# Multi-matrix metabolomics in rare monogenic diabetes syndromes: Analysis of oral fluids and serum in carriers of pathogenic variants in the ALMS1/BBS genes

## TL;DR

This study uses metabolomic profiling of saliva, gingival fluid, and serum to identify metabolic differences in individuals with monogenic diabetes syndromes or genetic predisposition.

## Contribution

The study introduces a multi-matrix metabolomic approach using oral fluids and serum to detect metabolic indicators in rare diabetes syndromes and carriers of ALMS1/BBS gene variants.

## Key findings

- Seven metabolites (valine, 3-HBA, alanine, threonine, urea, isoleucine, phenylalanine) were consistently significant across all sample types in ALMS+BBS patients.
- Levels of aromatic and branched-chain amino acids correlated with insulin resistance and obesity severity in saliva and serum.
- The multi-matrix approach provides a broader view of metabolic alterations linked to ALMS1 and BBS gene variants.

## Abstract

Metabolomic profiling enables the identification of specific biochemical alterations in various diseases, including rare monogenic diabetes and obesity syndromes such as Alström syndrome (ALMS) and Bardet–Biedl syndrome (BBS). These disorders are characterized by early-onset obesity, insulin resistance, diabetes mellitus, retinodystrophy and other symptoms, but some features may also occur in heterozygous carriers of pathogenic or likely pathogenic variants in ALMS1 and BBS genes. The aim of the study was to compare the metabolomic profiles of saliva, gingival crevicular fluid (GCF) and serum between ALMS/BBS patients and heterozygous carriers (n = 33) in relation to participants with simple obesity (n = 20) and healthy controls (n = 30) using gas chromatography coupled to mass spectrometry (GC-MS). The study showed significant differences in the levels of metabolites in saliva, GCF and serum, comparing the ALMS+BBS group with the other groups. In the analysis of statistically significant metabolites in all matrices, seven of them (valine, 3-HBA, alanine, threonine, urea, isoleucine, and phenylalanine) were consistently significant in all sample types. Levels of aromatic amino acids/branched-chain amino acids in saliva and serum were correlated with insulin resistance and the severity of obesity. In conclusion, the study identifies metabolic indicators that distinguish individuals with monogenic diabetes and obesity syndromes or genetic predisposition alone from other groups. The multi-matrix approach using available biological materials such as saliva and GCF provides a broader view of the metabolic alterations associated with variants in ALMS1 and BBS genes. This approach may support both future mechanistic and translational studies of metabolic dysfunction in these populations.