Lipidomic profiles and their relationship to incident diabetic retinopathy in type 2 diabetes: The Fremantle Diabetes Study Phase II.
TL;DR
This exploratory study identified five lipid biomarkers with the potential to improve diabetic retinopathy risk prediction and the understanding of pathophysiological mechanisms.
Abstract
Aims
To determine whether plasma lipid profiles predict diabetic retinopathy (DR).
Methods
DR status (none, mild non-proliferative diabetic retinopathy (NPDR), moderate NPDR, severe NPDR/worse) was categorised in 762 adults with type 2 diabetes (mean age 64.5 years, 54.3% males) at baseline and Year 4/6. Ultra-performance liquid chromatography-tandem mass spectrometry generated baseline plasma lipid profiles. Multiple logistic regression identified baseline associates of new/worsening DR and incident DR. The likelihood ratio test (LRT) evaluated incremental biomarker contribution. The net reclassification improvement (NRI) was calculated.
Results
New/worsening DR occurred in 121 (16%). Of 495 without DR at baseline, 35 (7.0%) developed DR. For new/worsening DR, the inclusion of cholesterol ester (20:4), fatty acid (20:3) and lysophosphatidylglycerol (18:1) in addition to conventional risk factors (hypertension, HbA1c, diabetes treatment intensity, urinary albumin:creatinine) added to the conventional model predictivity (LRT, P = 0.00002). The NRI gain at a 10% cut-off was 5.7% (SE 2.8%; P = 0.043). For incident DR, fatty acid (20:3), lysophosphatidylglycerol (18:0) and phosphatidylcholine (18:0_20:3) with HbA1c improved model performance (LRT, P = 0.00001). The NRI gain at 5% risk cut-off for incident DR was 28.3% (P = 0.002).
Conclusions
This exploratory study identified five lipid biomarkers with the potential to improve DR risk prediction and the understanding of pathophysiological mechanisms.