Associations between intensive diabetes therapy and NMR-determined lipoprotein subclass profiles in Type 1 diabetes

DCCT/EDIC Research Group

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Our objective is to define differences in circulating lipoprotein subclasses between intensive vs. conventional management of Type 1 diabetes during the randomization phase of the Diabetes Control and Complications Trial (DCCT). Nuclear magnetic resonance-determined lipoprotein subclass profiles (NMR-LSP), which estimate molar subclass concentrations and mean particle diameters, were determined in 1,294 DCCT subjects after a median of five (interquartile range: four, six) years following randomization to intensive or conventional diabetes management. In cross-sectional analyses, we compared standard lipids and NMR-LSP between treatment groups. Standard total-, LDL- and HDL-cholesterol levels were similar between randomization groups, while triglyceride levels were lower in the intensively treated group. NMR-LSP showed that intensive therapy was associated with larger LDL diameter (20.7 vs. 20.6 nm, p=0.01) and lower levels of small LDL (median: 465 vs. 552 nmol/l, p=0.007), total IDL/LDL (mean: 1000 vs. 1053 nmol/l, p=0.01), and small HDL (mean: 17.3 vs. 18.6 μmol/l, p<0.0001), the latter accounting for reduced total HDL (mean: 33.8 vs. 34.8 μmol/l, p=0.01). In conclusion, intensive diabetes therapy was associated with potentially favorable changes in LDL and HDL subclasses in sera. Further research will determine whether these changes contribute to the beneficial effects of intensive diabetes management on vascular complications.

Original languageEnglish
Pages (from-to)310-317
JournalJournal of Lipid Research
Volume57
Issue number2
Early online date09 Dec 2015
DOIs
Publication statusPublished - Feb 2016

Fingerprint

Dive into the research topics of 'Associations between intensive diabetes therapy and NMR-determined lipoprotein subclass profiles in Type 1 diabetes'. Together they form a unique fingerprint.

Cite this