Schizophrenia Research 146 (2013) 103–110

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Schizophrenia Research

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Premorbid impairments in early-onset psychosis: Differences between patients withschizophrenia and bipolar disorder

Beatriz Payá a,⁎, Jose Manuel Rodríguez-Sánchez a, Soraya Otero a, Pedro Muñoz b,Josefina Castro-Fornieles c, Mara Parellada d, Ana Gonzalez-Pinto e, Cesar Soutullo f, Inmaculada Baeza c,Marta Rapado-Castro d, Margarita Sáenz-Herrero e, Dolores Moreno d, Celso Arango d

a Child and Adolescent Psychiatry and Psychology Unit, Hospital Universitario Marques de Valdecilla, Santander, Spainb Unidad Docente de Medicina Familiar y Comunitaria. Gerencia de Atención Primaria, Santander, Spainc Department of Child and Adolescent Psychiatry and Psychology, Hospital Clínic Universitari of Barcelona, IDIBAPS (Institut d'Investigacions Biomèdiques August Pi Sunyer),2009 SGR 1119. Department of Psychiatry and Psychobiology, Health Sciences Division, University of Barcelona, CIBERSAM, Spaind Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spaine Stanley Institute International Mood-Disorders Research Center, 03-RC-003, Hospital Santiago Apóstol, CIBERSAM, Vitoria, Spainf Child & Adolescent Psychiatry Unit, Department of Psychiatry, University of Navarra Clinic, Pamplona, Spain

⁎ Corresponding author at: Hospital Universitario Marqlescent PsychiatryUnit. Department of Psychiatry. Planta 2de Valdecilla s/n, 39008 Santander (Cantabria), Spain. Te942 202537.

E-mail address: bpaya@humv.es (B. Payá).

0920-9964/$ – see front matter © 2013 Elsevier B.V. Allhttp://dx.doi.org/10.1016/j.schres.2013.01.029

a b s t r a c t

a r t i c l e i n f o

Article history:

Received 21 August 2012Received in revised form 8 January 2013Accepted 28 January 2013Available online 7 March 2013

Keywords:Premorbid adjustmentChildhood bipolar disorderChildhood schizophreniaChildhood psychosisPremorbid abnormalities

Background: Despite the large body of research on premorbid impairments in schizophrenia, studies compar-ing different early-onset psychoses are scarce.Aims: To examine premorbid impairments in first episodes of early-onset bipolar and schizophrenia disorders.Method:We compared premorbid adjustment and other premorbid variables such as IQ and developmental ab-normalities in a cohort of children and adolescents (N=69) with bipolar disorder (BP) or schizophrenia (SZ)experiencing their first psychotic episode and in a healthy control group (N=91).Results: Schizophrenia patients showed more social impairment in childhood than bipolar patients (pb0.05)and healthy controls (pb0.001) and had higher rates of developmental abnormalities (pb0.05) than healthycontrols. Between childhood and early adolescence, schizophrenia and bipolar patients showed a greater de-cline in academic adjustment than healthy controls, more specifically in adaptation to school (pb0.01).Conclusions: Early-onset schizophrenia patients showmore early social impairment than early-onset bipolar pa-

tients. Intellectual premorbid abnormalities are less specific and probably more linked to early-onset psychosis.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

In recent years, there has been growing interest in studying theperiod that precedes the onset of psychosis and its relevance forearly detection. Premorbid developmental impairments precedingonset of illness have been one of these lines of research (Hollis, 1995).Other studies (Addington and Addington, 2005; Rietschel et al., 2009)have focused their attention on premorbid adjustment (PMA), definedas the level of functioning prior to onset of illness. Developmentalabnormalities (Walker and Lewine, 1990) and impairment of PMA(Larsen et al., 1996; Malmberg et al., 1998; Schmael et al., 2007) havebeen described in adult-onset schizophrenia. Studies in early-onsetschizophrenia have also consistently reported abnormalities in speech,

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language, and motor development (Watkins et al., 1988; Hollis, 1995;Nicolson et al., 2000) as well as premorbid social and academic difficul-ties (Alaghband-Rad et al., 1995; Hollis, 1995). Furthermore, compari-son studies report that patients with schizophrenia with onset before18 years of age have worse PMA (Vourdas et al., 2003; Joa et al., 2009)than thosewith adult onset, suggesting a possible relationship betweenage at onset of illness and severity of premorbid impairments.

Several questions remain open on premorbid impairment in early-onset psychosis. Firstly, it is unclear whether premorbid impairmentsare a general feature of psychosis, or – as is the case in adult populations –if they are more specific to schizophrenia as compared with bipolardisorders (Rietschel et al., 2009). Secondly, it is not clear if premorbidfunctioning is a unitary construct or if it is expressed across at leasttwo related but unique domains, i.e., the academic and social domains(Allen et al., 2001). In this study, we assessed premorbid abnormalitiesincluding estimated premorbid IQ, developmental delays, and premorbidadjustment in samples of patients with early-onset (defined as onsetbefore 18 years of age) bipolar (BP) or schizophrenia (SZ) disordersexperiencing a first psychotic episode, versus healthy controls. Basedon previous studies in adult populations, we hypothesized greater

104 B. Payá et al. / Schizophrenia Research 146 (2013) 103–110

premorbid impairments in our early SZ sample compared with BPand healthy controls.

2. Materials and methods

2.1. Study setting

Data for the present investigation were obtained from a 2-yearlongitudinal multicenter Spanish study (CAFEPS) designed to assessdifferent clinical and laboratory variables. The design and the charac-teristics of the total study population have been reported elsewhere(Castro-Fornieles et al., 2007). The studywas conducted in 6 psychiatricunits at university hospitals throughout Spain, and was approved bythe IRBs of all participating clinical centers. Parents or legal guard-ians of patients gave written informed consent and patients agreedto participate.

2.2. Subjects

Inclusion criteria for patients were age between 7 and 17 yearswith a first episode of psychosis of less than 6 months' duration. Ex-clusion criteria included presence of another Axis I disorder at thetime of assessment that might explain the psychotic symptoms, mentalretardation, pervasive developmental disorder, neurological disorders,history of head trauma with loss of consciousness, and pregnancyor lactation.

The inclusion criteria for controls were age and sex similar to pa-tients, coming from the same geographical areas as patients, no psy-chiatric disorder at baseline assessment, and no neurological disorders,head trauma, pregnancy, or mental retardation.

History of previous psychiatric disorders was not an exclusioncriterion either in the patient samples or in the control group. Werecruited 116 patients, but 6 patients were excluded – 3 due to mentalretardation and 3 due to parental refusal of consent – leaving 110 pa-tients. Of the 104 healthy controls recruited, six controls were excludeddue to diagnosis of a psychiatric disorder at the time of baseline assess-ment (2 attention deficit hyperactivity disorder, 3 anxiety disorder, 1anorexia nervosa), leaving a total of 98 controls.

Diagnoses were established at baseline and after 24 months offollow-up according to DSM-IV criteria (American PsychiatricAssociation, 1994) using the Spanish version of the semi-structured di-agnostic interviewdesigned to assess current and past psychopathology:the Kiddie-Schedule for Affective Disorders and Schizophrenia, Presentand Lifetime version, K-SADS-PL (Ulloa et al., 2006), and diagnoseswere reviewed at 6 and 12 months using the same criteria. Parentsand patients were interviewed separately by experienced child psychi-atrists trained in the use of the instrument. Consensus diagnoses weremade in those caseswhere presence or absence of psychiatric diagnoseswas in doubt.

To increase the reliability of the diagnosis (Castro-Fornieles et al.,2011) and given that diagnostic changes are common during follow-upin first psychotic episodes (Tohen et al., 2012), we used the diagnosesestablished at 24 months to classify the subjects in each diagnosisgroup. For this study, we included only diagnoses of SZ and BP.

At 2 years, there were 40 patients with SZ and 20 with BP. At2 years, there were 17 patients with confirmed diagnoses other thanBP or SZ (major depressive disorder N=2; depressive disorder nototherwise specified N=1; hypomania N=1; schizoaffective disorderN=7; substance abuse N=1; others N=5), and these were excluded.

At the 2-year follow-up, 27 patients did not have an availablediagnosis. From that group, we included those with a confirmed1-year diagnosis of SZ (N=6) or BP (N=3).

In addition, we excluded 7 controls who did not complete thePremorbid Adjustment Scale (PAS). Thus, a final population of 69 pa-tients (46 SZ and 23 BP) and 91 healthy controls was analyzed in thisstudy.

2.3. Assessment

2.3.1. Sociodemographic and other premorbid variablesWe obtained age, gender, and years of formal education for all

subjects, as well as parental years of formal education. Parental socio-economic status (SES)was also assessedwith the Hollingshead–RedlichScale (Hollingshead and Redlich, 1958).

We interviewed parents and reviewed medical records to retro-spectively assess the presence of developmental abnormalities, ratedas present or absent.

Under the term “developmental abnormalities,” we include the en-tire spectrum of language abnormalities, such as articulation abnormal-ities, language delay, and receptive–expressive language dysfunctions,as well as motor impairments such as delayed motor milestones, clum-siness, and poor coordination.

We estimated baseline Intelligence Quotient (IQ) in patients andcontrols with the short-form combination of vocabulary and block de-sign subtests of the WAIS or WISC-R scales (Sattler, 2001). The vocabu-lary subtest from theWAIS or WISC-R was used to estimate premorbidIQ, since this subtest has been identified as a single valid measure ofpremorbid IQ (Lezak, 1995), and it has been used for estimation ofpremorbid IQ in schizophrenia samples (González-Blanch et al., 2007).

2.3.2. Assessment of premorbid adjustmentPremorbid adjustment was assessed retrospectively with the

premorbid adjustment scale (PAS) (Cannon-Spoor et al., 1982). Thisscale was administered based on information from both family mem-bers and the patient. As the assessment of premorbid adjustment isperformed at baseline, to avoid being influenced by the subject's clinicalsymptomatology, for the final score,we gave greaterweight to informa-tion gathered from parents than the subject's own report.

The PAS assesses premorbid functioning across four age ranges:childhood (PAS-C; up to age 11), early adolescence (PAS-EA; 12 to15 years), late adolescence (PAS-LA; 16 to 18 years), and adulthood(PAS-A; 19 years and older). Late adolescence and adulthood were notused in our study, given the age of our samples. Five item scores areobtained in each life period for sociability and withdrawal (PAS1), peerrelationships (PAS2), scholastic performance (PAS3), and adaptationto school (PAS4). The ability to initiate sociosexual relations (PAS5)is also assessed in early and late adolescent stages. Items are mea-sured with a Likert-type scale of 0–6, where lower values reflect bet-ter functioning.

Based on the results of factor analytic studies (Cannon et al., 1997;Allen et al., 2001), academic and social premorbid domain scoreswere calculated for childhood and early adolescence by summingthe appropriate item scores and dividing the resulting score by thetotal possible score for that stage and domain. A global score for eachlife period was also obtained by adding all item scores for that periodand dividing by the total possible score for that age period.

We consider that the premorbid period, as defined by Cannon-Spooret al. (1982), ends 6 months before the onset of psychotic symptoms.As the authors recommend rating only those life periods that arepremorbid by definition, use of the scale must exclude those 6 monthsprior to the onset of the psychotic symptoms.

However, since early-onset psychosis may have an insidious onset,in order to avoid as far as possible any bias resulting from the inclusionof prodromal or early symptomatology, the developmental period thatcorresponds to onset of illness was not rated (e.g., a patient withonset during late adolescence would be rated only for childhood andearly adolescence).

2.4. Statistical analysis

Gender and presence of developmental abnormalities were com-pared with chi-square tests. An Analysis of Variance (ANOVA) wasused to study age, premorbid IQ, parental years of education, and

Table 1Comorbidities and prior psychiatric diagnoses in schizophrenia and bipolar samples.

Schizophrenia (N=46) Bipolar (N=23)

Psychiatric disorders at thetime of assessmenta

Attention deficithyperactivity disorder2/46Anxiety disorders 1/46Oppositional defiantdisorder 1/46

Specific phobia 1/23

Prior psychiatric diagnosisa Language disorders8/46Reading/writingdisorders 7/46Motor developmentdisorders 4/46Sphincter disorders1/46Oppositional defiantdisorder 2/46Attention deficithyperactivity disorder1/46Anxiety disorders 4/46Mood disorders 1/46Others disorders2/46

Reading/writingdisorders 1/23Motor developmentaldisorders 1/23Sphincter disorders3/23Oppositional defiantdisorder 1/23Attention deficithyperactivity disorder1/23Anxiety disorder 4/23Mood disorders 5/23Other disorders1/23

a Comorbidities and prior diagnoses were assessed with the Kiddie-Schedule forAffective Disorders and Schizophrenia, Present and Lifetime version (K-SADS-PL).

105B. Payá et al. / Schizophrenia Research 146 (2013) 103–110

parental SES. Post-hoc analyses comparing differences among groupsin these continuous variables were done with a Bonferroni correctionfor multiple comparisons; those variables that differed between pa-tients and controls were used as covariates. The mean, standard devi-ation (SD), and sample size were used to describe the continuousvariables. Frequencies and percentages were used to describe discretevariables.

An Analysis of Covariance (ANCOVA), with premorbid IQ, parentalyears of education, parental SES, and developmental abnormalities ascovariates, was used to study differences in individual PAS items andPAS total, academic, and social scores at each developmental stage(childhood and early adolescence) between patients and healthycontrols. Due to the variation in age at onset of illness in the studypopulation, no information can be gathered for time periods not yetreached by younger subjects. Therefore sample size varied for the dif-ferent analyses. In order to assess longitudinal patterns of PMA, thechange in PAS scores between childhood and early adolescence pe-riods was calculated for the subsample with late adolescent onset.This subsample was chosen because it was the only subsample with2 consecutive PAS periods available. These change scores were calcu-lated by subtracting early adolescence PAS scores minus childhoodPAS scores for overall, social, and academic PAS domains, and individualPAS items. A positive difference in this subtraction indicates impair-ment in PMA between the two life periods, and a negative differenceindicates an improvement in PMA. Finally, all groups (SZ, BP, andcontrols) were compared for those change scores by means of a uni-variate ANCOVA. A Bonferroni correction was applied for post-hoccomparisons. The Statistical Package for Social Science (SPSS), ver-sion 12.0 (Norusis, 2005) was used for statistical analyses. All statis-tical tests were two-tailed, and significance was determined at the0.05 level.

3. Results

3.1. Clinical, demographic and premorbid characteristics of the samples

A description of comorbidities and prior psychiatric diagnoses inSZ and BP samples is presented in Table 1.

Means and SD of the three groups for sociodemographic charac-teristics, developmental abnormalities, and cognitive characteristicsare presented in Table 2. The ANOVA (Table 2) revealed that the groupsdid not differ in age or sex. BP and SZ had lower IQ and fewer parentalyears of education compared with controls, and there were no differ-ences between them. The BP group also had lower parental SES thanthe control group.

Since there were differences between groups in parental SES andparental education, and since these factors can influence IQ, an addi-tional ANCOVA was performed with parental years of education andparental SES as covariates. The ANCOVA confirmed differences acrossgroups in IQ (F=18.890, pb0.0001). Bonferroni post-hoc analysesagain revealed differences between both BP and SZ and the controlgroup, with both patient groups having lower IQs than the controlgroup (SZbcontrols, pb0.001; BPbcontrols, pb0.001).

Chi-square (χ2) tests revealed differences across groups in pres-ence of developmental abnormalities. Independent Chi-square testsrevealed a higher prevalence of developmental abnormalities in SZcompared with the control group (χ2=5.63; pb0.05) and a trendfor significance between SZ and BP (χ2=3.72; p=0.053), with theSZ group having a higher percentage of developmental abnormalitiesthan the BP group.

3.2. Between-groups differences in PAS scores

3.2.1. Gender differences in PAS scoresThere were no gender differences in either of the two diagnostic

groups with respect to PAS scores. In the healthy control group,

males had worse total and academic PAS scores with no differencein social scores as compared with females. There were no differencesin gender representation among the three groups (schizophrenia, bi-polar, and healthy controls).

3.2.2. PAS scores in childhoodTable 3 shows childhood PAS scores for the three groups and the

ANCOVA and post-hoc comparison results.The ANCOVAs showed significant differences across groups in all

PAS scores dimensions and items except for scholastic performance(PAS3-C), an item included in the academic dimension.

The post-hoc comparison revealed that both SZ and BP have worsescores than healthy controls in all childhood PAS dimensions and items,except for PAS3-C, where neither SZ nor BP patients differ from the con-trol group. For the sociability and withdrawal item (PAS1-C), only SZhave worse scores than controls, while BP patients have scores similarto the control group. Significant differences were also found betweenthe SZ and the BP group for PASC-1, where SZ had worse scores thanthe BP group. No other significant differences were found between thetwo psychosis groups in other childhood PAS scores.

3.2.3. PAS scores in early adolescenceEarly adolescence PAS scores for SZ, BP, and control groups and

the ANCOVA and post-hoc comparison results are shown in Table 4.We found differences across groups in all PAS scores and items.

Post-hoc analyses revealed that the main differences in the early ad-olescence period were between diagnostic groups and controls, withSZ and BP groups showing worse scores than the control group intotal, social, and academic PAS. For all individual PAS items, both psy-chosis groups scored worse than controls, except in scholastic perfor-mance, an item where BP was the only group that had significantdifferences from controls, i.e., worse scores. We found no significantdifferences between SZ and BP groups in any of the early adolescencePAS scores, although comparison scores in the PAS social dimensionshowed a trend toward significance (p=0.07) between the twogroups, with SZ scoring worse than the BP group.

Table 2Sociodemographic characteristics, premorbid IQ, and developmental abnormalities in SZ and BP groups compared with healthy controls.

Controls (N=91) SZ (N=46) BP (N=23) Statistic Comparisons

Mean (SD) Mean (SD) Mean (SD) Fa p

Age 15.1 (1.9) 15.42 (2.01) 16.04 (1.39) 2.113 0.124Subjects' years of education 8.8 (1.87) 8.2 (2.17) 8.96 (1.29) 2.229 0.111Parental years of education 14.91 (4.10) 11.69 (3.78) 10.87 (2.71) 16.463 b0.001 Controlsc>SZ⁎⁎⁎; controls>BP⁎⁎⁎

Parental SES 3.29 (1.34) 2.73 (1.35) 2.43 (1.04) 5.249 0.006 Controlsc>BP⁎

Premorbid IQ 103 (12.91) 86.33 (13.16) 87.17 (16.43) 25.887 b0.001 Controlsc>SZ⁎⁎⁎; controls>BP⁎⁎⁎

% % % χ2b pGender (% male) 61.5 73.3 69.6 2.017 0.365Developmental abnormalities 11.1 27.3 4.3 8.461 0.015 ControlsbbSZ⁎

SZ = Schizophrenia; BP = Bipolar disorder; and SES = Socioeconomic status.a Results of univariate ANOVA; significant results are shown in bold.b Correspond to results of chi-square test; significant results are shown in bold.c Correspond to Post-hoc Bonferroni pairwaise comparison.⁎ pb0.05.⁎⁎ pb0.01.

⁎⁎⁎ pb0.001.

106 B. Payá et al. / Schizophrenia Research 146 (2013) 103–110

3.2.4. Differences in PAS change scores between childhood and earlyadolescence in the subsample with late adolescent onset

Table 5 shows “PAS change scores” between childhood and earlyadolescence for all the groups and the ANCOVA and post-hoc compar-ison results.

The ANCOVA revealed differences across groups for “PAS changescores” in total PAS, academic PAS, and adaptation to school (PAS4).The post-hoc comparison revealed differences with respect to changein total PAS scores between SZ and controls. The control group showeda slight improvement in total adjustment scores between childhoodand early adolescence, while SZ showed a worsening in total adjust-ment scores between the two life periods.

Differences were also found with respect to change in academicPAS scores between childhood and early adolescence between BP andSZ and the control group, with both psychosis groups showing greaterworsening in academic adjustment scores than the control group.

In the individual items that comprise the academic dimension,the post-hoc comparison revealed differences only in adaptation toschool item change scores (PAS-4) between both SZ and BP and the con-trol group. Both psychosis groups showed greater worsening of scoresfor this item between childhood and early adolescence than the controlgroup. No differences between groups were found in change scores forthe scholastic performance item (PAS-3). All patient and control groupsshowed a similar change in scores on this item between childhood andearly adolescence.

Table 3Childhood PAS scores in schizophrenia and bipolar disorder compared with healthy contro

SZ (N=46) BP (N=23) Controls (N

χ SD χ SD χ

Total PAS-C 0.36 0.21 0.28 0.16 0.12PAS Acad-C 0.36 0.21 0.35 0.20 0.16PAS Social-C 0.36 0.28 0.21 0.21 0.08PAS1-C 2.24 1.93 1.13 1.52 0.53PAS2-C 2.07 1.74 1.39 1.20 0.45PAS3-C 3.04 1.55 3.09 1.31 1.82PAS4-C 1.33 1.38 1.09 1.28 0.15

SZ = Schizophrenia; BP = Bipolar disorder; Total PAS-C: scores on total PAS in childhoodSocial-C: scores on social dimension of PAS in childhood period; PAS1-C: scores on sociabitem in childhood period; PAS3-C: scores on scholastic performance item in childhood periRating scores for total, academic, and social PAS are expressed as decimal numbers from 0.0 tbetter adjustment.

a Post-hoc Bonferroni pairwise comparison.b Results of univariate ANCOVA with covariation of IQ, parental SES, parental years of ed⁎ pb0.05.

⁎⁎ pb0.01.⁎⁎⁎ pb0.001.

No group differences were found in change scores of the social PASdimension and the individual items that comprise this dimension ofpremorbid adjustment between the two life periods.

4. Discussion

In this study, higher rates of premorbid impairments were identi-fied in SZ and in BP, as compared with healthy controls. Higher ratesof developmental abnormalities were found in the SZ sample as com-pared with controls.

Both early-onset disorders showed lower premorbid IQ and worsetotal and social premorbid adjustment since childhood than healthycontrols. Adaptive scholastic aspects were also impaired in SZ andBP compared with the control group.

Although there are previous studies comparing premorbid func-tioning between early-onset schizophrenia and bipolar disorder(Hollis, 2003; McClellan et al., 2004), some using the same measuresof premorbid adjustment as in the present study (McClellan et al.,2003), to the best of our knowledge, this is the first study that ana-lyzes individual dimensions of PMA in early-onset psychosis using acomparison control group.

The childhood impairments founded in the SZ sample are in keepingwith previous research that has found premorbid adjustment and intel-lectual impairments preceding early- and adult-onset schizophrenia

l group.

=91) Statistic Comparisonsa

SD Fb p

0.10 18.554 b0.001 ControlsbSZ⁎⁎⁎; ControlsbBP⁎⁎⁎

0.13 5.784 0.004 ControlsbSZ⁎⁎; ControlsbBP⁎

0.13 20.787 b0.001 ControlsbSZ⁎⁎⁎; controlsbBP⁎⁎

0.87 16.078 b0.001 ControlsbSZ⁎⁎⁎; BPbSZ⁎

0.79 20.280 b0.001 ControlsbSZ⁎⁎⁎; controlsbBP⁎⁎⁎

1.30 1.389 0.2530.58 11.003 b0.001 ControlsbSZ⁎⁎⁎; controlsbBP⁎⁎

period; PAS Acad-C: scores on academic dimension of PAS in childhood period; PASility and withdrawal item in childhood period; PAS2-C: scores on peer relationshipsod; and PAS4-C: scores on adaptation to school item in childhood period.o 1.0. Individual PAS score items are expressed as real scores (0–6). Lower scores reflect

ucation, and developmental abnormalities. Significant results are shown in bold.

Table 4Early adolescence PAS scores in schizophrenia and bipolar disorder compared with healthy control group.

SZ (N=46) BP (N=23) Controls (N=91) Statistic Comparisonsa

χ SD χ SD χ SD Fb p

Total PAS-EA 0.41 0.23 0.32 0.17 0.12 0.09 28.299 b0.001 ControlsbSZ⁎⁎⁎; ControlsbBP⁎⁎⁎

PAS Acad-EA 0.47 0.25 0.51 0.27 0.20 0.16 11.308 b0.001 ControlsbSZ⁎⁎⁎; ControlsbBP⁎⁎⁎

PAS Social-EA 0.36 0.31 0.19 0.20 0.07 0.10 23.366 b0.001 ControlsbSZ⁎⁎⁎; ControlsbBP⁎⁎⁎

PAS1-EA 2.28 2.14 1.23 1.53 0.54 0.96 15.494 b0.001 ControlsbSZ⁎⁎⁎; ControlsbBP⁎

PAS2-EA 2.05 1.87 1.41 1.22 0.46 0.79 17.690 b0.001 ControlsbSZ⁎⁎⁎; ControlsbBP⁎⁎⁎

PAS3-EA 3.73 1.71 4.00 1.51 2.13 1.44 3.832 0.024 ControlsbBP⁎

PAS4-EA 1.98 1.58 2.14 1.98 0.29 0.80 17.089 b0.001 ControlsbSZ⁎⁎⁎; ControlsbBP⁎⁎⁎

PAS5-EA 2.13 2.04 1.10 1.48 0.23 0.42 22.110 b0.001 ControlsbSZ⁎⁎⁎; ControlsbBP⁎⁎

SZ = Schizophrenia; BP = Bipolar disorder; Total PAS-EA: scores on total PAS in early adolescence period; PAS Acad-EA: scores on academic dimension of PAS in early adolescence;PAS Social-EA: scores on social dimension of PAS in early adolescence period; PAS1-EA: scores on sociability and withdrawal item in early adolescence period; PAS2-EA: scores onpeer relationships item in early adolescence period; PAS3-EA: scores on scholastic performance item in early adolescence period; PAS4-EA: scores on adaptation to school item inearly adolescence period; and PAS5-EA: scores on sociosexual item in early adolescence period.Rating scores for total, academic, and social PAS are expressed as decimal numbers from 0.0 to 1.0. Individual PAS scores items are expressed as real scores (0–6). Lower scoresreflect better adjustment.

a Post-hoc Bonferroni pairwise comparison.b Results of univariate ANCOVA with covariation of IQ, parental SES, parental years of education, and developmental abnormalities. Significant results are shown in bold.⁎ pb0.05.

⁎⁎ pb0.01.⁎⁎⁎ pb0.001.

107B. Payá et al. / Schizophrenia Research 146 (2013) 103–110

(Jones et al., 1994; McKenna et al., 1994; Hollis, 1995; David et al.,1997; Gunnell et al., 2002; Zammit et al., 2004).

Premorbid impairments have been also described in affective dis-orders (Van Os et al., 1997; Sigurdsson et al., 1999) with an associa-tion between poor premorbid functioning and severe forms of thedisorder (Vocisano et al., 1996; Goldberg and Ernst, 2004; Haim et al.,2006).

However, other studies have found better premorbid adjustmentin BP patients than in normal controls (Larsen et al., 1996; Kutcher etal., 1998), as well as normal performance (Reichenberg et al., 2002;Zammit et al., 2004) or higher IQs in children who went on to developmania (Koenen et al., 2009).

Although differences in methodology may explain some of the dis-cordances between studies, more recent studies with large samples(MacCabe et al., 2010) support the existence of subgroups of BP withdifferent grades of premorbid impairment. In these studies, poor andexcellent school performanceswere both associatedwith risk of bipolardisorder.

In our study, all our patients were bipolar type I with psychoticsymptoms before the age of 18 and this may represent a more severe

Table 5Change in PAS scores between childhood and early adolescence: comparison between schsubsample.

SZ (N=28) BP (N=18) Controls

Changec in total PAS 0.05 0.037 −0.01Change in social PAS −0.004 −0.004 −0.027Change in academic PAS 0.139 0.138 0.031Change in PAS1 0 0.06 −0.13Change in PAS2 0.11 0.05 0.02Change in PAS3 0.79 0.72 0.29Change in PAS4 0.9 0.94 0.09

SZ = Schizophrenia; BP = Bipolar disorder.PAS1: sociability and withdrawal item of PAS; PAS2: peer relationships item of PAS; PAS3:The score determined by subtracting the early adolescence period minus the childhood periof individual items is based on actual scores.

a Results of univariate ANCOVA with covariation of IQ, parental SES, parental years of edub Post-hoc Bonferroni pairwise comparisons.c Change in PAS scores was calculated by subtracting scores from the early adolescence p

PMA between the two life periods and negative values indicate an improvement in PMA.⁎ pb0.05.⁎⁎ pb0.01.

⁎⁎⁎ pb0.001.

group of bipolar patients with early premorbid impairments. Sincewe do not have a comparison groupwith early-onset non-psychotic bi-polar disorder, we are not be able to conclude whether the premorbidimpairments found in the BP sample are inherent in the presence ofpsychotic symptomatology or the early age at onset in the sample.

Thepresence of impairment before onset of illness (childhood) couldpoint to abnormal neurodevelopment; however, contrary to what isobserved in SZ, the low percentage of developmental abnormalitiesfound in the BP sample does not strongly support this hypothesis.

Based on previous studies supporting the influence of depressedmood on PAS Scores (Goldberg and Ernst, 2004; Uzelac et al., 2006)and given the higher frequency of previous diagnoses such as anxietyand/ormood disorders in the BP sample as comparewith SZ (χ2=5.93;p=0.0149), we hypothesize that the presence of other factors linked toillness per se, such as affective symptomatology before the emergenceof the first psychotic symptoms, as well as symptoms linked to otherprevious diagnoses such as anxiety disorders may better explain thepremorbid impairment found in the BP sample and suggest the impor-tance on focussing on early detection and effective interventions forearly depressive and/or anxiety symptoms in BP disorder.

izophrenia, bipolar disorder, and healthy control groups for the late adolescent onset

(N=48) Fa p Comparisonsb

6.286 0.003⁎ ControlsbSZ⁎⁎

0.634 0.5336.695 0.002⁎ ControlsbSZ⁎⁎; controlsbBP⁎

0.395 0.6750.265 0.7672.573 0.0828.642 b0.001⁎ ControlsbSZ⁎⁎; controlsbBP⁎⁎

scholastic performance item of PAS; and PAS4: adaptation to school item of the PAS.od for total, academic, and social PAS is based on rating scores, whereas the subtraction

cation, and developmental abnormalities. Significant results are shown in bold.

eriod minus scores from the childhood period. Positive values indicate impairment in

108 B. Payá et al. / Schizophrenia Research 146 (2013) 103–110

As we hypothesized and in keeping with previous adult psychosisstudies, our early-onset SZ patients were more globally impaired inchildhood than BP patients, with more social impairment (Cannonet al., 1997; Tarbox et al., 2012) and higher rates of developmentalabnormalities (Cannon et al., 2002).

These findings are consistent with early-onset psychosis studies(McClellan et al., 2003) that emphasize the importance of aspects ofsociability and withdrawal in childhood to differentiate between BPand SZ. In addition, the early social impairment and the higher ratesof language and motor developmental abnormalities founded in theSZ sample may support a neurodevelopmental model for early onsetSZ. This model has long been dominant for childhood-onset neuro-psychiatric disorders and posits that the illness is the end state ofabnormal neurodevelopmental processes that started years beforeonset of illness.

4.1. Patterns of premorbid adjustment

Studies in adult-onset schizophrenia spectrum disorder (Addingtonand Addington, 2005) have identified several longitudinal patternsof global premorbid adjustment. A deterioratingpatternwasmore com-mon in subjects with earlier age at onset of illness, a finding that is inkeeping with the deteriorating pattern in global adjustment found inour early-onset SZ sample. Since those studies include neither a com-parison with other disorders nor with a control group, it is uncertainwhether these premorbid patterns differ from other psychiatric ornormal populations. Our comparison revealed that SZ clearly differedin their global adjustment compared with the control group betweenthe two periods that precede onset of illness. This finding suggeststhat worsening of global adjustment between childhood and early ado-lescence may be a marker of vulnerability or transition to illness.

In an attempt to go beyond global adjustment, other studies haveindependently analyzed patterns of academic and social adjustment.Most of those were conducted with adult-onset SZ (Allen et al., 2005;Monte et al., 2008; Strauss et al., 2012), and again they lacked a controlgroup or other comparison groups such bipolar disorder.

In keeping with our findings, most of these studies identified morepronounced deterioration in the academic dimension than in the socialdimension during the period that precedes onset of illness. Further-more, we found that adaptation to school is the aspect of the academicdimensionmost susceptible to impairmentwhen the onset of psychosisbecomes imminent.

The fact that the deviation from controls in the pattern of this itemoccurs in both early psychosis groups points to impairment in this itemas a vulnerability marker for transition to general psychosis, more thana specific schizophrenia transition marker.

4.2. Limitations

Our results need to be interpreted in the light of several limitations.Firstly, although compared with the existing literature on early-

onset psychotic disorders, our overall sample size was relatively large,when divided into diagnostic groups, the sample sizes become small,particularly for BD. This makes it difficult to generalize some of theresults and increases the possibilities of type II error.

Our inclusion criterion with respect to subject age between 7 and17 years fails to differentiate between “childhood onset” (b13 years)and “early onset” populations (13–18 years at onset).

The lack of differentiation between these two populations maycontaminate some of our results, since previous studies (Nicolson et al.,2000; Schaeffer and Ross, 2002) have shown that each group has a dif-ferent pattern of pre-morbid functioning.

We assessed the distribution of those two populations in our sam-ples, but given the low number of subjects with psychosis onset before13 years of age (5 in the SZ sample and 1 in the BP sample), we decidednot to do such stratification. The contamination of the results due to lack

of differentiation between these two populations is minor, given thesmall number of individuals with childhood onset.

Another limitation is the difference between patients and controlsin IQ, parental SES, and parental years of formal education. Given thefact that patients and controls came from the same types of schools andgeographical areas, these differencesmay be disease-related (see Castro-Fornieles et al., 2007), and they have been controlled for in the statisticalanalysis by introducing them as covariates.

We also found several methodological limitations linked to ourinclusion/exclusion criteria.

Firstly, the exclusion criterion regarding comorbidity at the timeof assessment differs between the patient and control groups. Thiscould lead to bias because of the use of “well controls” and becauseof the confounding influence of patient's comorbid symptomatologyon premorbid adjustment.

However, the presence of comorbidities at the time of assessmentwould have only a minor influence on premorbid adjustment, sincepremorbid adjustment includes periods much earlier than the onsetof illness.

Additionally, the percentage of patients with comorbidity at thetime of assessment was low. Therefore, we consider that differencesbetween controls and patients groups are not likely to be explained byother comorbid disorders.

The inclusion of subjects with possible prior psychiatric disordersor chronic life-time diagnoses is a more important methodologicallimitation of our study, since results could be reflecting the influenceof the broader psychiatric morbidity on premorbid adjustment andnot just the influence of the psychotic disorder. However, selectionof subjects with BP disorder and SZ with no comorbidity or psychiatrichistory would have been complicated, given that high prevalence ofprior psychiatric disorders is inherent in these populations in the re-search literature (Rubino et al., 2009; Duffy, 2010; Starling et al., 2012).

Finally, we found some limitations linked to the methodology ofassessment.

Although illness symptomatology seems to have little influence ontheWISC orWAIS vocabulary subtest, an evaluation of actual IQ in theperiods before the onset of illness would have been more accuratethan the measurement of IQ at the time of enrollment

Since PAS assesses premorbid adjustment retrospectively, it is sus-ceptible to memory bias. However, as compared with studies in adultpopulations, the time elapsed here is much shorter and therefore lesssusceptible to memory bias.

5. Conclusions

Our results suggest that early-onset schizophrenia and psychoticbipolar disorder are two serious diseases that show impairments indifferent domains before the onset of illness.

SZ shows earlier and more severe social impairment than psychoticBP and has higher rates of developmental abnormalities, aspects thatseem to be more specific markers of early-onset schizophrenia.

On the contrary, low intelligence and adaptive scholastic difficul-ties seem to be more non-specific markers and probably more linkedto general psychosis. Progressive impairment in adaptive scholasticaspects, more than impairment in school performance, seems to bethe aspect of adjustment most susceptible to impairment when theonset of psychosis becomes imminent.

Since teachers have a good understanding of the social and adap-tive functioning of individuals, the school environment may be idealfor implementing some early identification strategies.

FundingThis work was supported by a grant from the Instituto de Salud Carlos III, Spanish De-

partment of Health, Cooperative Research Thematic Network (RETICS)-G03/032, as well asthe Spanish Ministry of Economy and Competitiveness (CIBERSAM), Fundacion AliciaKoplowitz, and Fundacion Mutua Madrileña.

109B. Payá et al. / Schizophrenia Research 146 (2013) 103–110

ContributorsCAFEPS study is being led by CA.CA, BP and JMR designed the present study using data from the CAFEPS and in

selecting the measures.CA, JC, SO, AG, CS and MP designed the study and wrote the protocol.JMR and PM undertook the statistical analysis.BP wrote the first draft of the manuscript and all authors contributed to and have

approved the final manuscript.

Conflict of interestAll authors declare that they have no conflict of interest.

AcknowledgmentsThe authors would like to thank Jose de Arriba of the Child and Adolescent Psychi-

atry Department, Hospital General Universitario Gregorio Marañon and Centro deInvestigación Biomedica en Red de Salud Mental (CIBERSAM), Madrid, Spain for datamanagement.

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