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Might, Matthew; Wilsey, Matt

doi:10.1038/gim.2014.130

Cited by 2 publications

(3 citation statements)

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“…29 Not only can UDN researchers share data with those outside of the network, but UDN patients and families can also lead their own datasharing efforts, as illustrated by the work of Matthew Might, who is a family advisor to the UDN coordinating center. 30 Collaborative Clinical Sites To extend the reach of the UDN approach, we welcome the participation of investigators who are interested in collaborating with the network. A number of international sites have expressed interest in learning from the UDN experience, so as a first step, we announced the opportunity to participate as a UDN International Collaborative Clinical Site.…”

Section: External Data Sharingmentioning

confidence: 99%

The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease

Adams

Alejandro³

et al. 2017

The American Journal of Human Genetics

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Diagnosis at the edges of our knowledge calls upon clinicians to be data driven, cross-disciplinary, and collaborative in unprecedented ways. Exact disease recognition, an element of the concept of precision in medicine, requires new infrastructure that spans geography, institutional boundaries, and the divide between clinical care and research. The National Institutes of Health (NIH) Common Fund supports the Undiagnosed Diseases Network (UDN) as an exemplar of this model of precise diagnosis. Its goals are to forge a strategy to accelerate the diagnosis of rare or previously unrecognized diseases, to improve recommendations for clinical management, and to advance research, especially into disease mechanisms. The network will achieve these objectives by evaluating patients with undiagnosed diseases, fostering a breadth of expert collaborations, determining best practices for translating the strategy into medical centers nationwide, and sharing findings, data, specimens, and approaches with the scientific and medical communities. Building the UDN has already brought insights to human and medical geneticists. The initial focus has been on data sharing, establishing common protocols for institutional review boards and data sharing, creating protocols for referring and evaluating patients, and providing DNA sequencing, metabolomic analysis, and functional studies in model organisms. By extending this precision diagnostic model nationally, we strive to meld clinical and research objectives, improve patient outcomes, and contribute to medical science.

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Section: External Data Sharingmentioning

confidence: 99%

The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease

Adams

Alejandro³

et al. 2017

The American Journal of Human Genetics

Self Cite

147

112

View full text Add to dashboard Cite

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“…The development of cutting‐edge genomics to achieve the Holy Grail in terms of disease predictions and therapeutics has proven to be successful in various fields. Where the underlying causes were genetic, it did exceedingly well regarding diagnosis and, to some extent, treatment . However, it is well established that the proteome of a cell provides better dynamic manipulation over space and time as compared to genomics and transcriptomics readouts.…”

Section: Introductionmentioning

confidence: 99%

“…Where the underlying causes were genetic, it did exceedingly well regarding diagnosis and, to some extent, treatment. [5][6][7] However, it is well established that the proteome of a cell provides better dynamic manipulation over space and time as compared to genomics and transcriptomics readouts. Indeed, proteins are the macromolecules that ensure most of the cellular functions and confer new adaptations.…”

Section: Introductionmentioning

confidence: 99%

Targeted Proteomics Comes to the Benchside and the Bedside: Is it Ready for Us?

Arora

Somasundaram

2019

BioEssays

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While mass spectrometry (MS)‐based quantification of small molecules has been successfully used for decades, targeted MS has only recently been used by the proteomics community to investigate clinical questions such as biomarker verification and validation. Targeted MS holds the promise of a paradigm shift in the quantitative determination of proteins. Nevertheless, targeted quantitative proteomics requires improvisation in making sample processing, instruments, and data analysis more accessible. In the backdrop of the genomic era reaching its zenith, certain questions arise: is the proteomic era about to come? If we are at the beginning of a new future for protein quantification, are we prepared to incorporate targeted proteomics at the benchside for basic research and at the bedside for the good of patients? Here, an overview of the knowledge required to perform targeted proteomics as well as its applications is provided. A special emphasis is placed on upcoming areas such as peptidomics, proteoform research, and mass spectrometry imaging, where the utilization of targeted proteomics is expected to bring forth new avenues. The limitations associated with the acceptance of this technique for mainstream usage are also highlighted. Also see the video abstract here https://youtu.be/mieB47B8gZw.

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In This Issue

Cited by 2 publications

References 0 publications

The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease

The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease

Targeted Proteomics Comes to the Benchside and the Bedside: Is it Ready for Us?

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