ArticleJCI insight2019
Identification of dicarbonyl and L-xylulose reductase as a therapeutic target in human chronic kidney disease.
Article in JCI insight, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 12 citations in OpenAlex.
- Mitochondrial Function-Related Genes in Sleep Disorders: A Multi-Omics Mendelian Randomization Study.Journal of molecular neuroscience : MN · 2026Article
- HDAnalyzeR: streamlining data analysis for biomarker research.Bioinformatics advances · 2026Article
- Cuproptosis-related gene signatures define the immune microenvironment in diabetic nephropathy.PloS one · 2025Article
- Multi-omic insights into mitochondrial dysfunction and prostatic disease: evidence from transcriptomics, proteomics, and methylomics.Frontiers in genetics · 2025Article
- Downregulation of the kidney glucagon receptor, essential for renal function and systemic homeostasis, contributes to chronic kidney disease.Cell metabolism · 2024Article
- DCXR promotes cell proliferation by promoting the activity of aerobic glycolysis in breast cancer.Molecular medicine reports · 2023Article
- Assessment of Fibrinogen-like 2 (FGL2) in Human Chronic Kidney Disease through Transcriptomics Data Analysis.Biomolecules · 2022Article
- Scientific Advances in Diabetes: The Impact of the Innovative Medicines Initiative.Frontiers in medicine · 2021Review
- Review
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 at 2 institutions in 2 countries.
Funding
Abstract
An imbalance of nephroprotective factors and renal damaging molecules contributes to development and progression of chronic kidney disease (CKD). We investigated associations of renoprotective factor gene expression patterns with CKD severity and outcome. Gene expression profiles of 197 previously reported renoprotective factors were analyzed in a discovery cohort in renal biopsies of 63 CKD patients. Downregulation of dicarbonyl and L-xylulose reductase (DCXR) showed the strongest association with disease progression. This significant association was validated in an independent set of 225 patients with nephrotic syndrome from the multicenter NEPTUNE cohort. Reduced expression of DCXR was significantly associated with degree of histological damage as well as with lower estimated glomerular filtration rate and increased urinary protein levels. DCXR downregulation in CKD was confirmed in 3 publicly available transcriptomics data sets in the context of CKD. Expression of DCXR showed positive correlations to enzymes that are involved in dicarbonyl stress detoxification based on transcriptomics profiles. The sodium glucose cotransporter-2 (SGLT2) inhibitors canagliflozin and empagliflozin showed a beneficial effect on renal proximal tubular cells under diabetic stimuli-enhanced DCXR gene expression. In summary, lower expression of the renoprotective factor DCXR in renal tissue is associated with more severe disease and worse outcome in human CKD.
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.