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Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease.
Guo, Yu; Chen, Shi-Dong; You, Jia; Huang, Shu-Yi; Chen, Yi-Lin; Zhang, Yi; Wang, Lin-Bo; He, Xiao-Yu; Deng, Yue-Ting; Zhang, Ya-Ru; Huang, Yu-Yuan; Dong, Qiang; Feng, Jian-Feng; Cheng, Wei; Yu, Jin-Tai.
Afiliação
  • Guo Y; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Chen SD; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • You J; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Huang SY; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
  • Chen YL; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Zhang Y; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Wang LB; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • He XY; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
  • Deng YT; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Zhang YR; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Huang YY; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Dong Q; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Feng JF; Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
  • Cheng W; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
  • Yu JT; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
Nat Hum Behav ; 2024 Jul 10.
Article em En | MEDLINE | ID: mdl-38987357
ABSTRACT
Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Nat Hum Behav Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Nat Hum Behav Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido