# The integration of plasma non-target metabolomics and lipidomics analysis for the discovery of global developmental delay/intellectual disability biomarkers

## TL;DR

This study uses plasma metabolomics and lipidomics to find biomarkers for global developmental delay and intellectual disability in children.

## Contribution

The integration of metabolomics and lipidomics identifies novel biomarkers and metabolic pathways associated with GDD/ID.

## Key findings

- A combination of 11 metabolites and lipids effectively discriminates GDD/ID from typically developing children.
- Key biomarkers include glycerophosphocholine, sphinganine, 2-ketohexanoic acid, and specific diacylglycerols with high AUC values.
- Metabolic pathways like sphingolipid and lysine metabolism are implicated in GDD/ID pathogenesis.

## Abstract

This study aimed to identify metabolic signatures and potential biomarkers for global developmental delay (GDD) and intellectual disability (ID) using plasma metabolomics and lipidomics. The research sought to evaluate the feasibility of these methods for early identification and to explore the underlying metabolic pathways associated with GDD/ID.

A liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS)-based method integrated with multivariate data analysis was employed to comprehensively characterize plasma metabolomics and lipidomics profiles in children diagnosed with GDD/ID compared to typically developing (TD) children. The study focused on identifying distinct metabolites and lipids that could differentiate GDD/ID from TD children.

The analysis revealed that a combination of 11 metabolites and lipids could effectively discriminate between GDD/ID and TD children. Receiver operating characteristic (ROC) analysis identified several potential biomarkers for GDD/ID. In positive ion mode, glycerophosphocholine (AUC = 0.899) and sphinganine (AUC = 0.859) showed diagnostic potential. Negative ion mode analysis revealed five biomarkers, notably 2-ketohexanoic acid (AUC = 0.912) and N-acetyl-L-aspartic acid (AUC = 0.870). Lipidomics analysis highlighted two high-performance biomarkers: diacylglycerol (DAG) (16:0/16:0) (AUC = 0.956) and DAG (16:0/18:0) (AUC = 0.949). Key metabolic pathways associated with GDD/ID included D-glutamine, D-glutamate, alanine, aspartate, glutamate, sphingolipid, histidine, arginine, and proline metabolisms. Furthermore, lysine metabolic pathways, including degradation and biosynthesis, as well as aminoacyl-tRNA biosynthesis, were implicated in GDD/ID pathogenesis.

This study identified putative biomarkers and metabolic pathways associated with GDD/ID, highlighting the potential of combined plasma metabolomics and lipidomics for early screening of GDD/ID and providing tentative insights into its pathophysiology. The biomarkers show strong diagnostic performance as screening tools, but future studies are needed to validate their prognostic value and clinical utility in multi-center cohorts.