The timeline of brain aging in major depression: A prospective study from before first-onset to established illness
Konowski, M.; Kraus, A.; Goltermann, J.; Ernsting, J.; Mahjoory, K.; Fisch, L.; Spanagel, J.; Wellms, S.; Bedir, D.; Altegoer, L.; Borgers, T.; Teckentrup, S.; Papenbrock, S.; Hildebrand, A. S.; Ratnalingam, E.; Meisenzahl, E.; Herrmann, F.; Meinert, S.; Leehr, E. J.; Hubbert, J.; Krieger, J.; Meinert, H.; Meinert, H.; Slump, T.; Nenadic, I.; Jansen, A.; Javaheripour, N.; Thomas-Odenthal, F.; Jamalabadai, H.; Straube, B.; Hermesdorf, M.; Richter, M.; Helbok, R.; Jiang, X.; Opel, N.; Berger, K.; Kircher, T.; Dannlowski, U.; Hahn, T.; Winter, N. R.; Leenings, R.
Show abstract
Major depressive disorder (MDD) has been associated with accelerated structural brain aging, yet whether this reflects a pre-existing neurobiological vulnerability, a dynamic acute state effect, or an accumulating biological residual remains unresolved. Across two longitudinal cohorts (N=3220), including a unique sample of 78 initially healthy individuals who transitioned into their first depressive episode during the study course, we systematically tested all three hypotheses. Patients with diagnosed MDD showed elevated MRI-derived brain age relative to healthy controls (1.4 and 2.5 years across cohorts). For the vulnerability hypothesis, individuals scanned prior to their first episode showed no baseline elevation, despite already demonstrating subclinical elevations in self-reported symptom severity, indicating that advanced brain age does not precede illness onset. For the state hypothesis, we found no acceleration of brain aging following the first depressive episode, and longitudinal brain age trajectories were independent of acute clinical symptom severity. Finally, neither episode duration nor recurrence scaled with brain age. Accelerated brain aging in depression is therefore neither an antecedent vulnerability nor an acute state marker of the first episode, but rather a stable biological feature of a long term illness course.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Brain Aging in Major Depressive Disorder: Results from the ENIGMA Major Depressive Disorder working group 97%
- MRI-derived estimation of biological aging in patients with affective disorders in a 9-year follow-up - a prospective marker of future recurrence 95%
- Three major dimensions of human brain cortical ageing in relation to cognitive decline across the 8th decade of life. 93%
Similar papers in this journal
- Contributing Factors to Advanced Brain Aging in Depression and Anxiety Disorders 93%
- Childhood intelligence attenuates the association between biological ageing and health outcomes in later life 92%
- MRI signature of brain age underlying post-traumatic stress disorder in World Trade Center responders 92%
Similar papers in this journal
- Precision Estimates of Longitudinal Brain Aging Capture Unexpected Individual Differences in One Year 93%
- Lifetime brain atrophy estimated from a single MRI: measurement characteristics and genome-wide correlates 93%
- Spinal cord structural and functional architecture and its shared organization with the brain across the adult lifespan 93%
Similar papers in this journal
- The effect of 18 months lifestyle intervention on brain age assessed with resting-state functional connectivity 93%
- Social isolation is linked to declining grey matter structure and cognitive functions in the LIFE-Adult panel study 93%
- Quantification of the pace of biological aging in humans through a blood test: The DunedinPoAm DNA methylation algorithm 92%
Similar papers in this journal
- Resting state changes in aging and Parkinson's disease are shaped by underlying neurotransmission - a normative modeling study 92%
- Brain age prediction reveals aberrant brain white matter in schizophrenia and bipolar disorder: A multi-sample diffusion tensor imaging study 92%
- Regional brain age deviations reveal divergent developmental pathways in youth 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.