Predictors of Abnormal Involuntary Movement in an African Schizophrenia Population

Mental health workers were asked to identify possible participants, who were then screened for suitability and diagnosed according to DSM-IV criteria. Patients were included in the study after providing written, informed consent as stipulated in the protocol approved by the local Institutional Review Board of the University of Stellenbosch, South Africa. The father, mother, and/or unaffected sibling of the proband were contracted to the study in order to provide phenotypical and genealogical information.

Subjects were divided into two groups, those with involuntary movements (AIMS>0) and those without involuntary movements, which defined the dependent variable in the statistical analysis. The decision to consider any positive score on the AIMS on a cross-sectional assessment as indicative of abnormal movements is significantly less stringent than the Schooler-Kane criteria 5 and may be overinclusive of movements that would not necessarily lead to functional impairment. Nevertheless, we do report on the number of participants from this group who met criteria for tardive dyskinesia and a post hoc classification was done according to the Morgenstern-Glazer criteria 26 for the presence of tardive dyskinesia to allow for a direct comparison with Patterson et al. 3 This criterion specifies a score of “mild” on at least two items or “moderate” on any one item of the seven measured domains. However, the potential outcome of this study had to consider the structure and availability of health resources within South Africa. As the majority of mental health treatment takes place in a community setting under the care of nursing personnel, the use of our criteria (presence of any positive score on AIMS) was within the abilities of the available health resources and assisted in the screening of patients with possible tardive dyskinesia. Various potentially explanatory factors of involuntary movement were considered, including age at interview, gender, subsections of the SANS, duration of illness, drug use history, and smoking. The binary variable, presence/absence of involuntary movement, was modeled using a multivariate logistical (logit) model. The results were confirmed by substituting a probit model for the logit model.

This study found involuntary movements, as defined by a positive AIMS score, in 19.4% of this group of Xhosa schizophrenia patients. This is within the lower range of previously reported data in Caucasian and African samples. It is, however, important to note that previous studies in African population groups used samples with mixed diagnoses 3, 4, 6 and limited their reports to predefined tardive dyskinesia criteria.

Our results support the notion (in keeping with previous findings by Gatere et al. 6 ) that involuntary movements increases with increasing age, but in a nonlinear manner. Age had a nonlinear effect in the logit model, with opposing signs for age (p=0.003) and age-squared (p=0.001). The implication is that age has little impact on the probability of involuntary movements at an earlier age, but an increasing impact as age progresses. In contrast to Patterson et al., 3 neither the duration of illness nor the duration of treatment in our sample had any significant effect on the probability of involuntary movements. However, Patterson’s findings only held true for “documented” treatment duration; when patient collateral was taken into account, the significance disappeared. This issue is partly reflected by our data, where a large category exists with undetermined length of treatment (category 999). This could be due to the difficulties associated with recall bias in reporting treatment duration and the problems associated with the availability of treatment records at other hospitals. Since both Patterson’s study and our study were done in the same country, it clearly illustrates the challenge of establishing reliable treatment records over the period of treatment.

Waddington et al. 11, 12 found that those patients with and without involuntary movements could not be distinguished by type of neuroleptic treatment. Since more than 95% of our sample used typical antipsychotic treatment, it was not possible for us to evaluate atypical versus typical antipsychotics as a risk factor for involuntary movements. Although it can be argued that the current trend toward the use of atypical antipsychotics makes tardive dyskinesia or involuntary movements less of an issue, the direct cost of atypical treatment remains a stumbling block for its use in many developing countries. Involuntary movements due to the use of typical antipsychotics will, for the foreseeable future, remain a reality in these countries.

Modeling of the data set shows that a model which combines age at interview, age-squared, cannabis use or abuse, and anhedonia successfully identifies 82.35% (85.29% of tardive dyskinesia) of abnormal involuntary movements cases overall. The value of this model is that is provides a set of clinical risk factors to identify individuals at risk for the development of involuntary movements in an area with limited community health resources. The three factors (age at interview, cannabis use or abuse, and anhedonia) are relatively easy to monitor and will not be affected significantly by cross-sectional assessments or recall bias. Previously published data by our group 23 on an independent Xhosa schizophrenia sample suggested that negative symptoms may remain relatively stable and should thus be a reliable cross-sectional marker to use in future predictor studies.

Cannabis remains one of the most common drugs of abuse in South Africa. Our results seem to suggest that a history of cannabis use or abuse may be a protective factor against the development of involuntary movements. This protection seems not to significantly depend on current (at time of assessment) urine drug screen status or duration of use or abuse. We regard this as a fascinating, albeit not an altogether unexpected, finding as several lines of evidence suggest that cannabinoid receptors play an active role in dopamine homeostasis. Animal studies indicate that tetrahydrocannabinol (THC) increases dopamine synthesis and release in the CNS while inhibiting dopamine clearance via the dopamine transporter. Furthermore, antagonists to cannabinoid 1 (CB1) receptors reduce the activity of dopaminergic neurons in the mesolimbic area in animal models, and interaction between THC and the cannabanoid receptor leads to dopamine release in the mesolimbic pathway, which mediates the reinforcing properties of cannabis. 28, 29

Postmortem studies in human subjects have suggested that CB1 receptors are increased in the frontal cortex of individuals with schizophrenia who used cannabis shortly before death, 30 while elevated endogenous cannabinoid levels have been detected in the cerebro-spinal fluid of subjects with schizophrenia. 31 Also, THC seems to stimulate the nigrostriatal dopaminergic pathway, which projects from dopaminergic cell bodies in the substantia nigra of the brainstem via axons terminating in the basal ganglia or striatum. This pathway is part of the extrapyramidal nervous system and controls motor movements. Deficiencies in this pathway may cause movement disorders and THC mediated stimulation of this pathway could, in part, explain a protective role for cannabis in the development of movement disorders. 32

Anandamide, an endogenous ligand for cannabinoid receptors, increases the release of dopamine in the striatum and the mesolimbic system by activating the CB1 receptors. 33 Also, stimulation of cannabanoid receptors can increase gamma-aminobutyric acid (GABA) in the lateral segment of the globus pallidus and reduce glutamate release in the striatum. This, in addition to Dean et al.’s 30 finding of reduced dopamine transporter in the caudate of THC negative schizophrenia patients, suggests that cannabis use may reverse dopamine transporter associated changes found in schizophrenia.

Furthermore, CB1 receptors are encoded by the CNRI gene, which was cloned by Matsuda et al. 34 Ujike and Morita 29 demonstrated that certain alleles or genotypes of the CNRI gene may confer a susceptibility for schizophrenia, especially the subtype with predominantly negative symptoms. Brown and White 35 found that patients with high SANS scores had significantly more severe tardive dyskinesia. Put together, these findings could indicate that the common denominator linking involuntary movements and negative symptoms in schizophrenia may have a genetic underpinning.

The amotivational syndrome linked to long-term use of cannabis could theoretically influence the findings on the negative symptom scale of the SANS. However, this syndrome more closely resembles asociality, avolition, and apathy, which did not have a significant effect in our study. It is therefore possible that a relationship between involuntary movements and the latter group of negative symptoms may be obscured by the amotivational syndrome of long-term cannabis use.

According to Ujike and Morita 29 an increase in CB1 receptors can be demonstrated in the caudate and putamen in schizophrenia. It is thought that this increase in receptors may be associated with negative symptoms and with some of the cognitive disturbances found in schizophrenia. However, in our study, except for anhedonia, no significant effect for specific subcategories of the SANS (affective changes, alogia or avolition/apathy) were found.

What is interesting, however, is that, in our study, anhedonia was associated with the group that displayed fewer involuntary movements. Anhedonia can be defined as the loss of interest in, and withdrawal from, all regular and pleasurable activities. Anhedonia and other predominantly negative symptoms may be caused by a dysfunction in the ventral striatum, including the nucleus accumbens—a core region of the brain reward system. Ventral striatal activity has been associated with pleasant emotions of anticipation and ventral striatal dysfunction has long been associated with reduced motivation or anhedonia. 36 As the striatum also forms a central part of the basic motor loop that controls movement, it is possible that abnormal involuntary movement and anhedonia share a common underlying pathological mechanism.

One of the strengths of this study was the use of structured assessment tools in a relatively homogenous (schizophrenia) clinical population. Nevertheless, our study criteria for involuntary movement are specifically not limited to tardive dyskinesia. However, the post-hoc analysis to a large extent supports the validity of the results for tardive dyskinesia as well.

This study demonstrates that involuntary movements occur frequently in Xhosa patients with schizophrenia and that increasing age, as well as a negative cannabis use history and the absence of anhedonia, is a significant predictor of abnormal involuntary movements. The use of treatments that can effectively address negative symptoms may therefore have the possibility of reducing involuntary movements in patients with schizophrenia. Cannabinoid receptors may also serve as potential drug targets for the treatment or prevention of involuntary movements. In fact, Fox et al. 37 tested the hypothesis that the cannabanoid receptor agonist nabilone would alleviate L -dopa-induced dyskinesia. They demonstrated that coadministration of nabilone with L -dopa was associated with significantly less dyskinesia. It will also be important to investigate possible underlying genetic factors that could contribute to these findings, including Cytochrome P450 and cannabinoid receptor polymorphisms.