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Open Access 01-12-2023 | SARS-CoV-2 | Research

Role of epigenetics in the clinical evolution of COVID-19 disease. Epigenome-wide association study identifies markers of severe outcome

Authors: Luciano Calzari, Lucia Zanotti, Elvira Inglese, Francesco Scaglione, Rebecca Cavagnola, Francesco Ranucci, Anna Maria Di Blasio, Giulio Stefanini, Gaetano Carlo, Gianfranco Parati, Davide Gentilini

Published in: European Journal of Medical Research | Issue 1/2023

Abstract

Background

COVID-19 has a wide spectrum of clinical manifestations and given its impact on morbidity and mortality, there is an unmet medical need to discover endogenous cellular and molecular biomarkers that predict the expected clinical course of the disease. Recently, epigenetics and especially DNA methylation have been pointed out as a promising tool for outcome prediction in several diseases.

Methods and results

Using the Illumina Infinium Methylation EPIC BeadChip850K, we investigated genome-wide differences in DNA methylation in an Italian Cohort of patients with comorbidities and compared severe (n = 64) and mild (123) prognosis. Results showed that the epigenetic signature, already present at the time of Hospital admission, can significantly predict risk of severe outcomes. Further analyses provided evidence of an association between age acceleration and a severe prognosis after COVID-19 infection. The burden of Stochastic Epigenetic Mutation (SEMs) has been significantly increased in patients with poor prognosis. Results have been replicated in silico considering COVID-19 negative subjects and available previously published datasets.

Conclusions

Using original methylation data and taking advantage of already published datasets, we confirmed in the blood that epigenetics is actively involved in immune response after COVID-19 infection, allowing the identification of a specific signature able to discriminate the disease evolution. Furthermore, the study showed that epigenetic drift and age acceleration are associated with severe prognosis. All these findings prove that host epigenetics undergoes notable and specific rearrangements to respond to COVID-19 infection which can be used for a personalized, timely, and targeted management of COVID-19 patients during the first stages of hospitalization.

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Coronaviridae Study Group of the International Committee on Taxonomy of V. The species severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol. 2020;5(4):536–44. https://doi.org/10.1038/s41564-020-0695-z.CrossRef

Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72314 cases from the Chinese center for disease control and prevention. JAMA. 2020;323(13):1239–42. https://doi.org/10.1001/jama.2020.2648.CrossRefPubMed

Berlin DA, Gulick RM, Martinez FJ. Severe covid-19. N Engl J Med. 2020;383(25):2451–60. https://doi.org/10.1056/NEJMcp2009575.CrossRefPubMed

Marini JJ, Gattinoni L. Management of covid-19 respiratory distress. JAMA. 2020;323(22):2329–30. https://doi.org/10.1001/jama.2020.6825.CrossRefPubMed

Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol. 2020;146(1):110–8. https://doi.org/10.1016/j.jaci.2020.04.006.CrossRefPubMedPubMedCentral

Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054–62. https://doi.org/10.1016/S0140-6736(20)30566-3.CrossRefPubMedPubMedCentral

Balnis J, Madrid A, Hogan KJ, Drake LA, Chieng HC, Tiwari A, et al. Blood DNA methylation and COVID-19 outcomes. Clin Epigenetics. 2021;13(1):118. https://doi.org/10.1186/s13148-021-01102-9.CrossRefPubMedPubMedCentral

Bernardes JP, Mishra N, Tran F, Bahmer T, Best L, Blase JI, et al. Longitudinal multi-omics analyses identify responses of megakaryocytes, erythroid cells, and plasmablasts as hallmarks of severe COVID-19. Immunity. 2020;53(6):1296–314. https://doi.org/10.1016/j.immuni.2020.11.017.CrossRefPubMedPubMedCentral

de Castro Moura M, Davalos V, Planas-Serra L, Alvarez-Errico D, Arribas C, Ruiz M, et al. Epigenome-wide association study of COVID-19 severity with respiratory failure. EBio Med. 2021;66:103339. https://doi.org/10.1016/j.ebiom.2021.103339.CrossRef

10.

Konigsberg IR, Barnes B, Campbell M, Davidson E, Zhen Y, Pallisard O, et al. Host methylation predicts SARS-CoV-2 infection and clinical outcome. Commun Med. 2021;1(1):42. https://doi.org/10.1038/s43856-021-00042-y.CrossRefPubMedPubMedCentral

11.

Zhou S, Zhang J, Xu J, Zhang F, Li P, He Y, et al. An epigenome-wide DNA methylation study of patients with COVID-19. Ann Hum Genet. 2021;85(6):221–34. https://doi.org/10.1111/ahg.12440.CrossRefPubMedPubMedCentral

12.

Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14(10):R115. https://doi.org/10.1186/gb-2013-14-10-r115.CrossRefPubMedPubMedCentral

13.

Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 2003;34(3):267–73. https://doi.org/10.1038/ng1180.CrossRefPubMed

14.

Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102(43):15545–50. https://doi.org/10.1073/pnas.0506580102.CrossRefPubMedPubMedCentral

15.

Gentilini D, Garagnani P, Pisoni S, Bacalini MG, Calzari L, Mari D, et al. Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females. Aging. 2015;7(8):568–78. https://doi.org/10.1863/aging.100792.CrossRefPubMedPubMedCentral

16.

Gentilini D, Somigliana E, Pagliardini L, Rabellotti E, Garagnani P, Bernardinelli L, et al. Multifactorial analysis of the stochastic epigenetic variability in cord blood confirmed an impact of common behavioral and environmental factors but not of in vitro conception. Clin Epigenetics. 2018;10:77. https://doi.org/10.1186/s13148-018-0510-3.CrossRefPubMedPubMedCentral

17.

Guida V, Calzari L, Fadda MT, Piceci-Sparascio F, Digilio MC, Bernardini L, et al. Genome-wide DNA methylation analysis of a cohort of 41 patients affected by oculo-auriculo-vertebral spectrum (OAVS). Int J Mol Sci. 2021;22:3. https://doi.org/10.3390/ijms22031190.CrossRef

18.

Spada E, Calzari L, Corsaro L, Fazia T, Mencarelli M, Di Blasio AM, et al. Epigenome wide association and stochastic epigenetic mutation analysis on cord blood of preterm birth. Int J Mol Sci. 2020;21:14. https://doi.org/10.3390/ijms21145044.CrossRef

19.

Masood KI, Yameen M, Ashraf J, Shahid S, Mahmood SF, Nasir A, et al. Upregulated type I interferon responses in asymptomatic COVID-19 infection are associated with improved clinical outcome. Sci Rep. 2021;11(1):22958. https://doi.org/10.1038/s41598-021-02489-4.CrossRefPubMedPubMedCentral

20.

Khan A, Sergi C. SAMHD1 as the potential link between SARS-CoV-2 infection and neurological complications. Front Neurol. 2020;11:562913. https://doi.org/10.3389/fneur.2020.562913.CrossRefPubMedPubMedCentral

21.

Chen K, Liu J, Liu S, Xia M, Zhang X, Han D, et al. Methyltransferase SETD2-mediated methylation of STAT1 is critical for interferon antiviral activity. Cell. 2017;170(3):492–506. https://doi.org/10.1016/j.cell.2017.06.042.CrossRefPubMed

22.

Wang X, Xia H, Liu S, Cao L, You F. Epigenetic regulation in antiviral innate immunity. Eur J Immunol. 2021;51(7):1641–51. https://doi.org/10.1002/eji.202048975.CrossRefPubMed

23.

Russo C, Morello G, Malaguarnera R, Piro S, Furno DL, Malaguarnera L. Candidate genes of SARS-CoV-2 gender susceptibility. Sci Rep. 2021;11(1):21968. https://doi.org/10.1038/s41598-021-01131-7.CrossRefPubMedPubMedCentral

24.

Leite MM, Gonzalez-Galarza FF, Silva B, Middleton D, Santos E. Predictive immunogenetic markers in COVID-19. Hum Immunol. 2021;82(4):247–54. https://doi.org/10.1016/j.humimm.2021.01.008.CrossRefPubMedPubMedCentral

25.

Maarifi G, Smith N, Maillet S, Moncorge O, Chamontin C, Edouard J, et al. TRIM8 is required for virus-induced IFN response in human plasmacytoid dendritic cells. Sci Adv. 2019;5(11):3511. https://doi.org/10.1126/sciadv.aax3511.CrossRef

26.

Marzano F, Guerrini L, Pesole G, Sbisa E, Tullo A. Emerging roles of TRIM8 in health and disease. Cells. 2021;10:3. https://doi.org/10.3390/cells10030561.CrossRef

27.

Ye W, Hu MM, Lei CQ, Zhou Q, Lin H, Sun MS, et al. TRIM8 negatively regulates TLR3/4-mediated innate immune response by blocking TRIF-TBK1 interaction. J Immunol. 2017;199(5):1856–64. https://doi.org/10.4049/jimmunol.1601647.CrossRefPubMed

28.

Nyati KK, Kishimoto T. Recent advances in the role of arid5a in immune diseases and cancer. Front Immunol. 2021;12:827611. https://doi.org/10.3389/fimmu.2021.827611.CrossRefPubMed

29.

Schulte-Schrepping J, Reusch N, Paclik D, Bassler K, Schlickeiser S, Zhang B, et al. Severe COVID-19 is marked by a dysregulated myeloid cell compartment. Cell. 2020;182(6):1419–40. https://doi.org/10.1016/j.cell.2020.08.001.CrossRefPubMedPubMedCentral

30.

Mardomi A, Mohammadi N, Khosroshahi HT, Abediankenari S. An update on potentials and promises of T cell co-signaling molecules in transplantation. J Cell Physiol. 2020;235(5):4183–97. https://doi.org/10.1002/jcp.29369.CrossRefPubMed

31.

Fricke-Galindo I, Falfan-Valencia R. Genetics insight for COVID-19 susceptibility and severity: a review. Front Immunol. 2021;12:622176. https://doi.org/10.3389/fimmu.2021.622176.CrossRefPubMedPubMedCentral

32.

van Minkelen R, de Visser MC, Houwing-Duistermaat JJ, Vos HL, Bertina RM, Rosendaal FR. Haplotypes of IL1B, IL1RN, IL1R1, and IL1R2 and the risk of venous thrombosis. Arterioscler Thromb Vasc Biol. 2007;27(6):1486–91. https://doi.org/10.1161/ATVBAHA.107.140384.CrossRefPubMed

33.

Cao W, Birkenbach M, Chen S. Patterns of inflammatory cell infiltration and expression of STAT6 in the lungs of patients with COVID-19: an autopsy study. Appl Immunohistochem Mol Morphol. 2022;30(5):350–7. https://doi.org/10.1097/PAI.0000000000001023.CrossRefPubMedPubMedCentral

34.

Corley MJ, Pang APS, Dody K, Mudd PA, Patterson BK, Seethamraju H, et al. Genome-wide DNA methylation profiling of peripheral blood reveals an epigenetic signature associated with severe COVID-19. J Leukoc Biol. 2021;110(1):21–6. https://doi.org/10.1002/JLB.5HI0720-466R.CrossRefPubMed

35.

Ying K, Zhai R, Pyrkov TV, Shindyapina AV, Mariotti M, Fedichev PO, et al. Genetic and phenotypic analysis of the causal relationship between aging and COVID-19. Commun Med. 2021;1:1. https://doi.org/10.1038/s43856-021-00033-z.CrossRef

36.

Meng Y, Wu P, Lu W, Liu K, Ma K, Huang L, et al. Sex-specific clinical characteristics and prognosis of coronavirus disease-19 infection in Wuhan, China: a retrospective study of 168 severe patients. PLoS Pathog. 2020;16(4):e1008520. https://doi.org/10.1371/journal.ppat.1008520.CrossRefPubMedPubMedCentral

37.

Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: a systematic literature review and meta-analysis. J Infect. 2020;81(2):e16–25. https://doi.org/10.1016/j.jinf.2020.04.021.CrossRefPubMedPubMedCentral

38.

Chen R, Liang W, Jiang M, Guan W, Zhan C, Wang T, et al. Risk factors of fatal outcome in hospitalized subjects with coronavirus disease 2019 From a nationwide analysis in China. Chest. 2020;158(1):97–105. https://doi.org/10.1016/j.chest.2020.04.010.CrossRefPubMed

39.

Liu W, Tao ZW, Wang L, Yuan ML, Liu K, Zhou L, et al. Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease. Chin Med J. 2020;133(9):1032–8. https://doi.org/10.1097/CM9.0000000000000775.CrossRefPubMedPubMedCentral

40.

Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis. 2020;20(6):669–77. https://doi.org/10.1016/S1473-3099(20)30243-7.CrossRefPubMedPubMedCentral

41.

Watanabe M, Risi R, Tuccinardi D, Baquero CJ, Manfrini S, Gnessi L. Obesity and SARS-CoV-2: a population to safeguard. Diabetes Metab Res Rev. 2020. https://doi.org/10.1002/dmrr.3325.CrossRefPubMed

42.

Zbinden-Foncea H, Francaux M, Deldicque L, Hawley JA. Does high cardiorespiratory fitness confer some protection against proinflammatory responses after infection by SARS-CoV-2? Obesity. 2020;28(8):1378–81. https://doi.org/10.1002/oby.22849.CrossRefPubMed

43.

Guzik TJ, Mohiddin SA, Dimarco A, Patel V, Savvatis K, Marelli-Berg FM, et al. COVID-19 and the cardiovascular system: implications for risk assessment, diagnosis, and treatment options. Cardiovasc Res. 2020;116(10):1666–87. https://doi.org/10.1093/cvr/cvaa106.CrossRefPubMedPubMedCentral

44.

Huang I, Lim MA, Pranata R. Diabetes mellitus is associated with increased mortality and severity of disease in COVID-19 pneumonia—a systematic review, meta-analysis, and meta-regression. Diabetes Metab Syndr. 2020;14(4):395–403. https://doi.org/10.1016/j.dsx.2020.04.018.CrossRefPubMedPubMedCentral

45.

Miyashita H, Mikami T, Chopra N, Yamada T, Chernyavsky S, Rizk D, et al. Do patients with cancer have a poorer prognosis of COVID-19? an experience in New York City. Ann Oncol. 2020;31(8):1088–9. https://doi.org/10.1016/j.annonc.2020.04.006.CrossRefPubMed

46.

Zhang L, Zhu F, Xie L, Wang C, Wang J, Chen R, et al. Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan China. Ann Onco. 2020;31(7):894–901. https://doi.org/10.1016/j.annonc.2020.03.296.CrossRef

47.

La Vignera S, Cannarella R, Condorelli RA, Torre F, Aversa A, Calogero AE. Sex-specific SARS-CoV-2 mortality: among hormone-modulated ACE2 expression, risk of venous thromboembolism and hypovitaminosis D. Int J Mol Sci. 2020;21:8. https://doi.org/10.3390/ijms21082948.CrossRef

48.

Liu F, Li L, Xu M, Wu J, Luo D, Zhu Y, et al. Prognostic value of interleukin-6, C-reactive protein, and procalcitonin in patients with COVID-19. J Clin Virol. 2020;127:104370. https://doi.org/10.1016/j.jcv.2020.104370.CrossRefPubMedPubMedCentral

49.

Fan J, Wang H, Ye G, Cao X, Xu X, Tan W, et al. Letter to the editor: low-density lipoprotein is a potential predictor of poor prognosis in patients with coronavirus disease 2019. Metabolism. 2020;107:154243. https://doi.org/10.1016/j.metabol.2020.154243.CrossRefPubMedPubMedCentral

50.

Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging. 2019;11(2):303–27. https://doi.org/10.1863/aging.101684.CrossRefPubMedPubMedCentral

51.

Muller F, Scherer M, Assenov Y, Lutsik P, Walter J, Lengauer T, et al. RnBeads 2.0: comprehensive analysis of DNA methylation data. Genome Biol. 2019;20(1):55. https://doi.org/10.1186/s13059-019-1664-9.CrossRefPubMedPubMedCentral

52.

Fiorito G, Polidoro S, Dugue PA, Kivimaki M, Ponzi E, Matullo G, et al. Social adversity and epigenetic aging: a multi-cohort study on socioeconomic differences in peripheral blood DNA methylation. Sci Rep. 2017;7(1):16266. https://doi.org/10.1038/s41598-017-16391-5.CrossRefPubMedPubMedCentral

53.

Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, et al. A beta-mixture quantile normalization method for correcting probe design bias in illumina infinium 450 k DNA methylation data. Bioinformatics. 2013;29(2):189–96. https://doi.org/10.1093/bioinformatics/bts680.CrossRefPubMed

54.

Falcon S, Gentleman R. Using GOstats to test gene lists for GO term association. Bioinformatics. 2007;23(2):257–8. https://doi.org/10.1093/bioinformatics/btl567.CrossRefPubMed

55.

da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57. https://doi.org/10.1038/nprot.2008.211.CrossRefPubMed

56.

da Huang W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37(1):1–13. https://doi.org/10.1093/nar/gkn923.CrossRefPubMed

57.

Morris TJ, Butcher LM, Feber A, Teschendorff AE, Chakravarthy AR, Wojdacz TK, et al. ChAMP: 450k chip analysis methylation pipeline. Bioinformatics. 2014;30(3):428–30. https://doi.org/10.1093/bioinformatics/btt684.CrossRefPubMed

58.

Tian Y, Morris TJ, Webster AP, Yang Z, Beck S, Feber A, et al. ChAMP: updated methylation analysis pipeline for illumina beadchips. Bioinformatics. 2017;33(24):3982–4. https://doi.org/10.1093/bioinformatics/btx513.CrossRefPubMedPubMedCentral

Title: Role of epigenetics in the clinical evolution of COVID-19 disease. Epigenome-wide association study identifies markers of severe outcome
Authors: Luciano Calzari
Lucia Zanotti
Elvira Inglese
Francesco Scaglione
Rebecca Cavagnola
Francesco Ranucci
Anna Maria Di Blasio
Giulio Stefanini
Gaetano Carlo
Gianfranco Parati
Davide Gentilini
Publication date: 01-12-2023
Publisher: BioMed Central
Keywords: SARS-CoV-2
COVID-19
Epigenetics
Published in: European Journal of Medical Research / Issue 1/2023
Electronic ISSN: 2047-783X
DOI: https://doi.org/10.1186/s40001-023-01032-7

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Role of epigenetics in the clinical evolution of COVID-19 disease. Epigenome-wide association study identifies markers of severe outcome

Abstract

Background

Methods and results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods and results

Conclusions

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