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Neurocognition in schizophrenia: From prodrome to multi-episode illness
Psychiatry Research 220 (2014) 129–134
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Neurocognition in schizophrenia: From prodrome to multi-episode illness Valentina Corigliano a,n, Antonella De Carolis b, Giada Trovini a, Julia Dehning a, Simone Di Pietro a, Martina Curto a, Nicole Donato b, Eleonora De Pisa a, Paolo Girardi a, Anna Comparelli a a NESMOS Department (Neurosciences, Mental Health and Sense Organs) Unit of Psychiatry, Sant'Andrea Hospital, School of Medicine and Psychology, Sapienza University of Rome, Italy b NESMOS Department (Neurosciences, Mental Health and Sense Organs) Unit of Neurology, Sant'Andrea Hospital, School of Medicine and Psychology, Sapienza University of Rome, Italy
art ic l e i nf o
a b s t r a c t
Article history: Received 12 November 2013 Received in revised form 24 June 2014 Accepted 27 July 2014 Available online 6 August 2014
Individuals with schizophrenia present a neuropsychological deficit throughout the course of the disorder. Few studies have addressed the progression of the deficit since the prodromal phase of the disorder. This investigation explored neurocognition in accordance with the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus recommendations. The aim of the study was to explore the presence of neurocognitive impairment in ultra-high-risk individuals and the stage of this impairment in samples at different phases of illness. Thirty-six individuals with a prodromal syndrome, 53 first-episode and 44 multi-episode schizophrenia patients were assessed to examine neuropsychological performance. ANCOVA analysis adjusted for possible confounder factors and planned contrasts with healthy controls were undertaken. The results revealed deficits in speed-ofprocessing, visual-learning and social-cognition in prodromal individuals, and of all other neuropsychological domains in both first-episode and multi-episode patients. Furthermore impairment was found in the first-episode and in the multi-episode group, respectively on working-memory and attention. Within the framework of the neurodevelopmental model of schizophrenia, our results suggest the presence of neuropsychological impairment before the onset of full-blown psychosis. Moreover, the deficits are larger in the more chronic groups, according to the theory of an ongoing neurodevelopmental alteration. & 2014 Elsevier Ireland Ltd. All rights reserved.
Keywords: Neurocognitive impairment First-episode schizophrenia Ultra-high risk MATRICS Neurodevelopmental model Early psychosis
1. Introduction Substantial neuropsychological deficits, first described by Kraepelin (1919) and Bleuler (1950), have subsequently been observed in all phases of schizophrenia, beginning in the premorbid period and continuing throughout life. The most prominent of these deficits concern memory, attention, working memory, problem solving, processing speed, and social cognition (Nuechterlein et al., 2004). These impairments exist prior to the initiation of antipsychotic treatment (Saykin et al., 1994) and are not caused by positive psychotic symptoms in patients who are able to complete cognitive testing, which represent the overwhelming majority of patients (Keefe et al., 2006). The various
n Corresponding author at: Valentina Corigliano, NESMOS Department, Sapienza University, School of Medicine and Psychology, Sant'Andrea Hospital, Via di Grottarossa 1035-1039, 00189 Rome, Italy. Tel.: þ39 06 33775664, þ 39 06 33775951; fax: þ39 06 33775399. E-mail address: [email protected] (V. Corigliano).
http://dx.doi.org/10.1016/j.psychres.2014.07.067 0165-1781/& 2014 Elsevier Ireland Ltd. All rights reserved.
cognitive deficits in schizophrenia have all been shown to be associated with worse functional outcomes such as difficulty with community functioning, difficulty with instrumental and problemsolving skills, reduced success in psychosocial rehabilitation programs (Green et al., 2000) and the inability to maintain successful employment (Bryson and Bell, 2003). In fact, cognitive deficits are better able to explain important functional outcomes, such as work performance and independent living (Harvey et al., 1998) than positive or negative symptoms. The significant finding of premorbid neuropsychological impairment indicates that these measures may have utility as predictors of schizophrenia (Koutsouleris et al., 2012a). Over the past 5 years, several research groups have published studies of neuropsychological functioning in ultra-high risk (UHR) groups for impending psychosis (Fusar-Poli et al., 2012). Findings from crosssectional UHR studies have consistently documented that neuropsychological deficits are intermediate between control and first episode psychosis samples (Seidman et al., 2010), and one has shown that neuropsychological functioning is related to illness
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course (Niendam et al., 2007). Several specific deficits have been observed, most reliably in visual (Wood et al., 2003) and verbal memory (Lencz et al., 2006), in working memory (Pflueger et al., 2007) and attention (Francey et al., 2005). Some deficits (e.g., in sustained attention) may represent stable vulnerability markers while others (such as verbal memory, working memory, processing speed and verbal IQ) may be predictors for conversion to psychosis (Lencz et al., 2006). Patients in the first psychotic episode and during chronic periods manifest large neuropsychological impairments involving verbal memory, attention, processing speed and executive functioning (Nuechterlein et al., 2004), with effect sizes (ES) averaging approximately 1.0 (Heinrichs and Zakzanis, 1998; MesholamGately et al., 2009). The degree of impairment depends on the domain measured, with verbal memory and processing speed typically showing the largest deficits (ES¼ 1.3–1.6 using Cohen's d) (Heinrichs and Zakzanis, 1998; Mesholam-Gately et al., 2009). Although these impairments appear relatively stable during the course of the illness (Rund, 1998), there is also evidence of further widespread neurodegenerative progress (Harvey, 2001) or cognitive decline in selected domains (Eberhard and Riley, 2003; Seidman et al., 2003). The primary aim of this study is to characterize the neuropsychology of the psychosis prodrome using a neurocognitive battery exploring seven cognitive domains (processing speed, verbal learning, working memory, reasoning and problem solving, visual learning, attention/vigilance, and social cognition) recommended by the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) committee (Kern et al., 2008; Nuechterlein et al., 2008) in order to assess differences between subjects who met criteria for a prodromal syndrome and healthy control subjects. Neurocognitive deficits in “at risk” individuals may serve as a marker of risk, whereas the trend analysis of the deficit may help us to differentiate whether the deficit is a vulnerability or severity index. Since neuropsychological functions are important predictors of functioning in schizophrenia, these cognitive deficits have considerable relevance regarding prognosis and are feasible targets for psychopharmacological interventions (Hyman and Fenton, 2003). The secondary aim of our study is to compare the neuropsychological performance in three phases of the illness. Our hypotheses are that subjects experiencing their first episode of the illness are more impaired than UHR and that they have an intermediate level of performance between UHR and multi-episode subjects. To our knowledge, this is the first study exploring neurocognition in three phases of the illness using a neuropsychological assessment made according to the MATRICS Consensus recommendations.
current drug abuse. Of the 196 subjects initially screened, 48 were excluded for current substance abuse and 15 presented severe medical conditions or neurological disease. UHR patients were free of antipsychotic medication, while FES and MES were receiving atypical antipsychotic medication at the time of the assessment. According to Gardner et al. (2010), mean daily dose for antipsychotic medication in olanzapine equivalents was 18.4 mg (DS¼ 0.4) in recent onset psychosis and 16.9 mg (DS ¼0.8) in chronic psychosis, with no significant difference between the two dosages (T 2.63, d.f. ¼ 95, p 40.05). There was no change in the antipsychotic medication dosage over the 4 weeks prior to the study. Thirty healthy volunteers were recruited as controls in the same catchment area. None had prior history of psychiatric disease, mental retardation, neurological or general medical illnesses, including substance dependence, as determined by using an abbreviated version of the Comprehensive Assessment of Symptoms and History (CASH) (Andreasen et al., 1992). The absence of psychosis in first-degree relatives was confirmed by controlling clinical records and family interviews. All participants provided free, informed consent for participating in the study and for the publication of results. The research was approved by the hospital's Ethical Committee.
2.2. Assessments 2.2.1. Psychopathology Data on socio-demographic and psychopathological variables were collected at clinical interview. Criteria for a prodromal syndrome were determined using the validated Italian version of the Scale of Prodromal Symptoms (SOPS) (Comparelli et al., 2011), which consists of 19 items in four symptom domains: positive, negative, general and disorganized. Mean SOPS positive score was 7.7 (S.D. ¼4.3), mean SOPS negative score was 10.1 (S.D. ¼6.5), mean SOPS disorganization score was 6.0 (S.D.¼3.1) and mean SOPS general score was 8.1 (S.D. ¼4.1). The raters (A.C. and V.C.) are expert clinicians trained in the administration of the SIPS/SOPS. Cohen's κ for inter-rater reliability was 0.91 (p o 0.0001). Psychopathology was assessed with the Positive and Negative Syndrome Scale (PANSS) (Kay et al., 1987). For statistical analysis we also used the depressive (items G2-anxiety, G3-guilt feelings and G6-depression), the negative (items N1-blunted affect, N2-emotional withdrawal, N3-poor rapport, N4-passive withdrawal, N6-lack of spontaneity, G7-motor retardation, G16-active social avoidance), and the cognitive/disorganized (items N5-difficulty in abstract thinking, N7-stereotyped thinking, P2-conceptual disorganization, G10-disorientation and G11-poor attention) PANSS factors extracted by Lykouras et al. (2000). Current IQ was estimated through Raven's Standard Progressive Matrices (Raven, 2008).
2.2.2. Neuropsychological measures Neuropsychological assessment was conducted according to the ‘Measurement and Treatment Research to improve Cognition in Schizophrenia’ (Nuechterlein et al., 2008) Consensus recommendations, including the exploration of seven domains, which are speed of processing, sustained attention/vigilance, working memory, verbal learning, visual learning, reasoning/problem-solving and social cognition. To maximize cooperation and avoid acute effects of psychotic symptoms, the neurocognitive battery was administered after clinical stabilization of acute psychotic symptoms in the case of the FES and the MES groups, with a median time from admission to neuropsychological assessment of 4 weeks (range: 17–35 days) and, in any case, after hospital discharge. The tests used and the parameters considered for each domain are described in Table 1.
2.3. Statistical analysis
2. Methods 2.1. Subjects We enrolled 196 male and female patients aged 18 and older who were referred to our Acute Psychiatric Care Department or to our outpatient clinic. Thirty-six participants met psychosis risk syndrome criteria (McGlashan et al., 2010), i.e. Attenuated Psychotic Symptoms (APS), Brief Intermittent Psychotic Symptoms (BIPS) or functional decline and family history of schizophrenia (Genetic Risk and Deterioration, GRD). Ninety-seven patients met the diagnosis of DSM-IV schizophrenia or schizophreniform disorder based on the Structured Interview for DSM-IV Disorders-I (SCID-I) (First et al., 1996). Within this group, 53 patients were experiencing their first psychotic episode, with a very recent onset. Forty-four had an established diagnosis of schizophrenia with multiple-episode history. Exclusion criteria were (1) impaired vision (i.e., blurred or less than 20/40 vision with correction) and impaired auditory acuity (2) current or past comorbid diagnosis of autistic disorder or other pervasive developmental disorder, (3) history of severe head injury, (4) severe medical conditions or major neurological disorders, including mental retardation and dementia, which could prevent neuropsychological task performance or that could produce psychotic symptoms, and (5) any
For all groups, we calculated means and standard deviations of demographic, psychopathological (PANSS factors) and IQ measures. As some cognitive domains have been explored using more than one neuropsychological test, we calculated standardized z-scores to obtain a single score for each cognitive domain. The z-scores were computed using means and standard deviations (S.D.s) based on all participants but segregated by task. Then, we analyzed differences in sociodemographic, IQ, clinical features and neuropsychological performance among the three clinical subgroups (UHR, FES, and MES) and the healthy control group using one-way ANOVA and post-hoc analysis according to Bonferroni or Tahmane, whenever homogeneity of variance could not be assumed. To evaluate the possible confounding role of depressive, negative and disorganized/cognitive symptoms, we also carried out a one-way ANOVA analysis with the Depressive, the Negative and the Disorganized/Cognitive PANSS factors. A student's T-test was used to compare differences in antipsychotic dosages in FES and MES. Subsequent ANCOVA with adjustments for socio-demographic and clinical variables that differed significantly among groups according to the one-way ANOVA was computed to compare the neuropsychological measures in the UHR, FES, MES and healthy control (HC) groups. Planned simple comparisons were made for each of the UHR, FES and MES groups to the control group. We calculated effect sizes by dividing the adjusted mean difference from the group of interest by the pooled standard deviation of all groups. Cohen (1988) defined effect sizes as “small ¼0.2,”
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Table 1 Neuropsychological test battery according to the domains of the “Measurement and Treatment Research to Improve Cognition in Schizophrenia”. Cognitive domain
Variables
Speed of processing Trail Making Test-A subtest (TM A) (nonverbal) (Reitan and Wolfson, 1985) Stroop Word Test (Stroop W): word reading (verbal) (Stroop, 1935) Verbal Phonemic Fluency (all words starting with F, P, and L) (Novelli et al., 1986) Sustained attention/vigilance Wisconsin Card Sorting Test (WCST) (Grant and Berg, 1948) Working memory Corsi block test: spatial span (Orsini et al., 1987) Trail Making B-A subtest (TM B-A) (Reitan and Wolfson, 1985)
1. Time in seconds 2. Number of words read correctly in 30 s 3. Sum of words produced in 60 s 4. Number of non-perseverative errors (NPEs) 5. Raw score correct 6. Differential score between subtests B and A (time in seconds)
Verbal learning Buschke Verbal Selective Reminding Test (BVSRT) (Buschke, 1973) Visual learning Rey–Osterrieth Complex Figure (ROCF) (Osterrieth, 1944) Reasoning and problem solving WCST (Grant and Berg, 1948) Raven's Coloured Progressive Matrices (RCPM) (Raven, 2008) Social cognition Facial Affect Recognition (FAR): photographs of emotional faces and emotion labels were presented on a computer screen. Participants were asked to choose one of six emotions explicitly specified on the monitor for a given face (subtest A) or to select one of six faces that corresponded to the emotion displayed (subtest B) (Ekman and Friesen, 1971)
7. Delayed recall 15 min after six learning trials 8. Delayed recall after 15 min 9. Number of completed categories (CCs) 10. Number of correct answers 11. Sums of named (subtest A) and recognized (subtest B) emotions
Table 2 Socio-demographic and psychopathological characteristics of high-risk for psychosis, first-episode schizophrenia, multi-episode schizophrenia subjects and healthy controls.
Male Female Age Duration of illness (yrs) Years of education IQ PANSS pos PANSS neg PANSS gen PANSS tot
Ultra-high-risk (36)
First episode schizophrenia (53)
Multi-episode schizophrenia (44)
Healthy control subjects (30)
Analyses
N (%) 17 (47%) 19 (53%) Mean (S.D./95% CI) 22.4 (3.7/21.1–23.7) 0.4 (0.3/0.1–0.6) 12.9 (2.5/12.1–13.8) 99.3 (7.4/95.7–103.0) 17.4 (6.4%15.2–19.5) 21.1 (7.2/18.7–23.5) 43.0 (7.7/40.4–45.6) 81.4 (15.5/76.2–86.7)
N (%) 39 (73%) 14 (27%) Mean (S.D./95% CI) 25.9 (7.3/23.9–27.9) 0.8 (0.6/0.2–1.2) 12.6 (2.9/11.8–13.4) 93.8 (7.1/91.1–96.4) 24.5 (8.8/22.1–26.9) 22.9 (8.3/20.6–25.2) 49.6 (12.1/46.3–52.9) 97.6 (19.5/92.2–103.0)
N (%) 28 (64%) 16 (36%) Mean (S.D./95% CI) 35.1 (7.8/32.8–37.5) 9.9 (6.4/8.0–11.8) 13.0 (3.1/12.1–13.9) 91.9 (5.2/89.8–94.2) 19.2 (5.9/17.4–21.0) 25.1 (6.5/23.1–27.1) 47.3 (9.3/44.4–50.1) 92.0 (16.7/86.9–97.2)
N (%) 6 (20%) 24 (80%) Mean (S.D./95% CI) 25.8 (3.2/24.6–27.0)
χ2 24.5
d.f. 3
p o 0.001
F 32.1 87.8 9.2 68.2 10.0 1.5 2.7 1.4
d.f. 3–159 2–130 3–159 3–159 2–130 2–130 2–130 2–130
p o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 0.223 0.069 0.247
“medium ¼0.5,” and “large¼ 0.8”. A significance level of 0.05 was used for all statistical tests, and two-tailed tests were applied. Tests were carried out with the statistical package SPSS (version 17.0.2).
3. Results 3.1. Socio-demographic characteristics Socio-demographic characteristics of the different groups are shown in Table 2. There was a statistically significant difference for sex, with a lower proportion of males in the HC group (p o0.001). As expected, ANOVA one-way comparisons showed significant differences between groups in terms of age (F 32.1; d.f. 3,159; p o0.001), as the MES group was significantly older than the other two clinical groups (UHR and FES). Duration of illness in MES group was significantly longer (F 87.8; d.f. 2,130; p 40.001) than in the other two clinical groups (UHR and FES). Current IQ was higher in the UHR group (F 68.2; d.f. 3,159; p o0.001). 3.2. Clinical characteristics Psychopathological characteristics of the different groups are shown in Table 2. Regarding clinical variables, post-hoc
15.6 (1.2/15.1–16.0) 114.2 (5.5/112.1–116.4)
comparisons specifically showed that the groups differed significantly for PANSS positive scores (F 10; d.f. 2,130; p o0.05) (with highest scores for FES vs all other groups). ANOVA one-way analysis did not show significant differences among clinical groups for the PANSS depressive (UHR: 9.0, S.D. 3.7; FES: 10.1, S.D. 3.6; MES: 9.4, S.D. 3.8; F 3.8; d.f. 2,130; p ¼0.3), negative (UHR: 18.3, S.D. 6.7; FES: 19.1, S.D. 6.5; MES: 21.8, S.D. 6.2; d.f. 2,130; p¼ 0.3) and cognitive/disorganized factors (UHR:10.8, S.D.:4.1; FES:13.4, S. D. 5.1; MES: 12.3 S.D.:4.7; F¼1.4; d.f. ¼2,130; p ¼0.2).
3.3. Neuropsychological performance The results of ANCOVA analysis adjusted for socio-demographic and clinical variables that differed significantly in the previous ANOVA analysis (age, sex, IQ and PANSS positive score) are shown in Table 3 and Fig. 1. Planned comparisons within the ANCOVA framework confirmed the significant differences between FES vs HC and MES vs HC with all effect sizes 40.8 (Table 3). The planned contrast between the UHR group and HC revealed a strong difference on speed of processing (d ¼0.8), visual learning (d ¼0.8) and social cognition (d¼ 1.1), but not on other domains (Table 3).
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Table 3 Comparison between healthy control group and ultra-high risk, first-episode and multi-episode schizophrenia patients on neuropsychological measures. Neurocognitive domain
Speed of processing Sustained attention/ vigilance Working memory Verbal learning Visual learning Reasoning and problem solving Social cognition
UHR
FES
MES
HC
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
0.19 (0.59) 0.12 (0.91) 0.23 0.13 0.23 0.15
F
(0.54) 0.26 (0.75) 0.65 (0.94) 0.13 (0.93) 0.16 (0.76) 0.23 (0.91) 0.53 (0.74) 0.23 (0.89) 0.52
(0.92) (0.89) (0.73) (0.89)
0.69 0.94 1.04 0.71
(0.34) 13.154 0.002 (0.6) (0.32) 9.042 0.017 (0.4) (0.63) 15.263 0.000 (0.8) (0.34) 9.599 0.003 (0.6)
0.20 (0.85) 0.46 (0.70) 0.33 (0.89) 0.79 (0.42) 11.551 0.000 (1.1)
Z-Score (SD- Units)
1 0.5 0 SA/V
HC vs UHR (d)
0.27 (0.74) 0.56 (0.70) 0.89 (0.29) 20.590 0.000 (0.8) 0.12 (0.69) 0.92 (1.49) 0.80 (0.39) 8.159 0.005 (0.7)
1.5
SoP
p
WM
VeL
ViL
RaPS
SC
-0.5 -1 HC
UHR
FES
MES
-1.5 Cognitive domains
Fig. 1. Cognitive Profiles in healthy control group , ultra-high risk, first-episode and multi-episode schizophrenia patients. SOP, speed of processing; SA/V, sustained attention/vigilance; WM, working memory; VeL, verbal learning; ViL, visual learning; RaPS, reasoning and problem solving; SC, social cognition.
4. Discussion In this study we aimed to analyze differences in neurocognition among three groups of schizophrenia spectrum patients at different stages of illness. We found that 1) the UHR group performed significantly worse than controls; 2) the FES group performed significantly worse than UHR on working memory; 3) the MES group performed significantly worse than FES on attention/vigilance. Data were further statistically adjusted for IQ and PANSS scores, indicating that impairments were not simply a general intellectual deficit neither related to psychopathological conditions. In regard to the first finding, our results agree with two recent large meta-analyses (Fusar-Poli et al., 2012; Giuliano et al., 2012), who found strong evidence for a consistent impairment of performance in at-risk groups across different centers and highrisk inclusion criteria. Compared with controls, UHR subjects showed deficits in all explored domains, with an effect size 40.8 only on the speed of processing, visual learning, and social cognition. Deficits in the same domains have been already reported in prodromal subjects before the full blown psychosis (Seidman et al., 2010; Frommann et al., 2011; Amminger et al., 2012; Comparelli et al., 2013; Kelleher et al., 2013) and are also associated with a poor functional outcome even in studies conducted over many years of follow-up (Addington et al., 2006; Lin et al., 2011 Carrion et al., 2011). Interestingly, in our study the performance on the aforementioned domains is consistent in magnitude across the phases of illness, fitting the pattern of a vulnerability indicator. Up to here, our results are in accordance with the neurodevelopmental model of schizophrenia in which developmental insults
HC vs FES (d)
HC vs MES (d)
UHR vs FES
UHR vs MES
FES vs MES
0.000 (0.9) 0.004 (0.9)
0.000 (1.1) 0.000 (0.9)
0.783 1.000
0.029 0.047
0.672 0.026
0.000 0.004 0.000 0.000
0.000 0.005 0.000 0.000
(1.1) (0.9) (1.1) (1.1)
0.049 1.000 0.940 0.571
0.001 1.000 0.279 0.030
0.744 1.000 1.000 1.000
0.000 (1.2)
0.210
0.294
1.000
(1.1) (0.9) (1.1) (1.0)
0.000 (1.2)
(brain pathology, genetics, environmental factors and geneenvironmental interactions) lead to pathologic neural circuits (Fatemi and Folsom, 2009; Weinberger, 1987). Secondarily, in the first episode group, we found a more severe deficit compared with the UHR group performance on the domain of working memory. Thus, from a staging perspective, neurocognitive deficit apparently increases in severity from prodrome to the first episode. This finding suggests that additional neuropsychological deterioration, in those developing psychosis, may continue to occur during the late prodromal phase and/or during the first episode of psychosis, considering that our first-episode patients had a very recently onset of the illness. However, only longitudinal studies monitoring cognitive function in the same subjects may verify this progression. Our results are consistent with other studies identifying working memory as a putative marker of disease progression (Pflueger et al., 2007; Frommann et al., 2011). Interestingly, only in the UHR subjects who convert to psychosis, working memory impairment is specifically associated with prefronto-temporo-limbic and subcortical structures, as well as the interconnecting white matter alterations (Koutsouleris et al., 2012b). Our third finding shows that cognitive functioning seems to be relatively stable after the psychosis onset, with the exception of the attention/vigilance that is significantly more impaired in multi-episode patients. This is congruous with other crosssectional reports of relative neurocognitive stability in schizophrenia patients at different stages of illness and across domains (Goldberg et al., 1993), except for problem solving (Sponheim et al., 2010), verbal and visual memory (Pukrop et al., 2006). Longitudinal studies found out that patients had significant neurocognitive impairments at the first episode, and that these deficits were stable over the follow-up period (Heaton et al., 2001; Hoff et al., 2005). Of note, group data may reflect a mixture of patients who improve, decline or remain stable, making it difficult to identify trends in individuals. Indeed, none of the cited studies used a consensus cognitive battery or a neuropsychological assessment according to the MATRICS Consensus recommendations. Thus, differences across studies in cognitive domains involved in progression, may be due to the absence of such consensus. Overall, whereas cross-sectional evidence suggests that some neurocognitive domains worsen with illness progression, longitudinal findings indicate that neurocognitive deficits are relatively stable at the group level and not tightly linked to symptom severity after illness onset and possibly prior to a first break. Actually, the issue to clarify is whether the progression after the onset is real or not in order to solve the dichotomy between neurodevelopmental and neurodegenerative models of the disease. At the moment, the optimal way to integrate existing information is to remind that brain development is an ongoing process that occurs throughout life (Andreasen, 2010).
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Our study has some limitations. First of all, as mentioned above, the cross-sectional design does not allow to determine whether the deficit in neurocognition is stable throughout the illness or not and whether worsening of performance within specific domains can be considered a marker of progression. Because we could not compare UHR participants who did and did not convert, this consideration is reliable especially for the transition to psychosis, for which we need certain indicators of progression. The strength of our work is that we compared three clinical groups of the schizophrenia spectrum using the same cognitive tests with an assessment made according to a consensus neurocognitive battery. Our results show a high statistical power due to the large effect size shown. The large effect size is especially relevant for the UHR group. In fact the search for clear endophenotypes and genetic underpinnings of the illness may further clarify the pathophysiology of the disease and the need and the target for intervention. Finally our study confirms the existence of a neuropsychological deficit before the onset of the full blown psychosis but does not exclude the possibility of a further impairment after the beginning of schizophrenia, consistent with the fact that neurodevelopment is a process ongoing throughout life. References Addington, J., Saeedi, H., Addington, D., 2006. Facial affect recognition: a mediator between cognitive and social functioning in psychosis? Schizophrenia Research 85, 142–150. Amminger, G.P., Schäfer, M.R., Klier, C.M., Schlögelhofer, M., Mossaheb, N., Thompson, A., Bechdolf, A., Allott, K., McGorry, P.D., Nelson, B., 2012. Facial and vocal affect perception in people at ultra-high risk of psychosis, firstepisode schizophrenia and healthy controls. Early Intervention in Psychiatry 6, 450–454. Andreasen, N.C., Flaum, M., Arndt, S., 1992. The Comprehensive Assessment Of Symptoms And History (Cash). An instrument for assessing diagnosis and psychopathology. Archives of General Psychiatry 49, 615–623. Andreasen, N.C., 2010. The lifetime trajectory of schizophrenia and the concept of neurodevelopment. Dialogues in Clinical Neuroscience 12, 409–415. Bleuler, E., 1950. Dementia Praecox or the Group of Schizophrenias. International Universities Press, New York. Bryson, G., Bell, M.D., 2003. Initial and final work performance in schizophrenia: cognitive and symptom predictors. Journal of Nervous and Mental Disease 191, 87–92. Buschke, H., 1973. Selective reminding for analysis of memory and learning. Journal of Verbal Learning and Verbal Behavior 12, 543–550. Carrion, R.E., Goldberg, T.E., McLaughlin, D., Auther, A.M., Correll, C.U., Cornblatt, B. A., 2011. Impact of neurocognition on social and role functioning in individuals at clinical high risk for psychosis. American Journal of Psychiatry 168, 806–813. Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences, second ed. Lawrence Erlbaum, New Jersey. Comparelli, A., Corigliano, V., De Carolis, A., Mancinelli, I., Trovini, G., Ottavi, G., Dehning, J., Tatarelli, R., Brugnoli, R., Girardi, P., 2013. Emotion recognition impairment is present early and is stable throughout the course of schizophrenia. Schizophrenia Research 143, 65–69. Comparelli, A., Savoja, V., Kotzalidis, G.D., Woods, S.W., Mosticoni, S., Vassallo, F., Soscia, F., Piccione, R., Palma, G., Pucci, D., Girardi, P., Conti, L., Tatarelli, R., 2011. Factor-structure of the Italian version of the Scale of Prodromal Symptoms (SOPS): a comparison with the English version. Epidemiology and Psychiatric Sciences 20, 45–54. Eberhard, J., Riley, S., 2003. Premornid IQ and schizophrenia. Increasing cognitive reduction by episodes. European Archives of Psychiatry and Clinical Neuroscience 253, 84–88. Ekman, P., Friesen, W.V., 1971. Constants across cultures in the face and emotion. Journal of Personality and Social Psychology 17, 124–129. Fatemi, S.H., Folsom, T.D., 2009. The neurodevelopmental hypothesis of schizophrenia. revisited. Schizophrenia Bulettin 35, 528–548. First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B.W., 1996. Structured Clinical Interview for DSM-IV Axis I Disorders SCID-I: Clinician Version. American Psychiatric Press, Washington. Francey, S.M., Jackson, H.J., Phillips, L.J., Wood, S.J., Yung, A.R., McGorry, P.D., 2005. Sustained attention in young people at high risk of psychosis does not predict transition to psychosis. Schizophrenia Research 79, 127–136. Frommann, I., Pukrop, R., Brinkmeyer, J., Bechdolf, A., Ruhrmann, S., Berning, J., Decker, P., Riedel, M., Möller, H.J., Wölwer, W., Gaebel, W., Klosterkötter, J., Maier, W., Wagner, M., 2011. Neuropsychological profiles in different at-risk states of psychosis: executive control impairment in the early – and additional memory dysfunction in the late – prodromal state. Schizophrenia Bullettin 37, 861–873.
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Baseline neurocognitive dficits in the CATIE schizophrenia trial. Neuropsychopharmacology 31, 2033–2046. Kelleher, I., Murtagh, A., Clarke, M.C., Murphy, J., Rawdon, C., Cannon, M., 2013. Neurocognitive performance of a community-based sample of young people at putative ultra-high risk for psychosis: support for the processing speed hypothesis. Cognitive Neuropsychiatry 18, 9–25. Kern, R.S., Nuechterlein, K.H., Green, M.F., Baade, L.E., Fenton, W.S., Gold, J.M., Keefe, R.S., Mesholam-Gately, R., Mintz, J., Seidman, L.J., Stover, E., Marder, S.R., 2008. The MATRICS Consensus Cognitive Battery, part 2: co-norming and standardization. American Journal of Psychiatry 165, 214–220. Koutsouleris, N., Davatzikos, C., Bottlender, R., Patschurek-Kliche, K., Scheuerecker, J., Decker, P., Gaser, C., Möller, H.J., Meisenzahl, E.M., 2012a. Early recognition and disease prediction in the at-risk mental states for psychosis using neurocognitive pattern classification. 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Neurocognition in schizophrenia: From prodrome to multi-episode illness Valentina Corigliano a,n, Antonella De Carolis b, Giada Trovini a, Julia Dehning a, Simone Di Pietro a, Martina Curto a, Nicole Donato b, Eleonora De Pisa a, Paolo Girardi a, Anna Comparelli a a NESMOS Department (Neurosciences, Mental Health and Sense Organs) Unit of Psychiatry, Sant'Andrea Hospital, School of Medicine and Psychology, Sapienza University of Rome, Italy b NESMOS Department (Neurosciences, Mental Health and Sense Organs) Unit of Neurology, Sant'Andrea Hospital, School of Medicine and Psychology, Sapienza University of Rome, Italy
art ic l e i nf o
a b s t r a c t
Article history: Received 12 November 2013 Received in revised form 24 June 2014 Accepted 27 July 2014 Available online 6 August 2014
Individuals with schizophrenia present a neuropsychological deficit throughout the course of the disorder. Few studies have addressed the progression of the deficit since the prodromal phase of the disorder. This investigation explored neurocognition in accordance with the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus recommendations. The aim of the study was to explore the presence of neurocognitive impairment in ultra-high-risk individuals and the stage of this impairment in samples at different phases of illness. Thirty-six individuals with a prodromal syndrome, 53 first-episode and 44 multi-episode schizophrenia patients were assessed to examine neuropsychological performance. ANCOVA analysis adjusted for possible confounder factors and planned contrasts with healthy controls were undertaken. The results revealed deficits in speed-ofprocessing, visual-learning and social-cognition in prodromal individuals, and of all other neuropsychological domains in both first-episode and multi-episode patients. Furthermore impairment was found in the first-episode and in the multi-episode group, respectively on working-memory and attention. Within the framework of the neurodevelopmental model of schizophrenia, our results suggest the presence of neuropsychological impairment before the onset of full-blown psychosis. Moreover, the deficits are larger in the more chronic groups, according to the theory of an ongoing neurodevelopmental alteration. & 2014 Elsevier Ireland Ltd. All rights reserved.
Keywords: Neurocognitive impairment First-episode schizophrenia Ultra-high risk MATRICS Neurodevelopmental model Early psychosis
1. Introduction Substantial neuropsychological deficits, first described by Kraepelin (1919) and Bleuler (1950), have subsequently been observed in all phases of schizophrenia, beginning in the premorbid period and continuing throughout life. The most prominent of these deficits concern memory, attention, working memory, problem solving, processing speed, and social cognition (Nuechterlein et al., 2004). These impairments exist prior to the initiation of antipsychotic treatment (Saykin et al., 1994) and are not caused by positive psychotic symptoms in patients who are able to complete cognitive testing, which represent the overwhelming majority of patients (Keefe et al., 2006). The various
n Corresponding author at: Valentina Corigliano, NESMOS Department, Sapienza University, School of Medicine and Psychology, Sant'Andrea Hospital, Via di Grottarossa 1035-1039, 00189 Rome, Italy. Tel.: þ39 06 33775664, þ 39 06 33775951; fax: þ39 06 33775399. E-mail address: [email protected] (V. Corigliano).
http://dx.doi.org/10.1016/j.psychres.2014.07.067 0165-1781/& 2014 Elsevier Ireland Ltd. All rights reserved.
cognitive deficits in schizophrenia have all been shown to be associated with worse functional outcomes such as difficulty with community functioning, difficulty with instrumental and problemsolving skills, reduced success in psychosocial rehabilitation programs (Green et al., 2000) and the inability to maintain successful employment (Bryson and Bell, 2003). In fact, cognitive deficits are better able to explain important functional outcomes, such as work performance and independent living (Harvey et al., 1998) than positive or negative symptoms. The significant finding of premorbid neuropsychological impairment indicates that these measures may have utility as predictors of schizophrenia (Koutsouleris et al., 2012a). Over the past 5 years, several research groups have published studies of neuropsychological functioning in ultra-high risk (UHR) groups for impending psychosis (Fusar-Poli et al., 2012). Findings from crosssectional UHR studies have consistently documented that neuropsychological deficits are intermediate between control and first episode psychosis samples (Seidman et al., 2010), and one has shown that neuropsychological functioning is related to illness
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course (Niendam et al., 2007). Several specific deficits have been observed, most reliably in visual (Wood et al., 2003) and verbal memory (Lencz et al., 2006), in working memory (Pflueger et al., 2007) and attention (Francey et al., 2005). Some deficits (e.g., in sustained attention) may represent stable vulnerability markers while others (such as verbal memory, working memory, processing speed and verbal IQ) may be predictors for conversion to psychosis (Lencz et al., 2006). Patients in the first psychotic episode and during chronic periods manifest large neuropsychological impairments involving verbal memory, attention, processing speed and executive functioning (Nuechterlein et al., 2004), with effect sizes (ES) averaging approximately 1.0 (Heinrichs and Zakzanis, 1998; MesholamGately et al., 2009). The degree of impairment depends on the domain measured, with verbal memory and processing speed typically showing the largest deficits (ES¼ 1.3–1.6 using Cohen's d) (Heinrichs and Zakzanis, 1998; Mesholam-Gately et al., 2009). Although these impairments appear relatively stable during the course of the illness (Rund, 1998), there is also evidence of further widespread neurodegenerative progress (Harvey, 2001) or cognitive decline in selected domains (Eberhard and Riley, 2003; Seidman et al., 2003). The primary aim of this study is to characterize the neuropsychology of the psychosis prodrome using a neurocognitive battery exploring seven cognitive domains (processing speed, verbal learning, working memory, reasoning and problem solving, visual learning, attention/vigilance, and social cognition) recommended by the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) committee (Kern et al., 2008; Nuechterlein et al., 2008) in order to assess differences between subjects who met criteria for a prodromal syndrome and healthy control subjects. Neurocognitive deficits in “at risk” individuals may serve as a marker of risk, whereas the trend analysis of the deficit may help us to differentiate whether the deficit is a vulnerability or severity index. Since neuropsychological functions are important predictors of functioning in schizophrenia, these cognitive deficits have considerable relevance regarding prognosis and are feasible targets for psychopharmacological interventions (Hyman and Fenton, 2003). The secondary aim of our study is to compare the neuropsychological performance in three phases of the illness. Our hypotheses are that subjects experiencing their first episode of the illness are more impaired than UHR and that they have an intermediate level of performance between UHR and multi-episode subjects. To our knowledge, this is the first study exploring neurocognition in three phases of the illness using a neuropsychological assessment made according to the MATRICS Consensus recommendations.
current drug abuse. Of the 196 subjects initially screened, 48 were excluded for current substance abuse and 15 presented severe medical conditions or neurological disease. UHR patients were free of antipsychotic medication, while FES and MES were receiving atypical antipsychotic medication at the time of the assessment. According to Gardner et al. (2010), mean daily dose for antipsychotic medication in olanzapine equivalents was 18.4 mg (DS¼ 0.4) in recent onset psychosis and 16.9 mg (DS ¼0.8) in chronic psychosis, with no significant difference between the two dosages (T 2.63, d.f. ¼ 95, p 40.05). There was no change in the antipsychotic medication dosage over the 4 weeks prior to the study. Thirty healthy volunteers were recruited as controls in the same catchment area. None had prior history of psychiatric disease, mental retardation, neurological or general medical illnesses, including substance dependence, as determined by using an abbreviated version of the Comprehensive Assessment of Symptoms and History (CASH) (Andreasen et al., 1992). The absence of psychosis in first-degree relatives was confirmed by controlling clinical records and family interviews. All participants provided free, informed consent for participating in the study and for the publication of results. The research was approved by the hospital's Ethical Committee.
2.2. Assessments 2.2.1. Psychopathology Data on socio-demographic and psychopathological variables were collected at clinical interview. Criteria for a prodromal syndrome were determined using the validated Italian version of the Scale of Prodromal Symptoms (SOPS) (Comparelli et al., 2011), which consists of 19 items in four symptom domains: positive, negative, general and disorganized. Mean SOPS positive score was 7.7 (S.D. ¼4.3), mean SOPS negative score was 10.1 (S.D. ¼6.5), mean SOPS disorganization score was 6.0 (S.D.¼3.1) and mean SOPS general score was 8.1 (S.D. ¼4.1). The raters (A.C. and V.C.) are expert clinicians trained in the administration of the SIPS/SOPS. Cohen's κ for inter-rater reliability was 0.91 (p o 0.0001). Psychopathology was assessed with the Positive and Negative Syndrome Scale (PANSS) (Kay et al., 1987). For statistical analysis we also used the depressive (items G2-anxiety, G3-guilt feelings and G6-depression), the negative (items N1-blunted affect, N2-emotional withdrawal, N3-poor rapport, N4-passive withdrawal, N6-lack of spontaneity, G7-motor retardation, G16-active social avoidance), and the cognitive/disorganized (items N5-difficulty in abstract thinking, N7-stereotyped thinking, P2-conceptual disorganization, G10-disorientation and G11-poor attention) PANSS factors extracted by Lykouras et al. (2000). Current IQ was estimated through Raven's Standard Progressive Matrices (Raven, 2008).
2.2.2. Neuropsychological measures Neuropsychological assessment was conducted according to the ‘Measurement and Treatment Research to improve Cognition in Schizophrenia’ (Nuechterlein et al., 2008) Consensus recommendations, including the exploration of seven domains, which are speed of processing, sustained attention/vigilance, working memory, verbal learning, visual learning, reasoning/problem-solving and social cognition. To maximize cooperation and avoid acute effects of psychotic symptoms, the neurocognitive battery was administered after clinical stabilization of acute psychotic symptoms in the case of the FES and the MES groups, with a median time from admission to neuropsychological assessment of 4 weeks (range: 17–35 days) and, in any case, after hospital discharge. The tests used and the parameters considered for each domain are described in Table 1.
2.3. Statistical analysis
2. Methods 2.1. Subjects We enrolled 196 male and female patients aged 18 and older who were referred to our Acute Psychiatric Care Department or to our outpatient clinic. Thirty-six participants met psychosis risk syndrome criteria (McGlashan et al., 2010), i.e. Attenuated Psychotic Symptoms (APS), Brief Intermittent Psychotic Symptoms (BIPS) or functional decline and family history of schizophrenia (Genetic Risk and Deterioration, GRD). Ninety-seven patients met the diagnosis of DSM-IV schizophrenia or schizophreniform disorder based on the Structured Interview for DSM-IV Disorders-I (SCID-I) (First et al., 1996). Within this group, 53 patients were experiencing their first psychotic episode, with a very recent onset. Forty-four had an established diagnosis of schizophrenia with multiple-episode history. Exclusion criteria were (1) impaired vision (i.e., blurred or less than 20/40 vision with correction) and impaired auditory acuity (2) current or past comorbid diagnosis of autistic disorder or other pervasive developmental disorder, (3) history of severe head injury, (4) severe medical conditions or major neurological disorders, including mental retardation and dementia, which could prevent neuropsychological task performance or that could produce psychotic symptoms, and (5) any
For all groups, we calculated means and standard deviations of demographic, psychopathological (PANSS factors) and IQ measures. As some cognitive domains have been explored using more than one neuropsychological test, we calculated standardized z-scores to obtain a single score for each cognitive domain. The z-scores were computed using means and standard deviations (S.D.s) based on all participants but segregated by task. Then, we analyzed differences in sociodemographic, IQ, clinical features and neuropsychological performance among the three clinical subgroups (UHR, FES, and MES) and the healthy control group using one-way ANOVA and post-hoc analysis according to Bonferroni or Tahmane, whenever homogeneity of variance could not be assumed. To evaluate the possible confounding role of depressive, negative and disorganized/cognitive symptoms, we also carried out a one-way ANOVA analysis with the Depressive, the Negative and the Disorganized/Cognitive PANSS factors. A student's T-test was used to compare differences in antipsychotic dosages in FES and MES. Subsequent ANCOVA with adjustments for socio-demographic and clinical variables that differed significantly among groups according to the one-way ANOVA was computed to compare the neuropsychological measures in the UHR, FES, MES and healthy control (HC) groups. Planned simple comparisons were made for each of the UHR, FES and MES groups to the control group. We calculated effect sizes by dividing the adjusted mean difference from the group of interest by the pooled standard deviation of all groups. Cohen (1988) defined effect sizes as “small ¼0.2,”
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Table 1 Neuropsychological test battery according to the domains of the “Measurement and Treatment Research to Improve Cognition in Schizophrenia”. Cognitive domain
Variables
Speed of processing Trail Making Test-A subtest (TM A) (nonverbal) (Reitan and Wolfson, 1985) Stroop Word Test (Stroop W): word reading (verbal) (Stroop, 1935) Verbal Phonemic Fluency (all words starting with F, P, and L) (Novelli et al., 1986) Sustained attention/vigilance Wisconsin Card Sorting Test (WCST) (Grant and Berg, 1948) Working memory Corsi block test: spatial span (Orsini et al., 1987) Trail Making B-A subtest (TM B-A) (Reitan and Wolfson, 1985)
1. Time in seconds 2. Number of words read correctly in 30 s 3. Sum of words produced in 60 s 4. Number of non-perseverative errors (NPEs) 5. Raw score correct 6. Differential score between subtests B and A (time in seconds)
Verbal learning Buschke Verbal Selective Reminding Test (BVSRT) (Buschke, 1973) Visual learning Rey–Osterrieth Complex Figure (ROCF) (Osterrieth, 1944) Reasoning and problem solving WCST (Grant and Berg, 1948) Raven's Coloured Progressive Matrices (RCPM) (Raven, 2008) Social cognition Facial Affect Recognition (FAR): photographs of emotional faces and emotion labels were presented on a computer screen. Participants were asked to choose one of six emotions explicitly specified on the monitor for a given face (subtest A) or to select one of six faces that corresponded to the emotion displayed (subtest B) (Ekman and Friesen, 1971)
7. Delayed recall 15 min after six learning trials 8. Delayed recall after 15 min 9. Number of completed categories (CCs) 10. Number of correct answers 11. Sums of named (subtest A) and recognized (subtest B) emotions
Table 2 Socio-demographic and psychopathological characteristics of high-risk for psychosis, first-episode schizophrenia, multi-episode schizophrenia subjects and healthy controls.
Male Female Age Duration of illness (yrs) Years of education IQ PANSS pos PANSS neg PANSS gen PANSS tot
Ultra-high-risk (36)
First episode schizophrenia (53)
Multi-episode schizophrenia (44)
Healthy control subjects (30)
Analyses
N (%) 17 (47%) 19 (53%) Mean (S.D./95% CI) 22.4 (3.7/21.1–23.7) 0.4 (0.3/0.1–0.6) 12.9 (2.5/12.1–13.8) 99.3 (7.4/95.7–103.0) 17.4 (6.4%15.2–19.5) 21.1 (7.2/18.7–23.5) 43.0 (7.7/40.4–45.6) 81.4 (15.5/76.2–86.7)
N (%) 39 (73%) 14 (27%) Mean (S.D./95% CI) 25.9 (7.3/23.9–27.9) 0.8 (0.6/0.2–1.2) 12.6 (2.9/11.8–13.4) 93.8 (7.1/91.1–96.4) 24.5 (8.8/22.1–26.9) 22.9 (8.3/20.6–25.2) 49.6 (12.1/46.3–52.9) 97.6 (19.5/92.2–103.0)
N (%) 28 (64%) 16 (36%) Mean (S.D./95% CI) 35.1 (7.8/32.8–37.5) 9.9 (6.4/8.0–11.8) 13.0 (3.1/12.1–13.9) 91.9 (5.2/89.8–94.2) 19.2 (5.9/17.4–21.0) 25.1 (6.5/23.1–27.1) 47.3 (9.3/44.4–50.1) 92.0 (16.7/86.9–97.2)
N (%) 6 (20%) 24 (80%) Mean (S.D./95% CI) 25.8 (3.2/24.6–27.0)
χ2 24.5
d.f. 3
p o 0.001
F 32.1 87.8 9.2 68.2 10.0 1.5 2.7 1.4
d.f. 3–159 2–130 3–159 3–159 2–130 2–130 2–130 2–130
p o 0.001 o 0.001 o 0.001 o 0.001 o 0.001 0.223 0.069 0.247
“medium ¼0.5,” and “large¼ 0.8”. A significance level of 0.05 was used for all statistical tests, and two-tailed tests were applied. Tests were carried out with the statistical package SPSS (version 17.0.2).
3. Results 3.1. Socio-demographic characteristics Socio-demographic characteristics of the different groups are shown in Table 2. There was a statistically significant difference for sex, with a lower proportion of males in the HC group (p o0.001). As expected, ANOVA one-way comparisons showed significant differences between groups in terms of age (F 32.1; d.f. 3,159; p o0.001), as the MES group was significantly older than the other two clinical groups (UHR and FES). Duration of illness in MES group was significantly longer (F 87.8; d.f. 2,130; p 40.001) than in the other two clinical groups (UHR and FES). Current IQ was higher in the UHR group (F 68.2; d.f. 3,159; p o0.001). 3.2. Clinical characteristics Psychopathological characteristics of the different groups are shown in Table 2. Regarding clinical variables, post-hoc
15.6 (1.2/15.1–16.0) 114.2 (5.5/112.1–116.4)
comparisons specifically showed that the groups differed significantly for PANSS positive scores (F 10; d.f. 2,130; p o0.05) (with highest scores for FES vs all other groups). ANOVA one-way analysis did not show significant differences among clinical groups for the PANSS depressive (UHR: 9.0, S.D. 3.7; FES: 10.1, S.D. 3.6; MES: 9.4, S.D. 3.8; F 3.8; d.f. 2,130; p ¼0.3), negative (UHR: 18.3, S.D. 6.7; FES: 19.1, S.D. 6.5; MES: 21.8, S.D. 6.2; d.f. 2,130; p¼ 0.3) and cognitive/disorganized factors (UHR:10.8, S.D.:4.1; FES:13.4, S. D. 5.1; MES: 12.3 S.D.:4.7; F¼1.4; d.f. ¼2,130; p ¼0.2).
3.3. Neuropsychological performance The results of ANCOVA analysis adjusted for socio-demographic and clinical variables that differed significantly in the previous ANOVA analysis (age, sex, IQ and PANSS positive score) are shown in Table 3 and Fig. 1. Planned comparisons within the ANCOVA framework confirmed the significant differences between FES vs HC and MES vs HC with all effect sizes 40.8 (Table 3). The planned contrast between the UHR group and HC revealed a strong difference on speed of processing (d ¼0.8), visual learning (d ¼0.8) and social cognition (d¼ 1.1), but not on other domains (Table 3).
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Table 3 Comparison between healthy control group and ultra-high risk, first-episode and multi-episode schizophrenia patients on neuropsychological measures. Neurocognitive domain
Speed of processing Sustained attention/ vigilance Working memory Verbal learning Visual learning Reasoning and problem solving Social cognition
UHR
FES
MES
HC
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
Mean (S.D.)
0.19 (0.59) 0.12 (0.91) 0.23 0.13 0.23 0.15
F
(0.54) 0.26 (0.75) 0.65 (0.94) 0.13 (0.93) 0.16 (0.76) 0.23 (0.91) 0.53 (0.74) 0.23 (0.89) 0.52
(0.92) (0.89) (0.73) (0.89)
0.69 0.94 1.04 0.71
(0.34) 13.154 0.002 (0.6) (0.32) 9.042 0.017 (0.4) (0.63) 15.263 0.000 (0.8) (0.34) 9.599 0.003 (0.6)
0.20 (0.85) 0.46 (0.70) 0.33 (0.89) 0.79 (0.42) 11.551 0.000 (1.1)
Z-Score (SD- Units)
1 0.5 0 SA/V
HC vs UHR (d)
0.27 (0.74) 0.56 (0.70) 0.89 (0.29) 20.590 0.000 (0.8) 0.12 (0.69) 0.92 (1.49) 0.80 (0.39) 8.159 0.005 (0.7)
1.5
SoP
p
WM
VeL
ViL
RaPS
SC
-0.5 -1 HC
UHR
FES
MES
-1.5 Cognitive domains
Fig. 1. Cognitive Profiles in healthy control group , ultra-high risk, first-episode and multi-episode schizophrenia patients. SOP, speed of processing; SA/V, sustained attention/vigilance; WM, working memory; VeL, verbal learning; ViL, visual learning; RaPS, reasoning and problem solving; SC, social cognition.
4. Discussion In this study we aimed to analyze differences in neurocognition among three groups of schizophrenia spectrum patients at different stages of illness. We found that 1) the UHR group performed significantly worse than controls; 2) the FES group performed significantly worse than UHR on working memory; 3) the MES group performed significantly worse than FES on attention/vigilance. Data were further statistically adjusted for IQ and PANSS scores, indicating that impairments were not simply a general intellectual deficit neither related to psychopathological conditions. In regard to the first finding, our results agree with two recent large meta-analyses (Fusar-Poli et al., 2012; Giuliano et al., 2012), who found strong evidence for a consistent impairment of performance in at-risk groups across different centers and highrisk inclusion criteria. Compared with controls, UHR subjects showed deficits in all explored domains, with an effect size 40.8 only on the speed of processing, visual learning, and social cognition. Deficits in the same domains have been already reported in prodromal subjects before the full blown psychosis (Seidman et al., 2010; Frommann et al., 2011; Amminger et al., 2012; Comparelli et al., 2013; Kelleher et al., 2013) and are also associated with a poor functional outcome even in studies conducted over many years of follow-up (Addington et al., 2006; Lin et al., 2011 Carrion et al., 2011). Interestingly, in our study the performance on the aforementioned domains is consistent in magnitude across the phases of illness, fitting the pattern of a vulnerability indicator. Up to here, our results are in accordance with the neurodevelopmental model of schizophrenia in which developmental insults
HC vs FES (d)
HC vs MES (d)
UHR vs FES
UHR vs MES
FES vs MES
0.000 (0.9) 0.004 (0.9)
0.000 (1.1) 0.000 (0.9)
0.783 1.000
0.029 0.047
0.672 0.026
0.000 0.004 0.000 0.000
0.000 0.005 0.000 0.000
(1.1) (0.9) (1.1) (1.1)
0.049 1.000 0.940 0.571
0.001 1.000 0.279 0.030
0.744 1.000 1.000 1.000
0.000 (1.2)
0.210
0.294
1.000
(1.1) (0.9) (1.1) (1.0)
0.000 (1.2)
(brain pathology, genetics, environmental factors and geneenvironmental interactions) lead to pathologic neural circuits (Fatemi and Folsom, 2009; Weinberger, 1987). Secondarily, in the first episode group, we found a more severe deficit compared with the UHR group performance on the domain of working memory. Thus, from a staging perspective, neurocognitive deficit apparently increases in severity from prodrome to the first episode. This finding suggests that additional neuropsychological deterioration, in those developing psychosis, may continue to occur during the late prodromal phase and/or during the first episode of psychosis, considering that our first-episode patients had a very recently onset of the illness. However, only longitudinal studies monitoring cognitive function in the same subjects may verify this progression. Our results are consistent with other studies identifying working memory as a putative marker of disease progression (Pflueger et al., 2007; Frommann et al., 2011). Interestingly, only in the UHR subjects who convert to psychosis, working memory impairment is specifically associated with prefronto-temporo-limbic and subcortical structures, as well as the interconnecting white matter alterations (Koutsouleris et al., 2012b). Our third finding shows that cognitive functioning seems to be relatively stable after the psychosis onset, with the exception of the attention/vigilance that is significantly more impaired in multi-episode patients. This is congruous with other crosssectional reports of relative neurocognitive stability in schizophrenia patients at different stages of illness and across domains (Goldberg et al., 1993), except for problem solving (Sponheim et al., 2010), verbal and visual memory (Pukrop et al., 2006). Longitudinal studies found out that patients had significant neurocognitive impairments at the first episode, and that these deficits were stable over the follow-up period (Heaton et al., 2001; Hoff et al., 2005). Of note, group data may reflect a mixture of patients who improve, decline or remain stable, making it difficult to identify trends in individuals. Indeed, none of the cited studies used a consensus cognitive battery or a neuropsychological assessment according to the MATRICS Consensus recommendations. Thus, differences across studies in cognitive domains involved in progression, may be due to the absence of such consensus. Overall, whereas cross-sectional evidence suggests that some neurocognitive domains worsen with illness progression, longitudinal findings indicate that neurocognitive deficits are relatively stable at the group level and not tightly linked to symptom severity after illness onset and possibly prior to a first break. Actually, the issue to clarify is whether the progression after the onset is real or not in order to solve the dichotomy between neurodevelopmental and neurodegenerative models of the disease. At the moment, the optimal way to integrate existing information is to remind that brain development is an ongoing process that occurs throughout life (Andreasen, 2010).
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Our study has some limitations. First of all, as mentioned above, the cross-sectional design does not allow to determine whether the deficit in neurocognition is stable throughout the illness or not and whether worsening of performance within specific domains can be considered a marker of progression. Because we could not compare UHR participants who did and did not convert, this consideration is reliable especially for the transition to psychosis, for which we need certain indicators of progression. The strength of our work is that we compared three clinical groups of the schizophrenia spectrum using the same cognitive tests with an assessment made according to a consensus neurocognitive battery. Our results show a high statistical power due to the large effect size shown. The large effect size is especially relevant for the UHR group. In fact the search for clear endophenotypes and genetic underpinnings of the illness may further clarify the pathophysiology of the disease and the need and the target for intervention. Finally our study confirms the existence of a neuropsychological deficit before the onset of the full blown psychosis but does not exclude the possibility of a further impairment after the beginning of schizophrenia, consistent with the fact that neurodevelopment is a process ongoing throughout life. References Addington, J., Saeedi, H., Addington, D., 2006. Facial affect recognition: a mediator between cognitive and social functioning in psychosis? Schizophrenia Research 85, 142–150. Amminger, G.P., Schäfer, M.R., Klier, C.M., Schlögelhofer, M., Mossaheb, N., Thompson, A., Bechdolf, A., Allott, K., McGorry, P.D., Nelson, B., 2012. Facial and vocal affect perception in people at ultra-high risk of psychosis, firstepisode schizophrenia and healthy controls. Early Intervention in Psychiatry 6, 450–454. Andreasen, N.C., Flaum, M., Arndt, S., 1992. The Comprehensive Assessment Of Symptoms And History (Cash). An instrument for assessing diagnosis and psychopathology. Archives of General Psychiatry 49, 615–623. Andreasen, N.C., 2010. The lifetime trajectory of schizophrenia and the concept of neurodevelopment. Dialogues in Clinical Neuroscience 12, 409–415. Bleuler, E., 1950. Dementia Praecox or the Group of Schizophrenias. International Universities Press, New York. Bryson, G., Bell, M.D., 2003. Initial and final work performance in schizophrenia: cognitive and symptom predictors. Journal of Nervous and Mental Disease 191, 87–92. Buschke, H., 1973. Selective reminding for analysis of memory and learning. Journal of Verbal Learning and Verbal Behavior 12, 543–550. Carrion, R.E., Goldberg, T.E., McLaughlin, D., Auther, A.M., Correll, C.U., Cornblatt, B. A., 2011. Impact of neurocognition on social and role functioning in individuals at clinical high risk for psychosis. American Journal of Psychiatry 168, 806–813. Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences, second ed. Lawrence Erlbaum, New Jersey. Comparelli, A., Corigliano, V., De Carolis, A., Mancinelli, I., Trovini, G., Ottavi, G., Dehning, J., Tatarelli, R., Brugnoli, R., Girardi, P., 2013. Emotion recognition impairment is present early and is stable throughout the course of schizophrenia. Schizophrenia Research 143, 65–69. Comparelli, A., Savoja, V., Kotzalidis, G.D., Woods, S.W., Mosticoni, S., Vassallo, F., Soscia, F., Piccione, R., Palma, G., Pucci, D., Girardi, P., Conti, L., Tatarelli, R., 2011. Factor-structure of the Italian version of the Scale of Prodromal Symptoms (SOPS): a comparison with the English version. Epidemiology and Psychiatric Sciences 20, 45–54. Eberhard, J., Riley, S., 2003. Premornid IQ and schizophrenia. Increasing cognitive reduction by episodes. European Archives of Psychiatry and Clinical Neuroscience 253, 84–88. Ekman, P., Friesen, W.V., 1971. Constants across cultures in the face and emotion. Journal of Personality and Social Psychology 17, 124–129. Fatemi, S.H., Folsom, T.D., 2009. The neurodevelopmental hypothesis of schizophrenia. revisited. Schizophrenia Bulettin 35, 528–548. First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B.W., 1996. Structured Clinical Interview for DSM-IV Axis I Disorders SCID-I: Clinician Version. American Psychiatric Press, Washington. Francey, S.M., Jackson, H.J., Phillips, L.J., Wood, S.J., Yung, A.R., McGorry, P.D., 2005. Sustained attention in young people at high risk of psychosis does not predict transition to psychosis. Schizophrenia Research 79, 127–136. Frommann, I., Pukrop, R., Brinkmeyer, J., Bechdolf, A., Ruhrmann, S., Berning, J., Decker, P., Riedel, M., Möller, H.J., Wölwer, W., Gaebel, W., Klosterkötter, J., Maier, W., Wagner, M., 2011. Neuropsychological profiles in different at-risk states of psychosis: executive control impairment in the early – and additional memory dysfunction in the late – prodromal state. Schizophrenia Bullettin 37, 861–873.
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