Branched-Chain and Aromatic Amino Acids Mark Early Metabolic Shifts in Adults with Varying Adiposity

Amino acid metabolism has been increasingly recognized as a central determinant of obesity and insulin resistance, yet the specific contributions of individual amino acids require further clarification. The aim of the study was to detect relationships between serum amino acid concentrations and metabolic parameters in overweight and obese individuals. Amino acid concentrations were measured in 50 individuals classified as normal weight, overweight, or obese, and were analyzed using principal component analysis (PCA), K-means clustering, multiple linear regression, and Random Forest models. Obese individuals exhibited markedly elevated levels of branched-chain amino acids (BCAAs: valine, isoleucine, leucine) and glutamic acid, accompanied by reduced concentrations of serine, glycine, and glutamine, compared with normal weight participants. PCA revealed that the first component, which explained 35.5% of the total variance, was driven primarily by BCAAs, serine, and glutamine, while the second component, accounting for 9.5% of variance, was influenced by threonine, tryptophan, and asparagine. The multiple linear regression model explained 89.6% of the variance in HOMA-IR (R2 = 0.896, p < 0.001), with isoleucine emerging as the strongest positive predictor (p < 0.001), valine and leucine showing additional significant associations (p = 0.035), and tyrosine demonstrating a significant negative association (p = 0.039), while proline was not significant. The Random Forest model predicting insulin resistance achieved robust cross-validated performance (R2 = 0.86 ± 0.06), with valine, isoleucine, and leucine accounting for the majority of predictive importance, followed by tyrosine and glutamine. Together, these findings demonstrate that amino acid profiling provides powerful discriminatory and predictive capacity for insulin resistance and obesity. BCAAs consistently emerged as the most important predictors across complementary analytical frameworks, confirming their central role in metabolic dysregulation, while glycine appeared to exert a potential protective effect. The identification of a metabolically overweight subgroup underscores the heterogeneity of the overweight state and highlights the utility of amino acid profiling for early risk stratification and the development of targeted interventions.

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Journal
International Journal of Molecular Sciences
Published
2026-06-30
DOI
https://doi.org/10.3390/ijms27135912
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Branched-Chain and Aromatic Amino Acids Mark Early Metabolic Shifts in Adults with Varying Adiposity

Marta Jaskulak, Klaudia Antoniak, Katarzyna Zorena, Anna Sośnicka et al.
International Journal of Molecular Sciences
Metabolomics and Mass Spectrometry Studies
article

Branched-Chain and Aromatic Amino Acids Mark Early Metabolic Shifts in Adults with Varying Adiposity

Marta Jaskulak, Klaudia Antoniak, Katarzyna Zorena, Anna Sośnicka, Patrycja Jabłońska, Magdalena Gregorczyk, Iwona Rybakowska
article en

Abstract

Amino acid metabolism has been increasingly recognized as a central determinant of obesity and insulin resistance, yet the specific contributions of individual amino acids require further clarification. The aim of the study was to detect relationships between serum amino acid concentrations and metabolic parameters in overweight and obese individuals. Amino acid concentrations were measured in 50 individuals classified as normal weight, overweight, or obese, and were analyzed using principal component analysis (PCA), K-means clustering, multiple linear regression, and Random Forest models. Obese individuals exhibited markedly elevated levels of branched-chain amino acids (BCAAs: valine, isoleucine, leucine) and glutamic acid, accompanied by reduced concentrations of serine, glycine, and glutamine, compared with normal weight participants. PCA revealed that the first component, which explained 35.5% of the total variance, was driven primarily by BCAAs, serine, and glutamine, while the second component, accounting for 9.5% of variance, was influenced by threonine, tryptophan, and asparagine. The multiple linear regression model explained 89.6% of the variance in HOMA-IR (R2 = 0.896, p < 0.001), with isoleucine emerging as the strongest positive predictor (p < 0.001), valine and leucine showing additional significant associations (p = 0.035), and tyrosine demonstrating a significant negative association (p = 0.039), while proline was not significant. The Random Forest model predicting insulin resistance achieved robust cross-validated performance (R2 = 0.86 ± 0.06), with valine, isoleucine, and leucine accounting for the majority of predictive importance, followed by tyrosine and glutamine. Together, these findings demonstrate that amino acid profiling provides powerful discriminatory and predictive capacity for insulin resistance and obesity. BCAAs consistently emerged as the most important predictors across complementary analytical frameworks, confirming their central role in metabolic dysregulation, while glycine appeared to exert a potential protective effect. The identification of a metabolically overweight subgroup underscores the heterogeneity of the overweight state and highlights the utility of amino acid profiling for early risk stratification and the development of targeted interventions.

International Journal of Molecular SciencesVol. 27(13)
Maritime Institute in Gdansk (PL), Gdańsk Medical University (PL)
Gdański Uniwersytet Medyczny
Reduced inequalities
Openalex Percentile: Top 11%
Metabolomics and Mass Spectrometry Studies
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