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. Author manuscript; available in PMC: 2016 Dec 30.
Published in final edited form as: Psychiatry Res. 2015 Nov 25;230(3):878–884. doi: 10.1016/j.psychres.2015.11.033

Evaluating the relationship between cannabis use and IQ in youth and young adults at clinical high risk of psychosis

Lisa Buchy 1, Larry J Seidman 2, Kristin S Cadenhead 3, Tyrone D Cannon 4, Barbara A Cornblatt 5, Thomas H McGlashan 6, Diana O Perkins 7, William Stone 2, Ming T Tsuang 3, Elaine F Walker 8, Scott W Woods 5, Carrie E Bearden 9, Daniel H Mathalon 10, Jean Addington 1
PMCID: PMC5037441  NIHMSID: NIHMS740052  PMID: 26626949

Abstract

Among people with psychosis, those with a history of cannabis use show better cognitive performance than those who are cannabis naïve. It is unknown whether this pattern is present in youth at clinical high risk (CHR) of psychosis. We evaluated relationships between IQ and cannabis use while controlling for use of other substances known to impact cognition in 678 CHR and 263 healthy control (HC) participants. IQ was estimated using the Vocabulary and Block Design subtests of the Wechsler Abbreviated Scale of Intelligence. Drug and alcohol use severity and frequency were assessed with the Alcohol and Drug Use Scale, and we inquired participants’ age at first use. CHR were further separated into early and late age at onset of cannabis use sub-groups, and low-, moderate- and high-frequency sub-groups. No significant differences in IQ emerged between CHR or HC cannabis users vs. non-users, or between use frequency groups. CHR late-onset users showed significantly higher IQ than CHR early-onset users. Age at onset of cannabis use was significantly and positively correlated with IQ in CHR only. Results suggest that age at onset of cannabis may be a more important factor for IQ than use current use or use frequency in CHR.

Keywords: age at onset, alcohol, cannabis, IQ, prodrome, schizophrenia

Introduction

Cannabis is the most widely used illicit substance in both schizophrenia and in those at clinical high risk (CHR) of developing psychosis (Addington et al., 2014). Furthermore, cannabis use severity is associated with greater positive symptoms in CHR (Caspi et al., 2005; Fusar-Poli et al., 2012; Kuepper et al., 2011; Moore et al., 2007) and epidemiological data suggest a role for cannabis in the onset of psychosis (Buchy et al., 2015a). Recent prospective data in CHR individuals have indicated that among lifetime cannabis users, higher baseline use severity (Buchy et al., in press), frequency (Valmaggia et al., 2014) and first use before the age of 15 (Arseneault et al., 2002; Valmaggia et al., 2014) are associated with an increased rate of conversion to psychosis.

It is well documented that among people diagnosed with a psychotic disorder, those with a history of cannabis use show better cognitive performance than those who are cannabis naïve (Potvin et al., 2008; Rabin et al., 2011; Yucel et al., 2012). A recent meta-analysis (Rabin et al., 2011) excluded studies with patients with a current comorbid diagnosis of drug abuse and reported a medium effect size (Cohen’s d=0.48) for higher IQ in cannabis-using patients with schizophrenia compared to non-users. Stratifying patients according to cannabis use frequency has suggested higher IQ in low- vs. high-frequency users (Leeson et al., 2012), although another study failed to observe this relationship (Tosato et al., 2013). Yucel et al.(2012) did not observe differences in IQ in psychosis patients with a lifetime exposure to cannabis compared to never-users, or in users with an early vs. late age at onset of cannabis use. Thus there is some evidence that patients with psychosis with a positive lifetime exposure to cannabis and/or who are current users show higher IQ than abstinent patients, and that use frequency may associate with IQ. The relationship between IQ and age at onset of cannabis use in people with psychoses is less clear. No published studies have characterized IQ in youth at CHR of psychosis who use cannabis compared to those who do not.

Several explanations have been proposed to explain the higher cognitive abilities in cannabis-using vs. abstinent patients with schizophrenia. One suggestion is that those who have used cannabis are less neurodevelopmentally impaired than those who did not (Leeson et al., 2012; Loberg and Hugdahl, 2009; Schnell et al., 2009). Another explanation is that early cannabis use may induce psychosis onset in less cognitively vulnerable individuals, i.e., those with better cognitive capacities, thereby facilitating the onset of psychosis that may otherwise not have occurred (Yucel et al., 2012). A related suggestion is that the better cognition in patients who use cannabis may have facilitated their recreational drug use like in typical adolescents (Ferraro et al., 2013). or that superior social skills enable cannabis-using patients to acquire and sustain a drug habit, which is reflected in their cognition (Potvin et al., 2008; Solowij and Michie, 2007).

When assessing the relationship between cannabis and IQ, it is important to control for the effects of the consumption of other substances. Tobacco and alcohol are the most frequently used substances among people with schizophrenia and in CHR than in the general population (Addington et al., 2014; Buchy et al., in press; de Leon and Diaz, 2005) and have been associated with neurocognitive function in schizophrenia (Morisano et al., 2013; Wing et al., 2011; Yip et al., 2009)(Allen et al., 1999; Cantor-Graae et al., 2001; Fowler et al., 1998; Manning et al., 2009) Stimulant use also has a deleterious effect on cognitive functions in people diagnosed with a psychotic disorder (Bahorik et al., 2014; Serper et al., 2000a; Serper et al., 2000b; Smelson et al., 2003; van der Meer et al., 2014), and other studies have reported elevated neurocognition in people with schizophrenia currently using cocaine (Bahorik et al., 2014; Benaiges et al., 2013). Therefore, these variables must be taken into account when interpreting results of the relationship between cannabis use and IQ across the schizophrenia spectrum.

The goal of the present study was to assess the relationship between cannabis use patterns and IQ in CHR youth, while controlling for any use of other substances known to impact cognition such as tobacco, alcohol and stimulants, as well as antipsychotic medications. This cohort offers a unique opportunity to examine these associations prior to the onset of psychosis, in people with a greater probability of developing a psychotic disorder relative to the general population, but who do not have potential confounds seen in patient studies such as lengthy antipsychotic treatment. Based on the literature in schizophrenia, we hypothesized that: 1) CHR youth using cannabis will have a higher IQ compared to those who do not; 2) CHR youth with a lifetime exposure to cannabis will have a higher IQ compared to never-users; and 3) CHR low-frequency cannabis users will have a higher IQ than CHR high-frequency users. Additionally, we conducted exploratory analyses of IQ in relation to age at onset of cannabis use in CHR youth, and in CHR separated dichotomously by early vs. late age at onset of cannabis. We also conducted an exploratory analysis of IQ in CHR converters vs. non-converters separated by current cannabis use (Y/N).

Methods

Participants

Participants were recruited for the second phase of the multi-site North American Prodrome Longitudinal Study (NAPLS-2) (Addington et al., 2012). The final NAPLS-2 sample consists of 764 CHR participants and 280 healthy controls (HC). The present paper reports on the 678 CHR and 263 HC participants in NAPLS 2 who provided baseline IQ data and completed an assessment on cannabis use. All CHR participants were required to meet the Criteria of Prodromal Syndromes (COPS) using the Structured Interview for Prodromal-Risk Syndromes (SIPS) (McGlashan et al., 2010).

Participants were excluded if they met criteria for any current or lifetime axis I psychotic disorder, IQ<70, past or current history of a central nervous system disorder or DSM-IV criteria for a current substance dependence disorder. HC participants were also excluded if they had a first-degree relative with a current or past psychotic disorder. HC and CHR participants were not matched for IQ; however, we made every attempt to match groups on age, sex and parental socioeconomic status. A more detailed description of ascertainment, inclusion and exclusion criteria, and participant details is provided elsewhere.(Addington et al., 2012)

Measures

The SIPS and the Scale of Prodromal Symptoms (SOPS) (McGlashan et al., 2010) were used to assess criteria for a prodromal syndrome and severity of attenuated positive symptoms.

Alcohol and drug use for cannabis, cocaine and amphetamine severity over the last month was rated using the Alcohol and Drug Use Scale (Drake et al., 1996) as 1=abstinent, 2=use without impairment, 3=abuse, 4=dependence. Frequency of use was rated as 0=no use, 1=once or twice per month, 2=3–4 times per month, 3=1–2 times per week, 4=3–4 times per week, or 5=almost daily. Frequency of tobacco use was rated differently as 0=no use, 1=occasionally, 2=less than 10 per day, 3=11–25 per day, 4=more than 25 per day. Based on commonly used measures and interview questions in the literature (Arseneault et al., 2002; Caspi et al., 2005; Henquet et al., 2005), we also enquired whether they had ever used cannabis and the age at first use.

IQ was estimated with the Vocabulary and Block Design subtests of the Wechsler Abbreviated Scale of Intelligence (Wechsler, 1999).

Cannabis groups

First, we separated CHR participants into three groups of users: early-onset (>age 15), late-onset (≥age 15), and cannabis naïve.

Next, CHR individuals were grouped according to baseline cannabis use frequency and compared on IQ: Abstinent, low-frequency (<5 times per month), moderate-frequency (<5 times per week), and high-frequency users (Daily).

Lastly, we separated CHR youth into four sub-groups according to baseline cannabis use and subsequent conversion vs. non-conversion to psychosis: CHR who converted and were using cannabis (Converter+Cannabis), CHR who converted and were abstinent (Converter- Cannabis), CHR who did not convert and were using cannabis (NonConverter+Cannabis), and CHR non-converters abstinent from cannabis (NonConverter-Cannabis).

Procedures

All eight NAPLS sites (Emory University, Harvard University/Beth Israel Deaconess Medical Center, University of Calgary, University of California at Los Angeles, University of California at San Diego, University of North Carolina at Chapel Hill, Yale University, and Zucker Hillside Hospital) recruited CHR and HC participants. Raters were experienced research clinicians who demonstrated adequate reliability at routine reliability checks. Post-training agreement on the critical threshold for determining initial eligibility, subsequent conversion status and prodromal diagnoses based on the SIPS was excellent (kappa=.90). All testers across sites received training on IQ measures at the beginning of the study under the supervision of LJS and WS and ongoing within site and across site supervision was carried out at least a few times every month (Meyer et al., 2014). The Principal Investigator or clinical psychiatrist or psychologist at each site conducted a comprehensive clinical assessment to determine if entry criteria were met (Addington et al., 2012). Clinical assessments that included the AUS/DUS were conducted at baseline. The study protocols and informed consents were reviewed and approved by the ethical review boards of all eight NAPLS study sites. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

Statistical Analysis

Chi-square or Fisher’s Exact analyses for categorical variables and t-tests for continuous variables were used to compare CHR and HC groups on demographic variables and substance use. T-tests were used to compare participants using cannabis at baseline vs. those who were abstinent on IQ. Spearman’s correlations were used to evaluate associations of age at onset of cannabis use with IQ scores. ANCOVAs were then used to determine the relationship between IQ and cannabis use patterns while controlling statistically for the effects of confounding variables (demographics, alcohol, tobacco, cocaine and amphetamine use). Univariate ANOVAs were used to compare IQ in the following groups: 1) early-onset, late-onset, and naïve, and 2) CHR abstinent, low-frequency, moderate-frequency, and high-frequency. Similarly, ANCOVAs were then used to determine the relationship between IQ and cannabis use groups while controlling statistically for the effects of confounding variables (see above). Tukey’s post-hoc tests were used to compare groups where appropriate. The p-value was set to 0.05/6=0.008 to correct for the number of comparisons with IQ. Statistical analyses were performed using SPSS 21.0.

Results

Demographics, cannabis use patterns and IQ

In the entire sample, males and females did not significantly differ on IQ, t=0.24, p=0.81. Age and years of education showed small but significant positive correlations with IQ scores, r=0.11, p=0.001; r=0.18, p<0.001, respectively. Alcohol use was also significantly correlated with IQ, r=0.20, p<0.001. Tobacco, cocaine and amphetamine use did not significantly correlate with IQ, r=0.007, p=0.83; r=−0.02, p=0.38; r=0.02, p=0.50, respectively. In CHR, baseline IQ did not differ in those taking antipsychotics from those not taking antipsychotics, t=0.92, p=0.36. Therefore, years of education and alcohol use were entered as covariates in all analyses.

As summarized in Table 1, HC participants were significantly older and had greater years of education than CHR participants. These groups did not differ on gender or race.

Table 1.

Demographic and clinical characteristics of the clinical high risk and healthy control groups.

CHR
n=678		 HC
n=263
n (%) n (%) χ2 p-value
Sex
Male 390 (58) 136 (52) 2.60 0.11
Female 288 (42) 127 (48)
Race1
First Nations 13 (1.9) 5 (1.9) 3.56 0.94
Asian 52 (7.7) 24 (9.2)
Black 103 (15.2) 48 (18.3)
Latin America/Middle East/White 427 (62.9) 156 (59.2)
Native Hawaiian/Pacific Islander 3 (0.4) 1 (0.4)
Inter-racial 78 (11.5) 29 (11.0)
Mean (SD) Mean (SD) t p-value
Age (years) 18.5 (4.3) 19.7 (4.6) 3.78 <0.001
Range: 12 – 34 Range: 12 – 35
Education (years) 11.3 (2.8) 12.7 (3.6) 6.34 <0.001
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Note. CHR, Clinical High Risk; HC, Healthy Controls; SD, Standard Deviation.

1

Racial information was missing for two participants.

Table 2 displays cannabis use patterns of the CHR and HC groups. These groups did not differ on baseline cannabis use frequency, lifetime cannabis exposure, number of current users, or age at onset of cannabis use. However, CHR participants had significantly higher baseline cannabis use severity.

Table 2.

Rates and patterns of cannabis and other drug use over lifetime in clinical high risk and healthy control participants.

CHR
n=678		 HC
n=263		 Statistic
Mean (SD) Mean (SD) t p-value
Cannabis
  Number of times used in lifetime1 63.7 (109.5) 41.9 (89.4) 2.88 0.004
  Age first tried2 15.7 (2.9) 16.2 (2.5) 1.62 0.11
n (%) n (%) χ2 p-value
  Current user: Yes 149 (22.0) 43 (16.3) 3.32 0.07
  Lifetime exposure: Yes 351 (51.8) 128 (48.7) 0.73 0.39
  Use severity3
Abstinent 538 (79.4) 220 (83.7) 6.71 0.08
Use without impairment 116 (17.1) 41 (15.6)
Abuse 22 (3.2) 2 (0.8)
Dependence 2 (0.3) 0 (0.0)
  Use frequency for current users3
1–2 × per month 55 (41.6) 18 (6.8) 4.66 0.46
3–4 × per month 20 (13.4) 6 (2.3)
1–2 × per week 26 (18.1) 6 (2.3)
3–4 × per week 20 (13.4) 9 (3.4)
Every day 19 (12.8) 4 (1.5)
Missing 1 (0.6) 0 (0.0)
Tobacco Fisher’s exact
p-value
  Use severity3
Abstinent 532 (78.5) 227 (86.3) 0.04
Use without impairment 136 (20.1) 32 (12.2)
Abuse 5 (0.7) 0 (0.0)
Dependence 5 (0.7) 2 (0.8)
Missing 0 (0.0) 2 (0.8)
Other drug use
  Alcohol
Abstinent 412 (60.8) 133 (50.6) 0.01
Use without impairment 249 (36.7) 126 (47.9)
Abuse 13 (1.9) 3 (1.1)
Dependence 4 (0.6) 0 (0.0)
  Cocaine
Abstinent 667 (99.3) 262 (99.6) 0.47
Use without impairment 1 (0.1) 1 (0.4)
Abuse 0 (0.0) 0 (0.0)
Dependence 0 (0.0) 0 (0.0)
  Amphetamine
Abstinent 667 (99.9) 261 (99.2) 0.19
Use without impairment 1 (0.1) 2 (0.8)
Abuse 0 (0.0) 0 (0.0)
Dependence 0 (0.0) 0 (0.0)
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Abbreviations: CHR = Clinical High Risk, HC = Healthy Control, SD = Standard Deviation

1

Excludes never-users.

2

Excludes people who had never used cannabis.

3

Measured with the Alcohol and Drug Use Scale.

HC had significantly higher IQ than CHR participants, t=4.62, p<0.001; M=109.5, SD=14.0 and M=104.5, SD=15.4, respectively.

Relationship between IQ and cannabis use patterns when stratifying by CHR/controls

IQ scores in CHR and HC participants stratified by cannabis use are reported in Table 3.

Table 3.

IQ scores of CHR and healthy control participants stratified by cannabis use patterns.

IQ score
CHR
n=678		 HC
n=263
Mean (SD) Mean (SD)
Currently using
Yes 107.8 (14.9) 108.4 (15.0)
No 103.7 (15.4) 109.6 (13.8)
Lifetime exposure
Yes 106.5 (14.7) 108.1 (14.1)
No 102.5 (15.9) 109.9 (13.9)
Age first tried
Naïve (n=327) 102.5 (15.9) --
Early-onset (n=122) 102.0 (14.2)
Late-onset (n=227) 108.9 (14.4)
Frequency
Abstinent (n=529) 103.7 (15.5) --
Low-frequency (n=82) 108.6 (14.9)
Moderate-frequency (n=27) 106.9 (15.1)
High-frequency (n=20) 109.3 (13.8)
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Abbreviations: CHR = Clinical High Risk, HC = Healthy Control, SD = Standard Deviation

Current use

To test hypothesis 1, we evaluated IQ in CHR and HC cannabis users vs. non-users at baseline. In CHR participants, IQ was significantly higher among those who were using cannabis compared with those who were not, t=2.82, p=0.005. In contrast, in HC participants, there was no statistically significant difference in IQ scores between those who were or were not using cannabis, t=0.49, p=0.63. An ANCOVA adjusting for years of education and alcohol use in the CHR group indicated that the group difference in IQ was no longer significant, F(1,668)=0.53, p=0.47. The result in the HC group remained non-significant when adjusting for the same covariates with ANCOVA, F(1,244)=0.49, p=0.48.

Lifetime exposure

To test hypothesis 2, we evaluated IQ in CHR and HC with a positive vs. negative lifetime exposure to cannabis. CHR participants who reported a positive lifetime exposure had a higher IQ than those who had never used cannabis, t=3.38, p=0.001. By contrast, HC participants with and without a lifetime exposure to cannabis did not significantly differ on IQ scores, t=0.60, p=0.55. An ANCOVA adjusting for years of education and alcohol use in the CHR group indicated that this result was no longer significant, F(1,668)=0.01, p=0.93. The result in the HC group did not change when adjusting for the covariates with ANCOVA, F(1,258)=2.00, p=0.16.

Relationship between IQ and cannabis use frequency

To test hypothesis 3, we evaluated IQ in CHR participants categorized according to baseline cannabis use frequency. Twenty (3.0%) admitted to high-frequency use, 27 (4.9%) to moderate-frequency use, 82 (12.1%) to low-frequency use and 529 (78.0%) were abstinent (data were missing for one participant). Demographic and clinical characteristics as well as IQ scores for these groups are presented in Supplemental Table 1. IQ scores are presented in Table 3. These groups significantly differed in age, education, and SOPS total attenuated positive symptoms, as well as cannabis, alcohol, tobacco and cocaine use. Thus, these seven variables were entered as covariates using ANCOVA.

The group effect in the ANCOVA was non-significant, F(3,641)=0.51, p=0.68, indicating that CHR participants classified according to cannabis use frequency did not differ on IQ.

Relationship between age at cannabis use onset and IQ in CHR

To test exploratory hypothesis 1, we first correlated IQ with age at onset of cannabis use in CHR participants. Age at onset of cannabis use was significantly and positively correlated with IQ scores, r=0.26, p<0.001 (see Figure 1). The correlation between age at onset and IQ scores was non-significant in the HC group, r=0.16, p=0.08. In CHR, when controlling for years of education and alcohol use with partial correlation, the result remained significant, r=0.16, p=0.004. In HC participants, adding the same covariates using partial correlation did not change the results, r=0.12, p=0.18.

Figure 1.

Figure 1

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Correlation between age at onset of cannabis use and IQ in CHR, r=0.26, p<0.001.

Relationship between IQ and early age of onset of cannabis use

To test exploratory hypothesis 2, we evaluated IQ in CHR participants sub-grouped by age at onset of cannabis use. One-hundred twenty-two (18.0%) CHR participants had an early-onset, 227 (33.5%) had a late-onset, and 327 (48.2%) were cannabis naïve (data were missing for two participants). Demographic and clinical information for these three groups are presented in Supplemental Table 2. These groups significantly differed on age, education, SOPS total positive symptoms, as well as cannabis, alcohol, tobacco and cocaine use. Thus, these six variables were entered as covariates using ANCOVA.

When comparing these three CHR sub-groups on IQ, the ANCOVA indicated a significant main effect of Group, F(3,641)=6.13, p<0.001. Tukey’s post-hoc tests indicated that the late-onset group had significantly higher IQ than the early-onset (p<0.001) and naïve CHR groups (p=0.002).

IQ in CHR converters vs. non-converters separated by current cannabis use vs. no use

To test exploratory hypothesis 3, we evaluated IQ in CHR participants categorized by current cannabis use vs. no use and subsequent conversion vs. non-conversion to psychosis. Using this categorization, 23 were in the Converter+Cannabis group, 61 in the Converter-Cannabis group, 118 in the Non-converter+Cannabis group and 476 in the Non-converter-Cannabis group. Demographic and clinical information for these four sub-groups are presented in Supplemental Table 3. These sub-groups significantly differed on age, education, and alcohol and tobacco use. Thus, these four variables were entered as covariates using ANCOVA.

When comparing these four CHR groups on IQ, the ANCOVA indicated a significant main effect of Group, F(3,661)=2.61, p=0.05. As this effect was at trend level after correction for multiple comparisons, we conducted post-hoc tests to reveal potential group differences. Tukey’s post-hoc tests indicated that the Non-converter+Cannabis group had significantly higher IQ than the Non-converter-Cannabis (p=0.04) and Converter+Cannabis group (p=0.01).

Discussion

The aim of the current work was to evaluate IQ in relation to patterns of cannabis use in a large CHR sample while controlling statistically for confounding demographic variables and use of other substances that are known to alter cognition. Results indicated that although both CHR participants with a positive lifetime exposure to cannabis use and CHR current cannabis users showed higher IQ than CHR participants who were abstinent, these effects were confounded by age and other substance use. Thus, hypotheses 1 and 2 were not supported. Hypothesis 3 also received little support as CHR participants classified according to cannabis use frequency did not differ on IQ. On the other hand, our exploratory analysis indicated that in CHR participants, age at onset of cannabis use was significantly and positively correlated with IQ, and CHR participants with early-onset cannabis use (i.e., before age 15) and cannabis naïve CHR participants showed significantly lower IQ than CHR late-onset users (at or after age 15). Both effects survived when removing variance due to age and use of other substances, suggesting age at first use of cannabis may be a more important factor for IQ than use severity/frequency or lifetime exposure in people who are at CHR of psychosis.

CHR and HC participants with a positive lifetime exposure to cannabis use were indistinguishable on IQ from those who had never used cannabis. Our analysis of current users vs. non-users also suggested no differences in IQ in either CHR or HC groups. It should be noted that the positive lifetime exposure variable includes people who have used only once through people who use daily, thereby creating a heterogeneous group whose data are unlikely to yield meaningful information on which aspects of cannabis use relate to IQ. Yucel et al.(2012) also did not observe differences in IQ in their first-episode psychosis patients with a positive lifetime exposure to cannabis compared to never-users. However, two recent studies in first-episode psychosis reported higher IQ in patients with a positive lifetime exposure compared to never-exposed patients (Ferraro et al., 2013; Leeson et al., 2012), and retrospective data from a large cohort of Swedish conscripts have suggested that lifetime cannabis exposure and low IQ may have an additive relationship on risk for developing psychosis (Zammit et al., 2010). That current CHR cannabis users did not differ from CHR non-users is inconsistent with meta-analytic data in schizophrenia suggesting superior cognitive functioning in cannabis-using patients compared to non-using patients (Rabin et al., 2011). Our CHR sample had very few observations for “abuse” (n=22) or “dependence” (n=2), and analyses of samples with higher proportions of CHR youth with higher use severities may help clarify whether use severity is associated with IQ in this population. In light of our result, hypotheses that patients with schizophrenia who use cannabis are less neurodevelopmentally impaired than patients who did not use cannabis (Leeson et al., 2012; Loberg and Hugdahl, 2009; Schnell et al., 2009) may not extend to the CHR phenotype.

Categorizing CHR participants according to patterns of cannabis use frequency yielded no indication that low use frequencies were a differentiating factor for IQ in our sample. Although no studies have examined such relations in CHR individuals, one study in schizophrenia has reported higher premorbid IQ in low- compared to high-frequency users (Leeson et al., 2012), although another study failed to observe this relationship (Yucel et al., 2012). Our CHR sample had very few observations for moderate- and high-frequency users (n=27 and n=22, respectfully), and samples with higher representation in these categories may clarify whether an association between use frequency and IQ is seen in CHR youth. Our data do not provide support for the hypothesis that the neuroprotective properties of cannabis use accounts for observed relations between low frequency cannabis use and a higher IQ in schizophrenia (Jockers-Scherubl et al., 2007).

Perhaps the most novel result from our analyses is the significant correlation that emerged between IQ and age at onset of cannabis use in our CHR sample. This result was not observed in HC participants, suggesting a specific effect that is unique to the CHR status. A younger age at onset is now emerging as an important environmental risk factor in CHR youth, with findings suggesting that younger age at first usage confers greater risk for conversion to psychosis (Valmaggia et al., 2014), an earlier age at onset of prodromal and psychotic symptoms (Leeson et al., 2012), as well as altered brain activation patterns (Buchy et al., 2015b) and white matter microstructure (Dekker et al., 2010). That age at onset of cannabis use had a positive and linear association with IQ suggests that an older age at first use may be a protective factor for a higher IQ in CHR youth. Alternatively, a higher IQ may lead CHR individuals to delay the onset of their cannabis use during adolescence. Interestingly, this effect extended to CHR youth dichotomized into early- vs. late-onset groups, suggesting that first use before age 15 shares a particularly negative relationship with IQ in our sample. In concert, these results suggest that IQ is associated with the age of exposure to cannabis in a linear fashion and there may be a specific interaction with IQ when exposure occurs during a sensitive period in development. This result also has implications for current theories of cannabis use and IQ in schizophrenia. For instance, these older individuals may form a subgroup of higher intellectually functioning individuals who may also be less neurodevelopmentally impaired (Leeson et al., 2012; Loberg and Hugdahl, 2009; Schnell et al., 2009) and/or have higher social functioning than CHR individuals with an earlier age at onset (Ferraro et al., 2013).

Our analysis of CHR converters vs. non-converters sub-grouped by current cannabis use vs. no-use revealed some interesting findings. First, non-converters using cannabis showed higher IQ than non-converters abstinent from cannabis. This result is consistent with findings in people with schizophrenia (Yucel et al., 2012) and suggests that this well documented effect extends to the CHR population, thus providing support for accounts holding that those using cannabis are less neurodevelopmentally impaired than those who are not (Leeson et al., 2012; Loberg and Hugdahl, 2009; Schnell et al., 2009), and that cannabis users have less premorbid cognitive impairment than those who are abstinent (Joyal et al., 2003; Rodriguez-Sanchez et al., 2010; Stirling et al., 2005). Second, non-converters using cannabis at baseline showed higher IQ than converters using cannabis at baseline. This finding may suggest that in people at clinical risk for psychosis, a lower IQ may be a risk factor for conversion, or higher IQ may be a protective factor against conversion (Woodberry et al., 2010). Converters using cannabis did not differ from abstinent converters. This negative result is inconsistent with other findings in first-episode psychosis (Ferraro et al., 2013; Leeson et al., 2012), and the small number of people in these groups may have rendered this analysis under-powered to detect a significant effect.

Limitations include the self-report ascertainment of cannabis use, which may be less reliable than collection of biologically based specimens such as urine toxicology data. Further, details on cannabis dosage were not collected and therefore their potential impact on IQ cannot be determined. Nevertheless, the results provide partial support for findings in schizophrenia, and extend these results by establishing a link between an older age at onset of cannabis use and higher IQ in CHR. Future research in CHR samples should examine individuals’ long-term cannabis use patterns and its covariation with IQ over time.

Supplementary Material

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Acknowledgements

J Stowkowy, T Raedler, L McGregor, D Marulanda, L Legere, L Liu, C Marshall, E Falukozi, E Fitton, L McAusland, K Smith (University of Calgary). T Alderman, K Shafer, I Domingues, A Hurria, H Mirzakhanian (UCSD). B Walsh, J Saksa, N Santamauro, A Carlson, J Kenney, B Roman (Yale University). K Woodberry, AJ Giuliano, W Stone, JM Rodenhiser, L Tucker, R Serur, G Min, R Szent-Imrey (Beth Israel Deaconess Medical Center/Harvard). C Bearden, P Bachman, J Zinberg, S DeSilva, A Andaya, S Uguryan (UCLA). J Brasfield, H Trotman, (Emory University). A Pelletier, K Lansing, H Mates, J Nieri, B Landaas, K Graham, E Rothman, J Hurta, Y Sierra (University of North Carolina). A Auther, R Carrion, M McLaughlin, R Olsen (Zucker Hillside Hospital).

Funding

This study was supported by the National Institute of Mental Health (grant U01MH081984 to Dr Addington; grants U01 MH081928; P50 MH080272; Commonwealth of Massachusetts SCDMH82101008006 to Dr Seidman; grants R01 MH60720, U01 MH082022 and K24 MH76191 to Dr Cadenhead; grant U01MH081902 to Dr Cannon; P50 MH066286 (Prodromal Core) to Dr Bearden; grant U01MH082004 to Dr Perkins; grant U01MH081988 to Dr Walker; grant U01MH082022 to Dr Woods; and UO1 MH081857-05 grant to Dr Cornblatt. The NIMH had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.

Footnotes

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Conflict of Interest

All authors declare no conflict of interest.

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