White Matter Microstructure in Early-Onset Schizophrenia: A Systematic Review of Diffusion Tensor Imaging Studies

White Matter Microstructure in Early-Onset Schizophrenia: A Systematic Review of Diffusion Tensor Imaging Studies

Accepted Manuscript White Matter Microstructure in Early-Onset Schizophrenia: A Systematic Review of Diffusion Tensor Imaging Studies Christian K. Tam...

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Accepted Manuscript White Matter Microstructure in Early-Onset Schizophrenia: A Systematic Review of Diffusion Tensor Imaging Studies Christian K. Tamnes, PhD, Ingrid Agartz, MD, PhD PII:

S0890-8567(16)00038-1

DOI:

10.1016/j.jaac.2016.01.004

Reference:

JAAC 1364

To appear in:

Journal of the American Academy of Child & Adolescent Psychiatry

Received Date: 19 August 2015 Revised Date:

16 December 2015

Accepted Date: 10 January 2016

Please cite this article as: Tamnes CK, Agartz I, White Matter Microstructure in Early-Onset Schizophrenia: A Systematic Review of Diffusion Tensor Imaging Studies, Journal of the American Academy of Child & Adolescent Psychiatry (2016), doi: 10.1016/j.jaac.2016.01.004. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT White Matter Microstructure in Early-Onset Schizophrenia: A Systematic Review of Diffusion Tensor Imaging Studies RH: White Matter Microstructure in EOS Christian K. Tamnes, PhD, Ingrid Agartz, MD, PhD

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Accepted January 20, 2016

Dr. Tamnes is with the Research Group for Lifespan Changes in Brain and Cognition,

University of Oslo, Norway. Dr. Agartz is with NORMENT (Norwegian Centre for Mental

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Disorders Research; http://www.med.uio.no/norment), KG Jebsen Centre for Psychosis

Research, Division of Mental Health and Addiction, Institute of Clinical Medicine, University

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of Oslo, Norway and with Diakonhjemmet Hospital, Oslo, Norway.

Dr. Tamnes is supported by the Research Council of Norway and the Department of Psychology at the University of Oslo. Dr. Agartz is supported by the Research Council of

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Norway, South-Eastern Norway Regional Health Authority, the Institute of Clinical Medicine at the University of Oslo, Diakonhjemmet Hospital, and the Swedish Research Council. Disclosure: Drs. Tamnes and Agartz report no biomedical financial interests or potential

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conflicts of interest.

Correspondence to Christian K. Tamnes, PhD, Department of Psychology, University of Oslo,

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PO Box 1094 Blindern, 0317 Oslo, Norway; e-mail: [email protected].

ACCEPTED MANUSCRIPT ABSTRACT Objective: Neurodevelopmental processes and neural connectivity are thought to play pivotal roles in schizophrenia. This article reviews diffusion tensor imaging (DTI) studies of brain white matter connections and microstructure and their development in patients with early-onset schizophrenia (EOS), i.e. schizophrenia with an age of onset before 18 years.

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Method: A systematic literature search revealed 21 original case-control DTI studies of children and/or adolescents with EOS.

Results: Nearly all studies report significantly lower regional fractional anisotropy (FA) in patients with EOS

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than in healthy control participants. However, the anatomical locations and extent of these differences are highly variable across studies. Further, consistent evidence for associations between DTI indices and age of onset, medication variables, and measures of symptomatology and cognition in EOS is lacking. Only three available

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studies have investigated cross-sectional age-related differences or longitudinal changes in DTI measures in adolescents with EOS. The results are mixed, with different studies indicating diverging, converging, or parallel developmental FA trajectories between patients and controls.

Conclusion: The study of brain structural connectivity, as inferred from DTI, and its development in EOS may inform us on the origin and ontogeny of schizophrenia. We suggest some directions for future research in this

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field and argue for increased focus on developmental questions. Specifically, further investigations of age of onset effects and multimethod longitudinal studies of structural and functional connectivity development prior to, at, and following onset of schizophrenia and related syndromes in children and adolescents are called for.

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INTRODUCTION

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Key words: brain development; diffusion tensor imaging; early-onset; schizophrenia; white matter

Various models of the ontogeny of schizophrenia are still debated, but one of the central perspectives

remains the neurodevelopmental model, which, broadly stated, posits that the syndrome involves abnormal neurodevelopmental processes caused by an interplay of genetic and early environmental events that is set in motion before the brain approaches its adult anatomical state and/or psychosis onset.1,2 Early-onset schizophrenia (EOS), defined as onset before age 18 years, occurs rarely. Psychoses have an estimated prevalence of 0.9 in 10,000 at age 13 years, showing a steady increase during adolescence, reaching a prevalence of 17.6 in 10,000 at age 18 years.3 Patients with childhood-onset in particular present with more severe symptoms and have worse prognosis than patients with adult-onset schizophrenia.4 However, patients

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ACCEPTED MANUSCRIPT with EOS and adult-onset schizophrenia share similar patterns of phenomenological, genetic, and cognitive abnormalities.5 The study of brain structure and function in children and adolescents with schizophrenia, and, critically, the development of these, may provide important clues for understanding the origin of this major mental disorder. Brain imaging in adult samples has delineated the neural systems involved in schizophrenia, including

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but not limited to prefrontal, medial temporal, and superior temporal regions.6-8 Studies of children and

adolescents with EOS overall implicate similar brain regions, although it is unknown whether the brain

abnormalities are more or less severe than those observed in adult-onset schizophrenia.9,10 Magnetic resonance imaging (MRI) studies of brain structure in children and adolescents with EOS also indicate altered

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developmental trajectories of gray matter volumes and regional cortical thickness.11-14 Importantly, the distributed nature of the implicated brain regions may suggest that neural connectivity plays a central role.

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The disconnection hypothesis of schizophrenia15,16 suggests that the some of the core symptoms relate to abnormal connectivity between multiple, spatially distributed brain regions.17-19 The hypothesis has been investigated in a substantial number of both functional and structural imaging studies at different stages of schizophrenia. Functional connectivity is currently typically measured using task or resting-state functional MRI (fMRI), while structural connectivity is often examined using diffusion tensor imaging (DTI), which is the focus

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of the current review. Briefly, the basis for DTI is the measurement of the diffusion, or random translational motion, of water molecules, and the technique indirectly characterizes tissue architecture at a micrometer scale (for more in-depth introductions to DTI and its biological basis, we refer the reader elsewhere20-23). When

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unconstrained, water diffusion is equal in all directions, i.e. isotropic, while in brain tissue it to varying degrees reflects interactions with tissue compartments such as cell membranes, fibers, or macromolecules, and may

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because of these restricting structures be directional or anisotropic. Commonly reported DTI measures include fractional anisotropy (FA), indexing degree of net directionality in water diffusion, and mean diffusivity (MD), reflecting overall magnitude of diffusion. Further, measures of diffusion along (axial diffusivity [AD]) and across (radial diffusivity [RD]) the primary diffusion direction can yield additional information relevant for characterizing white matter microstructure. Although the results are not always consistent, the general consensus appears to be that, across different stages of the disorder and methods, schizophrenia is associated with abnormalities in neuroimaging measures that could be interpreted as connectivity alterations relative to healthy controls.17 Specifically, DTI studies of patients with schizophrenia or related disorders have reported FA reductions in many different brain regions, most consistently in frontal and temporal white matter.8,24 Many

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ACCEPTED MANUSCRIPT questions do remain, however, including the precise anatomical networks involved, the degree of regional specificity, and the relationships to clinical and cognitive manifestations and functions, developmental course, and outcome of the abnormal network connectivity. The current review focuses on DTI studies of white matter microstructure and its development in EOS. First, as we cannot understand how development may go awry in EOS and other disorders without first

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understanding the processes of normal development, we give an overview of DTI studies of white matter

microstructure development in healthy children and adolescents. Second, a systematic review and critical

discussion of DTI studies comparing children and adolescents with EOS and healthy controls is presented.

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Third, studies investigating relations between DTI indices and clinical and cognitive measures in EOS are

reviewed. Fourth, studies investigating cross-sectional age-related differences or longitudinal changes in DTI measures of white matter microstructure in EOS are reviewed and discussed. Finally, some future directions for

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the field are suggested. METHOD

An online search of the Scopus database was conducted on October 28, 2015 using the keywords "schizophrenia" AND "early-onset" OR "childhood-onset" OR "adolescent-onset" AND "DTI" OR "diffusion," and revealed 36 documents. For this review, articles were included if they met the following criteria: 1) original

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research article, 2) used DTI, 3) included patients with early-onset (<18 years) schizophrenia spectrum disorders, 4) included a healthy control group, 5) performed case-control group comparisons of FA/MD/RD/AD, 6) were written in English. This left only 16 studies published in the period 2004-2015.

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Reference lists of the identified publications and relevant review articles were then searched for additional studies, and 5 articles published in the period 2007-2015 meeting the above-listed criteria were identified,

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yielding a total number of 21 articles for the current review. Precise details regarding sample overlap between studies could not consistently be identified. Studies or analyses investigating samples with an increased risk for developing schizophrenia, either

individuals with relatives diagnosed with schizophrenia25 or individuals showing specific symptoms or functional decline26 or studies investigating other DTI indices than FA/MD/RD/AD,27-29 were not included in the review. For reviews of DTI findings in early stages of schizophrenia, including both EOS and adult-onset schizophrenia, and in individuals characterized as genetic or clinical high-risk, we refer the reader elsewhere.30,31

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ACCEPTED MANUSCRIPT A separate section of the review is devoted to cross-sectional studies investigating age-related differences and longitudinal studies investigating change in DTI measures over time, as these studies may shed light on whether white matter microstructural abnormalities in children and adolescents with EOS are stable over time or show a dynamic evolution reflecting altered trajectories of brain development. Two of the above-

Normal Development of White Matter Microstructure

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identified studies32,33 and one additional study34 were included in this section of the review.

The delineation of normal brain developmental trajectories provides an invaluable and necessary template in order to be able to identify possible atypical patterns of brain development in EOS and other

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disorders.35 Beyond the very rapid changes seen in DTI indices in infancy,36 cross-sectional studies have

consistently documented age-related differences across children and adolescents in the form of FA increases and overall diffusivity decreases with increasing age in most white matter regions.37,38 Studies with very wide age

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ranges have further extended these findings, indicating non-monotonic lifespan age trajectories of FA, MD, and RD characterized by three phases: 1) initially fast but decelerating changes through childhood and adolescence and into young adulthood followed by 2) relative stability in mid-adulthood with subsequent 3) reversed and accelerating changes in senescence.39,40 Longitudinal developmental studies following the same individuals over time to measure within-person change are now also confirming widespread white matter FA increases and MD

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and RD decreases through childhood and adolescence, but the results for AD are less consistent.41-45 Importantly, the rates and timing of developmental DTI changes vary regionally in the brain. Studies have revealed a pattern of maturation in which major white matter tracts with fronto-temporal connections

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develop more slowly than other tracts.37,41 Of the major fiber bundles, the cingulum appear to be among those with the most prolonged development of FA.39 Crucially, individual- and age-related differences in DTI

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measures of white matter microstructure have also been linked to behavioral measures, documenting their functional consequences.46-48

Animal and post mortem human studies indicate that axonal membranes, density, and coherence, as

well as myelin sheaths, are the main factors that drive diffusion anisotropy.49 In tightly controlled model systems, modulating either axon fibers or myelin can be shown to have an impact at least somewhat specifically on specific DTI measures50, but these models do not necessarily generalize. It does, for instance, not logically follow from animal studies that age-related differences in RD in healthy humans reliably indicate differences in myelination.51 Developmental changes in DTI indices in white matter are mainly thought to relate to processes including increased relative axon caliber and myelin content, as well as changes in fiber packing density.52

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ACCEPTED MANUSCRIPT Additionally, other factors such as brain water content, crossing or diverging fibers, and partial volume effects may also contribute, and the relative roles of the various factors are likely also age-dependent.21,51 White Matter Microstructure in EOS Twenty-one DTI research articles on children and adolescents with EOS met the inclusion criteria for this systematic review (see Method). Key details of the samples and methods as well as the main results for the

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studies are summarized in Table 1. Based on the available information, the mean age of the patient samples ranged from 14 to 19 years.

The studies can be divided based on whether they performed whole-brain (voxel-based analysis [VBA]

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or tract-based spatial statistics [TBSS]) or local analyses (region-of-interest [ROI] or tractography). VBA

involves spatially normalizing scans to a standard space and performing voxel-by-voxel statistical tests but is now considered suboptimal in terms of inter-subject image alignment. TBSS improves on this by projecting all

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participants’ FA data onto an average FA tract skeleton before performing voxel-wise analyses within this skeleton. ROI analysis involves investigating selected manually or automatically predefined brain regions, while tractography algorithms automatically reconstruct selected major white matter tracts. Of the 21 studies included in our review, nine performed VBA, and three used TBSS. These studies report lower FA in patients with EOS than in control participants in a range of different brain regions, including:

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frontal white matter,53,54 parietal white matter,55,56 temporal white matter,53 corpus callosum,53,57-59 cingulum,33,53,60 superior longitudinal fasciculus,57-59 inferior longitudinal fasciculus,58,61 fronto-occipital fasciculus,58 cortico-spinal tract,57-59 anterior thalamic radiation,58 optic radiation,59 fornix,57 posterior

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hippocampus,62 and cerebellum.53,55 One of the studies found no significant group differences,63 and none report significant differences in the opposite direction, i.e. higher FA in the patient group.

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Of the 21 identified studies, five performed ROI analyses and four included tractography. With only one exception,64 all report significantly lower regional FA in patients with EOS than in control participants. Reported regions and fiber tracts of lower FA include: frontal white matter,65 occipital white matter,25,65 corpus callosum,66,67 inferior longitudinal fasciculus,32,61,68 inferior fronto-occipital fasciculus,32,68 cortico-spinal tract,32,68 and optic radiation.67,69 None of the studies report any significant group differences in the opposite direction. Notably, however, there are also negative findings for several of the regions/tracts identified in either whole-brain or other local analyses, including: frontal white matter,25 corpus callosum,61,65 cingulum,25,32,68 superior longitudinal fasciculus,32,68 fornix,64 and cerebellum.25,67,69

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ACCEPTED MANUSCRIPT Only three studies examined other common DTI indices than FA. Two VBA studies found that lower regional FA in patients with EOS was accompanied by higher MD62 or higher MD and RD,61 respectively, while an ROI study found no significant difference in MD (or FA) in fornix.64 Future investigations should include multiple DTI indices to provide a fuller picture of white matter microstructure in EOS. In sum, available results from the reviewed studies consistently show lower regional FA in young

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patients with EOS relative to healthy control participants. However, the findings demonstrate large variability and inconsistency with regard to the anatomical locations and regional specificity of the apparent white matter microstructure alterations in EOS (see also70,71). Possible sources of the discrepancies across studies can be

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broadly categorized as related to sample effects or the DTI raw data, processing, and/or analysis. Below, we briefly discuss selected potential reasons from each of these categories. First, a likely source of discrepancy is the generally small samples sizes. The mean number of patients in the reviewed articles was 25 (range = 12-55),

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and only two studies included more than 40 patients.68,72 This limits statistical power and can lead to failure to detect effects but might also produce results with false spatial specificity.73 Further, small sample sizes also increase the effects of, for example, sampling bias and likelihood of spurious findings.74 Second, differences in the results across studies may depend on differing sample characteristics such as age, symptoms/diagnoses, sex, race, medication, and age of onset of schizophrenia (see Table 1). Associations between DTI measures and age

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of onset, medication and symptomatology, and age-related differences and longitudinal change in DTI indices in EOS are reviewed below. Given the low prevalence of EOS, challenges related to participant recruitment and the considerable heterogeneity in the population, future multisite studies with coordinated study protocols are

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warranted. Third, differences in the image acquisition, such as image resolution and diffusion weighting, have been shown to impact FA values70 and might also affect the sensitivity to group differences. Fourth, often

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necessitated by the small sample sizes, many of the available studies restrict the analyses to measurements from a small number of ROIs or tracts, potentially failing to detect effects outside these locations. Based on the current limited knowledge, the decision of which regions to investigate is difficult. For instance, Moran et al.25 included ROIs based on regions previously shown to have smaller longitudinal white matter volume increases over time in adolescents with EOS than in healthy controls,75 but other studies show that white matter volume and DTI are relatively independent indices of white matter properties and are likely to yield complimentary information.37,39 Further, as the selected ROIs and tracts vary greatly, direct comparisons across studies are difficult. A dual approach of whole-brain analysis with adequate methods to deal with the known challenge of

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ACCEPTED MANUSCRIPT DTI registration, followed by anatomically validated tractography, may yield increased knowledge of the regional specificity and anatomical location of white matter microstructure alterations in EOS. The pathophysiology underlying brain structure abnormalities in schizophrenia in general and differences in FA between patients with EOS and healthy controls specifically is unknown and likely involves a number of processes.76 Post mortem studies looking at microscopic changes at the cellular level in patients with

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schizophrenia have identified several abnormalities.77 One hypothesis that is accumulating evidence suggests that neuroinflammation is an early mechanism of schizophrenia, and DTI is one of several currently used imaging methods that can indirectly detect neuroinflammation. However, it must be stressed that DTI

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parameters are sensitive to general diffusion properties of brain tissue and lack neurobiological specificity.78 Faced with a difference in FA between two groups, it is not possible to be sure which properties of the white matter underlie the difference without additional information.50 Inferences about the underlying tissue

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alterations of DTI differences between patients with EOS and healthy controls are thus challenging and should be done with great caution.

Associations With Clinical and Cognitive Variables

In order to move beyond descriptive case-control differences and get a better understanding of the mechanisms and consequences of abnormal white matter microstructure in EOS, it is important to relate the

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imaging measures to clinical and cognitive variables, as well as to genetic and early environmental factors and biological markers (e.g., inflammation, immune function). This is most often achieved by restricting the analysis to the patient group and correlating FA, typically in the region(s) showing lower FA in the patients compared to

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controls, with other variables of interest. Below, we review results concerning relationships between FA and age of onset, medication variables, and measures of symptomatology and cognition.

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Associations with age of onset: If the timing of when the underlying pathophysiology affects brain structure is systematically related to the age of onset of schizophrenia, albeit with a delay, we could expect that onset associated with periods of more rapid neurodevelopment would result in greater abnormalities. Generally, we would then expect younger age at onset to be related to lower FA values, but disease severity and regional developmental differences also have to be considered. Age of onset is not consistently reported in all the reviewed studies, but based on the available information, the sample mean ranges from 12 to 15 years of age (see Table 1). Future studies should more thoroughly report descriptive statistics, including range, on this and other important sample characteristics.

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ACCEPTED MANUSCRIPT Only three studies report on analyses testing associations between regional FA and age of onset,55,60,65 and none of them found significant relationships. However, investigating a group of adolescent-onset schizophrenia (n=17), a group of adult-onset schizophrenia (n=17), and matched control groups, Kyriakopoulos et al.56 found a significant diagnostic group by onset age group interaction effect on FA. The results indicate that medial frontal white matter microstructure was more affected in the adult group than in the adolescent group,

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which showed lower FA only in parietal white matter. Further studies are needed to confirm this and to test whether the differential pattern of FA reductions in EOS and adult-onset schizophrenia remains over time or whether the white matter abnormalities progress to include frontal regions as individuals move into late

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adolescence and adulthood.

Associations With Medication: Several of the available studies report on analyses investigating associations between FA and medication-related variables. Based on the available reported sample

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characteristics, on average 92% (range = 73-100) of the patients were receiving some type of antipsychotic medication (see Table 1). Four studies report no significant associations between regional FA and current medication dose,25,33,55,60 while three studies report no significant associations with estimated cumulative medication exposure.33,55,56 Antipsychotic medication has been related to regional gray matter volumes in adults with schizophrenia,79-81 but there is less documentation that antipsychotics affect DTI indices (but see82).

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Medication effects might not be present in young samples where patients have shorter medication histories. Alternatively, most DTI studies of EOS might be underpowered to detect subtle effects. In conclusion, there is currently no evidence from studies of patients with EOS that medication affects DTI indices of white matter

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microstructure, but putative effects of antipsychotic medication need to be addressed in future studies. Associations With Symptomatology: Several of the available studies performed analyses investigating

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associations between FA and measures of symptoms of psychosis. Ashtari et al.61 found that relative to patients without a history of visual hallucinations (n=14), patients with such a history (n=9) had lower FA in the left inferior longitudinal fasciculus, an association tract connecting the occipital and temporal lobe. Five other studies found no significant associations between regional FA and symptom scores based on the following rating scales: Positive and Negative Syndrome Scale (PANSS) scores,55,56,60 Scale for the Assessment of Positive Symptoms (SAPS) scores,25 Scale for the Assessment of Negative Symptoms (SANS) scores,25,65 Brief Psychiatric Rating Scale (BPRS) scores,65 and Global Assessment Scale (GAS)/Global Assessment of Functioning (GAF) scores.25,55 In sum, current evidence linking clinical ratings of symptoms of psychosis in EOS and regional FA is weak, with the large majority of studies finding no such associations.

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ACCEPTED MANUSCRIPT Associations With Cognition: Central cognitive dysfunctions in schizophrenia, such as impaired executive, memory, and social-cognitive functions,83,84 are also thought to partly arise from suboptimal communication between distributed brain regions within specific neural networks. In the so-far largest available DTI study of patients with EOS (n=55), Epstein et al.68 found that lower FA in the left inferior fronto-occipital and inferior longitudinal fasciculi were associated with worse performance on neuropsychological tests

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proposed to index various executive functions. None of the other reviewed studies of EOS analyzed associations between DTI indices and performance on behavioral tasks measuring specific cognitive functions. Development of White Matter Microstructure in EOS

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Given the central positions of the neurodevelopmental model and the disconnection hypothesis in the current understanding of schizophrenia, as well as the substantial normal developmental changes in DTI indices throughout adolescence, white matter microstructure development in young patients with EOS is of great

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interest. Such studies could potentially provide critical data for understanding the origin and ontogeny of schizophrenia. To date there are only two longitudinal DTI studies of EOS,32,34 and only one of the available cross-sectional studies investigates age-related differences.33 An overview and summary of these is presented in Table 2.

First, the cross-sectional results from Kumra et al.33 suggest divergent trajectories for white matter

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microstructure in individuals with EOS and healthy controls in a selected brain region. Specifically, they found a significant age by diagnostic group interaction effect on FA in the left anterior cingulum. While the control group (n=34) showed an expected increase in FA with age, the adolescents with schizophrenia (n=26) showed a

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decrease in FA with age. None of these main effects were significant, however, and the analysis was restricted to this region, which showed a significant group difference.

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Second, comparing 25 adolescent patients and 25 young adult patients with their corresponding agematched control groups, Douaud et al.34 found a significantly greater FA difference in the pyramidal tracts in the adolescent groups. In the first longitudinal DTI investigation of EOS, Douaud et al.34 then collected follow-up data from 12 adolescent patients and 12 controls from after an average of 2.5 years. The results showed multiple regions in which adolescent patients showed differences in longitudinal change in FA relative to the healthy controls. Within these regions the healthy controls showed little change in FA over time, while the patients generally showed FA increase. Together, the results were interpreted as a delayed maturation towards normal values, i.e. converging trajectories.

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ACCEPTED MANUSCRIPT Third, in a recently published longitudinal study including 34 adolescents with EOS and 29 healthy controls scanned at two time-points approximately 18 months apart, Epstein and Kumra32 found significantly lower FA in the patient group in the inferior longitudinal and inferior fronto-occipital fasciculi and the corticospinal tracts but no significant group differences in longitudinal change in FA in any of the tracts investigated. These results indicate parallel developmental trajectories of white matter microstructure in

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individuals with EOS and healthy controls.

In summary, while claims have been made for aberrant development of neural connectivity in EOS, the evidence from DTI studies of white matter microstructure to date remains inconclusive. The three available

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studies respectively indicate diverging, converging, and parallel developmental FA trajectories between patients with EOS and healthy controls and thus support very different conclusions regarding white matter microstructure development in EOS (Figure 1).

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Future Directions

Many of the available DTI studies of EOS share common limitations as discussed earlier in this review. Future studies should improve upon these weaknesses by reporting sample characteristics in more detail as well as sample overlap with earlier publications, studying larger patient samples, performing whole-brain analyses on multiple DTI indices, and testing for association with clinical and cognitive variables and other relevant

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variables that may affect brain white matter microstructure, e.g. genes, early trauma, substance use, or smoking. Selected additional directions for future research are discussed below. First, longitudinal studies of large samples that incorporate imaging data pre-, peri-, and post psychosis

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onset are needed to directly test current models of the development and lifetime course of brain structure in schizophrenia. Presently, there is a shortage of data that describe white matter microstructure development prior

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to the onset of schizophrenia.85 However, studies of individuals at high risk for developing psychosis provide initial evidence that white matter microstructure changes may precede and potentially predict outcomes related to the disorder,86-88 and these cohorts need to be followed beyond the transition phase or non-transition development. Methodological considerations for longitudinal studies of brain development are discussed elsewhere.51 One concern is scanner software upgrade or change of scanner, and if this is unavoidable, its effects should be quantified and analyzed. Second, like all data, DTI data requires quality control procedures to reduce noise and the likelihood of spurious findings. A potential great source of bias in DTI studies of EOS is head motion, which may relate to

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ACCEPTED MANUSCRIPT both age and diagnostic group. The field would benefit from an increased focus on head motion measurement, as well as increased use of motion compensation procedures.89 Third, multimethod imaging may give indirect evidence about the mechanisms and biological processes underlying brain structure abnormalities and development in EOS. It is unknown how white matter microstructure alterations in schizophrenia in general and in EOS specifically are related to gray matter

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abnormalities. Douaud et al.59 observed anatomically related lower gray matter volume and FA in specific

regions in patients with EOS, but longitudinal studies are needed to investigate the staging of the appearance of these aberrations. Similarly, links between structural connectivity alterations, as reflected by DTI, and functional

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connectivity alterations, as measured using, for example, fMRI, should be further investigated.90,91 Moreover, although DTI is most commonly used to investigate white matter, the technique can also be used to examine tissue properties in subcortical gray matter structures or the cerebral cortex, and other new techniques, such as

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T1-weighted/T2-weighted “myelin mapping,” could be employed to investigate intracortical intrinsic circuits.92,93 Graph theoretical analyses have also demonstrated a central role of brain hubs in schizophrenia.94,95 Structural connectivity can also be indirectly investigated by looking at morphometric covariance between different gray matter structures or regions.96,97 Patterns of structural covariance have been shown to be altered in individuals suffering from schizophrenia98 and to relate to symptom severity.99 Synchronized development

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between gray matter regions has been described for typically developing children and adolescents,100-102 but it is not known whether such coordinated patterns of change are altered in EOS. Finally, a recent study found high spatial overlap between a widespread network of mainly transmodal

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gray matter regions that develops late during adolescence and regions showing atypical development in EOS.103 This might indicate that the pattern of brain structure alterations in schizophrenia is influenced and to some

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extent determined by the timing of the pathological processes in relation to healthy brain development. Together with observations suggesting that white matter microstructure alterations in EOS may depend on age of onset56 and possibly evolve over time,33,34 these findings call for an increased focus on developmental perspectives and not simply examinations of case-control differences in future DTI studies of white matter microstructure in EOS. DTI studies of white matter microstructure consistently find lower regional FA in children and adolescents with EOS compared to healthy control participants. Substantial heterogeneity is observed across studies with respect to the anatomical locations and regional specificity of the findings. Further, evidence for associations between FA and age of onset, medication variables, and measures of symptomatology and

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ACCEPTED MANUSCRIPT cognition in EOS is lacking or weak. To date, there are only two longitudinal studies and one cross-sectional study investigating development of DTI indices of white matter microstructure in EOS. The findings are inconclusive, as these studies indicate diverging, converging, and parallel developmental FA trajectories, respectively, in adolescents with EOS compared to healthy controls. Developmental perspectives are important when thinking about the nature of brain changes in schizophrenia, and large multimethod longitudinal studies

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are needed to understand the timing, extent, lifespan development, biological meaning, and consequences of the white matter microstructure alterations. References

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Diagnosis

Mean Age (SD/range)

% Receiving Antipsychotic Medication na

Healthy Controls, n

Method

Main Results: Patients Compared to Controls

Ashtari et al. (2007)61

23

Davenport et al. (2010)57

15

18 sz/4 sza/1 szf 12 sz/2 sza/1 nos

15.8 (1.9/1118) 15.2 (2.4/1019)

21

12.5 (2.2)

na

26

VBA and tractography VBA

16.3 (1.4/1318)

14.9 (1.6/1117)

100

25

TBSS

43 sz/5 sza/7 szf

16.9 (1.7/1418)

13.3 (3.4)

85

Lower FA and higher MD/RD: left ILF Lower FA: CST, CC, right anterior corona radiata, right SLF, left fornix Lower FA: CST, superior thalamic radiation, left OR, left arcuate fasciculus, CC Lower FA: CST, left inferior FOF, left ILF

Douaud et al. (2007)59

25

25 sz

Epstein et al. (2014)68

55

Epstein and Kumra (2015)32

34

20 sz/4 sza/4 szf/7 nos

16.4 (1.9)

na

Freitag et al. (2013)67

12

na

na (14-18)

na

Henze et al. (2012)66

13

12 sz, 1 sza

Henze et al. (2014)69

13

12 sz, 1 sza

17.1 (0.5/1420) 17.1 (0.5/1420)

James et al. (2011)58

32

32 sz

na (13-18)

Ke et al. (2009)54

24

24 sz

Kendi et al. (2008)64

15

14 sz/1 sza

Kumra et al. (2004)65

12

12 sz

Kumra et al. (2005)33

26

17 sz/8 sza/1 szf

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Patients, n

Tractography

85/79

29

Tractography

Lower FA: ILF, inferior FOF, CST

100

13

ROI

Lower FA: CC, OR

na

100

13

ROI

na

100

13

Tractography

Lower FA: genu and body of CC Lower FA: OR

na

100

28

TBSS

15.8 (1.1/1418)

na

na

31

VBA

14.5 (2.6/819) 16.5 (1.8/1418)

na

73

15

ROI

13.0 (3.1)

100

9

ROI

na (6-17)

88

34

VBA

15.2 (2.2/1117)

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Study

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Mean Age at Onset (SD/range) 13.5 (8-17)

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Table 1. Diffusion Tensor Imaging Studies of Early-Onset Schizophrenia

Lower FA: SLF, ILF, FOF, CST, ATR, CC Lower FA: right medial frontal gyrus, right frontal deep WM ns differences in FA or MD Lower FA: frontal WM, right occipital WM Lower FA: left anterior CG

Comments

Tractography: ILF, anterior CC

Tractography: CG, CST, inferior FOF, ILF, SLF, UF Tractography: CG, CST, inferior FOF, ILF, SLF, UF ROIs: CC, OR, cerebellar penducles. Sample overlapping with 66 ROIs: 4 positions in CC Tractography: OR, middle cerebellar penducle. Sample overlapping with 66 Sample partly overlapping with 34,59

ROI: fornix ROIs: frontal WM, occipital WM, genu and splenium of CC

20

Kyriakopoulos et al. (2008)55

19

19 sz

17.1 (1.7/1319)

14.8 (2.3)

100

20

VBA

Kyriakopoulos et al. (2009)56 Moran et al. (2015)25

17

17 sz

14.8 (2.4)

88

17

VBA

39

na

16.6 (1.3/1319) 19.7 (5.7)

na (<13)

na

Sugranyes et al. (2012)53

25

25 sz

17.1 (1.5)

14.7 (1.5)

100

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Tang et al. (2010)60

38

31 sz/7 szf

16.3 (1.0)

15.5 (1.0)

79

White et al. (2007)62

15

14 sz/1 sza

15.2 (2.6)

12.9 (1.9)

White et al. (2009)63

29

22 sz/4 sza/3 szf

14.2 (3.4/819)

na

White et al. (2015)72

43

37 sz/6 szf

17.0 (1.8)

14.4 (1.6)

19

VBA

SC

ROI

38

VBA

na

15

VBA

na

41

TBSS and within-subject clusters

86

29

Within-subject clusters

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Lower FA: parietal WM, left cerebellar peduncle Lower FA: parietal WM Lower FA: cuneus WM

Lower FA: frontal WM, left CG, temporal WM, CC, cerebellum Lower FA: right anterior CG Lower FA and higher MD: left posterior hippocampus TBSS: ns Within-subject cluster: Greater number of cluster with low FA Within-subject clusters: Greater number of cluster with low FA

Sample partly overlapping with 55 ROIs: precuneus, cuneus, middle frontal gyrus, superior frontal gyrus, CG, right cerebellum

Sample partly overlapping with 54

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Note: AD = axial diffusivity; ATR = anterior thalamic radiation; CC = corpus callosum; CG = cingulum; CST = corticospinal tract; FA = Fractional anisotropy; FOF = frontooccipital fasciculus; ILF = inferior longitudinal fasciculus; MD = mean diffusivity; na = not available; nos = psychotic disorder not otherwise specified; ns = nonsignificant; OR = optic radiation; RD = radial diffusivity; ROI = region of interest; SLF = superior longitudinal fasciculus; sz = schizophrenia; sza = schizoaffective; szf = schizofreniform; TBSS = Tract-based spatial statistics; UF = uncinate fasciculus; VBA = voxel-based analysis.

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Table 2. Diffusion Tensor Imaging (DTI) Studies of White Matter Microstructure Development in Early-Onset Schizophrenia Patients n (diagnoses)

Mean age (SD/range)

Douaud et al. (2009)34

Longitudinal

12 (12 sz)

Epstein and Kumra (2015)32 Kumra et al. (2005)33

Longitudinal

34 (20 sz/4 sza/4 szf/7 nos) 26 (17 sz/8 sza/1szf)

Cross-sectional

Mean followup time (SD/range) 2.5 (0.5)

Healthy controls, n

16 (13-22)

Mean age at onset (SD/range) na

Method

Main results: Patients compared to controls

12

TBSS

1.4 (0.4)

29

Tractography

Different FA change rates: CST, SLF, brainstem, CC, cerebellar peduncles ns difference in FA change rates

16.4 (1.9)

na

15.2 (2.2/11-17)

na (6-17)

na

34

VBA

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Design

Different FA-age association: left anterior CG

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Study

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Note: CC = corpus callosum; CG = cingulum; CST = corticospinal tract; FA = fractional anisotropy; na = not available; nos = psychotic disorder not otherwise specified; ns = nonsignificant; SLF = superior longitudinal fasciculus; sz = schizophrenia; sza = schizoaffective; szf = schizofreniform; TBSS = tract-based spatial statistics; VBA = voxelbased analysis.

Figure legends

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Figure 1. Development of white matter microstructure in early-onset schizophrenia. Note: The results of the available studies are mixed, indicating diverging, converging, or parallel developmental fractional anisotropy (FA) trajectories between patients and controls, respectively. A) Cross-sectional individual mean FA (x 1000) in a left anterior cingulate region plotted against age for healthy volunteers (n=34) and patients with schizophrenia (n=26). B) Longitudinal individual change in mean FA across multiple regions in the white matter skeleton plotted against age for healthy controls (CON, n=12) in the top panel and patients with schizophrenia (PAT, n=12) in the bottom panel. C) Longitudinal group-level change in mean FA (x 1000) in the left inferior longitudinal fasciculus (ILF) tract across time points in healthy controls (HC, n=29), adolescents with cannabis use disorder (CUD, n=19), and patients with early-onset schizophrenia-spectrum disorders (EOSS, n=34). Reprinted from the Journal of the American Academy of Child and Adolescent Psychiatry, vol. 44, Kumra S, Ashtari M, Cervellione KL, et al., White matter abnormalities in early-onset schizophrenia: a voxel-based diffusion tensor imaging study, 934–941, copyright 2005, with permission from Elsevier; with permission from Brain (http://brain.oxfordjournals.org); and from Psychiatry Research: Neuroimaging, vol. 232, Epstein KA, Kumra S, White matter fractional anisotropy over two time points in early onset schizophrenia and adolescent cannabis use disorder: a naturalistic diffusion tensor imaging study, 34–41, copyright 2015, with permission from Elsevier.

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