posted on 2020-10-28, 21:52authored byAda AdminAda Admin, Yow Keat Tham, Kaushala S. Jayawardana, Zahir H. Alshehry, Corey Giles, Kevin Huynh, Adam Alexander T. Smith, Jenny Y. Y. Ooi, Sophia Zoungas, Graham S. Hillis, John Chalmers, Peter J. Meikle, Julie R. McMullen
The incidence of atrial fibrillation (AF) is
higher in patients with diabetes. The goal of this study was to assess if the
addition of plasma lipids to traditional risk factors could improve the ability
to detect and predict future AF in patients with type 2 diabetes. Logistic
regression models were used to identify lipids associated with AF/future AF
from plasma lipids (n=316) measured from participants from the ADVANCE trial
(n=3,772). To gain mechanistic insight, follow-up lipid analysis was undertaken
in a mouse model which has an insulin-resistant heart and is susceptible to AF.
Sphingolipids, cholesteryl esters and phospholipids were associated with AF
prevalence, whereas two GM3 ganglioside species were associated with
future AF. For AF detection and prediction, addition of 6 and 3 lipids,
respectively, to a base model (12 conventional risk factors) increased the
C-statistics (detection:0.661 to 0.725; prediction:0.674 to 0.715), and categorical
net reclassification indices. GM3(d18:1/24:1) was lower in patients who
developed AF, improved the C-statistic for the prediction of future AF, and was
lower in the plasma of the mouse model susceptible to AF. This study
demonstrates that plasma lipids have the potential to improve both the detection
and prediction of AF in patients with diabetes.
This study was funded by National Health and Medical Research Council project grants to JRM (1045585, 1125514) and in part by the Victorian Government’s Operational Infrastructure Support Program. PJM and JRM are National Health and Research Council Senior Research Fellows (IDs 1042095, 1078985). The ADVANCE study was funded by the National Health and Medical Research Council of Australia (grants 211086 and 358395; trial registration: https://clinicaltrials.gov. Unique identifier: NCT00145925). ZHA was supported by a scholarship from King Fahad Medical City (Saudi Arabia).