Citation

Guo Z, Liu Y, Wang C, Li S, Yu L, Wu W, You X, Zhang Y, Teng Z, Zeng Y. Front. Psychiatry 2023; 14: e1126615.

Copyright

(Copyright © 2023, Frontiers Media)

DOI

10.3389/fpsyt.2023.1126615

PMID

37065902

PMCID

PMC10102595

Abstract

BACKGROUND: Non-suicidal self-injury (NSSI) is self-injurious behavior without suicidal intent commonly seen in the adolescent population and poses a serious threat to the life safety of adolescents. Related researches suggest a possible correlation between addiction and the occurrence of NSSI. This study aimed to explore the correlation between addiction and NSSI from a molecular biological perspective by analyzing the differential expression of addiction-related genes in NSSI patients.

METHODS: (1) The association between addiction and non-suicidal self-injury in a Chinese adolescent population was verified with the help of questionnaires on substance and non-substance addictions and non-suicidal self-injury among 1,329 adolescents in China, (2) Screening for key genes associated with addiction by bioinformatics analysis, and (3) RT-qPCR experiment was performed to validate key genes and Receiver Operating Characteristic curves were plotted for target genes.

RESULTS: (1) Substance and non-substance addictions were all significantly correlated with non-suicidal self-injury, (2) Four target genes: SERPINA3, SLC14A1, RPS6 and RPS3A were screened by bioinformatics technique, and (3) Relative quantitative analysis by RT-qPCR revealed that the expression levels of SLC14A1 (p < 0.01), RPS6 (p < 0.05) and RPS3A (p < 0.01) were significantly higher in NSSI patients than in healthy controls.

CONCLUSION: (1) The significant association between addiction and NSSI exists in the Chinese adolescent population and (2) Addiction-related genes SLC14A1, RPS6, and RPS3A are differentially expressed in adolescents with NSSI. The genes have the potential to become biological markers for the diagnosis of NSSI.

Language: en

Keywords

bioinformatics; addiction; non-suicidal self-injury; biomarker; genes