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Psychiatry Investig > Volume 16(6); 2019 > Article
Jeong, Paik, Choi, Cho, Choi, Choi, and Kim: Altered Plasma Levels of Glial Cell Line-Derived Neurotrophic Factor in Patients with Internet Gaming Disorder: A Case-Control, Pilot Study


Glial cell line-derived neurotrophic factor (GDNF) has been reported to be involved in negatively regulating the effects of addictive disorders. The objective of this study was to investigate alterations in the levels of GDNF in patients with Internet gaming disorder (IGD) and to assess the relationship between GDNF levels and the severity of IGD indices. Nineteen male patients with IGD and 19 sexmatched control subjects were evaluated for alteration of plasma GDNF levels and for relationship between GDNF levels and clinical characteristics of Internet gaming, including the Young’s Internet Addiction Test (Y-IAT). The GDNF levels were found to be significantly low in patients with IGD (103.2±62.0 pg/mL) compared with the levels of controls (245.2±101.6 pg/mL, p<0.001). GDNF levels were negatively correlated with Y-IAT scores (Spearman’s rho=-0.645, p=<0.001) and this negative correlation remained even after controlling for multiple variables (r=-0.370, p=0.048). These findings support the assumed role of GDNF in the regulation of IGD.


Glial cell line-derived neurotrophic factor (GDNF) is neuropeptide and it is essential for the maintenance of dopaminergic neurons [1] and has been shown to enhance re-growth of adult dopamine neurons following neural insult [2].
Furthermore, several preclinical studies indicate that GDNF plays an important role in the behavioral effects of abused drugs [3] and neuroadaptation induced by repeated exposure to drugs, including cocaine [4,5], methamphetamine [6,7], morphine [8], and alcohol [9-11] in the mesolimbic dopamine pathway. Intriguingly, most of the studies suggest that activation of the GDNF system results in the prevention of behavioral adaptation to drugs of abuse [3]. Intra-ventral tegmental area (VTA) infusion of GDNF was effective in decreasing conditioned place preference (CPP) to cocaine [3]; GDNF heterozygote knockout mice, which express lower GDNF levels than their wild-type counterparts, show increased methamphetamine [6] and morphine CPP [8]. In addition, previous studies have suggested that GDNF reduces ethanol consumption and relapse [9-11].
Internet gaming disorder (IGD) is currently included in Section III of the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the DSM-5 proposed that IGD is a pattern of excessive and prolonged Internet gaming that results in a cluster of cognitive and behavioral symptoms, including loss of control over gaming, tolerance, and withdrawal symptoms [12]. These characteristics are traditionally associated and shared with substance-related addictions [12,13] and gambling disorder [14,15]. Furthermore, from a neurobiological perspective, recent neuroimaging studies have shown that IGD may have an impact on the dopaminergic system [13]. Dopaminergic neurons in the VTA are a critical element of the neural circuitry implicated in addictive behavior and the mesolimbic dopaminergic circuit has also been implicated in addiction [16]. In studies using positron emission tomography scanning [17,18], increased release of dopamine to D2 receptors, especially in the ventral striatum, was suggested following a game play in a healthy male adult. Another study using single photon emission computed tomography [19] suggests that the level of dopamine release in the ventral striatum during an Internet game is comparable to that induced by psychostimulant drugs [20,21].
These findings suggest that GDNF, which plays a role in mesolimbic dopamine circuits, is associated with IGD. However, there are no clinical study results that show altered levels of GDNF in IGD. Therefore, the aims of the present study were to investigate alterations in the plasma levels of GDNF in IGD patients compared to that in healthy controls and to assess the relationship between GDNF levels and the severity of IGD indices.



Nineteen male IGD patients were recruited and diagnosed according to the DSM-5 criteria. The patients were still playing Internet games at the time of enrollment and had not previously received any treatment for IGD. IGD group subjects with past or current medical disorders, neurological disorders, or other psychiatric disorders including substance use disorders were excluded. The control group consisted of 19 healthy male subjects and was negative for medical, neurological, and psychiatric disorders and regular use of any medication.

Measures and procedure

Participants were assessed using the Alcohol Use Disorders Identification Test (AUDIT) [22], Fagerström Test for Nicotine Dependence (FTND) [23], Beck Depression Inventory (BDI)-II [24], Beck Anxiety Inventory (BAI)-II [25], and Barratt Impulsiveness Scale-11 (BIS-11) [26]. The characteristics of their Internet gaming were measured by the first period of Internet gaming, weekday/weekend average Internet gaming usage hours for the past year, elapsed time after the last game, and the Korean version of Young’s Internet Addiction Test (Y-IAT) to assess the severity of IGD. The Y-IAT comprised 20 items with 5 Likert scales ranging from 1 (Not at all) to 5 (Always) with higher scores indicating a greater tendency toward addiction [27]. Y-IAT scores of 20-39 are regarded as an average user, 40-69 as a possible addicted user, and more than 70 as an addicted user [27]. In a previous study to explore the psychometric properties of the Y-IAT, six factors were identified; salience, excessive use, neglecting work, anticipation, lack of control, and neglecting social life [28]. All subjects were also examined using the Korean Wechsler Adult Intelligence Scale (K-WAIS) to measure their intelligence quotient (IQ) and cognitive ability.
GDNF concentration was measured by enzyme-linked immunosorbent assay (ELISA) according to the manufacturer’s instructions (Wuhan EIAab Science Co., Ltd., China). Further explanation on the measurement of plasma GDNF are provided in the Supplementary Materials (in the onlineonly Data Supplement).
This study was approved by the Institutional Review Board (IRB) of Seoul St. Mary’s Hospital (IRB number: KC15EISI0103). All subjects were informed about the study and all provided informed consent.

Statistical analyses

Differences in sociodemographic, clinical variables, and plasma GDNF levels between the IGD and control groups were tested using the independent t-test, Mann-Whitney U test, or Fisher’s exact test. The correlation between GDNF levels and clinical characteristics in all participants was examined using Spearman’s rho and partial correlation that controlled for age, AUDIT, FTND, BDI-II, BAI-II and BIS-11 scores, and total IQ. All statistical analyses were conducted using SPSS, version 24.0 (IBM Corp., Armonk, NY, USA).


The sociodemographic, clinical characteristics, and GDNF levels of the IGD patients and control subjects are listed in Table 1. In the IGD group, the average playing duration per weekday or weekend day was 2.5±2.0 hours and 4.0±1.9 hours, respectively. The Y-IAT score of IGD patients was 52.1±10.0, which is regarded as possibly addicted. There was no difference in mean age, marital and employment status, smoking and alcohol drinking status, beginning of Internet gaming, weekday and weekend average usage hours of Internet gaming, elapsed time after the last game, and AUDIT, FTND, BDI-II, BAI-II, and K-WAIS scores between the two groups. However, the mean Y-IAT and BIS-11 scores were significantly higher in the IGD group (75.1±26.1 at BIS-11) than in the normal control group (38.8±5.1 and 54.9±17.0, respectively). With regard to the six factors of Y-IAT, the scores were higher in the IGD group compared to normal controls except for the salience factor. The mean plasma GDNF levels were found to be significantly low in the patients with IGD (103.2±62.0 pg/mL) when compared with those of the healthy controls (245.2±101.6 pg/mL, p<0.001) (Table 1).
GDNF plasma levels were negatively correlated with BIS-11 scores (Spearman’s rho=-0.526, p=0.001) but not significantly correlated with age (p=0.536), AUDIT (p=0.084), FTND (p=0.497), BDI-II (p=0.164) and BAI-II (p=0.138) scores, and total IQ (p=0.884). Regarding gaming characteristics and IGD severity, GDNF levels were negatively correlated with Y-IAT scores (Spearman’s rho=-0.645, p=<0.001) and positively correlated with elapsed time after the last game (Spearman’s rho=0.420, p=0.009) but not significantly correlated with weekday (p=0.126) and weekend average Internet gaming usage hours (p=0.074). After controlling age, AUDIT, FTND, BDI-II, BAI-II and BIS-11 scores, and total IQ, a negative correlation remained between plasma GDNF levels and Y-IAT scores (r=-0.370, p=0.048) and a negatively correlated trend was observed between GDNF levels and Y-IAT salience sub-factor scores (r=-0.339, p=0.055) (Figure 1).


In this study, we found significantly lower plasma GDNF levels among patients with IGD than in healthy controls. This finding is consistent with a previous study in which GDNF levels were lower in alcohol-dependent patients [29]. In addition, we found a negative correlation between GDNF levels and IGD severity. Similar to the present results, a previous study with heavy alcohol drinkers (years of drinking: 8.85±7.38, daily alcohol consumption: 193.27±58.59 grams) reported that GDNF levels were negatively associated with tolerance [29].
We also found that salience showed a negative correlated trend with GDNF levels. Salience, specifically incentive salience, is a cognitive process that produces a bias of attentional processing toward reward-associated stimuli [30-32] and regulated primarily by dopamine neurotransmission in the mesocorticolimbic pathway [32,33]. GDNF is associated with the mesolimbic dopaminergic system; the main area of action of GDNF is the midbrain [11,34,35] and the main site of GDNF in the midbrain is the striatum [36-38]. Moreover, signaling proteins for GDNF, GFRα1 (GDNF family receptor α1) and Ret (Rearranged during transfection receptor), are highly expressed in midbrain dopamine neurons [39,40]. Additionally, motivation to self-administer and amphetamine-seeking behavior related to incentive salience is enhanced and sensitivity to the rewarding activity is increased in GDNF heterozygote knockout mice [3,7].
The mechanisms of action of GDNF associated with addiction remain unknown at present. However, several studies suggest that increased GDNF levels are associated with a reduction in the activity of tyrosine hydroxylase, the rate-limiting enzyme for dopamine synthesis, in the midbrain [3,41,42]. GDNF VTA injections antagonized cocaine or morphine-induced induction of tyrosine hydroxylase, which its activation enhances dopamine release in terminal areas [3]. These changes could result in a synaptic alteration, changing the responsiveness of the mesolimbic dopaminergic system and subsequently blunting the incentive and/or rewarding property, and the neuroadaptations associated with addiction.
The present study has the following limitations; first, our sample size was modest, and we investigated plasma levels of GDNF in only male patients. Previous animal studies have shown gender differences in the regulation of neurotrophic factors [43,44]. Second, our sample did not include IGD patient with severe levels of severity such as patients who require hospitalization. Third, plasma GDNF levels were measured in peripheral blood rather than in the central nervous system although a prior study reported that reduced GDNF plasma levels may imply a decreased ability to repair neuronal injury [45].
Despite these limitations, it is worth noting that this research is the first clinical study to investigate alterations in GDNF levels in IGD. The present study showed that GDNF levels are significantly lower in IGD patients compared to controls and GDNF levels have a negative correlation with IGD severity. The findings of this study support the assumed role of GDNF in the regulation of addiction including IGD as observed in preclinical studies. Our findings show the possibility of the GDNF pathway as a promising target for understanding and treatment of addictions including IGD.

Supplementary Materials

The online-only Data Supplement is available with this article at


This research was supported by the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (NRF-2014M3C7A1062893).

The authors have no potential conflicts of interest to disclose.

Author Contributions

Conceptualization: Jo-Eun Jeong, Hyun Cho, Jung-Seok Choi, Sam-Wook Choi, Dai-Jin Kim. Data curation: Jo-Eun Jeong, Hyun Cho. Formal analysis: Jo-Eun Jeong, Funding acquisition: Dai-Jin Kim. Investigation: Jo-Eun Jeong, Soo-Hyun Paik, Mi Ran Choi, Hyun Cho, Jung-Seok Choi, Sam-Wook Choi, Dai-Jin Kim. Methodology: Jo-Eun Jeong, Hyun Cho, Jung-Seok Choi, Sam-Wook Choi, Dai-Jin Kim. Project administration: Dai-Jin Kim. Resources: Jo-Eun Jeong, Hyun Cho. Software: Jo-Eun Jeong, Soo-Hyun Paik, Mi Ran Choi, Hyun Cho. Supervision: Jung-Seok Choi, Sam-Wook Choi, Dai-Jin Kim. Validation: Jung-Seok Choi, Sam-Wook Choi, Dai-Jin Kim. Visualization: Jo-Eun Jeong. Writing—original draft: Jo-Eun Jeong. Writing—review & editing: Jo-Eun Jeong.

Figure 1.
Partial correlation between plasma GDNF levels and Y-IAT total and salience scores. *p<0.05. GDNF: glial cell line-derived neurotrophic factor, Y-IAT: Young’s Internet addiction test.
Table 1.
Sociodemographics, clinical characteristics, and GDNF levels of subjects
Variables IGD (N=19, male) Controls (N=19, male) p-value
Age, mean years (SD) 31.2 (8.0) 31.3 (4.2) 0.817
Marital status, N (%) 0.495
 Unmarried 14 (73.7) 11 (57.9)
 Married 5 (26.3) 8 (42.1)
Employment status, N (%) 0.313
 Yes 10 (52.6) 14 (73.7)
 No 9 (47.4) 5 (26.3)
Smoking, N (%) 1.000
 Non-smoker 6 (31.6) 6 (31.6)
 Current smoker 13 (68.4) 13 (68.4)
Alcohol, N (%) 1.000
 Non-drinker 7 (36.8) 6 (31.6)
 Drinker 12 (63.2) 13 (68.4)
AUDIT, mean (SD) 9.4 (11.5) 10.6 (9.0) 0.452
FTND, mean (SD) 2.4 (4.7) 2.8 (4.8) 0.977
First period of Internet gaming, N (%) 0.831
 Lower grade of elementary school 1 (5.3) 0 (0.0)
 Upper grade of elementary school 2 (10.5) 3 (15.8)
 Middle school 6 (31.6) 5 (26.3)
 High school 3 (15.8) 6 (31.6)
 20 s 5 (26.3) 4 (21.0)
 30 s 2 (10.5) 1 (5.3)
Weekday average Internet game usage hours, mean hours/day (SD) 2.5 (2.0) 1.9 (1.1) 0.181
Weekend average Internet game usage hours, mean hours/days (SD) 4.0 (1.9) 3.3 (1.7) 0.271
Elapsed time after the last game, mean hours (SD) 16.7 (9.2) 19.0 (12.3) 0.311
Y-IAT, mean (SD) 52.1 (10.0) 38.8 (5.1) <0.001*
 Salience 11.0 (2.0) 9.8 (2.6) 0.172
 Excessive use 15.1 (3.3) 11.1 (1.3) <0.001*
 Neglecting work 7.9 (2.8) 5.0 (1.6) <0.001*
 Anticipation 4.6 (1.6) 3.3 (1.5) 0.023*
 Lack of control 8.5 (2.5) 6.3 (1.5) 0.003*
 Neglecting social life 5.1 (1.3) 3.4 (1.1) <0.001*
BDI-II, mean (SD) 21.1 (5.5) 17.8 (7.9) 0.142
BAI-II, mean (SD) 20.7 (5.0) 17.1 (11.4) 0.109
BIS-11, mean (SD) 75.1 (26.1) 54.9 (17.0) 0.019*
GDNF, pg/mL (SD) 103.2 (62.0) 245.2 (101.6) <0.001*
K-WAIS, full scale IQ, mean (SD) 104.9 (17.0) 108.4 (11.6) 0.460

* p<0.05 in independent t-test, Mann-Whitney U test, or Fisher’s exact test.

IGD: Internet gaming disorder patients, SD: standard deviation, N: numbers, AUDIT: alcohol use disorders identification test, FTND: Fagerström test for nicotine dependence, Y-IAT: Young’s Internet addiction test, BDI: Beck depression inventory, BAI: Beck anxiety inventory, BIS: Barratt Impulsiveness Scale, GDNF: glial cell line-derived neurotrophic factor, K-WAIS: Korean Wechsler Adult Intelligence Scale, IQ: Intelligence quotient


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