Increased particle size of triacylglycerol-enriched remnant lipoproteins, but not their plasma concentration or lipid content, augments risk prediction of incident type 2 diabetes

Author(s):Show less -

Carvalho, Luiz Sergio F. ^{[1, 2, 3]} ; Bensenor, Isabela M. ^[4] ; Nogueira, Ana C. C. ^[3] ; Duncan, Bruce B. ^{[5, 6]} ; Schmidt, Maria I. ^{[5, 6]} ; Blaha, Michael J. ^[7] ; Toth, Peter P. ^{[7, 8]} ; Jones, Steven R. ^[7] ; Santos, Raul D. ^{[4, 9]} ; Lotufo, Paulo A. ^[4] ; Sposito, Andrei C. ^[2] ; Study, ELSA-Brasil

Affiliation

^[1] Clar Healthcare Intelligence, Data Lab, Jundiai, SP - Brazil

^[2] State Univ Campinas Unicamp, Fac Med Sci, Cardiol Div, Campinas, SP - Brazil

^[3] Inst Strateg Management Healthcare DF IGESDF, Lab Data Qual Care & Outcomes Res, Brasilia, DF - Brazil

^[4] Univ Sao Paulo, Univ Hosp, Ctr Clin & Epidemiol Res, Sao Paulo, SP - Brazil

^[5] Univ Fed Rio Grande do Sul, Hosp Clin, Porto Alegre, RS - Brazil

^[6] Univ Fed Rio Grande do Sul, Sch Med, Postgrad Studies Program Epidemiol, Porto Alegre, RS - Brazil

^[7] Johns Hopkins Ciccarone Ctr Prevent Heart Dis, Baltimore, MD - USA

^[8] CGH Med Ctr, Prevent Cardiol, Sterling, IL - USA

^[9] Univ Sao Paulo, Med Sch Hosp, Lipid ClinicHeart Inst InCor, Sao Paulo, SP - Brazil

• Document type: Journal article
• Source: Diabetologia; v. 64, n. 2 NOV 2020.
• Web of Science Citations: 1

Abstract

Aims/hypothesis Type 2 diabetes prevention requires the accurate identification of those at high risk. Beyond the association of fasting serum triacylglycerols with diabetes, triacylglycerol-enriched remnant lipoproteins (TRLs) more accurately reflect pathophysiological changes that underlie progression to diabetes, such as hepatic insulin resistance, pancreatic steatosis and systemic inflammation. We hypothesised that TRL-related factors could improve risk prediction for incident diabetes. Methods We included individuals from the Brazilian Longitudinal Study of Adult Health cohort. We trained a logistic regression model for the risk of incident diabetes in 80% of the cohort using tenfold cross-validation, and tested the model in the remaining 20% of the cohort (test set). Variables included medical history and traits of the metabolic syndrome, followed by TRL-related measurements (plasma concentration, TRL particle diameter, cholesterol and triacylglycerol content). TRL features were measured using NMR spectroscopy. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). Results Among 4463 at-risk individuals, there were 366 new cases of diabetes after a mean (+/- SD) of 3.7 (+/- 0.63) years of follow-up. We derived an 18-variable model with a global AUROC of 0.846 (95% CI: 0.829, 0.869). Overall TRL-related markers were not associated with diabetes. However, TRL particle diameter increased the AUROC, particularly in individuals with HbA(1c) <39 mmol/mol (5.7%) (hold-out test set {[}n = 659]; training-validation set {[}n = 2638]), but not in individuals with baseline HbA(1c) 39-46 mmol/mol (5.7-6.4%) (hold-out test set {[}n = 233]; training-validation set {[}n = 933]). In the subgroup with baseline HbA(1c) <39 mmol/mol (5.7%), AUROC in the test set increased from 0.717 (95% CI 0.603, 0.818) to 0.794 (95% CI 0.731, 0.862), and AUPRC in the test set rose from 0.582 to 0.701 when using the baseline model and the baseline model plus TRL particle diameter, respectively. TRL particle diameter was highly correlated with obesity, insulin resistance and inflammation in those with impaired fasting glucose at baseline, but less so in those with HbA(1c) <39 mmol/mol (5.7%). {[}GRAPHICS] Conclusions/interpretation TRL particle diameter improves the prediction of diabetes, but only in individuals with HbA(1c) <39 mmol/mol (5.7%) at baseline. These data support TRL particle diameter as a risk factor that is changed early in the course of the pathophysiological processes that lead to the development of type 2 diabetes, even before glucose abnormalities are established. (AU)

• FAPESP's process: 13/07607-8 - OCRC - Obesity and Comorbidities Research Center
• Grantee: Licio Augusto Velloso
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC