Roberto Goya-Maldonado1, Katja Brodmann1, Maria Keil1, Sarah Trost1, Peter Dechent2, Oliver Gruber1. 1. Department of Psychiatry and Psychotherapy, Center for Translational Research in Systems Neuroscience and Psychiatry, University Medical Center, Georg-August-University, Goettingen, Germany. 2. Department of Cognitive Neurology, Research Group 'MR-Research in Neurology and Psychiatry', University Medical Center, Georg-August-University, Goettingen, Germany.
Abstract
BACKGROUND: Misdiagnosing bipolar depression can lead to very deleterious consequences of mistreatment. Although depressive symptoms may be similarly expressed in unipolar and bipolar disorder, changes in specific brain networks could be very distinct, being therefore informative markers for the differential diagnosis. We aimed to characterize specific alterations in candidate large-scale networks (frontoparietal, cingulo-opercular, and default mode) in symptomatic unipolar and bipolar patients using resting state fMRI, a cognitively low demanding paradigm ideal to investigate patients. METHODS: Networks were selected after independent component analysis, compared across 40 patients acutely depressed (20 unipolar, 20 bipolar), and 20 controls well-matched for age, gender, and education levels, and alterations were correlated to clinical parameters. RESULTS: Despite comparable symptoms, patient groups were robustly differentiated by large-scale network alterations. Differences were driven in bipolar patients by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Conversely, unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network, as much as reduced connectivity of the cingulo-opercular network to default mode regions, a network involved in detecting the need to switch between internally and externally oriented demands. These findings were mostly unaffected by current medication, comorbidity, and structural changes. Moreover, network alterations in unipolar patients were significantly correlated to the number of depressive episodes. CONCLUSION: Unipolar and bipolar groups displaying similar symptomatology could be clearly distinguished by characteristic changes in large-scale networks, encouraging further investigation of network fingerprints for clinical use. Hum Brain Mapp 37:808-818, 2016.
BACKGROUND: Misdiagnosing bipolar depression can lead to very deleterious consequences of mistreatment. Although depressive symptoms may be similarly expressed in unipolar and bipolar disorder, changes in specific brain networks could be very distinct, being therefore informative markers for the differential diagnosis. We aimed to characterize specific alterations in candidate large-scale networks (frontoparietal, cingulo-opercular, and default mode) in symptomatic unipolar and bipolarpatients using resting state fMRI, a cognitively low demanding paradigm ideal to investigate patients. METHODS: Networks were selected after independent component analysis, compared across 40 patients acutely depressed (20 unipolar, 20 bipolar), and 20 controls well-matched for age, gender, and education levels, and alterations were correlated to clinical parameters. RESULTS: Despite comparable symptoms, patient groups were robustly differentiated by large-scale network alterations. Differences were driven in bipolarpatients by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Conversely, unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network, as much as reduced connectivity of the cingulo-opercular network to default mode regions, a network involved in detecting the need to switch between internally and externally oriented demands. These findings were mostly unaffected by current medication, comorbidity, and structural changes. Moreover, network alterations in unipolar patients were significantly correlated to the number of depressive episodes. CONCLUSION: Unipolar and bipolar groups displaying similar symptomatology could be clearly distinguished by characteristic changes in large-scale networks, encouraging further investigation of network fingerprints for clinical use. Hum Brain Mapp 37:808-818, 2016.
Authors: M E Raichle; A M MacLeod; A Z Snyder; W J Powers; D A Gusnard; G L Shulman Journal: Proc Natl Acad Sci U S A Date: 2001-01-16 Impact factor: 11.205
Authors: Dina M Kronhaus; Natalia S Lawrence; Andrew M Williams; Sophia Frangou; Michael J Brammer; Steve C R Williams; Christopher M Andrew; Mary L Phillips Journal: Bipolar Disord Date: 2006-02 Impact factor: 6.744
Authors: Xiaoqian J Chai; Susan Whitfield-Gabrieli; Ann K Shinn; John D E Gabrieli; Alfonso Nieto Castañón; Julie M McCarthy; Bruce M Cohen; Dost Ongür Journal: Neuropsychopharmacology Date: 2011-06-08 Impact factor: 7.853
Authors: Alan Anticevic; Michael W Cole; Grega Repovs; John D Murray; Margaret S Brumbaugh; Anderson M Winkler; Aleksandar Savic; John H Krystal; Godfrey D Pearlson; David C Glahn Journal: Cereb Cortex Date: 2013-07-03 Impact factor: 5.357
Authors: Sharon Chen; Thomas J Ross; Wang Zhan; Carol S Myers; Keh-Shih Chuang; Stephen J Heishman; Elliot A Stein; Yihong Yang Journal: Brain Res Date: 2008-08-18 Impact factor: 3.252
Authors: Hao He; Jing Sui; Yuhui Du; Qingbao Yu; Dongdong Lin; Wayne C Drevets; Jonathan B Savitz; Jian Yang; Teresa A Victor; Vince D Calhoun Journal: Brain Struct Funct Date: 2017-06-09 Impact factor: 3.270
Authors: Y Wang; J Wang; Y Jia; S Zhong; M Zhong; Y Sun; M Niu; L Zhao; L Zhao; J Pan; L Huang; R Huang Journal: Transl Psychiatry Date: 2017-07-04 Impact factor: 6.222