Aberrant limbic brain structures in young individuals at risk for mental illness

Aim Alterations in limbic structures may be present before the onset of serious mental illness, but whether subfield‐specific limbic brain changes parallel stages in clinical risk is unknown. To address this gap, we compared the hippocampus, amygdala, and thalamus subfield‐specific volumes in adoles...

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Veröffentlicht in:Psychiatry and clinical neurosciences 2020-05, Vol.74 (5), p.294-302
Hauptverfasser: Nogovitsyn, Nikita, Souza, Roberto, Muller, Meghan, Srajer, Amelia, Metzak, Paul D., Hassel, Stefanie, Ismail, Zahinoor, Protzner, Andrea, Bray, Signe L., Lebel, Catherine, MacIntosh, Bradley J., Goldstein, Benjamin I., Wang, JianLi, Kennedy, Sidney H., Addington, Jean, MacQueen, Glenda M.
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container_end_page 302
container_issue 5
container_start_page 294
container_title Psychiatry and clinical neurosciences
container_volume 74
creator Nogovitsyn, Nikita
Souza, Roberto
Muller, Meghan
Srajer, Amelia
Metzak, Paul D.
Hassel, Stefanie
Ismail, Zahinoor
Protzner, Andrea
Bray, Signe L.
Lebel, Catherine
MacIntosh, Bradley J.
Goldstein, Benjamin I.
Wang, JianLi
Kennedy, Sidney H.
Addington, Jean
MacQueen, Glenda M.
description Aim Alterations in limbic structures may be present before the onset of serious mental illness, but whether subfield‐specific limbic brain changes parallel stages in clinical risk is unknown. To address this gap, we compared the hippocampus, amygdala, and thalamus subfield‐specific volumes in adolescents at various stages of risk for mental illness. Methods MRI scans were obtained from 182 participants (aged 12–25 years) from the Canadian Psychiatric Risk and Outcome study. The sample comprised of four groups: asymptomatic youth at risk due to family history of mental illness (Stage 0, n = 32); youth with early symptoms of distress (Stage 1a, n = 41); youth with subthreshold psychotic symptoms (Stage 1b, n = 72); and healthy comparison participants with no family history of serious mental illness (n = 37). Analyses included between‐group comparisons of brain measurements and correlational analyses that aimed to identify significant associations between neuroimaging and clinical measurements. A machine‐learning technique examined the discriminative properties of the clinical staging model. Results Subfield‐specific limbic volume deficits were detected at every stage of risk for mental illness. A machine‐learning classifier identified volume deficits within the body of the hippocampus, left amygdala nuclei, and medial‐lateral nuclei of the thalamus that were most informative in differentiating between risk stages. Conclusion Aberrant subfield‐specific changes within the limbic system may serve as biological evidence to support transdiagnostic clinical staging in mental illness. Differential patterns of volume deficits characterize those at risk for mental illness and may be indicative of a risk‐stage progression.
doi_str_mv 10.1111/pcn.12985
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To address this gap, we compared the hippocampus, amygdala, and thalamus subfield‐specific volumes in adolescents at various stages of risk for mental illness. Methods MRI scans were obtained from 182 participants (aged 12–25 years) from the Canadian Psychiatric Risk and Outcome study. The sample comprised of four groups: asymptomatic youth at risk due to family history of mental illness (Stage 0, n = 32); youth with early symptoms of distress (Stage 1a, n = 41); youth with subthreshold psychotic symptoms (Stage 1b, n = 72); and healthy comparison participants with no family history of serious mental illness (n = 37). Analyses included between‐group comparisons of brain measurements and correlational analyses that aimed to identify significant associations between neuroimaging and clinical measurements. A machine‐learning technique examined the discriminative properties of the clinical staging model. Results Subfield‐specific limbic volume deficits were detected at every stage of risk for mental illness. A machine‐learning classifier identified volume deficits within the body of the hippocampus, left amygdala nuclei, and medial‐lateral nuclei of the thalamus that were most informative in differentiating between risk stages. Conclusion Aberrant subfield‐specific changes within the limbic system may serve as biological evidence to support transdiagnostic clinical staging in mental illness. Differential patterns of volume deficits characterize those at risk for mental illness and may be indicative of a risk‐stage progression.</description><identifier>ISSN: 1323-1316</identifier><identifier>EISSN: 1440-1819</identifier><identifier>DOI: 10.1111/pcn.12985</identifier><identifier>PMID: 32003517</identifier><language>eng</language><publisher>Melbourne: John Wiley &amp; Sons Australia, Ltd</publisher><subject>adolescent psychiatry ; Amygdala ; Child &amp; adolescent psychiatry ; classification ; clinical high risk ; Hippocampus ; Learning algorithms ; limbic brain ; Limbic system ; Magnetic resonance imaging ; Mental disorders ; Neuroimaging ; Thalamus</subject><ispartof>Psychiatry and clinical neurosciences, 2020-05, Vol.74 (5), p.294-302</ispartof><rights>2020 The Authors. Psychiatry and Clinical Neurosciences © 2020 Japanese Society of Psychiatry and Neurology</rights><rights>2020 The Authors. Psychiatry and Clinical Neurosciences © 2020 Japanese Society of Psychiatry and Neurology.</rights><rights>2020 The Author. 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To address this gap, we compared the hippocampus, amygdala, and thalamus subfield‐specific volumes in adolescents at various stages of risk for mental illness. Methods MRI scans were obtained from 182 participants (aged 12–25 years) from the Canadian Psychiatric Risk and Outcome study. The sample comprised of four groups: asymptomatic youth at risk due to family history of mental illness (Stage 0, n = 32); youth with early symptoms of distress (Stage 1a, n = 41); youth with subthreshold psychotic symptoms (Stage 1b, n = 72); and healthy comparison participants with no family history of serious mental illness (n = 37). Analyses included between‐group comparisons of brain measurements and correlational analyses that aimed to identify significant associations between neuroimaging and clinical measurements. A machine‐learning technique examined the discriminative properties of the clinical staging model. Results Subfield‐specific limbic volume deficits were detected at every stage of risk for mental illness. A machine‐learning classifier identified volume deficits within the body of the hippocampus, left amygdala nuclei, and medial‐lateral nuclei of the thalamus that were most informative in differentiating between risk stages. Conclusion Aberrant subfield‐specific changes within the limbic system may serve as biological evidence to support transdiagnostic clinical staging in mental illness. 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To address this gap, we compared the hippocampus, amygdala, and thalamus subfield‐specific volumes in adolescents at various stages of risk for mental illness. Methods MRI scans were obtained from 182 participants (aged 12–25 years) from the Canadian Psychiatric Risk and Outcome study. The sample comprised of four groups: asymptomatic youth at risk due to family history of mental illness (Stage 0, n = 32); youth with early symptoms of distress (Stage 1a, n = 41); youth with subthreshold psychotic symptoms (Stage 1b, n = 72); and healthy comparison participants with no family history of serious mental illness (n = 37). Analyses included between‐group comparisons of brain measurements and correlational analyses that aimed to identify significant associations between neuroimaging and clinical measurements. A machine‐learning technique examined the discriminative properties of the clinical staging model. 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source Wiley Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley Free Content; Open Access Titles of Japan; Alma/SFX Local Collection
subjects adolescent psychiatry
Amygdala
Child & adolescent psychiatry
classification
clinical high risk
Hippocampus
Learning algorithms
limbic brain
Limbic system
Magnetic resonance imaging
Mental disorders
Neuroimaging
Thalamus
title Aberrant limbic brain structures in young individuals at risk for mental illness
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