Evidence map›Paper›PMID 34934337›Full record

ArticleJournal of inflammation research2021

Identifying Potential Diagnostic Genes for Diabetic Nephropathy Based on Hypoxia and Immune Status.

Changyan Li, Feng Su, Le Zhang, Fang Liu, Wenxing Fan, Zhen Li, JingYuan Ma

Open access · goldAbstract read
In one paragraph

Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 21 citations in OpenAlex.

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  10. Biomarkers of Arginine Methylation in Diabetic Nephropathy: Novel Insights from Bioinformatics Analysis.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Changyan LiDepartment of Nephrology, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, People's Republic of China.
Feng SuDepartment of Nephrology, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, People's Republic of China.
Le ZhangInstitute for Integrative Genome Biology, University of California Riverside, Riverside, CA, USA.
Fang LiuDepartment of Nephrology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
Wenxing FanDepartment of Nephrology, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, People's Republic of China.ORCID 0000-0002-5526-6901
Zhen LiOrgan Transplantation Center, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, People's Republic of China.
JingYuan MaDepartment of Nephrology, the First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province, People's Republic of China.
Kunming Medical University · CNSichuan University · CNUniversity of California, Riverside · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe prognosis of diabetic nephropathy is poor, and early diagnosis of diabetic nephropathy is challenging. Fortunately, searching for DN-specific markers based on machine algorithms can facilitate diagnosis.

methodsxCell model and CIBERSORT algorithm were used to analyze the relationship between immune cells and DN, and WGCNA analysis was used to evaluate the regulatory relationship between hypoxia gene and DN-related immune cells. Lasso regression and ROC regression were used to detect the ability of core genes to diagnose DN, the PPI network of core genes with high diagnostic ability was constructed, and the interaction between core genes was discussed.

resultsThere were 519 differentially expressed genes in renal tubules and 493 differentially expressed genes in glomeruli. Immune and hypoxia responses are involved in the regulation of renal glomerulus and renal tubules. We found that there are 16 hypoxia-related genes involved in the regulation of hypoxia response. Seventeen hypoxia-related genes in renal tubules are involved in regulating hypoxia response on the proteasome signal pathway. Lasso and ROC regression were used to screen anoxic core genes. Further, we found that TGFBR3, APOLD1, CPEB1, and KDR are important in diagnosing DN glomerulopathy, respectively, PSMB8, PSMB9, RHOA, VCAM1, and CDKN1B, which have high specificity for renal tubulopathy in DN.

conclusionHypoxia and immune reactions are involved in the progression of DN. T cells are the central immune response cells. TGFBR3, APOLD1, CPEB1, and KDR have higher diagnostic accuracy in the diagnosis of DN. PSMB8, PSMB9, RHOA, VCAM1, and CDKN1B have higher diagnostic accuracy in DN diagnosis.

Indexed as

diabetic nephropathyearly diagnosishypoxiaLASSO modelT cellsWGCNA

Identifiers

PMID34934337
PMCPMC8684433
OpenAlexW4200024642

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.