Brain Age in Early Stages of Bipolar Disorders or Schizophrenia.


Journal

Schizophrenia bulletin
ISSN: 1745-1701
Titre abrégé: Schizophr Bull
Pays: United States
ID NLM: 0236760

Informations de publication

Date de publication:
01 01 2019
Historique:
pubmed: 23 12 2017
medline: 20 6 2019
entrez: 23 12 2017
Statut: ppublish

Résumé

The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the biological age of the brain from structural magnetic resonance imaging scans (MRI). The discrepancy between brain and chronological age could contribute to early detection and differentiation of BD and schizophrenia. We estimated brain age in 2 studies focusing on early stages of schizophrenia or BD. In the first study, we recruited 43 participants with first episode of schizophrenia-spectrum disorders (FES) and 43 controls. In the second study, we included 96 offspring of bipolar parents (48 unaffected, 48 affected) and 60 controls. We used relevance vector regression trained on an independent sample of 504 controls to estimate the brain age of study participants from structural MRI. We calculated the brain-age gap estimate (BrainAGE) score by subtracting the chronological age from the brain age. Participants with FES had higher BrainAGE scores than controls (F(1, 83) = 8.79, corrected P = .008, Cohen's d = 0.64). Their brain age was on average 2.64 ± 4.15 years greater than their chronological age (matched t(42) = 4.36, P < .001). In contrast, participants at risk or in the early stages of BD showed comparable BrainAGE scores to controls (F(2,149) = 1.04, corrected P = .70, η2 = 0.01) and comparable brain and chronological age. Early stages of schizophrenia, but not early stages of BD, were associated with advanced BrainAGE scores. Participants with FES showed neurostructural alterations, which made their brains appear 2.64 years older than their chronological age. BrainAGE scores could aid in early differential diagnosis between BD and schizophrenia.

Sections du résumé

Background
The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the biological age of the brain from structural magnetic resonance imaging scans (MRI). The discrepancy between brain and chronological age could contribute to early detection and differentiation of BD and schizophrenia.
Methods
We estimated brain age in 2 studies focusing on early stages of schizophrenia or BD. In the first study, we recruited 43 participants with first episode of schizophrenia-spectrum disorders (FES) and 43 controls. In the second study, we included 96 offspring of bipolar parents (48 unaffected, 48 affected) and 60 controls. We used relevance vector regression trained on an independent sample of 504 controls to estimate the brain age of study participants from structural MRI. We calculated the brain-age gap estimate (BrainAGE) score by subtracting the chronological age from the brain age.
Results
Participants with FES had higher BrainAGE scores than controls (F(1, 83) = 8.79, corrected P = .008, Cohen's d = 0.64). Their brain age was on average 2.64 ± 4.15 years greater than their chronological age (matched t(42) = 4.36, P < .001). In contrast, participants at risk or in the early stages of BD showed comparable BrainAGE scores to controls (F(2,149) = 1.04, corrected P = .70, η2 = 0.01) and comparable brain and chronological age.
Conclusions
Early stages of schizophrenia, but not early stages of BD, were associated with advanced BrainAGE scores. Participants with FES showed neurostructural alterations, which made their brains appear 2.64 years older than their chronological age. BrainAGE scores could aid in early differential diagnosis between BD and schizophrenia.

Identifiants

pubmed: 29272464
pii: 4767816
doi: 10.1093/schbul/sbx172
pmc: PMC6293219
doi:

Types de publication

Comparative Study Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

190-198

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Auteurs

Tomas Hajek (T)

Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.
National Institute of Mental Health, Klecany, Czech Republic.

Katja Franke (K)

Structural Brain Mapping Group, Department of Neurology, Jena University Hospital, Jena, Germany.

Marian Kolenic (M)

National Institute of Mental Health, Klecany, Czech Republic.

Jana Capkova (J)

National Institute of Mental Health, Klecany, Czech Republic.

Martin Matejka (M)

National Institute of Mental Health, Klecany, Czech Republic.
Psychiatric Hospital Bohnice, Prague, Czech Republic.

Lukas Propper (L)

Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.

Rudolf Uher (R)

Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.

Pavla Stopkova (P)

National Institute of Mental Health, Klecany, Czech Republic.

Tomas Novak (T)

National Institute of Mental Health, Klecany, Czech Republic.

Tomas Paus (T)

Rotman Research Institute and Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada.
Center for Developing Brain, Child Mind Institute, New York, NY.

Miloslav Kopecek (M)

National Institute of Mental Health, Klecany, Czech Republic.

Filip Spaniel (F)

National Institute of Mental Health, Klecany, Czech Republic.

Martin Alda (M)

Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.
National Institute of Mental Health, Klecany, Czech Republic.

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