ArticleAnalytical chemistry2020
Statistically Driven Metabolite and Lipid Profiling of Patients from the Undiagnosed Diseases Network.
Article in Analytical chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02450851 (Clinical and Genetic Evaluation of Patients With Undiagnosed Disorders Through the Undiagnosed Diseases Network), which is not on this map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Clinical and Genetic Evaluation of Patients With Undiagnosed Disorders Through the Undiagnosed Diseases Network
Who cites it
6 citing papers in PubMed.
- A guide for the diagnosis of rare and undiagnosed disease: beyond the exome.Genome medicine · 2022Review
- Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests.Analytical and bioanalytical chemistry · 2022Review
- LC-MS lipidomics of renal biopsies for the diagnosis of Fabry disease.Journal of mass spectrometry and advances in the clinical lab · 2021Article
- Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation.Nature protocols · 2021Review
- A resource of lipidomics and metabolomics data from individuals with undiagnosed diseases.Scientific data · 2021Article
- Rare disease care pathways in the EU: from odysseys and labyrinths towards highways.Journal of community genetics · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Advancements in molecular separations coupled with mass spectrometry have enabled metabolome analyses for clinical cohorts. A population of interest for metabolome profiling is patients with rare disease for which abnormal metabolic signatures may yield clues into the genetic basis, as well as mechanistic drivers of the disease and possible treatment options. We undertook the metabolome profiling of a large cohort of patients with mysterious conditions characterized through the Undiagnosed Diseases Network (UDN). Due to the size and enrollment procedures, collection of the metabolomes for UDN patients took place over 2 years. We describe the study designed to adjust for measurements collected over a long time scale and how this enabled statistical analyses to summarize the metabolome of individual patients. We demonstrate the removal of time-based batch effects, overall statistical characteristics of the UDN population, and two case studies of interest that demonstrate the utility of metabolome profiling for rare diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.