European Psychiatry Sex differences in cognitive functioning of www.cambridge.org/epa patients at-risk for psychosis and healthy controls: Results from the European Gene–Environment Interactions study Research Article Cite this article: Menghini-Müller S, Studerus Stephanie Menghini-Müller1, Erich Studerus2, Sarah Ittig1, Lucia R. Valmaggia3, E, Ittig S, Valmaggia LR, Kempton MJ, van der Gaag M, de Haan L, Nelson B, Bressan RA, Matthew J. Kempton4, Mark van der Gaag5,6, Lieuwe de Haan7,8, Barnaby Nelson9, Barrantes-Vidal N, Jantac C, Nordentoft M, Rodrigo A. Bressan10, Neus Barrantes-Vidal11, Célia Jantac12, Ruhrmann S, Sachs G, Rutten BP, van Os J, Riecher-Rössler A, the EU-GEI High Risk Study Merete Nordentoft13,14, Stephan Ruhrmann15, Garbiele Sachs16, Bart P. Rutten17, Group (2020). Sex differences in cognitive functioning of patients at-risk for psychosis Jim van Os18,19,20, Anita Riecher-Rössler1* and the EU-GEI High Risk Study Group21 and healthy controls: Results from the 1 European Gene–Environment Interactions University of Basel, Department of Psychiatry, Basel, Switzerland; 2Department of Psychology, Division of Personality and study. European Psychiatry, 63(1), e25, 1–9 Developmental Psychology, University of Basel, Basel, Switzerland; 3Department of Psychology, Institute of Psychiatry, https://doi.org/10.1192/j.eurpsy.2019.10 Psychology & Neuroscience, King’s College London, London, United Kingdom; 4Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom; 5Faculty of Received: 20 August 2019 Behavioural and Movement Sciences, Department of Clinical Psychology and EMGO+ Institute for Health Care Research, Revised: 11 October 2019 Accepted: 12 October 2019 VU University, Amsterdam, The Netherlands; 6Department of Psychosis Research, Parnassia Psychiatric Institute, The Hague, The Netherlands; 7Department Early Psychosis, AMC, Academic Psychiatric Centre, Amsterdam, The Key words: Netherlands; 8Mental Health Institute, Arkin, Amsterdam, The Netherlands, Amsterdam, The Netherlands; 9Centre for clinical high-risk; cognition; gender differences; Youth Mental Health, University of Melbourne, Melbourne, Australia; 10LiNC—Lab Interdisciplinar Neurociências risk for psychosis Clínicas, Depto Psiquiatria, Escola Paulista de Medicina, Universidade Federal de São Paulo—UNIFESP, São Paulo, Brazil; 11 Departament de Psicologia Clínica I de la Salut (Universitat Autònoma de Barcelona), Fundació Sanitària Sant Pere Author for correspondence: Claver (Spain), Spanish Mental Health Research Network (CIBERSAM), Barcelona, Spain; 12University Paris Descartes, *Anita Riecher-Rössler Hôpital Sainte-Anne, C’JAAD, Service Hospitalo-Universitaire, Inserm U894, Institut de Psychiatrie (CNRS 3557), Paris, E-mail: anita.riecher@unibas.ch France; 13Mental Health Center Copenhagen, Copenhagen, Denmark; 14Institute for Clinical Medicine, Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark; 15Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany; 16Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria; 17Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht, The Netherlands; 18Department Psychiatry, Brain Centre Rudolf Magnus, Utrecht University Medical Centre, Utrecht, The Netherlands; 19Department of Psychiatry and Psychology, School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Centre, Maastricht, The Netherlands; 20King's College London, King's Health Partners Department of Psychosis Studies, Institute of Psychiatry, London, United Kingdom and 21A full list of authors and affiliations appears in the Appendix. Abstract Background. Sex differences in cognitive functioning have long been recognized in schizophre- nia patients and healthy controls (HC). However, few studies have focused on patients with an at-risk mental state (ARMS) for psychosis. Thus, the aim of the present study was to investigate sex differences in neurocognitive performance in ARMS patients compared with HC. Methods. The data analyzed in this study were collected within the multicenter European Gene– Environment Interactions study (11 centers). A total of 343 ARMS patients (158 women) and 67 HC subjects (33 women) were included. All participants completed a comprehensive neurocognitive battery. Linear mixed effects models were used to explore whether sex differences in cognitive functioning were present in the total group (main effect of sex) and whether sex differences were different for HC and ARMS (interaction between sex and group). Results. Women performed better in social cognition, speed of processing, and verbal learning than men regardless of whether they were ARMS or HC. However, only differences in speed of processing and verbal learning remained significant after correction for multiple testing. Additionally, ARMS patients displayed alterations in attention, current IQ, speed of processing, verbal learning, and working memory compared with HC. © The Author(s) 2020. This is an Open Access Conclusions. Findings indicate that sex differences in cognitive functioning in ARMS are similar article, distributed under the terms of the to those seen between healthy men and women. Thus, it appears that sex differences in cognitive Creative Commons Attribution licence (http:// performance may not be specific for ARMS, a finding resembling that in patients with creativecommons.org/licenses/by/4.0/), which schizophrenic psychoses. permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction Sex differences in schizophrenia have been described in almost all features of the illness, including incidence, prevalence, age at onset, symptomatology, course, and in the response to treatment, 2 Stephanie Menghini-Müller et al. but only reliably established in age at onset and course [1]. Sex-related environmental determinants of schizophrenia [16]. EU-GEI is a differences in the illness course might be at least partially mediated by naturalistic prospective multicenter study that consisted of a base- sex-related differences in cognitive functioning [2]. Reduced cognitive line and up to three follow-up time points (at 6 months, 12 months, performance is one of the core features of schizophrenia and an and 24 months). Data were collected from May 1, 2010 to August important predictor of outcome [3]. Several studies have shown 6, 2015. For the current analyses, only baseline data, that is, at intake neurocognitive deficits already in patients with a so-called at-risk into the study, were used. mental state (ARMS) for psychosis [4]. Furthermore, it has been ARMS participants were recruited from 11 Early Detection and found that ARMS patients with later conversion to psychosis per- Intervention Centers (London, Amsterdam, The Hague, Vienna, formed worse at baseline in tests measuring attention/vigilance, speed Basel, Cologne, Copenhagen, Paris, Barcelona, Melbourne, Saõ of processing, verbal and visual learning, and current and premorbid Paulo). They were referred to the EU-GEI study by primary health IQ compared with patients who did not convert [4]. Consequently, care services, mental health professionals, or themselves or their several studies have shown that the prediction of transition to psy- families. chosis can be improved by including neurocognitive performance Control participants were recruited by four of the above- measures into multivariable risk prediction models [4–8]. mentioned centers: the Institute of Psychiatry, Psychology, and Cognitive performance is not only dependent on different stages Neuroscience (IoPPN) in London, the Personal Assessment and of psychotic disorders, but also on sex. In healthy controls (HC), it Crisis Evaluation Clinic in Melbourne, and the Amsterdam Medical is well established that women tend to perform better than men in Center and Parnassia, The Hague. They were approached by tele- tasks measuring verbal abilities (d = 0.24; for meta-analysis, see phone and through advertisements at educational institutes. In reference [9]), whereas men tend to outperform women on Melbourne, controls were additionally approached at community visual–spatial tasks (d = 0.45; for meta-analysis, see [9]) [10– centers/noticeboards and advertised via online platforms. Controls 12]. Most studies indicate that these differences are also maintained were matched to the ARMS patients in terms of age, sex, migrant, in patients with schizophrenic psychoses (for reviews, see refer- and ethnic status. All participants were screened with an inclusion/ ences [1,2]). Specifically, many studies have shown that women exclusion checklist (see below). diagnosed with schizophrenia have a better performance in verbal The protocol of the EU-GEI study was approved by the institu- learning and memory [1,13,14]. The female advantage in verbal tional review boards of all study sites. EU-GEI was conducted in domains has also been found in patients with first-episode psycho- accordance with the Declaration of Helsinki. The Medical Ethics sis (FEP), while men showed a better performance in tests of Committees of all participating sites approved the study protocol. reaction time, visual memory, and executive functions [1,10]. The impact of sex on cognitive functioning in ARMS has Inclusion and exclusion criteria received considerable attention in the literature in recent years. A meta-regression analysis based on 19 studies assessing neuropsy- Inclusion criteria for ARMS patients were: aged 14–45 (most of chological performance in 1,188 ARMS patients (women, n = 523; them were between 18 and 35 years); being at-risk for psychosis as 44%) and 1,029 HC (women, n = 464; 45%) showed a trend-level defined by the comprehensive assessment of at-risk mental state significance effect of sex on cognitive performance, with females (CAARMS) [17]; adequate language skills corresponding to each performing relatively better than males [15]. Our own group inves- center; and consent to study participation. The exclusion criteria tigated sex differences in cognitive functioning in 118 ARMS were: prior experience of a psychotic episode of more than 1-week patients (women, n = 45; 38%), 88 FEP patients (women, n = 32; as determined by the CAARMS [17] and Structural Clinical Inter- 36%), and 86 HC (women, n = 41; 47%) [10]. Women performed view for Diagnostic and Statistical Manual of Mental Disorders better in the domain of verbal learning and memory whereas men (DSM Disorders (SCID)) [18]; previous treatment with an antipsy- showed a shorter reaction time during the working memory task chotic for a psychotic episode; and IQ < 60. across all groups. However, these differences did not withstand Inclusion criteria for controls were: aged 18–35; adequate lan- correction for multiple testing. Taken together, existing studies guage skills local to each center; no evidence of current or past indicate that female patients with psychotic disorders or being at psychosis (including treatment with antipsychotic medication). clinical high risk for psychosis do not perform better than males Exclusion criteria for controls were similar to those for ARMS over and above what we see in HC. participants. Additionally, controls were excluded if they met the To the best of our knowledge, the present study is the first to criteria for an ARMS status as defined by the CAARMS [17]. investigate sex differences in cognitive functioning in a large mul- tinational sample of ARMS patients by using an extended neuro- Detection procedure psychological battery and a healthy comparison group. The goal of the study was to elucidate whether sex differences in cognitive The CAARMS was used to identify ARMS patients [17]. The functioning differ between ARMS and HC subjects. Based on the CAARMS is a semi-structured interview that encompasses psychotic evidence above and our own findings, we expected a better perfor- symptoms and a range of other psychopathological symptoms pre- mance of women in the domain of verbal learning and memory sent during the psychosis prodrome. Individuals were classified as irrespective of group. being in an ARMS for psychosis if they met at least one of the following risk criteria: (i) attenuated psychotic symptoms (psychotic symptoms subthreshold either in intensity or frequency); (ii) brief Methods limited psychotic symptoms (recent episode of brief psychotic symp- toms that spontaneously resolved within 1 week); or Setting and recruitment (iii) vulnerability group (a first-degree relative with a psychotic The neuropsychological data analyzed in this study were collected disorder or a diagnosis of a schizotypal personality disorder in within the EUropean Gene–Environment Interactions (EU-GEI) combination with a significant drop in functioning). The full criteria study, which aims to identify the interactive genetic, clinical, and can be found elsewhere [17]. European Psychiatry 3 Assessment of sociodemographic and clinical characteristics binary variable with 0 and 1 describing men and women, respec- tively. Thus, the regression coefficient for sex described the stan- Sociodemographic characteristics (e.g. age, sex, ethnicity) were dardized mean difference (SMD) of women compared with men. obtained using the modified Medical Research Council sociodemo- The results are presented with and without correction for multiple graphic schedule [19]. Current cannabis frequency was assessed testing. We used the false discovery rate procedure to adjust p- with the modified version of the Cannabis Experience Question- values for multiple testing [33]. naire [20]. Data on comorbid affective and anxiety disorders were assessed with the SCID [18]. Psychiatric medication (i.e., use of antipsychotics, antidepressants, and sedatives) was obtained using a medical history questionnaire, designed by the EU-GEI group. Results The general level of functioning was assessed with the modified Sample description version of the Global Assessment of Functioning (GAF) scale [21]. The sample of the present study consisted of 343 ARMS patients (185 men, 158 women) and 67 HC subjects (34 men, 33 women). Classification and assessment of neuropsychology Sociodemographic and clinical characteristics of our sample are Neuropsychological performance of each participant was assessed presented in Table 1. Cannabis use was more frequent in male by trained psychiatrists, psychologists, and research assistants. The ARMS patients than female ARMS patients (30.51% vs. 18.46% neuropsychological tests covered the following seven domains: used cannabis at least a few times per year). With regard to attention/vigilance, reasoning/problem solving, speed of proces- comorbid affective and anxiety disorders, female ARMS patients sing, verbal learning, working memory, social cognition, and cur- showed more often a current anxiety disorder as well as posttrau- rent IQ. Test scores were assigned to cognitive domains in matic stress disorders (PTSD) compared with male ARMS patients. accordance with Measurement and Treatment Research to There were no significant sex differences regarding any current Improve Cognition in Schizophrenia (MATRICS) Consensus Cog- affective disorder (i.e., current depressive, manic, or hypomanic nitive Battery (MCCB) [22]. Tests that are not part of the MCCB episode and dysthymic disorder), neither for ARMS nor for were assigned to domains according to their most commonly used HC. With regard to psychopathology, male ARMS patients showed function. The following measures were used to cover the cognitive significantly more severe BPRS “negative symptoms” (p = 0.006) domains of interest: than female ARMS patients. There were no sex differences in ARMS and HC with regard to age, years of education, current • Attention/vigilance: Digit Span Forward subtest of the Wechsler psychiatric medication, global functioning, BPRS “positive symp- Adult Intelligence Scale-third edition (WAIS-III) [23]; toms” and BPRS “total score.” • Reasoning/problem solving: Beads Task [24]; • Speed of processing: Digit Symbol Test of the WAIS-III and the Trail-Making Test parts A and B [25]; Effects of sex and diagnostic group on cognitive functioning • Verbal Learning: Rey Auditory Verbal Learning Test [26]; • Working memory: Digit Span Backwards and Arithmetic sub- Means and standard deviations (SD) of the total group, ARMS, and tests of the WAIS-III [23]; HC are presented in Table 2. Table 3 shows the results of the mixed • Social cognition: Degraded Affect Recognition Task [27] and the effects models using neurocognitive performance as the continuous Benton Facial Recognition Test [28]; and dependent variable and sex as well as group (ARMS, HC) as fixed • Current IQ: Block Design total raw score, the information total effects factors. SMDs of the neuropsychological measures are addi- raw score and the estimate of the total IQ of the shortened WAIS- tionally presented in Figure 1. III [23,29]. In the combined sample of ARMS and HC, women recognized more angry faces in the “Degraded Faces Affect Recognition” social cognition task (p = 0.034, b = 0.25), performed better in the “Digital Assessment of psychopathology Symbol Coding” speed of processing task (p ≤ 0.001, b = 0.44) of the The Brief Psychiatric Rating Scale expanded version (BPRS-E) [30] WAIS-III, and remembered more words in the “Rey Auditory was used to assess psychopathology. Sex differences were investi- Verbal Learning Test (RAVLT) delayed recall” (p = 0.003, b = gated using the BPRS total score and the following subscales: BPRS 0.41) and “RAVLT trials 1 to 5” (p = 0.001, b = 0.40) than men. positive symptoms and BPRS negative symptoms [31]. However, after correction for multiple testing, only the differences in “Digital Symbol Coding” and the RAVLT measures remained statistically significant. Effects of diagnostic group are presented in Table 3. ARMS Statistical analyses patients performed significantly worse in all cognitive performance All statistical analyses were performed using R [32]. Because obser- scores, except in all scores of the problem solving and social vations were nonindependent, that is, observations from the same cognition tasks. center were more similar than observations from different centers, There was one statistically significant interaction between sex sex differences were analyzed using linear mixed effects models and group (ARMS, HC) on the “WAIS-III Digit Span Backwards” including sex and group (ARMS, HC) as a fixed effects factors and working memory task (p = 0.011), which was due to a significantly randomly varying intercepts per center to account for the clustering better performance of female HC compared with male HC (p < in the data. Linear mixed effects models were applied to evaluate the 0.026, b = 0.59) and a nonsignificantly worse performance of main effects of sex and group (ARMS, HC) as well as their inter- female ARMS patients compared with male ARMS patients (p = actions on cognitive functioning. Dependent variables were z- 0.186, b = 0.16). However, this sex  group interaction was no transformed before inclusion to models and sex was included as a longer significant after correction for multiple testing. 4 Stephanie Menghini-Müller et al. Table 1. Sociodemographic and clinical sample characteristics ARMS HC All Men Women p value All Men Women p value (n = 343) (n = 185) (n = 158) N (n = 67) (n = 34) (n = 33) N Age 22.4 (4.91) 22.7 (5.08) 22.1 (4.70) 0.210 343 22.9 (4.09) 23.0 (4.09) 22.7 (4.15) 0.720 67 ** Ethnicity 0.481 342 0.009 67 White 245 (71.6%) 136 (73.5%) 109 (69.4%) 42 (62.7%) 23 (67.6%) 19 (57.6%) Black 34 (9.94%) 18 (9.73%) 16 (10.2%) 10 (14.9%) 8 (23.5%) 2 (6.06%) Mixed 28 (8.19%) 16 (8.65%) 12 (7.64%) 6 (8.96%) 0 (0.0%) 6 (18.2%) Asian 11 (3.22%) 6 (3.24%) 5 (3.18%) 9 (13.4%) 3 (8.82%) 6 (18.2%) North African 12 (3.51%) 6 (3.24%) 6 (3.82%) 0 (0.0%) 0 (0.0%) 0 (0.0%) Other 12 (3.51%) 3 (1.62%) 9 (5.73%) 0 (0.0%) 0 (0.0%) 0 (0.0%) Years of education 14.4 (3.07) 14.4 (3.28) 14.4 (2.83) 0.989 302 16.1 (2.79) 16.6 (2.97) 15.6 (2.55) 0.169 65 Cannabis current frequency 0.029* 334 0.081 67 None 247 (74.0%) 121 (68.4%) 126 (80.3%) 49 (73.1%) 22 (64.7%) 27 (81.8%) Only once or twice 4 (1.20%) 2 (1.13%) 2 (1.27%) 1 (1.49%) 0 (0.0%) 1 (3.03%) A few times each year 17 (5.09%) 7 (3.95%) 10 (6.37%) 4 (5.97%) 4 (11.8%) 0 (0.0%) A few times each month 17 (5.09%) 12 (6.78%) 5 (3.18%) 7 (10.4%) 4 (11.8%) 3 (9.09%) (More than) once a week 11 (3.29%) 9 (5.08%) 2 (1.27%) 3 (4.48%) 1 (2.94%) 2 (6.06%) Every day 38 (11.4%) 26 (14.7%) 12 (7.64%) 3 (4.48%) 3 (8.82%) 0 (0.0%) Antipsychotics currently 30 (11.8%) 15 (11.6%) 15 (11.9%) 1.000 255 0 (0.0%) 0 (0.0%) 0 (0.0%) 56 Antidepressants currently 82 (32.2%) 39 (30.2%) 43 (34.1%) 0.595 255 2 (3.57%) 0 (0.0%) 2 (7.14%) 0.491 56 Sedatives currently 15 (5.88%) 7 (5.43%) 8 (6.35%) 0.963 255 1 (1.79%) 0 (0.0%) 1 (3.57%) 1.000 56 Current affective disorder 127 (37.0%) 60 (32.4%) 67 (42.4%) 0.073 343 0 (0.0%) 0 (0.0%) 0 (0.0%) 67 ** Current anxiety disorder 166 (48.4%) 73 (39.5%) 93 (58.9%) 0.001 343 5 (7.46%) 2 (5.88%) 3 (9.09%) 0.673 67 Current OCD 29 (9.70%) 16 (10.1%) 13 (9.29%) 0.975 299 0 (0.0%) 0 (0.0%) 0 (0.0%) 53 Current PTSD 34 (10.6%) 11 (6.40%) 23 (15.4%) 0.015* 321 0 (0.0%) 0 (0.0%) 0 (0.0%) 65 GAF disability, impairment 55.5 (12.3) 55.8 (12.4) 55.1 (12.1) 0.584 331 85.0 (8.98) 85.2 (8.15) 84.7 (9.92) 0.819 66 BPRS positive symptoms 7.48 (3.17) 7.67 (3.28) 7.27 (3.03) 0.254 323 3.17 (0.53) 3.13 (0.43) 3.21 (0.63) 0.550 59 BPRS negative symptoms 5.05 (2.40) 5.38 (2.65) 4.66 (2.02) 0.006** 324 3.00 (0.00) 3.00 (0.00) 3.00 (0.00) 0.325 59 BPRS total score 43.6 (10.2) 44.1 (10.6) 43.0 (9.67) 0.361 324 25.4 (2.61) 25.3 (2.24) 25.6 (3.01) 0.618 59 Abbreviations: ARMS, at-risk mental state; BPRS, Brief Psychiatric Rating Scale; GAF, Global Assessment of Functioning; HC, healthy controls; OCD, obsessive–compulsive disorder; PTSD, post- traumatic stress disorder. Continuous variables are described by means and standard deviation in brackets. * p < 0.05. ** p < 0.01. The results did not change, when age or frequent cannabis use raw score) and social cognition (i.e., Degraded Facial Affect Rec- (i.e., at least several times per week) were included as covariates. ognition Task (DFAR) angry faces total correct), whereas men outperformed women on a trend-wise level on a task of working memory (i.e., arithmetic total raw score). Additionally, our results Discussion show that ARMS patients displayed alterations in attention, current To the best of our knowledge, this is the first study investigating sex- IQ, speed of processing, verbal learning, and working memory related neurocognitive performance differences in a multinational compared with HC. However, we will not discuss this aspect any ARMS sample of this size, using a comprehensive neuropsycholog- further since it is not the focal point of the present study. ical battery and a healthy comparison group. In line with our Finally, we found a sex  group interaction effect on working hypotheses, women showed superior performance in the domain memory (i.e., WAIS-III Digit Span Backwards), which was due to of verbal learning and memory independent of whether they were a significantly better performance of female HC compared with ARMS patients or HC. Furthermore, women outperformed men on male HC and a nonsignificantly better performance of male measures of speed of processing (i.e., Digital Symbol Coding total ARMS patients compared with female ARMS patients. However, European Psychiatry 5 Table 2. Means and standard deviations of neuropsychological test data in ARMS patients and HC Total group ARMS HC All Men Women All Men Women All Men Women (n = 410) (n = 219) (n = 191) (n = 343) (n = 185) (n = 158) (n = 67) (n = 34) (n = 33) Attention WAIS-III Digit Span Forward 9.69 (2.26) 9.66 (2.19) 9.73 (2.34) 9.51 (2.20) 9.50 (2.16) 9.51 (2.24) 10.7 (2.35) 10.5 (2.18) 11.0 (2.57) Current IQ Block Design total raw score 43.8 (15.2) 44.8 (15.2) 42.7 (15.3) 42.7 (15.5) 43.8 (15.1) 41.4 (15.8) 49.3 (12.9) 49.7 (14.8) 48.9 (11.0) Estimate of total IQ 101 (17.9) 102 (18.7) 100 (17.0) 98.6 (16.8) 99.9 (17.6) 97.2 (15.9) 113 (18.1) 112 (20.5) 113 (15.7) Information total raw score 16.9 (6.56) 17.5 (6.56) 16.2 (6.51) 16.3 (6.73) 17.1 (6.71) 15.5 (6.68) 19.4 (4.98) 19.4 (5.47) 19.4 (4.52) Problem solving Beads task draws to decision 6.62 (4.63) 6.90 (5.06) 6.31 (4.11) 6.54 (4.70) 6.74 (5.20) 6.33 (4.09) 7.02 (4.29) 7.73 (4.21) 6.22 (4.32) Social cognition BFR total correct 22.3 (2.33) 22.3 (2.24) 22.3 (2.43) 22.2 (2.32) 22.3 (2.24) 22.2 (2.42) 22.6 (2.36) 22.1 (2.31) 23.1 (2.36) DFAR angry faces total 10.2 (4.90) 9.67 (4.90) 10.7 (4.84) 10.5 (4.71) 9.99 (4.79) 11.0 (4.58) 8.61 (5.53) 7.94 (5.23) 9.30 (5.82) correct DFAR frightened faces total 8.59 (4.25) 8.17 (4.21) 9.07 (4.26) 8.80 (4.09) 8.26 (4.09) 9.43 (4.02) 7.50 (4.89) 7.68 (4.85) 7.31 (5.01) correct DFAR happy faces total 12.8 (5.08) 12.5 (5.23) 13.1 (4.89) 13.1 (4.78) 12.7 (5.07) 13.5 (4.38) 11.3 (6.23) 11.4 (6.01) 11.1 (6.54) correct DFAR neutral faces total 11.4 (4.84) 11.1 (4.95) 11.6 (4.72) 11.6 (4.57) 11.3 (4.76) 12.0 (4.31) 10.2 (5.97) 10.6 (5.92) 9.81 (6.09) correct Speed of processing Digital Symbol Coding total 73.1 (16.1) 70.2 (16.6) 76.4 (15.0) 71.7 (15.8) 69.2 (16.6) 74.5 (14.4) 80.1 (15.9) 75.2 (15.9) 85.0 (14.6) raw score TMT-A time to completion 29.6 (12.3) 30.7 (13.9) 28.4 (10.1) 30.2 (12.2) 31.2 (13.6) 29.1 (10.3) 26.6 (12.8) 28.1 (15.6) 25.0 (8.62) TMT-B time to completion 70.3 (29.4) 74.6 (30.8) 65.7 (27.2) 73.2 (30.4) 77.9 (31.6) 68.0 (28.2) 56.3 (18.8) 58.0 (19.5) 54.4 (18.2) Verbal learning RAVLT delayed recall correct 10.7 (3.14) 10.2 (3.31) 11.4 (2.79) 10.6 (3.05) 10.0 (3.21) 11.2 (2.72) 11.4 (3.48) 10.9 (3.76) 12.0 (3.09) RAVLT trial 1 correct 6.82 (2.02) 6.58 (1.93) 7.09 (2.09) 6.69 (1.99) 6.45 (1.86) 6.98 (2.11) 7.43 (2.04) 7.25 (2.14) 7.64 (1.93) RAVLT trials 1–5 correct 52.2 (9.91) 50.6 (9.68) 54.0 (9.88) 51.3 (9.98) 49.9 (9.64) 53.1 (10.1) 56.3 (8.50) 54.1 (9.20) 58.7 (7.01) Working memory Arithmetic total raw score 13.5 (4.76) 14.1 (4.68) 12.8 (4.76) 13.1 (4.70) 13.8 (4.64) 12.3 (4.65) 15.5 (4.58) 15.9 (4.60) 15.1 (4.60) WAIS-III Digit Span 6.73 (2.27) 6.74 (2.28) 6.71 (2.27) 6.60 (2.19) 6.72 (2.30) 6.46 (2.06) 7.44 (2.58) 6.87 (2.21) 8.17 (2.87) Backwards Abbreviations: ARMS, at-risk mental state; BFR, Benton Facial Recognition Test; DFAR, Degraded Facial Affect Recognition Task; HC, healthy controls; RAVLT, Rey Auditory Verbal Learning Test; TMT, Trail Making Test; WAIS, Wechsler Adult Intelligence Scale. only sex differences in the total group in speed of processing and sex differences in ARMS and healthy subjects by using well- verbal learning remained significant after correction for multiple established tests to evaluate processing speed (i.e., Trail Making Test, testing. WAIS-III Digit Symbol subtest). A previous study has investigated With regard to verbal learning and memory, our finding that the sex-related cognitive performance differences in ARMS, FEP and HC female advantage is equally present in ARMS patients as in HC is in but did not include tests specifically measuring processing speed line with previous research [1,15]. Furthermore, it corroborates the [10]. However, the authors found a shorter reaction time for men in findings of an earlier study of our own group that reported no the working memory task independent of diagnostic group. They interaction effect between diagnostic group (i.e., ARMS, FEP, HC) explain the findings by a superior working memory performance and verbal learning and memory [10]. rather than generally enhanced processing speed in men as no sex Regarding processing speed, our finding that women perform differences in reaction time during the Continuous Performance Test better than men is also consistent with earlier findings from the and the Go/No-Go subtest of the Test of Attentional Performance general population [34,35] and patients with schizophrenia (TAP) were detected, while maintaining a comparable overall work- [36,37]. To the best of our knowledge, this is the first study examining ing memory performance level [10]. 6 Stephanie Menghini-Müller et al. Table 3. p values and coefficients of fixed effects of mixed effects models Group Sex Group  sex p value p value corr a Coef p value p value corr a Coef p value p value corra Coef Attention WAIS-III Digit Span Forward <0.001*** 0.002** 0.55 0.441 0.530 0.11 0.467 0.782 0.22 Current IQ Block Design total raw score <0.001*** <0.001*** 0.59 0.364 0.505 0.12 0.561 0.782 0.15 *** *** Estimate of total IQ <0.001 <0.001 0.88 0.658 0.697 0.06 0.385 0.782 0.22 *** *** Information total raw score <0.001 <0.001 0.61 0.329 0.493 0.13 0.277 0.774 0.29 Problem solving Beads task draws to decision 0.331 0.426 0.15 0.098 0.252 0.23 0.659 0.782 0.13 Social cognition BFR total correct 0.143 0.198 0.22 0.201 0.329 0.18 0.124 0.705 0.45 DFAR angry faces total correct 0.435 0.489 0.10 0.034* 0.151 0.25 0.695 0.782 0.09 DFAR frightened faces total correct 0.421 0.489 0.11 0.409 0.525 0.10 0.112 0.705 0.40 DFAR happy faces total correct 0.531 0.563 0.08 0.547 0.615 0.07 0.301 0.774 0.24 DFAR neutral faces total correct 0.922 0.922 0.01 0.922 0.922 0.01 0.266 0.774 0.27 Speed of processing Digital Symbol Coding total raw score <0.001*** <0.001*** 0.63 <0.001*** 0.011* 0.44 0.157 0.705 0.37 * * TMT-A time to completion 0.017 0.028 0.36 0.162 0.291 0.20 0.549 0.782 0.17 *** *** TMT-B time to completion <0.001 <0.001 0.65 0.122 0.261 0.21 0.641 0.782 0.13 Verbal learning RAVLT delayed recall correct 0.026* 0.040* 0.33 0.003** 0.019* 0.41 0.936 0.936 0.02 * * RAVLT trial 1 correct 0.016 0.028 0.34 0.069 0.206 0.24 0.874 0.926 0.04 *** *** ** * RAVLT trials 1–5 correct <0.001 <0.001 0.49 0.001 0.011 0.40 0.593 0.782 0.13 Working memory Arithmetic total raw score <0.001*** <0.001*** 0.60 0.064 0.206 0.24 0.580 0.782 0.14 *** ** * WAIS-III Digit Span Backwards <0.001 0.002 0.51 0.130 0.261 0.22 0.011 0.197 0.75 Abbreviations: BFR, Benton Facial Recognition Test; coef, y-standardized regression coefficients of fixed effects; DFAR, Degraded Facial Affect Recognition Task; RAVLT, Rey Auditory Verbal Learning Test; TMT, Trail Making Test; WAIS, Wechsler Adult Intelligence Scale. a Corrected for multiple testing using Benjamini–Hochberg method. * p < 0.05. ** p < 0.01. *** p < 0.001. A strength of our study is that we examined sex differences in comparison to the ARMS group, which reduced the statistical with well-established tests using the classification of the power to detect interaction effects between sex and group. Finally, MATRICS panel [22,38]. As the MCCB domains are well known it is important to note that sex-related cognitive performance in schizophrenia research, this may help future studies to compare differences depend on a wide variety of conditions, for example, sex-related cognitive performance differences in ARMS and the severity of symptoms and especially the fluctuation of estrogen schizophrenic patients. Furthermore, this is the first study to levels during the menstrual cycle in women (for review, see investigate sex differences in cognitive functioning in an ARMS reference [1]). There is evidence that high levels of estrogen at sample of this size. the mid-luteal point are associated with better verbal memory and However, there are some limitations to the present study that diminished spatial ability [39]. Thus, it is possible that some need to be acknowledged. Our neuropsychological test battery was effects would have changed if we had measured women at a originally selected to identify genetic and environmental interac- specific time point during their monthly cycle. Unfortunately, in tions in psychosis and not specifically to detect sex differences. our study no assessment of the time point during the monthly Accordingly, the test battery did not include other sensitive tasks cycle was performed. to detect sex differences such as visuo-spatial tasks. Additionally, Taken together, our findings indicate that sex differences in the domain of visual learning in the MATRICS consensus battery cognitive functioning in ARMS patients are very similar to those was not covered. Furthermore, our control group was rather small seen in the general population and in schizophrenia patients. European Psychiatry 7 Current Problem Social Speed Verbal Working Attention IQ solving cognition of processing learning memory 1.0 0.5 ARMS 0.0 −0.5 Standardized mean difference from men 1.0 0.5 HC 0.0 −0.5 1.0 0.5 Total group 0.0 −0.5 e on e e n n e ds Q ct ct ct ct ct ct ct ct d or or or io tio or ar lI re rre rre re rre rre rre re ar si et sc sc sc sc e a rw ci or r r w pl l o o co o ot co o co p de ck aw w aw w fo lc c lc lc c om m t a ra al l l l1 of ba co ta ta ta ta l 5 an to lr lr lr ca c t 1− al to to to to to ria te ta ta ta Sp s an re to to t aw rm ma to to to to R s es s s AV LT t s Sp e e ce ce ce d al BF it n n c m tim ng c ye dr i ig tri st i fa fa fa a ig io AV et −T A ti it D lf la i E sk es at od ig LT m ym −B ry FA ned py ra de R III D ta T− ith D lC ng ap ut S− T III LT te fo s k M Ar M FA R a ne bo R h ad oc S− AI gh In −T AV R Bl Be R W FA fri AI R FA lS W D R D D ita D ig D Figure 1. Cognitive performance of women compared with men in at-risk mental state for psychosis individuals and healthy controls. The dotted horizontal line at zero represents the performance of men. Differences are expressed in units of standard deviation and are significant if the 95% confidence interval (vertical line) does not overlap with zero. Variables with a minus sign were reversed so that positive scores always represent good performance. Abbreviations: RAVLT, Rey Auditory Verbal Learning Test; TMT, Trail Making Test; WAIS, Wechsler Adult Intelligence Scale. Acknowledgments. We thank all patients who participated in the study as Academia Award). The French cohort was supported by the French Ministry well as the referring specialists. grant (PHRC AOM07-118) and by Fondation Pierre Deniker (CMLF). B.P.R. was supported by the Netherlands Organization for Scientific (VIDI Financial Support. This work was supported by the European Union grant number 91718336). (European Community’s Seventh Framework Program [grant number HEALTH-F2-2010-241909; Project EU-GEI]). M.J.K. was supported by a Med- ical Research Council Fellowship (grant number MR/J008915/1). N.B.-V. was supported by the Ministerio de Ciencia, Innovación e Universidades (PSI2017- Conflict of Interest. All authors declare not to have any conflicts of interest 87512-C2-1-R) and the Generalitat de Catalunya (2017SGR1612 and ICREA that might be interpreted as influencing the content of the manuscript. 8 Stephanie Menghini-Müller et al. References schizophrenia: the NIMH-MATRICS conference to select cognitive domains and test criteria. Biol Psychiatry. 2004;56(5):301–307. [1] Riecher-Rössler A, Butler S, Kulkarni J. Sex and gender differences in [23] Wechsler D. Wechsler Adult Intelligence Scales, third edition (WAIS-III). schizophrenic psychoses—a critical review. Arch Womens Ment Health. San Antonio, TX: The Psychological Corporation, 1997. 2018;21(6):627–648. [24] Huq SF, Garety PA, Hemsley DR. Probabilistic judgements in deluded and [2] Mendrek A, Mancini-Marie A. Sex/gender differences in the brain and non-deluded subjects. Q J Exp Psychol. 1988;40A:801–812. cognition in schizophrenia. Neurosci Biobehav Rev. 2016;67:57–78. [25] Battery AIT. Manual of directions and scoring. Washington, DC: War [3] Kahn RS, Keefe RS. Schizophrenia is a cognitive illness: time for a change Department, Adjutant General's Office, 1944. in focus. JAMA Psychiatry. 2013;70:1107. [26] Rey A. L'Examen clinique en psychologie. Paris, France: Presses Universi- [4] Hauser M, Zhang JP, Sheridan EM, Burdick KE, Mogil R, Kane JM, et al. taires de France, 1964. Neuropsychological test performance to enhance identification of subjects [27] van't Wout M, Aleman A, Kessels RP, Laroi F, Kahn RS. Emotional at clinical high risk for psychosis and to be most promising for predictive processing in a non-clinical psychosis-prone sample. Schizophr Res. algorithms for conversion to psychosis: a meta-analysis. J Clin Psychiatry. 2004;68:271–281. 2017;78(1):e28–e40. [28] Benton AL, Silvan AB, Hamsher KD, Varney NR, Spreen O. Benton's test [5] Studerus E, Papmeyer M, Riecher-Rössler A. Neurocognition and motor of facial recognition. New York, NY: Oxford University Press, 1983. functioning in the prediction of psychosis. In: Riecher-Rössler A, McGorry [29] Velthorst E, Levine SZ, Henquet C, De Haan L, Van Os J, Myin-Germeys I, PD, editors. Early detection and intervention in psychosis: state of the art et al. To cut a short test even shorter: reliability and validity of a brief and future perspectives. Key issues in mental health. 181. Basel, Switzer- assessment of intellectual ability in schizophrenia—a control-case family land: Karger; 2016. p. 116–132. study. Cogn Neuropsychiatry. 2013;18(6):574–593. [6] Riecher-Rössler A, Pflueger MO, Aston J, Borgwardt SJ, Warrick JB, [30] Ventura J, Lukoff D, Nuechterlein KH, Liberman RP, Green MF, Shaner A. Gschwandtner U, et al. Efficacy of using cognitive status in predicting Brief Psychiatric Rating Scale (BPRS) expanded version: scales, anchor psychosis: a 7-year follow-up. Biol Psychiatry. 2009;66:1023–1030. points, and administration manual. Int J Methods Psychiatr Res. 1993;3: [7] Riecher-Rössler A, Studerus E. Prediction of conversion to psychosis in 227–243. individuals with an at-risk mental state: a brief update on recent develop- [31] Shafer A, Dazzi F, Ventura J. Factor structure of the Brief Psychiatric ments. Curr Opin Psychiatry. 2017;30(3):209–219. Rating Scale-Expanded (BPRS-E) in a large hospitalized sample. J Psy- [8] Michel C, Ruhrmann S, Schimmelmann BG, Klosterkötter J, Schultze- chiatr Res. 2017;93:79–86. Lutter F. A stratified model for psychosis prediction in clinical practice. [32] R Core Team. A language and environment for statistical computing. Schizophr Bull. 2014;40(6):1533–1542. Vienna, Austria: Computing RFfS, 2017. [9] Hyde JS. How large are cognitive gender differences—a meta-analysis [33] Benjamini Y, Hochberg Y. Controlling the false discovery rate—a practival using omega-2 and D. Am Psychol. 1981;36:892–901. and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. [10] Ittig S, Studerus E, Papmeyer M, Uttinger M, Koranyi S, Ramyead A, et al. 1995(57):289–300. Sex differences in cognitive functioning in at-risk mental state for psycho- [34] Burns NR, Nettelbeck T. Inspection time and speed of processing: sex sis, first episode psychosis and healthy control subjects. Eur Psychiatry. differences on perceptual speed but not IT. Personal Individ Diff. 2005;39: 2015;30(2):242–250. 439–446. [11] Halpern DF. A cognitive-process taxonomy for sex differences in cognitive [35] Jorm AF, Anstey KJ, Christensen H, Rodgers B. Gender differences in abilities. Curr Direct Psychol Sci. 2004;13(4):135–139. cognitive abilities: the mediating role of health state and health habits. [12] Miller DI, Halpern DF. The new science of cognitive sex differences. Intelligence. 2004;32:7–23. Trends Cogn Sci. 2014;18(1):37–45. [36] Vaskinn A, Sundet K, Simonsen C, Hellvin T, Melle I, Andreassen OA. Sex [13] Zhang BH, Han M, Zhang XY, Hui L, Jiang SR, Yang FD, et al. Gender differences in neuropsychological performance and social functioning in differences in cognitive deficits in schizophrenia with and without diabe- schizophrenia and bipolar disorder. Neuropsychology. 2011;25(4): tes. Compr Psychiatry. 2015;63:1–9. 499–510. [14] Bozikas VP, Kosmidis MH, Peltekis A, Giannakou M, Nimatoudis I, [37] Torniainen M, Suvisaari J, Partonen T, Castaneda AE, Kuha A, Perala J, Karavatos A, et al. Sex differences in neuropsychological functioning et al. Sex differences in cognition among persons with schizophrenia and among schizophrenia patients. Austr N Z J Psychiatry. 2010;44:333–341. healthy first-degree relatives. Psychiatry Res. 2011;188(1):7–12. [15] Fusar-Poli P, Deste G, Smieskova R, Barlati S, Yung AR, Howes O, et al. [38] Nuechterlein KH, Green MF, Kern RS, Baade LE, Barch DM, Cohen JD, Cognitive functioning in prodromal psychosis: a meta-analysis. Archiv et al. The MATRICS Consensus Cognitive Battery, part 1: test selection, Gen Psychiatry. 2012;69(6):562–571. reliability, and validity. Am J Psychiatry. 2008;165(2):203–213. [16] Kraan TC, Velthorst E, Themmen M, Valmaggia L, Kempton MJ, [39] Hampson E. Variations in sex-related cognitive abilities across the men- McGuire P, et al. Child maltreatment and clinical outcome in individuals strual cycle. Brain Cogn. 1990;14(1):26–43. at ultra-high risk for psychosis in the EU-GEI High Risk Study. Schizophr Bull. 2018;44(3):584–592. [17] Yung AR, Yuen HP, McGorry PD, Phillips LJ, Kelly D, Dell'Olio M, et al. Mapping the onset of psychosis: the Comprehensive Assessment of At-Risk Mental States. Austr N Z J Psychiatry. 2005;39(11–12):964–971. Appendix [18] Wittchen H-U, Zauding M, Fydrich T. Strukturiertes klinisches interview für DSM-IV. Achse-I: psychische störungen. Göttingen, Germany: Hogrefe, 1997. EU-GEI High Risk Study Group—Author List [19] Mallett R. Sociodemographic schedule. London, UK: Section of Social Philip McGuire2, Lucia R. Valmaggia3, Matthew J. Kempton2, Maria Calem2, Psychiatry, Institute of Psychiatry, 1997. Stefania Tognin2, Gemma Modinos2, Lieuwe de Haan4,7, Mark van der Gaag8,10, [20] Barkus EJ, Stirling J, Hopkins RS, Lewis S. Cannabis-induced psychosis- Eva Velthorst5,11, Tamar C. Kraan6, Daniella S. van Dam4, Nadine Burger7, like experiences are associated with high schizotypy. Psychopathology. Barnaby Nelson12,13, Patrick McGorry12,13, G. Paul Amminger12,13, Christos 2006;39(4):175–178. Pantelis14, Athena Politis12,13, Joanne Goodall12,13, Anita Riecher-Rössler1, Stefan [21] Goldman HH, Skodol AE, Lave TR. Revising axis V for DSM-IV: a review Borgwardt1, Charlotte Rapp1, Sarah Ittig1, Erich Studerus1, Renata Smieskova1, of measures of social functioning. Am J Psychiatry. 1992;149(9): Rodrigo Bressan15, Ary Gadelha15, Elisa Brietzke16, Graccielle Asevedo15, Elson 1148–1156. Asevedo15, Andre Zugman15, Neus Barrantes-Vidal17, Tecelli Domínguez-Mart- [22] Green MF, Nuechterlein KH, Gold JM, Barch DM, Cohen J, Essock S, et al. ínez18, Anna Racioppi19, Lídia Hinojosa-Marqués19, Thomas R. Kwapil20, Manel Approaching a consensus cognitive battery for clinical trials in Monsonet19, Mathilde Kazes21, Claire Daban21, Julie Bourgin21, Olivier Gay21, European Psychiatry 9 Célia Mam-Lam-Fook21, Marie-Odile Krebs21, Dorte Nordholm22, Lasse Neurociências Clínicas, Depto Psiquiatria, Escola Paulista de Medicina, Uni- Randers22, Kristine Krakauer22, Louise Glenthøj22, Birte Glenthøj23, Merete versidade Federal de São Paulo—UNIFESP, São Paulo, Brazil; 16Depto Psiquia- Nordentoft22, Stephan Ruhrmann24, Dominika Gebhard24, Julia Arnhold25, tria, Escola Paulista de Medicina, Universidade Federal de São Paulo— Joachim Klosterkötter24, Gabriele Sachs26, Iris Lasser26, Bernadette Winklbaur26, UNIFESP, São Paulo, Brazil; 17Departament de Psicologia Clínica i de la Salut Philippe A. Delespaul27,28, Bart P. Rutten29, and Jim van Os29,30. (Universitat Autònoma de Barcelona), Fundació Sanitària Sant Pere Claver (Spain), Spanish Mental Health Research Network (CIBERSAM), Spain; 18 CONACYT-Dirección de Investigaciones Epidemiológicas y Psicosociales, Affiliations Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico; 19Departa- 1 ment de Psicologia Clínica i de la Salut (Universitat Autònoma de Barcelona), University Psychiatric Hospital, CH-4002 Basel, Switzerland; 2Department of Bellaterra, Spain; 20Department of Psychology, University of Illinois at Urbana- Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s Champaign, Urbana, Illinois, USA; 21University Paris Descartes, GHU Paris College London, London SE5 8AF, United Kingdom; 3Department of Psychol- Sainte-Anne, C’JAAD, Service Hospitalo-Universitaire, Inserm 1266, Institut de ogy, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, Psychiatrie (CNRS 3557) Paris, France; 22Mental Health Center Copenhagen and London SE5 8AF, United Kingdom; 4Amsterdam UMC, University of Amster- Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, dam, Psychiatry, Department Early Psychosis, Amsterdam, The Netherlands; CINS, Mental Health Center Glostrup, Mental Health Services in the Capital 5 Department of Psychiatry and Seaver Center for Research and Treatment, Region of Copenhagen, University of Copenhagen, Copenhagen, Denmark; Icahn School of Medicine at Mount Sinai, New York, USA; 6Mental Health 23 Centre for Neuropsychiatric Schizophrenia Research (CNSR) & Centre for Institute Arkin, Amsterdam, The Netherlands; 7Arkin Amsterdam; 8VU Uni- Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), versity, Faculty of Behavioral and Movement Sciences, Department of Clinical Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Psychology and Amsterdam Public Mental Health Research Institute, 1081 BT 24 Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Amsterdam, The Netherlands; 9Mental Health Institute Noord-Holland Noord, Germany; 25Psyberlin, Berlin, Germany; 26Medical University of Vienna, Depart- Hoorn, The Netherlands; 10Parnassia Psychiatric Institute, Department of ment of Psychiatry and Psychotherapy, Vienna, Austria; 27Department of Psy- Psychosis Research, 2512 HN The Hague, The Netherlands; 11Early Psychosis chiatry and Neuropsychology, School for Mental Health and Neuroscience, Section, Department of Psychiatry, Academic Medical Centre, University of Maastricht University Medical Centre, 6200 MD 464 Maastricht, The Nether- Amsterdam, Amsterdam, The Netherlands; 12Orygen, The National Centre of lands; 28Mondriaan Mental Health Trust, 4436 CX Heerlen, The Netherlands; Excellence in Youth Mental Health, University of Melbourne, Melbourne, 29 Medical University of Vienna, Department of Psychiatry and Psychotherapy; Australia; 13Centre for Youth Mental Health, University of Melbourne, Park- 30 Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuro- ville, Victoria 485 3052, Australia; 14Melbourne Neuropsychiatry Centre, The science, King’s College London, London SE5 8AF, United Kingdom. University of Melbourne, Melbourne, Australia; 15LiNC—Lab Interdisciplinar