Distal symmetrical polyneuropathy (DSPN) is a prevalent complication in Type 1 Diabetes, significantly affecting quality of life and healthcare resources. Findings presented at the European Association for the Study of Diabetes 2025 demonstrate that lipidomics can uncover biomarkers for early detection and risk stratification of DSPN.
The study included a discovery cohort of 153 individuals with Type 1 Diabetes and 50 non-diabetic controls. Untargeted serum lipidomics using liquid chromatography–mass spectrometry detected 543 lipid species, with machine learning identifying 42 key lipids. Statistical analysis revealed 14 DSPN-associated lipids, of which six were validated in an independent cohort. Specific ceramides, phosphatidylcholines, lysophosphatidylcholines, and phosphatidylethanolamines showed consistent directional changes between DSPN and non-DSPN participants.
A linear model combining these six lipids with HbA1c, diastolic blood pressure, and age achieved an area under the curve of 0.83 in the discovery cohort and 0.81 in validation, highlighting strong diagnostic performance.
These findings indicate that lipid biomarkers can provide mechanistic insights into DSPN and may guide early intervention and personalized management strategies.
