| Autor: |
Pauline eSoh, Balaji eNarayanan, Sabin eKhadka, Vince D Calhoun, Matcheri S Keshavan, Carol A Tamminga, John A Sweeney, Brett A Clementz, Godfrey D Pearlson |
| Jazyk: |
angličtina |
| Rok vydání: |
2015 |
| Předmět: |
|
| Zdroj: |
Frontiers in Psychiatry, Vol 6 (2015) |
| Druh dokumentu: |
article |
| ISSN: |
1664-0640 |
| DOI: |
10.3389/fpsyt.2015.00162 |
| Popis: |
Many studies have examined either electroencephalogram (EEG) frequency activity or gray matter volumes (GMV) in various psychoses (including schizophrenia, schizoaffective and psychotic bipolar disorder). Prior work demonstrated similar EEG and gray matter abnormalities in both schizophrenia and psychotic bipolar disorder. Integrating EEG and GMV and jointly analyzing the combined data fully elucidates the linkage between the two and may provide better biomarker- or endophenotype-specificity for a particular illness. Joint exploratory investigations of EEG and GMV are scarce in the literature and the relationship between the two in psychosis is even less explored. We investigated a joint multivariate model to test whether the linear relationship or linkage between awake EEG (AEEG) frequency activity and GMV is abnormal across the psychosis dimension and if such effects are also present in first-degree relatives.We assessed 607 subjects comprising 264 probands (105 schizophrenia (SZ), 72 schizoaffective (SZA) and 87 psychotic bipolar disorder (PBP)), 233 of their first degree relatives (82 SZ relatives (SZR), 71 SZA relatives (SZAR) and 80 PBP relatives (PBPR)) and 110 healthy comparison subjects (HC). All subjects underwent structural MRI (sMRI) and EEG scans. Frequency activity and voxel based morphometric GMV were derived from EEG and sMRI data respectively. Seven AEEG frequency and gray matter components were extracted using Joint independent component analysis (jICA). The loading coefficients (LC) were examined for group differences using analysis of covariance. Further, the LCs were correlated with psychopathology scores to identify relationship with clinical symptoms. Joint ICA revealed a single component differentiating SZ from HC (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
