Multimodal brain deficits shared in early-onset and adult-onset schizophrenia predict positive symptoms regardless of illness stage | |
Feng, Aichen1,2,3; Luo, Na1,2; Zhao, Wentao4; Calhoun, Vince D.5,6; Jiang, Rongtao7; Zhi, Dongmei8; Shi, Weiyang1,2,3; Jiang, Tianzi1,2,3; Yu, Shan1,2,3; Xu, Yong4; Liu, Sha4; Sui, Jing5,6,8 | |
发表期刊 | HUMAN BRAIN MAPPING |
ISSN | 1065-9471 |
2022-04-07 | |
页码 | 12 |
通讯作者 | Liu, Sha(liusha@sxmu.edu.cn) ; Sui, Jing(jsui@bnu.edu.cn) |
摘要 | Incidence of schizophrenia (SZ) has two predominant peaks, in adolescent and young adult. Early-onset schizophrenia provides an opportunity to explore the neuropathology of SZ early in the disorder and without the confound of antipsychotic mediation. However, it remains unexplored what deficits are shared or differ between adolescent early-onset (EOS) and adult-onset schizophrenia (AOS) patients. Here, based on 529 participants recruited from three independent cohorts, we explored AOS and EOS common and unique co-varying patterns by jointly analyzing three MRI features: fractional amplitude of low-frequency fluctuations (fALFF), gray matter (GM), and functional network connectivity (FNC). Furthermore, a prediction model was built to evaluate whether the common deficits in drug-naive SZ could be replicated in chronic patients. Results demonstrated that (1) both EOS and AOS patients showed decreased fALFF and GM in default mode network, increased fALFF and GM in the sub-cortical network, and aberrant FNC primarily related to middle temporal gyrus; (2) the commonly identified regions in drug-naive SZ correlate with PANSS positive significantly, which can also predict PANSS positive in chronic SZ with longer duration of illness. Collectively, results suggest that multimodal imaging signatures shared by two types of drug-naive SZ are also associated with positive symptom severity in chronic SZ and may be vital for understanding the progressive schizophrenic brain structural and functional deficits. |
关键词 | early-onset schizophrenia (EOS) MRI multimodal fusion PANSS symptom prediction |
DOI | 10.1002/hbm.25862 |
关键词[WOS] | ANTERIOR CINGULATE CORTEX ; FUNCTIONAL CONNECTIVITY ; DEFAULT-MODE ; 1ST-EPISODE SCHIZOPHRENIA ; ANTIPSYCHOTIC TREATMENT ; MENTAL-DISORDERS ; NETWORK ; FMRI ; ABNORMALITIES ; STRIATUM |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2017YFA0105203] ; National Natural Sciences Foundation of China[82022035] ; National Natural Sciences Foundation of China[61773380] ; National Natural Sciences Foundation of China[82001450] ; National Natural Sciences Foundation of China[81701326] ; China Postdoctoral Science Foundation[BX20200364] ; National Institute of Health[R01MH117107] ; National Institute of Health[P20GM103472] ; National Institute of Health[P30GM122734] ; Shanxi Provincial Science and Technology achievements transformation and guidance project[201904D131020] ; Special Project of Scientific Research Plan Talents of Shanxi Provincial Health Commission[2020081] ; Shanxi Province Overseas Students Science and Technology Activity Funding Project[20200038] ; National Science Foundation[1539067] ; National Science Foundation[2112455] |
项目资助者 | National Key Research and Development Program of China ; National Natural Sciences Foundation of China ; China Postdoctoral Science Foundation ; National Institute of Health ; Shanxi Provincial Science and Technology achievements transformation and guidance project ; Special Project of Scientific Research Plan Talents of Shanxi Provincial Health Commission ; Shanxi Province Overseas Students Science and Technology Activity Funding Project ; National Science Foundation |
WOS研究方向 | Neurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Neurosciences ; Neuroimaging ; Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000779378100001 |
出版者 | WILEY |
七大方向——子方向分类 | 脑网络分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48265 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
通讯作者 | Liu, Sha; Sui, Jing |
作者单位 | 1.Chinese Acad Sci, Brainnetome Ctr, Beijing, Peoples R China 2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 4.Shanxi Med Univ, Dept Psychiat, Clin Med Coll 1, Hosp 1, Taiyuan 030000, Peoples R China 5.Georgia State Univ, Triinst Ctr Translat Res Neuroimaging & Data Sci, Georgia Inst Technol, Atlanta, GA 30303 USA 6.Emory Univ, Atlanta, GA 30322 USA 7.Yale Univ, Dept Radiol & Biomed Imaging, New Haven, CT USA 8.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Feng, Aichen,Luo, Na,Zhao, Wentao,et al. Multimodal brain deficits shared in early-onset and adult-onset schizophrenia predict positive symptoms regardless of illness stage[J]. HUMAN BRAIN MAPPING,2022:12. |
APA | Feng, Aichen.,Luo, Na.,Zhao, Wentao.,Calhoun, Vince D..,Jiang, Rongtao.,...&Sui, Jing.(2022).Multimodal brain deficits shared in early-onset and adult-onset schizophrenia predict positive symptoms regardless of illness stage.HUMAN BRAIN MAPPING,12. |
MLA | Feng, Aichen,et al."Multimodal brain deficits shared in early-onset and adult-onset schizophrenia predict positive symptoms regardless of illness stage".HUMAN BRAIN MAPPING (2022):12. |
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