ArticleKidney international reports2023
Multiomics Analysis of Plasma Proteomics and Metabolomics of Steroid Resistance in Childhood Nephrotic Syndrome Using a "Patient-Specific" Approach.
Article in Kidney international reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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2 citing papers in PubMed, 5 citations in OpenAlex.
- Multi-omics integration of proteomics and metabolomics in pediatric health and disease.Communications medicine · 2026Review
- Integrative analysis of mitochondrial and immune pathways in diabetic kidney disease: identification of AASS and CASP3 as key predictors and therapeutic targets.Renal failure · 2025Article
Corrections and comments
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Authors and funding
14 authors at 6 institutions in 1 country.
Funding
Abstract
Introduction: Nephrotic syndrome (NS) occurs commonly in children with glomerular disease and glucocorticoids (GCs) are the mainstay treatment. Steroid resistant NS (SRNS) develops in 15% to 20% of children, increasing the risk of chronic kidney disease compared to steroid sensitive NS (SSNS). NS pathogenesis is unclear in most children, and no biomarkers exist that predict the development of pediatric SRNS. Methods: We studied a unique patient cohort with plasma specimens collected before GC treatment, yielding a disease-only sample not confounded by steroid-induced gene expression changes (SSNS Results: Joint pathway analyses revealed perturbations in nicotinate or nicotinamide and butanoate metabolic pathways in patients with SRNS. Patients with SSNS had perturbations of lysine degradation, mucin type O-glycan biosynthesis, and glycolysis or gluconeogenesis pathways. Molecular analyses revealed frequent alteration of molecules within these pathways that had not been observed by separate proteomic and metabolomic studies. We observed upregulation of NAMPT, NMNAT1, and SETMAR in patients with SRNS, in contrast to upregulation of ALDH1B1, ACAT1, AASS, ENPP1, and pyruvate in patients with SSNS Conclusion: These studies confirmed that a novel "patient-specific" bioinformatic approach can integrate disparate omics datasets and identify candidate SRNS biomarkers not observed by separate proteomic or metabolomic analysis.
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