Opposing Effects of Cannabis Use on Late Auditory Repetition Suppression in Schizophrenia Patients and Healthy Control Subjects

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Archival Report Opposing Effects of Cannabis Use on Late Auditory Repetition Suppression in Schizophrenia Patients and Healthy Control Subjects Johannes Rentzsch, Golo Kronenberg, Ada Stadtmann, Andres Neuhaus, Christiane Montag, Rainer Hellweg, and Maria Christiane Jockers-Scherübl

ABSTRACT BACKGROUND: Chronic cannabis use may cause neurocognitive deficits and increase the risk of psychosis. Nevertheless, the effects of cannabis use on neurocognitive functioning in schizophrenia have remained largely unspecified. METHODS: Here, we studied repetition suppression of auditory event-related responses in a paired-stimulus design in a mixed sample of schizophrenia patients (n 5 34) and healthy control subjects (n 5 45) with chronic heavy cannabis use and schizophrenia patients (n 5 33) and healthy control subjects (n 5 61) without cannabis use. RESULTS: Repeated measures analysis yielded an overall significant reduction of P50 amplitude between first and second stimulus (p , .02), which was not different between the groups, a reduction of N100 amplitude, which was different for schizophrenia patients compared with healthy control subjects independent of cannabis use (p , .02), and a significant interaction between diagnosis and chronic cannabis use on the reduction of the P200 amplitude (p , .001). While chronic cannabis use was related with increased P200 suppression ratios in control subjects (with chronic cannabis use: 0.55 6 0.04; without chronic cannabis use: 0.40 6 0.03; p , .02), the reverse effect was found in schizophrenia (with chronic cannabis use: 0.36 6 0.05; without chronic cannabis use: 0.54 6 0.05; p , .02). This result remained significant after inclusion of potential confounders. Total lifetime cannabis use showed a significant correlation with the P200 suppression ratio in otherwise healthy control subjects (r 5 .28, p , .007). By contrast, the duration of time since last cannabis use was significantly correlated with the P200 suppression ratio in schizophrenia patients (r 5 .42, p , .002). CONCLUSIONS: In aggregate, these diverging effects of chronic cannabis use on P200 repetition suppression may suggest underlying alterations in the endocannabinoid system in schizophrenia. Keywords: Addiction, Cannabis, Event-related potential, Repetition suppression, Schizophrenia, Sensory gating http://dx.doi.org/10.1016/j.bpsc.2016.10.004

The relationship between cannabis use and schizophrenia remains complex and often confusing. Cannabis is one of the most widely consumed illicit drugs worldwide (1). Not surprisingly, cannabis use is also prevalent in patients suffering from psychosis (2). On the one hand, cannabis use is associated with an elevated risk and earlier onset of schizophrenia. Moreover, psychosocial outcomes in schizophrenia patients with cannabis use seem to be generally poorer (3). On the other hand, several studies of cannabis users with schizophrenia found fewer negative symptoms (4,5). Similarly, at least during abstinence, schizophrenic cannabis users displayed better neuropsychological functioning relative to cannabis nonusers with schizophrenia (6,7), a finding that runs counter to the effects commonly described in healthy cannabis users [e.g., (8)]. Further paradoxical findings have come from epidemiological research demonstrating more

suicide attempts (9) and a higher level of neurological soft signs (10) in healthy cannabis users as compared with nonusers, whereas the reverse, again, seems to be the case in patients diagnosed with psychotic disorders (11–14). Interestingly, Koola et al. (15) also found a lower mortality risk in cannabis-using psychotic disorder patients as compared with cannabis nonusers despite subjects having similar symptoms and treatments. Unfortunately, there are as yet only a small number of studies that directly compared schizophrenia patients with and without cannabis use and simultaneously also investigated healthy cannabis users as control subjects. On the whole, these studies yielded either no interaction between cannabis use and schizophrenia [e.g., regarding cerebellar white matter volume (16,17), cannabinoid receptor type 1 (CB1R) density (18), mesocorticolimbic functional connectivity (19), face and

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affect recognition (20), sustained attention (21)] or some evidence of positive effects of cannabis in schizophrenia [e.g., regarding cerebral gray matter volume (22) and memory function (8)]. Neurocognitive processes are successfully conceptualized within the predictive coding framework, which posits constant comparisons between sensory input and top-down expectations, thus converging into the prediction error, which is reflected by higher neuronal responses to unexpected stimuli and reduced neuronal responses to repeated stimuli (23,24). The brain’s ability to suppress its response to repeated stimuli has been construed as a form of sensory gating or—according to the predictive coding hypothesis—repetition suppression (25) that protects higher brain centers from being flooded with irrelevant information (26,27). When presenting two identical stimuli the neuronal response evoked by the second stimulus is reduced compared with the first one. In the predictive coding view, the second stimulus increases the stability of the internal model of the environment, which conforms to a decrease of the prediction error. Accumulating evidence suggests that the capacity to gate out or suppress responses to irrelevant, repeated information is altered in patients with schizophrenia, the family members of patients with schizophrenia, and individuals with high risk of psychosis (28–31), reflecting abnormal prediction error generation. Interestingly, it appears that repetition suppression is also impaired in individuals with chronic cannabis use (32). In this study, we posed the question of whether cannabis use results in impairment of the brain's ability to suppress its response to stimuli lacking relevant information (repetition suppression) using an auditory paired click-stimuli design, thereby targeting a fundamental neurocognitive mechanism. Moreover, we hypothesized that the effects of cannabis use on repetition suppression might differ between schizophrenia patients and healthy control subjects. To address these questions, we chose a 2 3 2 study design that would allow us to dissect and understand the precise effects of schizophrenia and of cannabis use. Repetition suppression was assessed for auditory P50, N100, and P200 event-related

potentials (ERPs). These components cover different stages of information processing from preattentive to early and late attentive stages (24,33–35) and reflect the activity of different neural networks (36).

METHODS AND MATERIALS Participants Four groups of participants were included in the study: 1) 34 schizophrenia patients with a history of chronic heavy cannabis use (SZCA), 2) 33 schizophrenia patients without chronic drug use (SZ), 3) 45 otherwise healthy subjects with chronic heavy cannabis use (COCA), and 4) 61 healthy subjects without chronic drug use (CO). Chronic cannabis use was defined as consumption on at least 3 days/week for at least 1 year as indicated by self-reports. However, given that this was a relatively naturalistic study conducted in a busy urban center and focusing, in particular, on the effects of chronic heavy cannabis use, we did not require study participants in the SZ and CO groups to have never consumed cannabis. Further details are given in Table 1 as well as in the Supplemental Methods. The protocol had been approved by the local ethics committee and written informed consent was obtained from each participant according to the Declaration of Helsinki.

ERP Recordings and Analysis A detailed description of the procedures is given in the Supplemental Materials. Briefly, auditory stimuli (100 identical pairs of clicks, interclick interval 500 ms, and 118 distractor novelty tones) were presented in pseudorandomized order through earphones (interpair interval 2632 6 731 ms). Electroencephalography was recorded using an electrode cap with 29 electrodes. Offline ERP analysis was performed using Brain Vision Analyzer Version 2 (Brain Products GmbH, Gilching, Germany) and EEGlab Version v13.1.1 (37). After artifact correction procedures, data were transformed to current source density, filtered (P50: 10 Hz high pass; N100 and P200: 30 Hz low

Table 1. Study Population Gender, Male

SZ (n 5 33)

SZCA (n 5 34)

COCA (n 5 45)

CO (n 5 61)

Statistics

19 (75.6)

28 (82.4)

26 (57.8)

28 (45.9)

χ23 5 11.97, p , .01 F3,169 5 2.55, p , .06

Age, Years

34.2 6 10.2

28.9 6 7.4

31 6 8.6

30.1 6 7.7

MWT-B Score

29.5 6 4.4

29.9 6 3.2

30.2 6 2.9

31.1 6 3.1

F3,169 5 1.91, p . .1

10 (10.9)

26 (28.3)

44 (47.8)

χ23 5 20.61, p , .001

9 (11)

31 (37.8)

31 (37.8)

χ23 5 17.22, p , .001

Subjects With German Higher School Certificate

12 (13)

Subjects in Current Relationship

11 (13.4)

Edinburgh Laterality Index

74.7 6 45.9

76.2 6 38.4

78.2 6 30.5

77.6 6 40.4

F3,169 5 1.14, p . .9

Age at Onset of Schizophrenia, Years

27.5 6 7.3

22.6 6 4.99

—

—

t56 5 3.18, p , .003

2.5 6 1.8

3.1 6 2.6

—

—

t65 5 1.15, p . .2

PANSS-Positive

12.1 6 3.2

12.1 6 2.9

—

—

t65 5 0.44, p . .9

PANSS-Negative

19.9 6 5.8

16.7 6 3.9

—

—

t56 5 3.04, p , .004

6.2 6 6.2

—

—

t65 5 0.29, p . .7

494 6 364.7

—

—

t62 5 0.38, p . .7

Number of Hospitalizations

Duration of Illness Chlorpromazine Equivalent Dose

6.7 6 6.9 524.4 6 257.8

Values are mean 6 SD or n (%). CO, healthy control subjects; COCA, otherwise healthy control subjects with cannabis use; MWT-B, Multiple Choice Vocabulary Intelligence Test; PANSS, Positive and Negative Syndrome Scale; SZ, schizophrenia patients without cannabis use; SZCA, schizophrenia patients with cannabis use.

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pass), segmented, and baseline corrected. ERP mean amplitudes were measured at electrode Cz. Processing and analysis were performed in a blinded fashion.

Statistical Methods Statistical evaluation was performed using SPSS version 15 (IBM Corp., Armonk, NY). Demographic, substance-related, and clinical parameters were compared using one-way analysis of variance, t test, and χ2 test as indicated. To assess the effects of diagnosis and cannabis use on the amplitudes of P50, N100, and P200 ERPs, a multivariate repeated measures analysis of covariance (ANCOVA) was conducted. Stimulus (first click, second click) was treated as within-subjects factor; diagnosis (schizophrenia, otherwise healthy), chronic cannabis use (yes, no), and the interaction diagnosis 3 chronic cannabis use were included as betweensubjects factors. Gender and age were entered as covariates. Planned post hoc repeated measures ANCOVAs were done in the case of significant main or interaction effects. For those ERPs showing significant diagnosis 3 chronic cannabis use interactions, the suppression ratios (second click amplitude/ first click amplitude) were calculated and compared between the four groups using a two-way ANCOVA including gender and age as covariates. Post hoc comparisons of the ratios between the four groups were Holm–Bonferroni corrected. To test for a relation between suppression ratio and cannabis use parameters, a linear regression analysis was carried out for both schizophrenia patients and otherwise healthy individuals with any cannabis use. Statistical significance was defined as p # .05.

RESULTS Study Population A detailed summary of sociodemographic and clinical variables of the four study subgroups is provided in Table 1. Gender distribution was not homogenous across groups, with the highest percentage of male study subjects in the SZCA subgroup. Although premorbid verbal intelligence as estimated by the Multiple Choice Vocabulary Intelligence Test was similar in schizophrenia patients and control subjects, fewer schizophrenia patients had attained the higher German school certificate. Furthermore, schizophrenia patients were significantly less likely to be in a current relationship. The SZCA group showed a significantly earlier onset of schizophrenia as compared with the SZ group. Furthermore, negative symptoms on the Positive and Negative Syndrome Scale were significantly lower in the SZCA group. Finally, positive Positive and Negative Syndrome Scale scores, duration of illness, and the number of hospitalizations did not differ between the two schizophrenia groups (Table 1). Substance use-related parameters are summarized in Table 2. One participant in each of the groups without chronic cannabis use (i.e., SZ and CO) reported lifetime cannabis use of more than 50 times (i.e., SZ: 55 times; CO: 132 times). According to self-reports and urine drug testing, all study subjects except for one participant in each of the SZCA (3 days), COCA (10 days), and CO (14 days) group had refrained from cannabis use for at least 28 days. There were no significant differences between the SZCA and the COCA groups regarding total lifetime cannabis use (t77 5 0.88, p . .9), sum of cannabis use during time of chronic use

Table 2. Substance Use–Related Parameters SZ (n 5 33)

SZCA (n 5 34)

COCA (n 5 45)

CO (n 5 61)

Statistics

Last Cannabis Use, Monthsa

156 6 137

26 6 30

34 6 45

62 6 62

F3,120 5 15.69, p , .0001

[2–372]

[0.1–96]

[0.3–180]

[0.5–204]

Total Lifetime Cannabis Usea

3.4 6 11.5

10,997 6 13,190

10,779 6 8708

7.7 6 19.6

[0–55]

[468–51,100]

[624–32,595]

[0–132]

—

10,852 6 13,274

10,641 6 8658

—

t77 5 0.09, p . .9

[208–51,100]

[624–32,595]

6.6 6 4.9

8.8 6 6.4

—

t77 5 1.62, p . .1

[1–22]

[2–30]

18.8 6 6.6

16.6 6 3.2

15.7 6 2.3

18.2 6 3.2

F3,120 5 4.74, p , .004

[14–40]

[12–25]

[12–22]

[14–27]

—

17.7 6 3.8

18.2 6 4.1

—

[12–29]

[13–33]

Sum of Cannabis Use During Chronic Use

—

Years of Chronic Cannabis Use Age of First Cannabis Usea Age of Onset of Chronic Cannabis Use

F3,120 5 14.91, p , .0001

t77 5 0.52, p . .6

Any Cannabis Use Before Onset of SZa,b

12 (92)

32 (94)

—

—

—

Current Cigarette Smokers

18 (55)

29 (85)

24 (53)

21 (34)

χ23 5 22.71, p , .0001

1.9 6 2.8

2.9 6 3.8

3.0 6 2.4

2.7 6 2.7

F3,169 5 1.14, p . .3

[0–10]

[0–14]

[0–9]

[0–10]

0.6 6 2.7

104.9 6 324.8

61.9 6 241.9

0.4 6 1.8

[0–15]

[0–1750]

[0–1634]

[0–14]

Alcohol Consumption (Drinks/Week) Lifetime Use of Drugs Other Than Cannabisc

F3,169 5 2.89, p , .04

Values are mean 6 SD or n (%). Ranges are given in brackets. CO, healthy control subjects; COCA, otherwise healthy control subjects with cannabis use; SZ, schizophrenia patients without cannabis use; SZCA, schizophrenia patients with cannabis use. a Only values of the subjects with at least one lifetime cannabis use (SZ, n 5 13; CO, n 5 32). b A total of n 5 29 (85%) subjects of the SZCA group had onset of the chronic cannabis use before the onset of schizophrenia. c Number of participants with lifetime use of drugs other than cannabis: SZ, n 5 3; SZCA, n 5 27; COCA, n 5 37; CO, n 5 7.

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(t77 5 0.09, p . .9), duration of chronic use (t77 5 1.62, p . .1), time since last cannabis use (t77 5 0.91, p . .4), age of first cannabis use (t57 5 0.19, p 5 .17), and age of onset of chronic cannabis use (t77 5 0.52, p . .6; see Table 2). Current alcohol use did not differ across the four study groups. The highest rate of current smokers was in the SZCA group (85%), while the lowest rate was in the CO group (34%). Lifetime use of other drugs differed significantly between the four groups. However, there were no significant differences between the SZCA and the COCA groups (t77 5 0.67, p . .5). Three participants in the SZCA group and one in the COCA group reported lifetime use of other drugs of more than 150 times (i.e., SZCA: 305 times, 799 times, and 1750 times, respectively; COCA: 1634 times).

Event-Related Potentials Grand-average waveforms for the double-click stimuli are presented in Figure 1. Mean amplitudes of ERPs are summarized in Table 3. Latencies are reported in Supplemental Table S1. The multivariate repeated measures ANCOVA showed a significant effect of stimulus (F3,165 5 21.4, p , .0001), indicating differences between the first and second stimulus amplitudes. There was a statistical trend for a stimulus 3 diagnosis interaction (F3,165 5 2.27, p 5 .082), but no significant stimulus 3 chronic cannabis use interaction (F1,165 5 1.29, p . .2). However, there was a significant stimulus 3 diagnosis 3 chronic cannabis use interaction (F1,165 5 4.79, p , .004). Finally, there was a significant stimulus 3 age interaction (F3,165 5 4.90, p 5 .003), but no significant stimulus 3 gender interaction (F3,165 5 1.19, p . .3). To assess for which ERPs the interactions were significant, we subsequently conducted post hoc repeated measures ANCOVA separately for P50, N100, and P200 amplitudes. For the P50 amplitude, we found a significant effect of stimulus (F1,167 5 6.1, p , .02), but no further significant

effects were found (stimulus 3 diagnosis [F1,167 5 0.4, p . .5], stimulus 3 chronic cannabis use [F1,167 5 2.4, p . .1], stimulus 3 diagnosis 3 chronic cannabis use [F1,167 5 1.64, p . .2], stimulus 3 age [F1,167 5 0.01, p . .9], stimulus 3 gender [F1,167 5 3.26, p , .1]). For the N100 amplitude we found no significant effect of stimulus (F1,167 5 0.1, p . .7), but we did find a significant stimulus 3 diagnosis interaction (F1,167 5 6.9, p , .02). There were no significant stimulus 3 diagnosis 3 chronic cannabis use (F1,167 5 2.94, p , .09), stimulus 3 chronic cannabis use (F1,167 5 0.31, p . .5), stimulus 3 age (F1,167 5 2.06, p . .1), or stimulus 3 gender (F1,167 5 0.02, p . .8) interactions. For the P200 amplitude we found a significant effect of stimulus (F1,167 5 64.98, p , .0001). The interaction stimulus 3 diagnosis was not significant (F1,167 5 0.01, p . .9). There was a significant interaction for stimulus 3 diagnosis 3 chronic cannabis use (F1,167 5 12.20, p , .001). There was no significant interaction for stimulus 3 chronic cannabis use (F1,167 5 0.05, p . .8). There was a significant stimulus 3 age interaction (F1,167 5 11.87, p , .001), but no significant stimulus 3 gender interaction (F1,167 5 1.67, p . .6). To summarize, we found an overall P50 amplitude reduction, a deficit in N100 amplitude reduction in schizophrenia patients, and an interaction between diagnosis and chronic cannabis use on P200 amplitude reduction. Because the interaction between diagnosis and chronic cannabis use was significant for P200 amplitude reduction, we calculated the P200 suppression ratio and compared it between the groups. As suggested by a reviewer we also calculated P50 and N100 suppression scores, which are given in Supplemental Table S2. Using a two-way ANCOVA with age (F1,167 5 3.66, p 5 .057) and gender (F1,167 5 0.01, p 5 .9) as covariates we found a significant group effect (F3,167 5 5.21, p , .0029; P200 ratio, estimated marginal means 6 SE: SZ, 0.54 6 0.05; SZCA, 0.36 6 0.05; COCA, 0.55 6 0.04; CO, 0.40 6 0.03). Holm–Bonferroni corrected post hoc tests showed significantly lower P200 ratio for SZCA compared with COCA Figure 1. Grand-average waveforms at electrode Cz for the four study groups as evoked by paired-click stimuli. The first-click stimuli were presented at 0 ms and the second-click stimuli were presented at 500 ms. CO, healthy subjects without chronic cannabis use; COCA, otherwise healthy subjects with chronic heavy cannabis use; SZ, schizophrenia patients without chronic drug use; SZCA, schizophrenia patients with chronic heavy cannabis use.

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Table 3. Amplitudes of Evoked Potentials SZ

SZCA

COCA

CO

P50

First

1.8 6 1.6

2.5 6 1.9

2.3 6 1.9

2.8 6 2.0

Second

1.0 6 1.3

1.0 6 1.1

0.9 6 0.8

1.4 6 1.1

N100

First

3.5 6 3.1

4.8 6 4.3

4.8 6 3.6

6.2 6 4.4

Second

2.7 6 2.5

3.6 6 2.8

3.1 6 2.5

3.3 6 2.2

First

8.3 6 4.0

11.0 6 5.0

9.9 6 5.1

12.0 6 5.8

Second

3.9 6 2.4

3.3 6 2.5

4.9 6 2.8

4.6 6 3.0

P200

Values are mean 6 SD. Amplitudes are given in mV/m2. Please refer to main text for the statistical analysis. CO, healthy control subjects; COCA, otherwise healthy control subjects with cannabis use; SZ, schizophrenia patients without cannabis use; SZCA, schizophrenia patients with cannabis use.

(p , .01), CO compared with COCA (p , .02), SZCA compared with SZ (p , .02), and CO compared with the SZ group (p , .02; see Figure 2). Importantly, effects remained significant when current smoking status, alcohol consumption (drinks per week), Multiple Choice Vocabulary Intelligence Test score, and lifetime use of drugs other than cannabis were added to the model as covariates (three-way ANCOVA [F3,163 5 4.91, p , .003], Holm-Bonferroni corrected post hoc tests: SZCA vs. COCA, p , .02; COCA vs. CO, p , .02; SZCA vs. SZ, p , .03; SZ vs. CO, p , .03; all added covariates p . .7). To facilitate comparison with the literature, we also analyzed the P200 difference (first amplitude minus second amplitude). Again, ANCOVA showed a significant effect of group (F3,167 5 4.19, p 5 .007), age (F1,167 5 11.88, p 5 .001), and gender (F1,167 5 0.17, p . .6). Post hoc least significant difference test showed a significant difference between SZ (4.42 6 4.14 mV) and SZCA (7.64 6 5.38 mV; p 5 .019), between COCA (4.96 6 3.83 mV) and CO (7.37 6 4.45 mV; p 5 .009), between SZCA and COCA (p 5 .015), and between SZ and CO (p 5 .014). There were no significant differences between SZ and COCA (p 5 .91) and between SZCA and CO (p 5 .83). To evaluate whether differences in P200 ratio between groups were accompanied by differences in first and/or second P200 amplitudes, additional analyses were performed. The first amplitude differed significantly across groups (ANCOVA [F3,167 5 2.84, p , .04], post hoc least significant difference tests: SZCA vs. COCA, p . .4; COCA vs. CO, p , .06; SZCA vs. SZ, p . .1; SZ vs. CO, p , .007; SZCA vs. CO, p . .3). For the second amplitude there was a statistical trend for a significant difference (ANCOVA [F3,167 5 2.35, p , .1], post hoc least significant difference tests: SZCA vs. COCA, p , .02; COCA vs. CO, p . .5; SZCA vs. SZ, p . .4; SZ vs. CO, p . .2; SZCA vs. CO, p , .05). No significant amplitude differences, neither for the first amplitude nor for the second amplitude, were seen between both schizophrenia groups.

P200 Suppression, Cannabis Consumption, and Duration of Abstinence Next, we analyzed the association between cannabis use and the P200 ratio in all study subjects with a lifetime cannabis use of at least one joint (i.e., schizophrenia patients [n 5 47], P200 ratio: 0.42 6 0.34; otherwise healthy control subjects [n 5 77],

Figure 2. P200 repetition suppression ratio. The p values are Holm– Bonferroni corrected (see text). Horizontal dashed lines indicate median. P200 suppression ratio was calculated as P200 amplitude evoked by second click / P200 amplitude evoked by first click. CO, healthy subjects without chronic cannabis use; COCA, otherwise healthy subjects with chronic heavy cannabis use; SZ, schizophrenia patients without chronic drug use; SZCA, schizophrenia patients with chronic heavy cannabis use.

P200 ratio: 0.48 6 0.26). Total lifetime cannabis use showed a significant correlation with the P200 ratio (see Supplemental Figure S1) in otherwise healthy control subjects but not in schizophrenia patients (otherwise healthy control subjects, total lifetime cannabis use: 6306 6 8510 joints, regression analysis: β 5 .28, t75 5 2.55, p , .013, one-sided Pearson r 5 .28, p , .007; schizophrenia patients, total lifetime cannabis use: 7958 6 12,227 joints, regression analysis: β 5 –.18, t45 5 –1.2, p . .2, Pearson r 5 –.18, p . .1). Pearson's r differed significantly between both groups (Fisher's Z test, z 5 2.46, p , .05, two sided). In contrast, last cannabis use (i.e., months since last use) was significantly correlated with the P200 ratio (see Supplemental Figure S2) in schizophrenia patients, but not in otherwise healthy control subjects (schizophrenia patients: 61.7 6 95.2 months, regression analysis: β 5 .42, t45 5 3.09, p , .004, one-sided Pearson r 5 .42, p , .002; otherwise healthy control subjects: 45.5 6 54.4 months, regression analysis: β 5 .007, t75 5 0.062, p . .9, one-sided Pearson r 5 .007, p . .4). Pearson's r differed significantly between both groups (Fisher's Z test, z 5 2.31, p , .05, two sided).

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However, as shown in Supplemental Figure S2, the correlation between last use and P200 ratio is driven by a few patients at the extreme end of last use. Taken together, a higher amount of lifetime cannabis use was associated with a higher P200 ratio in otherwise healthy individuals. In contrast, the longer the duration of abstinence from cannabis in schizophrenia patients, the more pronounced their P200.

Sensitivity Analysis Finally, we performed a sensitivity analysis in which only SZCA patients whose onset of regular cannabis use predated the onset of schizophrenia by at least 2 years were included (n 5 26). An ANCOVA showed that the overall effect of group remained significant (F3,155 5 3.9, p , .01), and post hoc testing further confirmed that patients in the SZCA group showed lower P200 ratio than did patients in the SZ group (p , .05). Furthermore, we performed another analysis in which only subjects whose lifetime use of drugs other than cannabis amounted to less than 50 times were included (SZCA, n 5 27; COCA, n 5 36). Again, an ANCOVA confirmed that the effect of group remained significant (F3,147 5 5.73, p , .001). Post hoc testing also confirmed that SZCA patients had lower P200 ratio than did SZ patients (p , .003) and CO patients had lower P200 ratio than did COCA patients (p , .04).

DISCUSSION The current study yielded the following major findings: 1) an overall significant P50 repetition suppression effect, 2) N100 repetition suppression deficits in schizophrenia patients, and 3) an interaction between diagnosis and chronic cannabis use on P200 repetition suppression. In healthy control subjects, heavy chronic cannabis use was associated with a reduced P200 repetition suppression, whereas, cannabis use in schizophrenia was associated with increased repetition suppression. Importantly, these opposing effects of cannabis use remained statistically significant after inclusion of potential confounders such as smoking, use of other substances, gender, and age. Interestingly, total lifetime cannabis use showed a positive correlation with the P200 suppression ratio in healthy study participants but not in schizophrenia patients. The duration of time since last cannabis use was significantly associated with the P200 suppression ratio in schizophrenia patients but not in otherwise healthy control subjects. Our study confirms repetition suppression deficits of the N100 and P200 (34,38) but not of the P50 component [(39), but see (31) for a review of positive findings] in schizophrenia. In line with Broyd et al. (40) we also failed to replicate earlier findings from our own and other groups indicating deficits in P50 repetition suppression in cannabis users (32,41,42). Several explanations may apply. In the first place, P50 repetition suppression shows a relatively low retest reliability (43,44), which calls into question its generalized indiscriminate use as a bona fide neurobiological marker (45). Several other groups have also not been able to detect reduced P50 suppression ratio in schizophrenia (38,46–50). A recent largescale study from our group also found that P50 does not contribute to single-subject classification of schizophrenia

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versus control subjects (39). An additional explanation for these discrepant results may be the increasingly widespread use of atypical neuroleptics that have been reported to improve P50 repetition suppression (51). Of note, none of the schizophrenia patients in our study received monotherapy with classical neuroleptics. Accumulating evidence suggests that the neural circuitries underlying preattentive (i.e., at P50) and later (i.e., at P200) information processing differ (24,33–36,52–54). Interestingly, repetition suppression of P200, but not of P50, is correlated with P300 variables (i.e., with brain responses closely related to the engagement of attention) (38) and cognitive functioning (54,55), which may indicate that it is primarily late rather than preattentive repetition suppression that most strongly shapes subsequent information processing. A study in twins demonstrated differences in heritability with modest genetic influences on P50 but much higher effects on P200 repetition suppression (56). So far, surprisingly little research has been done on P200 repetition suppression in psychiatric disorders. Boutros et al. (34,38) reported reduced P200 repetition suppression in schizophrenia. Furthermore, a recent study of subjects at high risk of psychosis found a decrease of P200 repetition suppression after transition to overt psychosis (57). Our study confirms and extends these reports by demonstrating negative effects of both schizophrenia alone and chronic heavy cannabis use alone on P200 repetition suppression. What then may be the explanation for the diverging association of cannabis use with P200 suppression in schizophrenia patients and healthy control subjects? We can only speculate. First, it is important to acknowledge that in this cross-sectional study, cause-and-effect relationships cannot be firmly established. It has been argued that cannabis users with schizophrenia show fewer negative symptoms and better cognitive functioning because of a lower genetic risk for schizophrenia. In these patients, cannabis use would be the main precipitating factor for the development of psychosis, but would not at the same time lead to the negative symptoms and neurocognitive deficits typically associated with schizophrenia (58). The problem with this hypothesis is that is does not appear to fit well with the wealth of neuropsychological literature demonstrating adverse effects of cannabis use on cognitive functioning in nonpsychotic cannabis users (8). Taken to the extreme, this hypothesis would even seem to imply that nonpsychotic cannabis users should be the group with the lowest genetic risk for psychosis—and this despite clear evidence for cognitive deficits. Furthermore, there is little hard evidence to support the claim of a lower familial risk for psychosis in cannabis users with schizophrenia and quite some evidence to the contrary (59–62). In addition, prospective studies of cannabis use in adolescents at clinical high risk for psychosis did not indicate that lifetime cannabis use was a major contributing factor for the development of psychosis (63,64). An alternative explanation for the differences in cannabis effects between patients and healthy control subjects could be that endocannabinoid signaling is altered in schizophrenia [cannabinoid hypothesis of schizophrenia; e.g., (65,66)]. This idea is increasingly supported by exciting new data from rodent psychosis models indicating that increased cannabinoid CB1R stimulation may be beneficial regarding some

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schizophrenia-related deficits, but may be detrimental under normal conditions (67–71). One of the main sources of the P200 is the auditory cortex. Regions rich in CB1R such as the frontal lobe and hippocampus (72) may modulate the P200 amplitude (73,74). It could be speculated that the P200 suppression differences found across groups in the current study may relate to complex interactions of schizophreniarelated CB1R abnormalities and dysregulation of CB1R following long-term cannabis use. However, firm links among CB1R stimulation, exogenous cannabinoid binding, and schizophrenia remain to be established in a human sample. In this regard, the P200 repetition suppression found in this study offers a potential target variable that may help to aggregate preclinical and clinical data derived in future investigations of the endocannabinoid system. That cannabis has different neurobiological effects on otherwise healthy subjects and schizophrenia patients is reinforced by our correlation analysis. In healthy individuals, the positive correlation of the P200 suppression with the extent of cannabis use but not with cannabis abstinence suggests enduring neurobiological effects of cannabis. In schizophrenic cannabis users, however, the positive correlation of the P200 suppression with cannabis abstinence suggests a more dynamic neurobiological influence of cannabis in schizophrenia. However, sensory gating refers to the reduction of the response to the second stimulus caused by neuronal inhibitory effects induced by the first stimulus. We found higher first P200 amplitudes for the healthy control group compared with the groups with higher P200 ratio (i.e., COCA, SZ) but no differences for the second P200 amplitude. Thus, it remains unclear whether impairments in inhibitory neuronal mechanism underlie the higher P200 ratio (i.e., a deficit in gating out as a failure to reduce the prediction error signal to the expected irrelevant second stimulus) or whether the higher P200 ratios were rather caused by a reduced neuronal response to the first stimulus (i.e., a deficit in gating in as a failure to increase the prediction error signal to the unexpected relevant first stimulus). In contrast, a reduced second but not first P200 amplitude was seen for the SZCA group compared with the COCA group. Neither the first nor the second P200 amplitudes differed significantly between the SZCA and the SZ groups. However, differences of first and second amplitude among the groups underline neurobiological differences related to cannabis use between patients with schizophrenia and otherwise healthy cannabis users. There are several limitations to our study. First, we used a modified double-click protocol. Thus, our data may not be fully comparable with studies using the classic double-click paradigm. It is important to note that the information on drug use was collected by self-report. Given that our relatively naturalistic study sample was recruited from a large, socially diverse urban center, we did not require study participants in the SZ and CO groups to have never consumed cannabis. Rather, the focus of this study was laid on chronic heavy cannabis use. Not entirely surprisingly, lifetime use of other drugs was significantly increased in the cannabis groups. There were also significant differences in cigarette smoking between the four groups. Furthermore, a number of sociodemographic variables including gender, age, and educational level were

not distributed homogeneously. Interestingly, however, the differential effect of cannabis use on the P200 suppression ratio survived an ANCOVA with smoking status, alcohol consumption, lifetime use of drugs other than cannabis, and premorbid intelligence score as covariates. In addition, a subsequent sensitivity analysis with exclusion of subjects reporting a higher degree of illicit drug consumption further corroborated our results. To summarize, our study indicates that schizophrenia alone and chronic cannabis use alone are negatively associated with P200 repetition suppression. Paradoxically, cannabis use in schizophrenia was associated with a normal P200 repetition suppression. We speculate that these differential effects of cannabis on P200 repetition suppression may be caused by preexisting alterations of endocannabinoid signaling in schizophrenia.

ACKNOWLEDGMENTS AND DISCLOSURES This work was supported by a grant from the Friedrich-Ebert Foundation, Germany (to AS). We wish to thank all participants of this study. We also thank Dipl. Psych. Elise Buntebart, Dipl. Psych. Nicole Mauche, Dipl. Psych. Sophia Wagner, and Dipl. Psych. Jan Hülsenbeck for excellent organizational and technical support. The authors report no biomedical financial interests or potential conflicts of interest.

ARTICLE INFORMATION From the Departments of Psychiatry and Psychotherapy, Campus Mitte (JR, GK, AN, CM, RH), and Campus Benjamin Franklin (AS, MCJ-S), Charité – Universitätsmedizin Berlin, Berlin; Department of Psychiatry and Psychotherapy (GK), Universitätsmedizin Rostock, Rostock; and the Department of Psychiatry and Psychotherapy (MCJ-S), Oberhavel Kliniken GmbH, Hennigsdorf, Germany. JR and GK contributed equally to this work. Address correspondence to Johannes Rentzsch, M.D., Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin Berlin, Campus Mitte, Charitéplatz 1, 10117 Berlin, Germany; E-mail: johannes.rentzsch@ charite.de. Received Apr 7, 2016; revised Oct 29, 2016; accepted Oct 31, 2016. Supplementary material cited in this article is available online at http:// dx.doi.org/10.1016/j.bpsc.2016.10.004.

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