Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
BMC Psychiatry
Published in: BMC Psychiatry 1/2024

Open Access 01-12-2024 | Schizophrenia | Research

Fronto-temporal cortical grey matter thickness and surface area in the at-risk mental state and recent-onset schizophrenia: a magnetic resonance imaging study

Authors: Paul E. Rasser, Tim Ehlkes, Ulrich Schall

Published in: BMC Psychiatry | Issue 1/2024

Login to get access

Abstract

Background

Studies to date examining cortical thickness and surface area in young individuals At Risk Mental State (ARMS) of developing psychosis have revealed inconsistent findings, either reporting increased, decreased or no differences compared to mentally healthy individuals. The inconsistencies may be attributed to small sample sizes, varying age ranges, different ARMS identification criteria, lack of control for recreational substance use and antipsychotic pharmacotherapy, as well as different methods for deriving morphological brain measures.

Methods

A surfaced-based approach was employed to calculate fronto-temporal cortical grey matter thickness and surface area derived from magnetic resonance imaging (MRI) data collected from 44 young antipsychotic-naïve ARMS individuals, 19 young people with recent onset schizophrenia, and 36 age-matched healthy volunteers. We conducted group comparisons of the morphological measures and explored their association with symptom severity, global and socio-occupational function levels, and the degree of alcohol and cannabis use in the ARMS group.

Results

Grey matter thickness and surface areas in ARMS individuals did not significantly differ from their age-matched healthy counterparts. However, reduced left-frontal grey matter thickness was correlated with greater symptom severity and lower function levels; the latter being also correlated with smaller left-frontal surface areas. ARMS individuals with more severe symptoms showed greater similarities to the recent onset schizophrenia group. The morphological measures in ARMS did not correlate with the lifetime level of alcohol or cannabis use.

Conclusions

Our findings suggest that a decline in function levels and worsening mental state are associated with morphological changes in the left frontal cortex in ARMS but to a lesser extent than those seen in recent onset schizophrenia. Alcohol and cannabis use did not confound these findings. However, the cross-sectional nature of our study limits our ability to draw conclusions about the potential progressive nature of these morphological changes in ARMS.
Literature
1.
Borgwardt SJ, Riecher-Rössler A, Dazzan P, Chitnis X, Aston J, Drewe M, et al. Regional gray matter volume abnormalities in the at risk mental state. Biol Psychiatry. 2007;61:1148–56.PubMedCrossRef
2.
Pantelis C, Velakoulis D, McGorry PD, Wood SJ, Suckling J, Phillips LJ, et al. Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison. Lancet. 2003;361:281–8.PubMedCrossRef
3.
Ding Y, Ou Y, Pan P, Shan X, Chen J, Liu F, et al. Brain structural abnormalities as potential markers for detecting individuals with ultra-high risk for psychosis: a systematic review and meta-analysis. Schizophr Res. 2019;209:22–31.PubMedCrossRef
4.
Luna LP, Radua J, Fortea L, Sugranyes G, Fortea A, Fusar-Poli P, et al. A systematic review and meta-analysis of structural and functional brain alterations in individuals with genetic and clinical high-risk for psychosis and bipolar disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2022;117:110540.PubMedCrossRef
5.
Benetti S, Pettersson-Yeo W, Hutton C, Catani M, Williams SC, Allen P, et al. Elucidating neuroanatomical alterations in the at risk mental state and first episode psychosis: a combined voxel-based morphometry and voxel-based cortical thickness study. Schizophr Res. 2013;150:505–11.PubMedPubMedCentralCrossRef
6.
Chung Y, Allswede D, Addington J, Bearden CE, Cadenhead K, Cornblatt B, et al. Cortical abnormalities in youth at clinical high-risk for psychosis: findings from the NAPLS2 cohort. NeuroImage Clin. 2019;23:101862.PubMedPubMedCentralCrossRef
7.
Gisselgård J, Lebedev AV, Dæhli Kurz K, Joa I, Johannessen JO, Brønnick K. Structural and functional alterations in the brain during working memory in medication-naïve patients at clinical high-risk for psychosis. PLoS One. 2018;13:e0196289.PubMedPubMedCentralCrossRef
8.
Jung WH, Kim JS, Jang JH, Choi J-S, Jung MH, Park J-Y, et al. Cortical thickness reduction in individuals at ultra-high-risk for psychosis. Schizophr Bull. 2011;37:839–49.PubMedCrossRef
9.
Kwak YB, Kim M, Cho KIK, Lee J, Lee TY, Kwon JS. Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes. Aust N Z J Psychiatry. 2019;53:219–27.PubMedCrossRef
10.
Tognin S, Riecher-Rössler A, Meisenzahl EM, Wood SJ, Hutton C, Borgwardt SJ, et al. Reduced parahippocampal cortical thickness in subjects at ultra-high risk for psychosis. Psychol Med. 2014;44:489–98.PubMedCrossRef
11.
Tomyshev AS, Lebedeva IS, Akhadov TA, Omelchenko MA, Rumyantsev AO, Kaleda VG. Alterations in white matter microstructure and cortical thickness in individuals at ultra-high risk of psychosis: a multimodal tractography and surface-based morphometry study. Psychiatry Res Neuroimaging. 2019;289:26–36.PubMedCrossRef
12.
Dukart J, Smieskova R, Harrisberger F, Lenz C, Schmidt A, Walter A, et al. Age-related brain structural alterations as an intermediate phenotype of psychosis. J Psychiatry Neurosci. 2017;42:307–19.PubMedPubMedCentralCrossRef
13.
Bakker G, Caan MWA, Vingerhoets WAM, da Silva- Alves F, de Koning M, Boot E, et al. Cortical morphology differences in subjects at increased vulnerability for developing a psychotic disorder: a comparison between subjects with ultra-high risk and 22q11.2 deletion syndrome. PLoS One. 2016;11:e0159928.PubMedPubMedCentralCrossRef
14.
Cannon TD, Chung Y, He G, Sun D, Jacobson A, van Erp TGM, et al. Progressive reduction in cortical thickness as psychosis develops: a multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biol Psychiatry. 2015;77:147–57.PubMedCrossRef
15.
Haller S, Borgwardt SJ, Schindler C, Aston J, Radue EW, Riecher-Rössler A. Can cortical thickness asymmetry analysis contribute to detection of at-risk mental state and first-episode psychosis?: A pilot study. Radiology. 2009;250:212–21.PubMedCrossRef
16.
Klauser P, Zhou J, Lim JKW, Poh JS, Zheng H, Tng HY, et al. 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: table 1. Schizophr Bull. 2015;41:1285–93.PubMedPubMedCentralCrossRef
17.
Ziermans TB, Schothorst PF, Schnack HG, Koolschijn PCMP, Kahn RS, van Engeland H, et al. Progressive structural brain changes during development of psychosis. Schizophr Bull. 2012;38:519–30.PubMedCrossRef
18.
19.
Lynskey M, White V, Hill D, Letcher T, Hall W. Prevalence of illicit drug use among youth: results from the Australian school students’ alcohol and drugs survey. Aust N Z J Public Health. 1999;23:519–24.PubMedCrossRef
20.
Pfefferbaum A, Rohlfing T, Pohl KM, Lane B, Chu W, Kwon D, et al. Adolescent development of cortical and white matter structure in the NCANDA sample: role of sex, ethnicity, puberty, and alcohol drinking. Cereb Cortex. 2016;26:4101–21.PubMedPubMedCentralCrossRef
21.
Hamilton I. Cannabis, psychosis and schizophrenia: unravelling a complex interaction: Cannabis, psychosis and schizophrenia. Addiction. 2017;112:1653–7.PubMedCrossRef
22.
Phillips LJ, Curry C, Yung AR, Pan Yuen H, Adlard S, Mcgorry PD. Cannabis use is not associated with the development of psychosis in an ‘Ultra’ high-risk group. Aust N Z J Psychiatry. 2002;36:800–6.PubMedCrossRef
23.
Valmaggia LR, Day FL, Jones C, Bissoli S, Pugh C, Hall D, Bhattacharyya S, Howes O, Stone J, Fusar-Poli P, Byrne M, McGuire PK. Cannabis use and transition to psychosis in people at ultra-high risk. Psychol Med. 2014;44(12):2503–12.PubMedCrossRef
24.
Kraan T, Velthorst E, Koenders L, Zwaart K, Ising HK, van den Berg D, de Haan L, van der Gaag M. Cannabis use and transition to psychosis in individuals at ultra-high risk: review and meta-analysis. Psychol Med. 2016;46(4):673–81.PubMedCrossRef
25.
Farris MS, Shakeel MK, Addington J. Cannabis use in individuals at clinical high-risk for psychosis: a comprehensive review. Soc Psychiatry Psychiatr Epidemiol. 2020;55(5):527–37.PubMedCrossRef
26.
Glass M, Faull RLM, Dragunow M. Cannabinoid receptors in the human brain: a detailed anatomical and quantitative autoradiographic study in the fetal, neonatal and adult human brain. Neuroscience. 1997;77:299–318.PubMedCrossRef
27.
Cohen M, Rasser PE, Peck G, Carr VJ, Ward PB, Thompson PM, et al. Cerebellar grey-matter deficits, cannabis use and recent onset schizophrenia in adolescents and young adults. Int J Neuropsychopharmacol. 2012;15:297–307.PubMedCrossRef
28.
Hartberg CB, Lange EH, Lagerberg TV, Haukvik UK, Andreassen OA, Melle I, Agartz I. Cortical thickness, cortical surface area and subcortical volumes in schizophrenia and bipolar disorder patients with cannabis use. Eur Neuropsychopharmacol. 2018;28(1):37–47.PubMedCrossRef
29.
Buchy L, Mathalon DH, Cannon TD, Cadenhead KS, Cornblatt BA, McGlashan TH, Perkins DO, Seidman LJ, Tsuang MT, Walker EF, Woods SW, Bearden CE, Addington J. Relation between cannabis use and subcortical volumes in people at clinical high risk of psychosis. Psychiatry Res Neuroimaging. 2016;254:3–9.PubMedCrossRef
30.
van Erp TGM, Walton E, Hibar DP, Schmaal L, Jiang W, Glahn DC, et al. Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) consortium. Biol Psychiatry. 2018;84:644–54.PubMedPubMedCentralCrossRef
31.
Ho B-C, Andreasen NC, Ziebell S, Pierson R, Magnotta V. Long-term antipsychotic treatment and brain volumes: a longitudinal study of recent onset schizophrenia. Arch Gen Psychiatry. 2011;68:128.PubMedPubMedCentralCrossRef
32.
Friedman JI, Tang CY, de Haas HJ, Changchien L, Goliasch G, Dabas P, et al. Brain imaging changes associated with risk factors for cardiovascular and cerebrovascular disease in asymptomatic patients. JACC Cardiovasc Imaging. 2014;7:1039–53.PubMedCrossRef
33.
Overall JE, Gorham DR. The brief psychiatric rating scale. Psychol Rep. 1962;10:799–812.CrossRef
34.
Jung MH, Jang JH, Kang D-H, Choi J-S, Shin NY, Kim HS, et al. The reliability and validity of the korean version of the structured interview for prodromal syndrome. Psychiatry Investig. 2010;7:257–63.PubMedPubMedCentralCrossRef
35.
Group, ENIGMA Clinical High Risk for Psychosis Working. Association of structural magnetic resonance imaging measures with psychosis onset in individuals at clinical high risk for developing psychosis: an ENIGMA working group mega-analysis. JAMA Psychiatry. 2021;78:753–66.CrossRef
36.
Del Re EC, William SS, Sylvain B, Johanna S, et al. 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. 2021;47:562–74.PubMedCrossRef
37.
Atkinson RJ, Fulham WR, Michie PT, Ward PB, Todd J, Stein H, et al. Electrophysiological, cognitive, and clinical profiles of at-risk mental state: the longitudinal Minds in Transition (MinT) study. PLoS One. 2017;12:e0171657.PubMedPubMedCentralCrossRef
38.
Loughland C, Draganic D, McCabe K, Richards J, Nasir A, Allen J, et al. Australian schizophrenia research bank: a database of comprehensive clinical, endophenotypic and genetic data for aetiological studies of schizophrenia. Aust N Z J Psychiatry. 2010;44:1029–35.PubMed
39.
Yung AR, Yung AR, Yuen HP, Mcgorry PD, Phillips LJ, Kelly D, et al. Mapping the onset of psychosis: the comprehensive assessment of at-risk mental states. Aust N Z J Psychiatry. 2005;39:964–71.PubMedCrossRef
40.
American Psychiatric Association. Diagnostic and statistical manual of mental disorders (4th edition, text revison) (DSM-IV-TR). 4th ed. 2000.
41.
Saunders JB, Aasland OG, Babor TF, De La Fuente JR, Grant M. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption-II. Addiction. 1993;88:791–804.PubMedCrossRef
42.
Adamson SJ, Sellman JD. A prototype screening instrument for cannabis use disorder: the Cannabis Use Disorders Identification Test (CUDIT) in an alcohol-dependent clinical sample. Drug Alcohol Rev. 2003;22:309–15.PubMedCrossRef
43.
Darke S, Ward J, Hall W, Heather N, Wodak A. The Opiate Treatment Index (OTI) researcher’s manual. Technical Report. Sydney: National Drug and Alcohol Research Centre: National Drug and Alcohol Research Centre; 1991.
44.
Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage. 1999;9:179–94.PubMedCrossRef
45.
Fischl B, van der Kouwe A, Destrieux C, Halgren E, Ségonne F, Salat DH, et al. Automatically parcellating the human cerebral cortex. Cereb Cortex. 2004;14:11–22.PubMedCrossRef
46.
Fischl B, Sereno MI, Dale AM. Cortical surface-based analysis: II: inflation, flattening, and a surface-based coordinate system. Neuroimage. 1999;9:195–207.PubMedCrossRef
47.
48.
Buckner RL, Head D, Parker J, Fotenos AF, Marcus D, Morris JC, et al. A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume. Neuroimage. 2004;23:724–38.PubMedCrossRef
49.
Greve DN, Fischl B. False positive rates in surface-based anatomical analysis. Neuroimage. 2018;171:6–14.PubMedCrossRef
50.
Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006;31:968–80.PubMedCrossRef
51.
Bykowsky O, Harrisberger F, Schmidt A, Smieskova R, Hauke DJ, Egloff L, et al. Association of antidepressants with brain morphology in early stages of psychosis: an imaging genomics approach. Sci Rep. 2019;9:8516.PubMedPubMedCentralCrossRef
52.
53.
Immonen J, Jääskeläinen E, Korpela H, Miettunen J. Age at onset and the outcomes of schizophrenia: a systematic review and meta-analysis. Early Interv Psychiatry. 2017;11:453–60.PubMedPubMedCentralCrossRef
54.
Merritt K, Luque Laguna P, Irfan A, David AS. Longitudinal structural MRI findings in individuals at genetic and clinical high risk for psychosis: a systematic review. Front Psychiatry. 2021;12:620401.PubMedPubMedCentralCrossRef
55.
Mills KL, Goddings A-L, Herting MM, Meuwese R, Blakemore S-J, Crone EA, et al. Structural brain development between childhood and adulthood: convergence across four longitudinal samples. Neuroimage. 2016;141:273–81.PubMedCrossRef
Metadata
Title
Fronto-temporal cortical grey matter thickness and surface area in the at-risk mental state and recent-onset schizophrenia: a magnetic resonance imaging study
Authors
Paul E. Rasser
Tim Ehlkes
Ulrich Schall
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Psychiatry / Issue 1/2024
Electronic ISSN: 1471-244X
DOI
https://doi.org/10.1186/s12888-024-05494-9

Other articles of this Issue 1/2024

BMC Psychiatry 1/2024 Go to the issue

Research

Investigation of carotid intima-media thickness in patients with schizophrenia

Research

Young people’s views on the acceptability and feasibility of loneliness interventions for their age group

Research

Social media addiction: associations with attachment style, mental distress, and personality

Research

Face-to-face bullying in and outside of schools and cyberbullying are associated with suicidality in Kenyan high school students: a public health issue

Research

Comparing frequencies of adolescent suicide attempters pre- and during COVID-19 pandemic school terms

Research

Impact of depressive symptoms on medication adherence in older adults with chronic neurological diseases