PMID- 36046789
OWN - NLM
STAT- MEDLINE
DCOM- 20220908
LR  - 20220913
IS  - 1664-2392 (Print)
IS  - 1664-2392 (Electronic)
IS  - 1664-2392 (Linking)
VI  - 13
DP  - 2022
TI  - Integrated bioinformatic analysis reveals immune molecular markers and potential 
      drugs for diabetic cardiomyopathy.
PG  - 933635
LID - 10.3389/fendo.2022.933635 [doi]
LID - 933635
AB  - Diabetic cardiomyopathy (DCM) is a pathophysiological condition induced by 
      diabetes mellitus that often causes heart failure (HF). However, their 
      mechanistic relationships remain unclear. This study aimed to identify immune 
      gene signatures and molecular mechanisms of DCM. Microarray data from the Gene 
      Expression Omnibus (GEO) database from patients with DCM were subjected to 
      weighted gene co-expression network analysis (WGCNA) identify co-expression 
      modules. Core expression modules were intersected with the immune gene database. 
      We analyzed and mapped protein-protein interaction (PPI) networks using the 
      STRING database and MCODE and filtering out 17 hub genes using cytoHubba 
      software. Finally, potential transcriptional regulatory factors and therapeutic 
      drugs were identified and molecular docking between gene targets and small 
      molecules was performed. We identified five potential immune biomarkers: 
      proteosome subunit beta type-8 (PSMB8), nuclear factor kappa B1 (NFKB1), albumin 
      (ALB), endothelin 1 (EDN1), and estrogen receptor 1 (ESR1). Their expression 
      levels in animal models were consistent with the changes observed in the 
      datasets. EDN1 showed significant differences in expression in both the dataset 
      and the validation model by real-time quantitative PCR (qPCR) and Western 
      blotting(WB). Subsequently, we confirmed that the potential transcription factors 
      upstream of EDN1 were PRDM5 and KLF4, as its expression was positively correlated 
      with the expression of the two transcription factors. To repurpose known 
      therapeutic drugs, a connectivity map (CMap) database was retrieved, and nine 
      candidate compounds were identified. Finally, molecular docking simulations of 
      the proteins encoded by the five genes with small-molecule drugs were performed. 
      Our data suggest that EDN1 may play a key role in the development of DCM and is a 
      potential DCM biomarker.
CI  - Copyright (c) 2022 Guo, Zhu, Zhang, Qu, Cheang, Liao, Chen, Zhu, Shi and Li.
FAU - Guo, Qixin
AU  - Guo Q
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Zhu, Qingqing
AU  - Zhu Q
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Zhang, Ting
AU  - Zhang T
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Qu, Qiang
AU  - Qu Q
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Cheang, Iokfai
AU  - Cheang I
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Liao, Shengen
AU  - Liao S
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Chen, Mengli
AU  - Chen M
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Zhu, Xu
AU  - Zhu X
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Shi, Mengsha
AU  - Shi M
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
FAU - Li, Xinli
AU  - Li X
AD  - Department of Cardiology, The First Affiliated Hospital of Nanjing Medical 
      University, Nanjing, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20220815
PL  - Switzerland
TA  - Front Endocrinol (Lausanne)
JT  - Frontiers in endocrinology
JID - 101555782
RN  - 0 (Biomarkers)
RN  - 0 (Transcription Factors)
SB  - IM
MH  - Animals
MH  - Biomarkers
MH  - Computational Biology
MH  - *Diabetes Mellitus
MH  - *Diabetic Cardiomyopathies/drug therapy/genetics
MH  - Gene Expression Profiling
MH  - Gene Regulatory Networks
MH  - Molecular Docking Simulation
MH  - Transcription Factors/genetics
PMC - PMC9421304
OTO - NOTNLM
OT  - bioinformatics
OT  - biomarker
OT  - diabetes mellitus
OT  - diabetic cardiomyopathy
OT  - molecular docking
OT  - potential drugs
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest. The reviewers JS and JL declared a shared affiliation, with 
      no collaboration, with the authors to the handling editor at the time of the 
      review.
EDAT- 2022/09/02 06:00
MHDA- 2022/09/09 06:00
PMCR- 2022/01/01
CRDT- 2022/09/01 02:36
PHST- 2022/05/01 00:00 [received]
PHST- 2022/07/27 00:00 [accepted]
PHST- 2022/09/01 02:36 [entrez]
PHST- 2022/09/02 06:00 [pubmed]
PHST- 2022/09/09 06:00 [medline]
PHST- 2022/01/01 00:00 [pmc-release]
AID - 10.3389/fendo.2022.933635 [doi]
PST - epublish
SO  - Front Endocrinol (Lausanne). 2022 Aug 15;13:933635. doi: 
      10.3389/fendo.2022.933635. eCollection 2022.