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Dietary Manganese, Plasma Markers of Inflammation, and the Development of Type 2 Diabetes in Postmenopausal Women: Findings From the Women's Health Initiative.
Gong, JH, Lo, K, Liu, Q, Li, J, Lai, S, Shadyab, AH, Arcan, C, Snetselaar, L, Liu, S
Diabetes care. 2020;(6):1344-1351
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Abstract
OBJECTIVE To examine the association between manganese intake and the risk of type 2 diabetes in postmenopausal women and determine whether this association is mediated by circulating markers of inflammation. RESEARCH DESIGN AND METHODS We included 84,285 postmenopausal women without a history of diabetes from the national Women's Health Initiative Observational Study (WHI-OS). Replication analysis was then conducted among 62,338 women who participated in the WHI-Clinical Trial (WHI-CT). Additionally, data from a case-control study of 3,749 women nested in the WHI-OS with information on biomarkers of inflammation and endothelial dysfunction were examined using mediation analysis to determine the relative contributions of these known biomarkers by which manganese affects type 2 diabetes risk. RESULTS Compared with the lowest quintile of energy-adjusted dietary manganese, WHI-OS participants in the highest quintile had a 30% lower risk of type 2 diabetes (hazard ratio [HR] 0.70 [95% CI 0.65, 0.76]). A consistent association was also confirmed in the WHI-CT (HR 0.79 [95% CI 0.73, 0.85]). In the nested case-control study, higher energy-adjusted dietary manganese was associated with lower circulating levels of inflammatory biomarkers that significantly mediated the association between dietary manganese and type 2 diabetes risk. Specifically, 19% and 12% of type 2 diabetes risk due to manganese were mediated through interleukin 6 and hs-CRP, respectively. CONCLUSIONS Higher intake of manganese was directly associated with a lower type 2 diabetes risk independent of known risk factors. This association may be partially mediated by inflammatory biomarkers.
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Analysis for warning factors of type 2 diabetes mellitus complications with Markov blanket based on a Bayesian network model.
Liu, S, Zhang, R, Shang, X, Li, W
Computer methods and programs in biomedicine. 2020;:105302
Abstract
BACKGROUND AND OBJECTIVE Type 2 diabetes mellitus (T2DM) complications seriously affect the quality of life and could not be cured completely. Actions should be taken for prevention and self-management. Analysis of warning factors is beneficial for patients, on which some previous studies focused. They generally used the professional medical test factors or complete factors to predict and prevent, but it was inconvenient and impractical for patients to self-manage. With this in mind, this study built a Bayesian network (BN) model, from the perspective of diabetic patients' self-management and prevention, to predict six complications of T2DM using the selected warning factors which patients could have access from medical examination. Furthermore, the model was analyzed to explore the relationships between physiological variables and T2DM complications, as well as the complications themselves. The model aims to help patients with T2DM self-manage and prevent themselves from complications. METHODS The dataset was collected from a well-known data center called the National Health Clinical Center between 1st January 2009 and 31st December 2009. After preprocess and impute the data, a BN model merging expert knowledge was built with Bootstrap and Tabu search algorithm. Markov Blanket (MB) was used to select the warning factors and predict T2DM complications. Moreover, a Bayesian network without prior information (BN-wopi) model learned using 10-fold cross-validation both in structure and in parameters was added to compare with other classifiers learned using 10-fold cross-validation fairly. The warning factors were selected according the structure learned in each fold and were used to predict. Finally, the performance of two BN models using warning features were compared with Naïve Bayes model, Random Forest model, and C5.0 Decision Tree model, which used all features to predict. Besides, the validation parameters of the proposed model were also compared with those in existing studies using some other variables in clinical data or biomedical data to predict T2DM complications. RESULTS Experimental results indicated that the BN models using warning factors performed statistically better than their counterparts using all other variables in predicting T2DM complications. In addition, the proposed BN model were effective and significant in predicting diabetic nephropathy (DN) (AUC: 0.831), diabetic foot (DF) (AUC: 0.905), diabetic macrovascular complications (DMV) (AUC: 0.753) and diabetic ketoacidosis (DK) (AUC: 0.877) with the selected warning factors compared with other experiments. CONCLUSIONS The warning factors of DN, DF, DMV, and DK selected by MB in this research might be able to help predict certain T2DM complications effectively, and the proposed BN model might be used as a general tool for prevention, monitoring, and self-management.
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Relationship between dietary carbohydrates intake and circulating sex hormone-binding globulin levels in postmenopausal women.
Huang, M, Liu, J, Lin, X, Goto, A, Song, Y, Tinker, LF, Chan, KK, Liu, S
Journal of diabetes. 2018;(6):467-477
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Abstract
BACKGROUND Low circulating levels of sex hormone-binding globulin (SHBG) have been shown to be a direct and strong risk factor for type 2 diabetes, cardiovascular diseases, and hormone-dependent cancers, although the relationship between various aspects of dietary carbohydrates and SHBG levels remains unexplored in population studies. METHODS Among postmenopausal women with available SHBG measurements at baseline (n = 11 159) in the Women's Health Initiative, a comprehensive assessment was conducted of total dietary carbohydrates, glycemic load (GL), glycemic index (GI), fiber, sugar, and various carbohydrate-abundant foods in relation to circulating SHBG levels using multiple linear regressions adjusting for potential covariates. Linear trend was tested across quartiles of dietary variables. Benjamini and Hochberg's procedure was used to calculate the false discovery rate for multiple comparisons. RESULTS Higher dietary GL and GI (both based on total and available carbohydrates) and a higher intake of sugar and sugar-sweetened beverages were associated with lower circulating SHBG concentrations (all P trend < 0.05; Q -values = 0.04,0.01, 0.07, 0.10, 0.01, and <0.0001, respectively). In contrast, women with a greater intake of dietary fiber tended to have elevated SHBG levels (P trend = 0.01, Q -value = 0.04). There was no significant association between total carbohydrates or other carbohydrate-abundant foods and SHBG concentrations. CONCLUSIONS The findings suggest that low GL or GI diets with low sugar and high fiber content may be associated with higher serum SHBG concentrations among postmenopausal women. Future studies investigating whether lower GL or GI diets increase SHBG concentrations are warranted.
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Effects of Exercise Training on Cardiorespiratory Fitness and Biomarkers of Cardiometabolic Health: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.
Lin, X, Zhang, X, Guo, J, Roberts, CK, McKenzie, S, Wu, WC, Liu, S, Song, Y
Journal of the American Heart Association. 2015;(7)
Abstract
BACKGROUND Guidelines recommend exercise for cardiovascular health, although evidence from trials linking exercise to cardiovascular health through intermediate biomarkers remains inconsistent. We performed a meta-analysis of randomized controlled trials to quantify the impact of exercise on cardiorespiratory fitness and a variety of conventional and novel cardiometabolic biomarkers in adults without cardiovascular disease. METHODS AND RESULTS Two researchers selected 160 randomized controlled trials (7487 participants) based on literature searches of Medline, Embase, and Cochrane Central (January 1965 to March 2014). Data were extracted using a standardized protocol. A random-effects meta-analysis and systematic review was conducted to evaluate the effects of exercise interventions on cardiorespiratory fitness and circulating biomarkers. Exercise significantly raised absolute and relative cardiorespiratory fitness. Lipid profiles were improved in exercise groups, with lower levels of triglycerides and higher levels of high-density lipoprotein cholesterol and apolipoprotein A1. Lower levels of fasting insulin, homeostatic model assessment-insulin resistance, and glycosylated hemoglobin A1c were found in exercise groups. Compared with controls, exercise groups had higher levels of interleukin-18 and lower levels of leptin, fibrinogen, and angiotensin II. In addition, we found that the exercise effects were modified by age, sex, and health status such that people aged <50 years, men, and people with type 2 diabetes, hypertension, dyslipidemia, or metabolic syndrome appeared to benefit more. CONCLUSIONS This meta-analysis showed that exercise significantly improved cardiorespiratory fitness and some cardiometabolic biomarkers. The effects of exercise were modified by age, sex, and health status. Findings from this study have significant implications for future design of targeted lifestyle interventions.
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Adipokine levels during the first or early second trimester of pregnancy and subsequent risk of gestational diabetes mellitus: A systematic review.
Bao, W, Baecker, A, Song, Y, Kiely, M, Liu, S, Zhang, C
Metabolism: clinical and experimental. 2015;(6):756-64
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OBJECTIVE We aimed to systematically review available literature linking adipokines to gestational diabetes mellitus (GDM) for a comprehensive understanding of the roles of adipokines in the development of GDM. METHODS We searched PubMed/MEDLINE and EMBASE databases for published studies on adipokines and GDM through October 21, 2014. We included articles if they had a prospective study design (i.e., blood samples for adipokines measurement were collected before GDM diagnosis). Random-effects models were used to pool the weighted mean differences comparing levels of adipokines between GDM cases and non-GDM controls. RESULTS Of 1523 potentially relevant articles, we included 25 prospective studies relating adipokines to incident GDM. Our meta-analysis of nine prospective studies on adiponectin and eight prospective studies on leptin indicated that adiponectin levels in the first or early second trimester of pregnancy were 2.25 μg/ml lower (95% CI: 1.75-2.75), whereas leptin levels were 7.25 ng/ml higher (95% CI 3.27-11.22), among women who later developed GDM than women who did not. Prospective data were sparse and findings were inconsistent for visfatin, retinol binding protein (RBP-4), resistin, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and vaspin. We did not identify prospective studies for several novel adipokines, including chemerin, apelin, omentin, or adipocyte fatty acid-binding protein. Moreover, no published prospective studies with longitudinal assessment of adipokines and incident GDM were identified. CONCLUSION Adiponectin levels in the first or second trimester of pregnancy are lower among pregnant women who later develop GDM than non-GDM women, whereas leptin levels are higher. Well-designed prospective studies with longitudinal assessment of adipokines during pregnancy are needed to understand the trajectories and dynamic associations of adipokines with GDM risk.