Dataset Information

Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia.

ABSTRACT: The brain's default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree relatives of SZ probands (SZREL), and 206 unaffected first-degree relatives of PBP probands to identify DMNs and to test their biomarker and/or endophenotype status. A subset of controls and probands (n = 549) then was subjected to a parallel ICA (para-ICA) to identify imaging-genetic relationships. ICA identified three DMNs. Hypo-connectivity was observed in both patient groups in all DMNs. Similar patterns observed in SZREL were restricted to only one network. DMN connectivity also correlated with several symptom measures. Para-ICA identified five sub-DMNs that were significantly associated with five different genetic networks. Several top-ranking SNPs across these networks belonged to previously identified, well-known psychosis/mood disorder genes. Global enrichment analyses revealed processes including NMDA-related long-term potentiation, PKA, immune response signaling, axon guidance, and synaptogenesis that significantly influenced DMN modulation in psychoses. In summary, we observed both unique and shared impairments in functional connectivity across the SZ and PBP cohorts; these impairments were selectively familial only for SZREL. Genes regulating specific neurodevelopment/transmission processes primarily mediated DMN disconnectivity. The study thus identifies biological pathways related to a widely researched quantitative trait that might suggest novel, targeted drug treatments for these diseases.

SUBMITTER: Meda SA

PROVIDER: S-EPMC4024891 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia.

Meda Shashwath A SA Ruaño Gualberto G Windemuth Andreas A O'Neil Kasey K Berwise Clifton C Dunn Sabra M SM Boccaccio Leah E LE Narayanan Balaji B Kocherla Mohan M Sprooten Emma E Keshavan Matcheri S MS Tamminga Carol A CA Sweeney John A JA Clementz Brett A BA Calhoun Vince D VD Pearlson Godfrey D GD

Proceedings of the National Academy of Sciences of the United States of America 20140428 19

The brain's default mode network (DMN) is highly heritable and is compromised in a variety of psychiatric disorders. However, genetic control over the DMN in schizophrenia (SZ) and psychotic bipolar disorder (PBP) is largely unknown. Study subjects (n = 1,305) underwent a resting-state functional MRI scan and were analyzed by a two-stage approach. The initial analysis used independent component analysis (ICA) in 324 healthy controls, 296 SZ probands, 300 PBP probands, 179 unaffected first-degree ...[more]

PMID: 24778245

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Project description:BackgroundFunctional abnormalities, mostly involving functionally specialized subsystems, have been associated with disorders of emotion regulation such as bipolar disorder (BD). Understanding how independent functional subsystems integrate globally and how they relate with anatomical cortical and subcortical networks is key to understanding how the human brain's architecture constrains functional interactions and underpins abnormalities of mood and emotion, particularly in BD.MethodsResting-state functional magnetic resonance time series were averaged to obtain individual functional connectivity matrices (using AFNI software); individual structural connectivity matrices were derived using deterministic non-tensor-based tractography (using ExploreDTI, version 4.8.6), weighted by streamline count and fractional anisotropy. Structural and functional nodes were defined using a subject-specific cortico-subcortical mapping (using Desikan-Killiany Atlas, FreeSurfer, version 5.3). Whole-brain connectivity alongside a permutation-based statistical approach and structure-function coupling were employed to investigate topological variance in individuals with predominantly euthymic BD relative to psychiatrically healthy control subjects.ResultsPatients with BD (n = 41) exhibited decreased (synchronous) connectivity in a subnetwork encompassing frontolimbic and posterior-occipital functional connections (T > 3, p = .048), alongside increased (antisynchronous) connectivity within a frontotemporal subnetwork (T > 3, p = .014); all relative to control subjects (n = 56). Preserved whole-brain functional connectivity and comparable structure-function coupling among whole-brain and edge-class connections were observed in patients with BD relative to control subjects.ConclusionsThis study presents a functional map of BD dysconnectivity that differentially involves communication within nodes belonging to functionally specialized subsystems-default mode, frontoparietal, and frontolimbic systems; these changes do not extend to be detected globally and may be necessary to maintain a remitted clinical state of BD. Preserved structure-function coupling in BD despite evidence of regional anatomical and functional deficits suggests a dynamic interplay between structural and functional subnetworks.

Project description:Recent brain imaging findings by using different methods (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, due to many limitations associated with these methods, such as poor temporal resolution and limited number of samples per second, neuroscientists could not quantify the fast dynamic connectivity of causal information networks in SAD. In this study, SAD-related changes in brain connections within the default mode network (DMN) were investigated using eight electroencephalographic (EEG) regions of interest. Partial directed coherence (PDC) was used to assess the causal influences of DMN regions on each other and indicate the changes in the DMN effective network related to SAD severity. The DMN is a large-scale brain network basically composed of the mesial prefrontal cortex (mPFC), posterior cingulate cortex (PCC)/precuneus, and lateral parietal cortex (LPC). The EEG data were collected from 88 subjects (22 control, 22 mild, 22 moderate, 22 severe) and used to estimate the effective connectivity between DMN regions at different frequency bands: delta (1-3 Hz), theta (4-8 Hz), alpha (8-12 Hz), low beta (13-21 Hz), and high beta (22-30 Hz). Among the healthy control (HC) and the three considered levels of severity of SAD, the results indicated a higher level of causal interactions for the mild and moderate SAD groups than for the severe and HC groups. Between the control and the severe SAD groups, the results indicated a higher level of causal connections for the control throughout all the DMN regions. We found significant increases in the mean PDC in the delta (p = 0.009) and alpha (p = 0.001) bands between the SAD groups. Among the DMN regions, the precuneus exhibited a higher level of causal influence than other regions. Therefore, it was suggested to be a major source hub that contributes to the mental exploration and emotional content of SAD. In contrast to the severe group, HC exhibited higher resting-state connectivity at the mPFC, providing evidence for mPFC dysfunction in the severe SAD group. Furthermore, the total Social Interaction Anxiety Scale (SIAS) was positively correlated with the mean values of the PDC of the severe SAD group, r (22) = 0.576, p = 0.006 and negatively correlated with those of the HC group, r (22) = -0.689, p = 0.001. The reported results may facilitate greater comprehension of the underlying potential SAD neural biomarkers and can be used to characterize possible targets for further medication.

Dataset Information

Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia.

Publications

Multivariate analysis reveals genetic associations of the resting default mode network in psychotic bipolar disorder and schizophrenia.

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