TOPLINE:

The MetaboHealth score, derived from 14 metabolomic measures, showed varying effects of dietary strategies for fat loss in middle-aged or older adults with liver insulin resistance (LIR) or muscle insulin resistance (MIR). Combining insulin resistance metabotype with MetaboHealth score tertiles revealed that individuals with low MetaboHealth scores, reflecting better immune-metabolic health, experienced reductions in specific fat percentages with one diet plan, whereas those with the highest scores (poor health status) experienced reductions across two different diet plans.

METHODOLOGY:

• The PERSON study was a randomized controlled trial aimed to determine if the MetaboHealth score could improve the evaluation of dietary intervention effectiveness beyond simply categorizing participants by their tissue-specific insulin resistance metabotype.
• The PERSON study showed varied effects of different diets among individuals with distinct metabotypes of LIR or MIR in cardiometabolic outcomes and body composition. The MetaboHealth score, a recently developed blood-based biomarker, evaluated immune-metabolic health and predicted risks for mortality, frailty, and cognitive decline.
• A total of 242 participants (age, 40-75 years; BMI, 25-40) with insulin resistance underwent a 7-point oral glucose tolerance test to determine their hepatic insulin resistance index and muscle insulin sensitivity index for classification into two groups: LIR or MIR.
• Researchers randomly assigned participants to follow either a high-monounsaturated fatty acid diet or a low-fat, high-protein, high-fiber diet for 12 weeks. Body composition was measured using a DEXA scan, assessing android, gynoid, and total fat percentages; total lean mass percentage; and fat mass, lean mass, and appendicular lean mass indices (in kg/m²).
• Analysis included 117 participants with complete data who were grouped into the lowest and highest tertiles of MetaboHealth score to evaluate differences in cardiometabolic and body composition outcomes.This resulted in LIR and MIR groups with low MetaboHealth scores (n = 28 and n = 34, respectively) and LIR and MIR groups with high MetaboHealth scores (n = 19 and n = 36, respectively).

TAKEAWAY:

• No significant interaction was observed between the MetaboHealth score, insulin resistance metabotype, and diet for cardiometabolic outcomes.
• Individuals with MIR on the low-fat, high-protein, high-fiber diet showed significant reductions in android fat (beta, -0.71; 95% CI, -1.33 to -0.38), gynoid fat (beta, -0.68; 95% CI, -0.98 to -0.25), and total fat percentages (beta, -0.46; 95% CI, -0.80 to -0.12), as well as fat mass index (beta, -0.19; 95% CI, -0.29 to -0.09). Those in the high MetaboHealth tertile with MIR showed significant reductions in total fat percentage and android fat percentage regardless of diet.
• Significant four-way interactions were found between time, diet, metabotype, and MetaboHealth tertile for android fat (beta, 0.28; 95% CI, 0.13-0.54), gynoid fat (beta, 0.28; 95% CI, 0.07-0.39), and total fat percentages (beta, 0.17; 95% CI, 0.02-0.31), as well as fat mass index (beta, 0.07; 95% CI, 0.02-0.11).
• Individuals with LIR in the low MetaboHealth tertile showed reduced android fat and gynoid fat with the high-monounsaturated fatty acid diet, whereas those in the high MetaboHealth tertile showed reductions with both diets.
• As for individuals with MIR, those in the high MetaboHealth tertile showed reductions in android fat, gynoid fat, and total fat percentages across both dietary plans. However, those in the low MetaboHealth tertile had an increase in android fat and gynoid fat with the high-monounsaturated fatty acid diet.

IN PRACTICE:

“Our findings suggest that personalized dietary strategies for middle-aged and older adults with IR [insulin resistance] can be more effective when considering both the specific metabolic phenotype and the broader MetaboHealth score defined in tertiles at baseline. This may indicate that adding global markers of immune-metabolic health to disease-specific ones when investigating responses of adults to interventions may provide outcome benefits,” the authors of the study wrote.

SOURCE:

The study was led by Jordi Morwani-Mangnani, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands. It was published online in Obesity.

LIMITATIONS:

There was imbalance in the number of individuals in the subgroups, with some groups being relatively small. The short duration of the dietary interventions may not capture long-term metabolic adaptations. The reliance on specific dietary regimens may not represent the wider range of dietary patterns beneficial for diverse populations.

DISCLOSURES:

The study was funded by the VOILA consortium. The authors reported having no relevant financial relationships.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.