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Unraveling schizophrenia replicable functional connectivity disruption patterns across sites
Functional connectivity (FC) disruption is a remarkable characteristic of schizophrenia. However, heterogeneous patterns reported across sites severely hindered its clinical generalization. Based on qualified nodal‐based FC of 340 schizophrenia patients (SZ) and 348 normal controls (NC) acquired fro...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783440/ https://www.ncbi.nlm.nih.gov/pubmed/36222054 http://dx.doi.org/10.1002/hbm.26108 |
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author | Du, Xiaotong Wei, Xiaotong Ding, Hao Yu, Ying Xie, Yingying Ji, Yi Zhang, Yu Chai, Chao Liang, Meng Li, Jie Zhuo, Chuanjun Yu, Chunshui Qin, Wen |
author_facet | Du, Xiaotong Wei, Xiaotong Ding, Hao Yu, Ying Xie, Yingying Ji, Yi Zhang, Yu Chai, Chao Liang, Meng Li, Jie Zhuo, Chuanjun Yu, Chunshui Qin, Wen |
author_sort | Du, Xiaotong |
collection | PubMed |
description | Functional connectivity (FC) disruption is a remarkable characteristic of schizophrenia. However, heterogeneous patterns reported across sites severely hindered its clinical generalization. Based on qualified nodal‐based FC of 340 schizophrenia patients (SZ) and 348 normal controls (NC) acquired from seven different scanners, this study compared four commonly used site‐effect correction methods in removing the site‐related heterogeneities, and then tried to cluster the abnormal FCs into several replicable and independent disrupted subnets across sites, related them to clinical symptoms, and evaluated their potentials in schizophrenia classification. Among the four site‐related heterogeneity correction methods, ComBat harmonization (F1 score: 0.806 ± 0.145) achieved the overall best balance between sensitivity and false discovery rate in unraveling the aberrant FCs of schizophrenia in the local and public data sets. Hierarchical clustering analysis identified three replicable FC disruption subnets across the local and public data sets: hypo‐connectivity within sensory areas (Net1), hypo‐connectivity within thalamus, striatum, and ventral attention network (Net2), and hyper‐connectivity between thalamus and sensory processing system (Net3). Notably, the derived composite FC within Net1 was negatively correlated with hostility and disorientation in the public validation set (p < .05). Finally, the three subnet‐specific composite FCs (Best area under the receiver operating characteristic curve [AUC] = 0.728) can robustly and meaningfully discriminate the SZ from NC with comparable performance with the full identified FCs features (best AUC = 0.765) in the out‐of‐sample public data set (Z = −1.583, p = .114). In conclusion, ComBat harmonization was most robust in detecting aberrant connectivity for schizophrenia. Besides, the three subnet‐specific composite FC measures might be replicable neuroimaging markers for schizophrenia. |
format | Online Article Text |
id | pubmed-9783440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97834402022-12-27 Unraveling schizophrenia replicable functional connectivity disruption patterns across sites Du, Xiaotong Wei, Xiaotong Ding, Hao Yu, Ying Xie, Yingying Ji, Yi Zhang, Yu Chai, Chao Liang, Meng Li, Jie Zhuo, Chuanjun Yu, Chunshui Qin, Wen Hum Brain Mapp Research Articles Functional connectivity (FC) disruption is a remarkable characteristic of schizophrenia. However, heterogeneous patterns reported across sites severely hindered its clinical generalization. Based on qualified nodal‐based FC of 340 schizophrenia patients (SZ) and 348 normal controls (NC) acquired from seven different scanners, this study compared four commonly used site‐effect correction methods in removing the site‐related heterogeneities, and then tried to cluster the abnormal FCs into several replicable and independent disrupted subnets across sites, related them to clinical symptoms, and evaluated their potentials in schizophrenia classification. Among the four site‐related heterogeneity correction methods, ComBat harmonization (F1 score: 0.806 ± 0.145) achieved the overall best balance between sensitivity and false discovery rate in unraveling the aberrant FCs of schizophrenia in the local and public data sets. Hierarchical clustering analysis identified three replicable FC disruption subnets across the local and public data sets: hypo‐connectivity within sensory areas (Net1), hypo‐connectivity within thalamus, striatum, and ventral attention network (Net2), and hyper‐connectivity between thalamus and sensory processing system (Net3). Notably, the derived composite FC within Net1 was negatively correlated with hostility and disorientation in the public validation set (p < .05). Finally, the three subnet‐specific composite FCs (Best area under the receiver operating characteristic curve [AUC] = 0.728) can robustly and meaningfully discriminate the SZ from NC with comparable performance with the full identified FCs features (best AUC = 0.765) in the out‐of‐sample public data set (Z = −1.583, p = .114). In conclusion, ComBat harmonization was most robust in detecting aberrant connectivity for schizophrenia. Besides, the three subnet‐specific composite FC measures might be replicable neuroimaging markers for schizophrenia. John Wiley & Sons, Inc. 2022-10-12 /pmc/articles/PMC9783440/ /pubmed/36222054 http://dx.doi.org/10.1002/hbm.26108 Text en © 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Du, Xiaotong Wei, Xiaotong Ding, Hao Yu, Ying Xie, Yingying Ji, Yi Zhang, Yu Chai, Chao Liang, Meng Li, Jie Zhuo, Chuanjun Yu, Chunshui Qin, Wen Unraveling schizophrenia replicable functional connectivity disruption patterns across sites |
title | Unraveling schizophrenia replicable functional connectivity disruption patterns across sites |
title_full | Unraveling schizophrenia replicable functional connectivity disruption patterns across sites |
title_fullStr | Unraveling schizophrenia replicable functional connectivity disruption patterns across sites |
title_full_unstemmed | Unraveling schizophrenia replicable functional connectivity disruption patterns across sites |
title_short | Unraveling schizophrenia replicable functional connectivity disruption patterns across sites |
title_sort | unraveling schizophrenia replicable functional connectivity disruption patterns across sites |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783440/ https://www.ncbi.nlm.nih.gov/pubmed/36222054 http://dx.doi.org/10.1002/hbm.26108 |
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