Personalised nutrition perspectives-anti-inflammatory nutritional intervention selectively improves insulin sensitivity in overweight and obese adolescents wherein baseline metabotype predicts response

Introduction: Anti‐inflammatory nutritional approaches may attenuate obesity‐induced insulin resistance. However, results from clinical studies are not entirely consistent, warranting increased focus on determinants of inter‐subject variability particularly within young cohorts at high‐risk. Baseline metabotype may partially discriminate responders from non‐responders. Methods: Metabolic effects of an anti‐inflammatory nutritional supplement containing LC n‐3 PUFA, vitamin C, vitamin E, and polyphenols, were determined in overweight and obese adolescents (n = 58; mean +/‐ SD age 15.9 +/‐ 1.6y; BMI 32.1 +/‐ 6.5kg/m2) by an 8‐wk randomised, crossover, placebo‐controlled intervention. Subjects who demonstrated >10% improvement in HOMA‐IR were categorised as responders. Results: Anti‐inflammatory nutritional supplementation selectively reduced HOMA‐IR in 40% of subjects (responders; supplement ‐32.05 +/‐ 18.02% v placebo 13.13 +/‐ 54.09%, p = 0.004). In comparison with non‐responders, responding subjects demonstrated an adverse pre‐treatment metabotype characterised by increased HOMA‐IR, total cholesterol and LDL cholesterol despite similar BMI (p = 0.001, p = 0.029, p = 0.024, p = 0.236, respectively). Stepwise multiple regression analysis confirmed baseline HOMA‐IR and LDL:HDL ratio as significant independent predictors of HOMA‐IR response to anti‐inflammatory supplementation (R2 = 0.432, p < 0.001). On‐going analysis is defining the molecular basis of the differential response. Conclusion: These results demonstrate heterogeneity with respect to the insulin sensitising effects of anti‐inflammatory nutritional supplementation. Despite similar BMI to non‐responders, the insulin resistant and dyslipidaemic metabotype of responders enhanced the impact of anti‐inflammatory nutritional approaches. This illustrates potential efficacy optimisation within the context of personalised nutrition.