metabolic risk score
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2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 1058-1058
Author(s):  
Camille Mba ◽  
Albert Koulman ◽  
Stephen Sharp ◽  
Nita Forouhi ◽  
Fumiaki Imamura ◽  
...  

Abstract Objectives Previous studies mostly in Western populations suggest that a low exposure to B-vitamins (folate and vitamin B12 in particular) are associated with increased cardiometabolic disease risk. This study aimed to examine the association of blood concentrations of folate and holotranscobalamin (holoTC) with cardiometabolic risk factors in adults in Cameroon. Methods We conducted a cross-sectional population-based study in 497 adults. We measured serum folate and holoTC by liquid chromatography tandem mass spectrometry and “sandwich” ELISA respectively. Total folate was calculated excluding the oxidation product 5-methyltetrahydrofolate. The outcomes were individual cardiometabolic risk factors and a continuous metabolic risk score. We fitted linear regression models to examine the association between B-vitamins and cardiometabolic risk factors and estimated β-coefficients and 95% confidence intervals per standard deviation (SD) difference in each B vitamin variable. Results Mean age was 38.2 (SD: 8.6) years and 63.5% of the participants were women. Mean serum folate was 15.9 (SD: 10.8) nmol/L and holoTC was 74.1 (SD: 33.7) pmol/L. Rural residents had higher concentrations of serum folate but lower holoTC than urban residents. There was a significant inverse association between serum folate and the metabolic risk score (−0.22 (−0.41 to −0.03)) in a multivariable model adjusted for age, sex, education level, smoking, alcohol intake, rural/urban site and BMI. This association was attenuated to the null after further adjustments for objectively measured physical activity (PAEE) and holoTC. HoloTC was positively associated with the metabolic risk score in unadjusted analysis (0.29 (0.08 to 0.51)) but attenuated to the null after adjusting for socio-demographic characteristics. For individual risk factors, an inverse association was observed between serum folate and diastolic blood pressure, which was unaffected by adjustment for confounders including PAEE and holoTC (−1.18 (−2.16 to − 0.20)). Conclusions In Cameroon, serum folate and holoTC were associated with the metabolic risk score in opposite directions, partly depending on potential demographic and socioeconomic characteristics. The inverse association between serum folate and the metabolic risk score was likely driven by the blood pressure component. Funding Sources None.


Author(s):  
Joshua Garfein ◽  
Kerry S. Flannagan ◽  
Danielle Rittman ◽  
Manuel Ramirez‐Zea ◽  
Eduardo Villamor ◽  
...  

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 14-15
Author(s):  
Yang Liang ◽  
Han-ying Huang ◽  
Yun Wang ◽  
Weida Wang ◽  
Jin-Yuan Li ◽  
...  

Background: Models to predict survival of persons with plasma cell myeloma are mostly use clinical and laboratory co-variates including cytogenetics and mutation topography. These models have AUCs of 0.55 to 0.77 indicating considerable inaccuracy. We tested whether data of plasma cell metabolism might improve prediction accuracy. Methods: RNA matrix, clinical and laboratory data from datasets GSE13633 (training cohort) and GSE57317, GSE24080 and GSE2658 (validation cohorts) were downloaded from the Gene Expression Omnibus (GEO) database. Genes regulating plasma cell metabolism correlating with survival were identified in uni-variable Cox regression analyses and a metabolic risk score built by Lasso Cox regression analysis. Survivals was compared by Kaplan-Meier curves with log-rank tests. Prediction accuracy of the metabolic risk score was quantified by time-dependent receiver operating characteristic (ROC) curves and the area under the curve. A nomogram was developed including metabolic risk score and ISS stage. Enriched pathways in different metabolic risk score cohorts were evaluated by gene set enrichment analyses (GSEA). We interrogated validity of 3 genes with the largest risk coefficients in vitro using small molecule inhibitors to test effects on cell proliferation and apoptosis by CCK-8 and multi-parameter flow cytometry (MPFC). Results: 7 genes regulating plasma cell metabolism with high risk coefficients were used to develop a metabolic risk score. The score had robust predictive performance with AUCs for 3-year survival in the 4 cohorts of 0.71 [95% Confidence Interval, 0.65, 0.79], 0.88 [0.71, 1.03], 0.70 [0.63,0.76] and 0.71 [0.65, 0.79]. Subjects in the high-risk cohort had worse 3-year survivals compared with those in the low-risk cohort (62% [55, 68%] vs. 85% [80, 90%], P < 0.001; 54% [33, 76%] vs. 92% [82, 102%], P <0.001; 58% [52, 65%] vs. 77% [71, 82%], P <0.001; and 51% [38, 64%] vs. 74% [62, 85%], P <0.001). The metabolic risk score remained an independent prognostic factor for survival in multi-variable regression analyses. A nomogram combining metabolic risk score with ISS score increased prediction accuracy of 5-year survival (AUCs of 0.72 [0.69,0.81] vs. 0.66 [0.60, 0.72]; P = 0.015). In GSEA most gene enrichment pathways in high-risk cohort were metabolism-related. In vitro, the results showed that the three small molecule inhibitors combined with bortezomib had a synergistic inhibitory effect on the growth of myeloma cells H929, MM.1S, U266B1 and RPMI 8226, with an effective synergistic CI value; and enhanced the apoptosis of myeloma cell lines effect. Conclusion: A risk score based on expression of genes involved in plasma cell metabolism predicted survival and significantly improved prediction accuracy of the ISS score. Predictions based on gene expression were validated in vitro. Keywords GEO, plasma cell myeloma, metabolism, prognostic model Disclosures No relevant conflicts of interest to declare.


2020 ◽  
pp. 1-9
Author(s):  
Claudia R Villatoro-Santos ◽  
Manuel Ramirez-Zea ◽  
Eduardo Villamor ◽  

Abstract Objective: To examine the associations between vitamins of the methionine-homocysteine (Hcys) cycle (B6, B12 and folate) and Hcys with metabolic syndrome (MetS) among Mesoamerican children and their adult parents. Design: We conducted a cross-sectional study. Exposures were plasma vitamins B6 and B12 concentrations, erythrocyte folate and plasma Hcys. In children, the outcome was a continuous metabolic risk score calculated through sex- and age standardisation of waist circumference, the homoeostatic model assessment for insulin resistance, mean arterial pressure (MAP), serum HDL-cholesterol and serum TAG. In parents, the outcome was the prevalence of MetS according to the Adult Treatment Panel III Criteria. We estimated mean differences in the metabolic risk score and prevalence ratios of MetS between quartiles of the exposures using multivariable-adjusted linear and Poisson regression models, respectively. Setting: Capital cities of Belize, Guatemala, El Salvador, the Dominican Republic, Honduras, Nicaragua, Panama, Costa Rica and Chiapas State in Mexico. Participants: In total, 237 school-aged children and 524 parents. Results: Among children, vitamin B12 was inversely associated with the metabolic risk score (quartiles 4–1 adjusted difference = –0·13; 95 % CI: –0·21, –0·04; Ptrend = 0·008) through MAP, HDL-cholesterol and TAG. In contrast, folate was positively associated with the metabolic risk score (quartiles 4–1 adjusted difference = 0·11; 95 % CI: 0·01, 0·20; Ptrend = 0·02). In adults, vitamin B6 was inversely associated with MetS prevalence, whereas vitamin B12 and folate were positively related to this outcome. Conclusions: Vitamins of the methionine-Hcys cycle are associated with MetS in different directions. The associations differ between children and adults.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 702-P
Author(s):  
KENNETH M. MADDEN ◽  
JOCELYN M. CHASE

2020 ◽  
Vol 38 ◽  
Author(s):  
João Francisco de Castro Silveira ◽  
Cláudia Daniela Barbian ◽  
Leandro Tibiriçá Burgos ◽  
Jane Dagmar Pollo Renner ◽  
Dulciane Nunes Paiva ◽  
...  

ABSTRACT Objective: To verify the association between screen time and cardiorespiratory fitness with the presence of metabolic risk in schoolchildren in an isolated and clustered manner. Methods: Cross-sectional study with 1.200 schoolchildren from Santa Cruz do Sul-RS. Screen time and cardiorespiratory fitness were evaluated. The continuous metabolic risk score was calculated by summing the Z score of the waist circumference, systolic blood pressure, glucose, triglycerides, total cholesterol, low-density lipoprotein (LDL-C) and high-density lipoprotein (HDL-C). Results: Children (34.3%) and adolescents (48.2%) had high screen time, while 44.3% of the children and 53.3% of the adolescents were unfit in relation to cardiorespiratory fitness. Regarding the relation of screen time/cardiorespiratory fitness, 14.7% of the children and 26.9% of the adolescents presented high screen time and low levels of cardiorespiratory fitness. The presence of metabolic risk was shown in children (17.1%) and adolescents (14.7%). The presence of metabolic risk was directly associated with low levels of cardiorespiratory fitness in children and adolescents. When analyzed in clusters, the metabolic risk in children was 11% more prevalent in subjects with low screen time/unfit and 12% in subjects with high screen time/unfit, whereas in adolescents, the prevalence of metabolic risk was also higher in those with low screen time/unfit (8%) and high screen time/unfit (7%). Conclusions: The presence of metabolic risk in children and adolescents was associated with low levels of cardiorespiratory fitness, independent of screen time, in an isolated or clustered manner.


2019 ◽  
Vol 13 (3) ◽  
pp. 492-501
Author(s):  
Rutger Verbeek ◽  
Federico Oldoni ◽  
R. Preethi Surendran ◽  
Ailko H. Zwinderman ◽  
Kay T. Khaw ◽  
...  

2019 ◽  
Vol 31 (2) ◽  
pp. e23211 ◽  
Author(s):  
Cézane Priscila Reuter ◽  
Lars Bo Andersen ◽  
Andréia Rosane de Moura Valim ◽  
Éboni Marília Reuter ◽  
Leticia Borfe ◽  
...  

2019 ◽  
Vol 48 (1) ◽  
pp. 157-167 ◽  
Author(s):  
Izzuddin M Aris ◽  
Sheryl L Rifas-Shiman ◽  
Ling-Jun Li ◽  
Ken P Kleinman ◽  
Brent A Coull ◽  
...  

Abstract Background Few studies have examined the independent and combined relationships of body mass index (BMI) peak and rebound with adiposity, insulin resistance and metabolic risk later in life. We used data from Project Viva, a well-characterized birth cohort from Boston with repeated measures of BMI, to help fill this gap. Methods Among 1681 children with BMI data from birth to mid childhood, we fitted individual BMI trajectories using mixed-effects models with natural cubic splines and estimated age, and magnitude of BMI, at peak (in infancy) and rebound (in early childhood). We obtained cardiometabolic measures of the children in early adolescence (median 12.9 years) and analysed their associations with the BMI parameters. Results After adjusting for potential confounders, age and magnitude at infancy BMI peak were associated with greater adolescent adiposity, and earlier adiposity rebound was strongly associated with greater adiposity, insulin resistance and metabolic risk score independently of BMI peak. Children with a normal timing of BMI peak plus early rebound had an adverse cardiometabolic profile, characterized by higher fat mass index {β 2.2 kg/m2 [95% confidence interval (CI) 1.6, 2.9]}, trunk fat mass index [1.1 kg/m2 (0.8, 1.5)], insulin resistance [0.2 units (0.04, 0.4)] and metabolic risk score [0.4 units (0.2, 0.5)] compared with children with a normal BMI peak and a normal rebound pattern. Children without a BMI peak (no decline in BMI after the rise in infancy) also had adverse adolescent metabolic profiles. Conclusions Early age at BMI rebound is a strong risk factor for cardiometabolic risk, independent of BMI peak. Children with a normal peak-early rebound pattern, or without any BMI decline following infancy, are at greatest risk of adverse cardiometabolic profile in adolescence. Routine monitoring of BMI may help to identify children who are at greatest risk of developing an adverse cardiometabolic profile in later life and who may be targeted for preventive interventions.


Epigenetics ◽  
2018 ◽  
Vol 13 (10-11) ◽  
pp. 1072-1087 ◽  
Author(s):  
Jian V. Huang ◽  
Andres Cardenas ◽  
Elena Colicino ◽  
C. Mary Schooling ◽  
Sheryl L. Rifas-Shiman ◽  
...  

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