Klotho, BDNF, NGF, GDNF Levels and Related Factors in Withdrawal Period in Chronic Cannabinoid Users

Abstract

Klotho and neurotropic factors have recently been shown to be related to some psychiatric disorders and neurocognitive disorders, but there is no study on this issue within substance users. In this study, brain-derived neurotrophic factor (BDNF), nerve growth factor (NGF), glial derived neurotrophic factor (GDNF) and klotho serum levels of a patient group consisting of 27 chronic cannabis users according to the DSM-V and 27 healthy volunteers were compared, and their relationships with other the clinical features of other patients were evaluated. Clinical scales, the Buss–Perry Aggression Scale, and the Substance Craving Scale were repeated on the first day of hospitalisation and on the seventh day of withdrawal. BDNF, GDNF, NGF and klotho levels were analysed using the ELISA method. There was no differences between the cannabinoid use disorder group and the control group regarding their klotho and other neurotrophic levels, but initiation age of cannabis use was negatively correlated with these levels. In addition, there was a relationship between verbal aggression scores and BDNF and NGF levels. There was a positive correlation between klotho and neurotrophic factors in all groups (patient group Day 1, patient group Day 7, control group) (p < 0.01). When comparing the difference between the correlations using the cocor (a comprehensive solution for the statistical comparison of correlations), the klotho–GDNF and klotho–NGF correlations for the first day of the patient group and the control group were different. In this study, rather than a difference in klotho levels and neurotropic factors, a significant relationship between these markers and each other and clinical parameters was demonstrated; further studies are needed to understand the exact mechanism.

Introduction

Substance use disorders cause serious psychological, medical, social and economic problems [1]. It has been reported that approximately 5.5% of the world’s adult population—in other words, 271 million people between the ages of 15 and 64—used at least one drug in 2017, and in the same year, the number of people with substance use disorders increased to 35 million. Cannabinoids have been reported to rank first in terms of use for those between the ages of 15 and 64 (about 188 million people), with a rate of 3.8% [2]. Approximately 13.1 million people worldwide are cannabinoid addicts [3].

Synthetic cannabinoids (SCs) are similar natural cannabis in that they have the active substance of the cannabis plant, ∆⁹-tetrahydrocannabinol (THC). However, because of their high potency, SCs have been associated with serious health problems that may result in morbidity and mortality [4].

SC use occurs in less than 1% of the general population, but it is becoming more and more widespread, especially among young people. According to an online survey conducted with 14,966 people worldwide in 2011, 17% of the people used SCs, the average age was 26, and users were reported to be two-thirds men [5]. In Turkey, 19% of those seeking addiction treatment reported being SC users [6].

It is known that the use of both natural cannaboids and SCs has negative effects on learning, memory and executive functions [7, 8]. However, the neurodegenerative processes that may be associated with it have not yet been investigated. Cannabis abstinence symptoms have been identified in the DSM-V, and synthetic derivatives were added in the cannabis definition [9].

The most common symptoms of cannabis withdrawal syndrome include anger, aggressive behaviour, irritability, anxiety, appetite or weight loss, restlessness, sleep problems and strange vivid dreams; less common symptoms include moodiness, nausea, tremors and sweating. Similar to other substance withdrawal syndromes, most symptoms begin within 24 h of withdrawal and peak on the second or third day, lasting for about three weeks in total [10]. The relationship of cannabis and its derivatives with neuroplasticity has been previously shown [11]. Regular cannabis use is related to a desensitisation and downregulation of human brain cannabinoid 1 (CB1) receptors. This starts to reverse within the first two days of abstinence, and the receptors return to normal functioning within four weeks of abstinence, which could constitute a neurobiological time frame for the duration of withdrawal syndrome when not taking into account the cellular and synaptic long-term neuroplasticity elicited by long-term cannabis use before cessation, for example, being possibly responsible for cannabis craving [10].

To date, our information is that growth factors such as brain-derived neurotrophic factor (BDNF), nerve growth factor (NGF) and glial-derived neurotrophic factor (GDNF) and klotho play a role in neuroplasticity and neurodegeneration [12–17]. BDNF is a neurotrophic factor that has an important function in memory and learning by increasing the synaptic connectivity and neuroplasticity commonly found in the brain [18]. GDNF and BDNF are the main markers of synaptic plasticity and are associated with the pathogenesis and treatment of psychiatric disorders. BDNF levels have especially been shown to decrease in diseases such as depression, schizophrenia, attention and memory functions. There are conflicting results regarding NGF and GDNF in psychiatric disorders; one study reported a high NGF level in the withdrawal period of alcohol use disorder [19, 20]. Klotho is a relatively new molecule, which has been shown to be associated with attention memory functions, much like BDNF, NGF and GDNF, and its position in psychiatric diseases has recently become a matter of curiosity. Klotho was first discovered in 1997 by Kuro-o et al. [21]. Systemic age-related abnormalities such as walking disorder, emphysema, osteoporosis, arteriosclerosis, hypomyelination, hippocampal neurodegeneration and cognitive deficits have been shown in klotho-deficient (Klothoa-/-) mice [22–24]. Although there are a limited number of studies on the role of klotho in psychiatric diseases in patients with depression, bipolar mania and schizophrenia, no study has investigated the serum levels of cannabinoids in cannabinoid users [25].

In studies on cultures from rats, it has been shown that BDNF and brain cannabinoid signalling (CB1 and CB2) are interdependent or potentially interact in the control of neurogenesis [26].

In addition, in a double-blind placebo-controlled study with healthy controls (n = 14) and mild cannabis users (n = 9), BDNF levels were increased in the healthy controls after intravenous THC administration, while there was no similar increase in cannabis users [27]. In a recent study comparing chronic cannabis users and nonusers, there was no significant difference in NGF serum levels, while the BDNF levels were found to be significantly lower in cannabis users [28].

Although there is limited research on NGF and BDNF levels in chronic cannabinoid users, to the best of our knowledge, there is no study on klotho and GDNF. In the present study, BDNF, NGF, klotho and GDNF levels in patients with synthetic cannabinoid use disorder and withdrawal period were evaluated.

Methods

In the current study, the BDNF, NGF, GDNF and klotho serum levels of the patient group consisting of 27 chronic cannabis users and 27 healthy volunteers were compared, and their relationship with other clinical features and the sociodemographic characteristics of the patients were evaluated. Ethical approval was obtained from Clinical Trials Ethics Committee of Sakarya University Faculty of Medicine with the number 71522477/050.01.04/21. Informed consent was obtained from all cases and controls.

Sample Selection

The study included male individuals aged between 18 and 65 years who received inpatient treatment at Sakarya Training and Research Hospital Treatment and Education Centre of Alcohol and Substance Addiction (AMATEM) and who were diagnosed with cannabis use disorder according to the DSM-V [9]. Here, no more than one week elapsed since the last cannabis use, there was no use disorder of any other substance except cannabis and tobacco, there was no additional psychiatric diagnosis, there was no comorbid neurological or internal diseases, the individuals volunteered to participate in the study, and the individuals had the mental capacity to be able to participate. A total of 98 patients with substance use disorders were treated for six months, and 27 patients were included (see Fig. 1).

Fig. 1.

Flowchart of sample selection

The control group consisted of males of a similar age range who showed the absence of cannabis and any other substance use (licit or illicit with current or past use). In addition, in the control group, those with additional psychiatric diseases and any chronic diseases and those with limited mental capacity according to clinical evaluation were not included.

Application

The diagnosis of the patients was made by DSM-V-oriented clinical interviews [9]. Clinical scales were repeated on the first day of hospitalisation and on then again the seventh day. During this period, the patients continued their usual treatment. Here, 3 ml venous serum was collected from the patient group on Day 1 and Day 7 before filling out the scale; the BDNF; GDNF, NGF and klotho levels were analysed using the ELISA method.

Data Collection Tools

Sociodemographic data form This form includes descriptive data such as age, marital status, educational status, occupation and clinical features such as age of onset of cannabinoid use, previous treatment history, the longest period of use, withdrawal symptoms and so forth.

Addiction profile index (API) This scale was applied on Day 1 of their admission to the group. By evaluating different dimensions and the severity of the addiction, it assisted in the planning of treatment. The API is a self-reported scale consisting of 37 questions and five subscales. The subscales measure the substance use characteristics, addiction diagnostic criteria, the effect of substance use on the person’s life, the craving for substance use and the motivation to stop using the substance. After calculating the total score, low dependency severity was evaluated as below 12 points, moderate dependency severity between 12 and 14 points and high addiction severity above 14 points. A Turkish validity and reliability study for this scale was performed by Kültegin Ögel et al. in 2012 [29].

Drug craving scale This scale was applied on Day 1 and Day 7 of their admission to the dependent group. The scale, which is the adapted version of the Penn Alcohol Craving Scale for addicts who use nonalcohol substances, evaluates the substance use desire (frequency, duration, intensity, resistance and general craving) over the previous week. It is a self-reported scale consisting of five items, and each item is evaluated as between 0 and 6 points. The maximum total craving score is 30 [30].

Buss–Perry aggression questionnaire The Buss–Perry Aggression Scale (BPAS) is a five-item Likert-type scale consisting of 29 items; it is one of the most commonly used aggression scales [31]. It aims to measure four different dimensions of aggression: physical aggression, verbal aggression, hostility and anger. A Turkish validity and reliability study of the scale was performed by H. Andaç Demirtaş Madran [32].

Laboratory Methods

Collection of Blood Samples

Patients who were inpatients at the AMATEM clinic and who agreed to participate in the study had a blood sample taken between 8:00 and 9:00 a.m. after 12 h of fasting in the first three days after hospitalisation. Seven days later, another 12-h fast was followed by another blood sample being drawn at 08:00 a.m. Blood samples were centrifuged for 7 min at 5000 rpm within 2 h, and their serum was separated and placed in eppendorphs and stored at − 80 °C until analysis.

Analysis of Samples

When all the patient samples were completed, serums were removed from − 80 °C where they were stored and prepared for biochemical analysis at room temperature (22–24 °C). Commercial kits will be used for the study, and all reagents were kept at room temperature in accordance with the protocol before use. BDNF GDNF, NGF and klotho levels were analysed spectrophotometrically (Biotek ELX-800 Washer, USA; Biotek ELX50 Reader Instruments, Vinooski, VT, USA).

Statistical Analysis and Interpretation of the Data

The data were entered into the SPSS 22.00 programme on a computer running Windows 10.0. First, descriptive analyses and frequency analyses were made, and then, the groups were compared. When independent groups were evaluated, according to the Shapiro–Wilk test, a student-t test was used to compare the average of the variables that fit the normal distribution, and the Mann–Whitney U test was used for the variables that did not fit the normal distribution. For the dependent groups, non-normally distributed groups were compared with a Wilcoxon signed rank test, and normally distributed groups were compared with a paired samples t test. Marker levels and psychiatry scale scores were compared between the pretest and post-test groups and between the patient and control groups. In addition, a Pearson correlation analysis was performed to determine the relationship of the hormones among themselves and between them and the scale scores. Categorical variables such as gender and diagnosis were evaluated by a chi-square analysis. The difference between correlations was evaluated using cocor (a comprehensive solution for the statistical comparison of correlations) [33]. Significance level was accepted as p < 0.05.

Results

The patient group and healthy control group consisted of all men, and when the sociodemographic data were examined, there was no significant difference between the groups in terms of age, marital status, family structure and urban or rural location. The sociodemographic characteristics of the patients and controls are shown in Table 1.

Table 1.

Sociodemografical data of the groups

		Cannabis users n = 27		Control group n = 27		p
		Mean ± SD		Mean ± SD
Age		29.62 ± 6.12		30.70 ± 7.05		p = 0.553
Body mass index		22.88 ± 3.08		26.91 ± 3.51		T = − 4.47, p = 0.000*
		n	%	n	%
Education	Primary school	5	19	4	15	χ2 = 8.49 p = 0.037**
	Secondary school	13	48	4	15
	High school	7	26	14	52
	University	2	7	5	18
Occupational status	Occupied	13	48	27	100	χ2 = 18.90 p = 0.000*
	Unoccupied	14	52	0	0
Marital status	Married	17	63	15	55	p = 0.403
	Single/divorced	10	37	12	45
Location of living	Rural	4	15	9	33	p = 0.111
	Urban	23	85	18	67
Family structure	With family	22	82	24	89	p = 0.352
	Alone	5	18	3	11
Monthly income per person	0–1600 tl	13	48	0	0	χ2 = 20.76 p = 0.000*
	1601–5000 tl	12	45	27	100
	5000 tl and over	2	7	0	0
Tabaco use	Yes	27	100	18	67	χ2 = 10.80 p = 0.001***
	No	0	0	9	33
Suicide attempt	Yes	16	59	0	0	χ2 = 13.81 p = 0.000*
	No	11	41	27	100

^*p < 0.001, **p < 0.05, ***p < 0.005

When the clinical features of the substance use disorder group were evaluated, it was determined that 11.0% (n = 3) had a mild level of addiction severity, 29.6% (n = 8) had a moderate level, and 59.3% (n = 16) belonged to the severe addiction group. Some clinical features of the dependent group are presented in Table 2. The addiction profile indexes and item craving scores of Days 1 and 7 and the total scores of the Buss–Perry Aggression scale are presented in Table 3. It was determined that the Buss–Perry anger, hostility and total scores decreased on Day 7 of hospitalisation compared with the first day.

Table 2.

Clinical properties of the cannabis users

	Mean/median	SD	Min–max
Onset age of the substance	19.07	5.98	11–32
Duration of Substance use (year)	9.61	4.76	1.5–20
Number of previous hospitalisations	0.81	1.27	0–5
Addiction Profil index scores	14.46	1.90	10.23–17.65

Table 3.

Change in substance craving and the Buss–Perry scale

	1st day			7th day			Significance
	Mean	SD	Min–max	Mean	SD	Min–max
Drug craving scale	20.96	7.34	0–30	10.48	8.65	0–28	Z =  − 4.32, p = 0.000*
Buss–Perry aggression scale
Physical aggression	15.18	6.55	4–26	13.66	8.56	0–32	t**:1.418, p = 0.168
Verbal aggression	10.55	3.79	3–17	10.22	4.43	2–26	t:0.440 p = 0.663
Anger	17.14	5.11	6–25	14.22	6.33	2–26	t:3.33, p = 0.003***
Hostility	18.07	4.71	10–27	15.59	6.74	3–29	t:2.22, p = 0.035****
Total	60.96	16.03	25–87	54.07	22.99	15–107	t:2.53, p = 0.018****

^*Wilcoxon signed ranks test, p < 0.001, **Paired sample t test, ***p < 0.005, ****p < 0.05

Comparison of BDNF, GDNF, NGF and Klotho Levels of the Groups

The BDNF, GDNF, NGF and klotho values of the patient group (Days 1 and 7) and the control group were not found to be normally distributed (Shapiro–Wilkins p > 0.05). The comparisons of the cannabis users on Days 1 and 7 were made with the Wilcoxon ranking signed test, and the comparisons of the cannabis users with the control group were made with the Mann–Whitney U test. Although the values of the control group were higher than the others, the difference between the groups was not statistically significant (Table 4).

Table 4.

Comparison of BDNF, GDNF, NGF and klotho levels of the groups

	Cannabis users-day1	Cannabis users-day 7	Control	p
BDNF	4.28 ± 5.23	4.78 ± 5.59	4.83 ± 4.47	p > 0.05
GDNF	7.33 ± 7.75	7.62 ± 7.69	8.08 ± 6.91	p > 0.05
NGF	435.26 ± 482.77	471.13 ± 492.58	646.64 ± 722	p > 0.05
Klotho	6.78 ± 8.56	8.37 ± 9.49	8.59 ± 8.72	p > 0.05

Mann–Whitney U test was used between Cannabis users-day 1 and Control, and the Wilcoxon Signed ranks test was used between Cannabis users-day 1 and 2

Sociodemographic Characteristics of the Patient and Control Groups, and the Relationship Between Klotho and Neuroprotropic Factors

In the entire sample, the age of the patient showed a negative correlation with klotho (r = − 0.358 p = 0.008), NGF(r = − 0.373 p = 0.006), BDNF(r = − 0.400 p = 0.003) and GDNF(r = − 0.428 p = 0.001) levels.

When the patient and control groups were examined separately, the patient group showed negative correlations with age (r_s = −  0.652 for NGF, r_s = − 0.658 for BDNF, r_s = − 0.580 for klotho, r_s = − 0.656 for GDNF, for all p = 0.001), while in the control group, the reverse correlation was found, but the values were not statistically significant.

When marital status is evaluated. In the entire sample, the klotho, BDNF, GDNF and NGF values were higher in single individuals, but single individuals were younger; this remained significant when controlled by age in the covariance analysis (F: 8.634, aR2 = 0.304). When the groups were evaluated separately as a patient group and control group, there was no significant relationship between marital status and klotho and neurotrophic factors in the patient group (p > 0.05); in the control group, the klotho, BDNF, GDNF and NGF values were higher in single individuals, but single individuals were younger in this group, too, and this was not significant when controlled by an age covariance analysis (F: 6.790, aR2 = 0.226).

No significant relationship was found with other sociodemographic variables such as education and employment status.

Evaluation of the Relationship Between the Clinical Features of the Patients and the Levels of Klotho and Neurotropic Factors in Cannabis Users

On Day 1, a negative correlation was detected between the age of onset of cannabinoid use and BDNF (r: − 0.597, p = 0.001), GDNF (r: − 0.528, p = 0.005), NGF (r: − 0.558, p = 0.002) and klotho (r: − 0.665, p = 0.000). Day 7 BDNF (r: − 0.550, p = 0.003), GDNF (r: − 0.436, p = 0.023), NGF (r: − 0.481, p = 0.011) and klotho (r: − 0.624, p = 0.001) were found to have a negative correlation with the age of onset of cannabinoid use.

On Day 1, there was no significant correlation between the total duration of substance use and neurotropic factors (r:  − 0.037 for BDNF, r: − 0.193 for GDNF, r: − 0.088 for NGF and r: 0.149 for klotho, p > 0.05 for all). No significant correlation was found with the age of onset of cannabinoid use for the values on Day 7 (r: − 0.158 for BDNF, r: − 0.108 for GDNF, r: − 0.121 for NGF and r: − 0.061 for klotho, p > 0.05 for all).

No significant relationship was found when it came to hospitalisation for the first time, number of hospitalisations and substance abuse scale scores (p > 0.05).

No significant correlation was found in the correlation analysis between the severity of addiction and neurotropic factors and klotho (p > 0.05).

The relationship between the Buss–Perry aggression scores and neurotropic factors and klotho; A significant correlation was found between the Day 1 Buss–Perry verbal aggression scores and Day 1 BDNF values (r = 0.486, p = 0.010) and NGF values (r = 0.436, p = 0.023), but no significant correlation was found between the other variables.

Correlation of Klotho and Neurotropic Factors Among Themselves in the Patient and Control Groups

There was a positive correlation between klotho and neurotrophic factors in all groups (patient group Day 1, patient group Day 7 and control group) (r = 0.688–969, p < 0.001) (see Table 5). When comparing the difference between the correlations with the cocor, klotho–GDNF and klotho–NGF correlations for Day 1 of the patient group were different from the correlations of the control group (p = 0.01 z = − 2.42, p = 0.000 z = − 3.87, respectively). Although other correlations were also different, the difference between the correlations was not significant.

Table 5.

Comparison of hormone levels correlation coefficients in patients and controls

	Patient group 1st day	Patient 7th. day group	Control group
Klotho–BDNF	r = 0.767, p = 0.000*	r = 0.863, p = 0.000	r = 0.914, p = 0.000*
Klotho–GDNF	r = 0.688, p = 0.000*	r = 0.882, p = 0.000	r = 0.913, p = 0.000*
Klotho–NGF	r = 0.743, p = 0.000*	r = 0.834, p = 0.000	r = 0.969, p = 0.000*
BDNF–GDNF	r = 0.865, p = 0.000*	r = 0.862, p = 0.000	r = 0.924, p = 0.000*
BDNF–NGF	r = 0.907, p = 0.000*	r = 0.921, p = 0.000	r = 0.918, p = 0.000*
GDNF–NGF	r = 0.895, p = 0.000*	r = 0.843, p = 0.000	r = 0.885, p = 0.000*

Spearman correlation, *p < 0.001

Discussion

In the current study, the BDNF, NGF, GDNF and klotho serum levels of individuals diagnosed with cannabis use disorder and an age- and sex-matched volunteer control group were compared; the serum levels of the addicts on Day 1 of hospitalisation and Day 7 substance abstinence were compared with each other and with the control group. Additionally, their relationship with other clinical features and sociodemographic characteristics were evaluated.

There are several findings of this study. BDNF, NGF, GDNF and klotho serum levels were significantly negatively correlated with both current age (not found significant correlation in the control group) and age of first use of cannabis in individuals with cannabis use disorder. There was a relationship between verbal aggression and BDNF and NGF serum levels. There was a positive relation between klotho and neurotrophic factors in all matches, but only the klotho–GDNF and klotho–NGF correlations for the patient group on Day 1 and the control group were different.

In the present study, a sample consisting only of men was created, taking into account the possible interaction of the biochemical markers measured with hormones and difficulty of a comparison between genders in a small sample. Although the patient and control groups were similar in terms of age, marital status, family structure and residence parameters, the education, occupational status and monthly income of the patient group were significantly lower than the control group. Here, even though attention is paid to factors such as similar age and same gender when creating the groups, other characteristics were not matched. For this reason, the results, such as that substance users fall behind regarding education, working life and income compared with healthy volunteers, could be related to addiction. This is compatible with data from similar studies [1, 34].

The Buss–Perry verbal aggression scores were significantly correlated with BDNF and NGF, but the same relationship does not apply to physical aggression and hostility and the overall scores. The BDNF system in the brains of aggressive and nonaggressive animals in rats has previously been shown to be associated with aggression, suggesting that the BDNF system plays an important role in the development of a highly aggressive phenotype [35, 36]. Similarly, NGF has been shown to be associated with aggressive behaviour in mice, but the mechanism behind this relationship is not fully known, and this has not been investigated in humans [37]. It is also known that impulsivity and aggressive behaviour create a predisposition to addiction [38]. In the current study, a positive correlation was found between verbal aggression and NGF and BDNF levels on Day 1 of hospitalisation in the dependent group, but the significance disappeared at Day 7. Likewise, a decrease in the aggression scores of the patients as measured after one week was observed, and this correlation can be assumed to be correlated with the beginning of the withdrawal period. The fact that other aggression scores did not show any correlation may suggest that the BDNF and NGF levels may be associated with higher levels of evolutionary aggression, that is, verbal aggression, for humans [39]. However, to make such an interpretation, larger studies and replication of the data are needed. Nevertheless, the current study reveals that aggression in addicts may be related to NGF and BDNF levels.

A comparison of the BDNF, GDNF, NGF and klotho values of cannabis users on Day 1 and Day 7 and those values of the control group was made. Although the values of the control group were higher than the others, the difference between the groups was not statistically significant. Studies previously investigating the relationship between marijuana use and BDNF levels have yielded complex results. For example, IV THC administration increased BDNF in healthy controls but not in mild cannabis users [27]. In a recent study, it was found that BDNF levels increased over time (two-year period) compared with those who did not use them although they were similar at baseline in those who used marijuana; this increase was dependent on age and dose [40]. However, that study was conducted on adolescent groups, which was a younger demographic than in our study. In addition, in our study, the average substance use time was around 10 years, covering a much longer period than in the other study, and our group also consisted of synthetic cannabinoid users. This suggests that apart from age and dose, the duration of the cannabinoid use may cause an additional change in BDNF levels. In the first episode of psychosis patients, BDNF levels have been shown to decrease with the use of cannabis. [41] These findings suggest that cannabinoid use dysregulates the BDNF pathway.

Indeed, in the current study, a significant negative correlation was found between age and klotho levels when all participants (all sample) and only the patient group were included in analyses. However, the same significance was not found when only the control group was taken into consideration. Although there was no difference between the klotho serum levels and neurotrophic factor levels of the patient group and the control group, there was a correlation between klotho serum levels and age in the patient group, this was not the case in the control group, suggesting that cannabis use has a detrimental effect on klotho in the body. As a matter of fact, the relationship between klotho and neurotrophic factors regarding ageing has been defined for years [42, 43]. However, to the best of our knowledge, the relation between klotho and neurotrophic factors regarding age has not been investigated in cannabinoid users before.

When the relationship between the clinical features and klotho and neurotropic factor scores of the patients in the dependent group were evaluated, a negative correlation was found between the age of initiation of cannabis use and klotho levels and neurotropic factors. Hence, as the age of starting cannabinoid use decreased, the klotho levels and neurotrophic factors increased. In a previous study conducted by Miguez et al., the relationship between BDNF levels and marijuana was shown to be affected by the age of starting marijuana for those who started after the age of 15 [40]. However, in the current study, no relation was found between substance use time, number of hospitalisations, severity of addiction and klotho levels and neurotrophic factors. This relationship, which is determined by the age of the initiation of cannabinoid use alone, may suggest that the use of SCs during the developmental process as adolescence, has a time-specific effect on neurotrophy and klotho levels because the initiation age was generally at adolescence.

In addition, the klotho levels and neurotrophic factors in married individuals were found to be lower than in single individuals even when age was controlled. Here, it was previously shown that marriage affects the brain [44]. However, it is not known how this relates to the klotho levels and neurotropes obtained in our study.

In the current study, there was a positive correlation between klotho levels and neurotropic factors. This finding suggests that klotho levels have a correlation with neurotropic factors in both the patient and control groups. Previously, klotho’s relationship with other neurotrophic factors and vitamin D metabolism has been demonstrated in animal studies. In previous studies, it has been shown that klothoin in rats is associated with dysregulation and rapid ageing, emotional and behavioural changes and cognitive disorders in vitamin D metabolism [45]. Research has shown that calcitriolis can upregulate the expression of GDNF in the midbrain, a nucleus accumbency, which is the primary area for the dopaminergic mechanism of addiction [46]. Klotho, an enzyme and hormone, has been reported to participate in the regulation of cellular transport processes across the plasma membrane either indirectly through inhibiting calcitriol (1,25(OH)2D3) formation or through other mechanisms [46]. Accordingly, the klotho protein serves as a powerful regulator of cellular transport across the plasma membrane and may be related to GDNF in the neouroregenative pathway. NGF has been shown to be decreased in the salivary glands of klotho-deficient mice [47]. In the present study, when the difference between the correlations was evaluated using cocor, the correlations of the control group and the klotho–GDNF and klotho–NGF correlations for Day 1 were significantly higher in the patient group. Although there was a similar difference between other correlations, it was not statistically significant. The difference between klotho’s correlation with NGF and GDNF in the patient and control groups suggests that there is a change in the functioning of these molecules in the addiction process. In the current study, there were differences between the groups in terms of substance use and educational level and smoking. In the literature, in animal studies, it has been shown that vitamin D levels affect NGF and GDNF levels [48, 49]. In a study conducted in a similar population in our province, substance D users, here mostly composed of cannabis patients, were found to have higher vitamin D levels than healthy controls and schizophrenia patients [25]. In the present study, the change in the correlation of klotho with GDNF and NGF suggests that the effect of synthetic cannabinoid use on neurotrophic functions and its effect on the vitamin D pathway should be investigated. In addition, in other studies, NGF has also been shown to be associated with CB-1 and CB2 receptors in inflammatory pathways and with the relationship of endogenous cannabinoids (CB1 receptor agonists) with NGF in patients with prostate and breast cancer [50, 51]. However, it is not yet known how this process may affect the correlation with klotho. Data on the relationship that klotho has with BDNF, NGF and GDNF are limited, and there are no studies investigating the relationship of these molecules with each other in humans.

The current study design has limitations, such as a small sample size, limited follow-up time, a difference in tobacco use rate between the patient and control groups and consisting of only a male sample. Also, another limitation is that the measurements were made from serum, not from cerebrospinal fluid. The strength of the study is that it is the first study to evaluate klotho levels in dependent patients and evaluate the relationship between neurotropic factors and clinical features.

Conclusion

The current study has important implications. According to the results, there was no difference between the group with cannabinoid use disorder and control group regarding their klotho and other neurotrophic levels, but current age, initiation age of cannabis use and marital status were related with klotho and other neurotrophic levels. In addition, there was a relationship between the verbal aggression scores and BDNF and NGF levels; this seems to be the result of the complex and dynamic effect of cannabinoid use on klotho levels and neurotrophic factors. There may be many pathways and mechanisms in aggression regulation. In the current study, rather than the differences of klotho levels and neurotropic factors in cannabinoid addicts, the significant relationship between these markers and each other and clinical parameters was demonstrated. Further studies are needed to understand the effect of chronic cannabis use on these molecules’ cerebrospinal fluid levels and its relation with clinical and genetic features in large groups consisting of both genders.

Funding

None.

Data Availability

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available because of privacy or ethical restrictions.

Code Availability

All authors declare that all data and materials, as well as software applications or custom code, support their published claims and comply with field standards.

Compliance with Ethical Standards

Conflict of interest

All authors declare that they have no conflicts of interest.

Ethical Approval

Ethical approval was obtained from the local ethics committee (No. 71522473/050.01.04/21).

Informed Consent

Informed consent was obtained from all participants in the study.