Zhenfu Wen, Mira Z. Hammoud, Carole E. Siegel, Eugene M. Laska, Duna Abu-Amara, Amit Etkin, Mohammed R. Milad, Charles R. Marmar
{"title":"基于神经影像的精神病异质性生物标志物亚型变异性","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&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":"{\"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&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}","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}
Neuroimaging-based variability in subtyping biomarkers for psychiatric heterogeneity
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.
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.