Strategies for translating proteomics discoveries into drug discovery for dementia

作     者：Aditi Halder Eleanor Drummond Aditi Halder;Eleanor Drummond

作者机构：School of Medical Sciences and Brain&Mind CenterUniversity of SydneyNSWSydneyAustralia Department of Aged CarePrince of Wales HospitalSydneyNSWAustralia 

出 版 物：《Neural Regeneration Research》 (中国神经再生研究（英文版）)

年 卷 期：2024年第19卷第1期

页      面：132-139页

核心收录：

学科分类：0710[理学-生物学] 1007[医学-药学(可授医学、理学学位)] 1001[医学-基础医学(可授医学、理学学位)] 10[医学] 100701[医学-药物化学] 

基　　金：supported by funding from the Bluesand Foundation,Alzheimer's Association(AARG-21-852072 and Bias Frangione Early Career Achievement Award)to ED an Australian Government Research Training Program scholarship and the University of Sydney's Brain and Mind Centre fellowship to AH。 

主　　题：Alzheimer's disease biomarkers drug development drug discovery druggability frontotemporal dementia interactome proteomics tau tauopathies therapeutics 

摘      要：Tauopathies,diseases characterized by neuropathological aggregates of tau including Alzheimer s disease and subtypes of fro ntotemporal 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 datastudies,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.