Evidence map›Paper›PMID 37184672›Full record

ArticleActa diabetologica2023

Urinary metabolites associate with the presence of diabetic kidney disease in type 2 diabetes and mediate the effect of inflammation on kidney complication.

Caifeng Shi, Yemeng Wan, Aiqin He, Xiaomei Wu, Xinjia Shen, Xueting Zhu, Junwei Yang, Yang Zhou

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Acta diabetologica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

6 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
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  6. Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023
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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

8 authors at 1 institution in 1 country.

Caifeng Shi *Center for Kidney Disease, Second Affiliated Hospital of Nanjing Medical University, No. 262 N Zhongshan Road, Nanjing, 210003, Jiangsu, China.
Yemeng Wan *Center for Kidney Disease, Second Affiliated Hospital of Nanjing Medical University, No. 262 N Zhongshan Road, Nanjing, 210003, Jiangsu, China.
Aiqin He *Center for Kidney Disease, Second Affiliated Hospital of Nanjing Medical University, No. 262 N Zhongshan Road, Nanjing, 210003, Jiangsu, China.
Xiaomei Wu *Center for Kidney Disease, Second Affiliated Hospital of Nanjing Medical University, No. 262 N Zhongshan Road, Nanjing, 210003, Jiangsu, China.
Xinjia ShenCenter for Kidney Disease, Second Affiliated Hospital of Nanjing Medical University, No. 262 N Zhongshan Road, Nanjing, 210003, Jiangsu, China.
Xueting ZhuCenter for Kidney Disease, Second Affiliated Hospital of Nanjing Medical University, No. 262 N Zhongshan Road, Nanjing, 210003, Jiangsu, China.
Junwei YangCenter for Kidney Disease, Second Affiliated Hospital of Nanjing Medical University, No. 262 N Zhongshan Road, Nanjing, 210003, Jiangsu, China. jwyang@njmu.edu.cn.
Yang ZhouCenter for Kidney Disease, Second Affiliated Hospital of Nanjing Medical University, No. 262 N Zhongshan Road, Nanjing, 210003, Jiangsu, China. zhouyang@njmu.edu.cn.ORCID http://orcid.org/0000-0003-0453-4598
Second Affiliated Hospital of Nanjing Medical University · CN

Funding

National Natural Science Foundation of China 82270760Natural Science Foundation of Jiangsu Province BK20201497
6 · The paper itself

Abstract

aimsDiabetic kidney disease (DKD) is the one of the leading causes of end-stage kidney disease. Unraveling novel biomarker signatures capable to identify patients with DKD is favorable for tackle the burden. Here, we investigated the possible association between urinary metabolites and the presence of DKD in type 2 diabetes (T2D), and further, whether the associated metabolites improve discrimination of DKD and mediate the effect of inflammation on kidney involvement was evaluated.

methodsTwo independent cohorts comprising 192 individuals (92 DKD) were analyzed. Urinary metabolites were analyzed by targeted metabolome profiling  and inflammatory cytokine IL-18 were measured by ELISA. Differentially expressed metabolites were selected and mediation analysis was carried out.

resultsSeven potential metabolite biomarkers (i.e., S-Adenosyl-L-homocysteine, propionic acid, oxoadipic acid, leucine, isovaleric acid, isobutyric acid, and indole-3-carboxylic acid) were identified using the discovery and validation design. In the pooled analysis, propionic acid, oxoadipic acid, leucine, isovaleric acid, isobutyric acid, and indole-3-carboxylic acid were markedly and independently associated with DKD. The composite index of 7 potential metabolite biomarkers (CMI) mediated 32.99% of the significant association between the inflammatory IL-18 and DKD. Adding the metabolite biomarkers improved the discrimination of DKD.

conclusionsIn T2D, several associated urinary metabolites were identified to improve the prediction of DKD. Whether interventions aimed at reducing CMI also reduce the risk of DKD especially in patients with high IL-18 needs further investigations.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesBiomarkersHemiterpenesHumansInflammationInterleukin-18IsobutyratesKidneyLeucinePentanoic AcidsPropionatesBiomarkersHemiterpenesInterleukin-18Isobutyratesisobutyric acidisovaleric acidLeucinePentanoic AcidsPropionatespropionic acidInflammationKidneyMetabolite

Identifiers

PMID37184672
PMCPMC10359369
OpenAlexW4376630242

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LicenceCC BY
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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.