Sturchio Andrea, Marsili Luca, Vizcarra Joaquin A, Dwivedi Alok K, Kauffman Marcelo A, Duker Andrew P, Lu Peixin, Pauciulo Michael W, Wissel Benjamin D, Hill Emily J, Stecher Benjamin, Keeling Elizabeth G, Vagal Achala S, Wang Lily, Haslam David B, Robson Matthew J, Tanner Caroline M, Hagey Daniel W, El Andaloussi Samir, Ezzat Kariem, Fleming Ronan M T, Lu Long J, Little Max A, Espay Alberto J
James J. and Joan A. Gardner Family Center for Parkinson's disease and Movement Disorders, Department of Neurology, University of Cincinnati, Cincinnati, OH, United States.
Division of Biostatistics and Epidemiology, Department of Biomedical Sciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center, El Paso, TX, United States.
Front Aging Neurosci. 2020 Oct 8;12:553635. doi: 10.3389/fnagi.2020.553635. eCollection 2020.
Ongoing biomarker development programs have been designed to identify serologic or imaging signatures of clinico-pathologic entities, assuming distinct biological boundaries between them. Identified putative biomarkers have exhibited large variability and inconsistency between cohorts, and remain inadequate for selecting suitable recipients for potential disease-modifying interventions. We launched the Cincinnati Cohort Biomarker Program (CCBP) as a population-based, phenotype-agnostic longitudinal study. While patients affected by a wide range of neurodegenerative disorders will be deeply phenotyped using clinical, imaging, and mobile health technologies, analyses will not be anchored on phenotypic clusters but on bioassays of to-be-repurposed medications as well as on genomics, transcriptomics, proteomics, metabolomics, epigenomics, microbiomics, and pharmacogenomics analyses blinded to phenotypic data. Unique features of this cohort study include (1) a reverse biology-to-phenotype direction of biomarker development in which clinical, imaging, and mobile health technologies are subordinate to biological signals of interest; (2) hypothesis free, causally- and data driven-based analyses; (3) inclusive recruitment of patients with neurodegenerative disorders beyond clinical criteria-meeting patients with Parkinson's and Alzheimer's diseases, and (4) a large number of longitudinally followed participants. The parallel development of serum bioassays will be aimed at linking biologically suitable subjects to already available drugs with repurposing potential in future proof-of-concept adaptive clinical trials. Although many challenges are anticipated, including the unclear pathogenic relevance of identifiable biological signals and the possibility that some signals of importance may not yet be measurable with current technologies, this cohort study abandons the anchoring role of clinico-pathologic criteria in favor of biomarker-driven disease subtyping to facilitate future biosubtype-specific disease-modifying therapeutic efforts.
正在进行的生物标志物开发项目旨在识别临床病理实体的血清学或影像学特征，假定它们之间存在明显的生物学界限。已识别出的假定生物标志物在不同队列之间表现出很大的变异性和不一致性，并且在为潜在的疾病修饰干预选择合适的接受者方面仍然不足。我们启动了辛辛那提队列生物标志物项目（CCBP），这是一项基于人群、不考虑表型的纵向研究。虽然将使用临床、影像学和移动健康技术对受多种神经退行性疾病影响的患者进行深入的表型分析，但分析将不基于表型聚类，而是基于待重新利用药物的生物测定以及对表型数据不知情的基因组学、转录组学、蛋白质组学、代谢组学、表观基因组学、微生物组学和药物基因组学分析。这项队列研究的独特之处包括：（1）生物标志物开发从生物学到表型的反向方向，其中临床、影像学和移动健康技术从属于感兴趣的生物信号；（2）无假设、基于因果和数据驱动的分析；（3）纳入超出临床标准的神经退行性疾病患者，如帕金森病和阿尔茨海默病患者；（4）大量纵向随访的参与者。血清生物测定的平行开发旨在将生物学上合适的受试者与未来概念验证适应性临床试验中具有重新利用潜力的现有药物联系起来。尽管预计会有许多挑战，包括可识别生物信号的致病相关性不明确以及一些重要信号可能目前无法用现有技术测量的可能性，但这项队列研究放弃了临床病理标准的锚定作用，转而支持生物标志物驱动的疾病亚型分类，以促进未来针对生物亚型的疾病修饰治疗努力。
