A spectroscopic approach toward depression diagnosis: local metabolism meets functional connectivity.

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Bibliographic Details
Title:	A spectroscopic approach toward depression diagnosis: local metabolism meets functional connectivity.
Authors:	Demenescu, Liliana, Colic, Lejla, Li, Meng, Safron, Adam, Biswal, B., Metzger, Coraline, Li, Shijia, Walter, Martin
Source:	European Archives of Psychiatry & Clinical Neuroscience. Mar2017, Vol. 267 Issue 2, p95-105. 11p.
Subjects:	Diagnosis of mental depression, Brain metabolism, Cingulate cortex, Insular cortex, Functional magnetic resonance imaging, Glutamic acid
Abstract:	Abnormal anterior insula (AI) response and functional connectivity (FC) is associated with depression. In addition to clinical features, such as severity, AI FC and its metabolism further predicted therapeutic response. Abnormal FC between anterior cingulate and AI covaried with reduced glutamate level within cingulate cortex. Recently, deficient glial glutamate conversion was found in AI in major depression disorder (MDD). We therefore postulate a local glutamatergic mechanism in insula cortex of depressive patients, which is correlated with symptoms severity and itself influences AI's network connectivity in MDD. Twenty-five MDD patients and 25 healthy controls (HC) matched on age and sex underwent resting state functional magnetic resonance imaging and magnetic resonance spectroscopy scans. To determine the role of local glutamate-glutamine complex (Glx) ratio on whole brain AI FC, we conducted regression analysis with Glx relative to creatine (Cr) ratio as factor of interest and age, sex, and voxel tissue composition as nuisance factors. We found that in MDD, but not in HC, AI Glx/Cr ratio correlated positively with AI FC to right supramarginal gyrus and negatively with AI FC toward left occipital cortex ( p < 0.05 family wise error). AI Glx/Cr level was negatively correlated with HAMD score ( p < 0.05) in MDD patients. We showed that the local AI ratio of glutamatergic-creatine metabolism is an underlying candidate subserving functional network disintegration of insula toward low level and supramodal integration areas, in MDD. While causality cannot directly be inferred from such correlation, our finding helps to define a multilevel network of response-predicting regions based on local metabolism and connectivity strength. [ABSTRACT FROM AUTHOR]
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Database:	Psychology and Behavioral Sciences Collection

Description
Abstract:	Abnormal anterior insula (AI) response and functional connectivity (FC) is associated with depression. In addition to clinical features, such as severity, AI FC and its metabolism further predicted therapeutic response. Abnormal FC between anterior cingulate and AI covaried with reduced glutamate level within cingulate cortex. Recently, deficient glial glutamate conversion was found in AI in major depression disorder (MDD). We therefore postulate a local glutamatergic mechanism in insula cortex of depressive patients, which is correlated with symptoms severity and itself influences AI's network connectivity in MDD. Twenty-five MDD patients and 25 healthy controls (HC) matched on age and sex underwent resting state functional magnetic resonance imaging and magnetic resonance spectroscopy scans. To determine the role of local glutamate-glutamine complex (Glx) ratio on whole brain AI FC, we conducted regression analysis with Glx relative to creatine (Cr) ratio as factor of interest and age, sex, and voxel tissue composition as nuisance factors. We found that in MDD, but not in HC, AI Glx/Cr ratio correlated positively with AI FC to right supramarginal gyrus and negatively with AI FC toward left occipital cortex ( p < 0.05 family wise error). AI Glx/Cr level was negatively correlated with HAMD score ( p < 0.05) in MDD patients. We showed that the local AI ratio of glutamatergic-creatine metabolism is an underlying candidate subserving functional network disintegration of insula toward low level and supramodal integration areas, in MDD. While causality cannot directly be inferred from such correlation, our finding helps to define a multilevel network of response-predicting regions based on local metabolism and connectivity strength. [ABSTRACT FROM AUTHOR]
ISSN:	09401334
DOI:	10.1007/s00406-016-0726-1