Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia
Abstract Background Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific b...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2023-01-01
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| Series: | European Psychiatry |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S092493382302446X/type/journal_article |
| _version_ | 1797663528991064064 |
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| author | Chao Chai Hao Ding Xiaotong Du Yingying Xie Weiqi Man Yu Zhang Yi Ji Meng Liang Bin Zhang Yuping Ning Chuanjun Zhuo Chunshui Yu Wen Qin |
| author_facet | Chao Chai Hao Ding Xiaotong Du Yingying Xie Weiqi Man Yu Zhang Yi Ji Meng Liang Bin Zhang Yuping Ning Chuanjun Zhuo Chunshui Yu Wen Qin |
| author_sort | Chao Chai |
| collection | DOAJ |
| description |
Abstract
Background
Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated.
Methods
A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively.
Results
Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen’s Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western).
Conclusions
These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.
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| first_indexed | 2024-03-11T19:15:58Z |
| format | Article |
| id | doaj.art-40861882fda743b7a7d7179cb01edee6 |
| institution | Directory Open Access Journal |
| issn | 0924-9338 1778-3585 |
| language | English |
| last_indexed | 2024-03-11T19:15:58Z |
| publishDate | 2023-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | European Psychiatry |
| spelling | doaj.art-40861882fda743b7a7d7179cb01edee62023-10-09T07:32:43ZengCambridge University PressEuropean Psychiatry0924-93381778-35852023-01-016610.1192/j.eurpsy.2023.2446Dissociation between neuroanatomical and symptomatic subtypes in schizophreniaChao Chai0https://orcid.org/0000-0001-6267-9109Hao Ding1Xiaotong Du2https://orcid.org/0000-0003-2092-0448Yingying Xie3Weiqi Man4Yu Zhang5Yi Ji6https://orcid.org/0000-0002-5125-1163Meng Liang7https://orcid.org/0000-0003-0916-520XBin Zhang8https://orcid.org/0000-0002-9280-8247Yuping Ning9Chuanjun Zhuo10Chunshui Yu11https://orcid.org/0000-0001-5648-5199Wen Qin12https://orcid.org/0000-0002-9121-8296Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, ChinaSchool of Medical Imaging, Tianjin Medical University, Tianjin, ChinaDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, ChinaDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, ChinaDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, ChinaDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, ChinaDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, ChinaSchool of Medical Imaging, Tianjin Medical University, Tianjin, ChinaDepartment of Psychiatry, Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, ChinaDepartment of Psychiatry, Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, ChinaDepartment of Psychiatry, Tianjin Fourth Center Hospital, Tianjin, ChinaDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China School of Medical Imaging, Tianjin Medical University, Tianjin, ChinaDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China Abstract Background Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated. Methods A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively. Results Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen’s Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western). Conclusions These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia. https://www.cambridge.org/core/product/identifier/S092493382302446X/type/journal_articlegray matter volumeheterogeneitymagnetic resonance imagingPositive and Negative Syndrome Scaleschizophreniasubtypes |
| spellingShingle | Chao Chai Hao Ding Xiaotong Du Yingying Xie Weiqi Man Yu Zhang Yi Ji Meng Liang Bin Zhang Yuping Ning Chuanjun Zhuo Chunshui Yu Wen Qin Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia European Psychiatry gray matter volume heterogeneity magnetic resonance imaging Positive and Negative Syndrome Scale schizophrenia subtypes |
| title | Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia |
| title_full | Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia |
| title_fullStr | Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia |
| title_full_unstemmed | Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia |
| title_short | Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia |
| title_sort | dissociation between neuroanatomical and symptomatic subtypes in schizophrenia |
| topic | gray matter volume heterogeneity magnetic resonance imaging Positive and Negative Syndrome Scale schizophrenia subtypes |
| url | https://www.cambridge.org/core/product/identifier/S092493382302446X/type/journal_article |
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