scholarly journals SNP-Based Genetic Risk Score Modeling Suggests No Increased Genetic Susceptibility of the Roma Population to Type 2 Diabetes Mellitus

Genes ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 942 ◽  
Author(s):  
Nardos Abebe Werissa ◽  
Peter Piko ◽  
Szilvia Fiatal ◽  
Zsigmond Kosa ◽  
Janos Sandor ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
General Population ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Unhealthy Lifestyle ◽  
Roma Population

Background: In a previous survey, an elevated fasting glucose level (FG) and/or known type 2 diabetes mellitus (T2DM) were significantly more frequent in the Roma population than in the Hungarian general population. We assessed whether the distribution of 16 single nucleotide polymorphisms (SNPs) with unequivocal effects on the development of T2DM contributes to this higher prevalence. Methods: Genetic risk scores, unweighted (GRS) and weighted (wGRS), were computed and compared between the study populations. Associations between GRSs and FG levels and T2DM status were investigated in separate and combined study populations. Results: The Hungarian general population carried a greater genetic risk for the development of T2DM (GRSGeneral = 15.38 ± 2.70 vs. GRSRoma = 14.80 ± 2.68, p < 0.001; wGRSGeneral = 1.41 ± 0.32 vs. wGRSRoma = 1.36 ± 0.31, p < 0.001). In the combined population models, GRSs and wGRSs showed significant associations with elevated FG (p < 0.001) and T2DM (p < 0.001) after adjusting for ethnicity, age, sex, body mass index (BMI), high-density Lipoprotein Cholesterol (HDL-C), and triglyceride (TG). In these models, the effect of ethnicity was relatively strong on both outcomes (FG levels: βethnicity = 0.918, p < 0.001; T2DM status: ORethnicity = 2.484, p < 0.001). Conclusions: The higher prevalence of elevated FG and/or T2DM among Roma does not seem to be directly linked to their increased genetic load but rather to their environmental/cultural attributes. Interventions targeting T2DM prevention among Roma should focus on harmful environmental exposures related to their unhealthy lifestyle.

P6188Predicting type 2 diabetes mellitus: combining a genetic risk score with traditional risk factors

2018 ◽  
Vol 39 (suppl_1) ◽  
Author(s):  
J Ponte Monteiro ◽  
M I Mendonca ◽  
A Pereira ◽  
A C Sousa ◽  
R Rodrigues ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Traditional Risk Factors

scholarly journals Genetic Risk Score in Diabetes Associated With Chronic Pancreatitis Versus Type 2 Diabetes Mellitus

2019 ◽  
Vol 10 (7) ◽  
pp. e00057 ◽  
Author(s):  
Mark O. Goodarzi ◽  
Tanvi Nagpal ◽  
Phil Greer ◽  
Jinrui Cui ◽  
Yii-Der I. Chen ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Chronic Pancreatitis ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score

scholarly journals Risk stratification score for acute myocardial infarction and sudden cardiac death in type 2 diabetes mellitus

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
S Lee ◽  
J Zhou ◽  
CL Guo ◽  
WKK Wu ◽  
WT Wong ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Myocardial Infarction ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Cardiac Death ◽  
Adverse Outcomes ◽  
Risk Scores ◽  
Diabetic Patients ◽  
Type 2 Diabetic

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Acute myocardial infarction (AMI) and sudden cardiac death (SCD) are major cardiovascular adverse outcomes in patients with type 2 diabetic mellitus. Although there are many risk scores on composite outcomes of major cardiovascular adverse outcomes or cardiovascular mortality for diabetic patients, these existing scores did not account for the difference in pathogenesis and prognosis between acute coronary syndrome and lethal ventricular arrhythmias. Furthermore, recent studies reported that HbA1c and lipid levels, which were often accounted for in these risk scores, have J/U-shaped relationships with adverse outcomes. Purpose The present study aims to evaluate the application of incorporating non-linear J/U-shaped relationships between mean HbA1c and cholesterol levels into risk scores for predicting for AMI and non-AMI related SCD respectively, amongst type 2 diabetes mellitus patients. Methods This was a territory-wide cohort study of patients with type 2 diabetes mellitus above the age 40 and free from prior AMI and SCD, with or without prescriptions of anti-diabetic agents between January 1st, 2009 to December 31st, 2009 at government-funded hospitals and clinics in Hong Kong. Risk scores were developed for predicting incident AMI and non-AMI related SCD. The performance of conditional inference survival forest (CISF) model compared to that of random survival forests (RSF) model and multivariate Cox model. Results This study included 261308 patients (age = 66.0 ± 11.8 years old, male = 47.6%, follow-up duration = 3552 ± 1201 days, diabetes duration = 4.77 ± 2.29 years). Mean HbA1c and high-density lipoprotein-cholesterol (HDL-C) were significant predictors of AMI under multivariate Cox regression and were linearly associated with AMI. Mean HbA1c and total cholesterol were significant multivariate predictors with a J-shaped relationship with non-AMI related SCD. The AMI and SCD risk scores had an area-under-the-curve (AUC) of 0.666 (95% confidence interval (CI)= [0.662, 0.669]) and 0.677 (95% CI= [0.673, 0.682]), respectively. CISF significantly improves prediction performance of both outcomes compared to RSF and multivariate Cox models. Conclusions A holistic combination of demographic, clinical, and laboratory indices can be used for the risk stratification of type 2 diabetic patients against AMI and SCD.

scholarly journals A patient who does not like insulin

ABOUTOPEN ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 122-125
Author(s):  
Paola Ubaldi
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
General Population ◽  
Bone Metastases ◽  
Cancer Symptoms ◽  
The Past ◽  
The Right ◽  
Hypoglycemic Therapy

Hypoglycemic therapy over the past 20 years has expanded considerably with the use of new classes of more effective and safer medicines. Alongside the aging of the general population, the survival of diabetic subjects has significantly increased, thus exposing them to a greater risk of developing co-morbidities. This represents a challenge for the diabetologist, who must acquire ever broader concepts for the management of a complex and multi-organ disease. We report the case of a 72-year-old woman with type 2 diabetes mellitus and pulmonary adenocarcinoma of the right upper lobe with brain and bone metastases who, subjected to innovative and integrated treatments agreed between specialists of different disciplines, is still alive and free of cancer symptoms 23 months after diagnosis (Diabetology)

scholarly journals Use of Biomarkers in Predicting the Onset, Monitoring the Progression, and Risk Stratification for Patients with Type 2 Diabetes Mellitus

2017 ◽  
Vol 63 (1) ◽  
pp. 186-195 ◽  
Author(s):  
Benjamin M Scirica
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Risk Stratification ◽  
Cardiac Biomarkers ◽  
Risk Scores ◽  
Oral Glucose ◽  
Clinical Risk ◽  
Monitoring Therapy

Abstract BACKGROUND As the worldwide prevalence of type 2 diabetes mellitus (T2DM) increases, it is even more important to develop cost-effective methods to predict and diagnose the onset of diabetes, monitor progression, and risk stratify patients in terms of subsequent cardiovascular and diabetes complications. CONTENT Nonlaboratory clinical risk scores based on risk factors and anthropomorphic data can help identify patients at greatest risk of developing diabetes, but glycemic indices (hemoglobin A1c, fasting plasma glucose, and oral glucose tolerance tests) are the cornerstones for diagnosis, and the basis for monitoring therapy. Although family history is a strong predictor of T2DM, only small populations of patients carry clearly identifiable genetic mutations. Better modalities for detection of insulin resistance would improve earlier identification of dysglycemia and guide effective therapy based on therapeutic mechanisms of action, but improved standardization of insulin assays will be required. Although clinical risk models can stratify patients for subsequent cardiovascular risk, the addition of cardiac biomarkers, in particular, high-sensitivity troponin and natriuretic peptide provide, significantly improves model performance and risk stratification. CONCLUSIONS Much more research, prospectively planned and with clear treatment implications, is needed to define novel biomarkers that better identify the underlying pathogenic etiologies of dysglycemia. When compared with traditional risk features, biomarkers provide greater discrimination of future risk, and the integration of cardiac biomarkers should be considered part of standard risk stratification in patients with T2DM.

PS3 - 1. Validation of Cardiovascular Risk Scores Among Patients with Type 2 Diabetes Mellitus

2013 ◽  
Vol 11 (4) ◽  
pp. 139-140
Author(s):  
Susan van Dieren ◽  
Joep van der Leeuw ◽  
Linda M. Peelen ◽  
Yvonne T. van der Schouw ◽  
Joline W.J. Beulens
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Cardiovascular Risk ◽  
Risk Scores

scholarly journals DEMONSTRASI PENGENALAN VARIASI MENU DIET DIABETES MELLITUS BAGI PENDERITA DIABETES MELLITUS TIPE 2

2021 ◽  
Vol 4 (1) ◽  
pp. 56
Author(s):  
Zuhria Ismawanti ◽  
Nastitie Cinintya Nurzihan ◽  
Nining Prastiwi
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Drug Management ◽  
Unhealthy Lifestyle ◽  
Type 2 Dm ◽  
Post Test ◽  
Diet Management ◽  
Level Of Understanding

Diabetes mellitus (DM) is a disease that can be caused by an unhealthy lifestyle. DM treatment has four pillars in its management, namely education, DM diet management, physical activity and drug management. The recommended DM dietary arrangement is almost the same as the recommended diet in general, namely balanced nutrition in accordance with calorie needs, however DM sufferers will emphasize eating regularity in terms of eating schedules, types of food and amount of food. Based on these problems, it is necessary to demonstrate the introduction of variations in the diabetes mellitus diet menu for type 2 diabetes mellitus sufferers.This activity is carried out to increase knowledge about the variety of diabetes mellitus diet menus in type 2 diabetes mellitus sufferers.Pre-test and post-test are carried out to determine the level of understanding of the demonstration which are given. The method used was to provide a demonstration of introduction to the variation of the diabetes mellitus diet menu for people with type 2 diabetes. As many as 25 people participated in this activity from beginning to end. Based on the results of the evaluation using the post test value, it shows that there is an increase in knowledge and skills regarding the variation of the type 2 DM diet, so as to prevent complications of type 2 DM.

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