Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic Analysis

Type 2 diabetes (T2D) patients with SARS-CoV-2 infection hospitalized develop an acute cardiovascular syndrome. It is urgent to elucidate underlying mechanisms associated with the acute cardiac injury in T2D hearts. We performed bioinformatic analysis on the expression profiles of public datasets to...

Full description

Bibliographic Details
Main Authors: Xin Huang, Kai-jie Zhang, Jun-jie Jiang, Shou-yin Jiang, Jia-bin Lin, Yi-jia Lou
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-02-01
Series:Frontiers in Endocrinology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2022.801260/full
_version_ 1819278921072377856
author Xin Huang
Xin Huang
Kai-jie Zhang
Kai-jie Zhang
Jun-jie Jiang
Jun-jie Jiang
Shou-yin Jiang
Jia-bin Lin
Yi-jia Lou
author_facet Xin Huang
Xin Huang
Kai-jie Zhang
Kai-jie Zhang
Jun-jie Jiang
Jun-jie Jiang
Shou-yin Jiang
Jia-bin Lin
Yi-jia Lou
author_sort Xin Huang
collection DOAJ
description Type 2 diabetes (T2D) patients with SARS-CoV-2 infection hospitalized develop an acute cardiovascular syndrome. It is urgent to elucidate underlying mechanisms associated with the acute cardiac injury in T2D hearts. We performed bioinformatic analysis on the expression profiles of public datasets to identify the pathogenic and prognostic genes in T2D hearts. Cardiac RNA-sequencing datasets from db/db or BKS mice (GSE161931) were updated to NCBI-Gene Expression Omnibus (NCBI-GEO), and used for the transcriptomics analyses with public datasets from NCBI-GEO of autopsy heart specimens with COVID-19 (5/6 with T2D, GSE150316), or dead healthy persons (GSE133054). Differentially expressed genes (DEGs) and overlapping homologous DEGs among the three datasets were identified using DESeq2. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses were conducted for event enrichment through clusterProfile. The protein-protein interaction (PPI) network of DEGs was established and visualized by Cytoscape. The transcriptions and functions of crucial genes were further validated in db/db hearts. In total, 542 up-regulated and 485 down-regulated DEGs in mice, and 811 up-regulated and 1399 down-regulated DEGs in human were identified, respectively. There were 74 overlapping homologous DEGs among all datasets. Mitochondria inner membrane and serine-type endopeptidase activity were further identified as the top-10 GO events for overlapping DEGs. Cardiac CAPNS1 (calpain small subunit 1) was the unique crucial gene shared by both enriched events. Its transcriptional level significantly increased in T2D mice, but surprisingly decreased in T2D patients with SARS-CoV-2 infection. PPI network was constructed with 30 interactions in overlapping DEGs, including CAPNS1. The substrates Junctophilin2 (Jp2), Tnni3, and Mybpc3 in cardiac calpain/CAPNS1 pathway showed less transcriptional change, although Capns1 increased in transcription in db/db mice. Instead, cytoplasmic JP2 significantly reduced and its hydrolyzed product JP2NT exhibited nuclear translocation in myocardium. This study suggests CAPNS1 is a crucial gene in T2D hearts. Its transcriptional upregulation leads to calpain/CAPNS1-associated JP2 hydrolysis and JP2NT nuclear translocation. Therefore, attenuated cardiac CAPNS1 transcription in T2D patients with SARS-CoV-2 infection highlights a novel target in adverse prognostics and comprehensive therapy. CAPNS1 can also be explored for the molecular signaling involving the onset, progression and prognostic in T2D patients with SARS-CoV-2 infection.
first_indexed 2024-12-24T00:19:41Z
format Article
id doaj.art-27b5b72bf23c461496820fcd0ea9c9dc
institution Directory Open Access Journal
issn 1664-2392
language English
last_indexed 2024-12-24T00:19:41Z
publishDate 2022-02-01
publisher Frontiers Media S.A.
record_format Article
series Frontiers in Endocrinology
spelling doaj.art-27b5b72bf23c461496820fcd0ea9c9dc2022-12-21T17:24:38ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922022-02-011310.3389/fendo.2022.801260801260Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic AnalysisXin Huang0Xin Huang1Kai-jie Zhang2Kai-jie Zhang3Jun-jie Jiang4Jun-jie Jiang5Shou-yin Jiang6Jia-bin Lin7Yi-jia Lou8Cardiovascular Key Laboratory of Zhejiang Province, The 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, ChinaBiotherapy Research Center, The 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, ChinaInstitute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, ChinaChu Kochen Honors College, Zhejiang University, Hangzhou, ChinaInstitute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, ChinaChu Kochen Honors College, Zhejiang University, Hangzhou, ChinaDepartment of Emergency Medicine, The 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, ChinaClinical Research Center, The 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, ChinaInstitute of Pharmacology and Toxicology, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, ChinaType 2 diabetes (T2D) patients with SARS-CoV-2 infection hospitalized develop an acute cardiovascular syndrome. It is urgent to elucidate underlying mechanisms associated with the acute cardiac injury in T2D hearts. We performed bioinformatic analysis on the expression profiles of public datasets to identify the pathogenic and prognostic genes in T2D hearts. Cardiac RNA-sequencing datasets from db/db or BKS mice (GSE161931) were updated to NCBI-Gene Expression Omnibus (NCBI-GEO), and used for the transcriptomics analyses with public datasets from NCBI-GEO of autopsy heart specimens with COVID-19 (5/6 with T2D, GSE150316), or dead healthy persons (GSE133054). Differentially expressed genes (DEGs) and overlapping homologous DEGs among the three datasets were identified using DESeq2. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses were conducted for event enrichment through clusterProfile. The protein-protein interaction (PPI) network of DEGs was established and visualized by Cytoscape. The transcriptions and functions of crucial genes were further validated in db/db hearts. In total, 542 up-regulated and 485 down-regulated DEGs in mice, and 811 up-regulated and 1399 down-regulated DEGs in human were identified, respectively. There were 74 overlapping homologous DEGs among all datasets. Mitochondria inner membrane and serine-type endopeptidase activity were further identified as the top-10 GO events for overlapping DEGs. Cardiac CAPNS1 (calpain small subunit 1) was the unique crucial gene shared by both enriched events. Its transcriptional level significantly increased in T2D mice, but surprisingly decreased in T2D patients with SARS-CoV-2 infection. PPI network was constructed with 30 interactions in overlapping DEGs, including CAPNS1. The substrates Junctophilin2 (Jp2), Tnni3, and Mybpc3 in cardiac calpain/CAPNS1 pathway showed less transcriptional change, although Capns1 increased in transcription in db/db mice. Instead, cytoplasmic JP2 significantly reduced and its hydrolyzed product JP2NT exhibited nuclear translocation in myocardium. This study suggests CAPNS1 is a crucial gene in T2D hearts. Its transcriptional upregulation leads to calpain/CAPNS1-associated JP2 hydrolysis and JP2NT nuclear translocation. Therefore, attenuated cardiac CAPNS1 transcription in T2D patients with SARS-CoV-2 infection highlights a novel target in adverse prognostics and comprehensive therapy. CAPNS1 can also be explored for the molecular signaling involving the onset, progression and prognostic in T2D patients with SARS-CoV-2 infection.https://www.frontiersin.org/articles/10.3389/fendo.2022.801260/fulltype 2 diabetesacute cardiac injurydifferentially expressed genesbioinformaticscalpain small subunit 1 (capn4)COVID-19
spellingShingle Xin Huang
Xin Huang
Kai-jie Zhang
Kai-jie Zhang
Jun-jie Jiang
Jun-jie Jiang
Shou-yin Jiang
Jia-bin Lin
Yi-jia Lou
Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic Analysis
Frontiers in Endocrinology
type 2 diabetes
acute cardiac injury
differentially expressed genes
bioinformatics
calpain small subunit 1 (capn4)
COVID-19
title Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic Analysis
title_full Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic Analysis
title_fullStr Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic Analysis
title_full_unstemmed Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic Analysis
title_short Identification of Crucial Genes and Key Functions in Type 2 Diabetic Hearts by Bioinformatic Analysis
title_sort identification of crucial genes and key functions in type 2 diabetic hearts by bioinformatic analysis
topic type 2 diabetes
acute cardiac injury
differentially expressed genes
bioinformatics
calpain small subunit 1 (capn4)
COVID-19
url https://www.frontiersin.org/articles/10.3389/fendo.2022.801260/full
work_keys_str_mv AT xinhuang identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis
AT xinhuang identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis
AT kaijiezhang identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis
AT kaijiezhang identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis
AT junjiejiang identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis
AT junjiejiang identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis
AT shouyinjiang identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis
AT jiabinlin identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis
AT yijialou identificationofcrucialgenesandkeyfunctionsintype2diabeticheartsbybioinformaticanalysis