Abstract
Purpose
Psychosis is a symptom common to several mental illnesses and a defining feature of schizophrenia spectrum disorders, whose onset typically occurs in adolescence. Neuroradiological studies have reported evidence of brain structural abnormalities in patients with overt psychosis. However, early identification of brain structural changes in young subjects at risk for developing psychosis (such as those with Attenuated Psychosis Syndrome –APS) is currently lacking.
Methods
Brain 3D T1-weighted and 64 directions diffusion-weighted images were acquired on 55 help-seeking adolescents (12–17 years old) with psychiatric disorders who referred to our Institute. Patients were divided into three groups: non-APS (n = 20), APS (n = 20), and Early-Onset Psychosis (n = 15). Cortical thickness was calculated from T1w images, and Tract-Based Spatial Statistics analysis was performed to study the distribution of white matter fractional anisotropy and all diffusivity metrics. A thorough neuropsychological test battery was adopted to investigate cognitive performance in several domains.
Results
In patients with Attenuated Psychotic Syndrome, the left superior frontal gyrus was significantly thinner compared to patients with non-APS (p = 0.048), and their right medial orbitofrontal cortex thickness was associated with lower working memory scores (p = 0.0025, r = -0.668 for the working memory index and p = 0.001, r = -0.738 for the digit span). Early-Onset Psychosis patients showed thinner left pars triangularis compared to non-APS individuals (p = 0.024), and their left pars orbitalis was associated with impaired performance at the symbol search test (p = 0.005, r = -0.726). No differences in diffusivity along main tracts were found between sub-groups (p > 0.05).
Conclusion
This study showed specific associations between structural imaging features and cognitive performance in patients with APS. Characterizing this disorder using neuroimaging could reveal useful information that may aid in the development and evaluation of preventive strategies in these individuals.
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Data availability
The data that support the findings of this study are available from the corresponding author upon request (https://doi.org/10.5281/zenodo.6563681).
Abbreviations
- AD:
-
Axial Diffusivity
- APS:
-
Attenuated Psychosis Syndrome
- BLIPS:
-
Brief Limited Intermittent Psychotic Symptoms
- CAARMS:
-
Comprehensive Assessment of At-Risk Mental State
- CC:
-
Core-Coding
- CHR-P:
-
Clinical High-Risk state for Psychosis
- CGI-S:
-
Clinical Global Impression-Severity
- CT:
-
Cortical Thickness
- DS:
-
Digit Span
- DSM-5:
-
Diagnostic and Statistical Manual of mental disorders, Fifth edition
- DTI:
-
Diffusion Tensor Imaging
- DUP:
-
Duration of Untreated Psychosis
- EOP:
-
Early-Onset Psychosis
- FA:
-
Fractional Anisotropy
- FMRIB:
-
Functional Magnetic Resonance Imaging of the Brain
- FSL:
-
FMRIB Software Library
- GRD:
-
Genetic Risk and Deterioration syndrome
- HARDI:
-
High Angular Resolution Diffusion-weighted Imaging
- IQ:
-
Intelligence Quotient
- K-SADS-PL:
-
Kiddie Schedule for Affective Disorders and Schizophrenia – Present and Lifetime version
- LN:
-
Letter-Number sequencing
- MD:
-
Mean Diffusivity
- MNI:
-
Montreal Neurological Institute
- MRI:
-
Magnetic Resonance Imaging
- non-APS:
-
Non-Attenuated Psychotic Syndrome
- PS:
-
Processing Speed
- RD:
-
Radial Diffusivity
- SCID-5-PD:
-
Structured Clinical Interview for DSM-5 Personality Disorders
- sd:
-
standard deviation
- SE-EPI:
-
Spin-Echo EchoplanarImaging
- SES:
-
Socio-Economical Status
- SOFAS:
-
Social and Occupational Functioning Assessment Scale
- SS:
-
Symbol Search
- TBSS:
-
Tract-Based Spatial Statistics
- TFCE:
-
Threshold Free Cluster Enhancement
- WAIS:
-
Wechsler Adult Intelligence Scale
- WISC:
-
Wechsler Intelligence Scale for Children
- WM:
-
Working Memory
References
Arciniegas DB (2015) Psychosis. Continuum (Minneap Minn) 21:715–736. https://doi.org/10.1212/01.con.0000466662.89908.e7
American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. American Psychiatric Association, Washington, DC
Radua J, Ramella-Cravaro V, Ioannidis JPA, Reichenberg A, Phiphopthatsanee N, Amir T et al (2018) What causes psychosis? An umbrella review of risk and protective factors. World Psychiatry 17:49–66. https://doi.org/10.1002/wps.20490
Kahn RS, Sommer IE, Murray RM, Meyer-Lindenberg A, Weinberger DR, Cannon TD et al (2015) Schizophrenia. Nat Rev Dis Primers 1:15067. https://doi.org/10.1038/nrdp.2015.67
Salazar de Pablo G, Estradé A, Cutroni M, Andlauer O, Fusar-Poli P (2021) Establishing a clinical service to prevent psychosis: what, how and when? Systematic review. Transl Psychiatry 11:43. https://doi.org/10.1038/s41398-020-01165-x
Fusar-Poli P, Sullivan SA, Shah JL, Uhlhaas PJ (2019) Improving the detection of individuals at clinical risk for psychosis in the community, primary and secondary care: an integrated evidence-based approach. Front Psychiatry 10:774. https://doi.org/10.3389/fpsyt.2019.00774
Mensi MM, Molteni S, Iorio M, Filosi E, Ballante E, Balottin U et al (2021) Prognostic accuracy of DSM-5 attenuated psychosis syndrome in adolescents: prospective real-world 5-year cohort study. Schizophr Bull 47:1663–1673. https://doi.org/10.1093/schbul/sbab041
Addington J, Farris M, Devoe D, Metzak P (2020) Progression from being at-risk to psychosis: next steps. NPJ Schizophr 6:27. https://doi.org/10.1038/s41537-020-00117-0
Shakeel MK, MacQueen G, Addington J, Metzak PD, Georgopoulos G, Bray S et al (2020) White matter connectivity in youth at risk for serious mental illness: a longitudinal analysis. Psychiatry Res Neuroimaging 302:111106. https://doi.org/10.1016/j.pscychresns.2020.111106
Catalan A, Salazar de Pablo G, Vaquerizo Serrano J, Mosillo P, Baldwin H, Fernández-Rivas A et al (2021) Annual research review: prevention of psychosis in adolescents - systematic review and meta-analysis of advances in detection, prognosis and intervention. J Child Psychol Psychiatry 62:657–673. https://doi.org/10.1111/jcpp.13322
Jung WH, Kim JS, Jang JH, Choi J-S, Jung MH, Park J-Y et al (2011) Cortical thickness reduction in individuals at ultra-high-risk for psychosis. Schizophr Bull 37:839–849. https://doi.org/10.1093/schbul/sbp151
Buechler R, Wotruba D, Michels L, Theodoridou A, Metzler S, Walitza S et al (2020) Cortical volume differences in subjects at risk for psychosis are driven by surface area. Schizophr Bull 46:1511–1519. https://doi.org/10.1093/schbul/sbaa066
Klauser P, Zhou J, Lim JKW, Poh JS, Zheng H, Tng HY, Krishnan R et al (2015) Lack of evidence for regional brain volume or cortical thickness abnormalities in youths at clinical high risk for psychosis: findings from the longitudinal youth at risk study. Schizophr Bull 41:1285–1293. https://doi.org/10.1093/schbul/sbv012
Ziermans TB, Durston S, Sprong M, Nederveen H, van Haren NEM, Schnack HG et al (2009) No evidence for structural brain changes in young adolescents at ultra high risk for psychosis. Schizophr Res 112:1–6. https://doi.org/10.1016/j.schres.2009.04.013
von Hohenberg CC, Pasternak O, Kubicki M, Ballinger T, Vu M-A, Swisher T, Green K et al (2014) White matter microstructure in individuals at clinical high risk of psychosis: a whole-brain diffusion tensor imaging study. Schizophr Bull 40:895–903. https://doi.org/10.1093/schbul/sbt079
Mittal VA, Dean DJ, Bernard JA, Orr JM, Pelletier-Baldelli A, Carol EE et al (2014) Neurological soft signs predict abnormal cerebellar-thalamic tract development and negative symptoms in adolescents at high risk for psychosis: a longitudinal perspective. Schizophr Bull 40:1204–1215. https://doi.org/10.1093/schbul/sbt199
Fannon D, Chitnis X, Doku V, Tennakoon L, O’Ceallaigh S, Soni W et al (2000) Features of structural brain abnormality detected in first-episode psychosis. Am J Psychiatry 157:1829–1834. https://doi.org/10.1176/appi.ajp.157.11.1829
Saito J, Hori M, Nemoto T, Katagiri N, Shimoji K, Ito S et al (2017) Longitudinal study examining abnormal white matter integrity using a tract-specific analysis in individuals with a high risk for psychosis. Psychiatry Clin Neurosci 71:530–541. https://doi.org/10.1111/pcn.12515
Niznikiewicz MA (2019) Neurobiological approaches to the study of clinical and genetic high risk for developing psychosis. Psychiatry Res 277:17–22. https://doi.org/10.1016/j.psychres.2019.02.009
Zipursky RB, Reilly TJ, Murray RM (2013) The myth of schizophrenia as a progressive brain disease. Schizophr Bull 39:1363–1372. https://doi.org/10.1093/schbul/sbs135
Hartberg CB, Sundet K, Rimol LM, Haukvik UK, Lange EH, Nesvåg R et al (2011) Brain cortical thickness and surface area correlates of neurocognitive performance in patients with schizophrenia, bipolar disorder, and healthy adults. J Int Neuropsychol Soc 17:1080–1093. https://doi.org/10.1017/s1355617711001081
Molteni S, Filosi E, Mensi MM, Spada G, Zandrini C, Ferro F et al (2019) Predictors of outcomes in adolescents with clinical high risk for psychosis, other psychiatric symptoms, and psychosis: a longitudinal protocol study. Front Psychiatry 10:787. https://doi.org/10.3389/fpsyt.2019.00787
Kaufman J, Birmaher B, Axelson D, Perepletchikova F, Brent D, Ryan N (2016) Schedule for affective disorders and schizophrenia for school aged children (6-18 years): Kiddie-SADS - Lifetime version (K-SADS-PL DSM-5). In: Advanced Center for Intervention and Services Research (ACISR) for Early Onset Mood and Anxiety Disorders Western Psychiatric Institute and Clinic; Child and Adolescent Research and Education (CARE) Program. Yale University
Kaufman J, Birmaher B, Rao U, Ryan N (2019) K-SADS-PL DSM-5. Intervista diagnostica per la valutazione dei disturbi psicopatologici in bambini e adolescenti. Ed. Centro Studi Erickson, Trento
First MB, Williams JBW, Benjamin LS, Spitzer RL (2015) Structured clinical interview for DSM-5 personality disorders SCID-5-PD. American Psychiatric Association, Arlington
First MB, Williams JBW, Smith Benjamin L, Spitzer RL (2017) SCID-5-PD: Intervista clinica strutturata per i disturbi di personalità del DSM-5. Raffaello Cortina Editore, Milano
Fusar-Poli P, Hobson R, Raduelli M, Balottin U (2012) Reliability and validity of the Comprehensive Assessment of the At Risk Mental State, Italian version (CAARMS-I). Curr Pharm Des 18:386–391. https://doi.org/10.2174/138161212799316118
Yung AR, Yuen HP, McGorry PD, Phillips LJ, Kelly D, Dell’Olio M et al (2005) Mapping the onset of psychosis: the comprehensive assessment of at-risk mental states. Aust N Z J Psychiatry 39:964–971. https://doi.org/10.1080/j.1440-1614.2005.01714.x
Hollingshead AB (1975) Four factor index of social status. Yale Journal of Sociology, vol. 8, 2011, New Haven, pp 21–51. https://sociology.yale.edu/sites/default/files/files/yjs_fall_2011.pdf
Bradley RH, Corwyn RF (2002) Socioeconomic status and child development. Annu Rev Psychol 53:371–399. https://doi.org/10.1146/annurev.psych.53.100901.135233
Guy W (1976) ECDEU assessment manual for psychopharmacology. U.S. Dept. of Health, Education, and Welfare, Public Health Service, Alcohol, Drug Abuse, and Mental Health Administration, National Institute of Mental Health, Psychopharmacology Research Branch, Division of Extramural Research Programs. Rockville, MD
Wechsler D (2012) WISC-IV Wechsler Intelligence Scale for children IV ed. In: Nuovo modello teorico, nuovi subtest, nuovi punteggi, nuove norme: il perfezionamento dell’eccellenza. Giunti Psychometrics
Wechsler D (1997) Wechsler adult intelligence scale - revised. Giunti Psychometrics
Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31:968–980. https://doi.org/10.1016/j.neuroimage.2006.01.021
Fusar-Poli P, Radua J, McGuire P, Borgwardt S (2012) Neuroanatomical maps of psychosis onset: voxel-wise meta-analysis of antipsychotic-naÏve VBM studies. Schizophr Bull 38(6):1297–1307. https://doi.org/10.1093/schbul/sbr134
Cannon TD, Chung Y, He G, Sun D, Jacobson A, van Erp TGM et al (2015) Progressive reduction in cortical thickness as psychosis develops: a multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biol Psychiatry 77:147–157. https://doi.org/10.1016/j.biopsych.2014.05.023
Smith SM (2002) Fast robust automated brain extraction. Hum Brain Mapp 17:143–155. https://doi.org/10.1002/hbm.10062
Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TEJ, Johansen-Berg H et al (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23(Suppl 1):S208–S219. https://doi.org/10.1016/j.neuroimage.2004.07.051
R core team (2021) R: A language and environment for statistical computing. R Found Stat Comput, Vienna, Austria. https://www.r-project.org. Accessed 10 Jun 2022
Janssen J, Reig S, Alemán Y, Schnack H, Udias JM, Parellada M et al (2009) Gyral and sulcal cortical thinning in adolescents with first episode early-onset psychosis. Biol Psychiatry 66:1047–1054. https://doi.org/10.1016/j.biopsych.2009.07.021
Iwashiro N, Suga M, Takano Y, Inoue H, Natsubori T, Satomura Y et al (2012) Localized gray matter volume reductions in the pars triangularis of the inferior frontal gyrus in individuals at clinical high-risk for psychosis and first episode for schizophrenia. Schizophr Res 137:124–131. https://doi.org/10.1016/j.schres.2012.02.024
Zhu Y, Nakatani H, Yassin W, Maikusa N, Okada N, Kunimatsu A et al (2022) Application of a machine learning algorithm for structural brain images in chronic schizophrenia to earlier clinical stages of psychosis and autism spectrum disorder: a multiprotocol imaging dataset study. Schizophr Bull 48:563–574. https://doi.org/10.1093/schbul/sbac030
Del Re EC, Stone WS, Bouix S, Seitz J, Zeng V, Guliano A et al (2021) Baseline cortical thickness reductions in clinical high risk for psychosis: brain regions associated with conversion to psychosis versus non-conversion as assessed at one-year follow-up in the Shanghai-At-Risk-for-Psychosis (SHARP) study. Schizophr Bull 47:562–574. https://doi.org/10.1093/schbul/sbaa127
Yasuda Y, Okada N, Nemoto K, Fukunaga M, Yamamori H, Ohi K et al (2020) Brain morphological and functional features in cognitive subgroups of schizophrenia. Psychiatry Clin Neurosci 74:191–203. https://doi.org/10.1111/pcn.12963
Ding Y, Ou Y, Pan P, Shan X, Chen J, Liu F et al (2019) Brain structural abnormalities as potential markers for detecting individuals with ultra-high risk for psychosis: a systematic review and meta-analysis. Schizophr Res 209:22–31. https://doi.org/10.1016/j.schres.2019.05.015
Dukart J, Smieskova R, Harrisberger F, Lenz C, Schmidt A, Walter A et al (2017) Age-related brain structural alterations as an intermediate phenotype of psychosis. J Psychiatry Neurosci 42:307–319. https://doi.org/10.1503/jpn.160179
Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H et al (2007) Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 27:2349–2356. https://doi.org/10.1523/jneurosci.5587-06.2007
Guo S, Palaniyappan L, Liddle PF, Feng J (2016) Dynamic cerebral reorganization in the pathophysiology of schizophrenia: a MRI-derived cortical thickness study. Psychol Med 46:2201–2214. https://doi.org/10.1017/s0033291716000994
Palaniyappan L, Das T, Dempster K (2017) The neurobiology of transition to psychosis: clearing the cache. J Psychiatry Neurosci 42:294–299. https://doi.org/10.1503/jpn.170137
Borgwardt SJ, McGuire PK, Aston J, Gschwandtner U, Pflüger MO, Stieglitz R-D et al (2008) Reductions in frontal, temporal and parietal volume associated with the onset of psychosis. Schizophr Res 106:108–114. https://doi.org/10.1016/j.schres.2008.08.007
Smigielski L, Stämpfli P, Wotruba D, Buechler R, Sommer S, Gerstenberg M et al (2022) White matter microstructure and the clinical risk for psychosis: a diffusion tensor imaging study of individuals with basic symptoms and at ultra-high risk. NeuroImage Clin 35:103067. https://doi.org/10.1016/j.nicl.2022.103067
Kristensen TD, Glenthøj LB, Ragahava JM, Syeda W, Mandl RCW, Wenneberg C et al (2021) Changes in negative symptoms are linked to white matter changes in superior longitudinal fasciculus in individuals at ultra-high risk for psychosis. Schizophr Res 237:192–201. https://doi.org/10.1016/j.schres.2021.09.014
Hoptman MJ, Nierenberg J, Bertisch HC, Catalano D, Ardekani BA, Branch CA, Delisi LE (2008) A DTI study of white matter microstructure in individuals at high genetic risk for schizophrenia. Schizophr Res 106:115–124. https://doi.org/10.1016/j.schres.2008.07.023
DeLisi LE, Szulc KU, Bertisch H, Majcher M, Brown K, Bappal A et al (2006) Early detection of schizophrenia by diffusion weighted imaging. Psychiatry Res 148:61–66. https://doi.org/10.1016/j.pscychresns.2006.04.010
Carletti F, Woolley JB, Bhattacharyya S, Perez-Iglesias R, Fusar Poli P, Valmaggia L et al (2012) Alterations in white matter evident before the onset of psychosis. Schizophr Bull 38:1170–1179. https://doi.org/10.1093/schbul/sbs053
Kelly S, Jahanshad N, Zalesky A, Kochunov P, Agartz I, Alloza C et al (2018) Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group. Mol Psychiatry 23:1261–1269. https://doi.org/10.1038/mp.2017.170
Drakesmith M, Dutt A, Fonville L, Zammit S, Reichenberg A, Evans CJ et al (2016) Volumetric, relaxometric and diffusometric correlates of psychotic experiences in a non-clinical sample of young adults. NeuroImage Clin 12:550–558. https://doi.org/10.1016/j.nicl.2016.09.002
Peters BD, Karlsgodt KH (2015) White matter development in the early stages of psychosis. Schizophr Res 161:61–69. https://doi.org/10.1016/j.schres.2014.05.021
Sato J, Vandewouw MM, Bando N, Branson HM, O’Connor DL, Unger SL, Taylor MJ (2021) White matter alterations and cognitive outcomes in children born very low birth weight. Neuroimage Clin 32:102843. https://doi.org/10.1016/j.nicl.2021.102843
Darki F, Klingberg T (2015) The role of fronto-parietal and fronto-striatal networks in the development of working memory: a longitudinal study. Cereb Cortex 25:1587–1595. https://doi.org/10.1093/cercor/bht352
Borghesani PR, Madhyastha TM, Aylward EH, Reiter MA, Swarny BR, Schaie KW, Willis SL (2013) The association between higher order abilities, processing speed, and age are variably mediated by white matter integrity during typical aging. Neuropsychologia 51:1435–1444. https://doi.org/10.1016/j.neuropsychologia.2013.03.005
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We thank the patients and their families for their collaboration.
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We thank the Italian Ministry of Health for the financial support by RC 2017–2019 and 2020–2021.
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Conception and study design: Martina Maria Mensi, Umberto Balottin, Renato Borgatti and Anna Pichiecchio; data collection or acquisition: Laura Mazzocchi, Arianna Vecchio, Alexandra Paredes and Matteo Paoletti; statistical analysis: Laura Mazzocchi and Elena Ballante; interpretation of results: Luca Melazzini, Laura Mazzocchi, Arianna Vecchio, Alexandra Paredes, Martina Maria Mensi, Elena Ballante, Matteo Paoletti and Anna Pichiecchio; original draft preparation, review and editing: Luca Melazzini, Laura Mazzocchi, Arianna Vecchio, Alexandra Paredes, Matteo Paoletti, Renato Borgatti and Anna Pichiecchio. All authors read and approved the final version of the manuscript and agree to be accountable for the integrity and accuracy of all aspects of the work.
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Melazzini, L., Mazzocchi, L., Vecchio, A. et al. Magnetic resonance advanced imaging analysis in adolescents: cortical thickness study to identify attenuated psychosis syndrome. Neuroradiology 65, 1447–1458 (2023). https://doi.org/10.1007/s00234-023-03200-2
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DOI: https://doi.org/10.1007/s00234-023-03200-2