Differential relationship between neurological and cognitive dysfunction in first episode psychosis patients and in healthy individuals

Schizophrenia Research 142 (2012) 159–164

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Differential relationship between neurological and cognitive dysfunction in first episode psychosis patients and in healthy individuals Zefiro Mellacqua a, 1, Joanna Eyeson a, 1, Ken D. Orr b, Kevin D. Morgan a, Jolanta Zanelli a, Tuhina Lloyd c, Craig Morgan a, Paul Fearon a, Gerard Hutchinson d, Gillian A. Doody c, Raymond C.K. Chan e, Glynn Harrison f, Peter B. Jones g, Robin M. Murray a, Abraham Reichenberg a, Paola Dazzan a,⁎ a

King's College London, Institute of Psychiatry, Department of Psychosis Studies, London, UK Sir Charles Gairdner Hospital, Department of Psychiatry, Perth, Australia c Department of Psychiatry, University of Nottingham, Nottingham, UK d University of West Indies, Department of Psychiatry, Trinidad and Tobago e Neuropsychology and Applied Cognitive Neuroscience Laboratory, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China f Academic Unit of Psychiatry, University of Bristol, Bristol, UK g University of Cambridge, Department of Psychiatry, Addenbrooke's Hospital, Cambridge, UK b

a r t i c l e

i n f o

Article history: Received 1 July 2012 Received in revised form 9 August 2012 Accepted 27 September 2012 Available online 23 October 2012 Keywords: Schizophrenia Neurological signs IQ Motor coordination Executive function First episode psychosis Healthy individuals

a b s t r a c t The minor neurological and cognitive deficits consistently reported in psychoses may reflect the same underlying brain dysfunction. Still, even in healthy individuals minor neurological abnormalities are associated with worse cognitive function. Therefore, establishing which neurological and cognitive deficits are specific to psychosis is essential to inform the pathophysiology of this disorder. We evaluated a large epidemiological sample of patients with first episode psychosis (n = 242) and a population-based sample of healthy individuals (n = 155), as part of the AESOP study. We examined neurological soft signs using the Neurological Evaluation Scale (Buchanan and Heinrichs, 1989), and generalized and specific cognitive deficits (memory; verbal abilities; attention, concentration and mental speed; executive functions and working memory; language; visual constructual/perceptual abilities). In patients, more neurological signs across all subscales were associated with worse general cognitive function, while in controls this was only present for sensory integration and sequencing signs. Furthermore, in patients, but not in healthy individuals, more sensory integrative signs were associated with deficits in specific cognitive domains, such as memory, verbal abilities, language, visual/ perceptual, executive function (p ranging b 0.001–0.002); sequencing signs with language, executive function, and attention (p b 0.001–0.004); and motor signs with poorer verbal abilities (p = 0.001). These findings indicate the presence of specific associations between neurological and cognitive deficits in psychosis that are distinct from those of healthy individuals. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Minor neurological abnormalities in sensory and motor function are more prevalent in individuals with schizophrenia and other psychoses, and with vulnerability for these disorders, than in healthy individuals (Dazzan and Murray, 2002; Dazzan et al., 2008; Chan et al., 2010). The fact that these abnormalities are associated with cognitive deficits in psychosis has suggested that both phenomena reflect the same pathophysiological process underlying psychosis (Mohr et al., 2003; Chan et al., 2009). However, this suggestion has been hindered by increasing evidence that deficits in sensory function and in the

⁎ Corresponding author at: Department of Psychosis Studies PO 40, Institute of Psychiatry, King's College London, De Crespigny Park, London SE5 8AF, UK. Tel.: +44 207 848 0590; fax: +44 207 848 0287. E-mail address: [email protected] (P. Dazzan). 1 These authors contributed equally as first authors. 0920-9964/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.schres.2012.09.016

execution of complex motor sequences are associated with worse cognitive ability also in healthy individuals (Keshavan et al., 2003; Bombin et al., 2005; Dazzan et al., 2008). Furthermore, work by our group has shown that, once differences in general cognitive ability are taken into account, some minor neurological abnormalities are no longer more prevalent in patients than in controls (for example, the excess of sensory integrative deficits) (Dazzan et al., 2008). Therefore, it remains to be established which neurological and cognitive deficits co-occur in the affected and general population, and which may be specific to the pathophysiology of psychosis and could potentially inform patient stratification in psychiatry. Evidence that neurological signs (particularly motor) and neurocognitive deficits are associated in patients with psychosis suggests that at least some of these deficits represent features of the same illness dimension, reflective of the same neurobiological process (Ho et al., 2004; Tosato and Dazzan, 2005; Sewell et al., 2010). In support of this view, evidence from our and other groups proposes that

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different neurological abnormalities may have different origins. For example, sensory integrative deficits seem to share the same neuroanatomical correlates in both patients with psychosis and controls, that is, frontal and temporal lobe reductions (Dazzan et al., 2004, 2005). In contrast, motor coordination deficits appear associated with a reduction of the basal ganglia, but only in patients (Keshavan et al., 2003; Dazzan et al., 2005), suggesting that they may be indeed specifically associated with the pathogenesis of this illness. Establishing which neurological and cognitive dysfunctions are associated in schizophrenia and other psychoses as part of a construct specific to the illness, and which are independent of psychosis and occur together also in healthy individuals, has important implications for our understanding of the pathogenesis and nosology of psychoses. Unfortunately, previous studies evaluating neurological and neurocognitive functions simultaneously have mostly used relatively small samples, of individuals with schizophrenia rather than any psychosis, and with long illness duration, and have not evaluated multiple cognitive domains. Furthermore, most studies did not investigate the relationship between neurological and cognitive function separately in clinical and normal populations, an essential step to identify any cognitive and neurological abnormality specific to psychosis. In this study, we evaluated neurological signs and general and specific cognitive functions in a large epidemiological sample of patients with a first episode of any psychosis, and a large, population-based sample of healthy individuals, part of the AESOP study (Aetiology and Ethnicity in Schizophrenia and Other Psychoses) (Dazzan et al., 2008). To our knowledge, this is the largest existing epidemiological first-episode psychosis cohort in which both neurological and neuropsychological functions have been tested. Evaluating patients at their first episode limits the potential confounding effects of illness severity, progression, or long-term exposure to antipsychotic drugs. Furthermore, this is the first existing study using a large population-based comparison group, reflective of average cognitive and neurological functions. On the basis of our previous work and existing literature, we predicted that: (a) more neurological problems in sensory integration and motor sequencing would be associated with deficits in cognitive domains that rely on the integration within or between the motor and sensory systems, in both patients with psychosis and healthy individuals; (b) motor coordination signs would be present in excess in psychosis, and would only be associated with deficits in motor cognitive domain, to reflect a specific feature of psychosis.

were also assessed to establish the presence or otherwise of a psychotic illness, and excluded if necessary. A neurological evaluation was completed on 310 individuals with first-episode psychosis and 239 healthy individuals. Of these, 242 patients and 155 healthy individuals also completed the neuropsychology testing. Demographic and clinical characteristics are presented in Table 1. All analyses were conducted “within-group”, that is, withinpatients or within-healthy individuals. Details of the neurological and neurocognitive function of the main patient and healthy individual samples, and between-group differences, have been reported elsewhere (Dazzan et al., 2008; Zanelli et al., 2010). 2.2. Neurological assessment We assessed neurological function as soon as possible after initial presentation, with an expanded, previously validated version of the Neurological Evaluation Scale (NES) (Buchanan and Heinrichs, 1989; Griffiths et al., 1998). This version consists of four subscales reflecting different functional areas and showing good construct validity (Buchanan and Heinrichs, 1989; Sanders et al., 2000): (i) ‘Primary neurological dysfunction’ (dysfunction that can be identified by a standard neurological examination), including cranial nerves, eye movement, lateralizing limb pyramidal signs and frontal release signs; (ii) ‘Sensory integration dysfunction’ (dysfunction in the integration of sensory information), including right/left confusion, astereognosis, agraphaesthesia and audiovisual integration; (iii) ‘Motor coordination dysfunction’ (reflects signs of motor incoordination), including tandem walk, dysdiadochokinesis and the finger-to-nose test; (iv) ‘Motor sequencing dysfunction’ (reflects the ability to perform complex motor sequences), including fist-ring and the fist-edge-palm tests. We administered the schedule in a standardized manner, and according to a fixed order. The scores for the items present in the original NES (included in the three subscales sensory integration, motor coordination and motor sequencing) (Buchanan and Heinrichs, 1989) were left unchanged (from 0= no abnormality to 2 =marked impairment, except for the snout and suck reflexes, scored as either 0 or 2). The remaining items (in the primary signs subscale), were scored as 0= no abnormality; 1= intermediate criterion; 2 =clearly abnormal/marked impairment (Griffiths et al., 1998). Assessment of NSS was always performed blind to diagnosis. Inter-rater reliability showed agreement rates r ranging 0.87–0.96. We have previously reported, consistently with the literature, that neurological performance can be affected by age (Dazzan et al., 2008).

2. Material and methods 2.1. Sample Individuals aged 16–64 years who consecutively presented to local psychiatric services with a first episode of a functional psychotic illness were approached (see Dazzan et al., 2004 for details). Ethical approval was granted by the local Ethical Committee, and all participants gave written consent. Inclusion criteria were: (a) no organic medical cause or profound intellectual disability; (b) no history of head trauma resulting in loss of consciousness > 1 h; (c) presence of a functional psychotic illness (ICD-10 F10-19, excluding coding F1x.0 for Acute intoxication; F20-29 and F30-39, psychosis codings) (World Health Organisation, 1992a); (d) no previous contact with services for psychotic symptoms. Subjects with poor fluency in English or a disease of the central nervous system, were excluded. Healthy individuals, aged 16–64 years, were also recruited from the study areas using household visits, local press and hospital advertisements (Dazzan et al., 2008), using a sampling procedure adapted from the one used by the Office of Population and Census Statistics Psychiatric Morbidity Survey. The Psychosis Screening Questionnaire (Bebbington and Nayani, 1995) was used to screen for the presence of psychotic symptoms. Subjects who rated positive for psychosis

Table 1 Demographic and clinical characteristics of the samples.

Gender (male, n (%)) Age (mean (SD)) Age group (n (%)) b22 years 22–35 years >35 years Ethnicity (n (%)) White British Black and Minority Ethnic Diagnosis (n (%)) Schizophrenia Affective psychoses Other psychosis Duration of untreated psychosis (mean weeks (SD)) Estimated premorbid IQ (NART score mean (SD)) Estimated current IQ (WAIS-R score mean (SD))

Patients n= 242

Healthy individuals n = 155

p

141 (58.3) 30.4 (10.8)

66 (42.6) 36.8 (12.8)

0.002 b0.001

71 (29.3) 104 (43.0) 67 (27.7)

21 (13.5) 61 (39.4) 73 (47.1)

120 (49.6) 122 (50.4)

97 (62.6) 58 (37.4)

– – – 0.01 – –

118 82 41 55.3

– – – –

– – – –

97.5 (14)

106.2 (9)

b0.01

90.6 (17)

105.2 (15)

b0.01

(49.0) (34.0) (17.0) (151.9)

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‘animals’), and Letter Fluency (letters F, A, S); 5) Visual–Spatial perception and organisation were assessed using set A of Raven's Coloured Progressive Matrices (Raven, 1974) and the WAIS-R Block Design (Wechsler, 1981); and 6) WAIS-R Academic verbal abilities were assessed by the WAIS-R Vocabulary and Comprehension sub tests (Wechsler, 1981). Premorbid intelligence was estimated using the National Adult Reading Test (NART) (Nelson and Willison, 1991). Current full-scale IQ was derived from the WAIS-R (Wechsler, 1981). All tests were administered and scored by specially trained researchers. A regression-based approach was used to create normative standards for the neuropsychological tests (Zanelli et al., 2010). Age, gender, ethnicity, and education were regressed on each of the neuropsychological measures in the healthy comparison sample. Next, scores were adjusted on the basis of the regression results. The regression-corrected scores were also inspected for skewness and kurtosis. Only the Raven's Colored Progressive Matrices and Trail Making Test, Part A and Part B, had significant skewness, and these variables were log-transformed before standardization. The same adjustment and standardization procedure was applied to the patients, using the normative standards from the healthy group. We only included in the neuropsychological analysis cases and healthy individuals who were native speakers of English or had migrated to the United Kingdom by age 11, to ensure that all participants had a good command of English, even as a non-native language, since all would have completed at least their secondary education in the United Kingdom, thus minimizing the effect of linguistic or cultural biases on the performance of a multiethnic sample. Subjects with missing data for more than three neuropsychological measures were excluded, and therefore degrees of freedom varied slightly.

Table 2 Percentiles of neurological signs scores across different age groups, in patients with first episode psychosis and healthy individuals. Percentiles of neurological signs Scores across age groups b22 years (25th/50th/75th)

22–35 years (25th/50th/75th)

>35 years (25th/50th/75th)

Patients Primary Sensory integrative Motor coordination Motor sequencing

1/4/6 0/1/2 0/1/3 0/2/5

0/2/4 0/1/2 0/1/2 0/1/4

0/2/6 0/1/2 0/1/3 0/2/5

Healthy individuals Primary Sensory integrative Motor coordination Motor sequencing

0/1/3.5 0/1/2 0/0/0 0/1/2.5

0/1/2 0/1/2 0/0/0 0/1/2

0/1/3 0/1/2 0/0/1 1/2/3

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More specifically, we found that an older age is correlated with higher sensory integration and motor sequencing scores in the healthy controls, while in the psychosis group, older age is additionally associated with higher motor coordination and total neurological signs scores. In view of this, for this analysis we divided participants into three age groups: b 22 years, 22–35 and > 35 years. For each age group, we calculated quartiles for performance at each of NSS subscales, separately for patients and healthy individuals (values for each group shown in Table 2). Based on the quartile scores, participants were allocated to one of three neurological performance groups: “High” level of impairment (75th percentile and above); “Intermediate” level of impairment (25th to 75th percentile); and “Low” level of impairment (25th percentile and below).

2.4. Diagnostic assessment 2.3. Neuropsychological assessment Clinical data were collected from clinical interview, case note review, and informants using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN) (World Health Organisation, 1992b). We made consensus diagnoses according to ICD-10 criteria (World Health Organisation, 1992a). Interrater and intercentre reliability for diagnosis was high (80% agreement on diagnostic category; kappa values ranging from 0.63 to 0.75).

Sixteen neuropsychological measures were selected to assess six domains (Table 3) (Zanelli et al., 2010): 1) Memory–verbal (shortterm verbal immediate recall and delayed verbal recall) was assessed using trials 1–5, 6 and 7, respectively, of the Rey Auditory Verbal Learning Test (RAVLT) (Spreen and Strauss, 1991); and Memory–visual (immediate and delayed recall) was examined using Visual Reproduction of the Wechsler Memory Scale — Revised (WMS-R) (Wechsler, 1945); 2) Executive functions and working memory were evaluated using the Trail Making Test — part B (Reitan, 1979), Letter–Number Span (Gold et al., 1997), and Sets AB and B of Raven's Coloured Progressive Matrices (CPM) (Raven, 1974); 3) Attention, concentration and processing speed were measured using Trail Making — part A (Reitan, 1979) and the WAIS-R Digit Symbol subtest (Wechsler, 1981); 4) Language was evaluated using the Semantic Fluency (categories ‘body parts’, ‘fruits’ and

2.5. Statistical analysis We used One-way ANOVA tests with NSS performance (“Low”, “Intermediate” or “High” level of impairment) at each subscale as the independent variable, and the neuropsychology residual scores of each domain as the dependent variable. A corrected significance level for these comparisons was set at p ≤ 0.007 (0.05/7, to correct

Table 3 Proportion of subjects with different levels of neurological impairment (defined according to percentiles) and current IQ. Low/Intermediate/High neurological impairment⁎

Full scale IQ (Mean; SD)

% of subjects in each group

Low

F; df; p Some

Patients Primary Sensory integrative Motor coordination Motor sequencing

30/48/22 52/34/14 39/39/22 39/42/19

95.3 95.1 94.7 94.1

(18) (18) (16) (17)

Healthy individuals Primary Sensory integrative Motor coordination Motor sequencing

37/41/22 47/37/16 77/8/15 46/34/20

105.4 107.6 105.8 107.5

(15) (15) (16) (15)

High

89.6 (15) 88.9 (15) 88.9 (16) 89.5 (16)

106.4 104.9 110.2 105.9

(16) (14) (18) (14)

86.4 78.5 86.7 85.9

(17) (7) (16) (16)

235; 235; 235; 235;

4.8; 0.009 16.1; b0.001 5; 0.008 4.1; 0.02

102.3 98.6 99.5 99.1

(14) (15) (12) (15)

151; 151; 151; 151;

.8; NS 3.3; 0.04 2.5; NS 3.5; 0.03

⁎ Levels of neurological impairment: “Low” level of impairment is below 25th percentile; “Intermediate” level of impairment is between the 25th and the 75th percentile; “High” level of impairment is above 75th percentile; SD = standard deviation; NS = not significant.

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for the six specific and the general neuropsychological domains). When ANOVA models showed a statistically significant overall group difference, we examined the functional form of the relationship. All tests were performed in SPSS 19.0. 3. Results We first evaluated general cognitive performance across the 3 age groups of patients and healthy individuals with varying levels of neurological impairment. Neurological performance across age groups, and current IQ values are presented in Table 2. Here, we present the 25th and 75th percentiles of the NSS score for each NES subscale and for each age group (labelled “Neurological Signs score across age groups”). Based on these percentiles, we allocated each subject (patient or healthy individual) to a level of neurological impairment (“Low”, “Intermediate”, “High”). The percentage of subjects falling in each of these three categories is presented in the column “Low/ Intermediate/High neurological impairment”. Finally, we compared general cognitive performance across these Low, Intermediate and High neurological impairment groups (columns labelled “Full scale IQ”). We found that, in patients, more primary, sensory integrative, motor coordination, and motor sequencing signs, were significantly associated with lower IQ (p values ranging b0.001–0.02). In healthy individuals, only more sensory integrative and motor sequencing signs were associated with lower IQ (p values ranging 0.03–0.04).

between more motor sequencing signs and poorer attention, the linear trend analysis for language and executive functions did not reach statistical significance (p = 0.09). There were no significant associations between motor sequencing signs and memory, academic verbal and visual/perceptual tasks (Table 3). We considered whether potential differences in neurological performance across groups with Low, Intermediate, and High level of impairment in each neurological subscale were due to differences in antipsychotic medications. We therefore compared the type of antipsychotic taken in the 2 weeks prior to the neurological evaluation across the 3 groups. We found no between-group differences in the proportion of antipsychotic-naïve or drug-free subjects, or of subjects taking typical or atypical antipsychotic or both. This makes it unlikely that the different neurological performance was due to differences in antipsychotic treatment received. 3.2. Neurological function and cognitive domains in healthy individuals In healthy participants, the presence of primary signs was not associated with performance in any cognitive domain. There was also no association between sensory integrative signs and performance in any cognitive domain. Similarly, the performances for motor coordination signs and motor sequencing signs were not associated with performance in any cognitive domain (correction at p b 0.007). These data are therefore not shown. 4. Discussion

3.1. Neurological function and cognitive domains in patients with psychosis This analysis shows that the presence of primary signs was not associated with performance in any cognitive domain. However, having more sensory integrative signs was associated with poorer performance across most neurocognitive domains: memory, academic verbal, language, visual/perceptual, executive function (p values ranging b0.001–0.002) (Table 3). There was a significant positive linear trend in the relationship between sensory integrative performance and all cognitive domains, indicating that the higher the impairment in sensory integration, the poorer the neurocognitive performance in these domains (Table 4). Having more motor coordination signs was also associated with a poorer performance on academic verbal abilities (F = 7.35, df = 200, p = 0.001), with a significant linear trend (Table 3). There was no association between motor coordination signs and performance on memory, language, visual/perceptual, attention and executive function tasks. Finally, more motor sequencing signs were associated with poorer performance on language, executive function, and attention (p values ranging b0.001–0.004). While there was a significant linear trend

This is, to our knowledge, the first study that has evaluated neuropsychological and neurological functions in a large epidemiological cohort of patients at their first episode of any psychoses, in comparison to a population-based sample of healthy individuals. We have found a specific relationship between neurological abnormalities and cognitive function, different in patients and in healthy individuals. While in patients more neurological signs in all subscales were associated with a worse general cognitive function, in healthy individuals this was the case only for sensory integration and sequencing signs. Furthermore, in patients, but not in healthy individuals, more sensory integrative and motor sequencing signs were also associated with deficits in several cognitive domains. It is interesting that more sensory integrative and motor sequencing signs were associated with worse general intellectual function in both patients and healthy individuals. This is consistent with our previous analysis of this sample, showing that differences in these signs between patients and healthy individuals disappear when general intellectual function is taken into account (Dazzan et al., 2008). This would indicate that, independently from the presence of psychosis,

Table 4 Neurocognitive performance (means of residual scores and standard deviation) across different levels of impairment in NSS subscales (Low, Intermediate, High) in patients with first episode psychosis. Low

Intermediate

High

ANOVA

p (η2 effect size)⁎

Linear trend

Sensory integrative Memory Verbal abilities Language Visual/perceptual Executive function

−1.7 (4.1) −0.2 (7.7) −2.9 (7.6) −2.8 (7.2) −0.8 (1.5)

−3.2 (4.5) −3.5 (8.9) −6.1 (7.7) −4.2 (6.1) −1.2 (1.7)

−5.2 (4.5) −10.1 (9.2) −10.5 (8.1) −7.6 (5.1) −2.1 (1.7)

F = 7.73 F = 17.0 F = 10.9 F = 6.6 F = 7.0

0.001; 0.07 b0.001; 0.14 b0.001; 0.11 0.002; 0.06 0.001; 0.07

F = 15.4 F = 32.4 F = 21.7 F = 12.2 F = 13.4

b0.001 b0.001 b0.001 0.001 b0.001

Motor coordination Verbal abilities

0.03 (8.1)

−3.8 (9.4)

9.4 (8.6)

F = 7.3

0.001;0.07

F = 14.1

b0.001

Motor sequencing Language Attention Executive function

−2.8 (7.6) −0.1 (0.2) −0.6 (1.3)

−5.2 (7.5) −0.1 (0.2) −1.1 (1.7)

−9.6 (8.8) −0.2 (0.2) −2.1 (1.7)

F = 8.4 F = 5.6 F = 12.5

b0.001; 0.16 0.004; 0.55 b0.001; 0.1

F = 2.3 F = 7.7 F = 2.9

⁎ Eta squared: 0.0099 constitutes a small effect, 0.0588 a medium effect and 0.1379 a large effect.

0.09 0.006 0.09

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general intellectual ability affects the integration of sensory data (Doody et al., 1998). However, in patients, but not in controls, these signs were also associated with worse performance in multiple specific cognitive domains. Therefore, specific cognitive domains may become affected only when a significant disintegration of intellectual function is present, such as the one observed in psychosis. Sensory integrative tasks test the ability to interpret information from different sensory modalities coherently and interchangeably. Neuroimaging studies from ours and other groups have found that more sensory integrative signs are associated with distributed reductions of cortical parietal, frontal, and temporal association areas (Keshavan et al., 2003; Dazzan et al., 2004; Thomann et al., 2009). These areas play a critical role in supporting complex, widely distributed cognitive functions. Indeed, in patients but not in healthy individuals, more sensory integration signs were associated with poorer memory, verbal abilities, executive function and visual perceptual skills, which all require the processing and integration of multiple sensory stimuli. This is consistent with existing evidence from individuals in more advanced illness stages that, in psychosis, sensory integrative signs are associated with more cognitive measures that any other NSS subset, and thus may share the same underlying biological basis (Arango et al., 1999; Sewell et al., 2010). Motor sequencing signs were also associated with specific deficits in language, attention and executive function, in patients but not in controls. This may reflect a common underlying prefrontal dysfunction (Bombin et al., 2005). In fact, the test we included in the executive and language domains was a verbal fluency task, which is in itself an executive task. The Trail Making test, which is also part of the attention domain, is a planning task, and therefore affected by prefrontal function. Furthermore, specific motor sequencing signs, such as the fist-edge-palm, can also be considered frontal lobe signs, in line with the original description by Luria and supported by recent functional imaging studies (Chan et al., 2006; Rao et al., 2008). Evidence supporting a role of frontal dysfunction also comes from the finding that, in patients, motor coordination signs were associated with worse academic verbal performance. Motor abnormalities are a consistent finding in schizophrenia, and their presence has been linked to pathophysiological changes in the basal ganglia and the cerebellum (Dazzan et al., 2004; Pappa and Dazzan, 2009). Interestingly, these same structures are also involved in verbal impairments, and their association with motor signs provides further support for the hypothesis of a disrupted cortico-cerebellar-thalamic-cortical circuit in schizophrenia (Ho et al., 2004; Whitty et al., 2009). Perhaps not surprisingly, primary signs were not associated with any specific cognitive function, in either patients or healthy individuals. Primary signs (such as primitive reflexes, abnormal eye movements) indicate a dysfunction that can be identified by a standard neurological examination. This finding is consistent with our previous report that primary signs are present in excess in patients with psychosis independently from IQ, and with evidence that frontal release and eye movement signs are present in excess even in patients with a high IQ (Arango et al., 1999; Dazzan et al., 2008). A few limitations of our study should be discussed. We considered whether differences in the demographic composition of the samples, such as older age (seen in the healthy individuals) had affected some of our findings of an association between neurological and cognitive performance. However, this possibility is unlikely since all analyses were conducted separately for patients and healthy individuals, neurological performance was estimated separately within age groups, and neurocognitive function was evaluated using residuals corrected for age, gender and education. We have also considered whether differences in substance use in patients and controls could have affected cognitive and neurological performance. However, in this sample we have previously found no differences in cognitive performance between patients who abuse substances and those who do not (Donoghue et al., 2012; Mazzoncini et al., 2010). Furthermore, a

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recent literature review suggests that in fact patients who use cannabis have even lower scores of neurological signs than those who do not use this drug (Ruiz-Veguilla et al., 2009). This evidence suggests that it is unlikely that the association we observed between neurological and cognitive performance in the patient sample and not in the healthy individuals is due to a higher representation of subjects who abuse substances in the patient group. Our results suggest a shared substrate for integrative neurological dysfunction and specific cognitive impairments in memory, executive functions, language, attention, verbal abilities, in psychosis. Since these impairments have been proposed as markers of poorer response to treatment and outcome (Ho et al., 2004), a targeted assessment of these areas may be helpful for patient stratification in psychiatry. Medicine stratification refers to the use of genetic or endophenotypic measures that can potentially allow better targeting of treatments. While stratification has been effectively developed in other medical specialties, it lags behind in psychiatry, perhaps because no single genetic or endophenotypic measure has been identified to indicate, for example, which patients might benefit of a certain antipsychotic drug or of a more assertive treatment intervention. We have recently provided preliminary evidence that, already at the first episode of psychosis, is possible to use brain structure data to predict, with significant accuracy, how likely a single individual is to develop a poorer outcome (Mourao-Miranda et al., 2011). The quantification of this risk could improve and be refined if other risk factors are included into a decision-tree, and we propose that these factors may include endophenotypic measures specific to psychosis such as the neurological and cognitive impairments identified in this study. Role of funding source This study was funded by the UK Medical Research Council. We thank the Stanley Medical Research Institute for their support. Paola Dazzan's research is supported by NARSAD and the BIAL Foundation. Raymond Chan is supported by grants from the National Science Fund China Young Investigator Award (81088001), the Knowledge Innovation Project of the Chinese Academy of Sciences (KSCX2-EW-J-8), and the Key Laboratory of Mental Health, Institute of psychology. Contributors Z. Mellacqua and J. Eyeson analysed the data and prepared the first version of the manuscript; K. Orr, K. Morgan, J. Zanelli, T. Lloyd, C. Morgan, P. Fearon, and G. Hutchinson were involved in recruitment and manuscript preparation; G. Doody, G. Harrison, P. Jones, R. Murray supervised the AESOP study and contributed to manuscript preparation; R. Chan and A. Reichenberg contributed to data analysis and interpretation and manuscript preparation; P. Dazzan was involved in recruitment, data analysis and interpretation, manuscript preparation and supervision of the primary authors. Conflict of interest The authors report no competing interests. Acknowledgements We wish to acknowledge the contributions of the entire AESOP study team, listed on line at http://www.psychiatry.cam.ac.uk/aesop.

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