scholarly journals A 6-CpG Validated Methylation Risk Score Model for Metabolic Syndrome: The HyperGEN and GOLDN Studies

2021 ◽  
Author(s):  
Bertha A Hidalgo ◽  
Bre A Minniefield ◽  
Amit Patki ◽  
Rikki Tanner ◽  
Minoo Bagheri ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Ethnic Groups ◽  
Risk Score ◽  
Mixed Model ◽  
Disease Risk ◽  
Strong Predictor ◽  
Lipid Lowering ◽  
Risk Scores ◽  
Parameter Estimates ◽  
European Populations

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. In this study, we used cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N=614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N=995 European Americans (EA)), to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups. To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data and used the beta estimates as weights to construct a MRS in HyperGEN, which was validated in GOLDN. We performed association analyses using a logistic mixed model to test the association between the MRS and MetS adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two ethnic groups suggesting MRS may be useful to examine metabolic disease risk or related complications across ethnic groups.

scholarly journals A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259836
Author(s):  
Bertha A. Hidalgo ◽  
Bre Minniefield ◽  
Amit Patki ◽  
Rikki Tanner ◽  
Minoo Bagheri ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Risk Score ◽  
Disease Risk ◽  
Strong Predictor ◽  
Lipid Lowering ◽  
Risk Scores ◽  
Parameter Estimates ◽  
Cross Sectional ◽  
Association Analyses ◽  
European Populations

There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups.

scholarly journals Development and Validation of a Novel Dementia Risk Score in the UK Biobank Cohort

2021 ◽  
Author(s):  
Melis Anatürk ◽  
Raihaan Patel ◽  
Georgios Georgiopoulos ◽  
Danielle Newby ◽  
Anya Topiwala ◽  
...  
Keyword(s):  
At Risk ◽  
Cardiovascular Risk ◽  
Risk Score ◽  
Disease Risk ◽  
Risk Index ◽  
Risk Scores ◽  
Uk Biobank ◽  
Dementia Risk ◽  
History Of ◽  
The Uk

INTRODUCTION: Current prognostic models of dementia have had limited success in consistently identifying at-risk individuals. We aimed to develop and validate a novel dementia risk score (DRS) using the UK Biobank cohort.METHODS: After randomly dividing the sample into a training (n=166,487, 80%) and test set (n=41,621, 20%), logistic LASSO regression and standard logistic regression were used to develop the UKB-DRS.RESULTS: The score consisted of age, sex, education, apolipoprotein E4 genotype, a history of diabetes, stroke, and depression, and a family history of dementia. The UKB-DRS had good-to-strong discrimination accuracy in the UKB hold-out sample (AUC [95%CI]=0.79 [0.77, 0.82]) and in an external dataset (Whitehall II cohort, AUC [95%CI]=0.83 [0.79,0.87]). The UKB-DRS also significantly outperformed four published risk scores (i.e., Australian National University Alzheimer’s Disease Risk Index (ANU-ADRI), Cardiovascular Risk Factors, Aging, and Dementia score (CAIDE), Dementia Risk Score (DRS), and the Framingham Cardiovascular Risk Score (FRS) across both test sets.CONCLUSION: The UKB-DRS represents a novel easy-to-use tool that could be used for routine care or targeted selection of at-risk individuals into clinical trials.

Abstract 15997: Pooled Cohort Risk Equations: A Comparison of Their Predictions With Five Other Cardiovascular Risk Scores in Five Peruvian Sites

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Juan Bazo-Alvarez ◽  
Frank Peralta-Alvarez ◽  
Renato Quispe ◽  
Julio Poterico ◽  
Giancarlo Valle ◽  
...  
Keyword(s):  
Risk Score ◽  
Disease Risk ◽  
Heart Association ◽  
Population Based ◽  
Continuous Variable ◽  
World Health ◽  
Risk Scores ◽  
Cvd Risk ◽  
Low Middle Income Countries ◽  
Predicted Risk

Introduction: Cardiovascular disease (CVD) risk scores are used to estimate an individual’s risk of developing a disease or death from a cardiovascular event. Recently, the American College of Cardiology/American Heart Association (ACC/AHA) introduced the Pooled Cohort risk equations (ACC/AHA model). It is important to know how comparable CVD risk predictions are in low-middle income countries (LMIC). Hypothesis: ACC/AHA model has a poor concordance with any other CVD risk score. Methods: We used secondary data from two Peruvian, age and sex-matched, population-based studies across five geographical sites. The ACC/AHA model was compared to five other CVD risk prediction tools: two versions of the Framingham Risk Score (FRS-Lipids and FRS-BMI), Reynolds Risk Score (RRS), four versions of the Systematic Coronary Risk Evaluation (SCORE 1-4), World Health Organization risk chart (WHO), and Lancet Chronic Disease risk chart (LCD). We calculated predicted risk as a continuous variable and used Lin’s concordance correlation coefficient (CCC). We also compared the high predicted risk prevalence between all the scores using the cut-off levels suggested by each score’s guidelines. Results: We included 2183 subjects in the risk scores age range of 45-65 years (mean age 54.3 (SD±5.6) years). CCC agreement values found in this study were generally poor. The highest concordance was observed between the ACC/AHA model and the risk scores derived from the Framingham Study (40% with FRS-BMI and 44% with FRS-Lipids). ACC/AHA model depicted the highest proportion of people with predicted high-risk of 10-year CVD, at 29.0% (95%CI 26.9-31.0%) and the same tendency was observed in all study sites. Conclusions: In Peruvian population-based samples, agreement between ACC/AHA model and five other CVD risk scores was generally poor. There is an urgent need to use an appropriate risk score for CVD in LMIC. In an ideal scenario, it would be significant to have a proper CVD risk score for LMIC.

scholarly journals Orlistat and cardiovascular risk profile in hypertensive patients with metabolic syndrome: the ARCOS study

2006 ◽  
Vol 50 (2) ◽  
pp. 368-376 ◽  
Author(s):  
Maria Teresa Zanella ◽  
Marcelo Hiroshi Uehara ◽  
Artur Beltrame Ribeiro ◽  
Marcelo Bertolami ◽  
Ana Claudia Falsetti ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Weight Loss ◽  
Cardiovascular Risk ◽  
Glucose Metabolism ◽  
Disease Risk ◽  
Risk Scores ◽  
Risk Category ◽  
Coronary Risk ◽  
Hypertensive Patients ◽  
The Impact

Weight loss improves metabolic abnormalities and reduces cardiovascular risk in obese hypertensive patients. To evaluate the impact of a sustained weight loss on coronary risk, 181 hypertensive patients with metabolic syndrome underwent to orlistat therapy, 120 mg, t.i.d., plus diet for 36 weeks. During therapy, Framingham risk scores (FRS) were calculated for determination of coronary heart disease risk in ten years. Body mass index decreased from 35.0 ± 4.2 to 32.6 ± 4.5 kg/m² (p< 0.0001) and waist circumference from 108.1 ± 10.1 to 100.5 ± 11.1 cm (p< 0.0001), at the end of the study period (week 36). Systolic and diastolic blood pressure showed reductions after the two first weeks, which were maintained up to the end of the study. A clear shift to the left in FRS distribution curve occurred at the end of the study, compared to baseline, indicating a reduction in coronary risk. Over all patients at risk, 49.2% moved to a lower risk category. A weight loss > 5% occurred in 64.6% of all patients, associated with improvement in glucose metabolism. Among those with abnormal glucose metabolism, 38 out 53 patients (71.7%) improved their glucose tolerance (p< 0.0005). In conclusion, long-term orlistat therapy helps to reduce and maintain a lower body weight, decreasing risk of coronary disease and improving glucose metabolism, thus protecting against type 2 diabetes.

Effect of soluble-viscous dietary fibre on coronary heart disease risk score across 3 population health categories: data from randomized, double-blind, placebo-controlled trials

2020 ◽  
Vol 45 (7) ◽  
pp. 801-804
Author(s):  
Vladimir Vuksan ◽  
John L. Sievenpiper ◽  
Elena Jovanovski ◽  
Alexandra L. Jenkins ◽  
Allison Komishon ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Risk Score ◽  
Coronary Heart Disease Risk ◽  
Disease Risk ◽  
Blood Cholesterol ◽  
Double Blind ◽  
Framingham Risk ◽  
Heart Disease Risk

We applied the Framingham risk equation in healthy, metabolic syndrome, and diabetes populations, following treatment with viscous fibre from konjac-based blend (KBB). KBB yielded reduction in estimated risk score by 16% (1.04 ± 0.03 vs. 0.87 ± 0.04, p < 0.01) in type 2 diabetes, 24% (1.08 ± 0.01 vs. 0.82 ± 0.02, p < 0.01) in metabolic syndrome, and 25% (1.09 ± 0.05 vs. 0.82 ± 0.06, p < 0.01) in healthy individuals. Drivers for decreased risk were improvements in blood cholesterol and systolic blood pressure. The composite coronary heart disease risk across populations was reduced 22% (p < 0.01). Novelty Viscous fibre from konjac-xanthan reduced 10-year relative coronary heart disease using Framingham Risk Score across the glycemic status spectrum.

scholarly journals Comparisons of Polyexposure, Polygenic, and Clinical Risk Scores in Risk Prediction of Type 2 Diabetes

2021 ◽  
Author(s):  
Yixuan He ◽  
Chirag M Lakhani ◽  
Danielle Rasooly ◽  
Arjun K Manrai ◽  
Ioanna Tzoulaki ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Prediction ◽  
Risk Score ◽  
Prediction Models ◽  
Disease Risk ◽  
Clinical Risk Factors ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Clinical Risk

OBJECTIVE: <p>Establish a polyexposure score for T2D incorporating 12 non-genetic exposure and examine whether a polyexposure and/or a polygenic risk score improves diabetes prediction beyond traditional clinical risk factors.</p> <h2><a></a>RESEARCH DESIGN AND METHODS:</h2> <p>We identified 356,621 unrelated individuals from the UK Biobank of white British ancestry with no prior diagnosis of T2D and normal HbA1c levels. Using self-reported and hospital admission information, we deployed a machine learning procedure to select the most predictive and robust factors out of 111 non-genetically ascertained exposure and lifestyle variables for the polyexposure risk score (PXS) in prospective T2D. We computed the clinical risk score (CRS) and polygenic risk score (PGS) by taking a weighted sum of eight established clinical risk factors and over six million SNPs, respectively.</p> <h2><a></a>RESULTS:</h2> <p>In the study population, 7,513 had incident T2D. The C-statistics for the PGS, PXS, and CRS models were 0.709, 0.762, and 0.839, respectively. Hazard ratios (HR) associated with risk score values in the top 10% percentile versus the remaining population is 2.00, 5.90, and 9.97 for PGS, PXS, and CRS respectively. Addition of PGS and PXS to CRS improves T2D classification accuracy with a continuous net reclassification index of 15.2% and 30.1% for cases, respectively, and 7.3% and 16.9% for controls, respectively. </p> <h2><a></a>CONCLUSIONS:</h2> <p>For T2D, the PXS provides modest incremental predictive value over established clinical risk factors. The concept of PXS merits further consideration in T2D risk stratification and is likely to be useful in other chronic disease risk prediction models.</p>

scholarly journals MetS Risk Score: A Clear Scoring Model to Predict a 3-Year Risk for Metabolic Syndrome

2018 ◽  
Vol 50 (09) ◽  
pp. 683-689 ◽  
Author(s):  
Tian-Tian Zou ◽  
Yu-Jie Zhou ◽  
Xiao-Dong Zhou ◽  
Wen-Yue Liu ◽  
Sven Van Poucke ◽  
...  
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Risk Score ◽  
Validation Cohort ◽  
Medical Center ◽  
Characteristic Curve ◽  
Model Development ◽  
Predictive Performance ◽  
Risk Scores ◽  
Individual Risk

AbstractAlthough several risk factors for metabolic syndrome (MetS) have been reported, there are few clinical scores that predict its incidence. Therefore, we created and validated a risk score for prediction of 3-year risk for MetS. Three-year follow-up data of 4395 initially MetS-free subjects, enrolled for an annual physical examination from Wenzhou Medical Center were analyzed. Subjects at enrollment were randomly divided into the training and the validation cohort. Univariate and multivariate logistic regression models were employed for model development. The selected variables were assigned an integer or half-integer risk score proportional to the estimated coefficient from the logistic model. Risk scores were tested in a validation cohort. The predictive performance of the model was tested by computing the area under the receiver operating characteristic curve (AUROC). Four independent predictors were chosen to construct the MetS risk score, including BMI (HR=1.906, 95% CI: 1.040–1.155), FPG (HR=1.507, 95% CI: 1.305–1.741), DBP (HR=1.061, 95% CI: 1.002–1.031), HDL-C (HR=0.539, 95% CI: 0.303–0.959). The model was created as –1.5 to 4 points, which demonstrated a considerable discrimination both in the training cohort (AUROC=0.674) and validation cohort (AUROC=0.690). Comparison of the observed with the estimated incidence of MetS revealed satisfactory precision. We developed and validated the MetS risk score with 4 risk factors to predict 3-year risk of MetS, useful for assessing the individual risk for MetS in medical practice.

scholarly journals Triglycerides and low HDL cholesterol predict coronary heart disease risk in patients with stable angina

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chiara Caselli ◽  
Raffaele De Caterina ◽  
Jeff M Smit ◽  
Jonica Campolo ◽  
Mohammed El Mahdiui ◽  
...  
Keyword(s):  
Risk Score ◽  
Stable Angina ◽  
Disease Risk ◽  
Density Lipoprotein ◽  
Myocardial Damage ◽  
Hdl Cholesterol ◽  
Lipid Lowering ◽  
Low Hdl ◽  
Heart Disease Risk

AbstractWe assessed whether high triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C) levels, expressed by an increased TG/HDL-C ratio, predict coronary atherosclerotic disease (CAD) outcomes in patients with stable angina. We studied 355 patients (60 ± 9 years, 211 males) with stable angina who underwent coronary computed tomography angiography (CTA), were managed clinically and followed for 4.5 ± 0.9 years. The primary composite outcome was all-cause mortality and non-fatal myocardial infarction. At baseline, the proportion of males, patients with metabolic syndrome, diabetes and obstructive CAD increased across TG/HDL-C ratio quartiles, together with markers of insulin resistance, hepatic and adipose tissue dysfunction and myocardial damage, with no difference in total cholesterol or LDL-C. At follow-up, the global CTA risk score (HR 1.06, 95% confidence interval (CI) 1.03–1.09, P = 0.001) and the IV quartile of the TG/HDL-C ratio (HR 2.85, 95% CI 1.30–6.26, P < 0.01) were the only independent predictors of the primary outcome. The TG/HDL-C ratio and the CTA risk score progressed over time despite increased use of lipid-lowering drugs and reduction in LDL-C. In patients with stable angina, high TG and low HDL-C levels are associated with CAD related outcomes independently of LDL-C and treatments.Trial registration. EVINCI study: ClinicalTrials.gov NCT00979199, registered September 17, 2009; SMARTool study: ClinicalTrials.gov NCT04448691, registered June 26, 2020.

scholarly journals Cardiovascular disease risk assessment in diabetes and metabolic syndrome patients with and without non-alcoholic fatty liver disease

2015 ◽  
Vol 2 (4) ◽  
pp. 91 ◽  
Author(s):  
Mohammed Alim ◽  
Rakesh K. Sahay ◽  
Nuwairah Hafiz ◽  
B. Prabhakar ◽  
Mohammed Ibrahim
Keyword(s):  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Metabolic Syndrome ◽  
Fatty Liver ◽  
Risk Score ◽  
Disease Risk ◽  
Cardiovascular Disease Risk ◽  
Cvd Risk ◽  
Alcoholic Fatty Liver ◽  
Alcoholic Fatty Liver Disease

<p class="abstract"><strong><span lang="EN-US">Background:</span></strong><span lang="EN-US"> Recently non-alcoholic fatty liver disease (NAFLD) has been suggested as independent cardiovascular (CVD) risk factor and many studies have shown strong links between NAFLD and CVD but NAFLD has not been related to cardiovascular mortality independently on a long term follow up. Inflammation and oxidative stress is well recognized factors for NALFD which lead to many interrelated factors contributing to cardiovascular risk. Aim: To study the cardiovascular disease risk in diabetes and metabolic syndrome patients with and without NAFLD using different risk assessment calculators.</span></p><p class="abstract"><strong><span lang="EN-US">Methods: </span></strong>This was a single center, prospective cross sectional study. 62 patients with diabetes and metabolic syndrome attending the endocrinology &amp; gastroenterology clinics of Osmania General Hospital were enrolled in to the study with 31 patients in group A (NAFLD) and 31 patients in group B (Non-NAFLD). Patients were diagnosed with fatty liver by ultrasound examination.  </p><p class="abstract"><strong><span lang="EN-US">Results: </span></strong>The groups were individually evaluated for cardiovascular risk assessment by PROCAM risk score, atherosclerotic cardiovascular disease (ASCVD) score and atherosclerosis Index. The means ± standard(%) deviation of Procam risk score for NAFLD group was 6.00 ± 1.00 and for Non NAFLD group it was 10.00 ± 2.00 (p=0.039). ASCVD risk score shows 5.11 ± 1.12 for NAFLD and Non NAFLD group showed 8.25 ± 2.18 (p=0.235). The Atherosclerosis index for NAFLD group was 0.24 ± 0.03 and Non NAFLD 0.18 ± 0.04 (p=0.785). The QRsik2 score for NAFLD and Non-NAFLD patients was 13.16 ± 7.56 and 17.45 ± 10.36.</p><p class="abstract"><strong><span lang="EN-US">Conclusions: </span></strong>There was no difference in CVD risk assessment when assessed with different calculators in this population.</p>

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