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Machine-learning based brain age estimation in major depression showing no evidence of accelerated aging

Published on Aug 1, 2019in Psychiatry Research-neuroimaging2.208
· DOI :10.1016/j.pscychresns.2019.06.001
Bianca Besteher4
Estimated H-index: 4
,
Christian Gaser61
Estimated H-index: 61
,
Igor Nenadic25
Estimated H-index: 25
(University of Marburg)
Source
Abstract
Abstract Molecular biological findings indicate that affective disorders are associated with processes akin to accelerated aging of the brain. The use of the BrainAGE (brain age estimation gap) framework allows machine-learning based detection of a gap between age estimated from high-resolution MRI scans an chronological age, and thus an indicator of systems-level accelerated aging. We analysed 3T high-resolution structural MRI scans in 38 major depression patients (without co-morbid axis I or II disorders) and 40 healthy controls using the BrainAGE method to test the hypothesis of accelerated aging in (non-psychotic) major depression. We found no significant difference (or trend) for elevated BrainAGE in this pilot sample. Unlike previous findings in schizophrenia (and partially bipolar disorder), unipolar depression per se does not seem to be associated with accelerated aging patterns across the brain. However, given the limitations of the sample, further study is needed to test for effects in subgroups with comorbidities, as well as longitudinal designs.
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References29
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#1Tomas Hajek (Dal: Dalhousie University)H-Index: 30
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Abstract Prior studies have reported significant cross-sectional associations between depression or anxiety and shorter telomere lengths, but the temporality of associations is uncertain. Little is known regarding whether shorter telomere length is related to increased risk of developing depression or anxiety. In this study, using the genetic tool of polygenic risk score (PRS), we evaluated the association between genetic predisposition to shorter telomere length and the risks of lifetime clinic...
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Abstract Negative fateful life events (FLEs) such as interpersonal conflict, death in the family, financial hardship, and serious medical emergencies can act as allostatic stressors that accelerate biological aging. However, the relationship between FLEs and neuroanatomical aging is not well understood. We examined 359 men (mean age 62 years) participating in the Vietnam Era twin study of aging (VETSA) to determine whether negative midlife FLEs are associated with advanced brain aging after cont...
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Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 yea...
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#1Igor Nenadic (University of Marburg)H-Index: 23
Bildgebende Verfahren sind zentrale Methoden zur Erforschung dysfunktionaler neuronaler Netzwerke bei Schizophrenie. Die vorliegende Ubersichtsarbeit stellt aktuelle Befunde zur Storung neuronaler Netzwerke auf struktureller und funktioneller Ebene dar und fasst aktuelle Entwicklungen zusammen. Neben grosen multizentrischen Analysen haben vor allem methodische Neuerungen, z. B. die Magnetresonanz(MR)-Morphometrie, zu einem Erkenntnisgewinn der Differenzierung fruher vs. spater struktureller Alte...
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