scholarly journals Combined Influence of Insulin Resistance, Overweight/Obesity, and Fatty Liver as Risk Factors for Type 2 Diabetes

Diabetes Care ◽  
2012 ◽  
Vol 35 (4) ◽  
pp. 717-722 ◽  
Author(s):  
K.-C. Sung ◽  
W.-S. Jeong ◽  
S. H. Wild ◽  
C. D. Byrne
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Fatty Liver

scholarly journals Is Vitamin D Deficiency Related to Increased Cancer Risk in Patients with Type 2 Diabetes Mellitus?

2021 ◽  
Vol 22 (12) ◽  
pp. 6444
Author(s):  
Anna Gabryanczyk ◽  
Sylwia Klimczak ◽  
Izabela Szymczak-Pajor ◽  
Agnieszka Śliwińska
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Vitamin D ◽  
Cancer Risk ◽  
Vitamin D Deficiency ◽  
Cancer Development ◽  
Increased Risk

There is mounting evidence that type 2 diabetes mellitus (T2DM) is related with increased risk for the development of cancer. Apart from shared common risk factors typical for both diseases, diabetes driven factors including hyperinsulinemia, insulin resistance, hyperglycemia and low grade chronic inflammation are of great importance. Recently, vitamin D deficiency was reported to be associated with the pathogenesis of numerous diseases, including T2DM and cancer. However, little is known whether vitamin D deficiency may be responsible for elevated cancer risk development in T2DM patients. Therefore, the aim of the current review is to identify the molecular mechanisms by which vitamin D deficiency may contribute to cancer development in T2DM patients. Vitamin D via alleviation of insulin resistance, hyperglycemia, oxidative stress and inflammation reduces diabetes driven cancer risk factors. Moreover, vitamin D strengthens the DNA repair process, and regulates apoptosis and autophagy of cancer cells as well as signaling pathways involved in tumorigenesis i.e., tumor growth factor β (TGFβ), insulin-like growth factor (IGF) and Wnt-β-Cathenin. It should also be underlined that many types of cancer cells present alterations in vitamin D metabolism and action as a result of Vitamin D Receptor (VDR) and CYP27B1 expression dysregulation. Although, numerous studies revealed that adequate vitamin D concentration prevents or delays T2DM and cancer development, little is known how the vitamin affects cancer risk among T2DM patients. There is a pressing need for randomized clinical trials to clarify whether vitamin D deficiency may be a factor responsible for increased risk of cancer in T2DM patients, and whether the use of the vitamin by patients with diabetes and cancer may improve cancer prognosis and metabolic control of diabetes.

scholarly journals Functional high-intensity exercise training ameliorates insulin resistance and cardiometabolic risk factors in type 2 diabetes

2018 ◽  
Vol 103 (7) ◽  
pp. 985-994 ◽  
Author(s):  
Ciarán E. Fealy ◽  
Stephan Nieuwoudt ◽  
Julie A. Foucher ◽  
Amanda R. Scelsi ◽  
Steven K. Malin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Exercise Training ◽  
High Intensity ◽  
Cardiometabolic Risk ◽  
High Intensity Exercise ◽  
Cardiometabolic Risk Factors

Cardiovascular events in patients with type 2 diabetes

2002 ◽  
Vol 2 (1_suppl) ◽  
pp. S4-S8
Author(s):  
Erland Erdmann
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Risk Factor ◽  
Adverse Effects ◽  
Cardiovascular Events ◽  
Left Ventricular ◽  
Diabetic Patients ◽  
Increased Risk

Diabetes is a common risk factor for cardiovascular disease. Coronary heart disease and left ventricular dysfunction are more common in diabetic patients than in non-diabetic patients, and diabetic patients benefit less from revascularisation procedures. This increased risk can only partly be explained by the adverse effects of diabetes on established risk factors; hence, a substantial part of the excess risk must be attributable to direct effects of hyperglycaemia and diabetes. In type 2 diabetes, hyperinsulinaemia, insulin resistance and hyperglycaemia have a number of potential adverse effects, including effects on endothelial function and coagulation. Risk factor modification has been shown to reduce the occurrence of cardiovascular events in patients with diabetes; indeed, diabetic patients appear to benefit more in absolute terms than non-diabetic patients. There is thus a strong case for intensive treatment of risk factors, including insulin resistance and hyperglycaemia, in patients with type 2 diabetes.

scholarly journals Common Risk Factors in Relatives and Spouses of Patients with Type 2 Diabetes in Developing Prediabetes

Healthcare ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1010
Author(s):  
Wei-Hao Hsu ◽  
Chin-Wei Tseng ◽  
Yu-Ting Huang ◽  
Ching-Chao Liang ◽  
Mei-Yueh Lee ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Insulin Sensitivity ◽  
Cell Function ◽  
Diabetic Patients ◽  
Β Cell ◽  
Tyg Index ◽  
Β Cell Function

Prediabetes should be viewed as an increased risk for diabetes and cardiovascular disease. In this study, we investigated its prevalence among the relatives and spouses of patients with type 2 diabetes or risk factors for prediabetes, insulin resistance, and β-cell function. A total of 175 individuals were included and stratified into three groups: controls, and relatives and spouses of type 2 diabetic patients. We compared clinical characteristics consisting of a homeostatic model assessment for insulin resistance (HOMA-IR) and beta cell function (HOMA-β), a quantitative insulin sensitivity check index (QUICKI), and triglyceride glucose (TyG) index. After a multivariable linear regression analysis, the relative group was independently correlated with high fasting glucose, a high TyG index, and low β-cell function; the relatives and spouses were independently associated with a low QUICKI. The relatives and spouses equally had a higher prevalence of prediabetes. These study also indicated that the relatives had multiple factors predicting the development of diabetes mellitus, and that the spouses may share a number of common environmental factors associated with low insulin sensitivity.

scholarly journals Plasma metabolites predict both insulin resistance and incident type 2 diabetes: a metabolomics approach within the Prevención con Dieta Mediterránea (PREDIMED) study

2019 ◽  
Vol 109 (3) ◽  
pp. 626-634 ◽  
Author(s):  
Christopher Papandreou ◽  
Mònica Bulló ◽  
Miguel Ruiz-Canela ◽  
Courtney Dennis ◽  
Amy Deik ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Area Under The Curve ◽  
Predictive Ability ◽  
Plasma Metabolites ◽  
Incident Type ◽  
Dieta Mediterranea ◽  
Dieta Mediterránea

ABSTRACT Background Insulin resistance is a complex metabolic disorder and is often associated with type 2 diabetes (T2D). Objectives The aim of this study was to test whether baseline metabolites can additionally improve the prediction of insulin resistance beyond classical risk factors. Furthermore, we examined whether a multimetabolite model predicting insulin resistance in nondiabetics can also predict incident T2D. Methods We used a case-cohort study nested within the Prevención con Dieta Mediterránea (PREDIMED) trial in subsets of 700, 500, and 256 participants without T2D at baseline and 1 and 3 y. Fasting plasma metabolites were semiquantitatively profiled with liquid chromatography–tandem mass spectrometry. We assessed associations between metabolite concentrations and the homeostasis model of insulin resistance (HOMA-IR) through the use of elastic net regression analysis. We subsequently examined associations between the baseline HOMA-IR–related multimetabolite model and T2D incidence through the use of weighted Cox proportional hazard models. Results We identified a set of baseline metabolites associated with HOMA-IR. One-year changes in metabolites were also significantly associated with HOMA-IR. The area under the curve was significantly greater for the model containing the classical risk factors and metabolites together compared with classical risk factors alone at baseline [0.81 (95% CI: 0.79, 0.84) compared with 0.69 (95% CI: 0.66, 0.73)] and during a 1-y period [0.69 (95% CI: 0.66, 0.72) compared with 0.57 (95% CI: 0.53, 0.62)]. The variance in HOMA-IR explained by the combination of metabolites and classical risk factors was also higher in all time periods. The estimated HRs for incident T2D in the multimetabolite score (model 3) predicting high HOMA-IR (median value or higher) or HOMA-IR (continuous) at baseline were 2.00 (95% CI: 1.58, 2.55) and 2.24 (95% CI: 1.72, 2.90), respectively, after adjustment for T2D risk factors. Conclusions The multimetabolite model identified in our study notably improved the predictive ability for HOMA-IR beyond classical risk factors and significantly predicted the risk of T2D.

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