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Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives.

ABSTRACT: Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.We compared 70 schizophrenia and 64 psychotic bipolar probands, their respective unaffected first-degree relatives (n = 70, and n = 52), and 118 healthy subjects, all group age-, gender-, and ethnicity-matched. We used functional network connectivity analysis to measure differential connectivity among 16 functional magnetic resonance imaging resting state networks. First, we examined connectivity differences between probands and control subjects. Next, we probed these dysfunctional connections in relatives for potential endophenotypes. Network connectivity was then correlated with Positive and Negative Syndrome Scale (PANSS) scores to reveal clinical relationships.Three different network pairs were differentially connected in probands (false-discovery rate corrected q < .05) involving five individual resting-state networks: (A) fronto/occipital, (B) anterior default mode/prefrontal, (C) meso/paralimbic, (D) fronto-temporal/paralimbic, and (E) sensory-motor. One abnormal pair was unique to schizophrenia, (C-E), one unique to bipolar, (C-D), and one (A-B) was shared. Two of these three combinations (A-B, C-E) were also abnormal in bipolar relatives but none was normal in schizophrenia relatives (nonsignificant trend for C-E). The paralimbic circuit (C-D), which uniquely distinguished bipolar probands, contained multiple mood-relevant regions. Network relationship C-D correlated significantly with PANSS negative scores in bipolar probands, and A-B with PANSS positive and general scores in schizophrenia.Schizophrenia and psychotic bipolar probands share several abnormal resting state network connections, but there are also unique neural network underpinnings between disorders. We identified specific connections that might also be candidate psychosis endophenotypes.

SUBMITTER: Meda SA

PROVIDER: S-EPMC3968680 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives.

Meda Shashwath A SA Gill Adrienne A Stevens Michael C MC Lorenzoni Raymond P RP Glahn David C DC Calhoun Vince D VD Sweeney John A JA Tamminga Carol A CA Keshavan Matcheri S MS Thaker Gunvant G Pearlson Godfrey D GD

Biological psychiatry 20120307 10

<h4>Background</h4>Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.<h4>Methods</h4>We compared 70 schizophrenia and 64 psychotic bipolar probands, their respective unaffected first-degree relatives (n = 70, and n = 52), and 118 healthy subjects, all group age-, gender-, and ethnicity-matched. We used functional network connectivity analysis to measure differential connectivity among 16 functional magne ...[more]

PMID: 22401986

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Project description:Meehl conceptualized schizotypy as the phenotypic manifestations of a neural integrative defect resulting from a schizophrenia diathesis. The majority of schizotypy studies recruited subjects from the general population and revealed a multidimensional construct. This 2-phase investigation first examined the clustering of schizotypy in 194 unaffected relatives of schizophrenia patients using the Chapman Psychosis Proneness scales and then directly compared the cognitive profiles of negative schizotypal individuals and positive schizotypal individuals with schizophrenia patients and controls. In the first phase, cluster analysis categorized 194 unaffected relatives of schizophrenia patients into positive schizotypy (n = 33), negative schizotypy (n = 66), mixed schizotypy (n = 27), and low schizotypy (n = 64). Positive schizotypal participants showed more self-report pleasure experiences than negative schizotypal participants, replicating earlier cluster analytic findings. In the second phase, 27 negative schizotypal individuals, 18 positive schizotypal individuals, 19 schizophrenia patients, and 29 controls were recruited. Although the groups were matched in terms of age, gender, and IQ, they differed significantly in cognitive profiles. While schizophrenia patients exhibited the broadest cognitive impairments, negative schizotypal participants exhibited visual memory, working memory, and verbal fluency impairments, and positive schizotypal participants exhibited logical memory, visual memory, working memory, and theory-of-mind impairments. Among people with familial risk of schizophrenia, individuals exhibiting positive rather than negative schizotypal features resembled schizophrenia patients in cognitive profiles. Using the psychometric-familial method to identify schizotypy, our findings support the heterogeneity of schizotypy as well as the potential utility of the positive schizotypy dimension in genetically high-risk individuals to predict the risk of developing schizophrenia.

Dataset Information

Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives.

Publications

Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives.

Similar Datasets

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