scholarly journals The Lack of Utility of Circulating Biomarkers of Inflammation and Endothelial Dysfunction for Type 2 Diabetes Risk Prediction Among Postmenopausal Women

2010 ◽  
Vol 170 (17) ◽  
Author(s):  
Chun Chao ◽  
Yiqing Song ◽  
Nancy Cook ◽  
Chi-Hong Tseng ◽  
JoAnn E. Manson ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Endothelial Dysfunction ◽  
Postmenopausal Women ◽  
Risk Prediction ◽  
Diabetes Risk ◽  
Circulating Biomarkers

scholarly journals Factors Motivating Individuals to Consider Genetic Testing for Type 2 Diabetes Risk Prediction

PLoS ONE ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. e0147071 ◽  
Author(s):  
Jennifer Wessel ◽  
Jyoti Gupta ◽  
Mary de Groot
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Testing ◽  
Risk Prediction ◽  
Diabetes Risk

scholarly journals A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

2017 ◽  
Vol 17 (12) ◽  
Author(s):  
Jordi Merino ◽  
Miriam S. Udler ◽  
Aaron Leong ◽  
James B. Meigs
Keyword(s):  
Type 2 Diabetes ◽  
Risk Prediction ◽  
Diabetes Risk

scholarly journals Dietary manganese, plasma markers of inflammation, and the development of type 2 diabetes in postmenopausal women: findings from the Women’s Health Initiative

2020 ◽  
Author(s):  
Jung Ho Gong ◽  
Kenneth Lo ◽  
Qing Liu ◽  
Jie Li ◽  
Shuiqing Lai ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Postmenopausal Women ◽  
Case Control Study ◽  
Case Control ◽  
Diabetes Risk ◽  
Inflammatory Biomarkers ◽  
Health Initiative ◽  
Markers Of Inflammation ◽  
Control Study

Objective<b>: </b>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. <p>Research Design and Methods: We included 84,285 postmenopausal women without history of diabetes from the national Women’s Health Initiative Observational Study (WHI-OS). Replication analysis was then conducted among 62,338 women 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 affect T2D risk.</p> <p>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 (hazards 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 high-sensitivity C-reactive protein, respectively.</p> <p>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.</p>

scholarly journals Dietary manganese, plasma markers of inflammation, and the development of type 2 diabetes in postmenopausal women: findings from the Women’s Health Initiative

2020 ◽  
Author(s):  
Jung Ho Gong ◽  
Kenneth Lo ◽  
Qing Liu ◽  
Jie Li ◽  
Shuiqing Lai ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Postmenopausal Women ◽  
Case Control Study ◽  
Case Control ◽  
Diabetes Risk ◽  
Inflammatory Biomarkers ◽  
Health Initiative ◽  
Markers Of Inflammation ◽  
Control Study

Objective<b>: </b>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. <p>Research Design and Methods: We included 84,285 postmenopausal women without history of diabetes from the national Women’s Health Initiative Observational Study (WHI-OS). Replication analysis was then conducted among 62,338 women 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 affect T2D risk.</p> <p>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 (hazards 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 high-sensitivity C-reactive protein, respectively.</p> <p>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.</p>

Critical evaluation of DNA methylation markers for type-2-diabetes risk prediction

2018 ◽  
Author(s):  
C Krause ◽  
H Sievert ◽  
M Grohs ◽  
C Geißler ◽  
AT El Gammal ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Dna Methylation ◽  
Risk Prediction ◽  
Critical Evaluation ◽  
Diabetes Risk

scholarly journals Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Yiming Wu ◽  
Runyu Jing ◽  
Yongcheng Dong ◽  
Qifan Kuang ◽  
Yan Li ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Prediction ◽  
Functional Annotation ◽  
Diabetes Risk ◽  
Risk Snps

scholarly journals A Novel Integrated Type 2 Diabetes Prediction Model for Indian Population using Data Mining Techniques

2019 ◽  
Vol 9 (2) ◽  
pp. 3067-3072
Keyword(s):  
Type 2 Diabetes ◽  
Prediction Model ◽  
Risk Prediction ◽  
Indian Population ◽  
Integrated Model ◽  
Diabetes Risk ◽  
Classification Model ◽  
Diabetes Prediction ◽  
Diabetes Risk Score

Late diagnosis and undiagnosed type 2 diabetes are the two major concerns for India, which is going to be a diabetes capital shortly. Several diabetes risk score (DRS) tools have been proposed and deployed for detecting the persons with high risk. These DRS tools have been developed using the multiple logistic regression model. But this model is both imperfect and subject to misuse. Another major issue with the DRS tools developed for Indian population is that they are based on the very limited urban population that does not represent the population of India. The objective of current research work is to develop a classification model for type 2 diabetes prediction. Along with this, the building of a novel integrated model for type 2 diabetes risk prediction is discussed consisting of the aggregate classification model and Indian weighted diabetes risk score model. The dataset used to develop and validate the model is obtained from the Annual Health Survey comprising of nearly 0.7 million and nearly 75 thousand adult participants respectively from around 400 districts of India. The proposed integrated diabetes risk prediction model predicts diabetes with 69.89% sensitivity, 56.58% specificity. The positive predictive value of the proposed integrated model is 15.88%, which is a significant improvement as the prevalence of diabetes is only 3.68% for the study population. Developing countries such as India, where undiagnosed diabetes and limited financial resources are a significant concern, the proposed integrated model for diabetes risk prediction can be useful as a cheaper tool useful for mass-screening, which can save up to 30% of the total screening cost.

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