ReviewCell metabolism2016
A Next Generation Multiscale View of Inborn Errors of Metabolism.
Review in Cell metabolism, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed.
- Revolutionizing neonatal health: India's journey from assays to advanced genetics.Journal of applied genetics · 2026Review
- Personalized Genome-Scale Modeling Reveals Metabolic Perturbations in Fibroblasts of Methylmalonic Aciduria Patients.Journal of inherited metabolic disease · 2025Article
- A Multiomic Network Approach to Uncover Disease Modifying Mechanisms of Inborn Errors of Metabolism.Journal of inherited metabolic disease · 2025Article
- iPSC-Derived Liver Organoids as a Tool to Study Medium Chain Acyl-CoA Dehydrogenase Deficiency.Journal of inherited metabolic disease · 2025Article
- Article
- Systems Biology and Inborn Error of Metabolism: Analytical Strategy in Investigating Different Biochemical/Genetic Parameters.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients.BMC biology · 2023Article
- Metabolic systems approaches update molecular insights of clinical phenotypes and cardiovascular risk in patients with homozygous familial hypercholesterolemia.BMC medicine · 2023Article
- Metabolomic Approach to Screening Homozygotes in Chinese Patients with Severe Familial Hypercholesterolemia.Journal of clinical medicine · 2023Article
- Low-density lipoprotein receptor genotypes modify the sera metabolome of patients with homozygous familial hypercholesterolemia.iScience · 2022Article
- Clinical diagnosis of metabolic disorders using untargeted metabolomic profiling and disease-specific networks learned from profiling data.Scientific reports · 2022Article
- OMICS Approaches Evaluating Keloid and Hypertrophic Scars.International journal of inflammation · 2022Review
- Utility of Gene Panels for the Diagnosis of Inborn Errors of Metabolism in a Metabolic Reference Center.Genes · 2021Article
- Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted Panel.Diagnostics (Basel, Switzerland) · 2021Article
- Explaining the Black-White Disparity in Preterm Birth: A Consensus Statement From a Multi-Disciplinary Scientific Work Group Convened by the March of Dimes.Frontiers in reproductive health · 2021Review
- Fibroblast-specific genome-scale modelling predicts an imbalance in amino acid metabolism in Refsum disease.The FEBS journal · 2020Article
- Natural variation in a glucuronosyltransferase modulates propionate sensitivity in a C. elegans propionic acidemia model.PLoS genetics · 2020Article
- Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway.Science advances · 2020Article
- Animal Model Contributions to Congenital Metabolic Disease.Advances in experimental medicine and biology · 2020Review
- Multi-Omic Approach to Identify Phenotypic Modifiers Underlying Cerebral Demyelination in X-Linked Adrenoleukodystrophy.Frontiers in cell and developmental biology · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Inborn errors of metabolism (IEM) are not unlike common diseases. They often present as a spectrum of disease phenotypes that correlates poorly with the severity of the disease-causing mutations. This greatly impacts patient care and reveals fundamental gaps in our knowledge of disease modifying biology. Systems biology approaches that integrate multi-omics data into molecular networks have significantly improved our understanding of complex diseases. Similar approaches to study IEM are rare despite their complex nature. We highlight that existing common disease-derived datasets and networks can be repurposed to generate novel mechanistic insight in IEM and potentially identify candidate modifiers. While understanding disease pathophysiology will advance the IEM field, the ultimate goal should be to understand per individual how their phenotype emerges given their primary mutation on the background of their whole genome, not unlike personalized medicine. We foresee that panomics and network strategies combined with recent experimental innovations will facilitate this.
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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.