ArticleJournal of inherited metabolic disease2020
Confirmation of neurometabolic diagnoses using age-dependent cerebrospinal fluid metabolomic profiles.
Article in Journal of inherited metabolic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Untargeted Metabolomics for Diagnosis, Monitoring, and Understanding the Pathophysiology of Inherited Metabolic Disorders.Journal of inherited metabolic disease · 2026Review
- Huppke-Brendel syndrome: Novel cases and a therapeutic trial with ketogenic diet and N-acetylcysteine.JIMD reports · 2024Article
- Metabolite transport across central nervous system barriers.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024Review
- An evaluation of untargeted metabolomics methods to characterize inborn errors of metabolism.Molecular genetics and metabolism · 2024Review
- Novel cerebrospinal fluid biomarkers of glucose transporter type 1 deficiency syndrome: Implications beyond the brain's energy deficit.Journal of inherited metabolic disease · 2023Article
- The metabolomics of human aging: Advances, challenges, and opportunities.Science advances · 2022Review
- A narrative review of metabolomics in the era of "-omics": integration into clinical practice for inborn errors of metabolism.Translational pediatrics · 2022Review
- Comparison of extraction methods for intracellular metabolomics of human tissues.Frontiers in molecular biosciences · 2022Article
- Metabolic drift in the aging nervous system is reflected in human cerebrospinal fluid.Scientific reports · 2021Article
- Confirmation of neurometabolic diagnoses using age-dependent cerebrospinal fluid metabolomic profiles.Journal of inherited metabolic disease · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Timely diagnosis is essential for patients with neurometabolic disorders to enable targeted treatment. Next-Generation Metabolic Screening (NGMS) allows for simultaneous screening of multiple diseases and yields a holistic view of disturbed metabolic pathways. We applied this technique to define a cerebrospinal fluid (CSF) reference metabolome and validated our approach with patients with known neurometabolic disorders. Samples were measured using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry followed by (un)targeted analysis. For the reference metabolome, CSF samples from patients with normal general chemistry results and no neurometabolic diagnosis were selected and grouped based on sex and age (0-2/2-5/5-10/10-15 years). We checked the levels of known biomarkers in CSF from seven patients with five different neurometabolic disorders to confirm the suitability of our method for diagnosis. Untargeted analysis of 87 control CSF samples yielded 8036 features for semiquantitative analysis. No sex differences were found, but 1782 features (22%) were different between age groups (q < 0.05). We identified 206 diagnostic metabolites in targeted analysis. In a subset of 20 high-intensity metabolites and 10 biomarkers, 17 (57%) were age-dependent. For each neurometabolic patient, ≥1 specific biomarker(s) could be identified in CSF, thus confirming the diagnosis. In two cases, age-matching was essential for correct interpretation of the metabolomic profile. In conclusion, NGMS in CSF is a powerful tool in defining a diagnosis for neurometabolic disorders. Using our database with many (age-dependent) features in CSF, our untargeted approach will facilitate biomarker discovery and further understanding of mechanisms of neurometabolic disorders.
Indexed as
Identifiers
What OpenQuestion holds
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.