Interpretable machine learning identifies metabolites associated with glomerular filtration rate in type 2 diabetes patients.

Objective: The co-occurrence of kidney disease in patients with type 2 diabetes (T2D) is a major public health challenge. Although early detection and intervention can prevent or slow down the progression, the commonly used estimated glomerular filtration rate (eGFR) based on serum creatinine may be influenced by factors unrelated to kidney function. Therefore, there is a need to identify novel biomarkers that can more accurately assess renal function in T2D patients. In this study, we employed an interpretable machine-learning framework to identify plasma metabolomic features associated with GFR in T2D patients. Methods: We retrieved 1626 patients with type 2 diabetes (T2D) in Liaoning Medical University First Affiliated Hospital (LMUFAH) as a development cohort and 716 T2D patients in Second Affiliated Hospital of Dalian Medical University (SAHDMU) as an external validation cohort. The metabolite features were screened by the orthogonal partial least squares discriminant analysis (OPLS-DA). We compared machine learning prediction methods, including logistic regression (LR), support vector machine (SVM), random forest (RF), and eXtreme Gradient Boosting (XGBoost). The Shapley Additive exPlanations (SHAP) were used to explain the optimal model. Results: For T2D patients, compared with the normal or elevated eGFR group, glutarylcarnitine (C5DC) and decanoylcarnitine (C10) were significantly elevated in GFR mild reduction group, and citrulline and 9 acylcarnitines were also elevated significantly (FDR<0.05, FC > 1.2 and VIP > 1) in moderate or severe reduction group. The XGBoost model with metabolites had the best performance: in the internal validate dataset (AUROC=0.90, AUPRC=0.65, BS=0.064) and external validate cohort (AUROC=0.970, AUPRC=0.857, BS=0.046). Through the SHAP method, we found that C5DC higher than 0.1µmol/L, Cit higher than 26 µmol/L, triglyceride higher than 2 mmol/L, age greater than 65 years old, and duration of T2D more than 10 years were associated with reduced GFR. Conclusion: Elevated plasma levels of citrulline and a panel of acylcarnitines were associated with reduced GFR in T2D patients, independent of other conventional risk factors.

Identification of UDP-glucuronosyltransferase (UGT) isoforms involved in the metabolism of Chlorophenols (CPs).

Chlorophenols (CPs) are a group of pollutants that pose a great threat to the environment, they are widely used in industrial and agricultural wastes, pesticides, herbicides, textiles, pharmaceuticals and plastics. Among CPs, pentachlorophenol was listed as one of the persistent organic pollutants (POPs) by the Stockholm convention. This study aims to identify the UDP-glucosyltransferase (UGT) isoforms involved in the metabolic elimination of CPs. CPs' mono-glucuronide was detected in the human liver microsomes (HLMs) incubation mixture with co-factor uridine-diphosphate glucuronic acid (UDPGA). HLMs-catalyzed glucuronidation metabolism reaction equations followed Michaelis-Menten or substrate inhibition type. Recombinant enzymes and chemical reagents inhibition experiments were utilized to phenotype the main UGT isoforms involved in the glucuronidation of CPs. UGT1A6 might be the major enzyme in the glucuronidation of mono-chlorophenol isomer. UGT1A1, UGT1A6, UGT1A9, UGT2B4 and UGT2B7 were the most important five UGT isoforms for metabolizing the di-chlorophenol and tri-chlorophenol isomers. UGT1A1 and UGT1A3 were the most important UGT isoforms in the catalysis of tetra-chlorophenol and pentachlorophenol isomers. Species differences were investigated using rat liver microsomes (RLMs), pig liver microsomes (PLMs), dog liver microsomes (DLMs), and monkey liver microsomes (MyLMs). All these results were helpful for elucidating the metabolic elimination and toxicity of CPs.

Explainable Machine Learning-Based Prediction Model for Diabetic Nephropathy.

The aim of this study is to analyze the effect of serum metabolites on diabetic nephropathy (DN) and predict the prevalence of DN through a machine learning approach. The dataset consists of 548 patients from April 2018 to April 2019 in the Second Affiliated Hospital of Dalian Medical University (SAHDMU). We select the optimal 38 features through a least absolute shrinkage and selection operator (LASSO) regression model and a 10-fold cross-validation. We compare four machine learning algorithms, including extreme gradient boosting (XGB), random forest, decision tree, and logistic regression, by AUC-ROC curves, decision curves, and calibration curves. We quantify feature importance and interaction effects in the optimal predictive model by Shapley additive explanation (SHAP) method. The XGB model has the best performance to screen for DN with the highest AUC value of 0.966. The XGB model also gains more clinical net benefits than others, and the fitting degree is better. In addition, there are significant interactions between serum metabolites and duration of diabetes. We develop a predictive model by XGB algorithm to screen for DN. C2, C5DC, Tyr, Ser, Met, C24, C4DC, and Cys have great contribution in the model and can possibly be biomarkers for DN.

The association between plasma free amino acids and type 2 diabetes mellitus complicated with infection in Chinese patients.

BACKGROUND: Type 2 diabetes mellitus (T2DM), one of the most common public diseases threatening human health, is always accompanied by infection. Though there are still a variety of flaws in the treatment of some infectious diseases, metabolomics provides a fresh perspective to explore the relationship between T2DM and infection. Our research aimed to investigate the association between plasma free amino acids (PFAAs) and T2DM complicated with infection in Chinese patients. METHODS: A cross-sectional study was conducted from May 2015 to August 2016. We retrieved the medical records of 1032 inpatients with T2DM from Liaoning Medical University First Affiliated Hospital and we used mass spectrometry to quantify 23 PFAAs. Infections contained 15 individual categories that could be retrieved from the database. Principal component analysis was used to extract factors of PFAAs. Multi-variable binary logistic regression was used to obtain odds ratios (OR) and their 95% confidence intervals (CI). RESULTS: Among 1032 inpatients,109 (10.6%) had infectious diseases. Six factors, accounting for 68.6% of the total variance, were extracted. Factor 4 consisted of Glu, Asp and Orn. Factor 5 consisted of Hcy and Pip. After adjusting for potential confounders, factor 4 was positively correlated with T2DM complicated with infection in Chinese T2DM patients (OR: 1.27, 95%CI: 1.06-1.52). Individual Hcy in factor 5 was positively associated with T2DM complicated with infection (OR: 1.33, 95%CI: 1.08-1.64). Furthermore, factor 4 (OR: 1.44, 95%CI: 1.11-1.87), Orn (OR: 1.01, 95%CI: 1.00-1.02) and Hcy (OR: 1.56, 95%CI: 1.14-3.14) were positively associated with bacterial infection in Chinese T2DM patients, while factor 5 (OR: 0.71, 95%CI: 0.50-1.00) was negatively associated with bacterial infection. CONCLUSIONS: Urea cycle-related metabolites (Orn, Asp, Glu) and Hcy were positively associated with T2DM complicated with infection in China. Orn and Hcy were positively associated with bacterial infection in T2DM patients in China.

Effect of passive smoking exposure on risk of type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies.

Objective: The effect of passive smoking exposure on the risk of type 2 diabetes has not been systematically studied. A meta-analysis was conducted to assess the association between passive smoking exposure and the risk of diabetes. Methods: We searched three major databases up to 31 October 2022 to identify relevant prospective cohort studies on the association between passive smoking and the risk of type 2 diabetes. The pooled relative risk (RR) and 95% confidence interval (CI) for the association between passive smoking exposure and the risk of type 2 diabetes were analyzed using a fixed-effect model. Results: Ten prospective cohort studies were included in this meta-analysis, with a total of 251,620 participants involved. The pooled RR showed a significantly positive association between nonsmokers exposed to passive smoking and type 2 diabetes as compared to non-smokers who were not exposed to passive smoking [RR = 1.27; 95% CI (1.19, 1.36); p < 0.001]. Sensitivity analysis indicated that the pooled RR was not substantially affected by any of the individual studies. Conclusion: Exposure to passive smoking increases the risk of type 2 diabetes. This study may have a positive effect on the prevention of type 2 diabetes. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023372532.

Relationship between plasma glutamate and cardiovascular disease risk in Chinese patients with type 2 diabetes mellitus by gender.

Objectives: This study aimed to assess the association between plasma glutamate (Glu) and the risk of cardiovascular disease (CVD) in patients with type 2 diabetes mellitus (T2DM) and whether this association differs by gender. Material and methods: We retrieved clinical information on 1032 consecutive patients with T2DM from a same tertiary care center from May 2015 to August 2016. Glu was quantified by liquid chromatography-tandem mass spectrometry analysis. Glu was converted into a categorical variable based on the median concentration in the whole population, while logistic regression was used to obtain the odds ratio (OR) and 95% confidence interval (CI), and the correlation between Glu and various biochemical indices was analyzed. Results: We found that Glu was positively associated with the risk of CVD in patients with T2DM. This correlation was more significant in women. In T2DM patients, the higher the age, body mass index (BMI), weight and systolic blood pressure (SBP), the lower the glycosylated hemoglobin (HbA1C) concentration and the higher the Glu. In female patients, the correlation between age, weight, BMI, SBP, and plasma Triglycerides (TG), and Glu was also statistically significant. Conclusion: In conclusion, female T2DM patients with high levels of Glu have a higher risk of developing CVD.

A Metabolism-Based Interpretable Machine Learning Prediction Model for Diabetic Retinopathy Risk: A Cross-Sectional Study in Chinese Patients with Type 2 Diabetes.

The burden of diabetic retinopathy (DR) is increasing, and the sensitive biomarkers of the disease were not enough. Studies have found that the metabolic profile, such as amino acid (AA) and acylcarnitine (AcylCN), in the early stages of DR patients might have changed, indicating the potential of metabolites to become new biomarkers. We are amid to construct a metabolite-based prediction model for DR risk. This study was conducted on type 2 diabetes (T2D) patients with or without DR. Logistic regression and extreme gradient boosting (XGBoost) prediction models were constructed using the traditional clinical features and the screening features, respectively. Assessing the predictive power of the models in terms of both discrimination and calibration, the optimal model was interpreted using the Shapley Additive exPlanations (SHAP) to quantify the effect of features on prediction. Finally, the XGBoost model incorporating AA and AcylCN variables had the best comprehensive evaluation (ROCAUC = 0.82, PRAUC = 0.44, Brier score = 0.09). C18 : 1OH lower than 0.04 µmol/L, C18 : 1 lower than 0.70 µmol/L, threonine higher than 27.0 µmol/L, and tyrosine lower than 36.0 µmol/L were associated with an increased risk of developing DR. Phenylalanine higher than 52.0 µmol/L was associated with a decreased risk of developing DR. In conclusion, our study mainly used AAs and AcylCNs to construct an interpretable XGBoost model to predict the risk of developing DR in T2D patients which is beneficial in identifying high-risk groups and preventing or delaying the onset of DR. In addition, our study proposed possible risk cut-off values for DR of C18 : 1OH, C18 : 1, threonine, tyrosine, and phenylalanine.

Prevalence of Diabetic Retinopathy and Use of Common Oral Hypoglycemic Agents Increase the Risk of Diabetic Nephropathy-A Cross-Sectional Study in Patients with Type 2 Diabetes.

OBJECTIVE: This study investigated the effect of amino acid metabolism on the risk of diabetic nephropathy under different conditions of the diabetic retinopathy, and the use of different oral hypoglycemic agents. METHODS: This study retrieved 1031 patients with type 2 diabetes from the First Affiliated Hospital of Liaoning Medical University in Jinzhou, which is located in Liaoning Province, China. We conducted a spearman correlation study between diabetic retinopathy and amino acids that have an impact on the prevalence of diabetic nephropathy. Logistic regression was used to analyze the changes of amino acid metabolism in different diabetic retinopathy conditions. Finally, the additive interaction between different drugs and diabetic retinopathy was explored. RESULTS: It is showed that the protective effect of some amino acids on the risk of developing diabetic nephropathy is masked in diabetic retinopathy. Additionally, the additive effect of the combination of different drugs on the risk of diabetic nephropathy was greater than that of any one drug alone. CONCLUSIONS: We found that diabetic retinopathy patients have a higher risk of developing diabetic nephropathy than the general type 2 diabetes population. Additionally, the use of oral hypoglycemic agents can also increase the risk of diabetic nephropathy.

Associations of serum amino acids related to urea cycle with risk of chronic kidney disease in Chinese with type 2 diabetes.

Objective: Serum levels of amino acids related to urea cycle are associated with risk of type 2 diabetes mellitus (T2DM). Our study aimed to explore whether serum levels of amino acids related to urea cycle, i.e., arginine, citrulline, and ornithine, are also associated with increased risk of chronic kidney disease (CKD) in T2DM. Methods: We extracted medical records of 1032 consecutive patients with T2DM from the Electronic Administrative System of Liaoning Medical University First Affiliated Hospital (LMUFAH) system from May 2015 to August 2016. Of them, 855 patients with completed data available were used in the analysis. CKD was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2. Serum amino acids were measured by mass spectrometry (MS) technology. Binary logistic regression was performed to obtain odds ratios (ORs) and their 95% confidence intervals (CIs). Results: 52.3% of the 855 T2DM patients were male, and 143 had CKD. In univariable analysis, high serum citrulline, high ratio of arginine to ornithine, and low ratio of ornithine to citrulline were associated with markedly increased risk of CKD (OR of top vs. bottom tertile: 2.87, 95%CI, 1.79-4.62 & 1.98, 95%CI,1.25-3.14 & 2.56, 95%CI, 1.61-4.07, respectively). In multivariable analysis, the ORs of citrulline and ornithine/citrulline ratio for CKD remained significant (OR of top vs. bottom tertile: 2.22, 95%CI, 1.29-3.82 & 2.24, 1.29-3.87, respectively). Conclusions: In Chinese patients with T2DM, high citrulline and low ornithine/citrulline ratio were associated with increased risk of CKD.

Inhibition of human sulfotransferases (SULTs) by per- and polyfluoroalkyl substances (PFASs) and structure-activity relationship.

Per- and polyfluoroalkyl substances (PFASs) are a family of highly fluorinated aliphatic substances widely used in industrial and commercial applications. This study aims to determine the inhibition of PFASs towards sulfotransferases (SULTs) activity, and trying to explain the toxicity mechanism of PFASs. In vitro recombinant SULTs-catalyzed sulfation of p-nitrophenol (PNP) was utilized as a probe reaction. The incubation system was consisted of PFASs, SULTs, PNP, 3'-phosphoadenosine-5'-phosphosulfate, MgCl2 and Tris-HCl buffer. Ultra-performance liquid chromatography was employed for analysis of the metabolites. All tested PFASs showed inhibition towards SULTs. The longer the carbon chain length of the PFASs terminated with -COOH, the higher is its capability of inhibiting SULT1A3. PFASs with -SO3H had a relatively higher ability to inhibit SULT1A3 activity than those with -COOH, -I and -OH. The inhibition kinetic parameter was 2.16 and 1.42 µM for PFOS-SULT1A1, PFTA-SULT1B1. In vitro in vivo extrapolation showed that the concentration of PFOS and PFTA in human matrices might be higher than the threshold for inducing inhibition of SULTs. Therefore, PFASs could interfere with the metabolic pathways catalyzed by SULTs in vivo. All these results will help to understand the toxicity of PFASs from the perspective of metabolism.

Hepatic thyroid hormone signalling modulates glucose homeostasis through the regulation of GLP-1 production via bile acid-mediated FXR antagonism.

Thyroid hormones (TH) regulate systemic glucose metabolism through incompletely understood mechanisms. Here, we show that improved glucose metabolism in hypothyroid mice after T3 treatment is accompanied with increased glucagon-like peptide-1 (GLP-1) production and insulin secretion, while co-treatment with a GLP-1 receptor antagonist attenuates the effects of T3 on insulin and glucose levels. By using mice lacking hepatic TH receptor ß (TRß) and a liver-specific TRß-selective agonist, we demonstrate that TRß-mediated hepatic TH signalling is required for both the regulation of GLP-1 production and the insulinotropic and glucose-lowering effects of T3. Moreover, administration of a liver-targeted TRß-selective agonist increases GLP-1 and insulin levels and alleviates hyperglycemia in diet-induced obesity. Mechanistically, T3 suppresses Cyp8b1 expression, resulting in increased the levels of Farnesoid X receptor (FXR)-antagonistic bile acids, thereby potentiating GLP-1 production and insulin secretion by repressing intestinal FXR signalling. T3 correlates with both plasma GLP-1 and fecal FXR-antagonistic bile acid levels in people with normal thyroid function. Thus, our study reveals a role for hepatic TH signalling in glucose homeostasis through the regulation of GLP-1 production via bile acid-mediated FXR antagonism.

The Association of Homocysteine and Diabetic Retinopathy in Homocysteine Cycle in Chinese Patients With Type 2 Diabetes.

Objective: This study aimed to explore the relationship between homocysteine (Hcy) and diabetic retinopathy (DR) and the impacts of the Hcy pathway on this relationship against this background. Methods: This study retrieved 1979 patients with type 2 diabetes (T2D) from the First Affiliated Hospital of Liaoning Medical University in Jinzhou, Liaoning Province, China. Multiple logistic regression was used to analyze the effects of Hcy cycle on the relationship between Hcy and DR. Spearman's rank correlation analysis was used to analyze the correlation between risk factors related to DR progression and Hcy. Finally, the results of logistic regression were supplemented by mediation analysis. Results: We found there was a negative correlation between low concentration of Hcy and DR (OR : 0.83, 95%CI: 0.69-1). After stratifying all patients by cysteine (Cys) or Methionine (Met), this relationship remained significant only in low concentration of Cys (OR: 0.75, 95%CI: 0.61-0.94). Through the RCS curve, we found that the effect of Hcy on DR presents a U-shaped curve relationship. Mediating effect in Met and Hcy cycles was also significant [Total effect c (OR: 0.968, 95%CI: 0.938-0.998), Direct effect path c' (OR: 0.969, 95%CI: 0.940-0.999), Path a (OR: 1.047, 95%CI: 1.004-1.091), Path b (OR: 0.964, 95%CI: 0.932-0.998)]. Conclusions: The relationship between Hcy and DR presents a U-shaped curve and the homocysteine cycle pathway has an impact on it. And too low concentration of Hcy indicates a lack of other substances, such as vitamins. It is suggested that the progression of DR is the result of a combination of many risk factors. Further prospective studies are needed to determine the role of Hcy in the pathogenesis of DR.

Relationship Between Acylcarnitine and the Risk of Retinopathy in Type 2 Diabetes Mellitus.

Objective: Diabetic retinopathy is a common complication of type 2 diabetes mellitus (T2DM). Due to the limited effectiveness of current prevention and treatment methods, new biomarkers are urgently needed for the prevention and diagnosis of DR. This study aimed to explore the relationships between plasma acylcarnitine with DR in T2DM. Methods: From May 2015 to August 2016, data of 1032 T2DM patients were extracted from tertiary hospitals. Potential non-linear associations were tested by binary logistic regression models, and ORs and 95% CIs of the research variables were obtained. Correlation heat map was used to analyze the correlation between variables. The change of predictive ability was judged by the area under the receiver operating characteristic curve. Results: Of the 1032 patients with T2DM, 162 suffered from DR. After adjusting for several confounding variables, C2 (OR:0.55, 95%CI:0.39-0.76), C14DC (OR:0.64, 95%CI:0.49-0.84), C16 (OR:0.64, 95%CI:0.49-0.84), C18:1OH (OR:0.51, 95%CI:0.36-0.71) and C18:1 (OR:0.60, 95%CI:0.44-0.83) were negatively correlated with DR. The area under the curve increased from 0.794 (95% CI 0.745 to 0.842) to 0.840 (95% CI 0.797 to 0.833) when C2, C14DC, C18:1OH and C18:1 added to the traditional risk factor model. Conclusion: There was a negative correlation between C2, C14DC, C16, C18:1OH, and C18:1 and the risk of retinopathy in patients with T2DM. C2, C14DC, C18:1OH, and C18:1 may be new predictors and diagnostic markers of DR.

Short chain fatty acids for the risk of diabetic nephropathy in type 2 diabetes patients.

AIMS: This study aimed to explore relationships short chain fatty acids with diabetic nephropathy (DN) in type 2 diabetes (T2D) patients. METHODS: We extracted the clinical and omics data of 100 T2D patients and 100 DN patients from April 2018 to April 2019 from a tertiary hospital. Restricted cubic splines were used to examine full-range associations of short chain fatty acids with DN in T2D.Query Logistic regression was used to obtain odds ratio (OR) and confidence interval (CI). RESULTS: Acetate, butyrate and isovalerate were negatively correlated with DN. Isobutyrate was positively correlated with DN. Propionate ≥ 4.4 µg/mL and isobutyrate ≥ 1.4 µg/mL had threshold effects and their increasing levels above the cutoff points were associated with rapid rises in the risk of DN. The additive interaction between high propionate and high isobutyrate in serum significantly increased the risk of DN (OR34.35; 95%CI 7.11 to 166.08). Presence of hypertension further increased the OR of high propionate for DN to 8.27(95%CI 1.82 to 37.57) with a significant additive interaction. The additive interaction of the high isobutyrate and hypertension was not significant. CONCLUSIONS: Acetate, butyrate and isovalerate were negatively associated with DN. Isobutyrate was positively associated with DN. Serum high propionate and high isobutyrate worked independently and synergistically to increase the risk of DN in T2D. Presence of hypertension further amplified the effect of copresence of high propionate on DN risk.

Inhibition of hydroxylated polychlorinated biphenyls (OH-PCBs) on sulfotransferases (SULTs).

Polychlorinated biphenyls (PCBs) have been demonstrated as a kind of the persistent organic pollutants (POPs) that could exert complicated influences towards metabolism in human bodies. Since hydroxylated polychlorinated biphenyls (OH-PCBs) are important metabolites of PCBs, our study focuses on investigating the potential inhibitory capability of OH-PCBs on four human sulfotransferase (SULT) isoforms. P-nitrophenol (PNP) was utilized as nonselective probe substrate for this study, and recombinant SULT isoforms were utilized as the enzyme resources. Ultra-performance liquid chromatography (UPLC)-UV detecting system was used to analyze PNP and its metabolite PNP-sulfate. As result, 100 µM of most tested OH-PCBs significantly inhibited the activity of four SULT isoforms. Concentration-dependent inhibition of OH-PCBs towards SULTs was found, and half inhibition concentration values (IC50) of some inhibition processes were determined. Inhibition kinetics (inhibition kinetic type and parameters) were determined using 4'-OH-PCB106 as the representative OH-PCB, SULT1B1 and SULT1E1 as representative SULT isoforms. The inhibition kinetic parameters (Ki) were 1.73 µM and 1.81 µM for the inhibition of 4'-OH-PCB106 towards SULT1B1 and SULT1E1, respectively. In silico docking simulation was utilized to analyze the inhibition capability of 2'-OH-PCB5, 4'-OH-PCB9, 2'-OH-PCB12 towards SULT1A3.All these results obtained in this study are helpful for further understanding the toxicity of PCBs.

Genetic variants associated with beta-cell function and insulin sensitivity potentially influence bile acid metabolites and gestational diabetes mellitus in a Chinese population.

INTRODUCTION: To investigate associations between genetic variants related to beta-cell (BC) dysfunction or insulin resistance (IR) in type 2 diabetes (T2D) and bile acids (BAs), as well as the risk of gestational diabetes mellitus (GDM). RESEARCH DESIGN AND METHODS: We organized a case-control study of 230 women with GDM and 217 without GDM nested in a large prospective cohort of 22 302 Chinese women in Tianjin, China. Two weighted genetic risk scores (GRSs), namely BC-GRS and IR-GRS, were established by combining 39 and 23 single nucleotide polymorphisms known to be associated with BC dysfunction and IR, respectively. Regression and mediation analyses were performed to evaluate the relationship of GRSs with BAs and GDM. RESULTS: We found that the BC-GRS was inversely associated with taurodeoxycholic acid (TDCA) after adjustment for confounders (Beta (SE)=-0.177 (0.048); p=2.66×10-4). The BC-GRS was also associated with the risk of GDM (OR (95% CI): 1.40 (1.10 to 1.77); p=0.005), but not mediated by TDCA. Compared with individuals in the low tertile of BC-GRS, the OR for GDM was 2.25 (95% CI 1.26 to 4.01) in the high tertile. An interaction effect of IR-GRS with taurochenodeoxycholic acid (TCDCA) on the risk of GDM was evidenced (p=0.005). Women with high IR-GRS and low concentration of TCDCA had a markedly higher OR of 14.39 (95% CI 1.59 to 130.16; p=0.018), compared with those with low IR-GRS and high TCDCA. CONCLUSIONS: Genetic variants related to BC dysfunction and IR in T2D potentially influence BAs at early pregnancy and the development of GDM. The identification of both modifiable and non-modifiable risk factors may facilitate the identification of high-risk individuals to prevent GDM.

Plasma Amino Acids and Residual Hypertriglyceridemia in Diabetic Patients Under Statins: Two Independent Cross-Sectional Hospital-Based Cohorts.

Objective: The objective of the study was to investigate the relationship of amino acid metabolism with hypertriglyceridemia in diabetic patients under statins free of prior cardiovascular diseases. Methods: Two independent cross-sectional hospital based cohorts, i.e., Liaoning Medical University First Affiliated Hospital (LMUFAH, n = 146) and the Second Affiliated Hospital of Dalian Medical University (SAHDMU, n = 294) were included in the current analysis. Hypertriglyceridemia was defined as triglyceride ≥1.7 mmol/L, and well-controlled LDL-C was defined as <2.6 mmol/L. The adjusted ORs (95% CI) of circulating metabolic measures for hypertriglyceridemia were assessed using logistic regression. Pooled results of metabolites with the same direction of association in both cohorts were combined using inverse variance-weighted fixed-effect meta-analysis. Difference of identified metabolites in patients with and without hypertriglyceridemia were also obtained in the context of LDL-C. Results: Patients, 86 and 106, were with hypertriglyceridemia in LMUFAH and SAHDMU, respectively. We observed that elevated alanine, asparagine, leucine, and valine were consistently associated with increased hypertriglyceridemia in both cohorts. In fixed-effect pooled analysis, the OR (95% CI) per SD increase was 1.71 (1.32-2.20) for alanine, 1.62 (1.20-2.19) for asparagine, 1.64 (1.22-2.20) for leucine, and 1.62 (1.22-2.13) for valine (all P values ranged from 0.0018 to <0.0001); adjusting for C-peptide attenuated effect sizes of Ala, Leu, and Val for hypertriglyceridemia. The difference were robust in groups with well- or bad-controlled LDL-C. Conclusion: Among 23 amino acids, alanine, asparagine, leucine, and valine were positively associated with increased residual risk of hypertriglyceridemia in diabetic patients with statin treatment.

Hepatic miR-378 modulates serum cholesterol levels by regulating hepatic bile acid synthesis.

Rationale: An improved understanding of thyroid hormone (TH) action on cholesterol metabolism will facilitate the identification of novel therapeutic targets for hypercholesterolemia. TH-regulated microRNAs (miRNAs) have been implicated in TH-controlled biological processes; however, whether and how TH-regulated miRNAs mediate the cholesterol-lowering effect of TH remains unclear. Our aim was to identify TH-regulated microRNAs that have cholesterol-lowering effects and explore the underlying mechanism. Method: Microarray and RNA-seq were performed to identify TH-regulated microRNAs and the genes regulated by mmu-miR-378-3p (miR-378) in the liver of mice, respectively. Recombinant adenoviruses encoding miR-378, Mafg, and shRNA for Mafg, antagomiR-378, liver-specific miR-378 transgenic mice, and miR-378 knockout mice were employed to investigate the roles of hepatic miR-378 and MAFG in cholesterol and bile acid homeostasis. The levels of bile salt species were determined by using UFLC-Triple-time of flight/MS. Results: Here, we show that hepatic miR-378 is positively regulated by TH. Transient overexpression of miR-378 in the liver of mice reduces serum cholesterol levels, accompanied with an increase in the expression of key enzymes in primary bile acid synthetic pathways and corresponding increases in biliary and fecal bile acid levels. Consistently, liver-specific miR-378 transgenic mice with moderate overexpression of hepatic miR-378 display decreased serum cholesterol levels and resistance to diet-induced hypercholesterolemia, while mice lacking miR-378 exhibit defects in bile acid and cholesterol homeostasis. Mechanistically, hepatic miR-378 regulates the expression of key enzymes in both classic and alternative bile acid synthetic pathways through MAFG, a transcriptional repressor, thereby modulating bile acid and cholesterol metabolism. Conclusions: TH-responsive hepatic miR-378 is capable of modulating serum cholesterol levels by regulating both the classic and alternative BA synthetic pathways. Our study not only identifies a previously undescribed role of hepatic miR-378 but also provides new cholesterol-lowering approaches.

Decreased plasma n6 : n3 polyunsaturated fatty acids ratio interacting with high C-peptide promotes non-alcoholic fatty liver disease in type 2 diabetes patients.

AIMS/INTRODUCTION: To explore relationships between polyunsaturated fatty acids (PUFA) and non-alcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes, and whether insulin action has an interactive effect with PUFA on NAFLD progression. MATERIALS AND METHODS: We extracted clinical and omics data of 482 type 2 diabetes patients from a tertiary hospital consecutively from April 2018 to April 2019. NAFLD was estimated by ultrasound at admission. Plasma fasting n3 and n6 fatty acids were quantified by liquid chromatography-tandem mass spectrometry analysis. Restricted cubic spline nested in binary logistic regression was used to select the cut-off point, and estimate odds ratios and 95% confidence intervals. Additive interactions of the n6 : n3 ratio with insulin action for NAFLD were estimated using relative excess risk due to interaction, attributable proportion due to interaction and synergy index. Relative excess risk due to interaction >0, attributable proportion due to interaction >0 or synergy index >1 indicates biological interaction. Spearman correlation analysis was used to obtain partial correlation coefficients between PUFA and hallmarks of NAFLD. RESULTS: Of 482 patients, 313 were with and 169 were without NAFLD. N3 ≥800 and n6 PUFA ≥8,100 µmol/L were independently associated with increased NAFLD risk; n6 : n3 ratio ≤10 was associated with NAFLD (odds ratio 1.80, 95% confidence interval 1.20-2.71), and the effect size was amplified by high C-peptide (odds ratio 8.89, 95% confidence interval 4.48-17.7) with significant interaction. The additive interaction of the n6 : n3 ratio and fasting insulin was not significant. CONCLUSION: Decreased n6 : n3 ratio was associated with increased NAFLD risk in type 2 diabetes patients, and the effect was only significant and amplified when there was the co-presence of high C-peptide.

Interactive effects of asparagine and aspartate homeostasis with sex and age for the risk of type 2 diabetes risk.

BACKGROUND: Asparagine and aspartate homeostasis are linked with type 2 diabetes (T2D). This study aimed to explore whether asparagine and aspartate metabolism interacted with sex and age to increase the risk of T2D. METHODS: From 27 May 2015 to 3 August 2016, we consecutively retrieved 1032 T2D patients and 1522 subjects without T2D from a tertiary care hospital in Liaoning, China. Restricted cubic spline nested in the logistic regression was used to draw odds ratio curves of plasma asparagine to aspartate ratio for T2D by sex and age. Cut-off point was selected where curves went apart, indicating possible interaction. Addictive interactions of asparagine to aspartate ratio with sex or age and secondary interaction with copresence of unfavorable sex and age were further estimated using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S). RESULTS: Ratio of asparagine to aspartate > 1.5 was associated with elevated risk of T2D (OR 7.99, 95%CI 5.50 to 11.6), which was enhanced by female gender to 13.6, (95%CI 8.10-22.9) and by > 50 years of age to 28.7 (14.6-56.3), with significant additive interactions. There was a significant secondary-interaction of copresence of female sex and > 50 years of age with high asparagine to aspartate ratio for increased T2D risk with the OR being further increased to 34.4 (20.5-57.5). CONCLUSIONS: High asparagine to aspartate ratio was associated with markedly increased risk of T2D, which was further amplified by either female gender or > 50 years of age, and especially both.