Identification of vulnerability among first-degree relatives of patients with schizophrenia/[TEXT NOT REPRODUCIBLE IN ASCII].
The prediction of psychosis and related psychopathology has become an important focus in schizophrenia research. Pre-morbid studies of relatives at risk for schizophrenia are critical to closing in on the aetiopathology of the disease and providing promising directions for the earliest prevention and intervention strategies. Studies have emphasised the need for early detection and treatment of the prodrome in order to avoid a full psychotic episode. In addition, early detection of the prodrome may shorten the overtly psychotic period, help establish a good therapeutic alliance, and improve quality of life and long-term outcome by minimising severity and disability. (1,2) Recently, the rate of transition to psychosis in very high-risk individuals has been
shown to be 10 to 15%. (3,4) Various vulnerability markers (5-7) have been investigated for identifying individuals at risk for the later development of schizophrenia-spectrum disorders. Neuroanatomical changes in individuals at high genetic risk for schizophrenia have also been demonstrated, (8-12) thus further supporting the role of vulnerability markers. Several variables have been examined as potential vulnerability markers, including schizotypy, markers of neurodevelopmental insult (i.e. soft signs and minor physical anomalies), physiological markers (e.g. evoked potentials), and neurocognitive measures (especially episodic and working memory).
Most of the studies to date have examined individual domains, whereas the underlying neurocognitive systems are inherently complex and interrelated. It has been shown that the predictive power of individual factors by themselves is not large. (13) An integrative model that takes into account the relationship between neurobiological, cognitive, and clinical vulnerability markers for the disorder may provide a more powerful method for detecting risk for schizophrenia at the earliest phases of the illness. It is also possible that the issue of specificity of prediction might be addressed by a combination model.
The present study aimed to evaluate the status of schizotypy, neurological soft signs (NSS), and cognitive functions as vulnerability markers for schizophrenia; and to investigate the value of combining vulnerability markers in risk prediction. Psychometric measures (schizotypy), NSS, and neurocognitive domains (i.e. attention, verbal and visuospatial working memory, and verbal memory through paired associate learning) were selected for assessment of first-degree relatives of the schizophrenics. We hypothesised that they have more schizotypy and NSS findings and perform more poorly on cognitive function tasks than control subjects.
A cross-sectional study was conducted. Subjects were drawn from first-degree relatives (parents, siblings and offspring) of schizophrenic patients admitted as inpatients or outpatients at our institution. The study included 50 consecutive first-degree relatives of the schizophrenics (diagnosis of all patients was reviewed and confirmed by 2 psychiatrists independently based on the ICD-10 criteria) and 30 healthy controls. Recruited by word-of-mouth from hospital staff and attendants of hospitalised patients, the controls were then assessed by clinical interview prior to study inclusion to exclude any psychopathology.
The study was approved by the Research Review Board and Ethics Committee of the institution. Informed consent was obtained from subjects before taking part in the study.
A specially designed screening proforma (consisting of selection criteria) was adopted to ensure that all subjects who met the inclusion criteria were recruited into the study. Subjects of either sex, aged 18 to 65 years, and being literate enough to read and understand the questionnaires were recruited. Exclusion criteria included: (1) lifetime history of any psychiatric disorder; (2) substance abuse; (3) history of head injury with any documented cognitive sequelae or with loss of consciousness; (4) neurological disease or injury; (5) mental retardation; or (6) any medical illnesses that might significantly impair neurocognitive function. Subjects with a first-degree relative with a psychotic disorder were excluded from the control group.
Socio-demographic data of the subjects were recorded. After that, each participant in the study was subjected to selected measures for assessment.
Schizotypal Personality Questionnaire
The Schizotypal Personality Questionnaire-Brief Version (SPQ-B) (14,15) is a self-report questionnaire with a dichotomous response format (yes/no) for identification of individuals with schizotypal traits. It is a quick, 2-minute, 22-item instrument which consists of the most reliable items from the original SPQ. The SPQ-B yields a total score, together with 3 subscale scores (cognitive-perceptual, interpersonal, and disorganised domains). Internal reliabilities of these subscales ranged from 0.72 to 0.80 (mean = 0.76), and 2-month test-retest reliabilities from 0.86 to 0.95 (mean = 0.90). Inter-correlations between SPQ-B factors and SPQ factors ranged from 0.89 to 0.94 (mean = 0.91). After obtaining permission from the authors who developed the original SPQ, the SPQ-B was translated into Hindi version. The difference between the 2 versions (measured by applying both versions to a bilingual group and calculating difference with t test) was insignificant (p = 0.79). The internal consistency of the Hindi version was good (Cronbach's alpha = 0.76).
The Cambridge Neurological Inventory
The Cambridge Neurological Inventory (16) is a schedule for standardised neurological assessment of psychiatric patients. Part 2 of the Inventory is an examination for soft signs including primitive reflexes, motor coordination and repetitive sequential motor execution, as well as sensory integration. Primitive reflexes included the grasp reflex, snout reflex, and the palmomental reflex. Motor coordination and repetitive sequential motor execution were assessed with the finger-nose test, finger-thumb tapping, finger-thumb opposition, diadochokinesis, fist-edge-palm test, Oseretsky test, rhythm-tapping test, and the go/no-go test. Sensory integration was assessed via extinction, finger agnosia, stereognosis, graphesthesia, and left-right orientation.
Digit Span Test
The digit span test (17) comprised the digit forward test (a measure of attention) and the digit backward test (a measure of verbal working memory).
Paired Associate Learning Test
The paired associate learning test (18) is a subtest of the Postgraduate Institute Memory Scale. The test assesses auditory-verbal memory on indices of immediate recall and recognition. This is a cued recall test of verbal memory. The test consists of 2 series of associate pairs (5 pairs each). One is for similar pairs and another for dissimilar pairs.
Visuospatial Working Memory Matrix
The visuospatial working memory matrix (19,20) measures the capacity of a subject's visuospatial working memory. Two different components are critical to this part of memory: passive store and active imagery operation. Both are mutually independent and can be examined by this test. The test consists of ten 4 x 4 matrices, each printed on a different card in bright homogenous colours. Two consecutive squares are yellow and another one is red on a given card. In the 2-dimensional space of a card, the coloured squares are situated at a different location for each card. A stimulus was given to the subject according to a standard key for each card, and the subject was asked to move the red square's position in his/her mind and correct responses were noted.
Statistical analysis was completed using the Statistical Package for the Social Sciences, SPSS Windows version 17. An independent t test was used for group comparison. Significance (p value) and effect size (Cohen's d) for difference were calculated. A composite cognitive index was formulated by summing the weighted scores on individual scales. Weighting was done by multiplying raw scores with a component score coefficient (obtained via principal component analysis). Since the 2 groups in the study differed in education level (which was likely to affect cognitive and neurological function), two-way analysis of variance (ANOVA) was adopted to assess the effect and interaction of education level. Discriminant function analysis was conducted to assess the 2 groups on the basis of SPQ-B, NSS, and cognitive index in combination and independently. Wilks' A was calculated to determine statistical significance.
The socio-demographic profile of both groups is shown in Table 1. Subjects in both groups were all Hindu. They were predominantly married, male, had a monthly income of < 15,000 Rupees, and were living in joint families. In both groups, the majority had more than 8 years of education, though the controls had higher levels of educational attainment overall. Subjects who were first-degree relatives of the schizophrenics were mainly farmers or workers, living in rural areas, whereas the majority of the controls were professionals and lived in urban areas.
Among these first-degree relatives of the schizophrenics, 70% were relatives of patients with paranoid schizophrenia (ICD code: F20.0), and 30% were that with unspecified schizophrenia (ICD code: F20.9). Also, half were siblings, 32% the father of the patient, and 18% a son of the patient.
Group Difference in Various Vulnerability Markers First-degree relatives scored higher on all SPQ-B subscales. Differences were statistically significant for total score, as well as cognitive-perceptual and interpersonal subscale scores, with large effect sizes (Cohen's d > 0.8). The difference in group scores on the disorganisation subscale was not statistically significant (Table 2).
First-degree relatives had more NSS, with significant differences between the groups in total score, motor coordination, motor sequencing, and sensory integration. Differences in primitive reflex testing were not statistically significant. The effect size for differences was high for total score, motor coordination, and motor sequencing (Table 3).
The control group performed significantly better on all cognitive measures. The effect size was large for all except for digit span test backward. The effect size for composite cognitive index was higher (Table 4).
A two-way ANOVA was conducted to examine the effect of education level on cognitive index and total NSS. A confidence interval of 99.9% was used for analysis. Both variables were normally distributed for the groups as assessed by the Shapiro-Wilk test. There was homogeneity of variance between groups as assessed by Levene's test for equality of error variances. Interaction between the effects of group and education level was insignificant for cognitive index (F[2,74] = 1.397, p = 0.25) and total NSS (F[2,74] = 3.006, p = 0.06). Simple main effects analysis showed that first-degree relatives differed significantly from controls on cognitive index (p = 0.001) and total NSS (p < 0.001). Education level also showed significant effect on cognitive (p < 0.001) and neurological performance (p = 0.01). Two-way ANOVA for individual domains could not be conducted since assumptions for ANOVA were not met.
On conducting discriminant function analysis, SPQ-B, NSS, and cognitive index in combination were better discriminated between the first-degree relatives and the control group (Wilks' [lambda] = 0.54, [chi square] = 46.54, p < 0.001), with a canonical correlation of 0.675 (Table 5 and Fig). The SPQ-B (Wilks' A = 0.84), NSS (0.63), and cognitive index (0.72) independently showed lower discrimination between the groups. Among originally grouped subjects, 88.8% were correctly classified by a combination of these measures. The percentage was lower for individual measures, with the highest being for NSS.
The major focus of the present study was to assess multiple vulnerability markers in first-degree relatives of schizophrenic patients and the effect of their combination. First-degree relatives showed higher schizotypy scores on the SPQ-B and domains including cognitive-perceptual and interpersonal subscales. This finding indicates that schizotypy measures can successfully differentiate a population with high genetic risk (large effect size, i.e. Cohen's d > 0.8). There was not a statistically significant difference between groups on the disorganisation subscale of the SPQ-B. It is possible that due to stigma associated with psychiatric illness in our region, relatives were less likely to reveal odd symptoms/behaviour assessed on the disorganisation subscale.
Previous studies (21) reported similar findings. Kremen et al (22) showed that relatives of schizophrenic patients had higher scores on the cognitive-perceptual subscale (positive schizotypy) than the controls; a similar trend (p < 0.07) was also observed for the interpersonal subscale, but there was no main effect for disorganisation. While Yaralian et al (23) found that relatives of the schizophrenics scored significantly higher on the cognitive-perceptual subscale, Hawkins et al (24) also reported that disorganisation factor was absent in individuals who met criteria for the schizophrenia prodrome.
In contrast to the popular continuum hypothesis, Mata et al (25) suggested that schizotypy is more specific to psychotic symptoms than to schizophrenia per se, and that the clinical features of schizophrenia and schizotypy are not aetiologically continuous. Vollema and Postma (26) concluded that the positive dimensions assessed on the SPQ reflect genetic vulnerability to schizophrenia, while Calkins et al (27) found that social-interpersonal deficits were best at differentiating relatives from controls.
All NSS test results in this study were higher among first-degree relatives and the difference in motor coordination and motor sequencing showed a large effect size (Cohen's d > 0.8). Most studies (28-30) similarly reported that biological relatives of patients manifest more NSS than individuals without a family history. Ismail et al (31) reported that patients with schizophrenia and their siblings scored higher than normal controls on the soft signs total score, as well as the sensory integration and motor functioning subscales. Compton et al (32) also reported higher scores on motor coordination and integration subscales. Schubert and McNeil, (33) on the basis of a longitudinal study, suggested that familial risk for schizophrenia is associated with neurodevelopmental disturbance that is manifest throughout life and belongs to a different biological continuum from that of affective psychosis. Boks et al (34) found that only the movement disorder domain can be used to discriminate mood disorders from first-episode schizophrenia.
In a review, Bombin et al (35) found that healthy relatives of the schizophrenics showed higher overall NSS rates than healthy controls, and lower overall NSS rates than their affected relatives. Soft signs, especially those involving motor tasks, were found to be more genetically mediated. The authors (35) also suggested that motor signs appear to be less related to obstetric complications, a finding that gives further support to the hypothesis of motor signs being more intimately related to genetic vulnerability.
In contrast, Lawrie et al (36) suggested that soft signs are not an indicator of genetic risk specifically for psychosis. They suggested that soft signs and physical anomalies are non-specific markers of developmental deviance that are not mediated by genes for schizophrenia.
Performance on all cognitive domains, including attention, episodic verbal memory, as well as verbal and visuospatial working memory, was significantly poorer among first-degree relatives in our study. Differences in the composite cognitive index were also found to be significant. The cognitive index had a larger effect size (Cohen's d = -1.27) than the individual cognitive domains, providing evidence in support of a composite cognitive index. Since attention and working memory deficits have been implicated in the pathophysiology of schizophrenia, their presence in first-degree relatives suggests a substrate (probably genetically mediated) for future development of the disorder.
Several studies (37-43) and meta-analyses (44,45) demonstrated similar cognitive deficits among relatives of schizophrenic patients. Saperstein et al (46) suggested a continuum of risk for a schizophrenia-related deficit of spatial working memory, whereby a higher genetic loading for disease-related traits imparts greater cognitive impairment. In a review, Brewer et al (47) suggested that spatial working memory deficits exist prior to illness onset and may be more potent trait markers for psychosis than cognitively dense tasks, such as verbal memory.
Goldberg et al (48) suggested that neuropsychological dysfunction is a consistent feature of schizophrenia and that it is related primarily to the clinical disease process and not to genetic or non-specific environmental factors. Groom et al (49) also suggested that the cognitive measures are not specific and detect non-specific neurodevelopmental impairment.
Toomey et al (50) favoured combination of multiple cognitive risk indicators to help identify those relatives that carry the schizophrenia genotype. Neuroanatomical changes in the hippocampus, prefrontal cortex and white matter integrity, observed in relatives of patients with schizophrenia, (51-53) also lend support in favour of underlying cognitive deficits. Cannon et al (54) found that deficits in frontal lobe grey matter and associated neurocognitive functions (spatial working memory, divided attention) appear to be genetically mediated neuroendophenotypic indicators, while deficits in temporal lobe structures and associated cognitive functions (verbal episodic memory) are also influenced by non-genetic factors.
Skelley et al (55) suggested a relationship between NMDA receptor antagonists and impaired memory encoding (verbal memory) (56) and that the deficits shared by patients and their siblings may result from shared genes.
In our study, all the measures significantly differentiated first-degree relatives from the controls independently. On conducting discriminant function analysis, the combination of 3 measures (SPQ-B score, NSS, and cognitive index) was better at discriminating subjects with high risk for schizophrenia than the independent measure. This suggests that it is better to use a combination of vulnerability markers for identification of individuals at risk and probably that it could enhance specificity of identification. Although it is not possible to comment on future onset of illness from this cross-sectional data, it does appear possible to identify a person who carries a high genetic vulnerability. A longitudinal study would be required to explore the utility of these measures in the prediction of schizophrenia and to determine the proportion of people with high genetic vulnerability who develop schizophrenia.
Findings of the study must be viewed in light of its limitations. These include a small sample size, and issues of the representativeness of the sample and unmatched controls. Another limitation was the lack of patient measures. This would have allowed comment on whether there was a linear trend in scores; however, since the major focus of the present study was to assess multiple vulnerability markers and their combination, we omitted the patient group from the study. Reporting bias could have affected the SPQ-B scores, as control subjects may tend to respond defensively due to fear of detection of schizotypal phenomena. Due to time constraints, we could not apply assessment tools for anxiety and depression. Although we had excluded the presence of clinical depression and anxiety among the first-degree relatives, the possibility of subclinical anxiety and depression remained. This might have confounded the results.
To conclude, schizotypy as assessed on the SPQ-B, NSS, and neurocognition significantly differentiate first-degree relatives of schizophrenic patients, and that the combination of all 3 measures better discriminate these relatives and the controls than the individual measures alone. Further studies are needed in a larger representative sample for generalisation of these results. Longitudinal studies should also be carried out to determine the utility of these measures in the early identification of risk for schizophrenia.
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Prof. R. K. Solanki, MD, Department of Psychiatry, Sawai ManSingh Medical College, Jaipur, India.
Dr Mukesh Kr. Swami, MD, Department of Psychiatry, Sawai ManSingh Medical College, Jaipur, India.
Dr Paramjeet Singh, MD, Department of Psychiatry, Sawai ManSingh Medical College, Jaipur, India.
Dr Suresh Gupta, MD, Department of Psychiatry, Sawai ManSingh Medical College, Jaipur, India.
Address for correspondence: Dr Mukesh Kr. Swami, 53/104, V T Road, Mansarovar, Jaipur 302020, India.
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Submitted: 3 February 2012; Accepted: 24 May 2012
Table 1. Comparisons of socio-demographic profiles of the first-degree relatives and control groups. Variable First-degree Controls relatives (n = 50) (n = 30) Mean (standard deviation) 36.5 (12.1) 33.4 (9.3) age (years) Sex Male 49 (98%) 30 (100%) Female 1 (2%) - Marital status Married 42 (84%) 27 (90%) Unmarried 8 (16%) 3 (10%) Occupation Unemployed 5 (10%) 1 (3%) Retired pensioners 3 (6%) - Professionals 10 (20%) 22 (73%) Businessmen 7 (14%) - Farmer/skilled worker/semi- 25 (50%) 7 (23%) skilled worker/unskilled worker Education < 8 Years 17 (34%) 4 (13%) 8-12 Years 19 (38%) 3 (10%) Graduate/postgraduate 14 (28%) 23 (77%) Monthly income (Rupees) 0-6000 26 (52%) 6 (20%) 6001-15,000 19 (38%) 16 (53%) > 15,000 5 (10%) 8 (27%) Family type Nuclear 13 (26%) 10 (33%) Nuclear-extended 8 (16%) 7 (23%) Joint 29 (58%) 13 (43%) Locality Urban 20 (40%) 23 (77%) Rural 30 (60%) 7 (23%) Table 2. Comparison of groups on measures of schizotypy. * Measure First-degree Controls t Score relatives SPQ-B total 6.70 (4.395) 3.17 (3.312) 3.800 Cognitive-perceptual 2.32 (1.720) 0.83 (1.085) 4.249 Interpersonal 3.06 (2.064) 1.53 (1.655) 3.439 Disorganisation 1.32 (1.544) 0.80 (1.215) 1.574 Measure Degrees of p Value Effect size freedom (Cohen's d) SPQ-B total 78 < 0.001 0.88 Cognitive-perceptual 78 < 0.001 0.98 Interpersonal 78 0.001 0.80 Disorganisation 78 0.12 0.36 * Data are shown as mean (standard deviation). Abbreviation: SPQ-B total = Schizotypal Personality Questionnaire-Brief Version total score. Table 3. Comparison of groups on measures of neurological soft signs. * Measure First-degree Controls t Score relatives NSS-total 11.70 (5.003) 4.57 (3.785) 6.732 Primitive reflexes 0.06 (0.240) 0.00 (0.000) 1.366 Motor coordination 2.26 (1.805) 0.53 (1.008) 4.802 Motor sequencing 5.70 (2.573) 1.90 (2.218) 6.723 Sensory integration 3.68 (2.299) 2.13 (1.814) 3.142 Measure Degrees of p Value Effect size freedom (Cohen's d) NSS-total 78 < 0.001 1.55 Primitive reflexes 78 0.18 0.32 Motor coordination 78 < 0.001 1.11 Motor sequencing 78 < 0.001 1.55 Sensory integration 78 0.002 0.73 * Data are shown as mean (standard deviation). Abbreviation: NSS-total = Neurological soft signs total score. Table 4. Comparison of groups on measures of neurocognition. * Measure First-degree Controls t Score relatives Cognitive index 6.94 (1.83) 9.35 (1.94) -5.568 DSTF 4.32 (0.768) 5.10 (0.712) -4.519 DSTB 3.12 (0.480) 3.73 (1.230) -3.159 PALT 13.64 (4.169) 16.80 (2.511) -3.758 VSWM 2.18 (2.283) 4.83 (2.705) -4.693 Measure Degrees of p Value Effect size freedom (Cohen's d) Cognitive index 78 < 0.001 -1.27 DSTF 78 < 0.001 -1.04 DSTB 78 0.002 -0.73 PALT 78 < 0.001 -0.87 VSWM 78 < 0.001 -1.08 * Data are shown as mean (standard deviation). Abbreviations: DSTF = digit span test forward; DSTB = digit span test backward; PALT = paired associate learning test; VSWM = visuospatial working memory matrix. Table 5. Standardised canonical coefficients and structure weights from the discriminant model. Measure Standardised Structure coefficients weights SPQ-B 0.233 0.470 NSS 0.676 0.833 Cognitive index -0.475 -0.689 Abbreviations: SPQ-B = Schizotypal Personality Questionnaire-Brief Version; NSS = neurological soft signs.
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|Title Annotation:||Original Article|
|Author:||Solanki, R.K.; Swami, M.K.; Singh, P.; Gupta, S.|
|Publication:||East Asian Archives of Psychiatry|
|Date:||Sep 1, 2012|
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