Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-28T03:03:05.019Z Has data issue: false hasContentIssue false

Difficulties during delivery, brain ventricle enlargement and cognitive impairment in first episode psychosis

Published online by Cambridge University Press:  28 November 2023

Ana Costas-Carrera
Affiliation:
Hospital Universitario Central de Asturias (HUCA), Oviedo, Spain
Norma Verdolini
Affiliation:
Department of Mental Health, Umbria 1 Mental Health Center, Perugia, Italy
Clemente Garcia-Rizo*
Affiliation:
Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, University of Barcelona, Barcelona, Spain Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
Gisela Mezquida
Affiliation:
Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, University of Barcelona, Barcelona, Spain Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain Department of Basic Clinical Practice, Pharmacology Unit, University of Barcelona, Barcelona, Spain
Joost Janssen
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
Isabel Valli*
Affiliation:
Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain Institute of Psychiatry Psychology and Neuroscience, King's College London, UK
Iluminada Corripio
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Department of Psychiatry, Institut d'Investigació Biomèdica Sant Pau, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
Ana M. Sanchez-Torres
Affiliation:
Department of Psychiatry, Navarra University Hospital, Spain Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
Miquel Bioque
Affiliation:
Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, University of Barcelona, Barcelona, Spain Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
Antonio Lobo
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Department of Medicine and Psychiatry, University of Zaragoza, Zaragoza, Spain Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain
Ana Gonzalez-Pinto
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Department of Psychiatry, Hospital Universitario de Alava, UPV/EHU, BIOARABA, Spain
Marta Rapado-Castro
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, 161 Barry Street, Carlton South, Victoria 3053, Australia
Eduard Vieta
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain Bipolar and Depressive Disorders Unit, Hospital Clinic de Barcelona, Institute of Neurosciences, Barcelona, Spain
Helena De la Serna
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain Department of Child and Adolescent Psychiatry and Psychology, Institute of Neuroscience, Hospital Clínic de Barcelona, Barcelona, Spain
Anna Mane
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Hospital del Mar Medical Research Institute (IMIM), Pompeu Fabra University, Barcelona, Spain
Alexandra Roldan
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Department of Psychiatry, Institut d'Investigació Biomèdica Sant Pau, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
Nicolas Crossley
Affiliation:
Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile Department of Psychiatry, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
Rafael Penades
Affiliation:
Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, University of Barcelona, Barcelona, Spain Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
Manuel J. Cuesta
Affiliation:
Department of Psychiatry, Navarra University Hospital, Spain Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
Mara Parellada
Affiliation:
Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, School of Medicine, Universidad Complutense, Madrid, Spain
Miquel Bernardo
Affiliation:
Barcelona Clínic Schizophrenia Unit (BCSU), Neuroscience Institute, Hospital Clínic de Barcelona, University of Barcelona, Barcelona, Spain Centro de Investigación Biomédica en red de salud Mental (CIBERSAM), Spain Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
PEPs group
Affiliation:
Hospital Universitario Central de Asturias (HUCA), Oviedo, Spain
*
Corresponding author: Clemente Garcia-Rizo; Email: [email protected]; Isabel Valli; Email: [email protected]
Corresponding author: Clemente Garcia-Rizo; Email: [email protected]; Isabel Valli; Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Background

Patients with a first episode of psychosis (FEP) display clinical, cognitive, and structural brain abnormalities at illness onset. Ventricular enlargement has been identified in schizophrenia since the initial development of neuroimaging techniques. Obstetric abnormalities have been associated with an increased risk of developing psychosis but also with cognitive impairment and brain structure abnormalities. Difficulties during delivery are associated with a higher risk of birth asphyxia leading to brain structural abnormalities, such as ventriculomegaly, which has been related to cognitive disturbances.

Methods

We examined differences in ventricular size between 142 FEP patients and 123 healthy control participants using magnetic resonance imaging. Obstetric complications were evaluated using the Lewis–Murray scale. We examined the impact of obstetric difficulties during delivery on ventricle size as well as the possible relationship between ventricle size and cognitive impairment in both groups.

Results

FEP patients displayed significantly larger third ventricle size compared with healthy controls. Third ventricle enlargement was associated with diagnosis (higher volume in patients), with difficulties during delivery (higher volume in subjects with difficulties), and was highest in patients with difficulties during delivery. Verbal memory was significantly associated with third ventricle to brain ratio.

Conclusions

Our results suggest that difficulties during delivery might be significant contributors to the ventricular enlargement historically described in schizophrenia. Thus, obstetric complications may contribute to the development of psychosis through changes in brain architecture.

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

Introduction

Schizophrenia is a complex disorder characterized by psychotic symptoms and associated with increased medical co-morbidity and reduced life expectancy (Kirkpatrick et al., Reference Kirkpatrick, Miller, Garcia-Rizo, Fernandez-Egea, García-Rizo and Fernandez-Egea2013). Schizophrenia is considered to result from a gene–environment interaction with several contributing risk factors, including obstetric complications (OCs) (Cannon, Jones, & Murray, Reference Cannon, Jones and Murray2002; Davies et al., Reference Davies, Segre, Estradé, Radua, De Micheli, Provenzani and Fusar-Poli2020). In terms of patients' outcomes, recent research highlights the influence of pre and perinatal insults on measures of cognition (Amoretti et al., Reference Amoretti, Rabelo-da-Ponte, Garriga, Forte, Penadés, Vieta and Garcia-Rizo2022), psychopathology (Peralta et al., Reference Peralta, de Jalón, Campos, Zandio, Sanchez-Torres and Cuesta2011; Verdolini et al., Reference Verdolini, Mezquida, Valli, Garcia-Rizo, Cuesta, Vieta and Balanzá-Martínez2023), and brain structure (Costas-Carrera, Garcia-Rizo, Bitanihirwe, & Penadés, Reference Costas-Carrera, Garcia-Rizo, Bitanihirwe and Penadés2020), but also metabolic parameters (Garcia-Rizo et al., Reference Garcia-Rizo, Cabrera, Bioque, Mezquida, Lobo and Gonzalez-Pinto2022, Reference García-Rizo, Bioque, Mezquida, Amoretti, Cuesta, Díaz-Caneja and Selva-Vera2020; Garriga et al., Reference Garriga, Fernandez-Egea, Mallorqui, Serrano, Oliveira, Parellada and Garcia-Rizo2019).

Ventricular enlargement has been widely described in patients with schizophrenia, initially, almost a century ago, using pneumoencephalographic imaging (Jacobi & Winkler, Reference Jacobi and Winkler1927) and then, in the seminal study by Johnstone et al. through computerized axial tomography (Johnstone, Frith, Crow, Husband, & Kreel, Reference Johnstone, Frith, Crow, Husband and Kreel1976). Subsequent meta-analyses confirmed the finding (Kuo & Pogue-Geile, Reference Kuo and Pogue-Geile2019; Van Horn & McManus, Reference Van Horn and McManus1992; Wright et al., Reference Wright, Rabe-Hesketh, Woodruff, David, Murray and Bullmore2000), describing enlargements in lateral ventricles and the third ventricle with medium-to-large effect sizes. Meta-analyses reported ventricular enlargements with moderate effect sizes in chronic patients but also in antipsychotic naïve first episode psychosis (FEP) patients, suggesting that the enlargement precedes psychotropic medication use (Haijma et al., Reference Haijma, Van Haren, Cahn, Koolschijn, Hulshoff Pol and Kahn2013) and is related to developmental abnormalities, signaling a neurodevelopmental disturbance. Similar findings in lateral ventricles have also been reported in individuals with a high risk for psychosis (Sasabayashi et al., Reference Sasabayashi, Takayanagi, Takahashi, Katagiri, Sakuma, Obara and Suzuki2020) but not observed in first-degree relatives (Cuesta et al., Reference Cuesta, Lecumberri, Cabada, Moreno-Izco, Ribeiro, López-Ilundain and Gómez2017) or in affective psychosis (Nakamura et al., Reference Nakamura, Salisbury, Hirayasu, Bouix, Pohl, Yoshida and McCarley2007).

The ventricle-to-brain ratio (VBR) is a brain volumetric measurement calculated as a ratio of ventricular volume (i.e. lateral, III, and IV ventricles) to brain parenchymal volume (total white and gray matter) (Tate, Reference Tate, Kreutzer, DeLuca and Caplan2018). The VBR is able to capture global atrophic changes in aging, disease, and/or injury and provides a measure of atrophy that is directly comparable to that of other subjects. A higher VBR is associated with volume decrease in different brain areas such as the thalamus, striatum, and temporal lobe in patients diagnosed with schizophrenia (Gaser, Nenadic, Buchsbaum, Hazlett, & Buchsbaum, Reference Gaser, Nenadic, Buchsbaum, Hazlett and Buchsbaum2004). These areas are involved in multiple cognitive domains, such as attention, executive function, and verbal memory.

In schizophrenia, ventriculomegaly is associated with negative symptoms and cognitive deficits (Konishi et al., Reference Konishi, del Re, Bouix, Blokland, Mesholam-Gately, Woodberry and McCarley2018), with more significant enlargement reported for patients with global cognitive impairment compared to those whose cognition is preserved (Yasuda et al., Reference Yasuda, Okada, Nemoto, Fukunaga, Yamamori, Ohi and Hashimoto2020). In FEP patients lateral and third ventricle volumes were associated with the severity of negative symptoms (Cuesta et al., Reference Cuesta, Lecumberri, Cabada, Moreno-Izco, Ribeiro, López-Ilundain and Gómez2017).

The volume of the third ventricle, in particular, is the most frequently associated with deficits in neuropsychological performance, suggesting the involvement of periventricular diencephalic structures (Bornstein, Schwarzkopf, Olson, & Nasrallah, Reference Bornstein, Schwarzkopf, Olson and Nasrallah1992). Cognitive impairment is a core feature of schizophrenia with attention, working memory, executive function, and verbal memory as the most affected domains (Valli, Tognin, Fusar-Poli, & Mechelli, Reference Valli, Tognin, Fusar-Poli and Mechelli2012). These deficits can also be observed before illness onset and are associated with measures of outcome (Bowie & Harvey, Reference Bowie and Harvey2006; Valli et al., Reference Valli, Tognin, Fusar-Poli and Mechelli2012). In FEP patients cognitive impairment is related to negative symptoms and greater total PANNS score at follow-up (Mezquida et al., Reference Mezquida, Amoretti, Bioque, García-Rizo, Sánchez-Torres, Pina-Camacho and Bernardo2023).

OCs increase the risk of developing psychotic disorders, particularly schizophrenia (Cannon et al., Reference Cannon, Jones and Murray2002; Davies et al., Reference Davies, Segre, Estradé, Radua, De Micheli, Provenzani and Fusar-Poli2020), and have been associated with an earlier age of onset (Baeza et al., Reference Baeza, De La Serna, Amoretti, Cuesta, Díaz-Caneja, Mezquida and Balanza2021) and more severe psychopathology (Peralta et al., Reference Peralta, García de Jalón, Moreno-Izco, Peralta, Janda, Sánchez-Torres and Zandio2022). However, OCs are heterogeneous phenomena and recent research highlights the importance to differentiate between events occurring during gestation and during delivery (Mezquida et al., Reference Mezquida, Fernandez-Egea, Treen, Mané, Bergé, Savulich and Garcia-Rizo2018). In individuals with psychosis, exposure to difficulties during delivery is associated with several outcome measures in terms of psychopathology (Mezquida et al., Reference Mezquida, Fernández-Egea, Treen, Mané, Bergé, Savulich and García-Rizo2021), cognition (Sagué-Vilavella et al., Reference Sagué-Vilavella, Amoretti, Garriga, Mezquida, Williams, Serra-Navarro and Verdolini2022), and brain structure (Smith et al., Reference Smith, Thornton, Lang, MacEwan, Kopala, Su and Honer2015; Wortinger et al., Reference Wortinger, Engen, Barth, Andreassen, Nordbø Jørgensen and Agartz2020).

Delivery problems include multiple conditions such as premature rupture of membranes, umbilical cord prolapse, complicated cesarean delivery, and abnormal fetal presentation or use of forceps (Dars, Malik, Samreen, & Kazi, Reference Dars, Malik, Samreen and Kazi2014; Ecevit et al., Reference Ecevit, Anuk-Ince, Yapakç, Kupana-Ayva, Kurt, Yanik and Tarcan2014; Leung & Lao, Reference Leung and Lao2013; Mukhopadhyay & Arulkumaran, Reference Mukhopadhyay and Arulkumaran2002).

Among delivery problems, hypoxia (OR 1.63), rupture of membranes (OR 1.86), and particularly premature rupture of membranes (OR 2.29) are significant risk factors for psychotic disorders (Davies et al., Reference Davies, Segre, Estradé, Radua, De Micheli, Provenzani and Fusar-Poli2020). The common mechanism associated with increased schizophrenia risk is considered to involve fetal hypoxia (Cannon et al., Reference Cannon, Jones and Murray2002), a finding particularly robust for early-onset schizophrenia (Rosso et al., Reference Rosso, Cannon, Huttunen, Huttunen, Lönnqvist and Gasperoni2000). During delivery, the infant's brain is susceptible to different regional patterns of injury depending on the severity and duration of hypoxia and on gestational age but mostly affecting brain areas such as the parasagittal cortex, hippocampus, thalamus, and basal ganglia (De Haan et al., Reference De Haan, Wyatt, Roth, Vargha-Khadem, Gadian and Mishkin2006; Herrera-Marschitz et al., Reference Herrera-Marschitz, Neira-Pena, Rojas-Mancilla, Espina-Marchant, Esmar, Perez and Gebicke-Haerter2014; Mercogliano & Poddar, Reference Mercogliano and Poddar2021). The white matter dorsal and lateral to the external angles of the lateral ventricles is also sensitive to hypoxia, which can result in periventricular leukomalacia and over time may lead to ventriculomegaly (Collins & Popek, Reference Collins and Popek2018). The effect of asphyxia on white matter has been reported to be greater in patients with schizophrenia than in healthy controls (Wortinger et al., Reference Wortinger, Barth, Nerland, Jørgensen, Shadrin, Szabo and Agartz2021), suggesting an interaction between genetic predisposition and perinatal environmental exposures in the development of schizophrenia (Ursini et al., Reference Ursini, Punzi, Chen, Marenco, Robinson, Porcelli and Weinberger2018). However, the latter is still debated (Vassos et al., Reference Vassos, Kou, Tosato, Maxwell, Dennison, Legge and Murray2022) and other studies did not observe a significant difference in the effect of asphyxia on the brain between patients and controls (Wortinger et al., Reference Wortinger, Engen, Barth, Andreassen, Nordbø Jørgensen and Agartz2020).

In schizophrenia, perinatal complications have been associated with impairments across most cognitive domains. However, in a recent meta-analysis, patients with schizophrenia exposed to OC showed poorer performance specifically in terms of verbal memory and working memory compared to patients with no OC history (Amoretti et al., Reference Amoretti, Rabelo-da-Ponte, Garriga, Forte, Penadés, Vieta and Garcia-Rizo2022).

We, therefore, sought to examine the impact of difficulties during delivery on these two cognitive domains and on ventricular volumes. We focused on patients with FEP rather than established schizophrenia in order to minimize the potential impact of important confounders such as protracted illness and medication exposure.

We hypothesized that difficulties during delivery would be associated with increased ventricular size, especially in the FEP group compared to HC participants, with an interaction between group and exposure. We also hypothesized that such enlargement would be related to worse cognitive functioning in the two aforementioned cognitive domains, working memory, and verbal memory.

Material and methods

This study is a part of a multicenter study, (the PEPs study ‘phenotype–genotype and environmental interaction. Application of a predictive model in first psychotic episodes’), which is a longitudinal cohort study examining gene × environment interactions on the pathway to psychosis.

Participants

The sample of the PEPs study included 335 FEP patients and 253 HC, recruited between January 2009 and December 2011. The inclusion criteria and characteristics of the study have been previously described in detail (Salagre et al., Reference Salagre, Arango, Artigas, Ayuso-Mateos, Bernardo, Castro-Fornieles and Vieta2019). Briefly, subjects with FEP aged 7–35 years, presenting psychotic symptoms for less than 12 months, were recruited from the inpatient and outpatient units of 16 participating Spanish centers, members of the Center of Biomedical Research Network on Mental Health (CIBERSAM). Healthy controls were recruited at each site through advertisements and matched with patients by age (±10%), sex and parental socio-economic status (SES), measured with the Hollingshead-Redlich scale (±1 level). For the neuroimaging component of the study, a maximum time of 6 months was established from inclusion to scan time. All centers received the approval of their respective Independent Ethics Committee. Written informed consent was obtained from all participants prior to their participation in the study, and from parents/legal guardians for children under 16 years of age (children gave assent). In the present study, from the total sample, we included 142 FEP and 123 HC for whom both magnetic resonance imaging and data regarding obstetric complications exposure were available.

History of obstetric complications (OCs) assessment

OCs were assessed using the Lewis–Murray scale through a maternal interview (Lewis, Owen, & Murray, Reference Lewis, Owen, Murray, Schulz and Tamminga1989). The scale groups OCs in three categories, A, B, and C (Cannon et al., Reference Cannon, Jones and Murray2002; Mezquida et al., Reference Mezquida, Fernandez-Egea, Treen, Mané, Bergé, Savulich and Garcia-Rizo2018) according to the type of complication defined as follows:

  1. A. Complications of pregnancy (syphilis or rubella, rhesus isoimmunization/Rh incompatibility, severe preeclampsia, requiring hospitalization or induction of labor, and bleeding before delivery or threatened abortion).

  2. B. Abnormal fetal growth and development (twin delivery, preterm birth before 37 weeks, or long-term after 42 weeks, weight at birth less than 2500 g, and any important physical abnormality).

  3. C. Difficulties in delivery (premature rupture of membranes, duration of delivery more than 36 h or less than 3 h, umbilical cord prolapse, complicated cesarean delivery, abnormal fetal presentation, use of forceps, and being in an incubator for more than 4 weeks).

As our aim was to evaluate difficulties during delivery, patients were stratified as having or not having any event described in group C.

Image acquisition and processing

The MRI acquisition protocol for each scanner is described in online Supplementary Material. The FreeSurfer analysis package (v5.3, https://surfer.nmr.mgh.harvard.edu/) was used to generate measurements of cortical thickness and both cortical and subcortical volumes including ventricular volumes. The standard FreeSurfer processing pipeline was employed, which follows the workflow: motion and bias field correction, skull extraction, affine, and nonlinear alignment to the Talairach atlas, subcortical division, and cortical segmentation using the Desikan–Killiany atlas. For quality assurance, a visual inspection of the segmentation was performed by a neuroimaging technician, following the quality control protocol 2.0 of the ENIGMA consortium (https://enigma.ini.usc.edu/protocols/imaging-protocols).

Acquisition parameter characteristics are described in online Supplementary material.

In this multicenter study, data were collected from six distinct neuroimaging centers and different scanners (Siemens Magnetom Trio Tim 3T, Siemens Symphony 1.5T, Philips Achieva 3T, Philips Intera 1.5T, GE Signa Horizon MX 1.5T, and GE Signa Excite 1.5T). To adjust for site, we therefore employed the ComBat batch harmonization method.

Neuropsychological assessment

Neuropsychological performance was assessed using a battery of standardized neuropsychological tests, which includes the main cognitive domains proposed by the MATRICS initiative (Nuechterlein et al., Reference Nuechterlein, Green, Kern, Baade, Barch, Cohen and Marder2008). This battery was composed by: Continuous Performance Test-II (CPT-II) (Homack & Riccio, Reference Homack and Riccio2006) to test Attention/Vigilance; Trail Making Test-A (Reitan & Wolfson, Reference Reitan and Wolfson1995) and Stroop test to test Processing Speed (Golden, Reference Golden1978); Wisconsin Card Sorting Test (WCST) (Heaton, Reference Heaton1993) and TMT-B (Reitan & Wolfson, Reference Reitan and Wolfson2001) to test Executive Function; Digit span test of WAIS-III and Letter-number sequencing WAIS-III (Weschler, Reference Weschler1997) to test Working Memory; Controlled Oral Word Association Test (COWAT) (Ruff, Light, Parker, & Levin, Reference Ruff, Light, Parker and Levin1996) and Animal words from Test Barcelona (Benito-Cuadrado, Esteba-Castillo, Böhm, Cejudo-Bolívar, & Peña-Casanova, Reference Benito-Cuadrado, Esteba-Castillo, Böhm, Cejudo-Bolívar and Peña-Casanova2002) to test Verbal Fluency; and finally, Verbal Learning test España-Complutense (TAVEC) (Benedet & Alexandre, Reference Benedet and Alexandre1998) to test Verbal Memory. Additionally, the Vocabulary subtest of WAIS-III was used to estimate premorbid IQ. Higher T-scores correspond to better performance in all cognitive domains. Details on the neuropsychological assessment, tests, and measures included for each cognitive domain are described in Sánchez-Torres (Sánchez-Torres et al., Reference Sánchez-Torres, Peralta, Gil-Berrozpe, Mezquida, Ribeiro, Molina-García and Balanzá-Martínez2022).

Statistical analysis

Descriptive statistics were calculated for each sociodemographic, neuropsychological, and clinical variables. Continuous variables are presented as mean value ± standard deviation and compared using Student's t tests. Categorical variables were expressed as total number (percentages) and compared between groups using χ2 tests. Difficulties in delivery were considered as a dichotomous variable (yes/no).

Generalized linear model (GLM) analyses were performed to examine the relationship between each independent variable and ventricle structure (third ventricle, fourth ventricle, left-lateral ventricle, right-lateral ventricle, and lateral ventricles). Independent variables were sex, age, chlorpromazine equivalent dose, diagnostic group (FEP/HC), difficulties during delivery (presence/absence), and finally the interaction of diagnosis and difficulties during delivery. Dependent variables were volume of the third ventricle of the fourth ventricle; volume of left lateral ventricle of the right lateral ventricle, and total volume of both lateral ventricles combined. We also adjusted by estimated total intracranial volume (ICV). Post-hoc comparisons to evaluate the interaction of diagnosis with difficulties during delivery on different ventricular structures were performed with Bonferroni correction of multiple comparisons (Table 2). We described the main effects (χ2 wald; p value) for each of the main variables examined (diagnosis, difficulties during delivery, and interaction between diagnosis, and difficulties during delivery) for each ventricle (Table 2). To test the possible correlation between ventricle size and antipsychotic dose, we performed a correlation analysis between these variables.

For cognitive measures, a GLM analysis was performed to evaluate the effect of OC and third ventricle to brain ratio (3VTBR) on the two specific cognitive domains (working and verbal memory) that were associated with OCs in our previous meta-analysis. Independent variables included in the model were sex, age, chlorpromazine equivalent dose, diagnostic group (FEP/HC), presence or absence of difficulties during delivery, 3VTBR, and educational level. We also performed two other separate analyses for each cognitive domain, in which the interaction between 3VTBR and diagnosis, and the interaction between VTBR and difficulties during delivery were considered. Estimation parameters description for each main variable (diagnosis, difficulties during delivery and 3VTBR) in the analysis of both cognitive domains are reported in Table 3.

Statistical analyses were performed with statistical package for the social sciences (SPSS) (Version 22).

Results

Sociodemographic, cognitive, and volumetric characteristics

Sociodemographic characteristics of the sample are described in Table 1. There were no significant between group differences in sex, age, or ethnicity. However, as expected, the groups significantly differed in terms of educational level (χ2 36.88, p < 0.001), employment (χ2 52.44, p < 0.001), and socioeconomic status (χ2 16.52, p = 0.005), with higher levels in HC than patients.

Table 1. Sociodemographic, cognitive, and volumetric characteristics of the sample

CPZ, daily equivalent doses of chlorpromazine; NA, not applicable.

The mean age for the FEP patients was 24 years, the mean duration of total episodes was 8.8 months, and the mean duration of untreated psychosis was 103.63 days, while the daily equivalent doses of Chlorpromazine in FEP patients were 561.50. Finally, approximately 14.3% of the sample had history of difficulties during delivery, with no significant difference between patients with FEP and HC.

Difficulties during delivery and the relation with ventricle enlargement in FEP and HC

Patients displayed a significantly larger third ventricle (t = 2.72, p = 0.007) compared with HC. The fourth, right, left, and total lateral ventricles were larger in the patients but the between group difference did not reach statistical significance, although left lateral ventricle (t = 1.79, p = 0.075) and total lateral ventricle (t = 1.85, p = 0.065) showed a trend towards significance (Table 1).

To test the association between difficulties during delivery and ventricle volumes a GLM analysis was performed. In this analysis, the enlargement of the third ventricle was significantly associated with difficulties during delivery (χ2 wald = 12.11, p < 0.001) and with diagnosis (χ2 wald = 4.72, p = 0.030) but we observed no significant interaction between these two factors (χ2 wald = 0.08, p = 0.774). Since both independent factors were associated with third ventricle enlargement, participants with both FEP and exposure to difficulties during delivery displayed the highest volumes (1146.4 mm3/1000) followed by HC with difficulties during delivery (1033.9 mm3/1000), then FEP patients without difficulties during delivery (998.0 mm3/1000) and finally HC without difficulties during delivery (908.1 mm3/1000) (Table 2 and Fig. 1).

Table 2. Main effects of, diagnosis group, Lewis C (difficulties during delivery) and its interaction (estimated marginal means and post-hoc comparisons with Bonferroni) on ventricles' volume (mm3 /1000)

Lewis C, difficulties in delivery present or absent (±); CPZ, daily equivalent doses of chlorpromazine; CI, confidence interval.

Adjusted by age, sex, and total intracranial volume.

Data harmonized with COMBAT (center of acquisition).

* p < 0.05.

Figure 1. Generalized linear model third ventricle predicted values (mm3/1000) by presence/absence of difficulties during delivery (Lewis C; present/absent) stratified by diagnosis (psychosis/control). Predicted third ventricle values are adjusted by covariates, age, sex, difficulties during delivery, diagnosis, chlorpromazine equivalent mean dose, and estimated total intracranial volume.

We also performed a correlation analysis between third ventricle volume and chlorpromazine equivalent doses and observed no significant correlation (Pearson r = −0.056 p = 0.516, Spearman r = −0.037 p = 0.671).

Relation between difficulties during delivery and cognition

As expected, FEP patients performed significantly worse than HC across all cognitive domains (Table 1).

third ventricle to brain ratio (3VTBR) was inversely correlated with verbal memory performance (p = 0.034), thus worse performance was associated with greater ventricle enlargement (Fig. 2 and Table 3). We also examined the potential interaction between 3VTBR and difficulties during delivery on verbal memory performance and observed no significant effect (beta: −31 087.2; standard error: 52 518.7; p = 0.554). In a separate analysis, we examined whether there was an interaction between 3VTBR and diagnostic group on verbal memory, and observed no significant effect (beta: −65 228.3; standard error: 51 117.8; p = 0.202).

Figure 2. Generalized linear model predicted verbal memory values and third ventricle-to-brain ratio (FEP patients and controls). Predicted verbal memory values are adjusted by covariates, age, sex, difficulties during delivery, diagnosis, chlorpromazine equivalent mean dose, and educational level.

Table 3. Parameter estimation for cognitive outcomes (verbal memory and working memory)

s.e., standard error; 3VTBR, third ventricle to brain ratio.

This analysis was controlled by age, sex, educational level, and chlorpromazine equivalents.

We observed no significant associations between 3VTBR and working memory.

Discussion

Our findings confirm an increased ventricular volume in patients with a FEP compared with HC in each part of the ventricular system examined, with significant differences in the third ventricle and trend level differences in the left lateral ventricle and total lateral ventricles.

Within the subsample of participants who had been exposed to difficulties during delivery, patients did not show a significantly increased volume of the third ventricle compared to HC. However, contrary to our hypothesis, there was no significant interaction between diagnosis and difficulties during delivery on ventricular enlargement, despite subjects with FEP and difficulties during delivery showing the largest volume of all subgroups. We also observed a significant association between larger 3VTBR and worse verbal memory performance in both patients and HC. However, there was no significant interaction between either 3VTBR and diagnosis or 3VTBR and difficulties during delivery on verbal memory.

The difference we observed in ventricle volume between HC and FEP patients is consistent with previous findings, with third ventricle enlargement reported in almost 2/3 of patients diagnosed with schizophrenia (McCarley et al., Reference McCarley, Wible, Frumin, Hirayasu, Levitt, Fischer and Shenton1999) and third/lateral ventricle enlargement also observed in FEP (Fannon et al., Reference Fannon, Tennakoon, Sumich, O'Ceallaigh, Doku, Chitnis and Sharma2000; Sasabayashi et al., Reference Sasabayashi, Takayanagi, Takahashi, Katagiri, Sakuma, Obara and Suzuki2020). Our results are thus in keeping with the suggestion that ventricular enlargement is not an epiphenomenon of chronic illness or prolonged medication exposure but might be neurodevelopmental in origin since it has been described in the earliest stages of the disease, especially in males (Nakamura et al., Reference Nakamura, Kawasaki, Suzuki, Hagino, Kurokawa, Takahashi and Kurachi2004). This enlargement might be related to abnormalities in the choroid plexus and its physiological functions that have been observed in patients with schizophrenia (Haukvik et al., Reference Haukvik, McNeil, Nesvåg, Söderman, Jönsson and Agartz2010a; Lizano et al., Reference Lizano, Lutz, Ling, Lee, Eum, Bishop and Keshavan2019). Increased choroid plexus volume in psychosis was observed to be correlated with worse cognitive function, regional brain atrophy, and increased ventricular size (Lizano et al., Reference Lizano, Lutz, Ling, Lee, Eum, Bishop and Keshavan2019).

Within delivery complications, perinatal asphyxia is considered the mechanism involved in brain changes such as smaller intracranial volume, total brain volume, white and gray matter volumes, and reduced total surface area, not only in patients with schizophrenia or bipolar disorder but also in HC (Wortinger et al., Reference Wortinger, Engen, Barth, Andreassen, Nordbø Jørgensen and Agartz2020). So, even though we employed perinatal adversity as a proxy measure for hypoxia during birth, our results on third ventricle volume are consistent with those of Wortinger et al., who observed no interaction between asphyxia and diagnosis in most areas of the brain (Wortinger et al., Reference Wortinger, Engen, Barth, Andreassen, Nordbø Jørgensen and Agartz2020). Similarly, Haukvik et al. reported an effect of obstetric complications on the volume of the nucleus accumbens (Haukvik et al., Reference Haukvik, McNeil, Nesvåg, Söderman, Jönsson and Agartz2010a), the hippocampus (Haukvik et al., Reference Haukvik, Saetre, McNeil, Bjerkan, Andreassen, Werge and Agartz2010b), and the cortical folding in Broca's area in both patients and controls (Haukvik et al., Reference Haukvik, Schaer, Nesvåg, McNeil, Hartberg, Jönsson and Agartz2012).

Thus, our finding of a relationship between difficulties during delivery and third ventricle volume that was not significantly more pronounced in patients with psychosis, suggests that perinatal OCs may increase the risk of third ventricle enlargement with an additive effect (Wortinger et al., Reference Wortinger, Engen, Barth, Andreassen, Nordbø Jørgensen and Agartz2020). Falkai et al. hypothesized that OCs may exert a diffuse add-on effect leading to structural changes related to the pathophysiology of schizophrenia (Falkai et al., Reference Falkai, Schneider-Axmann, Honer, Vogeley, Schönell, Pfeiffer and Tepest2003). This summative effect has been suggested to act both by impacting brain development (Smeland et al., Reference Smeland, Wang, Frei, Li, Hibar, Franke and Andreassen2018) and impairing the resilience of the fetal brain (Murray, Bhavsar, Tripoli, & Howes, Reference Murray, Bhavsar, Tripoli and Howes2017). Furthermore, the relationship between genetic vulnerability for schizophrenia and perinatal adversity is still under debate (Ursini et al., Reference Ursini, Punzi, Chen, Marenco, Robinson, Porcelli and Weinberger2018; Vassos et al., Reference Vassos, Kou, Tosato, Maxwell, Dennison, Legge and Murray2022), and a recent study in FEP showed no significant interaction between genetic risk of psychosis and obstetric vulnerability (Valli et al., Reference Valli, Segura, Verdolini, Garcia-Rizo, Berge, Baeza and Zorrilla2023).

The enlargement in ventricular size has been reported to predict a longer time to remission of psychotic symptoms and poorer outcomes (Dazzan et al., Reference Dazzan, Arango, Fleischacker, Galderisi, Glenthøj, Leucht and McGuire2015). It could thus be hypothesized that difficulties during delivery could be a risk factor for a worse prognosis considering that, also in our FEP sample, difficulties during delivery were associated with a more severe psychopathological profile (Peralta et al., Reference Peralta, García de Jalón, Moreno-Izco, Peralta, Janda, Sánchez-Torres and Zandio2022).

Our work also sought to examine the relationship between ventricular enlargement and cognition as well as its relationship with difficulties during delivery. In healthy subjects, third ventricle and total ventricular volume were reported to be associated with global cognition but also with specific cognitive domains, such as verbal memory and executive function (de Mélo Silva Júnior, Diniz, de Souza Vilanova, Basto, & Valença, Reference de Mélo Silva Júnior, Diniz, de Souza Vilanova, Basto and Valença2022). In schizophrenia, among ventricular measures, third ventricular enlargement was the most frequently associated with cognitive performance, especially with dysfunctional frontal and limbic processing as well as with negative symptoms (Cuesta et al., Reference Cuesta, Lecumberri, Cabada, Moreno-Izco, Ribeiro, López-Ilundain and Gómez2017; McCarley et al., Reference McCarley, Wible, Frumin, Hirayasu, Levitt, Fischer and Shenton1999). We observed that 3VTBR was associated with verbal memory. However, this finding was not specific to patients with FEP, as we also observed this relationship in HC. Furthermore, the interaction between 3VTBR and difficulties during delivery did not predict performance in either of the cognitive domains that we examined. The only meta-analysis to date that examined the relationship between cognitive dysfunction and OCs in schizophrenia reported an association between verbal memory deficits and OCs, but not specifically for difficulties during delivery (Mezquida et al., Reference Mezquida, Fernández-Egea, Treen, Mané, Bergé, Savulich and García-Rizo2021). Yet a number of other environmental and genetic risk factors are considered to be involved in the pathophysiology of cognitive impairment in schizophrenia, such as family history of psychosis (Bora & Murray, Reference Bora and Murray2014), childhood adversity (Wells et al., Reference Wells, Jacomb, Swaminathan, Sundram, Weinberg, Bruggemann and Weickert2020), and substance abuse (Manning et al., Reference Manning, Betteridge, Wanigaratne, Best, Strang and Gossop2009).

Several methodological limitations should be acknowledged in our study. Data on obstetric complications were gathered via a maternal interview, which could be associated with risk of recall bias in mothers of patients compared to mothers of HC. However, a study examining the validity of a retrospective OCs interview, Janssen-Cilag reported high concordance between medical records and maternal recall in schizophrenia research (Borrajo et al., Reference Borrajo, Zandio, Zarzuela, Serrano, Rosa, Fañanás and Cuesta2011). The Lewis–Murray scale, though, records only a limited number of adverse events during gestation and delivery, while several others may have not been assessed. In addition, we employed difficulties during delivery as a proxy measure for perinatal hypoxia, yet the Lewi–-Murray scale does not include a rating of severity, therefore difficulties during delivery might be especially heterogeneous in terms of potential hypoxic consequences to the brain. The presence of difficulties during delivery does not exclude the presence of other difficulties during the gestational period, such as placental abnormalities, which might have confounded our results. The low number of participants with abnormalities during delivery might have also impacted the power of our analyses, increasing the odds of negative findings in terms of other ventricular areas and cognitive domains. We were also not able to rule out the potential effect of antipsychotic medication on ventricular volume, as patients were not antipsychotic naïve. However, we observed no correlation between treatment exposure and ventricular size within the patient group. Another factor to consider is our wide age of inclusion, with participants at the younger end of the range still undergoing important brain maturational changes. However, OCs are associated with an earlier age of onset (Baeza et al., Reference Baeza, De La Serna, Amoretti, Cuesta, Díaz-Caneja, Mezquida and Balanza2021) thus we opted to include younger patients in order to increase the representativeness of the sample in terms of obstetric risk.

Our results suggest that difficulties during delivery might be important contributors to one of the most replicated correlates of psychosis, increased third ventricle volume. However, we observed no significant interaction between diagnosis and exposure to perinatal adversity. Difficulties during delivery were associated with larger ventricular volumes in both patients with FEP and HC. This is in keeping with the previously reported lack of an interactive effect between birth asphyxia and diagnosis on brain structure (Wortinger et al., Reference Wortinger, Engen, Barth, Andreassen, Nordbø Jørgensen and Agartz2020). Similarly verbal memory function was associated with third ventricular volume in both patients and controls. However, an additive risk of perinatal adversity and genetic predisposition has been suggested and, in our sample, FEP patients with difficulties during delivery had the largest third ventricle volume. Our findings thus further highlight the importance of peri-natal risk reduction interventions.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291723003185

Acknowledgments

This study is part of a coordinated-multicentre Project, PEPs study, funded by the Ministerio de Economía y Competitividad (PI08/0208; PI11/ 00325; PI14/00612), Instituto de Salud Carlos III – Fondo Europeo de Desarrollo Regional. Union Europea. Una manera de hacer Europa, Centro de Investigacion Biomédica en Red de salud Mental, CIBERSAM, Instituto de Salud Carlos III, by the CERCA Programme/Generalitat de Catalunya and Secretaria d'Universitats i Recerca del Departament d'Economia I Coneixement (2017SGR1355). Departament de Salut de la Generalitat de Catalunya, en la convocatoria corresponent a l'any 2017 de concessío de subvencions del Pla Estratègic de Recerca i Innovacío en Salut (PERIS) 2016–2020, modalitat Projectes de recerca orientats a l'atencío primària, amb el codi d'expedient SLT006/17/00345. This study has been funded by Instituto de Salud Carlos III (ISCIII) through the project ‘PI20/00661’ and co-funded by the European Union. NV has received financial support for CME activities and travel funds from the following entities (unrelated to the present work): Angelini, Janssen-Cilag, Lundbeck, and Otsuka. Dr Verdolini thanks the BITRECS project, which has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 754550 and from ‘La Caixa’ Foundation (ID 100010434), under the agreement LCF/PR/GN18/50310006. IV is supported by a BITRECS fellowship that received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 754 550 and from ‘La Caixa’ Foundation, under the agreement LCF/PR/GN18/5031000. RC is a Ramón y Cajal Research Fellow (RYC-2017-23144), Spanish Ministry of Science, Innovation and Universities and was supported by a NARSAD independent investigator grant (no. 24628) from the Brain &amp; Behavior Research Foundation. RC is partially supported by the Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III (PI15/00723, PI18/00753, PI21/0070) CIBER-Consorcio Centro de Investigación Biomédica en Red- (CB/07/09/0023), co-financed by the European Union and ERDF Funds from the European Commission, ‘A way of making Europe’, financed by the European Union—NextGenerationEU (PMP21/00051), Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds, EU Seventh Framework Program, H2020 Program, and Horizon Europe, National Institute of Mental Health of the National Institutes of Health, FundaciónFamilia Alonso, and Fundación Alicia Koplowitz.

Competing interest

CGR has received grants from/or served as consultant, advisor or speaker for the following entities Adamed, Angelini, Casen-Recordati, Janssen-Cilag, and Lunbeck. MB has been a consultant for, received grant/research support and honoraria from, and been on the speakers/advisory board of, has received honoraria from talks and/or consultancy of Adamed, Angelini, Ferrer, Janssen-Cilag, Lundbeck, Otsuka, Pfizer, and Sanofi. AL received financial support to attend scientific meetings from Janssen. E.V. has received research support from or served as consultant, adviser, or speaker for AB-Biotics, Actavis, Allergan, Angelini, AstraZeneca, Bristol-Myers Squibb, Dainippon Sumitomo Pharma, Ferrer, Forest Research Institute, Gedeon Richter, Glaxo-Smith-Kline, Janssen, Lund- beck, Otsuka, Pfizer, Roche, Sanofi-Aventis, Servier, Shire, Sunovion, Takeda, Telefonica, the Brain and Behaviour Foundation, the Spanish Ministry of Science and Innovation (CIBERSAM), the Seventh European Framework Programme (ENBREC), and the Stanley Medical Research Institute, unrelated to the present work. AG-P has received grants and served as consultant, advisor, or CME speaker for the following entities: Janssen-Cilag, Lundbeck, Otsuka, Pfizer, Sanofi-Aventis, Alter, Angelini, Exeltis, the Spanish Ministry of Science and Innovation (CIBERSAM), the Ministry of Science (Carlos III Institute), the Basque Government, and the European Framework Program of Research. AM has served as a speaker and received honoraria for travel expenses /attending conferences from Otsuka and Angelini MB has been a consultant for received grant/research support and honoraria from and has been on the speakers/advisory board of ABBiotics, Adamed, AMGEN, Eli Lilly, Ferrer, Forum Pharmaceuticals, Gedeon, Janssen-Cilag, Lundbeck, Otsuka, Pfizer, and Roche.

Footnotes

*

Both are first authors.

Both are senior authors.

PEPs group: M. Florencia Forte3,16, Jairo M. Gonzalez-Diaz3,22,23, Vito Cavone4,7, Celia Ordas4,7, Iñaki Zorrilla4,14, Saioa Lopez-Zurbano4,14, Concepcion De la Camara4,12,13, David Vaquero Puyuelo4,12,13, Juan Nacher4,24,25, Maria José Escartí Fabra4,25,26, Alba Toll Privat4,18, Laura Martínez Sadurní4,18, Sara Martín-Parra4,16, Derek Clougher4,16, Inmaculada Baeza4,5,17, J. Castro-Fornielles4,5,17, Fernando Contreras4,27, M. Paz García-Portilla4,28, Leticia González-Blanco4,28,29,30, Roberto Rodriguez-Jimenez4,31,32, Ángeles Sánchez-Cabezudo31, Judith Usall4,33, Anna Butjosa4,34, Salvador Sarro4,35, Edith Pomarol-Clotet4,35, Judit Selma4,9, Aina Àvila-Parcet4,9 and María Ribeiro10,11

22

UR Center for Mental Health-CERSAME, School of Medicine and Health Sciences, Universidad del Rosario, Bogota, Colombia

23

Clinica Nuestra Señora de la Paz, Bogota, Colombia

24

Neurobiology Unit, Program in Neurosciences and Institute of Biotechnology and Biomedicine (BIOTECMED), Universitat de València, Burjassot, Spain

25

Biomedical Research Institute INCLIVA, Valencia, Spain

26

Department of Psychiatry, Hospital Clínico Universitario de Valencia, Valencia, Spain

27

Department of Psychiatry- Bellvitge University Hospital, Bellvitge Biomedical Research Institute IDIBELL, Hospitalet de Llobregat- Barcelona, Spain

28

Department of Psychiatry, Universidad de Oviedo, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain

29

Instituto Universitario de Neurociencias del Principado de Asturias (INEUROPA), Oviedo, Spain

30

Servicio de Salud del Principado de Asturias (SESPA) Oviedo, Spain

31

Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Barcelona, Spain

32

Universidad Complutense de Madrid (UCM), Madrid, Spain

33

Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Barcelona

34

Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu of Barcelona, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain

35

FIDMAG Germanes Hospitalàries Research Foundation, Sant Boi de Llobregat, Barcelona, Spain

References

Amoretti, S., Rabelo-da-Ponte, F. D., Garriga, M., Forte, M. F., Penadés, R., Vieta, E., … Garcia-Rizo, C. (2022). Obstetric complications and cognition in schizophrenia: A systematic review and meta-analysis. Psychological Medicine, 52(14), 28742884. doi: 10.1017/s0033291722002409CrossRefGoogle ScholarPubMed
Baeza, I., De La Serna, E., Amoretti, S., Cuesta, M. J., Díaz-Caneja, C. M., Mezquida, G., … Balanza, V. (2021). Premorbid characteristics as predictors of early onset versus adult onset in patients with a first episode of psychosis. Journal of Clinical Psychiatry, 82(6), 21m13907. doi: 10.4088/JCP.21m13907.Google ScholarPubMed
Benedet, M. J., & Alexandre, M. A. (1998). Test de aprendizaje verbal españa-complutense (TAVEC) (TEA Ediciones). Madrid.Google Scholar
Benito-Cuadrado, M. M., Esteba-Castillo, S., Böhm, P., Cejudo-Bolívar, J., & Peña-Casanova, J. (2002). Semantic verbal fluency of animals: A normative and predictive study in a Spanish population. Journal of Clinical and Experimental Neuropsychology, 24(8), 11171122. doi: 10.1076/jcen.24.8.1117.8376CrossRefGoogle Scholar
Bora, E., & Murray, R. M. (2014). Meta-analysis of cognitive deficits in ultra-high risk to psychosis and first-episode psychosis: Do the cognitive deficits progress over, or after, the onset of psychosis? Schizophrenia Bulletin, 40(4), 744755. doi: 10.1093/schbul/sbt085CrossRefGoogle ScholarPubMed
Bornstein, R. A., Schwarzkopf, S. B., Olson, S. C., & Nasrallah, H. A. (1992). Third-ventricle enlargement and neuropsychological deficit in schizophrenia. Biol Psychiatry, 31(9), 954961. doi: 10.1016/0006-3223(92)90121-FCrossRefGoogle ScholarPubMed
Borrajo, R. H., Zandio, M., Zarzuela, A., Serrano, J. F., Rosa, A., Fañanás, L., … Cuesta, M. J. (2011). Validity of maternal recall of obstetric complications in mothers of patients with schizophrenia spectrum disorders and their healthy siblings Schizophrenia Research, Vol. 126, pp. 308309. doi: 10.1016/j.schres.2010.09.017CrossRefGoogle Scholar
Bowie, C. R., & Harvey, P. D. (2006). Cognitive deficits and functional outcome in schizophrenia. Neuropsychiatric Disease and Treatment, 2(4), 531536. doi: 10.2147/nedt.2006.2.4.531CrossRefGoogle ScholarPubMed
Cannon, M., Jones, P. B., & Murray, R. M. (2002). Obstetric complications and schizophrenia: Historical and meta-analytic review. American Journal of Psychiatry, 159(7), 10801092. doi: 10.1176/appi.ajp.159.7.1080CrossRefGoogle ScholarPubMed
Collins, K. A., & Popek, E. (2018). Birth injury: Birth asphyxia and birth trauma. Academic Forensic Pathology, 8, 788864. doi: 10.1177/1925362118821468CrossRefGoogle ScholarPubMed
Costas-Carrera, A., Garcia-Rizo, C., Bitanihirwe, B., & Penadés, R. (2020). Obstetric complications and brain imaging in schizophrenia: A systematic review. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 5, 10771084. doi: 10.1016/j.bpsc.2020.07.018Google ScholarPubMed
Cuesta, M. J., Lecumberri, P., Cabada, T., Moreno-Izco, L., Ribeiro, M., López-Ilundain, J. M., … Gómez, M. (2017). Basal ganglia and ventricle volume in first-episode psychosis. A family and clinical study. Psychiatry Research – Neuroimaging, 269, 9096. doi: 10.1016/j.pscychresns.2017.09.010CrossRefGoogle ScholarPubMed
Dars, S., Malik, S., Samreen, I., & Kazi, R. A. (2014). Maternal morbidity and perinatal outcome in preterm premature rupture of membranes before 37 weeks gestation. Pakistan Journal of Medical Sciences, 30(3), 626629. doi: 10.12669/pjms.303.4853Google ScholarPubMed
Davies, C., Segre, G., Estradé, A., Radua, J., De Micheli, A., Provenzani, U., … Fusar-Poli, P. (2020). Prenatal and perinatal risk and protective factors for psychosis: A systematic review and meta-analysis. The Lancet Psychiatry, 7(5), 399410. doi: 10.1016/S2215-0366(20)30057-2CrossRefGoogle ScholarPubMed
Dazzan, P., Arango, C., Fleischacker, W., Galderisi, S., Glenthøj, B., Leucht, S., … McGuire, P. (2015). Magnetic resonance imaging and the prediction of outcome in first-episode schizophrenia: A review of current evidence and directions for future research. Schizophrenia Bulletin, 41(3), 574583. doi: 10.1093/schbul/sbv024CrossRefGoogle ScholarPubMed
De Haan, M., Wyatt, J. S., Roth, S., Vargha-Khadem, F., Gadian, D., & Mishkin, M. (2006). Brain and cognitive-behavioural development after asphyxia at term birth. Developmental Science, 9(4), 350358. doi: 10.1111/j.1467-7687.2006.00499.xCrossRefGoogle ScholarPubMed
de Mélo Silva Júnior, M. L., Diniz, P. R. B., de Souza Vilanova, M. V., Basto, G. P. T., & Valença, M. M. (2022). Brain ventricles, CSF and cognition: A narrative review. Psychogeriatrics: The Official Journal of the Japanese Psychogeriatric Society, 22(4), 544552. doi: 10.1111/PSYG.12839CrossRefGoogle ScholarPubMed
Ecevit, A., Anuk-Ince, D., Yapakç, E., Kupana-Ayva, Ş, Kurt, A., Yanik, F. F., & Tarcan, A. (2014). Association of respiratory distress syndrome and perinatal hypoxia with histologic chorioamnionitis in preterm infants. Turkish Journal of Pediatrics, 56(1), 5661.Google ScholarPubMed
Falkai, P., Schneider-Axmann, T., Honer, W. G., Vogeley, K., Schönell, H., Pfeiffer, U., … Tepest, R. (2003). Influence of genetic loading, obstetric complications and premorbid adjustment on brain morphology in schizophrenia: A MRI study. European Archives of Psychiatry and Clinical Neuroscience, 253(2), 9299. doi: 10.1007/s00406-003-0414-9CrossRefGoogle ScholarPubMed
Fannon, D., Tennakoon, L., Sumich, A., O'Ceallaigh, S., Doku, V., Chitnis, X., … Sharma, T. (2000). Third ventricle enlargement and developmental delay in first-episode psychosis: Preliminary findings. The British Journal of Psychiatry: The Journal of Mental Science, 177(OCT.), 354359. doi: 10.1192/BJP.177.4.354CrossRefGoogle ScholarPubMed
García-Rizo, C., Bioque, M., Mezquida, G., Amoretti, S., Cuesta, M. J., Díaz-Caneja, C. M., … Selva-Vera, G. (2020). Birth weight and antipsychotic induced weight gain: A prenatal programming approach in the PEPs study. Schizophrenia Research, 218, 292294. doi: 10.1016/j.schres.2019.12.030CrossRefGoogle ScholarPubMed
Garcia-Rizo, C., Cabrera, B., Bioque, M., Mezquida, G., Lobo, A., Gonzalez-Pinto, A., … GROUP, Pep. (2022). The effect of early life events on glucose levels in first-episode psychosis. Frontiers in Endocrinology, 13, 2696. doi: 10.3389/FENDO.2022.983792CrossRefGoogle ScholarPubMed
Garriga, M., Fernandez-Egea, E., Mallorqui, A., Serrano, L., Oliveira, C., Parellada, E., … Garcia-Rizo, C. (2019). Antipsychotic-induced weight gain and birth weight in psychosis: A fetal programming model. Journal of Psychiatric Research, 115, 2935. doi: 10.1016/j.jpsychires.2019.05.004CrossRefGoogle ScholarPubMed
Gaser, C., Nenadic, I., Buchsbaum, B. R., Hazlett, E. A., & Buchsbaum, M. S. (2004). Ventricular enlargement in schizophrenia related to volume reduction of the thalamus, striatum, and superior temporal cortex. American Journal of Psychiatry, 161(1), 154156. doi: 10.1176/APPI.AJP.161.1.154/ASSET/IMAGES/LARGE/M424F1.JPEGCrossRefGoogle ScholarPubMed
Golden, C. J. (1978). Stroop color and word test. A manual for clinical and experimental uses. (Wood Dale, Illinois Stoelting Company). Illinois.Google Scholar
Haijma, S. V., Van Haren, N., Cahn, W., Koolschijn, P. C. M. P. P., Hulshoff Pol, H. E., & Kahn, R. S. (2013). Brain volumes in schizophrenia: A meta-analysis in over 18 000 subjects. Schizophrenia Bulletin, 39(5), 11291138. doi: 10.1093/schbul/sbs118CrossRefGoogle ScholarPubMed
Haukvik, U. K., McNeil, T., Nesvåg, R., Söderman, E., Jönsson, E., & Agartz, I. (2010a). No effect of obstetric complications on basal ganglia volumes in schizophrenia. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 34(4), 619623. doi: 10.1016/j.pnpbp.2010.02.024CrossRefGoogle ScholarPubMed
Haukvik, U. K., Saetre, P., McNeil, T., Bjerkan, P. S., Andreassen, O. A., Werge, T., … Agartz, I. (2010b). An exploratory model for G x E interaction on hippocampal volume in schizophrenia; obstetric complications and hypoxia-related genes. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 34(7), 12591265. doi: 10.1016/j.pnpbp.2010.07.001CrossRefGoogle Scholar
Haukvik, U. K., Schaer, M., Nesvåg, R., McNeil, T., Hartberg, C. B., Jönsson, E. G., … Agartz, I. (2012). Cortical folding in Broca's area relates to obstetric complications in schizophrenia patients and healthy controls. Psychological Medicine, 42(6), 13291337. doi: 10.1017/S0033291711002315CrossRefGoogle ScholarPubMed
Heaton, R. (1993). Wisconsin card sorting test manual. Odessa, Florida: Psychological Assessment Resources.Google Scholar
Herrera-Marschitz, M., Neira-Pena, T., Rojas-Mancilla, E., Espina-Marchant, P., Esmar, D., Perez, R., … Gebicke-Haerter, P. J. (2014). Perinatal asphyxia: CNS development and deficits with delayed onset. Frontiers in Cellular Neuroscience, 26(8), 47. doi: 10.3389/fnins.2014.00047Google Scholar
Homack, S., & Riccio, C. A. (2006). Conners’ continuous performance test (2nd ed.; CCPT-II). Journal of Attention Disorders, 9(3), 556558. doi: 10.1177/1087054705283578CrossRefGoogle ScholarPubMed
Jacobi, W., & Winkler, H. (1927). Encephalographische studien an chronisch schizophrenen. Archiv Für Psychiatrie Und Nervenkrankheiten, 81(1), 299332. doi: 10.1007/BF01825649CrossRefGoogle Scholar
Johnstone, E. C., Frith, C. D., Crow, T. J., Husband, J., & Kreel, L. (1976). Cerebral ventricular size and cognitive impairment in chronic schizophrenia. Lancet (London, England), 2(7992), 924926. doi: 10.1016/S0140-6736(76)90890-4CrossRefGoogle ScholarPubMed
Kirkpatrick, B., Miller, B., Garcia-Rizo, C., Fernandez-Egea, E., García-Rizo, C., & Fernandez-Egea, E. (2013). Schizophrenia. Clin Schizophr Relat Psychoses, 8(2), 7379. doi: 10.3371/CSRP.KIMI.0315131626661L777U2665 [pii]CrossRefGoogle Scholar
Konishi, J., del Re, E. C., Bouix, S., Blokland, G. A. M., Mesholam-Gately, R., Woodberry, K., … McCarley, R. W. (2018). Abnormal relationships between local and global brain measures in subjects at clinical high risk for psychosis: A pilot study. Brain Imaging and Behavior, 12(4), 974988. doi: 10.1007/s11682-017-9758-zCrossRefGoogle ScholarPubMed
Kuo, S. S., & Pogue-Geile, M. F. (2019). Variation in fourteen brain structure volumes in schizophrenia: A comprehensive meta-analysis of 246 studies. Neuroscience & Biobehavioral Reviews, 98, 8594. doi: 10.1016/J.NEUBIOREV.2018.12.030CrossRefGoogle ScholarPubMed
Leung, T. Y., & Lao, T. T. (2013). Timing of caesarean section according to urgency. Best Practice and Research: Clinical Obstetrics and Gynaecology, 27(2), 251267. doi: 10.1016/j.bpobgyn.2012.09.005Google ScholarPubMed
Lewis, S., Owen, M., & Murray, R. (1989). Obstetric complications and schizophrenia: Methodology and mechanisms. In Schulz, S. & Tamminga, C. (Eds.), Schizophrenia: Scientific progress (pp. 5668). New York, NY: Oxford University Press.Google Scholar
Lizano, P., Lutz, O., Ling, G., Lee, A. M., Eum, S., Bishop, J. R., … Keshavan, M. (2019). Association of choroid plexus enlargement with cognitive, inflammatory, and structural phenotypes across the psychosis spectrum. American Journal of Psychiatry, 176(7), 564572. doi: 10.1176/appi.ajp.2019.18070825CrossRefGoogle ScholarPubMed
Manning, V., Betteridge, S., Wanigaratne, S., Best, D., Strang, J., & Gossop, M. (2009). Cognitive impairment in dual diagnosis inpatients with schizophrenia and alcohol use disorder. Schizophrenia Research, 114(1–3), 98104. doi: 10.1016/j.schres.2009.05.020CrossRefGoogle ScholarPubMed
McCarley, R. W., Wible, C. G., Frumin, M., Hirayasu, Y., Levitt, J. J., Fischer, I. A., & Shenton, M. E. (1999). MRI anatomy of schizophrenia. Biological Psychiatry, 45, 10991119. doi: 10.1016/S0006-3223(99)00018-9CrossRefGoogle ScholarPubMed
Mercogliano, C., & Poddar, K. (2021). Long-term comorbid neuropsychiatric sequelae of hypoxia at birth. Cureus, 13(1), e12687. doi: 10.7759/cureus.12687Google ScholarPubMed
Mezquida, G., Amoretti, S., Bioque, M., García-Rizo, C., Sánchez-Torres, A. M., Pina-Camacho, L., … Bernardo, M. (2023). Identifying risk factors for predominant negative symptoms from early stages in schizophrenia: A longitudinal and sex-specific study in first-episode schizophrenia patients. Revista de Psiquiatria y Salud Mental, S1888-9891(23)00005-8. doi: 10.1016/j.rpsm.2023.01.004Google ScholarPubMed
Mezquida, G., Fernández-Egea, E., Treen, D., Mané, A., Bergé, D., Savulich, G., … García-Rizo, C. (2021). Difficulties in delivery and depressive symptomatology in schizophrenia. Revista de Psiquiatria y Salud Mental, 14(1), 6668. doi: 10.1016/j.rpsm.2019.12.002CrossRefGoogle ScholarPubMed
Mezquida, G., Fernandez-Egea, E., Treen, D., Mané, A., Bergé, D., Savulich, G., … Garcia-Rizo, C. (2018). Obstetric phenotypes in the heterogeneity of schizophrenia. Journal of Nervous and Mental Disease, 206(11), 882886. doi: 10.1097/NMD.0000000000000897CrossRefGoogle ScholarPubMed
Mukhopadhyay, S., & Arulkumaran, S. (2002). Breech delivery. Best Practice and Research: Clinical Obstetrics and Gynaecology, 16(1), 3142. doi: 10.1053/beog.2001.0253Google ScholarPubMed
Murray, R. M., Bhavsar, V., Tripoli, G., & Howes, O. (2017). 30 years on: How the neurodevelopmental hypothesis of schizophrenia morphed into the developmental risk factor model of psychosis. Schizophrenia Bulletin, 43(6), 11901196. doi: 10.1093/schbul/sbx121CrossRefGoogle ScholarPubMed
Nakamura, K., Kawasaki, Y., Suzuki, M., Hagino, H., Kurokawa, K., Takahashi, T., … Kurachi, M. (2004). Multiple structural brain measures obtained by three-dimensional magnetic resonance imaging to distinguish between schizophrenia patients and normal subjects. Schizophrenia Bulletin, 30(2), 393404. doi: 10.1093/oxfordjournals.schbul.a007087CrossRefGoogle ScholarPubMed
Nakamura, M., Salisbury, D. F., Hirayasu, Y., Bouix, S., Pohl, K. M., Yoshida, T., … McCarley, R. W. (2007). Neocortical gray matter volume in first-episode schizophrenia and first-episode affective psychosis: A cross-sectional and longitudinal MRI study. Biological Psychiatry, 62(7), 773783. doi: 10.1016/j.biopsych.2007.03.030CrossRefGoogle ScholarPubMed
Nuechterlein, K. H., Green, M. F., Kern, R. S., Baade, L. E., Barch, D. M., Cohen, J. D., … Marder, S. R. (2008). The MATRICS consensus cognitive battery, part 1: Test selection, reliability, and validity. The American Journal of Psychiatry, 165, 203213. doi: 10.1176/appi.ajp.2007.07010042CrossRefGoogle ScholarPubMed
Peralta, V., de Jalón, E. G., Campos, M. S., Zandio, M., Sanchez-Torres, A., & Cuesta, M. J. (2011). The meaning of childhood attention-deficit hyperactivity symptoms in patients with a first-episode of schizophrenia-spectrum psychosis. Schizophrenia Research, 126(1–3), 2835. doi: 10.1016/J.SCHRES.2010.09.010CrossRefGoogle ScholarPubMed
Peralta, V., García de Jalón, E., Moreno-Izco, L., Peralta, D., Janda, L., Sánchez-Torres, A. M., … Zandio, M. (2022). Long-term outcomes of first-admission psychosis: A naturalistic 21-year follow-up study of symptomatic, functional and personal recovery and their baseline predictors. Schizophrenia Bulletin, 48(3), 631642. doi: 10.1093/schbul/sbab145CrossRefGoogle ScholarPubMed
Reitan, R. M., & Wolfson, D. (1995). Category test and trail making test as measures of frontal lobe functions. The Clinical Neuropsychologist, 9(1), 5056. doi: 10.1080/13854049508402057CrossRefGoogle Scholar
Reitan, R. M., & Wolfson, D. (2001). The Halstead–Reitan neuropsychological test battery: Research findings and clinical application. In Cambridge Child and Adolescent Psychiatry (Eds.), Specific learning disabilities and difficulties in children and adolescents: Psychological assessment and evaluation (pp. 309346). New York, NY, USA: Cambridge University Press. doi: 10.1017/CBO9780511526794.011CrossRefGoogle Scholar
Rosso, I. M., Cannon, T. D., Huttunen, T., Huttunen, M. O., Lönnqvist, J., & Gasperoni, T. L. (2000). Obstetric risk factors for early-onset schizophrenia in a Finnish birth cohort. American Journal of Psychiatry, 157(5), 801807. doi: 10.1176/appi.ajp.157.5.801CrossRefGoogle Scholar
Ruff, R. M., Light, R. H., Parker, S. B., & Levin, H. S. (1996). Benton controlled oral word association test: Reliability and updated norms. Archives of Clinical Neuropsychology, 11(4), 329338. doi: 10.1016/0887-6177(95)00033-XCrossRefGoogle ScholarPubMed
Sagué-Vilavella, M., Amoretti, S., Garriga, M., Mezquida, G., Williams, E., Serra-Navarro, M., … Verdolini, N. (2022). Shaped before birth: Obstetric complications identify a more severe clinical phenotype among patients presenting a first affective or non-affective episode of psychosis. Journal of Psychiatric Research, 151, 461468. doi: 10.1016/j.jpsychires.2022.05.005CrossRefGoogle ScholarPubMed
Salagre, E., Arango, C., Artigas, F., Ayuso-Mateos, J. L., Bernardo, M., Castro-Fornieles, J., … Vieta, E. (2019). CIBERSAM: Ten years of collaborative translational research in mental disorders. Revista de Psiquiatria y Salud Mental, 12(1), 18. doi: 10.1016/j.rpsm.2018.10.001CrossRefGoogle ScholarPubMed
Sánchez-Torres, A. M., Peralta, V., Gil-Berrozpe, G. J., Mezquida, G., Ribeiro, M., Molina-García, M., … Balanzá-Martínez, V. (2022). The network structure of cognitive deficits in first episode psychosis patients. Schizophrenia Research, 244, 4654. doi: 10.1016/j.schres.2022.05.005CrossRefGoogle Scholar
Sasabayashi, D., Takayanagi, Y., Takahashi, T., Katagiri, N., Sakuma, A., Obara, C., … Suzuki, M. (2020). Subcortical brain volume abnormalities in individuals with an at-risk mental state. Schizophrenia Bulletin, 46(4), 834845. doi: 10.1093/schbul/sbaa011CrossRefGoogle ScholarPubMed
Smeland, O. B., Wang, Y., Frei, O., Li, W., Hibar, D. P., Franke, B., … Andreassen, O. A. (2018). Genetic overlap between schizophrenia and volumes of hippocampus, putamen, and intracranial volume indicates shared molecular genetic mechanisms. Schizophrenia Bulletin, 44(4), 854864. doi: 10.1093/schbul/sbx148CrossRefGoogle ScholarPubMed
Smith, G. N., Thornton, A. E., Lang, D. J., MacEwan, G. W., Kopala, L. C., Su, W., & Honer, W. G. (2015). Cortical morphology and early adverse birth events in men with first-episode psychosis. Psychological Medicine, 45(9), 18251837. doi: 10.1017/S003329171400292XCrossRefGoogle ScholarPubMed
Tate, D. F. (2018). Ventricle-to-Brain (VBR) ratio BT. In Kreutzer, J. S., DeLuca, J. & Caplan, B. (Eds.), Encyclopedia of clinical neuropsychology. Cham: Springer International Publishing, pp 12. doi: 10.1007/978-3-319-57111-9_9075Google Scholar
Ursini, G., Punzi, G., Chen, Q., Marenco, S., Robinson, J. F., Porcelli, A., … Weinberger, D. R. (2018). Convergence of placenta biology and genetic risk for schizophrenia article. Nature Medicine, 24(6), 792801. doi: 10.1038/s41591-018-0021-yCrossRefGoogle Scholar
Valli, I., Segura, A. G., Verdolini, N., Garcia-Rizo, C., Berge, D., Baeza, I., … Zorrilla, I. (2023). Obstetric complications and genetic risk for schizophrenia: Differential role of antenatal and perinatal events in first episode psychosis. Acta Psychiatrica Scandinavica, 148(1), 8190. doi: 10.1111/acps.13546CrossRefGoogle ScholarPubMed
Valli, I., Tognin, S., Fusar-Poli, P., & Mechelli, A. (2012). Episodic memory dysfunction in individuals at high-risk of psychosis: A systematic review of neuropsychological and neurofunctional studies. Current Pharmaceutical Design, 18(4), 443458. doi: 10.2174/138161212799316271CrossRefGoogle ScholarPubMed
Van Horn, J. D., & McManus, I. C. (1992). Ventricular enlargement in schizophrenia. A meta-analysis of studies of the ventricle:brain ratio (VBR). The British Journal of Psychiatry: The Journal of Mental Science, 160(MAY.), 687697. doi: 10.1192/BJP.160.5.687CrossRefGoogle ScholarPubMed
Vassos, E., Kou, J., Tosato, S., Maxwell, J., Dennison, C. A., Legge, S. E., … Murray, R. M. (2022). Lack of support for the genes by early environment interaction hypothesis in the pathogenesis of schizophrenia. Schizophrenia Bulletin, 48(1), 2026. doi: 10.1093/SCHBUL/SBAB052CrossRefGoogle ScholarPubMed
Verdolini, N., Mezquida, G., Valli, I., Garcia-Rizo, C., Cuesta, M., Vieta, E., … Balanzá-Martínez, V. (2023). Obstetric complications and clinical presentation in first episode of psychosis. Acta Neuropsychiatrica, 35(3), 156164. doi: 10.1017/neu.2023.9CrossRefGoogle ScholarPubMed
Wells, R., Jacomb, I., Swaminathan, V., Sundram, S., Weinberg, D., Bruggemann, J., … Weickert, T. W. (2020). The impact of childhood adversity on cognitive development in schizophrenia. Schizophrenia Bulletin, 46(1), 140153. doi: 10.1093/schbul/sbz033CrossRefGoogle ScholarPubMed
Weschler, D. (1997). Wechsler adult intelligence scale-III (WAIS-III). San Antonio, TX: The Psychological Association.Google Scholar
Wortinger, L. A., Barth, C., Nerland, S., Jørgensen, K. N., Shadrin, A. A., Szabo, A., … Agartz, I. (2021). Association of birth asphyxia with regional white matter abnormalities among patients with schizophrenia and bipolar disorders. JAMA Network Open, 4(12), e2139759. doi: 10.1001/jamanetworkopen.2021.39759CrossRefGoogle ScholarPubMed
Wortinger, L. A., Engen, K., Barth, C., Andreassen, O. A., Nordbø Jørgensen, K., & Agartz, I. (2020). Asphyxia at birth affects brain structure in patients on the schizophrenia-bipolar disorder spectrum and healthy participants. Psychological Medicine, 52(6), 10501059. doi: 10.1017/S0033291720002779CrossRefGoogle ScholarPubMed
Wright, I. C., Rabe-Hesketh, S., Woodruff, P. W. R., David, A. S., Murray, R. M., & Bullmore, E. T. (2000). Meta-analysis of regional brain volumes in schizophrenia. American Journal of Psychiatry, 157(1), 1625. doi: 10.1176/AJP.157.1.16/FORMAT/EPUBCrossRefGoogle ScholarPubMed
Yasuda, Y., Okada, N., Nemoto, K., Fukunaga, M., Yamamori, H., Ohi, K., … Hashimoto, R. (2020). Brain morphological and functional features in cognitive subgroups of schizophrenia. Psychiatry and Clinical Neurosciences, 74(3), 191203. doi: 10.1111/pcn.12963CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Sociodemographic, cognitive, and volumetric characteristics of the sample

Figure 1

Table 2. Main effects of, diagnosis group, Lewis C (difficulties during delivery) and its interaction (estimated marginal means and post-hoc comparisons with Bonferroni) on ventricles' volume (mm3 /1000)

Figure 2

Figure 1. Generalized linear model third ventricle predicted values (mm3/1000) by presence/absence of difficulties during delivery (Lewis C; present/absent) stratified by diagnosis (psychosis/control). Predicted third ventricle values are adjusted by covariates, age, sex, difficulties during delivery, diagnosis, chlorpromazine equivalent mean dose, and estimated total intracranial volume.

Figure 3

Figure 2. Generalized linear model predicted verbal memory values and third ventricle-to-brain ratio (FEP patients and controls). Predicted verbal memory values are adjusted by covariates, age, sex, difficulties during delivery, diagnosis, chlorpromazine equivalent mean dose, and educational level.

Figure 4

Table 3. Parameter estimation for cognitive outcomes (verbal memory and working memory)

Supplementary material: File

Costas-Carrera et al. supplementary material

Costas-Carrera et al. supplementary material
Download Costas-Carrera et al. supplementary material(File)
File 38.4 KB