Retrospective cohort study identifies that immune-metabolic status affects postoperative recovery in adults after sleeve gastrectomy, suggesting personalized treatments may improve outcomes.
Background: Sleeve gastrectomy (SG) is an effective treatment for severe obesity; however, postoperative metabolic responses vary considerably. Immune-metabolic dysregulation has been suggested as a key driver of this heterogeneity, yet the integrated effects of immune and metabolic status on surgical outcomes remain unclear. Methods: We conducted a retrospective single-center cohort study of adults undergoing SG between January 2021 and December 2023, with a 12-month postoperative follow-up. Comprehensive molecular analyses – including circulating cytokine profiling, plasma lipid analysis, and transcriptomic sequencing of subcutaneous and visceral adipose tissues – were performed. Participants were stratified into two groups based on preoperative immune-metabolic profiles defined by fasting insulin, C-reactive protein, and cytokine levels: a resilient profile (Group1) and a dysregulated profile (Group2). Results: Among 45 patients who underwent SG [mean (standard deviation, SD) age, 36.7 (11.0) years; 26 (57.8%) female], nine (20.0%) were classified as Group1 and 36 (80.0%) as Group2. At 12 months, mean (SD) total weight loss was 31.0 (6.8)% in Group1 vs. 25.9 (7.1)% in Group2 [difference, 5.1 (95% CI 1.9–8.3); P = .003]. Group1 showed greater improvement in insulin sensitivity and transient cytokine activation, whereas Group2 exhibited persistent inflammation, elevated long-chain lipid species, and transcriptomic enrichment in lipid storage, interleukin-17 signaling, and olfactory receptor pathways. Subclustering of Group2 revealed adipose-tissue-specific heterogeneity associated with divergent postoperative weight-loss trajectories, despite similar baseline profiles. Conclusions: Preoperative immune-metabolic status was associated with postoperative metabolic recovery after SG. Integrating immune-metabolic profiling with adipose transcriptomics may help identify patients more likely to achieve favorable outcomes and guide personalized interventions to enhance metabolic recovery.
No takes yet. Share an insight, caveat, or question.
Choi et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: