LC-MS/MS Based Metabolomic and Lipidomic Profiling for Biomarker Discovery in Global Developmental Delay

Researchers aiming to identify metabolic signatures and potential biomarkers for global developmental delay (GDD) and intellectual disability (ID) using plasma metabolomics and lipidomics employed a liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based method integrated with multivariate data analysis to comprehensively characterize plasma metabolomics and lipidomics profiles in children diagnosed with GDD/ID compared to typically developing (TD) children. 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 paper based on their work was published in Frontiers in Cell Neuroscience.¹

Global developmental delay (GDD) is defined as the failure for children 5 years of age or younger to achieve developmental milestones; intellectual disability (ID) encompasses general mental ability problems affecting both intellectual and adaptive functioning in those younger than 18 years.² Previous etiologic investigations of GDD and ID exhibit significant overlap, with shared pathogenic mechanisms and risk factors. GDD and ID impact up to 3% of the pediatric population and are connected to significant comorbidities, emotional burden, and high lifetime costs.^3,4

Although metabolomic profiling has emerged as a promising method in the conducting of neurodevelopmental research, with well-characterized biomarkers recognized in autism spectrum disorders (ASD), among them dysregulations in microbial metabolites, niacin metabolism, mitochondria-related metabolites, and amino acid metabolites, a complete metabolomic characterization of GDD/ID remains significantly lacking.⁵ It was this lack of information that inspired the researchers to attempt identifying metabolic signatures and potential biomarkers for diagnosis, as well as possible etiologies of GDD/ID.¹

The researchers report that their 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.¹

“This study,” wrote the authors in their paper,¹ “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.”

While the researchers believe that the biomarkers discovered show strong diagnostic performance as screening tools, future studies are needed to validate their prognostic value and clinical utility in multi-center cohorts.¹

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References

1. Chen, B.; Chen, S.; Xiong, J. et al. The Integration of Plasma Non-Target Metabolomics and Lipidomics Analysis for the Discovery of Global Developmental Delay/Intellectual Disability Biomarkers. Front Cell Neurosci. 2026, 20, 1688339. DOI: 10.3389/fncel.2026.1688339
2. Vasudevan, P.; Suri, M. A Clinical Approach to Developmental Delay and Intellectual Disability. Clin Med (Lond). 2017,17 (6), 558-561. DOI: 10.7861/clinmedicine.17-6-558
3. Bélanger, S. A.; Caron, J. Evaluation of the Child with Global Developmental Delay and Intellectual disability. Paediatr Child Health. 2018, 23 (6), 403-419. DOI: 10.1093/pch/pxy093
4. Hoytema van Konijnenburg, E. M. M.; Wortmann, S. B.; Koelewijn, M. J. et al. Treatable Inherited Metabolic Disorders Causing Intellectual Disability: 2021 Review and Digital App. Orphanet J Rare Dis. 2021, 16 (1), 170. DOI: 10.1186/s13023-021-01727-2
5. Chen, Q.; Qiao, Y.; Xu, X. J. et al. Urine Organic Acids as Potential Biomarkers for Autism-Spectrum Disorder in Chinese Children. Front Cell Neurosci. 2019, 13, 150. DOI: 10.3389/fncel.2019.00150