ReviewOrphanet journal of rare diseases2024
A review of multiple diagnostic approaches in the undiagnosed diseases network to identify inherited metabolic diseases.
Review in Orphanet journal of rare diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.
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Who cites it
6 citing papers in PubMed.
- Cross-species functional analysis of aResearch square · 2026Article
- Expanded Clinical Spectrum of Autosomal-Dominant STT3A-CDG.Biomolecules · 2026Review
- Timely Diagnosis of Cobalamin C Disease via Rapid Genome Sequencing in a Neonate With Severe Prenatally Detected Biventricular Dysfunction.Case reports in critical care · 2026Article
- The Undiagnosed Diseases Network (UDN) Solves Ocular Syndromic Diagnostic Dilemmas.American journal of ophthalmology · 2025Article
- The Impact of Ethnic and Communication Barriers on Fatal Metabolic Emergent Management of Traumatic Injury: A Case Report.Reports (MDPI) · 2025Article
- Rapid whole genome sequencing in newborn screening for metabolic diseases.Frontiers in pediatrics · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundThe number of known inherited metabolic diseases (IMDs) has been expanding, and the rate of diagnosis is improving with the development of innovative approaches including next generation sequencing (NGS). However, a substantial proportion of IMDs remain undetected by traditional diagnostic approaches. We aim to highlight the spectrum of IMDs diagnosed by the Undiagnosed Diseases Network (UDN) and to learn from the UDN diagnostic processes that were able to detect IMDs.
methodsWe conducted a retrospective analysis of 757 UDN participants diagnosed from 2015 until 2023 using the cohort database, which were divided into a cohort with IMDs (n = 194; 27%) and a cohort whose phenotypes were not explained by an IMD (n = 563; 73%), based on the International Classification of Inherited Metabolic Disorders (ICIMD). Then, we divided the causes of the metabolic 194 diagnoses into seven groups that included all the ICIMD categories. We inspected which clinical and laboratory approaches contributed to a final UDN diagnosis. We also present a UDN case example from each group to highlight the diagnostic yields that resulted from combining newer diagnostic approaches in the UDN and illustrate potential pitfalls of current NGS methods.
resultsThese 194 cases of IMDs included examples from 21/25 (84%) of the ICIMD categories. Of the UDN subjects 164/194 (85%) were diagnosed with IMDs through NGS.
conclusionThe spectrum of IMDs detected in the UDN cohort is large and growing and appropriate use of newer multiple diagnostic approaches should further increase diagnosis of IMDs that are presently missed by the traditional laboratory screening methods.
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