Differences in Resting-State Functional Magnetic Resonance Imaging Functional Network Connectivity Between Schizophrenia and Psychotic Bipolar Probands and Their Unaffected First-Degree Relatives
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 sub...
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| Published in | Biological psychiatry (1969) Vol. 71; no. 10; pp. 881 - 889 |
|---|---|
| Main Authors | , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
Elsevier Inc
15.05.2012
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0006-3223 1873-2402 1873-2402 |
| DOI | 10.1016/j.biopsych.2012.01.025 |
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| 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. |
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| AbstractList | Background Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders. Methods 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. Results 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. Conclusions 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. 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. Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.BACKGROUNDSchizophrenia 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.METHODSWe 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.RESULTSThree 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.CONCLUSIONSSchizophrenia 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. |
| Author | Glahn, David C. Gill, Adrienne Lorenzoni, Raymond P. Meda, Shashwath A. Keshavan, Matcheri S. Tamminga, Carol A. Pearlson, Godfrey D. Stevens, Michael C. Sweeney, John A. Calhoun, Vince D. Thaker, Gunvant |
| Author_xml | – sequence: 1 givenname: Shashwath A. surname: Meda fullname: Meda, Shashwath A. organization: Olin Neuropsychiatry Research Center, Hartford Hospital/Institute of Living, Hartford, Connecticut – sequence: 2 givenname: Adrienne surname: Gill fullname: Gill, Adrienne organization: Olin Neuropsychiatry Research Center, Hartford Hospital/Institute of Living, Hartford, Connecticut – sequence: 3 givenname: Michael C. surname: Stevens fullname: Stevens, Michael C. organization: Olin Neuropsychiatry Research Center, Hartford Hospital/Institute of Living, Hartford, Connecticut – sequence: 4 givenname: Raymond P. surname: Lorenzoni fullname: Lorenzoni, Raymond P. organization: Olin Neuropsychiatry Research Center, Hartford Hospital/Institute of Living, Hartford, Connecticut – sequence: 5 givenname: David C. surname: Glahn fullname: Glahn, David C. organization: Olin Neuropsychiatry Research Center, Hartford Hospital/Institute of Living, Hartford, Connecticut – sequence: 6 givenname: Vince D. surname: Calhoun fullname: Calhoun, Vince D. organization: Olin Neuropsychiatry Research Center, Hartford Hospital/Institute of Living, Hartford, Connecticut – sequence: 7 givenname: John A. surname: Sweeney fullname: Sweeney, John A. organization: Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois – sequence: 8 givenname: Carol A. surname: Tamminga fullname: Tamminga, Carol A. organization: Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, Texas – sequence: 9 givenname: Matcheri S. surname: Keshavan fullname: Keshavan, Matcheri S. organization: Department of Psychiatry, Harvard Medical School, Cambridge, Massachusetts – sequence: 10 givenname: Gunvant surname: Thaker fullname: Thaker, Gunvant organization: Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland – sequence: 11 givenname: Godfrey D. surname: Pearlson fullname: Pearlson, Godfrey D. email: godfrey.pearlson@yale.edu organization: Olin Neuropsychiatry Research Center, Hartford Hospital/Institute of Living, Hartford, Connecticut |
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| Snippet | Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.
We compared 70... Background Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.... Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both... |
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| SubjectTerms | Adult Adult and adolescent clinical studies Biological and medical sciences Bipolar Bipolar Disorder - genetics Bipolar Disorder - physiopathology Brain - physiopathology Case-Control Studies default mode Female functional connectivity Functional Neuroimaging gene Humans Magnetic Resonance Imaging Male Medical sciences Middle Aged Psychiatry Psychology. Psychoanalysis. Psychiatry Psychopathology. Psychiatry Psychoses Psychotic Disorders - physiopathology relatives resting state Schizophrenia Schizophrenia - genetics Schizophrenia - physiopathology |
| Title | Differences in Resting-State Functional Magnetic Resonance Imaging Functional Network Connectivity Between Schizophrenia and Psychotic Bipolar Probands and Their Unaffected First-Degree Relatives |
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