Aging and Disease  2020 , 11 (3): 509-522

Orginal Article

COVID-19 Virulence in Aged Patients Might Be Impacted by the Host Cellular MicroRNAs Abundance/Profile

Fulzele Sadanand12*, Sahay Bikash3, Yusufu Ibrahim1, Lee Tae Jin4, Sharma Ashok4, Kolhe Ravindra5, Isales Carlos M12

1Department of Medicine, Augusta University, Augusta, GA, USA.
2Center for Healthy Aging, Augusta University, Augusta, GA, USA.
3Department of Infectious Diseases and Immunology, University of Florida, Gainesville, FL, USA.
4Center for Biotechnology and Genomic Medicine, Augusta University, Augusta, GA 30912, USA.
5Departments of Pathology, Augusta University, Augusta, GA 30912, USA

通讯作者:  Correspondence should be addressed to: Dr. Sadanand Fulzele, Department of Medicine, Center for Healthy Aging, Augusta University, Augusta, GA 30912, USA. Email: should be addressed to: Dr. Sadanand Fulzele, Department of Medicine, Center for Healthy Aging, Augusta University, Augusta, GA 30912, USA. Email:

收稿日期: 2020-04-1

修回日期:  2020-04-27

接受日期:  2020-04-28

网络出版日期:  2020-05-09

版权声明:  2020 This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.



The World health organization (WHO) declared Coronavirus disease 2019 (COVID-19) a global pandemic and a severe public health crisis. Drastic measures to combat COVID-19 are warranted due to its contagiousness and higher mortality rates, specifically in the aged patient population. At the current stage, due to the lack of effective treatment strategies for COVID-19 innovative approaches need to be considered. It is well known that host cellular miRNAs can directly target both viral 3'UTR and coding region of the viral genome to induce the antiviral effect. In this study, we did in silico analysis of human miRNAs targeting SARS (4 isolates) and COVID-19 (29 recent isolates from different regions) genome and correlated our findings with aging and underlying conditions. We found 848 common miRNAs targeting the SARS genome and 873 common microRNAs targeting the COVID-19 genome. Out of a total of 848 miRNAs from SARS, only 558 commonly present in all COVID-19 isolates. Interestingly, 315 miRNAs are unique for COVID-19 isolates and 290 miRNAs unique to SARS. We also noted that out of 29 COVID-19 isolates, 19 isolates have identical miRNA targets. The COVID-19 isolates, Netherland (EPI_ISL_422601), Australia (EPI_ISL_413214), and Wuhan (EPI_ISL_403931) showed six, four, and four unique miRNAs targets, respectively. Furthermore, GO, and KEGG pathway analysis showed that COVID-19 targeting human miRNAs involved in various age-related signaling and diseases. Recent studies also suggested that some of the human miRNAs targeting COVID-19 decreased with aging and underlying conditions. GO and KEGG identified impaired signaling pathway may be due to low abundance miRNA which might be one of the contributing factors for the increasing severity and mortality in aged individuals and with other underlying conditions. Further, in vitro and in vivo studies are needed to validate some of these targets and identify potential therapeutic targets.

Keywords: Coronavirus ; microRNAs ; aging


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Fulzele Sadanand, Sahay Bikash, Yusufu Ibrahim, Lee Tae Jin, Sharma Ashok, Kolhe Ravindra, Isales Carlos M. COVID-19 Virulence in Aged Patients Might Be Impacted by the Host Cellular MicroRNAs Abundance/Profile[J]. Aging and Disease, 2020, 11(3): 509-522

Novel Coronavirus was identified near the end of 2019, presenting with a spectrum of symptoms including febrile illness, cough, severe pneumonia, and in some patients, death. The pathogen is now widely called Coronavirus disease 2019 (COVID-19) and has rapidly turned into a global pandemic since originally being identified in Wuhan, China. Coronaviridae is the family of single-stranded (+ssRNA), pleomorphic, enveloped RNA viruses that consists of the Coronavirus genus [1]. COVID-19 is also referred to as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to the genomic and symptomatic similarities with the SARS-CoV that caused an epidemic in 2002-2004 [2]. SARS-CoV-2 is predominantly spread by person-to-person contact via virally loaded respiratory droplets [3]. However, the transmission may also occur by touching contaminated surfaces and subsequently touching one's eyes, nose, or mouth [4, 5]. The incubation period, the period before the first symptoms present itself, is on average of 4-5 days, with 95% presenting within 12.5 days [6,7].

The World Health Organization (WHO) reported 2,920,905 confirmed infected, and 203,269 COVID-19 related deaths globally as of April 25th, 2020 [8]. Drastic measures to combat SARS-CoV-2 are warranted due to its contagiousness, viability, and higher death toll compared to its predecessor SARS-CoV. Although SARS-CoV had a significantly higher case-fatality (around 10%) [9], the virus was not viable enough to remain in the human population and never spread in the United States and other countries like SARS-CoV-2 [10]. SARS-CoV-2, on the other hand, appears to rapidly spread, which is contributing to its global spread and a significantly higher number of cases.

Severe and critical cases of COVID-19 disproportionately affect middle-aged and older/aged populations, with increased mortality in aged adults [11]. Illness severity ranges from asymptomatic, mild, severe, and critical. Mild illness is characterized as no to mild pneumonia [11]. The severe disease presents with dyspnea, hypoxia, or >50% lung involvement, and critical illness occurs when there is respiratory failure, shock, or multiorgan failure [11]. The Centers for Disease Control and Prevention (CDC) and the WHO estimate the mortality rates of SARS-CoV-2 to be around 3.4% and case fatality rates (CFR) may increase up to 10-27 % in individuals 80 years old or older [8, 12]. SARS-CoV-2 is a novel virus, and very little is known about it. In such a scenario, it is crucial to understand the COVID-19 pathobiology to identify the innovative treatment strategy. Our laboratory and others have reported that miRNAs play a critical role in age-related complications [13-16].

MiRNAs play a vital role in the pathogenesis of various diseases, including viral infections, disease progression, and inhibition [17-23]. MicroRNAs are small noncoding RNAs, bind to 3'UTR of mRNA, and inhibit translation or induce degradation of mRNAs [19, 21, 23]. Recent studies suggested that host cellular miRNAs can directly target both viral 3’UTR and coding region of the viral genome to induce antiviral effect [19, 21, 23]. For example, the number of groups previously reported that host miRNAs (miR-323, miR-491, miR-485, miR-654, and miR-3145) bind to influenza PB1 gene coding region, degrade RNA and inhibit viral translation and reduce the accumulation of viral particles [19, 24, 25]. Furthermore, the host cellular miRNA-29a inhibit Human immunodeficiency virus type 1 (HIV-1) nef protein expression and thus, inhibit viral replication [26]. On the contrary, some groups also suggested the positive effect of host miRNAs on viral replication. For example, miR-122 binding to 3’ and 5’ UTR of hepatotropic virus RNA and increase viral RNA stability leads to viral propagation [18, 20, 22]. Based on the above reports, we did in silico analysis of miRNAs targeting SARS and COVID-19 (recent isolates from different regions) to understand the pathophysiology and identify novel therapeutic targets.


Table 1   Details of SARS and COVID-19 isolates from different geographic locations, sequence length, and the number of human miRNA targets.

Virus typeGenBank IDLocationMonth and year of isolates/sequencedSequence Length
Number of miR Targets
SARSAY338175.1TaiwanJuly 200329573855
SARSAY348314.1TaiwanJuly 200329573855
SARSAY291451.1TaiwanJuly 200329729858
SARSNC_004718.3CanadaApril 200329751857
COVID -19EPI_ISL_406798Wuhan/ChinaDecember 201929866893
COVID -19EPI_ISL_403929Wuhan/ChinaDecember 201929890900
COVID -19EPI_ISL_402121Wuhan/ChinaDecember 201929891898
COVID -19EPI_ISL_402123Wuhan/ChinaDecember 201929899900
COVID -19EPI_ISL_403931Wuhan/ChinaDecember 201929889903
COVID -19EPI_ISL_403930Wuhan/ChinaDecember 201929899899
COVID -19NC_045512.2Wuhan (China)January 202029903900
COVID -19MT007544.1AustraliaJanuary 202029893902
COVID -19EPI_ISL_406862GermanyJanuary 202029782896
COVID -19EPI_ISL_403962ThailandJanuary 202029848897
COVID -19EPI_ISL_412974ItalyJanuary 202029903900
COVID -19EPI_ISL_407893AustraliaJanuary 202029782898
COVID -19EPI_ISL_406223Arizona/USAJanuary 202029882900
COVID -19EPI_ISL_406597FranceJanuary 202029809901
COVID -19EPI_ISL_420799S. KoreaFebruary 202029882901
COVID -19EPI_ISL_413214AustraliaFebruary 202029782899
COVID -19EPI_ISL_419211IsrealFebruary 202029851897
COVID -19MT050493.1IndiaFenruary 202029851895
COVID -19MT066176.1TaiwanFebruary 202029870900
COVID -19EPI_ISL_418001PortugalMarch 202029763895
COVID -19EPI_ISL_417507USAMarch 202029782898
COVID -19MT159718.1USA (Cruise A)March 202029882900
COVID -19MT126808.1BrazilMarch 202029876900
COVID -19EPI_ISL_428847SingaporeApril 202029888900
COVID -19EPI_ISL_426565Arizona/USAApril 202029882897
COVID -19EPI_ISL_420144GeorgiaApril 202029833900
COVID -19EPI_ISL_427391TurkeyApril 202029895899
COVID -19EPI_ISL_429223SwitzerlandApril 202029894895
COVID -19EPI_ISL_422601NetherlandApril 202029775902



Viral genome sequence retrieval, homology, and phylogenetic analyses

The complete genome sequences of the SARS and COVID-19 isolates were retrieved from the GenBank database. We retrieved four SARS and 29 COVID-19 sequences from NCBI and GISAID for for homology and phylogenetic analysis. Details of sequence identification are summarizing in Table 1. The sequences were aligned using the Multiple Sequence Alignment tool at Clustal Omega 1.2.3 on Geneious Prime 2020.1.1. The phylogenetic alignment tree generated using the neighbor-joining method.

COVID-19 genome and human MiRNA target analysis

As previously mentioned above, miRNAs are known to target 3'UTR and coding sequences and prevent mRNA translation or degrade RNA. Keeping this in consideration, we used the whole viral genome sequence for miRNA target analysis. We used miRDB ( software to identify novel human miRNAs targeting the COVID-19 viral genome [27, 28]. Furthermore, we used this data to correlate with the existing literature.

GO, and KEGG pathway analysis

Gene Ontology (GO) and KEGG signaling pathway analyses were performed on human microRNAs targeting the COVID-19 genome using DIANA-miRPath v 3.0 ( [29]. We used miRNAs with a target score above 90 because these miRNAs have high probability of being real targets [27, 28].


Viral genome sequence homology and phylogenetic analyses

The sequences of the COVID-19 isolates have been stored, compiled, and analyzed by various sources; one of the major resources for these sequences has been the Global Initiative on Sharing All Influenza Data (GISAID), which is a public-private initiative initially made for sharing sequences of influenza data. The organization provides a complete daily analysis of the viruses uploaded by the various researchers across the Globe. The COVID-19 belongs to a family of RNA viruses, which are very stable, unlikely other RNA viruses common to us, such as Human Immunodeficiency Virus (HIV), and Foot and Mouth Diseases Virus (FMDV).


Table 2   Sequence homology between the SARS and COVID-19 isolates from different geographic locations.



However, GISAID showed a constant drift in the COVID-19 population-based upon three specific mutations in its genome. To assimilate different sequences, we chose 29 genome sequences of COVID-19 from five continents covering 17 countries (Table 1). To gather the most diverse sequences, we collected these sequences based upon their date of isolation. Among 29 viral sequences, six isolated in 2019, and the remaining 23 were isolated at different months of 2020 from January to April (Table 1). These 29 COVID-19 sequences were compared with the four SARS genome sequences to evaluate the differences between the COVID-19 and SARS and among different isolates of COVID-19. The sequences were analyzed using Geneious Prime 2020.1.1. The data suggested the SARS genomes are approximately 78.7% similar to the COVID-19 sequences (Table 2). All 29 sequences of COVID-19 are very similar (99.9% - 100% sequence similarity). Phylogenetic analysis showed that COVID-19 is closely related to SARS isolates but still genetically different (Fig. 1). All 29 COVID-19 isolates are close to each other with little change in sequence. Since variability among different COVID-19 isolates was minimal, we calculated the number of different individual nucleotides in each COVID-19 isolates that revealed a total nucleotide difference among these COVID-19 is from 1-55 nucleotides in the entire genome of approximately 29kb (Supplementary Table 1). The most diverse sequence that has a difference of 55 nucleotides were between the isolates from Australia (MT007544.1) and Turkey (EPI_ISL_427391) isolated in 2019 and April 2020, respectively (Fig. 1 & Table 2, Supplementary Table 1).


Figure 1.   Phylogenetic analysis of Coronavirus isolates from different geographic locations. The phylogenetic analysis shows sequence relatedness among COVID-19 isolates (blue) and SARS isolates (black).


Table 3   List of human miRNAs with higher target score (above 94), the number of binding sites, and miRNAs seed binding site on COVID-19 isolates.

miRNAsTarget ScoreNumber of Sites and Seed locations of miRNAs and COVID-19 genome binding sites
9916 SITES (3163, 5384, 8458, 8614, 13090, 14562, 14781, 19857, 24094, 24634, 25683, 26723, 28921, 28935, 28938, 29023)
(Note: miR-15b-5p, and miR-15a-5p have same target site)
miR-548c-5p9715 SITES (2733, 4025, 4531, 6783, 7774, 9508, 10962, 11641, 11672, 12950, 13644, 20196, 21886, 23026, 25807)
miR-548d-3p9413 SITES (6960, 7245, 7272, 8927, 11540, 13459, 15517, 15814, 18367, 21100, 22217, 22583, 26653)
miR-409-3p9612 SITES (4990, 8386, 11785, 12403, 12525, 17285, 19760, 19803, 20759, 20829, 28767, 29694)
miR-30b-5p9514 SITES (3451, 4974, 7939, 9354, 10426, 11657, 16863, 19567, 19710, 20069, 20360, 26729, 27955, 28140)
miR-505-3p9511 SITES (152, 8488, 10609, 10792, 14208, 15648, 17580, 18123, 18156, 18612, 18906)


MicroRNAs targeting SARS and COVID-19 genome

As we mentioned above, we performed miRNA analysis on the whole genome of SARS and COVID-19 due to the efficiency of miRNAs targeting both 3'UTR and coding region. Our analysis found some interesting results. We found 848 common miRNAs targeting the SARS genome (four isolates, NC_004718.3, AY291451, AY338175, AY348314) and 873 common microRNAs targeting the 29 isolates of COVID-19 genome (Supplementary Table 2). Out of a total of 848 miRNAs from SARS, only 558 commonly present in all COVID-19 isolates (Fig. 2, Supplementary Table 2). Interestingly, 315 miRNAs are unique for COVID-19 isolates and 290 miRNAs unique to SRAS (Fig. 2). Furthermore, the COVID-19 targeting miRNAs with a higher target score (above 94) showed more than ten target sites and maximum complementary miRNA-RNA seed paring (~6-8 nucleotide seed base pairing) (Table 3). We also noted that out of 29 COVID-19 isolates, 19 have identical miRNA targets (Table 4). Ten isolates have unique miRNAs targets. Among ten isolates, Netherland (EPI_ISL_422601), Australia (EPI_ISL_413214), and Wuhan (EPI_ISL_403931) showed six, four, and four unique miRNAs targets respectively. The detail is given in the table (Table 4).


Table 4   Summary of important findings on human miRNAs targeting SARS and COVID-19 genome.

Serial. NoImportant findings on human miRNAs targeting Coronavirus
1848 miRNAs are common in SARS
2873 miRNAs are common inCOVID-19
3558 miRNAs are common between SARS and COVID-19
4315 miRNAs are unique to COVID-19
5290 miRNAs are unique to SARS
610 COVID-19 isolates have some unique miR targets
7MT050493.1 (India): 1 unique miRNA (hsa-miR-449c-3p)
8MT007544.1 (Australia): 2 unique miRNAs (hsa-miR-4538, hsa-miR-4453)
9EPI_ISL_402121 (Wuhan/China): 1 unique miRNA (hsa-miR-5590-5p)
10EPI_ISL_402123 (Wuhan/China): 1 unique miRNA (hsa-miR-106a-3p)
11EPI_ISL_420799 (South Korea): 1 unique miRNA (hsa-miR-4641)
12EPI_ISL_427391 (Turkey): 1 unique miRNA (hsa-miR-496)
13EPI_ISL_429223 (Switzerland): 1 unique miRNA (hsa-miR-146b-3p)
14EPI_ISL_403931 (Wuhan): 4 unique miRNAs (hsa-miR-4474-3p, hsa-miR-6762-3p, hsa-miR-10401-5p, hsa-miR-4304)
15EPI_ISL_413214 (Australia): 4 unique miRNAs (hsa-miR-5088-5p, hsa-miR-9900, hsa-miR-3677-5p, hsa-miR-892c-5p)
16EPI_ISL_422601 (Netherland): 6 unique miRNAs (hsa-miR-4666a-3p, hsa-miR-98-3p, hsa-let-7b-3p, hsa-let-7a-3p, hsa-miR-381-3p, hsa-miR-300)



Table 5   Human miRNAs targeting the COVID-19 genome regulating KEGG pathway.

KEGG pathwayp-value#genes#miRNAs
Proteoglycans in cancer5.75E-0814576
Hippo signaling pathway1.04E-0711374
Arrhythmogenic right ventricular cardiomyopathy (ARVC)6.54E-075772
Adherens junction6.54E-076275
Renal cell carcinoma2.40E-065674
Wnt signaling pathway2.99E-0610776
Fatty acid biosynthesis1.25E-05950
ECM-receptor interaction1.25E-055670
Axon guidance1.58E-059475
FoxO signaling pathway4.68E-0510076
Ubiquitin mediated proteolysis5.75E-0510276
Pathways in cancer6.76E-0527576
ErbB signaling pathway8.02E-056675
Pancreatic cancer0.0001655373
TGF-beta signaling pathway0.0002345773
Focal adhesion0.00023414774
Rap1 signaling pathway0.00023414876
Gap junction0.0007536476
Long-term depression0.0009624573
N-Glycan biosynthesis0.0011193369
Prion diseases0.0011662066
Fatty acid metabolism0.0015473169
Endometrial cancer0.0015674172
Signaling pathways regulating pluripotency of stem cells0.0015679976
Prostate cancer0.0017696675
Colorectal cancer0.0024584972
Cell cycle0.0027038973
PI3K-Akt signaling pathway0.00270322576
Circadian rhythm0.005912670
Prolactin signaling pathway0.0063645075
Adrenergic signaling in cardiomyocytes0.0067169777
Glycosaminoglycan biosynthesis - heparan sulfate / heparin0.0069641762
Dorso-ventral axis formation0.0116822373
AMPK signaling pathway0.0121718775
Tight junction0.0126169876
Thyroid hormone signaling pathway0.014957972
Morphine addiction0.014956373
Oocyte meiosis0.014957975
Ras signaling pathway0.0149514576
Lysine degradation0.0165073366
Amphetamine addiction0.0166874572
Sphingolipid signaling pathway0.0166877976
Glutamatergic synapse0.0166877776
mRNA surveillance pathway0.017136474
RNA transport0.0183311275
MAPK signaling pathway0.01874516677
Chronic myeloid leukemia0.019255174
Estrogen signaling pathway0.0220666576
GABAergic synapse0.0235225973
p53 signaling pathway0.0263524873
Biosynthesis of unsaturated fatty acids0.0273421549
mTOR signaling pathway0.0317974570
Regulation of actin cytoskeleton0.03729813975
Protein processing in endoplasmic reticulum0.03808411274
cAMP signaling pathway0.03808413076
Oxytocin signaling pathway0.03808410477
Glycosaminoglycan biosynthesis - keratan sulfate0.0394241223
Central carbon metabolism in cancer0.046644670



Figure 2.   Common and different human miRNAs targeting SARS and COVID-19 isolates from different geographic locations.

GO and KEGG pathway analysis of miRNAs targeting COVID-19

To identify the functional relevance of human miRNAs targeting COVID-19, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation and GO analysis. The KEGG annotation analysis data reveal that these miRNAs plays important in various Cancer signaling (e.g Renal, Pancreatic, Prostate, Colorectal, Melanoma ), Hippo signaling pathway, cardiomyopathy, Wnt signaling, Circadian rhythm, stem cell signaling, Adrenergic signaling in cardiomyocytes and number of other signaling pathways (Table 5). GO analysis data showed more than 72 biological processes were associated with the miRNAs targeting COVID-19 (Table 6). The biological processes such as organelle, ion binding, cellular, biosynthesis process, protein complex, immune response, and viral process are regulated by human miRNAs targeting the COVID-19 genome. Details of KEGG annotation and GO analysis are shown in Table 5, and Table 6, respectively.


Host cellular miRNAs are known to play an antiviral role in the number of published studies [18-23]. In this study, we performed in silico analysis of human cellular miRNAs targeting SARS and COVID-19 (isolates) genome and identified some novel miRNAs. We identified number (558) of common human cellular miRNAs targeting both SARS and COVID-19 genome. Top 10 common miRNAs have a target score of ≥95 (target score between 99-95), and each miRNA contains more than at least ten sites in the targeting viral genome (Table 3), indicating possible antiviral property for coronavirus infection (for both SARS and COVID-19). It will be interesting to verify these miRNA in-vitro and in-vivo animal models to use as a therapeutic target in the future. Cocktail of multiple miRNAs mimics through the intranasal route will be useful in coronavirus infection. These human miRNAs targeting coronavirus can be useful to combat any future outbreaks. In a previous report, host cellular miRNAs-181 binds to the ORF-4 region at the viral genome of porcine reproductive and respiratory syndrome virus (PRRSV) to inhibit its replication [17]. One step further, Guo et al. (2013) delivered intranasal inhalation of miR-181 mimics to slow down the progression of PRRSV in an experimental porcine model [17]. Another study used intranasal inoculation of miR-130 mimic to protect piglets from lethal challenge of PRRSV [30]. Similarly, the intranasal administration of chemically modified five miRNA mimics protected mice from H1N1 viral infection [31].


Table 6   Human miRNAs targeting the COVID-19 genome regulating GO pathway.

GO Categoryp-value#genes#miRNAs
ion binding5.53E-2861164
cellular nitrogen compound metabolic process1.82E-2347463
biosynthetic process1.36E-1338842
neurotrophin TRK receptor signaling pathway7.06E-134444
protein binding transcription factor activity1.83E-127529
Fc-epsilon receptor signaling pathway5.76E-123224
protein complex6.82E-1138564
gene expression4.82E-107035
cellular protein modification process7.10E-1023241
extracellular matrix disassembly1.72E-092614
viral process1.82E-096049
symbiosis, encompassing mutualism through parasitism1.82E-096649
small molecule metabolic process4.04E-0922957
catabolic process1.70E-0819758
collagen catabolic process3.52E-082212
cellular component assembly5.85E-0814136
macromolecular complex assembly1.77E-0710136
blood coagulation8.36E-075526
nucleic acid binding transcription factor activity1.97E-0610738
protein complex assembly4.08E-068848
epidermal growth factor receptor signaling pathway1.64E-053123
enzyme binding1.92E-0513051
extracellular matrix organization2.18E-055121
cellular protein metabolic process3.33E-054929
xenobiotic metabolic process4.07E-052321
immune system process4.82E-0516036
nucleobase-containing compound catabolic process6.69E-059253
endoplasmic reticulum lumen0.0001543052916
response to stress0.00015993421039
innate immune response0.0002244628028
microtubule organizing center0.0004537485643
Fc-gamma receptor signaling pathway involved in phagocytosis0.000932321217
toll-like receptor TLR1:TLR2 signaling pathway0.0016155041115
toll-like receptor TLR6:TLR2 signaling pathway0.0016155041115
fibroblast growth factor receptor signaling pathway0.0016155042623
mitotic cell cycle0.0016850883945
glutathione derivative biosynthetic process0.001906053712
DNA metabolic process0.001918187934
phosphatidylinositol-mediated signaling0.0027370272022
toll-like receptor 2 signaling pathway0.0059682041217
cytoskeleton-dependent intracellular transport0.0072631341715
toll-like receptor 4 signaling pathway0.0072631341417
membrane organization0.0073466685645
cellular response to jasmonic acid stimulus0.00756371131
cell motility0.0080919766031
G2/M transition of mitotic cell cycle0.0100599052036
cell-cell signaling0.0109592156531
platelet degranulation0.0119411991115
protein N-linked glycosylation via asparagine0.0128234731414
homeostatic process0.0132230788127
post-translational protein modification0.0139168861820
toll-like receptor 10 signaling pathway0.015857167914
cell death0.0158571678525
substrate-dependent cell migration, cell extension0.01871762859
nervous system development0.0198127895126
toll-like receptor 9 signaling pathway0.0217908351016
RNA binding0.02179083516842
platelet activation0.0232234542220
extracellular matrix structural constituent0.034117778164
transcription coactivator activity0.0341177784123
cytoskeletal protein binding0.0363708467134
toll-like receptor 5 signaling pathway0.039177086914
axon guidance0.0403714364921
cAMP metabolic process0.04377834939
TRIF-dependent toll-like receptor signaling pathway0.045227284914



Table 7   List of selected human miRNAs targeting the COVID-19 genome down-regulated with age and underlying conditions.

miRNADecrease Expression in age related diseases (Human)Reference
miR-15b-5pCoronary Artery DiseaseZhu et al 2017 [37]
miR-15a-5pKidney diseaseShang et al 2019 [38]
miR-548c-5pColorectal CancerPeng et al 2018 [49]
miR-548d-3pOsteosarcomaChen et al 2019 [50]
miR-409-3pOsteosarcomaWu et al 2019 [51]
miR-30b-5pPlasma (Aging)Hatse et al 2014 [52]
miR-505-3pProstate cancerTang et al 2019 [53]
miR-520c-3pObesity/diabetesOrtega et al 2013 [39]
miR-30e-3pMyocardial InjuryWang et al 2017 [40]
miR-23cHepatocellular carcinomaZhang et al 2018 [41]
miR-30d-5pNon-small cell lung cancerGao et al, 2018 [42]
miR-4684-3pColorectal cancerWu et al, 2015 [43]
miR-518a-5pGastrointestinal tumorsShi et al, 2016 [44]


In humans, coronavirus infection is pervasive and usually causes common cold-like symptoms, but some of them can lead to serious illness. Previous coronavirus outbreak in 2002, known as SARS-CoV spread worldwide but was contained quickly [9]. On the other hand, the current coronavirus (COVID-19) is highly contagious and spread worldwide rapidly and became a global pandemic [8,11]. It will be interesting to know what separates these two viruses based on the genomic sequence. Ours (Table 2 and Fig. 1) and other data [32-34] of SARS-CoV and COVID-19 genome sequence analysis showed sequence homology of around ~78.7%, which was obvious, but our miRNA target scan data showed striking results. We found considerable changes in the number of human miRNAs targeting SARS-CoV (848 miRNAs) and COVID-19 (~873 miRNAs). Moreover, we also found unique miRNAs for SARS-CoV (290 miRNAs) and COVID-19 (315 miRNAs) isolates. At nucleotide (Table 2) and phylogenetic levels (Fig. 1), both viruses look closely related, but host cellular miRNAs target comparison differences are much more significant. This might be one of the reasons for COVID-19 to increase infectivity and easy viral propagation compared to SARS-CoV. The COVID-19 recent isolates (twenty-nine different isolates) are closely related at nucleotide, phylogenetic (Fig. 1 and Table 2), and host cellular miRNAs target level (Fig. 2 and Supplementary Table 2). The Netherland (EPI_ISL_422601), Australia (EPI_ISL_413214), and Wuhan (EPI_ISL_403931) isolates have more mutation and few different host cellular miRNAs targeting sites compared to other 26 COVID-19 isolates (Table 4). In our study, we used 29 isolates from different geographical reagion, which informs that COVID-19 nucleotide sequences and thus the human miRNAs target sites are not changing among the isolates/viruses (Table 4). In most of the COVID-19 cases, the virus entered a country from different geographical locations. At the time of writing this paper, only the USA and China had sequenced multiple viruses isolates from a different region. There is a need to sequence more of the COVID-19 viral genome from different parts of each country before coming to any conclusion.

The most important and striking feature of COVID-19 is the increased case fatality rate in aged individuals. The CDC reports 45% of cases requiring hospitalization are patients ≥65 years old [12]. Furthermore, 80% of COVID-19 related deaths occur in these patients (≥65 years old) [12]. Moreover, individuals with underlying conditions such as cardiovascular, chronic lung disease, diabetes, kidney, liver diseases, and cancer are at higher risk for severe illness and mortality. On the contrary, <1% mortality is observed in patients between 20-54 years of age or younger [12]. Based on miRNA target analysis and published literature, we hypothesized that the COVID-19 genome replicates and propagates viral particles easily in the aged individuals compared to younger due to the overall low abundance of miRNA expression with age. Recent human studies reported that the overall expression of miRNAs levels goes down with age [16, 35, 36]. For example, Huan et al. (2018) reported that 81% (103 miRNAs) microRNAs were negatively, and 19% (24 miRNAs) positively correlated with age in human peripheral blood [36]. We speculate that in younger individuals with COVID-19 infection, host cellular miRNAs bind to the complementary site of the viral RNA genome and prevent its replication; however, in an aged individual, this mechanism is not that efficient leads to accumulation of viral particle and severe illness. This might be true for underlying conditions as well. Some of the miRNAs targeting the COVID-19 genome showed low abundance (down-regulated) with some underlying conditions (Table 7). For example, miR-15b-5p (Coronary artery disease) [37], miR-15a-5p (Kidney disease) [38], miR-520c-3p (obesity/diabetes) [39], miR-30e-3p (Myocardial Injury) [40], miR-23c (hepatocellular carcinoma) [41], miR-30d-5p (non-small cell lung cancer) [42], miR-4684-3p (colorectal cancer) 43], and miR-518a-5p (Gastrointestinal stromal tumors) [44] down-regulated in pathophysiological condition.

To identify the biological relevance of COVID-19 targeting human cellular miRNAs, KEGG pathway annotation, and GO analysis was performed on target gene pools. KEGG annotation data showed that COVID-19 targeting human miRNAs plays an important role in various cancer signaling, Hippo signaling pathways, cardiac (e.g cardiomyopathy, Adrenergic signaling in cardiomyocytes), cell cycle, FoxO and number of other signaling pathways (Table.5). Furthermore, GO pathway annotation analysis showed that the COVID-19 targeting human miRNAs involved in important signaling dysregulated during age-related complications, such as biosynthesis, metabolic, cellular protein modification, and cellular component assembly. Most importantly, we also found that signaling related to immune response, Fc-epsilon receptor signaling pathway, viral process, and symbiosis, encompassing mutualism through parasitism signaling affected by the COVID-19 targeting human cellular miRNAs (Table.6). The signaling mentioned above is important to fight against viral infections [45-48]. Both KEGG and GO pathway analysis revealed that COVID-19 targeting human cellular miRNAs are involved in the number of age-related complications. Impaired GO and KEGG pathways may be due to low abundance miRNA and might be one of the contributing factors for the increasing severity and mortality of the COVID-19 infection in aged individuals and with other underlying conditions.

The dual role of host cellular miRNAs cannot be denied in the viral replication or inhibition. Host miRNAs can have both functions, antiviral, which is beneficial to host, or miRNA-viral genome interaction can increase stability and beneficiary for viral propagation [18, 20, 22]. In a viral infection, we hypothesized that host cellular miRNAs predominantly have antiviral activity. Though possible, positive regulation of viral genome translation by miRNAs is less likely. Our data and hypothesis are based on in silico analysis and realize that not all miRNAs targets will be real. Considering the many miRNAs targets identified in our in-silico analysis, even if 5% of total miRNAs targets are real (based on target score), it is possible that these could be used for therapeutic purposes. Further, in vitro and in vivo studies will be needed to validate some of these targets. However, in view of the current lack of effective treatment strategies, innovative approaches need to be considered.

Supplementary Materials

Competing interests

The author declares no competing interests.


We would like to thank The Department of Medicine for their support. This publication is based upon work supported in part by the National Institutes of Health AG036675 (National Institute on Aging-AG036675 S.F, and C.I). The above-mentioned funding did not lead to any conflict of interest regarding the publication of this manuscript.


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