Exploratory metabolomics of biomarker identification for the internet gaming disorder in young Korean males

- Atypical blood metabolite levels may reflect abnormal homeostasis in internet gaming disorder (IGD).
- Multiple logistic regression model suggested significant association between plasma metabolites and internet addiction severity.
- Potential biomarker cluster simultaneously discriminated different psychiatric status in combination of metabolites and clinical characteristics.
- Among them were arabitol, myo-inositol, methionine, and depression that were the unique predictors for IGD group.

The main aim of the current research is to characterize the molecular dynamics related to internet gaming disorder (IGD) using non-targeted plasma metabolite profiling based on gas-chromatography time-of-flight mass spectrometry (GC-TOF MS). IGD is a psychiatric disorder instigated by excessive and prolonged internet gaming, which shared many pathological symptoms with attention deficit hyperactivity disorder (ADHD). The prevalence of the disorder has been rapidly increased particularly in East Asia countries (5.9% in South Korea) compared to Europe or North America (0.3-1.0% in United States and 1.16% in Germany). Thus we comparably explored the correlation between plasma metabolites and internet addiction severity in IGD patients, and potential biomarker composite in combination with clinical parameters. The systematic metabolite profiling of 54 blood samples (normal user, N = 28 and IGD, N = 24) identified a total of 104 metabolites out of 1212 metabolic feature, and revealed unique relation of co-linearly regressed set of plasma metabolites (arabitol, myo-inositol, methionine, pyrrole-2-carboxylic acid, and aspartic acid) with internet addiction severity scale (R = 0.795). In addition, orthogonal partial least squared discriminant analysis (OPLS-DA) and receiver operating characteristic (ROC) analysis identified the potential biomarker cluster that simultaneously discriminated the different types of the psychiatric status. The potential biomarker re-composite was comprehensively evaluated by a receiver operating characteristic (ROC) analysis where the AUCs were 0.890, 0.880, 1.000, and 0.935 for control, IGD, AD and IGD + AD, respectively (N = 18, 19, 5, and 10) against the others. This exploratory method may provide robustness of predictive diagnosis in population screening of IGD. The identified metabolic features, the relatedness with clinical parameters, and the putative biochemical linkage will hopefully aid future pathological studies in IGD.