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Urinary Branched-Chain Amino Acids are New Biomarkers for Insulin Resistance Detection and Cardiometabolic Diseases Prevention

20 Pages Posted: 5 Sep 2022

See all articles by Francisco Santos Schneider

Francisco Santos Schneider

Université de Montpellier - Sys2Diag UMR9005 CNRS

Alimata Ouedraogo

Université de Montpellier - Sys2Diag UMR9005 CNRS

Hugo Fenech

Université de Montpellier - Sys2Diag UMR9005 CNRS

Julie Baptiste

Université de Montpellier - Sys2Diag UMR9005 CNRS

Marie Christine Picot

University Hospital of Montpellier - Clinical Investigation Centre (CIC)

Mellis Alali

Université de Montpellier - Sys2Diag UMR9005 CNRS

Telma Mountou

Université de Montpellier - Sys2Diag UMR9005 CNRS

Eric Renard

Université de Montpellier - Montpellier University Hospital

Franck Molina

Université de Montpellier - Sys2Diag UMR9005 CNRS

More...

Abstract

Background: Insulin resistance (IR) is a risk factor for type 2 diabetes (T2D) and cardiovascular diseases (CVD). Early identification of IR in large populations remains uneasy, although desirable for promoting lifestyle modifications and T2D/CVD prevention. Fasting blood branched-chain amino acids (bBCAA) are biomarkers for IR and their impaired catabolism contributes to IR development.

Methods: We present here an innovative test for fast and reliable IR screening based on the detection of urine BCAA (uBCAA). In this monocentric clinical study, individuals presenting normal kidney function were recruited and distributed in three groups according to their BMI and IR states (normal weight, insulin-sensitive (NWIS); overweight insulin-sensitive (OWIS); and overweight insulin-resistant (OWIR).

Findings: uBCAA levels were significantly higher in OWIR compared to OWIS and NWIS (148·2µM; 100·5µM; and 51·0µM, respectively). uBCCA levels were still significantly higher in OWIR when compared to the gathered composite insulin-sensitive individuals (CIS – 78·7µM).

Interpretations: Our results demonstrate that uBCAA can be used as biomarkers of insulin-resistant subjects despite their BMI. Their simplified quantification using our lab-free approach and appropriate thresholds could allow action for an effective reduction of risk for cardiometabolic-based chronic diseases.

Trial Registration: The study was registered at www.clinicaltrials.gov (NCT04010903).

Funding: SkillCell, CNRS, Région Occitanie

Declaration of Interest: FSS, FM and ER declare a pending patent related to this work (Application number EP22177090.2). The other authors declare no conflict of interest.

Ethical Approval: A French ethical committee (CPP-Ile de France VII) approved the study and all subsequent amendments on August 23, 2019.

Keywords: Non-invasive screening test, Cardiometabolic-based Chronic Disease, Risk for diabetes, Risk for cardiovascular disease, insulin resistance, Urinary Branched-Chain Amino Acids

Suggested Citation

Santos Schneider, Francisco and Ouedraogo, Alimata and Fenech, Hugo and Baptiste, Julie and Picot, Marie Christine and Alali, Mellis and Mountou, Telma and Renard, Eric and Molina, Franck, Urinary Branched-Chain Amino Acids are New Biomarkers for Insulin Resistance Detection and Cardiometabolic Diseases Prevention. Available at SSRN: https://ssrn.com/abstract=4210299 or http://dx.doi.org/10.2139/ssrn.4210299

Francisco Santos Schneider

Université de Montpellier - Sys2Diag UMR9005 CNRS ( email )

Montpellier
France

Alimata Ouedraogo

Université de Montpellier - Sys2Diag UMR9005 CNRS ( email )

Montpellier
France

Hugo Fenech

Université de Montpellier - Sys2Diag UMR9005 CNRS ( email )

Montpellier
France

Julie Baptiste

Université de Montpellier - Sys2Diag UMR9005 CNRS ( email )

Montpellier
France

Marie Christine Picot

University Hospital of Montpellier - Clinical Investigation Centre (CIC) ( email )

France

Mellis Alali

Université de Montpellier - Sys2Diag UMR9005 CNRS ( email )

Montpellier
France

Telma Mountou

Université de Montpellier - Sys2Diag UMR9005 CNRS ( email )

Eric Renard

Université de Montpellier - Montpellier University Hospital ( email )

Franck Molina (Contact Author)

Université de Montpellier - Sys2Diag UMR9005 CNRS ( email )

Montpellier
France
+33 (0) 467 047 463 (Phone)

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