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NEFA can serve as good biological markers for the diagnosis of depression in adolescents
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DOI：10.1016/j.jad.2024.01.274.png)
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Abstract
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Background: The incidence of adolescent depression has markedly risen in recent years, with a high recurrence rate into adulthood. Diagnosis in adolescents is challenging due to subjective factors, highlighting the crucial need for objective diagnostic markers. Methods: Our study enrolled 204 participants, including healthy controls (n = 88) and first -episode adolescent depression patients (n = 116). Serum samples underwent gas chromatography-mass spectrometry (GC-MS) analysis to assess non-esterified fatty acids (NEFA) expression. Machine learning and ROC analysis were employed to identify potential biomarkers, followed by bioinformatics analysis to explore underlying mechanisms. Results: Nearly all differentially expressed NEFA exhibited significant downregulation. Notably, nonanoic acid, cis-10-pentadecenoic acid, cis-10-carboenoic acid, and cis-11-eicosenoic acid demonstrated excellent performance in distinguishing adolescent depression patients. Metabolite -gene interaction analysis revealed these NEFAs interacted with multiple genes. KEGG pathway analysis on these genes suggested that differentially expressed NEFA may impact PPAR and cAMP signaling pathways. Limitations: Inclusion of diverse populations for evaluation is warranted. Biomarkers identified in this study require samples that are more in line with the experimental design for external validation, and further basic research is necessary to validate the potential depressive mechanisms of NEFA. Conclusions: The overall reduction in NEFA expression in first -episode adolescent depression patients suggests a potential mediation of depression symptoms through cAMP and PPAR signaling pathways. NEFA levels show promise as a diagnostic tool for identifying first -episode adolescent depression patients.
Keywords:
Adolescent depression
Diagnostic markers
Non-esterified fatty acids
Machine learning
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