 diabetes (T2DM) and non-alcoholic fatty liver disease (NAFLD) and to determine whether they might be used to predict high-risk individuals effectively. Patients and Methods: This cross-sectional study included 245 nonobese patients with T2DM who underwent FibroTouch in the National Metabolic Management Center of the Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University from January 2021 to December 2022. All individuals were divided into NAFLD and non-NAFLD groups. Patients with NAFLD were further grouped by UAP tertiles (T1, T2 and T3). We created a Cardiovascular Score (total scale: 0-5 points; ≥3 points was defined as high-risk individual) based on baPWV, carotid ultrasound, and urinary microalbumin creatinine ratio (UA/CR) to assess the risk of cardiovascular disease in non-obese T2DM patients with NAFLD. Risk factors were evaluated using univariate and multivariate analysis. The performance of risk factors was compared according to the area under the receiver operating characteristic (ROC) curve. Results: Atherogenic index of plasma (AIP), atherosclerosis index (AI), prevalence of hypertension, body mass index (BMI) and homeostatic model assessment of insulin resistance (HOMA-IR) were higher in the NAFLD group compared to the non-NAFLD group. In T3 group, AIP, AI, BMI and HOMA-IR were higher than those of T1 group. Multivariate logistic regression showed that age, systolic blood pressure, low-density lipoprotein-cholesterol (LDL-C) and AIP were risk factors for cardiovascular disease among nonobese patients with T2DM and NAFLD. The area under the ROC curve for age, systolic blood pressure, LDL-C and AIP were 0.705, 0.688, 0.738 and 0.642, respectively. The area under the ROC curve was 0.895 when combining them. Conclusion: Age, systolic blood pressure, AIP and LDL-C are all independent risk factors for cardiovascular disease in non-obese individuals with T2DM and NAFLD, which can be combined to identify high-risk populations and carry out intervention.

Polycyclic aromatic hydrocarbons exposure and plasma lncRNA signature: A profile and functional analysis.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants that pose detrimental effects on human health, and the exploration of the associations of PAHs exposure with long non-coding RNA (lncRNA) may provide novel clues to the underlying mechanisms. In the present study, we detected 10 urinary PAHs metabolites by GC-MS and plasma lncRNAs levels by Human LncRNA Array v4 among 230 participants from two panels (160 in the Shiyan panel and 70 in the Wuhan-Zhuhai panel). We applied linear regression models to assess the associations between PAHs metabolites and lncRNAs separately in each panel and combined the results using fixed-effect meta-analysis. To explore the potential origin of PAHs-related lncRNAs in plasma, we estimated their tissue-specificity and associations between lncRNAs levels in plasma and leukocytes. Leukocytes mRNA sequencing data and RNA binding proteins were utilized to explore implicated pathways of identified lncRNAs. We found that urinary 1-hydroxyphenanthrene (1-OH-Phe) was inversely associated with 8 lncRNAs and positively associated with 1 lncRNA, as well as 9-hydroxyphenanthrene (9-OH-Phe) was inversely associated with 11 lncRNAs (FDR < 0.1). Tissue specificity analysis using Genome Tissue Expression database suggested that several identified lncRNAs might specifically express in organs targeted by PAHs exposure (lung, liver, heart, kidney, and brain). Besides, plasma levels of 1-OH-Phe related ENSG00000260616 and 9-OH-Phe related STARD4-AS1 were inversely associated with their intra-leukocytes levels (P value < 0.05). Notably, STARD4-AS1 was positively associated with the expression levels of its neighboring protein-coding gene (CAMK4 and STARD4) in leukocytes and were involved in pathways related to cellular response to DNA damage, which we further confirmed using DNA damage biomarker, 8-hydroxydeoxyguanosine. Functional analysis also revealed vital pathways related to cytokine-mediated signaling and glucose homeostasis. Our findings provided novel insights into plausible biological mechanisms underlying the adverse effects of PAHs exposure.

Circulating metals, leukocyte microRNAs and microRNA networks: A profiling and functional analysis in Chinese adults.

BACKGROUND: Metals in the human body represent both environmental exposure and nutritional status. Little is known about the miRNA signature in relation to circulating metals in humans. OBJECTIVES: To characterize metal-associated miRNAs in leukocytes, individually and collectively as networks. METHODS: In a panel of 160 Chinese adults, we measured 23 metals/metalloids in plasma, and sequenced miRNAs and mRNAs in leukocytes. We used linear regression to model the associations between ln-transformed metal concentrations and normalized miRNA levels adjusting for potential confounders. We inferred the enriched leukocyte subtypes for the identified miRNAs using an association approach. We utilized mRNA sequencing data to explore miRNA functions. We also constructed modules to identify metal-associated miRNA networks. RESULTS: We identified 55 metal-associated miRNAs at false discovery rate-adjusted P < 0.05. In particular, we found that lead, nickel, and vanadium were positively associated with potentially lymphocyte-enriched miR-142-3p, miR-150-3p, miR-28-5p, miR-361-3p, and miR-769-5p, and were inversely associated with potentially granulocyte-enriched let-7a/c/d-5p and miR-1294. Interestingly, the five lymphocyte-enriched miRNAs inhibited, whereas miR-1294 activated, ROS and DNA repair pathways. We further confirmed the findings using oxidative damage biomarkers. Next, we clustered co-expressed miRNAs into modules, and identified four miRNA modules that were associated with different metals. The identified modules represented miRNAs enriched in different leukocyte subtypes, and were involved in biological processes including hematopoiesis and immune response, mitochondrial functions, and response to the stimulus. CONCLUSIONS: At commonly exposed low levels, circulating metals were associated with distinct miRNA signatures in leukocytes. The identified miRNAs, individually or as regulatory networks, may provide a mechanistic link between metal exposure and pathophysiological changes in the immune system.