[Skip to Navigation]
Sign In
Change in regional cortical gray matter volumes during adolescence (between mean ages 13 and 18 years) by brain magnetic resonance imaging for healthy volunteers (n=34) and patients with childhood-onset schizophrenia (COS) (n=15) (multivariate analysis of variance for gray matter volume by diagnosis: F, 3.68; P=.004).

Change in regional cortical gray matter volumes during adolescence (between mean ages 13 and 18 years) by brain magnetic resonance imaging for healthy volunteers (n=34) and patients with childhood-onset schizophrenia (COS) (n=15) (multivariate analysis of variance for gray matter volume by diagnosis: F, 3.68; P=.004).

Table 1. 
Demographic Data for Patients With Childhood-Onset Schizophrenia and Healthy Controls*
Demographic Data for Patients With Childhood-Onset Schizophrenia and Healthy Controls*
Table 2. 
Anatomical Brain Magnetic Resonance Imaging Measures and Percentage Changes at Baseline and 3- to 5-Year Follow-up During Adolescence for Patients With Childhood-Onset Schizophrenia and Healthy Controls*
Anatomical Brain Magnetic Resonance Imaging Measures and Percentage Changes at Baseline and 3- to 5-Year Follow-up During Adolescence for Patients With Childhood-Onset Schizophrenia and Healthy Controls*
1.
Weinberger  DR Implications of normal brain development for the pathogenesis of schizophrenia.  Arch Gen Psychiatry. 1987;44660- 669Google ScholarCrossref
2.
Weinberger  D From neuropathology to neurodevelopment.  Lancet. 1995;346552- 557Google ScholarCrossref
3.
Murray  R Neurodevelopmental schizophrenia: the rediscovery of dementia praecox.  Br J Psychiatry. 1994;1656- 12Google Scholar
4.
Jones  PRodgers  BMurray  RMarmot  M Child developmental risk factors for adult schizophrenia in the British 1946 birth cohort.  Lancet. 1994;3441398- 1402Google ScholarCrossref
5.
Done  DCrow  TJohnstone  ESacker  A Childhood antecedents of schizophrenia and affective illness: social adjustment at ages 7 and 11.  BMJ. 1994;309699- 703Google ScholarCrossref
6.
Walker  ELewine  R Predictions of adult onset schizophrenia from childhood home movies of the parents.  Am J Psychiatry. 1990;1471052- 1056Google Scholar
7.
Mathalon  DHSullivan  EVLim  KOPfefferbaum  A Longitudinal analysis of MRI brain volumes in schizophrenia.  Schizophr Res. 1997;24152Google ScholarCrossref
8.
DeLisi  LETew  WXie  SHoff  ALSakuma  MKushner  MLee  GShadlock  KSmith  AMGrimson  R A prospective follow-up study of brain morphology and cognition in first-episode schizophrenic patients: preliminary findings.  Biol Psychiatry. 1995;38349- 360Google ScholarCrossref
9.
DeLisi  LESakuma  MTew  WKushner  MHoff  ALGrimson  R Schizophrenia as a chronic active brain process: a study of progressive brain structural change subsequent to the onset of schizophrenia.  Psychiatry Res. 1997;74129- 140Google ScholarCrossref
10.
DeLisi  LEStritzke  PRiordan  HHolan  VBoccio  AKushner  MMcClelland  JVan Eyl  OAnand  A The timing of brain morphological changes in schizophrenia and their relationship to clinical outcome.  Biol Psychiatry. 1992;31241- 254Google ScholarCrossref
11.
Nair  TRChristensen  JDKingsbury  SJKumar  NGTerry  WMGarver  DL Progression of cerebroventricular enlargement and the subtyping of schizophrenia.  Psychiatry Res. 1997;74141- 150Google ScholarCrossref
12.
Gur  RECowell  PTuretsky  BIGallacher  FCannon  TBilker  WGur  RC A follow-up magnetic resonance imaging study of schizophrenia: relationship of neuroanatomical changes to clinical and neurobehavioral measures.  Arch Gen Psychiatry. 1998;55145- 152Google ScholarCrossref
13.
Asarnow  J Annotation: childhood onset schizophrenia.  J Child Psychol Psychiatry. 1994;351345- 1371Google ScholarCrossref
14.
Asarnow  RBrown  WStrandburg  R Children with a schizophrenic disorder: neurobehavioral studies.  Eur Arch Psychiatry Clin Neurosci. 1995;24570- 79Google ScholarCrossref
15.
Frazier  JAGiedd  JNHamburger  SDAlbus  KEKaysen  DVaituzis  ACRajapakse  JCLenane  MCMcKenna  KJacobsen  LKGordon  CTBreier  ARapoport  J Brain anatomic magnetic resonance imaging in childhood-onset schizophrenia.  Arch Gen Psychiatry. 1996;53617- 624Google ScholarCrossref
16.
Jacobsen  LRapoport  J Childhood-onset schizophrenia: implications of clinical and neurobiological research.  J Child Psychol Psychiatry. 1998;39101- 113Google ScholarCrossref
17.
Alaghband-Rad  JMcKenna  KGordon  CAlbus  KHamburger  SRumsey  JLenane  MRapoport  J Childhood onset schizophrenia: the severity of premorbid course.  J Am Acad Child Adolesc Psychiatry. 1995;431273- 1283Google ScholarCrossref
18.
Kumra  SWiggs  EKrasnewich  DMeck  JSmith  ABedwell  JFernandez  TJacobsen  LRapoport  J Association of sex chromosome anomalies with childhood onset psychotic disorder.  J Am Acad Child Adolesc Psychiatry. 1998;37292- 296Google ScholarCrossref
19.
Nicolson  RRapoport  J Childhood-onset schizophrenia: what can it teach us? Rapoport  Jed Childhood Onset of Adult Psychopathology: Clinical and Research Advances. Washington, DC American Psychiatric Press Inc.In press.Google Scholar
20.
Rapoport  JLGiedd  JKumra  SJacobsen  LSmith  ALee  PNelson  JHamburger  S Childhood-onset schizophrenia: progressive ventricular change during adolescence.  Arch Gen Psychiatry. 1997;54897- 903Google ScholarCrossref
21.
Collins  DLNeelin  PPeters  TMEvans  AC Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space.  J Comput Assist Tomogr. 1994;18192- 205Google ScholarCrossref
22.
Collins  DLHolmes  CPeters  TMEvans  AC Automatic 3D segmentation of neuroanatomical structures from MRI.  Hum Brain Mapping. 1995;3190- 208Google ScholarCrossref
23.
Zijdenbos  AEvans  ARiahi  FSled  JChui  H-CKollokian  V Automatic quantification of multiple sclerosis lesion volume using stereotaxic space. Hohne  KHKikinis  Reds Proceedings of the Fourth International Conference on Visualization in Biomedical Computing (VBC). New York, NY Springer Publishing Co Inc1996;439- 448Google Scholar
24.
Evans  ACCollins  DLHolmes  CJ Automatic 3D regional MRI segmentation and statistical probability anatomy maps. Uemura  KJones  TLassen  NAKanno  Ieds Quantification of Brain FunctionTracer Kinetics and Image Analysis in Brain PET. New York, NY Excerpta Medica1995;123- 130Google Scholar
25.
Sled  JGZijdenbos  APEvans  AC A non-parametric method for automatic correction of intensity non-uniformity in MRI data.  IEEE Trans Med Imaging. 1998;1787- 97Google ScholarCrossref
26.
Gordon  CTFrazier  JAMcKenna  KGiedd  JZametkin  AZahn  THommer  DHong  WKaysen  DAlbus  KE Childhood-onset schizophrenia: an NIMH study in progress.  Schizophr Bull. 1994;20697- 712Google ScholarCrossref
27.
McKenna  KGordon  CTLenane  MKaysen  DFahey  KRapoport  J Looking for childhood onset schizophrenia: the first 71 cases screened.  J Am Acad Child Adolesc Psychiatry. 1994;33636- 644Google ScholarCrossref
28.
Kumra  SFrazier  JAJacobsen  LKMcKenna  KGordon  CTLenane  MCHamburger  SDSmith  AKAlbus  KEAlaghband-Rad  JRapoport  JL Childhood-onset schizophrenia: a double-blind clozapine-haloperidol comparison.  Arch Gen Psychiatry. 1996;531090- 1097Google ScholarCrossref
29.
Giedd  JNSnell  JWLange  NRajapakse  JCCasey  BJKozuch  PLVaituzis  ACVauss  YCHamburger  SDKaysen  DRapoport  JL Quantitative magnetic resonance imaging of human brain development: ages 4-18.  Cereb Cortex. 1996;6551- 560Google ScholarCrossref
30.
Hollingshead  AB Four Factor Index of Social Status.  >New Haven, Conn Yale University Department of Sociology1975;
31.
Collins  DLEvans  AC Animal: validation and applications of non-linear registration-based segmentation.  Int J Pattern Recognition Artif Intell. 1997;111271- 1294Google ScholarCrossref
32.
Zijdenbos  AForghani  REvans  AC Automatic quantification of MS lesions in 3D MRI brain data sets: validation of INSECT. Delp  SWells  WMColchester  Aeds Medical Image Computing and Computer-Assisted Intervention—MICCAI '98First International Conference, Cambridge, MA, USA, October 11-13, 1998, Proceedings. New York, NY Springer-Verlag NY Inc1998;439- 448Google Scholar
33.
Duvernoy  HM The Human Brain: Surface, Three-Dimensional Sectional Anatomy With MRI and Blood Supply.  New York, NY Springer-Verlag NY Inc1995;3- 15
34.
Pfefferbaum  AMathalon  DHSullivan  EVRawles  JMZipursky  RBKim  KO A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood.  Arch Neurol. 1994;51874- 887Google ScholarCrossref
35.
Reiss  AAbrams  MSinger  HRoss  JDenckla  M Brain development, gender, and IQ in children: a volumetric imaging study.  Brain. 1996;1191763- 1774Google ScholarCrossref
36.
Sowell  EThompson  PHolmes  CJernigan  TRBarth  RNaravan  SToga  A Statistical parametric mapping of structural brain changes between childhood and adolescence.  Presented as poster 123.4 at: 28th Annual Meeting of the Society for Neurosciences November 7-12, 1998 Los Angeles, Calif
37.
Sowell  EJernigan  T Further MRI evidence of late brain maturation: limbic volume increases and changing asymmetries during childhood and adolescence.  Dev Neuropsychol. In press.Google Scholar
38.
Benes  FTurtle  MKhan  YFarol  P Myelenization of a key relay zone in the hippocampal formation occurs in the human brain during childhood, adolescence, and adulthood.  Arch Gen Psychiatry. 1994;51477- 484Google ScholarCrossref
39.
Jernigan  TTallal  P Late childhood changes in brain morphology observable with MRI.  Dev Med Child Neurol. 1990;32379- 385Google ScholarCrossref
40.
Huttenlocher  PDeCourten  C The development of synapses in striate cortex of man.  Hum Neurobiol. 1987;61- 9Google Scholar
41.
Sauer  BKammradt  IKrauthausen  GKretchmann  HLange  HWingert  F Qualitative and quantitative development of the visual cortex in man.  J Comp Neurol. 1983;214441- 450Google ScholarCrossref
42.
Cannon  TDvan Erp  TGHuttunen  MLonnqvist  JSalonen  OValanne  LPoutanen  VPStandertskjold-Nordenstam  CGGur  REYan  M Regional gray matter, white matter, and cerebrospinal fluid distributions in schizophrenic patients, their siblings, and controls.  Arch Gen Psychiatry. 1998;551084- 1091Google ScholarCrossref
43.
Weinberger  DBerman  KSuddath  RTorrey  E Evidence of dysfunction of a prefrontal-limbic network in schizophrenia: a magnetic resonance imaging and regional cerebral blood flow study of discordant monozygotic twins.  Am J Psychiatry. 1992;149890- 897Google Scholar
44.
Selemon  LDRajkowska  GGoldman-Rakic  PS Abnormally high neuronal density in the schizophrenic cortex: a morphometric analysis of prefrontal area 9 and occipital area 17.  Arch Gen Psychiatry. 1995;52805- 818Google ScholarCrossref
45.
Rajkowska  GSelemon  LDGoldman-Rakic  PS Neuronal and glial somal size in the prefrontal cortex: a postmortem morphometric study of schizophrenia and Huntington disease.  Arch Gen Psychiatry. 1998;55215- 224Google ScholarCrossref
46.
Selemon  LDGoldman-Rakic  PS The reduced neuropil hypothesis: a circuit-based model of schizophrenia.  Biol Psychiatry. 1999;4517- 25Google ScholarCrossref
47.
Huttenlocher  PR Synaptic density in human frontal cortex—developmental changes and effects of aging.  Brain Res. 1979;163195Google ScholarCrossref
48.
Huttenlocher  PRDabholkar  AS Regional differences in synaptogenesis in human cerebral cortex.  J Comp Neurol. 1997;387167- 178Google ScholarCrossref
49.
Chugani  HPhelps  MMazziotta  JC Positron emission tomography study of human brain functional development.  Ann Neurol. 1987;22487- 497Google ScholarCrossref
50.
Giedd  JJeffries  NNicolson  RHamburger  SDNelson  JVaituzis  ACLenane  MRapoport  JL Differential progression of MRI ventricular and temporal lobe structure during adolescence for childhood onset schizophrenics.  Biol Psychiatry. In press.Google Scholar
51.
Feinberg  I Schizophrenia: caused by a fault in programmed synaptic elimination during adolescence?  J Psychiatr Res. 1982;17317- 334Google ScholarCrossref
52.
Feinberg  IThode  HC  JrChugani  HTMarch  JD Gamma distribution model describes maturational curves for delta wave amplitudes, cortical metabolic rate and synaptic density.  J Theor Biol. 1990;142149- 161Google ScholarCrossref
53.
Irwin  SASwain  RAChristion  FAChakravarti  AGalvez  RGreenough  WT Behavioral alleration of fragile X mental retardation protein expression.  Presented as poster 171.7 at: 28th Annual Meeting of the Society for Neurosciences November 7-12, 1998 Los Angeles, Calif
Original Article
July 1999

Progressive Cortical Change During Adolescence in Childhood-Onset Schizophrenia: A Longitudinal Magnetic Resonance Imaging Study

Author Affiliations

From the Child Psychiatry Branch, National Institute of Mental Health (Drs Rapoport, Giedd, and Nicolson, Messrs Blumenthal, Fernandez, and Bedwell, and Mss Hamburger and Lenane), and Biometry Branch, National Institute of Neurological Disorders and Stroke (Dr Jeffries), Bethesda, Md; and the Montreal Neurological Institute, McGill University, Montreal, Quebec (Drs Zijdenbos, Paus, and Evans).

Arch Gen Psychiatry. 1999;56(7):649-654. doi:10.1001/archpsyc.56.7.649
Abstract

Background  Adolescence provides a window to examine regional and disease-specific late abnormal brain development in schizophrenia. Because previous data showed progressive brain ventricular enlargement for a group of adolescents with childhood-onset schizophrenia at 2-year follow-up, with no significant changes for healthy controls, we hypothesized that there would be a progressive decrease in volume in other brain tissue in these patients during adolescence.

Methods  To examine cortical change, we used anatomical brain magnetic resonance imaging scans for 15 patients with childhood-onset schizophrenia (defined as onset of psychosis by age 12 years) and 34 temporally yoked, healthy adolescents at a mean (SD) age of 13.17 (2.73) years at initial baseline scan and 17.46 (2.96) years at follow-up scan. Cortical gray and white matter volumes were obtained with an automated analysis system that classifies brain tissue into gray matter, white matter, and cerebrospinal fluid and separates the cortex into anatomically defined lobar regions.

Results  A significant decrease in cortical gray matter volume was seen for healthy controls in the frontal (2.6%) and parietal (4.1%) regions. For the childhood-onset schizophrenia group, there was a decrease in volume in these regions (10.9% and 8.5%, respectively) as well as a 7% decrease in volume in the temporal gray matter. Thus, the childhood-onset schizophrenia group showed a distinctive disease-specific pattern (multivariate analysis of variance for change×region×diagnosis: F, 3.68; P=.004), with the frontal and temporal regions showing the greatest between-group differences. Changes in white matter volume did not differ significantly between the 2 groups.

Conclusions  Patients with very early-onset schizophrenia had both a 4-fold greater decrease in cortical gray matter volume during adolescence and a disease-specific pattern of change. Etiologic models for these patients' illness, which seem clinically and neurobiologically continuous with later-onset schizophrenia, must take into account both early and late disruptions of brain development.

THE neurodevelopmental hypothesis of schizophrenia suggests that a brain "lesion" is present early in life but does not manifest itself until late adolescence or early adulthood.1-3 Compelling clinical support for this model comes from numerous demonstrations of subtle but consistent abnormalities in cognitive and behavioral development noted years before the onset of psychosis.4-6 In addition, the postmortem neuropathological findings in schizophrenia can be viewed as consistent with an early nonprogressive event.2

The lack of progressive change in longitudinal brain imaging studies of patients with adult-onset schizophrenia is also cited as support for the "fixed-lesion" neurodevelopmental hypothesis. Of the 5 prospective longitudinal anatomical brain magnetic resonance imaging (MRI) studies of adult-onset schizophrenia that compared patients with temporally yoked controls, only 2 found greater progression for their schizophrenic group as a whole.7-9 Others found either no progression10 or evidence of progression for only a subgroup.11,12

Childhood-onset schizophrenia (COS) (defined as onset of psychosis by age 12 years) is a rare, usually severe manifestation of the disorder that has been shown to be continuous with the adult-onset disorder with respect to clinical and neurobiological characteristics, including brain MRI pattern.13-16 There is also continuity in the pattern of associated risk factors, such as early developmental language and speech abnormalities years before the onset of psychosis,17 cytogenetic abnormalities,18 and various psychopathologic conditions, including schizophrenia and/or "spectrum" disorders, smooth-pursuit eye movement abnormalities, and/or cognitive abnormalities in the close relatives of the COS patients.14,19

An ongoing National Institute of Mental Health study of COS included brain MRI rescans at regular intervals as part of the follow-up examination. A previous report documented an increase in brain ventricular volume between mean ages 14 and 16 years for this group that was more striking and consistent than that reported for adult-onset cases.20 The study also found a trend for differential decrease in total brain volume for adolescents with schizophrenia, but regional cortical volumes were not examined.

The present report is of regional cortical gray and white matter volumes for a group of patients with COS scanned at initial contact (mean age, 13.9 years) and at 3- to 5-year follow-up (mean age, 18.1 years). To carry out this examination, an automated segmentation system developed at the Montreal Neurological Institute, Montreal, Quebec, was used.21-25 Because of our earlier brain ventricular data and the smaller total brain and temporal lobe volumes with greater loss of gray matter characteristic of adults with schizophrenia, we hypothesized that there would be commensurate differential changes in other brain tissue, including cortical gray matter, with patients with COS showing a greater and more regionally selective decline than seen for healthy controls.

Subjects and methods

Subjects included 15 children and adolescents who had been recruited to the National Institute of Mental Health study of COS. Recruiting and diagnostic methods have been described elsewhere.26-28 Briefly, children were sought via national recruiting who met unmodified DSM-III-R criteria for schizophrenia, with onset of psychotic symptoms by age 12 years. From more than 1000 referrals, approximately 250 patients and their families were screened in person, using both clinical examination and structured interviews over a daylong evaluation. The clinical diagnosis of schizophrenia for this group showed good reliability.27 Fifty-four patients received the diagnosis of COS; 47 had participated in the study at the time of this report. As patients were also participating in a clozapine treatment trial,28 they were refractory to treatment with typical neuroleptics.

All subjects returned at regular intervals, at which time clinical reevaluation and MRI follow-up scans were carried out.

Of the 47 subjects studied to date, valid baseline scans could not be obtained for 2. Of the remaining 45, 28 had returned for at least 1 follow-up scan; 18 were rescanned after 3 to 5 years while they were still in adolescence, and 3 of these 18 had 1 scan each that could not be processed by the automated system. Most of the remaining subjects who had not been rescanned were not yet due for their 4-year (approximate) follow-up scan. Thus, only 3 eligible cases were truly unavailable to our team for MRI reevaluation. The 15 cases in the present study did not differ significantly with respect to any clinical or demographic measure from the remainder of the sample.

A temporally yoked, age- and sex-matched healthy control group of 46 adolescents was selected by a systematic evaluation process29; 34 with processable scans served as the contrast group for this report. Controls were free of lifetime medical or psychiatric disorders as determined by clinical examination and standardized interview. Psychiatric illness in a first-degree relative was also exclusionary. The combined groups had a mean (SD) age of 13.17 (2.73) years at the time of initial scan, and returned after 4.28 (0.63) years for follow-up scans. Characteristics of patients and control subjects at baseline and follow-up scan are shown in Table 1.

As shown in Table 1, patients were severely ill, with a mean±SD age of onset of psychotic symptoms at 10.3±2.0 years. The patient group received a considerable amount of medication prior to initial scan, and at follow-up, all but 2 were taking medication. The scan intervals did not differ for the 2 groups. Moreover, while at first scan, the medications were primarily typical neuroleptics, at follow-up, 11 of the 15 patients were receiving atypical neuroleptics, with 2 receiving both a typical and an atypical agent. All met the criteria for schizophrenia (4 were in remission while taking clozapine) at the follow-up scan. None of these young subjects had a history of substance abuse. Thus, while patients were matched for age, sex, and time of scan, they differed significantly with respect to ethnicity, socioeconomic status, IQ score, exposure to medication, and weight at follow-up scan.

The study was approved by the National Institute of Mental Health Institutional Review Board. Parents gave written consent, and minor volunteers and patients gave verbal assent for this study.

Mri acquisition and analysis

All images were acquired on the same 1.5-T Signa scanner (General Electric, Milwaukee, Wis) located at the National Institutes of Health Clinical Center, Bethesda, Md. A 3-dimensional spoiled gradient-recalled echo in the steady-state sequence designed to optimize discrimination between gray matter, white matter, and cerebrospinal fluid was used to acquire 124 contiguous 1.5-mm-thick slices in the axial plane and 124 contiguous 2.0-mm-thick slices in the coronal plane. Imaging parameters were as follows: time to echo, 5 milliseconds; time to repeat, 24 milliseconds; flip angle, 45°; acquisition matrix, 256×192; number of excitations, 1; and field of view, 24 cm.

Three vitamin E capsules, 1 placed in the meatus of each ear and 1 taped to the left lateral inferior orbital ridge, were used to standardize head placement across individuals. The vitamin E capsules showed up brightly on the scans, and an axial-localizing sequence was acquired to assess whether the 3 capsules were visible in the same axial plane. This served to ensure brain coverage and minimize partial volume losses. If this criterion was not met the subject's head was repositioned. The subject's nose was aligned at the 12-o'clock position to assist standardization within the axial plane. Foam padding was placed around the head to minimize scanner noise and help steady the head position. Subjects were scanned in the evening to promote natural sleep. Sedation with chloral hydrate (0.5-2.0 g) or lorazepam (0.5-2.0 mg) was used for 20% of the COS subjects. No controls were sedated.

Gray matter, white matter, and cerebrospinal fluid segmentation was performed via a 3-part automated image analysis process.21-25,31 First, the images are corrected for regional intensity nonuniformities resulting from magnetic field inhomogeneities inherent in the image acquisition process. Next, the images are transformed to a standardized stereotactic (Talairach) space using a 9-parameter linear process.21 The images are then registered in a nonlinear way to a template brain for which anatomical regions have been manually defined. The nonlinear registration of each subject's MRI with the anatomically defined template brain allows each voxel to be assigned a tissue type and an anatomical structure of which it is a part.22,23,32

The lobar boundaries were defined as in a standard atlas.33 The central sulcus was used to separate the frontal lobe from the parietal lobe, which was bounded inferiorlyby the lateral fissure and a line extending the lateral fissure to the occipital lobe. The temporal lobe was bounded superiorly by the lateral fissure and an extension of the lateral fissure to the occipital lobe. The occipital lobe was bounded by a curved line extending from the parieto-occipital fissure to the temporo-occipital incisure.

This information was merged with information from an artificial neural network classification technique that assigns a gray matter, white matter, or cerebrospinal fluid designation based on voxel intensity.

Statistical analysis

Demographic characteristics of patients and controls were compared using t tests or χ2 tests where appropriate.

Subtracting the baseline MRI value from the follow-up value and then dividing by the baseline measurement value created change scores for total and regional gray and white matter. These percentage change scores were then used in all statistical analyses. Group differences were examined with 1-way analysis of variance (ANOVA), repeated-measures ANOVA, or multivariate ANOVA (MANOVA) using the Wilks λ result. Post hoc testing determined significant differences.

For the control group, regional regression slopes for individual change over time were examined, using absolute values of the region, in relation to sex, socioeconomic status, and the Wechsler Intelligence Scale for Children Vocabulary and Block Design scores. For the patients with schizophrenia, these slopes were examined in relation to sex, ethnicity, age of onset, weight gain while taking neuroleptics, and neuroleptic exposure (typical and atypical separately). The results were expressed as standard regression β coefficients.

The SPSS 9.0 statistical package for Windows (SPSS Inc, Chicago, Ill) was used for all analyses, with a 2-tailed α level of .05.

Results

Both absolute baseline and follow-up scan values and percentage change for total and regional gray and white volumes are shown in Table 2 for COS patients and healthy controls.

Within-group change

For the 34 healthy controls, there was a significant (1.3%) decrease in total cerebral volume that was accounted for by a decrease in gray matter volume (1.98%) (t=2.12, P=.04). As seen in Table 2, the regional gray matter changes also showed a statistically significant selective regional pattern (MANOVA Wilks λ: F, 19.1; P<.001), with the greatest change in the frontal and parietal gray matter and the smallest change in the occipital and temporal gray matter regions.

For the 15 COS patients, there was a significant (5.5%) decrease in total cerebral volume that was accounted for by a decrease in gray matter (8.0%). The regional gray matter change also differed selectively for COS patients (MANOVA Wilks λ: F, 11.2; P=.001), with 7% to 10% decreases for frontal, parietal, and temporal gray matter volume and no significant change in the occipital region.

Between-group comparisons

As shown in Table 2, the percentage change differed strikingly between the groups for gray matter, with the COS group showing an exaggerated and unique pattern (MANOVA Wilks λ: F, 3.72; P=.002 overall; F, 3.68; P=.004 for regional×diagnosis interaction). The diagnostic differences were most striking for temporal (P<.001) and frontal (P=.001) gray matter volumes. There was no significant difference between the groups with respect to white matter change.

The disease-specific change in brain development is seen most clearly in Figure 1, showing the difference in the percentage and pattern of decline between the COS and healthy control groups.

Clinical and demographic relationships

Boys had more robust decreases in gray matter than did girls (P=.05), and this difference was more pronounced for the COS group (ANOVA: F, 4.09; P=.05 for diagnosis×sex). For the healthy controls, there was no significant relationship between full-scale IQ score, socioeconomic status, or ethnicity and slope of change for any region. For the COS group, those with higher baseline Brief Psychiatric Rating Scale scores had a greater rate of volume decrease for temporal, parietal, and frontal gray matter (t, 2.6-3.5; P<.01). There was no significant relationship between weight gain or drug exposure and slope for any region. Further clinically relevant analyses were precluded by missing data and small sample size.

Comment

Within a 4-year mid-adolescent period, a significant decline in cortical gray matter volume was seen for the healthy controls. The frontal gray and white matter and parietal gray matter volumes decreased, while white matter volumes in the parietal temporal and occipital regions increased. These data support previous cross-sectional studies of clinically referred children and adolescents34 and healthy prescreened controls,35 which found age-related decreases in cortical gray matter.35 Most recently, Sowell et al36,37 found similar and striking age-related decreases in frontal and parietal gray matter for 35 healthy children and adolescents for whom statistical mapping of subtraction images was carried out. Brain regions do not normally mature in parallel, and the regional changes seen here are more robust than generally seen in young adults.12

These longitudinal data for middle and late adolescence show that frontocortical gray matter volume is decreasing. While it is tempting to ascribe these developmental brain changes to peripubertal events, this is clearly not the case. Evidence from cross-sectional studies,29,34,35,38,39 shows that the trend for decrease in gray matter volume and continued myelination occurs across a wide age range. Previous postmortem40,41 data also show decreases in occipital cortex volume during the first decade of life.

The adolescents with schizophrenia showed an exaggerated pattern of brain changes similar in part to that of the controls, with a significantly more robust decrease in volume for the frontal and parietal gray matter and no significant change in occipital gray matter. The significant decrease in temporal lobe volume was, however, unique to the schizophrenic group. The selective regional decline in frontal and temporal gray matter is consistent with the MRI findings in adult-onset schizophrenia, for which the greatest regional difference is found in the frontal and temporal areas.42 These data are also consistent with evidence suggesting that abnormalities in frontal and temporal lobe connectivity underlie the symptoms of schizophrenia.43 Thus, a specific pattern in keeping with MRI findings for adults with schizophrenia develops across the adolescent years. The presumed changes underlying this differential progression would include excessive synaptic and dendritic pruning, and probably also trophic glial and vascular decreases, compatible with the neuropathological findings of Selemon et al,44 Rajkowska et al,45 and Selemon and Goldman-Rakic46 showing increased neuronal density and possible trophic glial changes in the schizophrenic cortex.

Adolescence is a period of marked change in brain anatomy and metabolism.47-49 Because neuropathological observations of normal development are based on very meager data sets since death during childhood and adolescence of otherwise healthy individuals is rare, brain MRI studies provide a unique and noninvasive way to study brain development in healthy children.29 This study extends our earlier cross-sectional data with the first longitudinal brain MRI study of healthy adolescents; surprisingly robust changes are seen during this limited period between ages 13 and 18 years.

This study of diagnostic differences in brain development is limited by many factors. The samples are not matched for socioeconomic status, race, IQ score, or exposure to neuroleptic medication. Moreover, several COS patients were switched to therapy with newer atypical antipsychotics at follow-up. In addition, COS patients represent a severely ill, treatment-refractory population; "episodes" of illness were virtually unknown and fluctuations in clinical state were regrettably few. Thus, it might be argued that these differences in progression reflect the course of a subgroup of subjects with poor outcomes described in previous studies of patients with adult-onset schizophrenia. This seems unlikely, however, given that as our patients reach their early adult years, the rate of ventricular enlargement slows and does not differ from that of healthy controls.50 Thus, the lack of progression seen in most studies of adult patients was also observed in our subjects after they passed through adolescence.

In theory, the late progressive brain changes might reflect some unique interaction between adolescent brain development and the illness, including stress and drastically altered environmental exposure and/or treatments, not seen in schizophrenia at other ages. This possibility cannot be addressed by these data. An ongoing longitudinal MRI study of our patients' siblings may shed further light on a familial genetic basis for these progressive events. It is unlikely, however, that the patients' differential weight gain affected our findings; after age was taken into account, neither weight nor body mass index was significantly related to any brain measure or to these progressive changes.

The differential changes seen in our COS patients are not directly relevant to the issue of "triggers" for psychosis. Our patients had a mean age of onset of psychotic symptoms of 10.3 years (Table 1), while their mean age at first scan was 14 years. These data do, however, indirectly support models of schizophrenia postulating51,52 later abnormalities of brain development.

Finally, this study does not undermine the neurodevelopmental model of schizophrenia. In fact, the early developmental histories of our group show more striking impairments in language and motor development than reported for patients with adult-onset schizophrenia. However, it is already evident that genes known to influence prenatal brain development may also play a role in later maturation.53 These findings do indicate that etiologic models of schizophrenia, whether genetic or environmental, need to take into account both early and late neurodevelopmental events.

Accepted for publication March 30, 1999.

Reprints: Judith L. Rapoport, MD, Child Psychiatry Branch, National Institute of Mental Health, Bldg 10, Room 3N202, 10 Center Dr, MSC 1600, Bethesda, MD 20892-1600 (e-mail: rapoport@helix.nih.gov).

References
1.
Weinberger  DR Implications of normal brain development for the pathogenesis of schizophrenia.  Arch Gen Psychiatry. 1987;44660- 669Google ScholarCrossref
2.
Weinberger  D From neuropathology to neurodevelopment.  Lancet. 1995;346552- 557Google ScholarCrossref
3.
Murray  R Neurodevelopmental schizophrenia: the rediscovery of dementia praecox.  Br J Psychiatry. 1994;1656- 12Google Scholar
4.
Jones  PRodgers  BMurray  RMarmot  M Child developmental risk factors for adult schizophrenia in the British 1946 birth cohort.  Lancet. 1994;3441398- 1402Google ScholarCrossref
5.
Done  DCrow  TJohnstone  ESacker  A Childhood antecedents of schizophrenia and affective illness: social adjustment at ages 7 and 11.  BMJ. 1994;309699- 703Google ScholarCrossref
6.
Walker  ELewine  R Predictions of adult onset schizophrenia from childhood home movies of the parents.  Am J Psychiatry. 1990;1471052- 1056Google Scholar
7.
Mathalon  DHSullivan  EVLim  KOPfefferbaum  A Longitudinal analysis of MRI brain volumes in schizophrenia.  Schizophr Res. 1997;24152Google ScholarCrossref
8.
DeLisi  LETew  WXie  SHoff  ALSakuma  MKushner  MLee  GShadlock  KSmith  AMGrimson  R A prospective follow-up study of brain morphology and cognition in first-episode schizophrenic patients: preliminary findings.  Biol Psychiatry. 1995;38349- 360Google ScholarCrossref
9.
DeLisi  LESakuma  MTew  WKushner  MHoff  ALGrimson  R Schizophrenia as a chronic active brain process: a study of progressive brain structural change subsequent to the onset of schizophrenia.  Psychiatry Res. 1997;74129- 140Google ScholarCrossref
10.
DeLisi  LEStritzke  PRiordan  HHolan  VBoccio  AKushner  MMcClelland  JVan Eyl  OAnand  A The timing of brain morphological changes in schizophrenia and their relationship to clinical outcome.  Biol Psychiatry. 1992;31241- 254Google ScholarCrossref
11.
Nair  TRChristensen  JDKingsbury  SJKumar  NGTerry  WMGarver  DL Progression of cerebroventricular enlargement and the subtyping of schizophrenia.  Psychiatry Res. 1997;74141- 150Google ScholarCrossref
12.
Gur  RECowell  PTuretsky  BIGallacher  FCannon  TBilker  WGur  RC A follow-up magnetic resonance imaging study of schizophrenia: relationship of neuroanatomical changes to clinical and neurobehavioral measures.  Arch Gen Psychiatry. 1998;55145- 152Google ScholarCrossref
13.
Asarnow  J Annotation: childhood onset schizophrenia.  J Child Psychol Psychiatry. 1994;351345- 1371Google ScholarCrossref
14.
Asarnow  RBrown  WStrandburg  R Children with a schizophrenic disorder: neurobehavioral studies.  Eur Arch Psychiatry Clin Neurosci. 1995;24570- 79Google ScholarCrossref
15.
Frazier  JAGiedd  JNHamburger  SDAlbus  KEKaysen  DVaituzis  ACRajapakse  JCLenane  MCMcKenna  KJacobsen  LKGordon  CTBreier  ARapoport  J Brain anatomic magnetic resonance imaging in childhood-onset schizophrenia.  Arch Gen Psychiatry. 1996;53617- 624Google ScholarCrossref
16.
Jacobsen  LRapoport  J Childhood-onset schizophrenia: implications of clinical and neurobiological research.  J Child Psychol Psychiatry. 1998;39101- 113Google ScholarCrossref
17.
Alaghband-Rad  JMcKenna  KGordon  CAlbus  KHamburger  SRumsey  JLenane  MRapoport  J Childhood onset schizophrenia: the severity of premorbid course.  J Am Acad Child Adolesc Psychiatry. 1995;431273- 1283Google ScholarCrossref
18.
Kumra  SWiggs  EKrasnewich  DMeck  JSmith  ABedwell  JFernandez  TJacobsen  LRapoport  J Association of sex chromosome anomalies with childhood onset psychotic disorder.  J Am Acad Child Adolesc Psychiatry. 1998;37292- 296Google ScholarCrossref
19.
Nicolson  RRapoport  J Childhood-onset schizophrenia: what can it teach us? Rapoport  Jed Childhood Onset of Adult Psychopathology: Clinical and Research Advances. Washington, DC American Psychiatric Press Inc.In press.Google Scholar
20.
Rapoport  JLGiedd  JKumra  SJacobsen  LSmith  ALee  PNelson  JHamburger  S Childhood-onset schizophrenia: progressive ventricular change during adolescence.  Arch Gen Psychiatry. 1997;54897- 903Google ScholarCrossref
21.
Collins  DLNeelin  PPeters  TMEvans  AC Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space.  J Comput Assist Tomogr. 1994;18192- 205Google ScholarCrossref
22.
Collins  DLHolmes  CPeters  TMEvans  AC Automatic 3D segmentation of neuroanatomical structures from MRI.  Hum Brain Mapping. 1995;3190- 208Google ScholarCrossref
23.
Zijdenbos  AEvans  ARiahi  FSled  JChui  H-CKollokian  V Automatic quantification of multiple sclerosis lesion volume using stereotaxic space. Hohne  KHKikinis  Reds Proceedings of the Fourth International Conference on Visualization in Biomedical Computing (VBC). New York, NY Springer Publishing Co Inc1996;439- 448Google Scholar
24.
Evans  ACCollins  DLHolmes  CJ Automatic 3D regional MRI segmentation and statistical probability anatomy maps. Uemura  KJones  TLassen  NAKanno  Ieds Quantification of Brain FunctionTracer Kinetics and Image Analysis in Brain PET. New York, NY Excerpta Medica1995;123- 130Google Scholar
25.
Sled  JGZijdenbos  APEvans  AC A non-parametric method for automatic correction of intensity non-uniformity in MRI data.  IEEE Trans Med Imaging. 1998;1787- 97Google ScholarCrossref
26.
Gordon  CTFrazier  JAMcKenna  KGiedd  JZametkin  AZahn  THommer  DHong  WKaysen  DAlbus  KE Childhood-onset schizophrenia: an NIMH study in progress.  Schizophr Bull. 1994;20697- 712Google ScholarCrossref
27.
McKenna  KGordon  CTLenane  MKaysen  DFahey  KRapoport  J Looking for childhood onset schizophrenia: the first 71 cases screened.  J Am Acad Child Adolesc Psychiatry. 1994;33636- 644Google ScholarCrossref
28.
Kumra  SFrazier  JAJacobsen  LKMcKenna  KGordon  CTLenane  MCHamburger  SDSmith  AKAlbus  KEAlaghband-Rad  JRapoport  JL Childhood-onset schizophrenia: a double-blind clozapine-haloperidol comparison.  Arch Gen Psychiatry. 1996;531090- 1097Google ScholarCrossref
29.
Giedd  JNSnell  JWLange  NRajapakse  JCCasey  BJKozuch  PLVaituzis  ACVauss  YCHamburger  SDKaysen  DRapoport  JL Quantitative magnetic resonance imaging of human brain development: ages 4-18.  Cereb Cortex. 1996;6551- 560Google ScholarCrossref
30.
Hollingshead  AB Four Factor Index of Social Status.  >New Haven, Conn Yale University Department of Sociology1975;
31.
Collins  DLEvans  AC Animal: validation and applications of non-linear registration-based segmentation.  Int J Pattern Recognition Artif Intell. 1997;111271- 1294Google ScholarCrossref
32.
Zijdenbos  AForghani  REvans  AC Automatic quantification of MS lesions in 3D MRI brain data sets: validation of INSECT. Delp  SWells  WMColchester  Aeds Medical Image Computing and Computer-Assisted Intervention—MICCAI '98First International Conference, Cambridge, MA, USA, October 11-13, 1998, Proceedings. New York, NY Springer-Verlag NY Inc1998;439- 448Google Scholar
33.
Duvernoy  HM The Human Brain: Surface, Three-Dimensional Sectional Anatomy With MRI and Blood Supply.  New York, NY Springer-Verlag NY Inc1995;3- 15
34.
Pfefferbaum  AMathalon  DHSullivan  EVRawles  JMZipursky  RBKim  KO A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood.  Arch Neurol. 1994;51874- 887Google ScholarCrossref
35.
Reiss  AAbrams  MSinger  HRoss  JDenckla  M Brain development, gender, and IQ in children: a volumetric imaging study.  Brain. 1996;1191763- 1774Google ScholarCrossref
36.
Sowell  EThompson  PHolmes  CJernigan  TRBarth  RNaravan  SToga  A Statistical parametric mapping of structural brain changes between childhood and adolescence.  Presented as poster 123.4 at: 28th Annual Meeting of the Society for Neurosciences November 7-12, 1998 Los Angeles, Calif
37.
Sowell  EJernigan  T Further MRI evidence of late brain maturation: limbic volume increases and changing asymmetries during childhood and adolescence.  Dev Neuropsychol. In press.Google Scholar
38.
Benes  FTurtle  MKhan  YFarol  P Myelenization of a key relay zone in the hippocampal formation occurs in the human brain during childhood, adolescence, and adulthood.  Arch Gen Psychiatry. 1994;51477- 484Google ScholarCrossref
39.
Jernigan  TTallal  P Late childhood changes in brain morphology observable with MRI.  Dev Med Child Neurol. 1990;32379- 385Google ScholarCrossref
40.
Huttenlocher  PDeCourten  C The development of synapses in striate cortex of man.  Hum Neurobiol. 1987;61- 9Google Scholar
41.
Sauer  BKammradt  IKrauthausen  GKretchmann  HLange  HWingert  F Qualitative and quantitative development of the visual cortex in man.  J Comp Neurol. 1983;214441- 450Google ScholarCrossref
42.
Cannon  TDvan Erp  TGHuttunen  MLonnqvist  JSalonen  OValanne  LPoutanen  VPStandertskjold-Nordenstam  CGGur  REYan  M Regional gray matter, white matter, and cerebrospinal fluid distributions in schizophrenic patients, their siblings, and controls.  Arch Gen Psychiatry. 1998;551084- 1091Google ScholarCrossref
43.
Weinberger  DBerman  KSuddath  RTorrey  E Evidence of dysfunction of a prefrontal-limbic network in schizophrenia: a magnetic resonance imaging and regional cerebral blood flow study of discordant monozygotic twins.  Am J Psychiatry. 1992;149890- 897Google Scholar
44.
Selemon  LDRajkowska  GGoldman-Rakic  PS Abnormally high neuronal density in the schizophrenic cortex: a morphometric analysis of prefrontal area 9 and occipital area 17.  Arch Gen Psychiatry. 1995;52805- 818Google ScholarCrossref
45.
Rajkowska  GSelemon  LDGoldman-Rakic  PS Neuronal and glial somal size in the prefrontal cortex: a postmortem morphometric study of schizophrenia and Huntington disease.  Arch Gen Psychiatry. 1998;55215- 224Google ScholarCrossref
46.
Selemon  LDGoldman-Rakic  PS The reduced neuropil hypothesis: a circuit-based model of schizophrenia.  Biol Psychiatry. 1999;4517- 25Google ScholarCrossref
47.
Huttenlocher  PR Synaptic density in human frontal cortex—developmental changes and effects of aging.  Brain Res. 1979;163195Google ScholarCrossref
48.
Huttenlocher  PRDabholkar  AS Regional differences in synaptogenesis in human cerebral cortex.  J Comp Neurol. 1997;387167- 178Google ScholarCrossref
49.
Chugani  HPhelps  MMazziotta  JC Positron emission tomography study of human brain functional development.  Ann Neurol. 1987;22487- 497Google ScholarCrossref
50.
Giedd  JJeffries  NNicolson  RHamburger  SDNelson  JVaituzis  ACLenane  MRapoport  JL Differential progression of MRI ventricular and temporal lobe structure during adolescence for childhood onset schizophrenics.  Biol Psychiatry. In press.Google Scholar
51.
Feinberg  I Schizophrenia: caused by a fault in programmed synaptic elimination during adolescence?  J Psychiatr Res. 1982;17317- 334Google ScholarCrossref
52.
Feinberg  IThode  HC  JrChugani  HTMarch  JD Gamma distribution model describes maturational curves for delta wave amplitudes, cortical metabolic rate and synaptic density.  J Theor Biol. 1990;142149- 161Google ScholarCrossref
53.
Irwin  SASwain  RAChristion  FAChakravarti  AGalvez  RGreenough  WT Behavioral alleration of fragile X mental retardation protein expression.  Presented as poster 171.7 at: 28th Annual Meeting of the Society for Neurosciences November 7-12, 1998 Los Angeles, Calif
×