Urinary Ferritin: A Non-inflammatory Iron Marker Linked to Insulin Resistance and Metabolic Syndrome Components

Serum ferritin is well known to be associated with chronic inflammation and insulin resistance. This study investigates urinary ferritin as a potential non-invasive biomarker for metabolic alterations and insulin resistance.

This study analyzed ferritin levels in urine samples from two independent cross-sectional cohorts: IRONMET-continuous glucose monitoring (CGM) (a middle-aged cohort, n=78) and Aging Imageomics (an aged cohort, n=47). Associations between urinary ferritin and clinical and biochemical parameters were assessed using correlation analyses. Untargeted plasma metabolomics was performed in the IRONMET-CGM cohort, and differentially abundant metabolites associated with urinary ferritin and ultrasensitive C-reactive protein were identified using linear models for microarray regression analysis.

In the IRONMET-CGM cohort, urinary ferritin correlated positively with serum glucose, serum ferritin, and transferrin saturation and negatively with transferrin and total iron-binding capacity. In the Aging Imageomics cohort, urinary ferritin showed positive associations with serum glucose, fasting plasma insulin, low-density lipoprotein cholesterol, serum ferritin, right ankle diastolic blood pressure, and the percentage of mean arterial pressure of the right brachial pulse wave and a negative association with high-density lipoprotein cholesterol. Plasma metabolomics profiling revealed that urinary ferritin was positively associated with succinic acid, adipic acid and cis-4-decenoic acid concentrations, suggesting disruptions in fatty acid metabolism. In contrast, metabolites linked to elevated ultrasensitive C-reactive protein, including 3-hydroxyanthranilic acid and formyl-5-hydroxykynurenamine, were associated with the kynurenine pathway and systemic inflammation.

Urinary ferritin is a promising, non-invasive marker of iron metabolism disturbances and metabolic dysregulation. Its associations with glucose metabolism, lipid profiles, and distinct metabolomics signatures suggest potential utility for early detection of metabolic alterations.