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- Title
Saliva insulin tracks plasma insulin across the day following high-carbohydrate and low-carbohydrate meals.
- Authors
Rafiei, Hossein; Omidian, Kosar; Chang, Courtney Rochelle; Little, Jonathan Peter
- Abstract
Non-invasive monitoring of insulin could hold promise to identify those with, or at risk for developing, insulin resistance. We aimed to examine saliva insulin responses across the day following high- and low-carbohydrate meals and evaluate whether changes in saliva insulin might accurately reflect changes in plasma insulin. In two randomized crossover studies, young normal weight men (NW; n = 8; Study 1) and adults with overweight/obesity (OO; n = 8; Study 2) completed two 9-h experimental trials in which the participants consumed isocaloric mixed high-carbohydrate (HC) or low-carbohydrate (LC) meals at 0, 3, and 6 h. Plasma and saliva samples were collected at fasted baseline and every 30 min for a total of 19 samples across 9 h. Overall, findings revealed a similar trend for postprandial saliva and plasma insulin responses regardless of the time of the day with a ∼30–45 min lag between saliva and plasma insulin responses. In both NW and OO groups, saliva and plasma insulin area under the curve (AUC) and incremental AUC were significantly higher in HC condition as compared to LC condition (all P ≤ 0.002). Nine-hour plasma and saliva insulin total AUCs were strongly and very strongly correlated in both HC (r = 0.68; P = 0.007) and LC (r = 0.84, P < 0.001) conditions, respectively. Saliva insulin is proportionate to and appears to reasonably track plasma insulin across the day with a ∼30–45 min delay. Saliva insulin shows promise as a non-invasive method to discern between low and high plasma insulin and may have utility in predicting the degree of insulin resistance (NCT03374436).
- Subjects
OBESITY; SALIVA; FOOD consumption; BLOOD sugar; INSULIN; COMPARATIVE studies; RESEARCH funding; DIETARY carbohydrates; CROSSOVER trials; RECEIVER operating characteristic curves; MEALS
- Publication
Applied Physiology, Nutrition & Metabolism, 2023, Vol 48, Issue 9, p700
- ISSN
1715-5312
- Publication type
Article
- DOI
10.1139/apnm-2023-0066