HPLC–MS-Based Targeted Metabolomics Reveals Urinary Biomarkers Linked to the Microbiota–Gut–Brain Axis in Children with ASD

While multiple studies have shown that autism spectrum disorder (ASD) is accompanied by abnormalities in multiple metabolic pathways, the fluctuations of certain metabolites involved in these pathways have shown debatable results. A study conducted by researchers at Southeast University, the Changsha Cultural Creative and Arts Vocational College, Soochow University, and the Southeast University in Suzhou (all in China) aimed to identify metabolic characteristics that can distinguish children with ASD by using targeted metabolomics analysis on several types of metabolites related to the microbiota-gut-brain axis, using high-performance liquid chromatography-mass spectrometry (HPLC-MS) in the separation process. A paper based on this work was published in Frontiers in Psychology.¹

Research shows that ASD is linked to changes in how the body processes things like energy and gut bacteria, but the findings have been mixed.² For example, one study found a difference in how autistic children process sugar, while another study found no difference at all.^3,4 When researchers measure these chemicals in the body, they generally use two approaches:

• Broad (non-targeted) testing,which looks at a wide range of chemicals to get a “big picture,” but the measurements aren't always exact or easy to reproduce.
• Specific (targeted) testing,which focuses on a smaller group of chemicals and provides much more accurate and reliable measurements.⁵

The researchers working on the study which this paper is focused on used chromatography and spectrometry techniques to closely examine specific chemicals in urine (such as vitamins, proteins, and stress hormones) that help communicate between the gut and the brain. By looking for unusual patterns in these chemicals, they hope to better understand autism and find new diagnostic and treatment methods.¹

A total of 54 children with ASD and 47 healthy children (HC) were recruited for this study, with data from the Autism Behavior Checklist (ABC) scale for children with ASD collected. Based on HPLC-MS analysis, the metabolic characteristics of several types of metabolites related to the microbiota-gut-brain axis were discovered in urine samples. Single-variable and multi-variable analyses were conducted using MetaboAnalyst 6.0 and SPSS 27.0.1 to identify potential differential metabolites. The association between differential metabolite concentrations and ABC scores in children with ASD was evaluated using Spearman's rank correlation analysis.¹

The researchers report that seven differential indicators (the ratio of cortisol to cortisone (R), creatinine, cortisol, taurine, histamine, homocysteine, and methionine) were identified in the analysis. The combined index diagnostic model constructed based on these indicators demonstrated strong discriminatory power, with an area under the receiver operating characteristic (ROC) curve of 0.943, a sensitivity of 92.6%, and a specificity of 93.7%. The researchers believe that the abovementioned biochemical indicators may be involved in the pathological physiological process of autistic behavioral symptoms from different aspects, and that their findings contribute to a better understanding of the underlying mechanisms of ASD.¹

However, the authors of the paper admit to their study having some limitations. Firstly, the sample size is relatively small, with only 54 children with ASD and 47 healthy children included, which may limit the general applicability of the research results and increase the possibility of selection bias. “Repeating these results in a larger cohort, the authors write,¹ “would make the conclusions more convincing. Furthermore, information on potential confounding factors which may affect the metabolic profile and introduce additional variability in the results (such as diet, weight, and medication) was not examined. Thirdly, using creatinine as a standard baseline to measure other chemicals doesn't work perfectly because creatinine levels naturally change on their own. A shifting baseline can throw off the math and make the results less accurate. To make the findings more trustworthy, it would be better to use a few different baseline methods at the same time to double-check the work. Finally, all participants were preschool children from one city in China, thus renderingresearch conclusions as inapplicable to all individuals with ASD in different regions, races, and ages.¹

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References

1. Shen, K.; Huang, J.; Liu, D. et al. Alterations of Several Types of Metabolites Related to Microbiota-Gut-Brain Axis in Urine of Children with Autism Spectrum Disorder. Front Psychiatry 2026, 17, 1784658. DOI: 10.3389/fpsyt.2026.1784658
2. Rangel-Huerta, O. D.; Gomez-Fernández, A.; de la Torre-Aguilar, M. J. et al. Metabolic Profiling in Children with Autism Spectrum Disorder with and without Mental Regression: Preliminary Results from a Cross-Sectional Case-Control Study. Metabolomics 2019, 15 (7), 99. DOI: 10.1007/s11306-019-1562-x
3. Noto, A.; Fanos, V.; Barberini, L. et al. The Urinary Metabolomics Profile of an Italian Autistic Children Population and their Unaffected Siblings. J Matern Fetal Neonatal Med. 2014, 27 (S2), 46-52. DOI: 10.3109/14767058.2014.954784
4. Evans, C.; Dunstan, R. H.; Rothkirch, T. et al. Altered Amino Acid Excretion in Children with Autism. Nutr Neurosci. 2008, 11 (1), 9-17. DOI: 10.1179/147683008X301360
5. Anh, N. K.; Thu, N. Q.; Tien, N. T. N. et al. Advancements in Mass Spectrometry-Based Targeted Metabolomics and Lipidomics: Implications for Clinical Research. Molecules 2024, 29 (24), 5934. DOI: 10.3390/molecules29245934