Abnormal habenula functional connectivity characterizes treatment-resistant depression.
Neuroimage Clin
; 34: 102990, 2022.
Article
em En
| MEDLINE
| ID: mdl-35305499
ABSTRACT
BACKGROUND:
A significant proportion of patients with major depressive disorder are resistant to antidepressant medication and psychological treatments. A core symptom of treatment-resistant depression (TRD) is anhedonia, or the inability to feel pleasure, which has been attributed to disrupted habenula function - a component of the reward network. This study aimed to map detailed neural circuitry architecture related to the habenula to identify neural mechanisms of TRD.METHODS:
35 TRD patients, 35 patients with treatment-sensitive depression (TSD), and 38 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Functional connectivity analyses were performed using the left and right habenula as seed regions of interest, and the three groups were compared using whole-brain voxel-wise comparisons.RESULTS:
The TRD group demonstrated hyperconnectivity of the left habenula to the left precuneus cortex and the right precentral gyrus, compared to the TSD group, and to the right precuneus cortex, compared to the TSD and HC groups. In contrast, TSD demonstrated hypoconnectivity than HC for both connectivity measures. These connectivity values were significantly higher in patients with a history of suicidal ideation.CONCLUSIONS:
This study provides evidence that, unlike TSD, TRD is characterized by hyperconnectivity of the left habenula particularly with regions of the default mode network. An increased interplay between reward and default mode networks is linked to suicidality and could be a possible mechanism for anhedonia in hard to treat depression.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Habenula
/
Transtorno Depressivo Maior
/
Transtorno Depressivo Resistente a Tratamento
Tipo de estudo:
Observational_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Neuroimage Clin
Ano de publicação:
2022
Tipo de documento:
Article