Neuroimaging-based variability in subtyping biomarkers for psychiatric heterogeneity

IF 9.6 1区 医学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Zhenfu Wen, Mira Z. Hammoud, Carole E. Siegel, Eugene M. Laska, Duna Abu-Amara, Amit Etkin, Mohammed R. Milad, Charles R. Marmar
{"title":"Neuroimaging-based variability in subtyping biomarkers for psychiatric heterogeneity","authors":"Zhenfu Wen, Mira Z. Hammoud, Carole E. Siegel, Eugene M. Laska, Duna Abu-Amara, Amit Etkin, Mohammed R. Milad, Charles R. Marmar","doi":"10.1038/s41380-024-02807-y","DOIUrl":null,"url":null,"abstract":"<p>Neuroimaging-based subtyping is increasingly used to explain heterogeneity in psychiatric disorders. However, the clinical utility of these subtyping efforts remains unclear, and replication has been challenging. Here we examined how the choice of neuroimaging measures influences the derivation of neuro-subtypes and the consequences for clinical delineation. On a clinically heterogeneous dataset (total <i>n</i> = 566) that included controls (<i>n</i> = 268) and cases (<i>n</i> = 298) of psychiatric conditions, including individuals diagnosed with post-traumatic stress disorder (PTSD), traumatic brain injury (TBI), and comorbidity of both (PTSD&amp;TBI), we identified neuro-subtypes among the cases using either structural, resting-state, or task-based measures. The neuro-subtypes for each modality had high internal validity but did not significantly differ in their clinical and cognitive profiles. We further show that the choice of neuroimaging measures for subtyping substantially impacts the identification of neuro-subtypes, leading to low concordance across subtyping solutions. Similar variability in neuro-subtyping was found in an independent dataset (<i>n</i> = 1642) comprised of major depression disorder (MDD, <i>n</i> = 848) and controls (<i>n</i> = 794). Our results suggest that the highly anticipated relationships between neuro-subtypes and clinical features may be difficult to discover.</p>","PeriodicalId":19008,"journal":{"name":"Molecular Psychiatry","volume":"3 1","pages":""},"PeriodicalIF":9.6000,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Psychiatry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41380-024-02807-y","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Neuroimaging-based subtyping is increasingly used to explain heterogeneity in psychiatric disorders. However, the clinical utility of these subtyping efforts remains unclear, and replication has been challenging. Here we examined how the choice of neuroimaging measures influences the derivation of neuro-subtypes and the consequences for clinical delineation. On a clinically heterogeneous dataset (total n = 566) that included controls (n = 268) and cases (n = 298) of psychiatric conditions, including individuals diagnosed with post-traumatic stress disorder (PTSD), traumatic brain injury (TBI), and comorbidity of both (PTSD&TBI), we identified neuro-subtypes among the cases using either structural, resting-state, or task-based measures. The neuro-subtypes for each modality had high internal validity but did not significantly differ in their clinical and cognitive profiles. We further show that the choice of neuroimaging measures for subtyping substantially impacts the identification of neuro-subtypes, leading to low concordance across subtyping solutions. Similar variability in neuro-subtyping was found in an independent dataset (n = 1642) comprised of major depression disorder (MDD, n = 848) and controls (n = 794). Our results suggest that the highly anticipated relationships between neuro-subtypes and clinical features may be difficult to discover.

Abstract Image

基于神经影像的精神病异质性生物标志物亚型变异性
基于神经影像学的亚型分析越来越多地被用来解释精神疾病的异质性。然而,这些亚型划分工作的临床实用性仍不明确,复制工作也一直面临挑战。在此,我们研究了神经影像学测量方法的选择如何影响神经亚型的推导及其对临床分型的影响。在一个临床异质性数据集(总人数为 566 人)中,包括精神疾病的对照组(人数为 268 人)和病例组(人数为 298 人),其中包括被诊断为创伤后应激障碍(PTSD)、创伤性脑损伤(TBI)和两者合并症(PTSD&TBI)的患者。每种模式的神经亚型都具有较高的内部有效性,但在临床和认知特征方面并无显著差异。我们进一步发现,选择神经影像测量方法进行亚型划分会对神经亚型的识别产生重大影响,导致亚型划分方案之间的一致性较低。在一个由重度抑郁症(MDD,n = 848)和对照组(n = 794)组成的独立数据集(n = 1642)中也发现了神经亚型鉴定的类似变异性。我们的研究结果表明,神经亚型与临床特征之间的预期关系可能难以发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Molecular Psychiatry
Molecular Psychiatry 医学-精神病学
CiteScore
20.50
自引率
4.50%
发文量
459
审稿时长
4-8 weeks
期刊介绍: Molecular Psychiatry focuses on publishing research that aims to uncover the biological mechanisms behind psychiatric disorders and their treatment. The journal emphasizes studies that bridge pre-clinical and clinical research, covering cellular, molecular, integrative, clinical, imaging, and psychopharmacology levels.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信