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Cerebral Blood Flow Changes And Their Genetic Mechanisms In Major Depressive Disorder: A Combined Neuroimaging And Transcriptome Study

Posted on:2024-02-19Degree:MasterType:Thesis
Country:ChinaCandidate:X T SunFull Text:PDF
GTID:2544307082468354Subject:Medical imaging and nuclear medicine
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Background: Extensive research has shown abnormal cerebral blood flow(CBF)in patients with major depressive disorder(MDD)that is a heritable disease.The objective of this study was to investigate the genetic mechanisms of CBF abnormalities in MDD.Methods: A comprehensive neuroimaging meta-analysis of previous literature and group CBF differences in an independent sample of 133 MDD patients and 133 controls were performed to achieve a more thorough characterization of CBF changes in MDD.In combination with the Allen Human Brain Atlas,transcriptome neuroimaging spatial association analyses were conducted to identify genes whose expression correlated with CBF changes in MDD,followed by a set of gene functional feature analyses.Results: This study revealed increased CBF in the reward circuitry and default-mode network and decreased CBF in the visual system in MDD patients.Moreover,these CBF changes were spatially associated with expression of 1532 genes,which could build a protein-protein interaction network,supported by 60 hub genes with specific functional significance.These genes were enriched for important molecular functions,biological processes,and cellular components of the cerebral cortex as well as several common mental disorders.Concurrently,these genes were specifically expressed in immune cells,neuronal cells,brain tissues,and during nearly all developmental stages.Regarding behavioral relevance,these genes were associated with domains involving emotion and sensation.Conclusions: This study suggest a cerebral perfusion redistribution in MDD,which may be a consequence of complex interactions of a wide range of genes with diverse functional features.
Keywords/Search Tags:major depressive disorder, cerebral blood flow, neuroimaging, gene expression, meta-analysis
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