Timothy M E Davis, Jocelyn J Drinkwater, Alanah Grant-St James, Elaine Holmes, Wendy A Davis, Nicola Gray
This exploratory study identified five lipid biomarkers with the potential to improve DR risk prediction and the understanding of pathophysiological mechanisms.
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.