People of South Asian (SA) origin have an elevated risk of cardiometabolic dysfunction and respond differentially to physical activity. Mechanisms underpinning these observations are incompletely understood. We investigated protein signatures of ethnicity, changing physical activity and their interaction. A discovery analysis was conducted using data from 794 SA to 49,153 white European (WE) participants in UK Biobank, assessing associations between 726 plasma proteins and physical activity and ethnicity. Findings were validated in a targeted cohort of 58 individuals with non-diabetic hyperglycaemia, taken from a larger randomised controlled trial (PROPELS, n = 1366), stratified by ethnicity and changes in accelerometer assessed physical activity (steps/day) over 48 months. Individuals matched for ethnicity, age and sex that increased and decreased their physical activity over time were sampled, creating four groups (SA increasers [n = 15], SA decreasers [n = 15], WE increasers [n = 14], WE decreasers [n = 14]). Proteins were analysed using Olink inflammation and cardiovascular panels. In the discovery phase, 464 proteins were associated with physical activity and 375 with ethnicity. In the validation cohort, only interleukin-6 (IL-6) was significantly associated with physical activity, showing downregulation in those who increased activity. Sixteen proteins were validated for ethnicity, including upregulated chemokines (e.g., CCL28, CCL15, CCL13, CCL11, CCL26), hepatokines (FABP1), adipokines (FABP2), and pancreatic proteins (AMY2A, AMY2B), with CXCL14, GHRL and PRTN3 downregulated in SAs. Distinct proteomic profiles were associated with ethnicity and physical activity. IL-6 emerged as a key marker of physical activity response, while ethnicity-related proteins highlighted immune, inflammatory, and metabolic pathways. NIHR Leicester Biomedical Research Centre.

Objective: To determine whether a pre-lunch single bout of moderate-intensity aerobic exercise (AEX) alters time spent in hypoglycaemia (<3.0 mmol/L) during the subsequent 24 hours (24-h) and parameters of glucose homeostasis in individuals without diabetes after metabolic/bariatric surgery (MBS). Methods: In a randomised crossover study, 15 participants completed two conditions: 30min treadmill walking at 60% V̇O₂peak (AEX) and time-matched sitting (CON). After an overnight fast and a standardised breakfast, participants performed AEX or CON, and both conditions were followed by an identical lunch administered as a mixed-meal tolerance test (MMTT). Continuous glucose monitoring (CGM) assessed glucose levels for 24-h post-intervention, during which participants consumed standardised meals. CGM data were available for analysis in 11 participants. The primary outcome was time spent with glucose <3.0 mmol/L during the 24-h post-intervention. Secondary outcomes included other CGM-derived glucose metrics and plasma glucose and insulin responses during the 3-h MMTT. Results: Only one isolated hypoglycaemic event (<3.0 mmol/L) occurred, precluding statistical analysis of the primary outcome. Mean 24-h glucose (AEX: 6.4 (1.0); CON: 6.5 (0.9) mmol/L; p = 0.57) and time <3.9 mmol/L (AEX 0 (0.0, 0.5); CON 0 (0.0, 0.5) %; p = 0.68) did not differ between conditions. AEX reduced glucose coefficient of variation (p < 0.01). During the MMTT, nadir, peak, and AUC _0-180 glucose, as well as pre-MMTT insulin concentrations, were higher following AEX (all p < 0.05). Conclusions: A pre-lunch 30-min bout of AEX did not increase the 24-h risk of hypoglycaemia post-MBS but elevated post-MMTT glucose levels.

Background/Objectives: Sleeve gastrectomy (SG) improves glycaemic control; however, it also markedly accelerates gastric emptying, which can lead to exaggerated postprandial glucose and insulin excursions and, in some cases, postprandial hyperinsulinaemic hypoglycaemia. In non-surgical populations, fat preloads can reduce postprandial glycaemia by slowing gastric emptying, but their effects after SG are unclear. Methods: Ten adults >1-year post-SG completed a randomised, open-label, crossover study involving two mixed-meal tolerance tests (MMTTs), preceded (−30 min) by either a moderate, fat-dominant preload (28 g Brazil nuts) or 100 mL water (control). Blood samples were collected over three hours to assess plasma glucose, insulin, c-peptide, and total glucagon-like peptide-1 (GLP-1). Hypoglycaemia and dumping symptoms were assessed using validated questionnaires. Nadir plasma glucose concentration was the primary outcome. Results: Nadir plasma glucose was identical between conditions (both 3.8 mmol/L; 95% CI: −0.4, 0.3, p = 0.849), and neither peak glucose nor overall postprandial glucose exposure (incremental area under the curve iAUC_{0–180 min}) differed between the preload and water conditions. Insulin and c-peptide concentrations immediately before the MMTT were higher after the fat-dominant preload (both p < 0.001). Overall insulin and c-peptide responses during the MMTT (iAUC_{0–180 min}) remained comparable between conditions (95% CI −225, 2665; p = 0.442 and −67,787, 70,263; 0.968), but peak values for both hormones were higher after the preload (95% CI 2.9, 79.1, p = 0.038 and 17.3, 2402.7, p = 0.040, respectively). Total GLP-1 was also elevated prior to the MMTT (95% CI 1.6, 22.8, p = 0.028), while its early and overall postprandial responses did not differ (both p > 0.05). Ratings of hypoglycaemia and dumping symptoms were similar for both study arms. Discussion: A moderate, fat-dominant preload consumed before a mixed meal did not alter nadir or overall postprandial glucose in adults without diabetes after SG. However, the preload was associated with higher peak insulin secretion, a finding that should be interpreted with caution, as the study was not powered for secondary outcomes. Given the unique gastrointestinal physiology after SG, further research is needed to determine how different nutrient compositions or timing approaches influence postprandial glucose homeostasis in this population.