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. 2020 Sep 9:11:584637.
doi: 10.3389/fphar.2020.584637. eCollection 2020.

Age-Dependent Assessment of Genes Involved in Cellular Senescence, Telomere, and Mitochondrial Pathways in Human Lung Tissue of Smokers, COPD, and IPF: Associations With SARS-CoV-2 COVID-19 ACE2-TMPRSS2-Furin-DPP4 Axis

Krishna P Maremanda  1 , Isaac K Sundar  1 , Dongmei Li  2 , Irfan Rahman  1
Affiliations

Age-Dependent Assessment of Genes Involved in Cellular Senescence, Telomere, and Mitochondrial Pathways in Human Lung Tissue of Smokers, COPD, and IPF: Associations With SARS-CoV-2 COVID-19 ACE2-TMPRSS2-Furin-DPP4 Axis

Krishna P Maremanda et al. Front Pharmacol. .

Abstract

Background: Aging is one of the key contributing factors for chronic obstructive pulmonary diseases (COPD) and other chronic inflammatory lung diseases. Here, we determined how aging contributes to the altered gene expression related to mitochondrial function, cellular senescence, and telomeric length processes that play an important role in the progression of COPD and idiopathic pulmonary fibrosis (IPF).

Methods: Total RNA from the human lung tissues of non-smokers, smokers, and patients with COPD and IPF were processed and analyzed using a Nanostring platform based on their ages (younger: <55 years and older: >55 years).

Results: Several genes were differentially expressed in younger and older smokers, and patients with COPD and IPF compared to non-smokers which were part of the mitochondrial biogenesis/function (HSPD1, FEN1, COX18, COX10, UCP2 & 3), cellular senescence (PCNA, PTEN, KLOTHO, CDKN1C, TNKS2, NFATC1 & 2, GADD45A), and telomere replication/maintenance (PARP1, SIRT6, NBN, TERT, RAD17, SLX4, HAT1) target genes. Interestingly, NOX4 and TNKS2 were increased in the young IPF as compared to the young COPD patients. Genes in the mitochondrial dynamics and quality control mechanisms like FIS1 and RHOT2 were decreased in young IPF compared to their age matched COPD subjects. ERCC1 and GADD45B were higher in young COPD as compared to IPF. Aging plays an important role in various infectious diseases including the SARS-CoV-2 infection. Lung immunoblot analysis of smokers, COPD and IPF subjects revealed increased abundance of proteases and receptor/spike protein like TMPRSS2, furin, and DPP4 in association with a slight increase in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor ACE2 levels.

Conclusions: Overall, these findings suggest that altered transcription of target genes that regulate mitochondrial function, cellular senescence, and telomere attrition in the pathobiology of lung aging in COPD and IPF is associated with alterations in SARS-CoV-2 ACE2-TMPRSS2-Furin-DPP4 axis as pharmacological targets for COVID-19.

Keywords: DNA damage; aging; cellular senescence; chronic obstructive pulmonary diseases; idiopathic pulmonary fibrosis; mitochondria; smokers; telomere.

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Figures

Figure 1
Figure 1
Boxplot analysis of normalized mRNA transcript analyzed by NanoString. Boxplot shows distribution of normalized gene expression levels from young and old non-smokers, smokers, and COPD subjects.
Figure 2
Figure 2
Venn diagram showing the number of altered mRNA transcripts analyzed by NanoString. Venn diagram representing the number of gene changes among non-smokers, smokers, and COPD, which were further divided for pairwise comparisons into (A) young vs. young, (B) old vs. old, and (C) young vs. old aged subjects. Lung RNA was isolated, processed, and analyzed by NanoString. Normalized gene expressions were used for all the comparisons.
Figure 3
Figure 3
Volcano plots showing differentially expressed genes related to mitochondrial biogenesis and function, telomere replication and cellular senescence genes among non-smokers, smokers, and COPD subjects. Altered genes in comparisons between (A) young (smokers vs. non-smokers), (B) young (smokers vs. COPD), and (C) young (COPD vs. non-smokers). The genes differentially expressed in each comparison are indicated in green (increased) and red (decreased) colors. The green dotted horizontal line indicates the significance threshold of p-values from comparisons at P < 0.05. The Benjamini-Hochberg procedure was further used to adjust the p-values to control the false discovery rate at 5%.
Figure 4
Figure 4
Volcano plots showing differentially expressed genes related to mitochondrial biogenesis and function, telomere replication and cellular senescence genes among non-smokers, smokers, and COPD subjects. Altered genes in comparisons between (A) old (smokers vs. non-smokers), (B) old (smokers vs. COPD), and (C) old (COPD vs. non-smokers). The genes differentially expressed in each comparison are indicated in green (increased) and red (decreased) colors. The green dotted horizontal line indicates the significance threshold of p-values from comparisons at P < 0.05. The Benjamini-Hochberg procedure was further used to adjust the p-values to control the false discovery rate at 5%.
Figure 5
Figure 5
Volcano plots showing differentially expressed genes related to mitochondrial biogenesis and function, telomere replication and cellular senescence genes among non-smokers, smokers, and COPD subjects. Altered genes in comparisons between (A) non-smokers (young vs. old), (B) smokers (young vs. Old), (C) COPD (young vs. old). The genes differentially expressed in each comparison are indicated in green (increased) and red (decreased) colors. The green dotted horizontal line indicates the significance threshold of p-values from comparisons at P < 0.05. The Benjamini-Hochberg procedure was further used to adjust the p-values to control the false discovery rate at 5%.
Figure 6
Figure 6
Boxplot analysis of normalized mRNA transcript analyzed by NanoString. Boxplot shows distribution of normalized gene expression levels in combined subjects from non-smokers, smokers, and COPD subjects.
Figure 7
Figure 7
Venn diagram showing the number of altered mRNA transcripts analyzed by NanoString. Venn diagram representing the number of gene changes among (A) non-smokers, smokers, and COPD. (B) Non-smokers and IPF groups. Lung RNA was isolated, processed, and analyzed by NanoString. Normalized gene expressions were used for all the comparisons.
Figure 8
Figure 8
Volcano plots showing differentially expressed genes related to mitochondrial biogenesis and function, telomere replication and cellular senescence genes among non-smokers, smokers, and COPD subjects. Altered genes in comparisons between (A) smokers vs. non-smokers, (B) smokers vs. COPD, (C) COPD vs. non-smokers. The genes differentially expressed in each comparison are indicated in green (increased) and red (decreased) colors. The green dotted horizontal line indicates the significance threshold of p-values from comparisons at P < 0.05. The Benjamini-Hochberg procedure was further used to adjust the p-values to control the false discovery rate at 5%.
Figure 9
Figure 9
Quantitative PCR validation of the selected genes, which were found to significantly and differentially altered across various pairwise comparisons. The values were deduced based on 2-ΔΔCt method. The genes represented were found to be significant in their pairwise comparisons (p < 0.05). Student t-test was used to compare the level of significance in pairwise comparisons, while ANOVA was used for multiple comparisons.
Figure 10
Figure 10
Western blot analysis of the crucial targets involved in COVID19 in non-smokers, smokers, and COPD subjects. Five samples per groups were used to probe for the TMPRSS2, furin, ACE2, and DPP4. Data were shown as mean ± SEM (n = 5/group). Level of significance were indicated as **P < 0.01 and ***P < 0.001 across the groups.
Figure 11
Figure 11
Western blot analysis of the crucial targets involved in COVID19 in non-smokers and IPF subjects. Five samples per groups were used to probe for the TMPRSS2, furin, and ACE2. Data were shown as mean ± SEM (n = 5/group). Level of significance were indicated as *P < 0.05 and ***P < 0.001 across the groups.
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