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Brain Age in Early Stages of Bipolar Disorders or Schizophrenia
T. Hajek, K. Franke, M. Kolenic, J. Capkova, M. Matejka, L. Propper, R. Uher, P. Stopkova, T. Novak, T. Paus, M. Kopecek, F. Spaniel, M. Alda,
Jazyk angličtina Země Spojené státy americké
Typ dokumentu srovnávací studie, časopisecké články, práce podpořená grantem
Grantová podpora
NV16-32791A
MZ0
CEP - Centrální evidence projektů
NV16-32791A
MZ0
CEP - Centrální evidence projektů
Digitální knihovna NLK
Plný text - Článek
Plný text - Článek
NLK
Free Medical Journals
od 2006 do Před 1 rokem
PubMed Central
od 2006 do Před 1 rokem
Europe PubMed Central
od 2006 do Před 1 rokem
Medline Complete (EBSCOhost)
od 1996-01-01 do Před 1 rokem
PubMed
29272464
DOI
10.1093/schbul/sbx172
Knihovny.cz E-zdroje
- MeSH
- bipolární porucha diagnostické zobrazování MeSH
- diferenciální diagnóza MeSH
- dospělí MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- mladiství MeSH
- mladý dospělý MeSH
- psychotické poruchy diagnostické zobrazování MeSH
- riziko MeSH
- schizofrenie diagnostické zobrazování MeSH
- strojové učení * MeSH
- věkové faktory MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- srovnávací studie MeSH
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.
Department of Psychiatry Dalhousie University Halifax NS Canada
National Institute of Mental Health Klecany Czech Republic
Structural Brain Mapping Group Department of Neurology Jena University Hospital Jena Germany
Citace poskytuje Crossref.org
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