Elaine Holmes

Background and aims: Diabetic retinopathy (DR) is a major complication of diabetes mellitus and a leading cause of blindness globally. Early detection and intervention underpin optimal DR management and remain challenging. The underlying biological mechanisms are also poorly understood. This study examined comprehensive plasma lipid profiles using a targeted approach to detect potential DR biomarkers.

Materials and methods: We utilised data and samples from 762 adult participants with type 2 diabetes (mean age 64.5 years, 54.3% males, median diabetes duration 7.0 years) from the community-based longitudinal Fremantle Diabetes Study Phase II. All had DR status (none, mild non-proliferative diabetic retinopathy (NPDR), moderate NPDR, or severe NPDR or worse) assessed by colour fundus photography at baseline and at the Year 4 or 6 review. Ultra-performance liquid chromatography-tandem mass spectrometry was used for plasma lipid profiling using baseline samples. Multiple logistic regression was used to identify baseline associates of i) any new or worsening DR and ii) any incident DR. The likelihood ratio test (LRT) was used to evaluate the incremental contribution of potential new lipid biomarkers. The net reclassification improvement (NRI) was also calculated.

Results: Any new/worsening DR was observed in 121 participants (16%) and 35 of 495 without DR at baseline (7.0%) developed DR during follow-up. We detected five lipids independently associated with one or both DR outcomes, specifically cholesterol ester (20:4), fatty acid (20:3), lysophosphatidylglycerol (18:0), lysophosphatidylglycerol (18:1) and phosphatidylcholine (18:0_20:3). For any new/worsening DR, the inclusion of lipid parameters (cholesterol ester (20:4), fatty acid (20:3) and lysophosphatidylglycerol (18:1)) in addition to conventional risk factors (systolic hypertension, HbA1c, blood glucose-lowering treatment intensity and urinary albumin:creatinine) added significantly to the conventional model (LRT, P=0.00002). The NRI gain for at a moderate cut-off of 10% was 5.7% (SE 2.8%; P=0.043). For incident DR, inclusion of lipid parameters (fatty acid (20:3), lysophosphatidylglycerol (18:0) and phosphatidylcholine (18:0_20:3)) with HbA1c as the only conventional risk factor improved model performance (LRT, P=0.00001). The NRI gain at a moderate cut-off of 5% risk of incident DR was 28.3% (P=0.002).

Conclusion: These data demonstrate that disturbances in lipid metabolism are associated with DR progression in type 2 diabetes. The present five lipid biomarkers have not been identified as determinants of incident DR in limited previous longitudinal studies but have the potential to improve DR risk prediction and provide novel insights into the mechanistic pathways underlying the development and progression of DR.