Association Between Genetic Risk for Type 2 Diabetes and Structural Brain Connectivity in Major Depressive Disorder.
Biol Psychiatry Cogn Neurosci Neuroimaging
; 7(3): 333-340, 2022 03.
Article
em En
| MEDLINE
| ID: mdl-33684623
ABSTRACT
BACKGROUND:
Major depressive disorder (MDD) and type 2 diabetes mellitus (T2D) are known to share clinical comorbidity and to have genetic overlap. Besides their shared genetics, both diseases seem to be associated with alterations in brain structural connectivity and impaired cognitive performance, but little is known about the mechanisms by which genetic risk of T2D might affect brain structure and function and if they do, how these effects could contribute to the disease course of MDD.METHODS:
This study explores the association of polygenic risk for T2D with structural brain connectome topology and cognitive performance in 434 nondiabetic patients with MDD and 539 healthy control subjects.RESULTS:
Polygenic risk score for T2D across MDD patients and healthy control subjects was found to be associated with reduced global fractional anisotropy, a marker of white matter microstructure, an effect found to be predominantly present in MDD-related fronto-temporo-parietal connections. A mediation analysis further suggests that this fractional anisotropy variation may mediate the association between polygenic risk score and cognitive performance.CONCLUSIONS:
Our findings provide preliminary evidence of a polygenic risk for T2D to be linked to brain structural connectivity and cognition in patients with MDD and healthy control subjects, even in the absence of a direct T2D diagnosis. This suggests an effect of T2D genetic risk on white matter integrity, which may mediate an association of genetic risk for diabetes and cognitive impairments.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Transtorno Depressivo Maior
/
Diabetes Mellitus Tipo 2
/
Conectoma
Tipo de estudo:
Etiology_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Biol Psychiatry Cogn Neurosci Neuroimaging
Ano de publicação:
2022
Tipo de documento:
Article