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 |
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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 |
format | Article |
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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.</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 & Sons Australia, Ltd</publisher><subject>adolescent psychiatry ; Amygdala ; Child & 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. Psychiatry and Clinical Neurosciences © 2020 Japanese Society of Psychiatry and Neurology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4785-229ef20b5ce425f2beab35c2adf8fd5745d634100a2cf8556261ce25f94267423</citedby><cites>FETCH-LOGICAL-c4785-229ef20b5ce425f2beab35c2adf8fd5745d634100a2cf8556261ce25f94267423</cites><orcidid>0000-0001-5445-1841 ; 0000-0003-3352-6781</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fpcn.12985$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fpcn.12985$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32003517$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Nogovitsyn, Nikita</creatorcontrib><creatorcontrib>Souza, Roberto</creatorcontrib><creatorcontrib>Muller, Meghan</creatorcontrib><creatorcontrib>Srajer, Amelia</creatorcontrib><creatorcontrib>Metzak, Paul D.</creatorcontrib><creatorcontrib>Hassel, Stefanie</creatorcontrib><creatorcontrib>Ismail, Zahinoor</creatorcontrib><creatorcontrib>Protzner, Andrea</creatorcontrib><creatorcontrib>Bray, Signe L.</creatorcontrib><creatorcontrib>Lebel, Catherine</creatorcontrib><creatorcontrib>MacIntosh, Bradley J.</creatorcontrib><creatorcontrib>Goldstein, Benjamin I.</creatorcontrib><creatorcontrib>Wang, JianLi</creatorcontrib><creatorcontrib>Kennedy, Sidney H.</creatorcontrib><creatorcontrib>Addington, Jean</creatorcontrib><creatorcontrib>MacQueen, Glenda M.</creatorcontrib><title>Aberrant limbic brain structures in young individuals at risk for mental illness</title><title>Psychiatry and clinical neurosciences</title><addtitle>Psychiatry Clin Neurosci</addtitle><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.</description><subject>adolescent psychiatry</subject><subject>Amygdala</subject><subject>Child & adolescent psychiatry</subject><subject>classification</subject><subject>clinical high risk</subject><subject>Hippocampus</subject><subject>Learning algorithms</subject><subject>limbic brain</subject><subject>Limbic system</subject><subject>Magnetic resonance imaging</subject><subject>Mental disorders</subject><subject>Neuroimaging</subject><subject>Thalamus</subject><issn>1323-1316</issn><issn>1440-1819</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp10ElLAzEABeAgiq3Vg39AAl70MG3WWY6luEHRHvQcMplEUmepyUTpvzd1qgfBXPICH4_wADjHaIrjmW1UO8WkyPkBGGPGUIJzXBzGTAlNMMXpCJx4v0YIUZriYzCiJEaOszFYzUvtnGx7WNumtAqWTtoW-t4F1QenPYyvbRfa1xgq-2GrIGsPZQ-d9W_QdA42uu1lDW1dt9r7U3BkotBn-3sCXm5vnhf3yfLp7mExXyaKZTlPCCm0IajkSjPCDSm1LClXRFYmNxXPGK9SyjBCkiiTc56SFCsdZcFImjFCJ-Bq6N247j1o34vGeqXrWra6C14QyhHKs4zu6OUfuu6Ca-PvoiqyAnOMeFTXg1Ku895pIzbONtJtBUZiN7OIM4vvmaO92DeGstHVr_zZNYLZAD5trbf_N4nV4nGo_ALKVIWz</recordid><startdate>202005</startdate><enddate>202005</enddate><creator>Nogovitsyn, Nikita</creator><creator>Souza, Roberto</creator><creator>Muller, Meghan</creator><creator>Srajer, Amelia</creator><creator>Metzak, Paul D.</creator><creator>Hassel, Stefanie</creator><creator>Ismail, Zahinoor</creator><creator>Protzner, Andrea</creator><creator>Bray, Signe L.</creator><creator>Lebel, Catherine</creator><creator>MacIntosh, Bradley J.</creator><creator>Goldstein, Benjamin I.</creator><creator>Wang, JianLi</creator><creator>Kennedy, Sidney H.</creator><creator>Addington, Jean</creator><creator>MacQueen, Glenda M.</creator><general>John Wiley & Sons Australia, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>K9.</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-5445-1841</orcidid><orcidid>https://orcid.org/0000-0003-3352-6781</orcidid></search><sort><creationdate>202005</creationdate><title>Aberrant limbic brain structures in young individuals at risk for mental illness</title><author>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.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4785-229ef20b5ce425f2beab35c2adf8fd5745d634100a2cf8556261ce25f94267423</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>adolescent psychiatry</topic><topic>Amygdala</topic><topic>Child & adolescent psychiatry</topic><topic>classification</topic><topic>clinical high risk</topic><topic>Hippocampus</topic><topic>Learning algorithms</topic><topic>limbic brain</topic><topic>Limbic system</topic><topic>Magnetic resonance imaging</topic><topic>Mental disorders</topic><topic>Neuroimaging</topic><topic>Thalamus</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nogovitsyn, Nikita</creatorcontrib><creatorcontrib>Souza, Roberto</creatorcontrib><creatorcontrib>Muller, Meghan</creatorcontrib><creatorcontrib>Srajer, Amelia</creatorcontrib><creatorcontrib>Metzak, Paul D.</creatorcontrib><creatorcontrib>Hassel, Stefanie</creatorcontrib><creatorcontrib>Ismail, Zahinoor</creatorcontrib><creatorcontrib>Protzner, Andrea</creatorcontrib><creatorcontrib>Bray, Signe L.</creatorcontrib><creatorcontrib>Lebel, Catherine</creatorcontrib><creatorcontrib>MacIntosh, Bradley J.</creatorcontrib><creatorcontrib>Goldstein, Benjamin I.</creatorcontrib><creatorcontrib>Wang, JianLi</creatorcontrib><creatorcontrib>Kennedy, Sidney H.</creatorcontrib><creatorcontrib>Addington, Jean</creatorcontrib><creatorcontrib>MacQueen, Glenda M.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Psychiatry and clinical neurosciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nogovitsyn, Nikita</au><au>Souza, Roberto</au><au>Muller, Meghan</au><au>Srajer, Amelia</au><au>Metzak, Paul D.</au><au>Hassel, Stefanie</au><au>Ismail, Zahinoor</au><au>Protzner, Andrea</au><au>Bray, Signe L.</au><au>Lebel, Catherine</au><au>MacIntosh, Bradley J.</au><au>Goldstein, Benjamin I.</au><au>Wang, JianLi</au><au>Kennedy, Sidney H.</au><au>Addington, Jean</au><au>MacQueen, Glenda M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Aberrant limbic brain structures in young individuals at risk for mental illness</atitle><jtitle>Psychiatry and clinical neurosciences</jtitle><addtitle>Psychiatry Clin Neurosci</addtitle><date>2020-05</date><risdate>2020</risdate><volume>74</volume><issue>5</issue><spage>294</spage><epage>302</epage><pages>294-302</pages><issn>1323-1316</issn><eissn>1440-1819</eissn><abstract>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.</abstract><cop>Melbourne</cop><pub>John Wiley & Sons Australia, Ltd</pub><pmid>32003517</pmid><doi>10.1111/pcn.12985</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-5445-1841</orcidid><orcidid>https://orcid.org/0000-0003-3352-6781</orcidid><oa>free_for_read</oa></addata></record> |
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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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