Abstract
BACKGROUND: Schizophrenia (SCZ) is a severe mental disorder, and early diagnosis and intervention are crucial for improving prognosis. An increasing number of studies have demonstrated the association between neurotransmitters and the SCZ. This study aims to explore potential diagnostic biomarkers for early-onset SCZ from the perspective of neurotransmitters. METHODS: We recruited 116 patients with early-onset SCZ and 70 healthy controls. Targeted metabolomics was used to detect the expression of neurotransmitters in peripheral blood. Further analysis was conducted using pathway analysis, correlation analysis, and machine learning methods. RESULTS: There were 25 neurotransmitters that were differentially expressed and significantly upregulated in the SCZ group. These substances were enriched in four metabolic pathways, including cysteine and methionine metabolism; glycine, serine and threonine metabolism; phenylalanine, tyrosine and tryptophan biosynthesis, as well as alanine, aspartate and glutamate metabolism. Further analysis revealed that neurotransmitters such as methionine, sarcosine, tryptophan, tyrosine, phenylalanine and glutamine are positively correlated with positive symptoms. Sarcosine is also positively correlated with negative symptoms and general psychiatric symptoms. Methionine, sarcosine, tyrosine and glutamine are positively correlated with the total score of the Positive and Negative Syndrome Scale (PANSS). Finally, we constructed a diagnostic model using machine learning techniques. CONCLUSION: In this study, we found 25 differentially expressed neurotransmitters. Among them, the neurotransmitters with key roles were correlated with the patients’ PANSS scores. Furthermore, we constructed a diagnostic model based on six neurotransmitters. Upon validation, the model demonstrated high diagnostic efficacy, providing new insights into the pathogenesis and diagnosis of early-onset SCZ. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12967-025-07289-2.