Deep serum lipidomics identifies evaluative and predictive biomarkers for individualized glycemic responses following low-energy diet-induced weight loss: a PREVIEW sub-study

Background Weight loss through lifestyle interventions, notably low-energy diets, offers glycemic benefits in populations with overweight-associated prediabetes. However, more than 50% of these individuals fail to achieve normoglycemia after weight loss. Circulating lipids hold potential for evaluating dietary impacts and predicting diabetes risk. Objective This study sought to identify serum lipids that could serve as evaluative or predictive biomarkers for individual glycemic changes following diet-induced weight loss. Methods We studied 104 participants with overweight-associated prediabetes, who lost ≥8% weight via a low-energy diet over eight weeks. High coverage lipidomics was conducted in serum samples before and after the dietary intervention. The lipidomic recalibration was assessed using Differential Lipid Abundance Comparisons and Partial Least Squares Discriminant Analyses. Associations between lipid changes and clinical characteristics were determined by Spearman’s correlation and Bootstrap Forest of Ensemble Machine Learning model. Baseline lipids, predictive of glycemic parameters changes post-weight loss, were using Bootstrap Forest Analyses. Results We quantified 439 serum lipid species and 9 related organic acids. Dietary intervention significantly reduced diacylglycerols, ceramides, lysophospholipids and ether-linked phosphatidylethanolamine. In contrast, acylcarnitines, short-chain fatty acids, organic acids, and ether-linked phosphatidylcholine were significantly increased. Changes in certain lipid species (e.g. saturated and monounsaturated fatty acid-containing glycerolipids, sphingadienine-based very long-chain sphingolipids and organic acids) were closely associated with clinical glycemic parameters. Six baseline bioactive sphingolipids primarily predicted changes in fasting plasma glucose. In addition, a number of baseline lipid species, mainly diacylglycerols and triglycerides, were predictive of clinical changes in hemoglobin A1c, insulin and HOMA-IR. Conclusions Newly discovered serum lipidomic alterations and the associated changes in lipid-clinical variables suggest broad metabolic reprogramming related to diet-mediated glycemic control. Novel lipid predictors of glycemic outcomes could facilitate early stratification of individuals with prediabetes who are metabolically less responsive to weight loss, enabling more tailored intervention strategies beyond one-size-fits-all lifestyle modification advice. The PREVIEW lifestyle intervention study was registered at clinicaltrials.gov as NCT01777893 (https://clinicaltrials.gov/study/NCT01777893).