Evidence mapPaperPMID 34028657Full record

ArticleCardiovascular drugs and therapy2022

A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology.

Ziling Mai, Huanqiang Li, Guanzhong Chen, Enzhao Chen, Liwei Liu, Zhubin Lun, Wenguang Lai, Chunyun Zhou, Sijia Yu, Jin Liu and 3 more

Open access · hybridAbstract read
In one paragraph

Article in Cardiovascular drugs and therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

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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

13 authors at 2 institutions in 1 country.

Ziling Mai *Guangdong Provincial People's Hospital, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Huanqiang Li *Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Guanzhong Chen *Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Enzhao Chen *Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Liwei Liu *Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Zhubin LunDepartment of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Wenguang LaiGuangdong Provincial People's Hospital, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Chunyun ZhouDepartment of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Sijia YuDepartment of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Jin LiuDepartment of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Shiqun ChenDepartment of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Jiyan ChenGuangdong Provincial People's Hospital, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China. chenjiyandr@126.com.
Yong LiuGuangdong Provincial People's Hospital, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China. liuyong@gdph.org.cn.ORCID 0000-0003-2224-4885
Guangdong Academy of Medical Sciences · CNGuangdong Medical College · CN

Funding

Cardiovascular Research Foundation Project of the Chinese Medical Doctor Association SCRFCMDA201216Dengfeng Project in Guangdong Province DFJH201919Dengfeng Project in Guangdong Province DFJH2020026National Science Foundation of China 81670339the National Science Foundation of China 81970311the Progress of Science and Technology Project in Guangdong Province 2017B020247060
6 · The paper itself

Abstract

purposeDiabetes mellitus (DM) is a major risk factor for the development of heart failure (HF). Sodium-glucose co-transporter 2 (SGLT2) inhibitors have demonstrated consistent benefits in the reduction of hospitalization for HF in patients with DM. However, the pharmacological mechanism is not clear. To investigate the mechanisms of SGLT2 inhibitors in DM with HF, we performed target prediction and network analysis by a network pharmacology method.

methodsWe selected targets of SGLT2 inhibitors and DM status with HF from databases and studies. The "Drug-Target" and "Drug-Target-Disease" networks were constructed using Cytoscape. Then the protein-protein interaction (PPI) was analyzed using the STRING database. Gene Ontology (GO) biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed to investigate using the Bioconductor tool for analysis.

resultsThere were 125 effective targets between SGLT2 inhibitors and DM status with HF. Through further screening, 33 core targets were obtained, including SRC, MAPK1, NARS, MAPK3 and EGFR. It was predicted that the Rap1 signaling pathway, MAPK signaling pathway, EGFR tyrosine kinase inhibitor resistance, AGE-RAGE signaling pathway in diabetic complications and other signaling pathways were involved in the treatment of DM with HF by SGLT2 inhibitors.

conclusionOur study elucidated the possible mechanisms of SGLT2 inhibitors from a systemic and holistic perspective based on pharmacological networks. The key targets and pathways will provide new insights for further research on the pharmacological mechanism of SGLT2 inhibitors in the treatment of DM with HF.

Indexed as

Diabetes Mellitus, Type 2Heart FailureSodium-Glucose Transporter 2 InhibitorsSymportersComputational BiologyErbB ReceptorsGlucoseHumansNetwork PharmacologySodiumErbB ReceptorsGlucoseSodiumSodium-Glucose Transporter 2 InhibitorsSymportersDiabetes mellitusHeart failureNetwork pharmacologySodium-glucose co-transporter 2 inhibitors

Identifiers

PMID34028657
PMCPMC9270285
OpenAlexW3135484908

What Socratic holds

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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 Socratic graph.