Dataset Information

Arterial Calcification in Diabetes Mellitus: Preclinical Models and Translational Implications.

ABSTRACT: Diabetes mellitus increasingly afflicts our aging and dysmetabolic population. Type 2 diabetes mellitus and the antecedent metabolic syndrome represent the vast majority of the disease burden-increasingly prevalent in children and older adults. However, type 1 diabetes mellitus is also advancing in preadolescent children. As such, a crushing wave of cardiometabolic disease burden now faces our society. Arteriosclerotic calcification is increased in metabolic syndrome, type 2 diabetes mellitus, and type 1 diabetes mellitus-impairing conduit vessel compliance and function, thereby increasing the risk for dementia, stroke, heart attack, limb ischemia, renal insufficiency, and lower extremity amputation. Preclinical models of these dysmetabolic settings have provided insights into the pathobiology of arterial calcification. Osteochondrogenic morphogens in the BMP-Wnt signaling relay and transcriptional regulatory programs driven by Msx and Runx gene families are entrained to innate immune responses-responses activated by the dysmetabolic state-to direct arterial matrix deposition and mineralization. Recent studies implicate the endothelial-mesenchymal transition in contributing to the phenotypic drift of mineralizing vascular progenitors. In this brief overview, we discuss preclinical disease models that provide mechanistic insights-and point to challenges and opportunities to translate these insights into new therapeutic strategies for our patients afflicted with diabetes mellitus and its arteriosclerotic complications.

SUBMITTER: Stabley JN

PROVIDER: S-EPMC5480317 | biostudies-other | 2017 Feb

REPOSITORIES: biostudies-other

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Arterial Calcification in Diabetes Mellitus: Preclinical Models and Translational Implications.

Stabley John N JN Towler Dwight A DA

Arteriosclerosis, thrombosis, and vascular biology 20161222 2

Diabetes mellitus increasingly afflicts our aging and dysmetabolic population. Type 2 diabetes mellitus and the antecedent metabolic syndrome represent the vast majority of the disease burden-increasingly prevalent in children and older adults. However, type 1 diabetes mellitus is also advancing in preadolescent children. As such, a crushing wave of cardiometabolic disease burden now faces our society. Arteriosclerotic calcification is increased in metabolic syndrome, type 2 diabetes mellitus, a ...[more]

PMID: 28062508

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Project description:BACKGROUND:Diabetes Mellitus is an increasingly prevalent chronic disease characterized by the body's inability to metabolize glucose. The objective of this study was to build an effective predictive model with high sensitivity and selectivity to better identify Canadian patients at risk of having Diabetes Mellitus based on patient demographic data and the laboratory results during their visits to medical facilities. METHODS:Using the most recent records of 13,309 Canadian patients aged between 18 and 90 years, along with their laboratory information (age, sex, fasting blood glucose, body mass index, high-density lipoprotein, triglycerides, blood pressure, and low-density lipoprotein), we built predictive models using Logistic Regression and Gradient Boosting Machine (GBM) techniques. The area under the receiver operating characteristic curve (AROC) was used to evaluate the discriminatory capability of these models. We used the adjusted threshold method and the class weight method to improve sensitivity - the proportion of Diabetes Mellitus patients correctly predicted by the model. We also compared these models to other learning machine techniques such as Decision Tree and Random Forest. RESULTS:The AROC for the proposed GBM model is 84.7% with a sensitivity of 71.6% and the AROC for the proposed Logistic Regression model is 84.0% with a sensitivity of 73.4%. The GBM and Logistic Regression models perform better than the Random Forest and Decision Tree models. CONCLUSIONS:The ability of our model to predict patients with Diabetes using some commonly used lab results is high with satisfactory sensitivity. These models can be built into an online computer program to help physicians in predicting patients with future occurrence of diabetes and providing necessary preventive interventions. The model is developed and validated on the Canadian population which is more specific and powerful to apply on Canadian patients than existing models developed from US or other populations. Fasting blood glucose, body mass index, high-density lipoprotein, and triglycerides were the most important predictors in these models.

Project description:Background and Purpose: Intracranial arterial calcification (IAC) has been the focus of much attention by clinicians and researchers as an indicator of intracranial atherosclerosis, but correlations of IAC patterns (intimal or medial) with the presence of atherosclerotic plaques and plaque stability are still a matter of debate. Our study aimed to assess the associations of IAC patterns identified on computed tomography (CT) with the presence of plaque detected on vessel wall magnetic resonance imaging and plaque stability. Materials and Methods: Patients with stroke or transient ischemic attack and intracranial artery stenosis were recruited. IAC was detected and localized (intima or media) on non-contrast CT images. Intracranial atherosclerotic plaques were identified using vessel wall magnetic resonance imaging and matched to corresponding CT images. Associations between IAC patterns and culprit atherosclerotic plaques were assessed by using multivariate regression. Results: Seventy-five patients (mean age, 63.4 ± 11.6 years; males, 46) were included. Two hundred and twenty-one segments with IAC were identified on CT in 66 patients, including 86 (38.9%) predominantly intimal calcifications and 135 (61.1%) predominantly medial calcifications. A total of 72.0% of intimal calcifications coexisted with atherosclerotic plaques, whereas only 10.2% of medial calcifications coexisted with plaques. Intimal calcification was more commonly shown in non-culprit plaques than culprit plaques (25.9 vs. 9.4%, P = 0.008). The multivariate mixed logistic regression adjusted for the degree of stenosis showed that intimal calcification was significantly associated with non-culprit plaques (OR, 2.971; 95% CI, 1.036-8.517; P = 0.043). Conclusion: Our findings suggest that intimal calcification may indicate the existence of a stable form of atherosclerotic plaque, but plaques can exist in the absence of intimal calcification especially in the middle cerebral artery.

Dataset Information

Arterial Calcification in Diabetes Mellitus: Preclinical Models and Translational Implications.

Publications

Arterial Calcification in Diabetes Mellitus: Preclinical Models and Translational Implications.

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