Department of Molecular and Human Genetics, Baylor College of Medicine (BCM), Houston, Texas, USA.
Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital (TCH), Houston, Texas, USA.
Hum Mutat. 2022 Jun;43(6):743-759. doi: 10.1002/humu.24364. Epub 2022 Mar 24.
Next-generation sequencing is a prevalent diagnostic tool for undiagnosed diseases and has played a significant role in rare disease gene discovery. Although this technology resolves some cases, others are given a list of possibly damaging genetic variants necessitating functional studies. Productive collaborations between scientists, clinicians, and patients (affected individuals) can help resolve such medical mysteries and provide insights into in vivo function of human genes. Furthermore, facilitating interactions between scientists and research funders, including nonprofit organizations or commercial entities, can dramatically reduce the time to translate discoveries from bench to bedside. Several systems designed to connect clinicians and researchers with a shared gene of interest have been successful. However, these platforms exclude some stakeholders based on their role or geography. Here we describe ModelMatcher, a global online matchmaking tool designed to facilitate cross-disciplinary collaborations, especially between scientists and other stakeholders of rare and undiagnosed disease research. ModelMatcher is integrated into the Rare Diseases Models and Mechanisms Network and Matchmaker Exchange, allowing users to identify potential collaborators in other registries. This living database decreases the time from when a scientist or clinician is making discoveries regarding their genes of interest, to when they identify collaborators and sponsors to facilitate translational and therapeutic research.
下一代测序是一种常见的诊断工具,用于诊断不明疾病,并在发现罕见病基因方面发挥了重要作用。尽管这项技术解决了一些病例,但其他病例则会得到一系列可能具有破坏性的遗传变异,需要进行功能研究。科学家、临床医生和患者(受影响的个体)之间的富有成效的合作可以帮助解决这些医学谜团,并深入了解人类基因的体内功能。此外,促进科学家和研究资助者之间的互动,包括非营利组织或商业实体,可以大大缩短从实验室到病床的发现转化时间。已经有几个旨在将临床医生和研究人员与共同感兴趣的基因联系起来的系统取得了成功。然而,这些平台基于其角色或地理位置排除了一些利益相关者。在这里,我们描述了 ModelMatcher,这是一个全球性的在线匹配工具,旨在促进跨学科合作,特别是科学家和其他罕见和未确诊疾病研究的利益相关者之间的合作。ModelMatcher 集成到罕见疾病模型和机制网络和匹配交换中,允许用户在其他注册处识别潜在的合作者。这个活的数据库缩短了从科学家或临床医生发现他们感兴趣的基因到他们确定合作者和赞助商以促进转化和治疗研究的时间。