Title |
Model Organisms Facilitate Rare Disease Diagnosis and Therapeutic Research
|
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Published in |
Genetics, August 2017
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DOI | 10.1534/genetics.117.203067 |
Pubmed ID | |
Authors |
Michael F. Wangler, Shinya Yamamoto, Hsiao-Tuan Chao, Jennifer E. Posey, Monte Westerfield, John Postlethwait, Members of the Undiagnosed Diseases Network, Philip Hieter, Kym M. Boycott, Philippe M. Campeau, Hugo J. Bellen |
Abstract |
Efforts to identify the genetic underpinnings of rare undiagnosed diseases increasingly involve the use of next-generation sequencing and comparative genomic hybridization methods. These efforts are limited by a lack of knowledge regarding gene function, and an inability to predict the impact of genetic variation on the encoded protein function. Diagnostic challenges posed by undiagnosed diseases have solutions in model organism research, which provides a wealth of detailed biological information. Model organism geneticists are by necessity experts in particular genes, gene families, specific organs, and biological functions. Here, we review the current state of research into undiagnosed diseases, highlighting large efforts in North America and internationally, including the Undiagnosed Diseases Network (UDN) (Supplemental Material, File S1) and UDN International (UDNI), the Centers for Mendelian Genomics (CMG), and the Canadian Rare Diseases Models and Mechanisms Network (RDMM). We discuss how merging human genetics with model organism research guides experimental studies to solve these medical mysteries, gain new insights into disease pathogenesis, and uncover new therapeutic strategies. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 35 | 34% |
Canada | 9 | 9% |
United Kingdom | 7 | 7% |
France | 4 | 4% |
Spain | 3 | 3% |
India | 2 | 2% |
Japan | 2 | 2% |
Germany | 1 | <1% |
Finland | 1 | <1% |
Other | 7 | 7% |
Unknown | 33 | 32% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 50 | 48% |
Scientists | 48 | 46% |
Science communicators (journalists, bloggers, editors) | 4 | 4% |
Practitioners (doctors, other healthcare professionals) | 2 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 285 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 43 | 15% |
Student > Bachelor | 41 | 14% |
Student > Ph. D. Student | 39 | 14% |
Student > Master | 19 | 7% |
Professor | 19 | 7% |
Other | 47 | 16% |
Unknown | 77 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 89 | 31% |
Agricultural and Biological Sciences | 41 | 14% |
Neuroscience | 18 | 6% |
Medicine and Dentistry | 15 | 5% |
Computer Science | 6 | 2% |
Other | 28 | 10% |
Unknown | 88 | 31% |