Psychological Medicine
cambridge.org/psm
Original Article
*Joint last authorship.
Cite this article: Fares-Otero NE et al (2024).
Triangulating the associations of different
types of childhood adversity and first-episode
psychosis with cortical thickness across brain
regions. Psychological Medicine 54, 4561–4574.
https://doi.org/10.1017/S0033291724002393
Received: 3 May 2024
Revised: 22 August 2024
Accepted: 2 September 2024
First published online: 16 December 2024
Keywords:
adolescents; adults; brain structure; bullying;
childhood maltreatment; early life adversity;
early psychosis; frontal cortex; MRI; neglect;
neuroimaging; stress
Corresponding authors:
Natalia E. Fares-Otero;
Email: nefares@recerca.clinic.cat;
Eduard Vieta;
Email: evieta@clinic.cat;
Celso Arango;
Email: carango@hggm.es
© The Author(s), 2024. Published by
Cambridge University Press. 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.
Triangulating the associations of different
types of childhood adversity and first-episode
psychosis with cortical thickness across
brain regions
Natalia E. Fares-Otero1,2,3,4 , Norma Verdolini1,2,3,4,5 , Helena Melero6 ,
Pablo Andrés-Camazón7 , Enric Vilajosana3 , Vito Cavone7 ,
Borja García-Bueno8 , Marta Rapado-Castro7,9 , Ana Izquierdo10 ,
David Martín-Hernández8 , Pablo Mola Cárdenes11 , Itziar Leal10 ,
Monica Dompablo12,13, Ana Ortiz-Tallo10 , Isabel Martinez-Gras12,
Ainoa Muñoz-Sanjose14 , Carmen Loeck de Lapuerta15 ,
Roberto Rodriguez-Jimenez12 , Marina Díaz Marsá11 ,
Maria-Fe Bravo-Ortiz14 , Angela Ibañez15 , Enrique Baca-García16,17 ,
Eduard Vieta1,2,3,4 , J. L. Ayuso-Mateos10 , Norberto Malpica18 ,
Celso Arango7 , Covadonga M. Díaz-Caneja7,* and Joaquim Radua2,3,4,*
1Bipolar and Depressive Disorders Unit, Department of Psychiatry and Psychology, Hospital Clínic, Institute of
Neurosciences (UBNeuro), Barcelona, Catalonia, Spain; 2Department of Medicine, Faculty of Medicine and Health
Sciences, University of Barcelona (UB), Barcelona, Catalonia, Spain; 3Institut d’Investigacions Biomèdiques August Pi i
Sunyer (IDIBAPS), Barcelona, Catalonia, Spain; 4Centro de Investigación Biomédica en Red de Salud Mental
(CIBERSAM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain; 5Local Health Unit Umbria 1, Department of Mental
Health, Mental Health Center of Perugia, Perugia, Italy; 6Department of Psychobiology and Methodology in Behavioural
Sciences, University Complutense of Madrid (UCM), Madrid, Spain; 7Department of Child and Adolescent Psychiatry,
Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón (IiSGM), CIBERSAM, ISCIII,
School of Medicine, UCM, Madrid, Spain; 8Department of Pharmacology and Toxicology, School of Medicine, UCM,
Instituto de Investigación Hospital 12 de Octubre (imas12), Instituto Universitario de Investigación en Neuroquímica
(IUIN), CIBERSAM, ISCIII, Madrid, Spain; 9Department of Psychiatry, Melbourne Neuropsychiatry Centre, The University
of Melbourne and Melbourne Health, Melbourne, VIC, Australia; 10Department of Psychiatry, Universidad Autónoma de
Madrid, Instituto de Investigación Sanitaria Princesa (IIS-Princesa), CIBERSAM, ISCIII, Madrid, Spain; 11Department of
Legal Medicine, Psychiatry and Pathology; Faculty of Medicine, Health Research Institute, Hospital Clínico San Carlos
(IdISSC), UCM, CIBERSAM, ISCIII, Madrid, Spain; 12Department of Psychiatry, Instituto de Investigación Sanitaria
Hospital 12 de Octubre (imas12), CIBERSAM-SCIII, School of Medicine, Universidad Complutense de Madrid (UCM),
Madrid, Spain; 13Cardenal Cisneros, Centro de Enseñanza Superior Adscrito a la Universidad Complutense de Madrid,
Madrid, Spain; 14Department of Psychiatry, Clinical Psychology, and Mental Health, Instituto de Investigación Hospital
Universitario La Paz (IdiPaz), University Hospital La Paz, CIBERSAM, ISCIII, Universidad Autónoma de Madrid (UAM),
Madrid, Spain; 15Department of Psychiatry, Hospital Universitario Ramón y Cajal, IRYCIS, Universidad de Alcala,
CIBERSAM, ISCIII, Madrid, Spain; 16Department of Psychiatry, Hospital Universitario Fundación Jiménez Díaz, Hospital
Universitario Rey Juan Carlos, Hospital General de Villalba, Hospital Universitario Infanta Elena, CIBERSAM, ISCIII, UAM,
Madrid, Spain; 17Department of Psychiatry, Centre Hospitalier Universitaire de Nîmes, Nîmes, France and 18Medical
Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Madrid, Spain
Abstract
Background. Both childhood adversity (CA) and first-episode psychosis (FEP) have been
linked to alterations in cortical thickness (CT). The interactive effects between different
types of CAs and FEP on CT remain understudied.
Methods. One-hundred sixteen individuals with FEP (mean age = 23.8 ± 6.9 years, 34% females,
80.2% non-affective FEP) and 98 healthy controls (HCs) (mean age = 24.4 ± 6.2 years, 43%
females) reported the presence/absence of CA <17 years using an adapted version of the
Childhood Experience of Care and Abuse (CECA.Q) and the Retrospective Bullying
Questionnaire (RBQ) and underwent magnetic resonance imaging (MRI) scans. Correlation ana-
lyses were used to assess associations between brain maps of CA and FEP effects. General linear
models (GLMs) were performed to assess the interaction effects of CA and FEP on CT.
Results. Eighty-three individuals with FEP and 83 HCs reported exposure to at least one CA.
CT alterations in FEP were similar to those found in participants exposed to separation from
parents, bullying, parental discord, household poverty, and sexual abuse (r = 0.50 to 0.25).
Exposure to neglect (β =−0.24, 95% CI [−0.37 to −0.12], p = 0.016) and overall maltreatment
(β =−0.13, 95% CI [−0.20 to −0.06], p = 0.043) were associated with cortical thinning in the
right medial orbitofrontal region.
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
Conclusions. Cortical alterations in individuals with FEP are similar to those observed in the
context of socio-environmental adversity. Neglect and maltreatment may contribute to CT
reductions in FEP. Our findings provide new insights into the specific neurobiological effects
of CA in early psychosis.
Introduction
Psychotic disorders are among the leading causes of disability
(Navarro-Mateu et al., 2017) and a public health concern world-
wide (Anderson, 2019). Besides genetic predisposition, severe
forms of childhood adversity (CA), such as childhood abuse or
neglect, parental discord or loss, peer bullying, or household pov-
erty, have consistently been shown to strongly increase the risk for
mental disorders, including psychotic disorders (Arango et al.,
2021; Morgan & Gayer-Anderson, 2016). CA is the most robust
and potentially modifiable risk factor for schizophrenia spectrum
disorders (Dragioti et al., 2022) and can also influence the clinical
manifestations and course of the illness (Rosenfield, Jiang, &
Pauselli, 2022; Sideli et al., 2020; Turner et al., 2019), including
social and functional outcomes (Christy et al., 2023;
Fares-Otero et al., 2023a). General population-based studies indi-
cate that approximately half of all children will experience at least
one form of adversity by the time they reach adulthood
(McLaughlin, Weissman, & Bitrán, 2019), and approximately
half of youth with first-episode psychosis (FEP) report at least
one type of CA (Vila-Badia et al., 2022).
At a neurobiological level, CA has been found to trigger a cas-
cade of neurobiological processes that may impact brain structure
and function (Begemann et al., 2023; Lim, Howells, Radua, &
Rubia, 2020; Quinlan et al., 2020). CA can lead to lasting structural
changes in a number of brain regions that include cortical regions
relevant for processing trauma information, as well as key areas
implicated in emotion processing, such as the anterior cingulate
cortex and hippocampus, as well as in threat processing and
higher-order cognitive functions, such as the amygdala (Calem,
Bromis, McGuire, Morgan, & Kempton, 2017; Gold et al., 2016;
Teicher, Samson, Anderson, & Ohashi, 2016) and the orbitofrontal
cortex (Bounoua, Miglin, Spielberg, Johnson, & Sadeh, 2022). Such
structural changes may be adaptive in the face of expected future
adversity and seem to extend to most individuals exposed to adver-
sity, regardless of psychopathology. Interestingly, there seems to be
an overlap between brain structures and regions affected in people
exposed to CA and those reported to be altered in psychotic disor-
ders (Hoy et al., 2012), including reductions in hippocampal vol-
ume (Adriano, Caltagirone, & Spalletta, 2012) and
fronto-temporal, insular and occipital abnormalities with a similar
pattern in both FEP (Vieira et al., 2021) and those exposed to CA
(Calem et al., 2017; Pollok et al., 2022).
The vulnerability-stress and traumagenic neurodevelopmental
models of psychosis posit that CAs may impact the structural
development of the brain over time, increasing the vulnerability
of exposed individuals to FEP (Lardinois, Lataster, Mengelers,
Van Os, & Myin-Germeys, 2011; Read, Fosse, Moskowitz, &
Perry, 2014). However, to date, neuroimaging studies of CA in
individuals with FEP have focused mostly on volume changes
in some brain structures, e.g., the hippocampus and/or amygdala
(Aas et al., 2012; du Plessis et al., 2020; Hoy et al., 2012).
Although this work has been important for understanding how
CA shapes key stress-related brain mechanisms in people with
FEP, this approach has prevented comprehensive research on
whole-brain regions. Cortical thickness, which reflects the num-
ber of neurons within cortical columns (Narr et al., 2005; Rakic,
1988), appears to be highly susceptible to environmental factors
and could constitute a more specific and biologically meaningful
metric of neurodevelopmental processes than brain volume
(Panizzon et al., 2009).
A number of studies have indicated the effects of CAs on cor-
tical thickness (Cassiers et al., 2018). For instance, one study
demonstrated reduced visual cortex thickness in adults who wit-
nessed domestic violence in childhood (Tomoda, Polcari,
Anderson, & Teicher, 2012). A meta-analysis revealed that neglect
and abuse were associated with reduced thickness in the superior
temporal sulcus, supramarginal gyrus, parietal lobe, middle tem-
poral lobe, and the praecuneus (Tozzi et al., 2020). Additionally,
in individuals with FEP, several studies have shown cortical altera-
tions in fronto-temporal networks (Schultz et al., 2010) and the
prefrontal cortex (Wiegand et al., 2004). These cortical alterations
have been mostly observed in those with non-affective (v. affect-
ive) FEP (Zhao et al., 2022).
While several studies have previously reported data on reduced
cortical thickness in people with FEP (Crespo-Facorro et al., 2011;
Pigoni et al., 2021; Pina-Camacho et al., 2022; Wiegand et al.,
2004), as well as in those exposed to CAs (McCrory, De Brito,
& Viding, 2011; Teicher et al., 2016; Yang et al., 2023), no previ-
ous study has explored potential similarities between patterns of
CA and FEP on cortical thickness alterations or assessed the
link between the effects of exposure to different types of CAs
and FEP on cortical thickness across brain regions.
Disentangling the effects of FEP from those of CAs is an import-
ant step in better understanding psychotic disorders and could
have important consequences for prevention, diagnosis, and treat-
ment. Furthermore, previous evidence indicates differential effects
of specific types of CA (physical, emotional, sexual abuse, neglect)
(Cancel et al., 2015; Stevelink et al., 2018) and dimensional
approaches (threat v. deprivation) on brain architecture
(LoPilato et al., 2019; Thomas et al., 2023), which could help dis-
entangle the neurobiological correlates of CA in psychosis; how-
ever, further studies are needed in individuals with FEP.
Consequently, we explored the differential and shared patterns
of cortical thickness alterations associated with exposure to CA
and FEP and we investigated the interactive effects of different
types/dimensions of CA and FEP on cortical thickness across
brain regions. On the basis of collective evidence from previous
studies (Cascino et al., 2023; Kim et al., 2023; Luo et al., 2023;
Rapado-Castro et al., 2020), we hypothesized that FEP and CA
would be associated with reduced cortical thickness and that
interactive effects across brain regions would be dependent on
CA types and dimensions.
Methods
Participants and study design
This study includes participants from the ‘Genes and Environment
in Schizophrenia’ (AGES-CM) project (https://web.agescm.es/), an
4562 Natalia E. Fares‐Otero et al.
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
ongoing multicentric study carried out at the seven largest univer-
sity hospitals in the Community of Madrid, Spain, that recruits
patients seeking help for recent-onset psychosis. The study proto-
col, sampling characteristics and methods are described in detail
elsewhere (Izquierdo et al., 2021). Briefly, the study included socio-
demographic, clinical and functional examinations, CA question-
naires, and brain magnetic resonance (MRI) scanning.
The study obtained ethical approval from the medical research
ethics committee of the coordinating center Hospital General
Universitario Gregorio Marañón (identification number 355/12),
and was subsequently reviewed and approved by the research eth-
ics committee of each participating center. The study was con-
ducted in accordance with the Declaration of Helsinki and its
later amendments. Prior to study inclusion, participants and/or
their legal guardians provided written informed consent.
The inclusion criteria for individuals with FEP were as follows:
(a) aged between 7 and 40 years at the time of the first evaluation;
(b) experienced FEP (Breitborde, Srihari, & Woods, 2009) with a
total lifetime duration of positive psychotic symptoms shorter
than 24 months; and (c) provided written informed consent or
parental consent for the minors. The exclusion criteria were (a)
meeting diagnostic criteria for another current Axis-I mental dis-
order (except for substance use disorder); (b) the presence of
intellectual disability, defined as an intelligence quotient (IQ) <
70 with impaired functioning; (c) a history of neurodevelopmen-
tal and/or neurological disorders (e.g. epilepsy) or head injury
with loss of consciousness; and (d) were pregnant at the time of
signing the consent form. The inclusion criteria for HCs were
as follows: (a) aged between 7 and 40 years at the time of the
first evaluation and (b) provided written informed consent or par-
ental consent for the minors. The exclusion criteria were (a) met
the diagnostic criteria for current Axis-I mental disorders; (b) had
a history of intellectual disability or a history of neurodevelop-
mental and/or neurological disorders or head injury with loss
of consciousness; (c) had a family history of a psychotic disorder
in a first- or second-degree relative; (d) were pregnant at the time
of signing the consent form; and (e) refused to perform MRI or
blood tests to ensure that neuroimaging data and laboratory sam-
ples were obtained.
Additional exclusion criteria, for both participants with FEP
and HCs, to undergo MRI assessment were contraindications
such as metal implants or claustrophobia.
Sociodemographic data and clinical assessment
Relevant sociodemographic data, including age, sex, ethnicity, edu-
cational level, marital status, and work status were collected. Parental
socioeconomic status (SES) was determined using Hollingshead’s
Two-Factor Index of Social Position (Hollingshead & Redlich,
2007), a common system that is based upon parental occupation
and educational levels (i.e. years of education and highest educa-
tional degree of the parent with the highest level).
Clinical assessment was conducted by trained psychiatrists or
psychologists who confirmed the diagnosis of FEP, including
non-affective (i.e. schizophrenia spectrum and other psychoses)
v. affective FEP (i.e. bipolar disorder type I or major depressive
disorder with psychotic symptoms), using the Semistructured
Diagnostic Interview for DSM-IV-TR Axis I Disorders (SCID-I)
or the Spanish version of the Kiddie Schedule for Affective
Disorders and Schizophrenia for School-Age Children-Present
and Lifetime version (K-SADS-PL) (Ulloa et al., 2006), as
appropriate. Further clinical assessment details and the reliability
of the instruments used are presented in S1 in the Supplement.
Childhood adversity
Self-reported exposure to different types of CA was determined
using an adapted version of the Childhood Experience of Care
and Abuse Questionnaire (CECA-Q) (Bifulco, Bernazzani,
Moran, & Jacobs, 2005). The CECA-Q is designed to assess CA
that occurs before the age of 17 years, including emotional or
physical abuse by the main parental figures (usually but not
necessarily the biological mother or father), sexual abuse by any
adult or an individual at least five years older than the recipient,
neglect, i.e. physical neglect or failure to give needed care or atten-
tion, and emotional neglect, including neglectful failure to supply
emotional needs (Golden, Samuels, & Southall, 2003), household
poverty, parental discord (including frequent disagreements and
insults between parents), separation from a parent that involved
living apart from the parent for at least 6 months, death of a par-
ent or parental loss, and/or being expelled or suspended from
school and/or high school. Each CA (occurring < 17 years) was
scored dichotomously as being present or absent for the partici-
pant. The items were dichotomously scored as 0 = no (‘did not
apply to me at all’) or 1 = yes (‘applied to me’) based on a previous
report (Fisher et al., 2009).
A history of bullying by peers, including emotional or verbal
and/or physical victimization, before 17 years of age was assessed
using an adapted short version of the Retrospective Bullying
Questionnaire (RBQ) (Guloksuz et al., 2019; Schäfer et al.,
2004), which measures the self-reported severity of bullying
exposure as follows: 0 = ‘none’; 1 = ‘some (no physical injuries)’;
2 = ‘moderate (minor injuries or transient emotional reactions)’;
3 = ‘marked (severe and frequent physical or emotional harm)’.
For the purposes of this study, exposure to childhood bullying
was dichotomized using≥ 1 as the cut-off point (0 = ‘absent’
and ≥1 = ‘present’).
Based on the dimensional model of early adversity
(McLaughlin, Sheridan, & Lambert, 2014) and prior evidence syn-
thesis (Thomas et al., 2023), we operationalized deprivation as
experiences of emotional and/or physical neglect (or failure to
meet the child’s basic needs, including food and clothing), house-
hold poverty, and separation from parents (i.e. when the child’s
attachment to his or her caregiver is significantly broken due to
no or poor quality care being given to the child) > 6 months.
This period is long enough for the child-caregiver bond to be ser-
iously damaged. We operationalized threat as emotional, physical
or sexual abuse; bullying (i.e. emotional and/or physical peer vic-
timization); and parental discord (including witnessing parental
victimization) (Peverill et al., 2023; Sumner, Colich, Uddin,
Armstrong, & McLaughlin, 2019).
MRI acquisition, image data processing, and cortical thickness
calculation
Structural whole-brain T1-weighted images were acquired using a
3T General Electric Signa HDxt scanner with a 3D FSPGR (cor-
onal slices parallel to the anterior commissure-posterior line with-
out a gap; repetition time, 1900 ms; echo time, 2.6 ms; field of
view, 220 mm; matrix size, 256 × 256; slice thickness, 1 mm;
voxel volume, 0.86 × 0.86 × 1mm2; flip angle, 16°; number of exci-
tations, 1). The quality of the scans was visually assessed prior to
image processing, and no scans were deemed of insufficient
Psychological Medicine 4563
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
quality. FreeSurfer (v6.0, http://surfer.nmr.mgh.harvard.edu/) was
used to estimate cortical thickness (Fischl et al., 2002) for 68 cor-
tical regions of interest (ROIs, 34 in the left hemisphere and 34 in
the right hemisphere) of the ‘Desikan-Killiany’ cortical atlas
(Desikan et al., 2006). All the segmentation methods were
found to be accurate after visual inspection.
Statistical analyses
Frequency analysis was performed to evaluate the characteristics
of the sample. To test for differences in categorical variables, chi-
square tests (χ2) were performed between groups. To test for dif-
ferences in continuous variables, Student’s t test was used.
Pearson correlations were performed between the brain maps
of CA effects and the brain map of FEP effects (in participants
not exposed to CA). General linear models (GLMs) were per-
formed to assess the interactive effects between different CAs
and FEP on cortical thickness. The Family-Wise Error Rate
(FWER) Holm method (Holm, 1979) was used to correct p values
( pcorr) for multiple comparisons across multiple cortical regions.
Age and sex were considered covariates given that these factors
have been associated with neural structure developmental trajec-
tories between childhood and early adulthood (Cheng et al.,
2021; Kim et al., 2023; Luo et al., 2023).
Power and sample size calculation for analyzing the different
interaction effects was performed using the R package
InteractionPoweR (Baranger et al., 2023). With 214 individuals,
the power to detect a weak to moderate interaction correlation
(0.35) with p < 0.05/1292 (the number of interactions to test: 19
CAs × 68 cortical regions) was 80.7%.
For all analyses, p values less than 0.05 and 95% confidence
intervals (CIs) were used to indicate statistical significance.
Statistical analyses were conducted using R version 4.1.2
(R Core Team, 2021), and brain figures were created using the
ggseg package (Mowinckel & Vidal-Piñeiro, 2020).
Results
Participant characteristics
Of 357 individuals recruited in the AGES-CM 2-CM project, 214
who completed MRI scans and CA measurements at baseline were
included; 116 individuals with FEP (mean age ± S.D. = 23.8 ± 6.9
years, 34% female, 80.2% non-affective FEP), and 98 HCs
(mean age ± S.D. = 25.1 ± 5.3 years, 43% female). No significant
differences were found between groups with respect to age, sex,
or educational level. Further sociodemographic and clinical char-
acteristics of the study population are presented in Table 1.
Exposure to CA types in the sample
Frequencies of exposure to each CA type in participants with FEP
are shown in Table 1, and in those with non-affective v. affective
FEP are shown in Table S2 in the Supplement. The percentages of
individuals who reported at least one CA (72% FEP v. 85% HCs,
p = 0.01) and overall maltreatment (i.e. physical/emotional/sexual
abuse and/or physical/emotional neglect) (27% FEP v. 41% HCs,
p = 0.04) were greater in HCs than in individuals with FEP.
Correlations between brain maps of CA effects and FEP effects
The spatial distribution of cortical thickness abnormalities was
similar (r = 0.82) in individuals with CA and in those with FEP
(v. HCs). When different types of CA were considered, cortical
thickness alterations in individuals with FEP were similar to
those found in individuals with exposure to separation from par-
ents (>6 months), bullying, parental discord, household poverty,
and sexual abuse (r = 0.50 to 0.25), see online Supplementary
Table S3 and for diagnoses (non-affective v. affective psychosis)
see Table S4 in the Supplement.
Interaction between CA and FEP effects on cortical thickness
In terms of CA and FEP, exposure to any adversity ( p = 0.008),
threat ( p = 0.042), or overall maltreatment ( p = 0.045) was asso-
ciated with experiencing FEP. This significant association between
CA and experiencing FEP was observed in non-affective psychosis
(see Table S5.1 in the Supplement).
In terms of FEP and cortical thickness, experiencing FEP was
associated with cortical thinning in both the left and right hemi-
spheres across the occipital, temporal, parietal, and frontal regions
( p < 0.001 to p = 0.039) (see Fig. 1). This significant association
between FEP and cortical thickness was observed in non-affective
psychosis (see Tables S5.2 and S5.3 in the Supplement).
In HCs, exposure to emotional abuse (β =−0.09, [−0.14 to
−0.04], pcorr = 0.026) was associated with cortical thinning in
the left hemisphere paracentral region, whereas sexual abuse (β
= 0.14, [0.06–0.22], pcorr = 0.040) was associated with cortical
thickening in the left hemisphere medial orbitofrontal region
(see Fig. 2).
In the overall FEP sample, exposure to neglect was associated
with cortical thinning in the right medial orbitofrontal region (β
=−0.24, [−0.37 to −0.12], pcorr = 0.016). This significant inter-
action effect between FEP and neglect was observed for both non-
affective FEP (β =−0.22, [−0.35 to −0.10], uncorrected p = 0.001)
and affective FEP (β =−0.31, [−0.51 to −0.10], uncorrected p =
0.004). We also found that exposure to overall maltreatment (β
=−0.13, [−0.20 to −0.06], pcorr = 0.043) was associated with cor-
tical thinning in the right medial orbitofrontal region. This sig-
nificant interaction effect between FEP and overall maltreatment
was observed for both non-affective FEP (β =−0.12, [−0.19 to
−0.04], uncorrected p = 0.002) and affective FEP (β = −0.17,
[−0.29 to −0.04], uncorrected p = 0.011) (see Figs 3 and 4).
In those with affective psychosis, a significant interaction effect
was observed between experiencing FEP and exposure to emo-
tional bullying on cortical thickening in the right hemisphere pos-
terior cingulate cortex (β = 0.34, [0.19–0.49], pcorr = 0.002); (see
Fig. S1 in the Supplement). In those with non-affective psychosis,
no interaction effects were observed between FEP and exposure to
CA on cortical thickness measures.
Discussion
Here, we aimed to identify differential and shared patterns of cor-
tical thickness alterations associated with exposure to CAs and
FEP and to explore the interactive effects of different types of
CA and FEP on cortical thickness across brain regions. This
approach allowed us to disentangle the effects of FEP from
those of CA on cortical alterations.
First, when exploring deviant cortical thickness patterns asso-
ciated with CA and FEP across brain regions, we found that cor-
tical thickness alterations observed in people with FEP were
similar to those observed in people exposed to CA. This finding
is in line with prior neuroimaging studies on brain volume (Aas
et al., 2012; du Plessis et al., 2020; Hoy et al., 2012).
4564 Natalia E. Fares‐Otero et al.
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
Table 1. Sociodemographic and clinical characteristics of the sample (N = 214)
FEP (n = 116) HCs (n = 98) t or X2, p value, Cohen’s d
Sociodemographic variables
Age, Mean in years (S.D.), [range] 23.77 (6.88), [11–44] 25.11 (5.29), [12–39] t = 1.62, p = 0.11, d = 0.22
Sex, Female, No. (%) 39 (33.6) 42 (42.9) χ2 = 1.55, p = 0.21, d = 0.17
Ethnicity, No. (%) χ2 = 5.57, p = 0.23, d = 0.33
Caucasian 95 (81.9) 90 (91.8)
Hispanic 15 (12.9) 7 (7.1)
African 3 (2.6) 1 (1.0)
Gipsy 2 (1.7) –
Other 1 (0.7) –
Education level, No. (%) χ2 = 7.26, p = 0.30, d = 0.37
Primary 12 (10.5) 4 (4.1)
Secondary 70 (60.9) 54 (55.1)
Tertiary 30 (26.1) 36 (36.7)
Other 2 (2.6) 4 (4.1)
Marital status, No. (%) χ2 = 1.86, p = 0.60, d = 0.19
Single 101 (87.8) 85 (87.6)
Married 10 (8.7) 11 (11.3)
Divorced/separated 4 (3.5) 1 (1.0)
Work status, No (%) χ2 = 48.82, p = 0.00, d = 1.09
Currently working 9 (8.2) 51 (52.0)
Student 54 (49.1) 26 (26.5)
Inactive 47 (42.7) 21 (21.4)
SESa, Mean (S.D.) 40.7 (18.17) 45.26 (16.60) t =−1.87, p = 0.06, d =− 0.26
Functioning
GAF/C-GAS score 52.77 (15.04) 90.02 (9.83) t = 21.64, p < 0.001, d = 2.97
Childhood adversitiesb No. (%)
Any adversityc 83 (71.6) 83 (84.7) χ2 = 6.36, p = 0.01, d = 0.35
Overall maltreatmentd 31 (26.7) 40 (40.8) χ2 = 4.44, p = 0.04, d = 0.29
Emotional abuse 29 (25.0) 16 (16.3) χ2 = 3.81, p = 0.05, d = 0.27
Physical abuse 20 (17.2) 18 (18.4) χ2 = 0.00, p = 0.99, d = 0.00
Sexual abuse 11 (9.5) 7 (7.1) χ2 = 1.12, p = 0.29, d = 0.16
Neglecte (emotional and physical) 9 (7.8) 8 (8.2) χ2 = 0.11, p = 0.75, d = 0.05
Parental discordf 52 (44.8) 43 (43.8) χ2 = 0.19, p = 0.66, d = 0.06
Parental death or loss 3 (2.6) 5 (5.1) χ2 = 0.01, p = 0.91, d = 0.01
Separation from parentsg 32 (27.6) 35 (35.7) χ2 = 1.52, p = 0.22, d = 0.17
Expelled from schoolh 26 (22.4) 18 (18.4) χ2 = 0.16, p = 0.65, d = 0.05
Household poverty 36 (31.3) 28 (28.6) χ2 = 0.71, p = 0.40, d = 0.12
Peer bullyingi 40 (34.5) 24 (24.5) χ2 = 1.58, p = 0.21, d = 0.17
Emotional/verbal bullying 30 (25.9) 22 (22.4) χ2 = 1.09, p = 0.58, d = 0.14
Physical bullying 12 (10.3) 8 (8.2) χ2 = 6.11, p = 0.43, d = 0.34
Threatj No. (%) 66 (56.9) 66 (67.3) χ2 = 0.07, p = 0.80, d = 0.05
Deprivationk No. (%) 57 (49.1) 46 (46.9) χ2 = 2.46, p = 0.12, d = 0.31
Clinical variables
(Continued )
Psychological Medicine 4565
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
Importantly, when different types/dimensions of CA were consid-
ered, cortical alterations in people with FEP were similar to those
associated predominantly with socio-environmental exposures
reflecting enduring social adversity and isolation or interpersonal
hostility (e.g. socio-economic deprivation, family disadvantage,
negative peer relationships) relative to other types of CA, such
as parental death or having been expelled from school. Further
studies are needed to explore the moderating factors and under-
lying pathways through which this association occurs, e.g., attach-
ment, mood symptoms, or cognitive ability (Cortes Hidalgo et al.,
2024; Fares-Otero et al., 2023a; Newbury et al., 2023).
Second, we found that exposure to certain types/dimensions of
CA (i.e. maltreatment, threat) was associated with an increased
likelihood of experiencing FEP and that experiencing FEP was
related to reduced cortical thickness in several cortical regions
of both hemispheres, which is in line with findings of previous
studies (Gong, Lui, & Sweeney, 2016; Scanlon et al., 2014; Wen
et al., 2021). Consistent with previous research (Trauelsen et al.,
2015; Zhao et al., 2022), cortical thickness deficits were found
in non-affective psychosis only. However, future studies in larger
samples with affective psychosis are warranted.
Intriguingly, in our sample of healthy subjects, we found that
emotional abuse was associated with cortical thinning in the left
hemisphere paracentral region, whereas sexual abuse was asso-
ciated with cortical thickening in the medial orbitofrontal region.
Notably, no effects of sexual abuse on cortical thickness have been
shown in trauma-exposed adolescents (Rinne-Albers et al., 2020),
although prospective research is needed to further evaluate the
Table 1. (Continued.)
FEP (n = 116) HCs (n = 98) t or X2, p value, Cohen’s d
Diagnostic subgroupl, No (%)
Non-affective psychosis 93 (80.2) – –
Affective psychosis 23 (19.8) – –
PANSS, Mean (S.D.)
Positive 14.74 (7.29) – –
Negative 17.18 (8.00) – –
General 33.59 (13.24) – –
Total 65.51 (24.25) – –
HDRS, Mean (S.D.) 11.21 (8.54) – –
YMRS, Mean (S.D.) 5.69 (7.91) – –
CGI-S, Mean (S.D.) 2.66 (1.72) – –
DUP, Mean (S.D.) 118.1 (185.29) – –
Psychopharmacological treatment Medication > 1, No (%) 19 (17.4)
Risperidone 39 (35.8) – –
Aripiprazole 21 (19.3) – –
Olanzapine 14 (12.8) – –
Quetiapine 10 (9.2) – –
Amisulpride 8 (7.3) – –
Paliperidone 4 (3.7) – –
Clozapine 4 (3.7) – –
Haloperidol 1 (0.9) – –
Other 8 (7.3) – –
C-GAS, Child Global Assessment Scale; CGI-S, Illness severity; DUP, Duration of Untreated Psychosis (in days); GAF, Global Assessment of Functioning; HC, Healthy control group; HDRS,
Hamilton Depression Rating Scale; NA, Not available; YMRS, Young Mania Rating Scale; PANNS, Positive and Negative Syndrome Scale; S.D., Standard deviation.
Note: In all cells, % refers to percentages (within columns) of participants for whom information was available. For qualitative variables, Chi-square (χ2) test was used. For quantitative
variables, Student t test was used, significant at p < 0.05; Cohen’s d was used for standardized effect sizes (0.20 = small, 0.50 = medium, and 0.80 = high) (Cohen, 1988).
aSES: Socioeconomic Status defined with the Hollingshead’s Index.
bFrequencies reflect experience of at least one behavior associated with each childhood adversity (CA) subtype occurring before the age of 17 years.
cWith at least one CA.
dOverall maltreatment: Frequencies reflect experience of at least one behavior associated with each abuse or neglect subtype occurring before the age of 17 years.
eNeglect: the failure to meet child’s basic needs (emotional and/or physical).
fParental discord: domestic violence including witnessing the abuse or violence of their parents.
gSeparation from parents: a parent-child separation that involved living apart from the parent > 6 months.
hExpelled from school and/or high school.
iPeer bullying: Frequencies reflect experience of at least one behavior associated with each bullying subtype (i.e. emotional/verbal, or physical).
jThreat: experiences of harm or threat of harm (i.e. emotional, physical, sexual abuse, bullying, parental discord).
kDeprivation: the absence of expected inputs from the environment or absence of stimulation that occurs in the context of caregiver interactions (i.e. experiences of neglect, household
poverty, separation from parents > 6 months).
lNon-affective FEP: schizophrenia spectrum disorders and other psychoses; Affective FEP: bipolar disorder type I or major depressive disorder with psychotic symptoms.
4566 Natalia E. Fares‐Otero et al.
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
differential biological and pathological consequences of sexual
abuse.
In addition to the independent effects of FEP and CAs on cor-
tical thickness in certain brain regions, we confirmed the inter-
active effects of CAs and FEP on cortical thickness, with
differential effects of some CAs on specific brain regions, which
is in line with previous research (LoPilato et al., 2019;
Rapado-Castro et al., 2020). This finding also supports converging
evidence on common underlying mechanisms and unique path-
ways of different types of CA that emerge from the immediate
surroundings of an individual (Vaidya, Marquand, Nees, Siehl,
& Schumann, 2024). It is crucial to further investigate the cumu-
lative/interactive effects resulting from exposure to multiple
adverse events, both simultaneously and successively, i.e., by mir-
roring the complex and interconnected nature of real-life
situations.
As a main finding, exposure to neglect and overall maltreat-
ment were significantly associated with reduced cortical thickness
in the right medial orbitofrontal cortex in FEP. Our findings may
also support emerging preliminary data suggesting that patients
with psychotic disorders and a history of maltreatment may con-
stitute a distinct neurobiological subgroup (Kaufman & Torbey,
2019). Notably, in our study, cortical alterations in FEP were spe-
cifically related to interpersonal (family and peers) dysfunction.
Furthermore, comparable results in both non-affective and affect-
ive FEP suggest potential common neurobiological pathways for
CA across the psychosis spectrum. Understanding these neuro-
biological mechanisms could provide new intervention targets
for individuals with FEP and CA.
The medial orbitofrontal cortex is a subregion of the ventro-
medial prefrontal cortex that regulates sensitivity to outcome value
and is involved in evaluation, goal decision-making, and mainten-
ance of a choice over successive decisions (Molinaro & Collins,
2023). An essential component of goal-directed decision-making is
the ability to maintain flexible responses based on the value of a
given reward or ‘reinforcer’ (Noonan, Kolling, Walton, &
Rushworth, 2012), and the medial orbitofrontal cortex is uniquely
positioned to regulate this process (Gourley, Zimmermann, Allen,
Figure 1. Effects of FEP on cortical thickness.
Note: LH, left hemisphere; RH, right hemisphere; lighter blue represents cortical thinning.
Figure 2. Effects of CA on cortical thickness in HCs.
Note: HCs, healthy controls; LH, left hemisphere; MEDIAL, medial view of the brain; lighter blue represents cortical thinning; stronger orange represents cortical
thickening. The figure on the left shows that exposure to emotional abuse was associated with cortical thinning in the left hemisphere paracentral region; the
figure on the right shows that sexual abuse was associated with cortical thickening in the left hemisphere medial orbitofrontal region in HCs.
Psychological Medicine 4567
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
& Taylor, 2016). Hypoactivation of brain areas of the reward system
has been found in people with both CA (Armbruster-Genç et al.,
2022; Boecker et al., 2014; Dillon et al., 2009; Oltean, Șoflău, Miu,
& Szentágotai-Tătar, 2023) and FEP (Fett et al., 2019).
In fact, goal-oriented reward decision-making dysfunction
is a key feature of psychotic psychopathology and has been
identified as a variable that increases individuals’ vulnerability
to negative symptoms (Cooper et al., 2019; Reddy et al., 2018).
The localization of cortical thickness deficits in the medial
orbitofrontal cortex in the presence of FEP is consistent with
previous findings that suggest an association between medial
orbitofrontal cortical thinning and negative symptom severity in
patients with schizophrenia (Walton et al., 2018). Taken together,
our findings further support the involvement of reward
mechanisms in the pathophysiology of FEP and suggest that the
dysregulation of reward mechanisms may be, at least in part,
linked to CA. These effects of CA on behavior and reward-related
cortical areas could underlie deficits in autonomy and social life
through alterations in motivation and effortful decision making
observed in people with psychotic disorders (Fares-Otero et al.,
2023a) and affective disorders with psychotic features (Fares-
Otero et al., 2023b).
Interestingly, we found that exposure to emotional bullying
(verbal victimization) was associated with increased cortical
thickness in the posterior cingulate cortex in those with affective
FEP. Specifically, the posterior cingulate cortex has been demon-
strated to be involved in both narrative comprehension and
autobiographical memories, such as those concerning friends
and family, and in emotional memory imagery. In addition, the
posterior cingulate cortex forms a central node in the default
mode network of the brain (Leech, Braga, & Sharp, 2012), and
it has been linked to psychotic symptoms such as hallucinations,
delusions, disorganized thinking, and a lack of emotional intelli-
gence (Maddock, Garrett, & Buonocore, 2001). Further research
Figure 3. Interaction effects of FEP and CA on cortical thickness.
Note: MEDIAL, Medial view of the brain; RH, Right hemisphere; Lighter blue represents cortical thinning. Brain figures show significant interaction effects of FEP and
both exposure to neglect (left) and overall maltreatment (right) on cortical thinning in the right medial orbitofrontal region.
Figure 4. Interaction effects of neglect/overall maltreatment and FEP on right medial orbitofrontal cortical thickness.
Note: Experiencing FEP together with neglect (A) or overall maltreatment (B) was associated with cortical thinning in the right medial orbitofrontal region.
4568 Natalia E. Fares‐Otero et al.
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
on the effects of bullying on cortical thickness in larger samples
with affective psychosis using functional neuroimaging may
provide new avenues for studying connectivity, mapping brain
networks, and decoding cognitive and emotional processes.
Finally, while we observed cortical thickness alterations in the
left hemisphere associated with FEP, we found significant inter-
action effects between FEP and CA in the right hemisphere
only. Although there is some evidence supporting associations
of reduced left middle temporal cortical thickness with altered
left hemisphere language network organization in individuals
with schizophrenia (Schijven et al., 2023), to our knowledge, no
previous study has reported laterality effects of CA and FEP on
cortical thickness. Our results may provide new clues on laterality
in those with FEP and CA exposure. Future studies should assess
these associations including clinical and cognitive measures.
Implications and future directions
Our study adds to previous evidence supporting the independent
and joint effects of exposure to CAs and FEP on specific brain cir-
cuits. This could improve our understanding of the mechanisms
of environmental risk factors and how they interact with other
variables to guide preventive and therapeutic strategies.
Further studies should include other psychophysiological and/
or neuroimaging measures (e.g. functional magnetic resonance)
and cognitive/emotion processing assessments, to test and under-
stand the extent of CA effects on cortical alterations and brain
function, and their associations with (social) goal-oriented reward
and decision-making, through virtual reality and/or interactive
and (close to) real-life assessments (Bell et al., 2024; Fares-
Otero, Halligan, Vieta, & Heilbronner, 2024b) in FEP.
Although early childhood neglect is associated with alterations
in adult brain structure despite subsequent environmental enrich-
ment (Mackes et al., 2020), whether cortical thickness increases in
response to interventions enhancing cognitive reserve
(Fares-Otero et al., 2024a; Sánchez-Torres et al., 2023) or whether
resilience (Fares-Otero et al., 2023c) protects against FEP needs to
be established. Understanding specific changes in brain circuits
and compensatory mechanisms may help in the design of inter-
ventions that augment such beneficial strategies. Future studies
should also attempt to map differentially sensitive periods
(Fares-Otero & Schalinski, 2024) of cortical thickness effects
across brain regions resulting from adversity exposure and assess
the effects of these exposures on neurodevelopment and vulner-
ability to psychotic disorders. Additionally, granular data on CA
severity and duration, the number of CA exposures and the num-
ber of repeated exposures to a single CA type (e.g. sexual abuse)
should be collected (Fares-Otero & Seedat, 2024).
Strengths and limitations
This study has several methodological strengths, such as the use of
a relatively large and well-characterized sample of people meeting
the diagnostic criteria for FEP. We included a sample of HCs to
disentangle the effect of FEP from that of CAs. We explored the
associations between the effects of many types of CAs and FEP
on cortical thickness in a wide variety of brain regions. We
assessed parental discord and peer bullying (making distinctions
between emotional v. physical types), which have been relatively
understudied thus far but are often experienced by children and
adolescents (Finkelhor, 2018) – even more so in children with
neurodevelopmental disorders and at risk for mental disorders
(Abregú-Crespo et al., 2024). We also used a dimensional
model of adversity to help disentangle effects unique to certain
adversity types to identify both shared and distinct mechanisms
through which different adversities affect cortical thickness across
brain regions.
Several limitations should be considered when our findings are
interpreted. First, because data on CA and neuroimaging were
collected at the same point in time, causal relationships between
study constructs cannot be addressed. Further large-scale and lon-
gitudinal studies are needed. Second, CAs were retrospectively
reported by the participants through retrospective assessments.
The reliability of retrospective reports on CA is often questioned
because they are prone to a certain recollection bias (Hardt &
Rutter, 2004). However, empirical studies have shown that retro-
spective self-reports on the presence of CA by individuals with
psychotic disorders are sufficiently reliable and provide strong
support for their validity and reliability (Fisher et al., 2011).
Surprisingly, we found that exposure to any CA and overall mal-
treatment was more prevalent in HCs than in those with FEP in
our sample. However, previous studies have reported similar
prevalence rates of CA in both the general population
(McLaughlin et al., 2019) and FEP (Vila-Badia et al., 2022).
Furthermore, our exclusion criteria did not exclude the possibility
that some participants could have presented a lifetime but not a
current psychiatric diagnosis. This could have been the case for
mood and anxiety disorders as well as disorders with childhood
onset that are not prominent later in life (e.g. Attention Deficit
Hyperactivity Disorder). Third, different traumatic and stressful
experiences throughout life can contribute to brain structure
changes, which may vary based on the individual’s experience
(Ansell, Rando, Tuit, Guarnaccia, & Sinha, 2012). Future research
on the cumulative and interactive effects of CA and traumatic life
events may contribute to explaining brain structure in people with
FEP. Finally, the use of a sample composed of individuals with
FEP limits the generalizability of our results to other stages of
the illness. Fourth, notably, the present study sample was drawn
from public hospitals in Madrid. The degree to which the current
findings may be generalized more broadly to children, youth, and
adults from demographically and culturally dissimilar contexts is
unknown.
Conclusions
The results of this study suggest that the cortical thickness altera-
tions observed in people with FEP are similar to those observed in
people exposed to socio-environmental adversity. Our findings
also reveal the interactive effects of FEP and exposure to neglect
and overall maltreatment on reduced cortical thickness in the
right medial orbitofrontal cortex. These findings suggest that
neural markers of the CA in regions involved in decision-making
and reward mechanisms potentially underlie the association
between CA and psychosis, thus revealing shared vulnerability
pathways and mechanisms that could become targets for prevent-
ive and therapeutic efforts. Future longitudinal neuroimaging
studies aimed at addressing the biological mechanisms underlying
the interactive effects of CA and psychosis risk on brain develop-
ment are warranted.
Supplementary material. The supplementary material for this article can
be found at https://doi.org/10.1017/S0033291724002393.
Data availability statement. N. E. F.-O. and J. R. have full access to all the
data in the study and take responsibility for the integrity of the data and the
Psychological Medicine 4569
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
accuracy of the data analyses. The data are not publicly available due to privacy
restrictions. The R code is available from the authors upon reasonable request.
Acknowledgements. We thank the participants of the AGES-CM research
project for their contributions and the AGES-CM group for their dedication
to the collection and stewardship of the data used in this study.
Author contributions. Term, Conceptualization, Methodology: N. E. F.-O.,
J. R. Data collection and data curation: N. E. F.-O., H. M., M. R.-C., V. C.,
B. G.-B., P. A.-C., A. I., D. M.-H., P. M. C., I. L., M. D., A. O.-T., I. M.-G.,
A. M.-S., C. L. L., N. M., and AGES-CM group. Writing – original draft:
N. E. F.-O., C. M. D.-C., J. R. Writing – reviewing & editing: All the authors.
Formal analysis, Software, Validation, Interpretation of the data:
N. E. F.-O., C. M. D.-C., J. R. Visualization: N. E. F.-O., E. Vila,
J. R. Investigation: N. E. F.-O., J. R., and AGES-CM group. Resources and
funding acquisition: R. R.-J., M. D. M., M.-F. B.-O., A. I., E. B.-G., E. V.,
J. L. A.-M., N. M., C. A., and C. M. D.-C. All the authors approved the
final version of the submitted manuscript.
AGES-CM group. Miriam Ayora1, Raquel Álvarez-García2, Ana
Sánchez-Cámara1, Santiago Ovejero-García3, Daniel Hernández Huerta4,
Iosune Torío-Palmero3, Daniel Lourido4, Ángeles Sánchez-Cabezudo5,
Beatriz Serván Rendón-Luna6, Aggie Núñez-Doyle5, Maria Dolores
Saiz-Gonzalez6, Karina McDowell7, Katya B. March8, M. Paz Vidal-Villegas8,
Juan Carlos Leza7
1Department of Child and Adolescent Psychiatry, Institute of Psychiatry
and Mental Health, Hospital General Universitario Gregorio Marañón,
IiSGM, CIBERSAM, ISCIII, School of Medicine, UCM, Madrid, Spain.
2Hospital Rey Juan Carlos, Madrid, Spain.
3Department of Psychiatry, University Hospital Fundación Jiménez Díaz,
Madrid. Universidad Autónoma de Madrid, Spain.
4Department of Psychiatry, Hospital Universitario Ramón y Cajal, Madrid,
Spain.
5Department of Psychiatry, Instituto de Investigación Sanitaria Hospital 12
de Octubre (imas12), Madrid, Spain.
6Health Research Institute, Hospital Clínico San Carlos (IdISSC), Madrid,
Spain.
7Department of Pharmacology y Toxicology, School of Medicine, UCM,
Instituto de Investigación Hospital 12 de Octubre (imas12), Instituto
Universitario de Investigación en Neuroquímica (IUIN), CIBERSAM, ISCIII,
Madrid, Spain.
8Department of Psychiatry, Clinical Psychology, and Mental Health,
Instituto de Investigación Hospital Universitario La Paz (IdiPaz), Hospital
Universitario La Paz, Madrid, Spain.
The work by NEF-O was made possible by the support of the European
Union’s Horizon 2020 Research and Innovation Program (PSY-PGx,
EU.3.1.3. Treating and managing disease, Grant agreement No. 945151), and
DAAD (Deutscher Akademischer Austauschdienst) (ID-57681229 – Ref. No.
91629413). PAC has received grant support from Programa Intramural de
Impulso a la I + D + i 2023 (Instituto de Investigación Sanitaria Gregorio
Marañón). MR-C has received funding from the Instituto de Salud Carlos
III, ISCIII, (PI15/00723, PI18/00753, PI21/00701, PI24/01298), and the
Spanish Ministry of Science, Innovation and Universities (RYC-2017-23144;
CNS2023-144038) and was supported by a NARSAD independent investigator
grant (No. 24628) from the Brain & Behavior Research Foundation. AIzq was
supported by Grant JDC2022-048291-I funded by MCIN/AEI/10.13039/
501100011033 and by the ‘European Union NextGenerationEU/PRTR’. RR-J
received funding from the Instituto de Salud Carlos III (PI19/00766; Fondo
de Investigaciones Sanitarias/FEDER) and the Madrid Regional Government
(S2017/BMD-3740; P2022/BMD-7216). AIba acknowledges the support of
CIBER-Consorcio Centro de Investigación Biomédica en Red- (CB/07/09/
0025), Instituto de Salud Carlos III, and Ministerio de Ciencia e Innovación;
the Madrid Regional Government (S2022/BMD-7216 – AGES 3-CM) and
European Union Structural Funds; and grants PI19/01295 and PI22/01183,
which were integrated into the Plan Nacional de I + D + I and co-financed
by the ISCIII-Subdirección General de Evaluación and the Fondo Europeo
de Desarrollo Regional (FEDER). EV acknowledges the support of CIBER-
Consorcio Centro de Investigación Biomédica en Red- (CB07/09/0004),
Instituto de Salud Carlos III, the Spanish Ministry of Science and
Innovation and grants PI18/00805 and PI21/00787, which were integrated
into the Plan Nacional de I + D + I and co-financed by the
ISCIII-Subdirección General de Evaluación and the Fondo Europeo de
Desarrollo Regional (FEDER); the Instituto de Salud Carlos III; the
Secretaria d’Universitats i Recerca del Departament d’Economia i
Coneixement (2021 SGR 01358), the CERCA Programme, and the
Departament de Salut de la Generalitat de Catalunya for the PERIS grant
SLT006/17/00357; and the support of the European Union Horizon 2020
Research and Innovation Program (EU.3.1.1. Understanding health, wellbeing
and disease: Grant No 754907 and EU.3.1.3. Treating and managing disease:
Grant No 945151). CA has received funding from the Spanish Ministry of
Science and Innovation, Instituto de Salud Carlos III (ISCIII), co-financed
by the European Union; ERDF Funds from the European Commission, ‘A
way of making Europe’, financed by the European Union –
NextGenerationEU (PMP21/00051), PI19/01024. CIBERSAM, Madrid
Regional Government (B2017/BMD-3740 AGES-CM-2), European Union
Structural Funds, European Union Seventh Framework Program, European
Union H2020 Program under the Innovative Medicines Initiative 2 Joint
Undertaking: Project PRISM-2 (Grant agreement No. 101034377), Project
AIMS-2-TRIALS (Grant agreement No. 777394), Horizon Europe: Project
Youth-GEMs (Grant agreement No. 101057182), the National Institute of
Mental Health of the National Institutes of Health under Award Number
1U01MH124639-01 (Project ProNET) and Award Number
5P50MH115846-03 (project FEP-CAUSAL), Fundación Familia Alonso, and
Fundación Alicia Koplowitz. CMD-C has received funding from Instituto de
Salud Carlos III, the Spanish Ministry of Science and Innovation (JR19/
00024, PI17/00481, PI20/00721, PI23/00625) and the European Union
under grant number 101057182 (project Youth-GEMs). JR is thankful for
the support from Instituto de Salud Carlos III, the European Regional
Development Fund (FEDER) (CPII19/00009) and the Secretaria
d’Universitats i Recerca del Departament d’Economia i Coneixement (2021
SGR 1128).
Funding statement. This study was supported by the Madrid Regional
Government (R&D activities in Biomedicine, grant number S2022/
BMD-7216 – AGES 3-CM). The funder had no role in the study design,
data collection, data analysis, data interpretation, or writing of the
report. This article has been funded for open access by University of
Barcelona.
Competing interests. N. V. has received financial support for CME activities
and travel funds from the following entities (unrelated to the present work):
Angelini, Janssen, Lundbeck, Otsuka. A. Iba has received research support
from or served as speaker or advisor for Janssen-Cilag, Lundbeck, Otsuka
Pharmaceutical SA and Alter. R. R.-J. has been a consultant for, spoken in
activities of, or received grants from Instituto de Salud Carlos III, Fondo de
Investigación Sanitaria (FIS), Centro de Investigación Biomédica en Red de
Salud Mental (CIBERSAM), Madrid Regional Government (S2010/
BMD-2422 AGES; S2017/BMD-3740; P2022/BMD-7216), JanssenCilag,
Lundbeck, Otsuka, Pfizer, Ferrer, Juste, Takeda, Exeltis, Casen-Recordati,
Angelini, Rovi. E. V. has received grants and served as a consultant, advisor
or CME speaker for the following entities: AB-Biotics, AbbVie, Adamed,
Angelini, BeckleyPsych, Biogen, Biohaven, Boehringer-Ingelheim, Celon
Pharma, Compass, Dainippon Sumitomo Pharma, Ethypharm, Ferrer,
Gedeon Richter, GH Research, Glaxo-Smith Kline, HMNC, Idorsia, Janssen,
Lundbeck, Luye Pharma, Medincell, Merck, Newron, Novartis, Orion
Corporation, Organon, Otsuka, Roche, Rovi, Sage, Sanofi-Aventis, Sunovion,
Takeda, Teva, and Viatris, outside of the submitted work. C. A. has been a con-
sultant to or has received honoraria or grants from Abbot, Acadia, Angelini,
Biogen, Boehringer, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape,
Menarini, Minerva, Otsuka, Pfizer, Roche, Sage, Servier, Shire, Schering
Plough, Sumitomo Dainippon Pharma, Sunovion, Takeda and Teva. C. M.
D.-C. has received honoraria from Angelini and Viatris and support in attend-
ing conferences from Janssen and Angelini. J. R. has received CME honoraria
from Inspira Networks for a machine learning course promoted by Adamed,
outside the submitted work. The remaining authors have no conflicts of inter-
est to declare.
4570 Natalia E. Fares‐Otero et al.
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
References
Aas, M., Navari, S., Gibbs, A., Mondelli, V., Fisher, H. L., Morgan, C., …
Dazzan, P. (2012). Is there a link between childhood trauma, cognition,
and amygdala and hippocampus volume in first-episode psychosis?
Schizophrenia Research, 137(1), 73–79. https://doi.org/10.1016/j.schres.
2012.01.035
Abregú-Crespo, R., Garriz-Luis, A., Ayora, M., Martín-Martínez, N., Cavone,
V., Carrasco, MÁ,… Díaz-Caneja, C. M. (2024). School bullying in children
and adolescents with neurodevelopmental and psychiatric conditions: A
systematic review and meta-analysis. The Lancet. Child & Adolescent
Health, 8(2), 122–134. https://doi.org/10.1016/S2352-4642(23)00289-4
Adriano, F., Caltagirone, C., & Spalletta, G. (2012). Hippocampal volume
reduction in first-episode and chronic schizophrenia: A review and
meta-analysis. The Neuroscientist: A Review Journal Bringing
Neurobiology, Neurology and Psychiatry, 18(2), 180–200. https://doi.org/
10.1177/1073858410395147
Anderson, K. K. (2019). Towards a public health approach to psychotic disor-
ders. The Lancet Public Health, 4(5), e212–e213. https://doi.org/10.1016/
S2468-2667(19)30054-4
Ansell, E. B., Rando, K., Tuit, K., Guarnaccia, J., & Sinha, R. (2012).
Cumulative adversity and smaller gray matter volume in medial prefrontal,
anterior cingulate, and insula regions. Biological Psychiatry, 72(1), 57–64.
https://doi.org/10.1016/j.biopsych.2011.11.022
Arango, C., Dragioti, E., Solmi, M., Cortese, S., Domschke, K., Murray, R. M.,
… Fusar-Poli, P. (2021). Risk and protective factors for mental disorders
beyond genetics: An evidence-based atlas. World Psychiatry: Official
Journal of the World Psychiatric Association (WPA), 20(3), 417–436.
https://doi.org/10.1002/wps.20894
Armbruster-Genç, D. J. N., Valton, V., Neil, L., Vuong, V., Freeman, Z. C. L.,
Packer, K. C., … McCrory, E. (2022). Altered reward and effort processing
in children with maltreatment experience: A potential indicator of mental
health vulnerability. Neuropsychopharmacology, 47(5), 1063–1070.
https://doi.org/10.1038/s41386-022-01284-7
Baranger, D. A. A., Finsaas, M. C., Goldstein, B. L., Vize, C. E., Lynam, D. R.,
& Olino, T. M. (2023). Tutorial: Power analyses for interaction effects in
cross-sectional regressions. Advances in Methods and Practices in
Psychological Science, 6(3), 25152459231187531. https://doi.org/10.1177/
25152459231187531
Begemann, M. J. H., Schutte, M. J. L., van Dellen, E., Abramovic, L., Boks, M.
P., van Haren, N. E. M., … Sommer, I. E. C. (2023). Childhood trauma is
associated with reduced frontal gray matter volume: A large transdiagnostic
structural MRI study. Psychological Medicine, 53(3), 741–749. https://doi.
org/10.1017/S0033291721002087
Bell, I. H., Pot-Kolder, R., Rizzo, A., Rus-Calafell, M., Cardi, V., Cella, M., …
Valmaggia, L. (2024). Advances in the use of virtual reality to treat mental
health conditions. Nature Reviews Psychology, 3, 552–567. https://doi.org/10.
1038/s44159-024-00334-9
Bifulco, A., Bernazzani, O., Moran, P. M., & Jacobs, C. (2005). The childhood
experience of care and abuse questionnaire (CECA.Q): Validation in a com-
munity series. The British Journal of Clinical Psychology, 44(Pt 4), 563–581.
https://doi.org/10.1348/014466505X35344
Boecker, R., Holz, N. E., Buchmann, A. F., Blomeyer, D., Plichta, M. M., Wolf,
I., … Laucht, M. (2014). Impact of early life adversity on reward processing
in young adults: EEG-fMRI results from a prospective study over 25 years.
PLoS One, 9(8), e104185. https://doi.org/10.1371/journal.pone.0104185
Bounoua, N., Miglin, R., Spielberg, J. M., Johnson, C. L., & Sadeh, N. (2022).
Childhood trauma moderates morphometric associations between orbito-
frontal cortex and amygdala: Implications for pathological personality traits.
Psychological Medicine, 52(13), 2578–2587. https://doi.org/10.1017/
S0033291720004468
Breitborde, N. J. K., Srihari, V. H., & Woods, S. W. (2009). Review of the oper-
ational definition for first-episode psychosiseip. Early Intervention in
Psychiatry, 3(4), 259–265. https://doi.org/10.1111/j.1751-7893.2009.00148.x
Calem, M., Bromis, K., McGuire, P., Morgan, C., & Kempton, M. J. (2017).
Meta-analysis of associations between childhood adversity and hippocampus
and amygdala volume in non-clinical and general population samples.
NeuroImage. Clinical, 14, 471–479. https://doi.org/10.1016/j.nicl.2017.02.016
Cancel, A., Comte, M., Truillet, R., Boukezzi, S., Rousseau, P.-F., Zendjidjian,
X. Y., … Fakra, E. (2015). Childhood neglect predicts disorganization in
schizophrenia through grey matter decrease in dorsolateral prefrontal cor-
tex. Acta Psychiatrica Scandinavica, 132(4), 244–256. https://doi.org/10.
1111/acps.12455
Cascino, G., Canna, A., Russo, A. G., Monaco, F., Esposito, F., Di Salle, F., …
Monteleone, A. M. (2023). Childhood maltreatment is associated with cor-
tical thinning in people with eating disorders. European Archives of
Psychiatry and Clinical Neuroscience, 273(2), 459–466. https://doi.org/10.
1007/s00406-022-01456-y
Cassiers, L. L. M., Sabbe, B. G. C., Schmaal, L., Veltman, D. J., Penninx, B. W.
J. H., & Van Den Eede, F. (2018). Structural and functional brain abnormal-
ities associated with exposure to different childhood trauma subtypes: A
systematic review of neuroimaging findings. Frontiers in Psychiatry, 9,
329. Retrieved from https://www.frontiersin.org/articles/10.3389/fpsyt.
2018.00329
Cheng, T. W., Mills, K. L., Miranda Dominguez, O., Zeithamova, D., Perrone,
A., Sturgeon, D., … Mackiewicz Seghete, K. L. (2021). Characterizing the
impact of adversity, abuse, and neglect on adolescent amygdala resting-state
functional connectivity. Developmental Cognitive Neuroscience, 47, 100894.
https://doi.org/10.1016/j.dcn.2020.100894
Christy, A., Cavero, D., Navajeeva, S., Murray-O’Shea, R., Rodriguez, V., Aas,
M., … Alameda, L. (2023). Association between childhood adversity and
functional outcomes in people with psychosis: A meta-analysis.
Schizophrenia Bulletin, 49(2), 285–296. https://doi.org/10.1093/schbul/
sbac105
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.).
New York: Routledge. https://doi.org/10.4324/9780203771587
Cooper, J. A., Barch, D. M., Reddy, L. F., Horan, W. P., Green, M. F., &
Treadway, M. T. (2019). Effortful goal-directed behavior in schizophrenia:
Computational subtypes and associations with cognition. Journal of
Abnormal Psychology, 128(7), 710–722. https://doi.org/10.1037/abn0000443
Cortes Hidalgo, A. P., Hammerton, G., Heron, J., Bolhuis, K., Madley-Dowd,
P., Tiemeier, H., … Jones, H. J. (2024). Childhood adversity and incident
psychotic experiences in early adulthood: Cognitive and psychopathological
mediators. Schizophrenia Bulletin, 50(4), 903–912. https://doi.org/10.1093/
schbul/sbae023
Crespo-Facorro, B., Roiz-Santiáñez, R., Pérez-Iglesias, R., Rodriguez-Sanchez,
J. M., Mata, I., Tordesillas-Gutierrez, D., … Vázquez-Barquero, J. L.
(2011). Global and regional cortical thinning in first-episode psychosis
patients: Relationships with clinical and cognitive features. Psychological
Medicine, 41(7), 1449–1460. https://doi.org/10.1017/S003329171000200X
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker,
D., … Killiany, R. J. (2006). An automated labeling system for subdividing
the human cerebral cortex on MRI scans into gyral based regions of interest.
NeuroImage, 31(3), 968–980. https://doi.org/10.1016/j.neuroimage.2006.01.
021
Dillon, D. G., Holmes, A. J., Birk, J. L., Brooks, N., Lyons-Ruth, K., &
Pizzagalli, D. A. (2009). Childhood adversity is associated with left basal
ganglia dysfunction during reward anticipation in adulthood. Biological
Psychiatry, 66(3), 206–213. https://doi.org/10.1016/j.biopsych.2009.02.019
Dragioti, E., Radua, J., Solmi, M., Arango, C., Oliver, D., Cortese, S., …
Fusar-Poli, P. (2022). Global population attributable fraction of potentially
modifiable risk factors for mental disorders: A meta-umbrella systematic
review. Molecular Psychiatry, 27(8), 3510–3519. https://doi.org/10.1038/
s41380-022-01586-8
du Plessis, S., Scheffler, F., Luckhoff, H., Asmal, L., Kilian, S., Phahladira, L., &
Emsley, R. (2020). Childhood trauma and hippocampal subfield volumes in
first-episode schizophrenia and healthy controls. Schizophrenia Research,
215, 308–313. https://doi.org/10.1016/j.schres.2019.10.009
Fares-Otero, N. E., Alameda, L., Pfaltz, M. C., Martinez-Aran, A., Schäfer, I., &
Vieta, E. (2023a). Examining associations, moderators and mediators
between childhood maltreatment, social functioning, and social cognition
in psychotic disorders: A systematic review and meta-analysis.
Psychological Medicine, 53(13), 5909–5932. https://doi.org/10.1017/
S0033291723001678
Fares-Otero, N. E., Borràs, R., Solé, B., Torrent, C., Garriga, M., Serra-Navarro,
M., … Verdolini, N. (2024a). Cognitive reserve moderates the relationship
Psychological Medicine 4571
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
between childhood maltreatment, objective and subjective cognition, and
psychosocial functioning in individuals with first-episode psychosis.
Psychological Trauma: Theory, Research, Practice and Policy. Advance
online publication. https://doi.org/10.1037/tra0001650
Fares-Otero, N. E., De Prisco, M., Oliva, V., Radua, J., Halligan, S. L., Vieta, E.,
& Martinez-Aran, A. (2023b). Association between childhood maltreatment
and social functioning in individuals with affective disorders: A systematic
review and meta-analysis. Acta Psychiatrica Scandinavica, 148(2), 142–164.
https://doi.org/10.1111/acps.13557
Fares-Otero, N. E., Halligan, S. L., Vieta, E., & Heilbronner, U. (2024b). Pupil
size as a potential marker of emotion processing in child maltreatment.
Journal of Affective Disorders, 351, 392–395. https://doi.org/10.1016/j.jad.
2024.01.242
Fares-Otero,N. E.,O, J., Spies,G.,Womersley, J. S.,Gonzalez,C.,Ayas,G.,…Seedat,
S. (2023c). Child maltreatment and resilience in adulthood: A protocol for a
systematic review and meta-analysis. European Journal of Psychotraumatology,
14(2), 2282826. https://doi.org/10.1080/20008066.2023.2282826
Fares-Otero, N. E., & Schalinski, I. (2024). Social cognition in maltreated indi-
viduals: Do type and timing of maltreatment matter? European
Neuropsychopharmacology: The Journal of the European College of
Neuropsychopharmacology, 81, 38–40. https://doi.org/10.1016/j.euroneuro.
2023.12.011
Fares-Otero, N. E., & Seedat, S. (2024). Childhood maltreatment: A call for a
standardised definition and applied framework. European
Neuropsychopharmacology: The Journal of the European College of
Neuropsychopharmacology, 87, 24–26. https://doi.org/10.1016/j.euroneuro.
2024.07.002
Fett, A.-K. J., Mouchlianitis, E., Gromann, P. M., Vanes, L., Shergill, S. S., &
Krabbendam, L. (2019). The neural mechanisms of social reward in early
psychosis. Social Cognitive and Affective Neuroscience, 14(8), 861–870.
https://doi.org/10.1093/scan/nsz058
Finkelhor, D. (2018). Screening for adverse childhood experiences (ACEs):
Cautions and suggestions. Child Abuse & Neglect, 85, 174–179.
https://doi.org/10.1016/j.chiabu.2017.07.016
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., …
Dale, A. M. (2002). Whole brain segmentation: Automated labeling of
neuroanatomical structures in the human brain. Neuron, 33(3), 341–355.
https://doi.org/10.1016/s0896-6273(02)00569-x
Fisher, H. L., Craig, T. K., Fearon, P., Morgan, K., Dazzan, P., Lappin, J., …
Morgan, C. (2011). Reliability and comparability of psychosis patients’
retrospective reports of childhood abuse. Schizophrenia Bulletin, 37(3),
546–553. https://doi.org/10.1093/schbul/sbp103
Fisher, H., Morgan, C., Dazzan, P., Craig, T. K., Morgan, K., Hutchinson, G.,
… Fearon, P. (2009). Gender differences in the association between child-
hood abuse and psychosis. The British Journal of Psychiatry: The Journal of
Mental Science, 194(4), 319–325. https://doi.org/10.1192/bjp.bp.107.047985
Gold, A. L., Sheridan, M. A., Peverill, M., Busso, D. S., Lambert, H. K., Alves,
S., … McLaughlin, K. A. (2016). Childhood abuse and reduced cortical
thickness in brain regions involved in emotional processing. Journal of
Child Psychology and Psychiatry, and Allied Disciplines, 57(10),
1154–1164. https://doi.org/10.1111/jcpp.12630
Golden, M. H., Samuels, M. P., & Southall, D. P. (2003). How to distinguish
between neglect and deprivational abuse. Archives of Disease in
Childhood, 88(2), 105–107. https://doi.org/10.1136/adc.88.2.105
Gong, Q., Lui, S., & Sweeney, J. A. (2016). A selective review of cerebral abnor-
malities in patients with first-episode schizophrenia before and after treat-
ment. American Journal of Psychiatry, 173(3), 232–243. https://doi.org/10.
1176/appi.ajp.2015.15050641
Gourley, S. L., Zimmermann, K. S., Allen, A. G., & Taylor, J. R. (2016). The
medial orbitofrontal cortex regulates sensitivity to outcome value. Journal
of Neuroscience, 36(16), 4600–4613. https://doi.org/10.1523/JNEUROSCI.
4253-15.2016
Guloksuz, S., Pries, L.-K., Delespaul, P., Kenis, G., Luykx, J. J., Lin, B. D., …
van Os, J. (2019). Examining the independent and joint effects of molecular
genetic liability and environmental exposures in schizophrenia: Results
from the EUGEI study. World Psychiatry: Official Journal of the World
Psychiatric Association (WPA), 18(2), 173–182. https://doi.org/10.1002/
wps.20629
Hardt, J., & Rutter, M. (2004). Validity of adult retrospective reports of adverse
childhood experiences: Review of the evidence. Journal of Child Psychology
and Psychiatry, and Allied Disciplines, 45(2), 260–273.
Hollingshead, A. B., & Redlich, F. C. (2007). Social class and mental illness: A
community study. 1958. American Journal of Public Health, 97(10),
1756–1757. https://doi.org/10.2105/ajph.97.10.1756
Holm, S. (1979). A simple sequentially rejective multiple test procedure.
Scandinavian Journal of Statistics, 6(2), 65–70.
Hoy, K., Barrett, S., Shannon, C., Campbell, C., Watson, D., Rushe, T., …
Mulholland, C. (2012). Childhood trauma and hippocampal and amygdalar
volumes in first-episode psychosis. Schizophrenia Bulletin, 38(6),
1162–1169. https://doi.org/10.1093/schbul/sbr085
Izquierdo, A., Cabello, M., Leal, I., Mellor-Marsá, B., Ayora, M., Bravo-Ortiz,
M.-F., … Malpica, N. (2021). The interplay between functioning problems
and symptoms in first episode of psychosis: An approach from network
analysis. Journal of Psychiatric Research, 136, 265–273.
Kaufman, J., & Torbey, S. (2019). Child maltreatment and psychosis.
Neurobiology of Disease, 131, 104378. https://doi.org/10.1016/j.nbd.2019.
01.015
Kim, J., Lee, C., Kang, Y., Kang, W., Kim, A., Tae, W.-S.,… Han, K.-M. (2023).
Childhood sexual abuse and cortical thinning in adults with major depres-
sive disorder. Psychiatry Investigation, 20(3), 255–261. https://doi.org/10.
30773/pi.2022.0314
Lardinois, M., Lataster, T., Mengelers, R., Van Os, J., & Myin-Germeys, I.
(2011). Childhood trauma and increased stress sensitivity in psychosis.
Acta Psychiatrica Scandinavica, 123(1), 28–35. https://doi.org/10.1111/j.
1600-0447.2010.01594.x
Leech, R., Braga, R., & Sharp, D. J. (2012). Echoes of the brain within the pos-
terior cingulate cortex. The Journal of Neuroscience: The Official Journal of
the Society for Neuroscience, 32(1), 215–222. https://doi.org/10.1523/
JNEUROSCI.3689-11.2012
Lim, L., Howells, H., Radua, J., & Rubia, K. (2020). Aberrant structural con-
nectivity in childhood maltreatment: A meta-analysis. Neuroscience &
Biobehavioral Reviews, 116, 406–414. https://doi.org/10.1016/j.neubiorev.
2020.07.004
LoPilato, A. M., Goines, K., Addington, J., Bearden, C. E., Cadenhead, K. S.,
Cannon, T. D.,…Walker, E. F. (2019). Impact of childhood adversity on cor-
ticolimbic volumes in youth at clinical high-risk for psychosis. Schizophrenia
Research, 213, 48–55. https://doi.org/10.1016/j.schres.2019.01.048
Luo, Q., Chen, J., Li, Y., Lin, X., Yu, H., Lin, X., … Peng, H. (2023). Cortical
thickness and curvature abnormalities in patients with major depressive
disorder with childhood maltreatment: Neural markers of vulnerability?
Asian Journal of Psychiatry, 80, 103396. https://doi.org/10.1016/j.ajp.2022.
103396
Mackes, N. K., Golm, D., Sarkar, S., Kumsta, R., Rutter, M., Fairchild, G., …
Sonuga-Barke, E. J. S. (2020). Early childhood deprivation is associated
with alterations in adult brain structure despite subsequent environmental
enrichment. Proceedings of the National Academy of Sciences of the
United States of America, 117(1), 641–649. https://doi.org/10.1073/pnas.
1911264116
Maddock, R. J., Garrett, A. S., & Buonocore, M. H. (2001). Remembering
familiar people: The posterior cingulate cortex and autobiographical mem-
ory retrieval. Neuroscience, 104(3), 667–676. https://doi.org/10.1016/S0306-
4522(01)00108-7
McCrory, E., De Brito, S. A., & Viding, E. (2011). The impact of childhood
maltreatment: A review of neurobiological and genetic factors. Frontiers
in Psychiatry, 2, 48. https://doi.org/10.3389/fpsyt.2011.00048
McLaughlin, K. A., Sheridan, M. A., & Lambert, H. K. (2014). Childhood
adversity and neural development: Deprivation and threat as distinct
dimensions of early experience. Neuroscience and Biobehavioral Reviews,
47, 578–591. https://doi.org/10.1016/j.neubiorev.2014.10.012
McLaughlin, K. A., Weissman, D., & Bitrán, D. (2019). Childhood adversity
and neural development: A systematic review. Annual Review of
Developmental Psychology, 1, 277–312. https://doi.org/10.1146/annurev-
devpsych-121318-084950
Molinaro, G., & Collins, A. G. E. (2023). Intrinsic rewards explain context-
sensitive valuation in reinforcement learning. PLOS Biology, 21(7),
e3002201. https://doi.org/10.1371/journal.pbio.3002201
4572 Natalia E. Fares‐Otero et al.
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
Morgan, C., & Gayer-Anderson, C. (2016). Childhood adversities and psych-
osis: Evidence, challenges, implications. World Psychiatry, 15(2), 93–102.
https://doi.org/10.1002/wps.20330
Mowinckel, A. M., & Vidal-Piñeiro, D. (2020). Visualization of brain statistics
with R packages ggseg and ggseg3d. Advances in Methods and Practices
in Psychological Science, 3(4), 466–483. https://doi.org/10.1177/
2515245920928009
Narr, K. L., Bilder, R. M., Toga, A. W., Woods, R. P., Rex, D. E., Szeszko, P. R.,
… Thompson, P. M. (2005). Mapping cortical thickness and gray matter
concentration in first episode schizophrenia. Cerebral Cortex, 15(6),
708–719. https://doi.org/10.1093/cercor/bhh172
Navarro-Mateu, F., Alonso, J., Lim, C. C. W., Saha, S., Aguilar-Gaxiola, S.,
Al-Hamzawi, A., … WHO World Mental Health Survey Collaborators.
(2017). The association between psychotic experiences and disability:
Results from the WHO world mental health surveys. Acta Psychiatrica
Scandinavica, 136(1), 74–84. https://doi.org/10.1111/acps.12749
Newbury, J. B., Arseneault, L., Moffitt, T. E., Odgers, C. L., Howe, L. D.,
Bakolis, I., … Fisher, H. L. (2023). Socioenvironmental adversity and ado-
lescent psychotic experiences: Exploring potential mechanisms in a UK lon-
gitudinal cohort. Schizophrenia Bulletin, 49(4), 1042–1054. https://doi.org/
10.1093/schbul/sbad017
Noonan, M. P., Kolling, N., Walton, M. E., & Rushworth, M. F. S. (2012).
Re-evaluating the role of the orbitofrontal cortex in reward and reinforce-
ment. European Journal of Neuroscience, 35(7), 997–1010. https://doi.org/
10.1111/j.1460-9568.2012.08023.x
Oltean, L.-E., Șoflău, R., Miu, A. C., & Szentágotai-Tătar, A. (2023). Childhood
adversity and impaired reward processing: A meta-analysis. Child Abuse &
Neglect, 142, 105596. https://doi.org/10.1016/j.chiabu.2022.105596
Panizzon, M. S., Fennema-Notestine, C., Eyler, L. T., Jernigan, T. L.,
Prom-Wormley, E., Neale, M., … Kremen, W. S. (2009). Distinct genetic
influences on cortical surface area and cortical thickness. Cerebral Cortex
(New York, NY), 19(11), 2728–2735. https://doi.org/10.1093/cercor/bhp026
Peverill, M., Rosen, M. L., Lurie, L. A., Sambrook, K. A., Sheridan, M. A., &
McLaughlin, K. A. (2023). Childhood trauma and brain structure in chil-
dren and adolescents. Developmental Cognitive Neuroscience, 59, 101180.
https://doi.org/10.1016/j.dcn.2022.101180
Pigoni, A., Dwyer, D., Squarcina, L., Borgwardt, S., Crespo-Facorro, B.,
Dazzan, P., … ClassiFEP Group. (2021). Classification of first-episode
psychosis using cortical thickness: A large multicenter MRI study.
European Neuropsychopharmacology: The Journal of the European College
of Neuropsychopharmacology, 47, 34–47. https://doi.org/10.1016/j.
euroneuro.2021.04.002
Pina-Camacho, L., Martinez, K., Diaz-Caneja, C. M., Mezquida, G., Cuesta, M. J.,
Moreno, C., … PEPs Group. (2022). Cortical thinning over two years after
first-episode psychosis depends on age of onset. Schizophrenia (Heidelberg,
Germany), 8(1), 20. https://doi.org/10.1038/s41537-021-00196-7
Pollok, T. M., Kaiser, A., Kraaijenvanger, E. J., Monninger, M., Brandeis, D.,
Banaschewski, T., … Holz, N. E. (2022). Neurostructural traces of early
life adversities: A meta-analysis exploring age- and adversity-specific effects.
Neuroscience & Biobehavioral Reviews, 135, 104589. https://doi.org/10.1016/
j.neubiorev.2022.104589
Quinlan, E. B., Barker, E. D., Luo, Q., Banaschewski, T., Bokde, A. L. W.,
Bromberg, U., … Schumann, G. (2020). Peer victimization and its impact
on adolescent brain development and psychopathology. Molecular
Psychiatry, 25(11), 3066–3076. https://doi.org/10.1038/s41380-018-0297-9
Rakic, P. (1988). Specification of cerebral cortical areas. Science (New York,
N.Y.), 241(4862), 170–176. https://doi.org/10.1126/science.3291116
Rapado-Castro, M., Whittle, S., Pantelis, C., Thompson, A., Nelson, B.,
Ganella, E. P., … Bartholomeusz, C. F. (2020). Does cortical brain morph-
ology act as a mediator between childhood trauma and transition to psych-
osis in young individuals at ultra-high risk? Schizophrenia Research, 224,
116–125. https://doi.org/10.1016/j.schres.2020.09.017
R Core Team. (2021). R: A language and environment for statistical computing.
Vienna, Austria: R Foundation for Statistical Computing. Retrieved from
https://www.R-project.org/
Read, J., Fosse, R., Moskowitz, A., & Perry, B. (2014). The traumagenic neuro-
developmental model of psychosis revisited. Neuropsychiatry, 4(1), 65–79.
https://doi.org/10.2217/NPY.13.89
Reddy, L. F., Horan, W. P., Barch, D. M., Buchanan, R. W., Gold, J. M.,
Marder, S. R., … Green, M. F. (2018). Understanding the association
between negative symptoms and performance on effort-based decision-
making tasks: The importance of defeatist performance beliefs.
Schizophrenia Bulletin, 44(6), 1217–1226. https://doi.org/10.1093/schbul/
sbx156
Rinne-Albers, M. A., Boateng, C. P., van der Werff, S. J., Lamers-Winkelman,
F., Rombouts, S. A., Vermeiren, R. R., & van der Wee, N. J. (2020).
Preserved cortical thickness, surface area and volume in adolescents with
PTSD after childhood sexual abuse. Scientific Reports, 10(1), 3266.
https://doi.org/10.1038/s41598-020-60256-3
Rosenfield, P. J., Jiang, D., & Pauselli, L. (2022). Childhood adversity and
psychotic disorders: Epidemiological evidence, theoretical models and clin-
ical considerations. Schizophrenia Research, 247, 55–66. https://doi.org/10.
1016/j.schres.2021.06.005
Sánchez-Torres, A. M., Amoretti, S., Enguita-Germán, M., Mezquida, G.,
Moreno-Izco, L., Panadero-Gómez, R., … González-Blanco, L. (2023).
Relapse, cognitive reserve, and their relationship with cognition in
first episode schizophrenia: A 3-year follow-up study. European
Neuropsychopharmacology, 67, 53–65. https://doi.org/10.1016/j.euroneuro.
2022.11.011
Scanlon, C., Anderson-Schmidt, H., Kilmartin, L., McInerney, S., Kenney, J.,
McFarland, J., … McDonald, C. (2014). Cortical thinning and caudate
abnormalities in first episode psychosis and their association with clinical
outcome. Schizophrenia Research, 159(1), 36–42. https://doi.org/10.1016/j.
schres.2014.07.030
Schäfer, M., Korn, S., Smith, P. K., Hunter, S. C., Mora-Merchán, J. A., Singer,
M. M., & Van der Meulen, K. (2004). Lonely in the crowd: Recollections of
bullying. British Journal of Developmental Psychology, 22(3), 379–394.
https://doi.org/10.1348/0261510041552756
Schijven, D., Postema, M. C., Fukunaga, M., Matsumoto, J., Miura, K., de
Zwarte, S. M. C., … Francks, C. (2023). Large-scale analysis of structural
brain asymmetries in schizophrenia via the ENIGMA consortium.
Proceedings of the National Academy of Sciences of the United States of
America, 120(14), e2213880120. https://doi.org/10.1073/pnas.2213880120
Schultz, C. C., Koch, K., Wagner, G., Roebel, M., Schachtzabel, C., Gaser, C.,
… Schlösser, R. G. M. (2010). Reduced cortical thickness in first episode
schizophrenia. Schizophrenia Research, 116(2), 204–209. https://doi.org/10.
1016/j.schres.2009.11.001
Sideli, L., Murray, R. M., Schimmenti, A., Corso, M., La Barbera, D., Trotta, A.,
& Fisher, H. L. (2020). Childhood adversity and psychosis: A systematic
review of bio-psycho-social mediators and moderators. Psychological
Medicine, 50(11), 1761–1782. https://doi.org/10.1017/S0033291720002172
Stevelink, R., Abramovic, L., Verkooijen, S., Begemann, M. J. H., Sommer,
I. E. C., Boks, M. P., … Vinkers, C. H. (2018). Childhood abuse and
white matter integrity in bipolar disorder patients and healthy controls.
European Neuropsychopharmacology, 28(7), 807–817. https://doi.org/10.
1016/j.euroneuro.2018.05.003
Sumner, J. A., Colich, N. L., Uddin, M., Armstrong, D., & McLaughlin, K. A.
(2019). Early experiences of threat, but not deprivation, are associated with
accelerated biological aging in children and adolescents. Biological
Psychiatry, 85(3), 268–278. https://doi.org/10.1016/j.biopsych.2018.09.008
Teicher, M. H., Samson, J. A., Anderson, C. M., & Ohashi, K. (2016). The
effects of childhood maltreatment on brain structure, function and connect-
ivity. Nature Reviews Neuroscience, 17(10), 652–666. https://doi.org/10.
1038/nrn.2016.111
Thomas, M., Rakesh, D., Whittle, S., Sheridan, M., Upthegrove, R., & Cropley,
V. (2023). The neural, stress hormone and inflammatory correlates of child-
hood deprivation and threat in psychosis: A systematic review.
Psychoneuroendocrinology, 157, 106371. https://doi.org/10.1016/j.psyneuen.
2023.106371
Tomoda, A., Polcari, A., Anderson, C. M., & Teicher, M. H. (2012). Reduced
visual cortex gray matter volume and thickness in young adults who wit-
nessed domestic violence during childhood. PLoS One, 7(12), e52528.
https://doi.org/10.1371/journal.pone.0052528
Tozzi, L., Garczarek, L., Janowitz, D., Stein, D. J., Wittfeld, K., Dobrowolny, H.,
… Frodl, T. (2020). Interactive impact of childhood maltreatment, depres-
sion, and age on cortical brain structure: Mega-analytic findings from a
Psychological Medicine 4573
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press
large multi-site cohort. Psychological Medicine, 50(6), 1020–1031.
https://doi.org/10.1017/S003329171900093X
Trauelsen, A. M., Bendall, S., Jansen, J. E., Nielsen, H.-G. L., Pedersen, M. B.,
Trier, C. H., … Simonsen, E. (2015). Childhood adversity specificity and
dose-response effect in non-affective first-episode psychosis. Schizophrenia
Research, 165(1), 52–59. https://doi.org/10.1016/j.schres.2015.03.014
Turner, S., Harvey, C., Hayes, L., Castle, D., Galletly, C., Sweeney, S., … Spittal,
M. J. (2019). Childhood adversity and clinical and psychosocial outcomes in
psychosis. Epidemiology and Psychiatric Sciences, 29, e78. https://doi.org/10.
1017/S2045796019000684
Ulloa, R. E., Ortiz, S., Higuera, F., Nogales, I., Fresán, A., Apiquian, R., … de la
Peña, F. (2006). [Interrater reliability of the Spanish version of schedule for
affective disorders and schizophrenia for school-age children – present and
lifetime version (K-SADS-PL)]. Actas Espanolas De Psiquiatria, 34(1),
36–40.
Vaidya, N., Marquand, A. F., Nees, F., Siehl, S., & Schumann, G. (2024). The
impact of psychosocial adversity on brain and behaviour: An overview of
existing knowledge and directions for future research. Molecular
Psychiatry, 29(10), 3245–3267. https://doi.org/10.1038/s41380-024-02556-y
Vieira, S., Gong, Q., Scarpazza, C., Lui, S., Huang, X., Crespo-Facorro, B., …
Mechelli, A. (2021). Neuroanatomical abnormalities in first-episode psychosis
across independent samples: A multi-centre mega-analysis. Psychological
Medicine, 51(2), 340–350. https://doi.org/10.1017/S0033291719003568
Vila-Badia, R., Del Cacho, N., Butjosa, A., Serra Arumí, C., Esteban Santjusto,
M., Abella, M., … Usall, J. (2022). Prevalence and types of childhood
trauma in first episode psychosis patients. Relation with clinical onset vari-
ables. Journal of Psychiatric Research, 146, 102–108. https://doi.org/10.1016/
j.jpsychires.2021.12.033
Walton, E., Hibar, D. P., van Erp, T. G., Potkin, S. G., Roiz-Santiañez, R.,
Crespo-Facorro, B., … Ehrlich, S. (2018). Left medial orbitofrontal cortical
thinning is associated with negative symptom severity in schizophrenia: A
meta-analysis by the ENIGMA-Schizophrenia consortium. Psychological
Medicine, 48(1), 82–94. https://doi.org/10.1017/S0033291717001283
Wen, K., Zhao, Y., Gong, Q., Zhu, Z., Li, Q., Pan, N., … Biswal, B. B. (2021).
Cortical thickness abnormalities in patients with first episode psychosis: A
meta-analysis of psychoradiologic studies and replication in an independent
sample. Psychoradiology, 1(4), 185–198. https://doi.org/10.1093/psyrad/
kkab015
Wiegand, L. C., Warfield, S. K., Levitt, J. J., Hirayasu, Y., Salisbury, D. F.,
Heckers, S., … Shenton, M. E. (2004). Prefrontal cortical thickness in first-
episode psychosis: A magnetic resonance imaging study. Biological
Psychiatry, 55(2), 131–140. https://doi.org/10.1016/j.biopsych.2003.07.009
Yang, W., Jin, S., Duan, W., Yu, H., Ping, L., Shen, Z., … Zhou, C. (2023). The
effects of childhood maltreatment on cortical thickness and gray matter vol-
ume: A coordinate-based meta-analysis. Psychological Medicine, 53(5),
1681–1699. https://doi.org/10.1017/S0033291723000661
Zhao, Y., Zhang, Q., Shah, C., Li, Q., Sweeney, J. A., Li, F., & Gong, Q. (2022).
Cortical thickness abnormalities at different stages of the illness course in
schizophrenia: A systematic review and meta-analysis. JAMA Psychiatry,
79(6), 560–570. https://doi.org/10.1001/jamapsychiatry.2022.0799
4574 Natalia E. Fares‐Otero et al.
https://doi.org/10.1017/S0033291724002393 Published online by Cambridge University Press