A resource of lipidomics and metabolomics data from individuals with undiagnosed diseases
| Autor: | Matthew Monroe, Chloe Reuter, Richard Lewis, Erika Zink, Kelly Stratton, Patrick Allard, Mahshid Azamian, Tom Metz, Emilie Douine, Jennifer Louise Patrick Murphy, Young-Mo Kim, Katrina Waters, Bobbie-Jo Webb-Robertson, Nicholas Stong |
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| Rok vydání: | 2021 |
| Předmět: |
Male
Data Descriptor Datasets as Topic Diseases Disease Mass Spectrometry 0302 clinical medicine Research community Medicine Reference population Child 0303 health sciences education.field_of_study Middle Aged Computer Science Applications Child Preschool Female Statistics Probability and Uncertainty Information Systems Statistics and Probability Adult medicine.medical_specialty Adolescent Science Population Library and Information Sciences Undiagnosed Diseases Education 03 medical and health sciences Young Adult Metabolic Diseases Clinical Research Common fund Lipidomics Humans Metabolomics Intensive care medicine education Preschool Metabolic and endocrine 030304 developmental biology Mass spectrometry business.industry Infant Newborn Infant Diagnostic markers Undiagnosed Diseases Network Newborn Metabolomics data business Healthcare providers 030217 neurology & neurosurgery |
| Zdroj: | Scientific data, vol 8, iss 1 Scientific Data Scientific Data, Vol 8, Iss 1, Pp 1-12 (2021) |
| Popis: | Every year individuals experience symptoms that remain undiagnosed by healthcare providers. In the United States, these rare diseases are defined as a condition that affects fewer than 200,000 individuals. However, there are an estimated 7000 rare diseases, and there are an estimated 25–30 million Americans in total (7.6–9.2% of the population as of 2018) affected by such disorders. The NIH Common Fund Undiagnosed Diseases Network (UDN) seeks to provide diagnoses for individuals with undiagnosed disease. Mass spectrometry-based metabolomics and lipidomics analyses could advance the collective understanding of individual symptoms and advance diagnoses for individuals with heretofore undiagnosed disease. Here, we report the mass spectrometry-based metabolomics and lipidomics analyses of blood plasma, urine, and cerebrospinal fluid from 148 patients within the UDN and their families, as well as from a reference population of over 100 individuals with no known metabolic diseases. The raw and processed data are available to the research community so that they might be useful in the diagnoses of current or future patients suffering from undiagnosed disorders. Measurement(s) Metabolomics • Lipidomics Technology Type(s) gas chromatography-mass spectrometry • Ultra High-performance Liquid Chromatography/Tandem Mass Spectrometry Factor Type(s) age group • sex Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment blood plasma material • urine material • cerebrospinal fluid material Sample Characteristic - Location United States of America Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13656581 |
| Databáze: | OpenAIRE |
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