# The Association Between Metabolomic and Usual Biochemical Data Helps to Detect Insulin Resistance

## TL;DR

This study shows that metabolomic markers can detect early signs of insulin resistance even when traditional blood tests appear normal.

## Contribution

The study identifies novel metabolomic biomarkers that predict insulin resistance in individuals with normal conventional biochemical profiles.

## Key findings

- A TG/HDL ratio > 2 and increased urinary kynurenate excretion are linked to a 3.6-fold higher risk of insulin resistance.
- Elevated insulin levels with urinary α-ketoisovalerate are associated with a 2.7-fold increased risk of insulin resistance.
- Significant differences in plasma insulin, HbA1c, and HOMA-IR were found between healthy and diseased individuals.

## Abstract

Background: Chronic noncommunicable diseases account for nearly 80% of global deaths and are strongly associated with insulin resistance (IR). One of the most significant clinical findings of the past two decades is that the molecular mechanisms underlying immune and metabolic systems have been evolutionarily conserved across species. Methods: This study included 34 volunteers (19 men and 15 women). Demographic data were collected using validated questionnaires. Anthropometric measurements (weight, height, waist-to-hip ratio, and body composition assessed by tetrapolar bioimpedance) were obtained directly. Laboratory analyses included fasting glucose and insulin, glycated hemoglobin, HDL cholesterol, total cholesterol, triglycerides, organic aciduria, and additional biochemical markers assessed using standard methods. Group comparisons were performed using parametric or nonparametric statistical tests according to data distribution, as specified in the figure legends. Results: The primary analyses focused on identifying early metabolomic alterations associated with insulin resistance in individuals whose conventional biochemical parameters were within laboratory reference ranges. Individuals with a TG/HDL ratio > 2 and increased urinary kynurenate excretion exhibited a 3.6-fold higher relative risk of insulin resistance, while elevated insulin levels combined with urinary α-ketoisovalerate were associated with a 2.7-fold increased risk. Significant differences in plasma insulin, HbA1c, and HOMA-IR were observed between healthy and diseased individuals (p < 0.05), indicating early metabolic dysfunction preceding clinical disease onset. Conclusions: Metabolomic biomarkers serve as reliable indicators of subclinical metabolic disturbances, revealing significant risks in major metabolic pathways even in individuals with conventional exams within normal limits. Early detection through these metabolomic markers may enable personalized interventions aimed at preserving cellular function and systemic metabolic balance.