中国神经再生研究(英文版) ›› 2024, Vol. 19 ›› Issue (1): 132-139.doi: 10.4103/1673-5374.373681

• 综述:退行性病与再生 • 上一篇    下一篇

将蛋白质组学发现转化为治疗痴呆症药物的策略

  

  • 出版日期:2024-01-15 发布日期:2023-08-02

Strategies for translating proteomics discoveries into drug discovery for dementia

Aditi Halder1, 2, Eleanor Drummond1, *   

  1. 1School of Medical Sciences and Brain & Mind Center, University of Sydney, NSW, Sydney, Australia; 2Department of Aged Care, Prince of Wales Hospital, Sydney, NSW, Australia
  • Online:2024-01-15 Published:2023-08-02
  • Contact: Eleanor Drummond, PhD, eleanor.drummond@sydney.edu.au.
  • Supported by:
    This work was supported by funding from the Bluesand Foundation, Alzheimer’s Association (AARG-21-852072 and Blas Frangione Early Career Achievement Award) to ED, and an Australian Government Research Training Program scholarship and the University of Sydney’s Brain and Mind Centre fellowship to AH.

摘要: https://orcid.org/0000-0002-5466-4609 (Eleanor Drummond)

Abstract: Tauopathies, diseases characterized by neuropathological aggregates of tau including Alzheimer’s disease and subtypes of frontotemporal dementia, make up the vast majority of dementia cases. Although there have been recent developments in tauopathy biomarkers and disease-modifying treatments, ongoing progress is required to ensure these are effective, economical, and accessible for the globally ageing population. As such, continued identification of new potential drug targets and biomarkers is critical. “Big data” studies, such as proteomics, can generate information on thousands of possible new targets for dementia diagnostics and therapeutics, but currently remain underutilized due to the lack of a clear process by which targets are selected for future drug development. In this review, we discuss current tauopathy biomarkers and therapeutics, and highlight areas in need of improvement, particularly when addressing the needs of frail, comorbid and cognitively impaired populations. We highlight biomarkers which have been developed from proteomic data, and outline possible future directions in this field. We propose new criteria by which potential targets in proteomics studies can be objectively ranked as favorable for drug development, and demonstrate its application to our group’s recent tau interactome dataset as an example.

Key words: Alzheimer’s disease, biomarkers, drug development, drug discovery, druggability, frontotemporal dementia, interactome, proteomics, tau, tauopathies, therapeutics