In silico analysis of the impact of toxic metals on COVID-19 complications: molecular insights

1. Cuschieri S, Grech S. Obesity population at risk of COVID-19 complications. Glob Health Epidemiol Genom 2020;5:e6. doi: 10.1017/gheg.2020.6 CuschieriS GrechS Obesity population at risk of COVID-19 complications Glob Health Epidemiol Genom 2020 5 e6 10.1017/gheg.2020.6 Open DOISearch in Google Scholar

2. Wiemers EE, Abrahams S, AlFakhri M, Hotz VJ, Schoeni RF, Seltzer JA. Disparities in vulnerability to complications from COVID-19 arising from disparities in preexisting conditions in the United States. Res Soc Stratif Mobil 2020;69:100553. doi: 10.1016/j.rssm.2020.100553 WiemersEE AbrahamsS AlFakhriM HotzVJ SchoeniRF SeltzerJA Disparities in vulnerability to complications from COVID-19 arising from disparities in preexisting conditions in the United States Res Soc Stratif Mobil 2020 69 100553 10.1016/j.rssm.2020.100553 Open DOISearch in Google Scholar

3. Long B, Brady WJ, Koyfman A, Gottlieb M. Cardiovascular complications in COVID-19. Am J Emerg Med 2020;38:1504–7. doi: 10.1016/j.ajem.2020.04.048 LongB BradyWJ KoyfmanA GottliebM Cardiovascular complications in COVID-19 Am J Emerg Med 2020 38 1504 7 10.1016/j.ajem.2020.04.048 Open DOISearch in Google Scholar

4. Kunutsor SK, Laukkanen JA. Renal complications in COVID-19: a systematic review and meta-analysis. Ann Med 2020;52:345–53. doi: 10.1080/07853890.2020.1790643 KunutsorSK LaukkanenJA Renal complications in COVID-19: a systematic review and meta-analysis Ann Med 2020 52 345 53 10.1080/07853890.2020.1790643 Open DOISearch in Google Scholar

5. Rashedi J, Mahdavi Poor B, Asgharzadeh V, Pourostadi M, Samadi Kafil H, Vegari A, Tayebi-Khosroshahi H, Asgharzadeh M. Risk factors for COVID-19. Infez Med 2020;28:469–74. PMID: 33257620 RashediJ Mahdavi PoorB AsgharzadehV PourostadiM Samadi KafilH VegariA Tayebi-KhosroshahiH AsgharzadehM Risk factors for COVID-19 Infez Med 2020 28 469 74 33257620 Search in Google Scholar

6. Zeng H, Yang Q, Yuan P, Wang X, Cheng L. Associations of essential and toxic metals/metalloids in whole blood with both disease severity and mortality in patients with COVID-19. FASEB J 2021;35(3):e21392. doi: 10.1096/fj.202002346RR ZengH YangQ YuanP WangX ChengL Associations of essential and toxic metals/metalloids in whole blood with both disease severity and mortality in patients with COVID-19 FASEB J 2021 35 3 e21392 10.1096/fj.202002346RR Open DOISearch in Google Scholar

7. Wolff D, Nee S, Hickey NS, Marschollek M. Risk factors for Covid-19 severity and fatality: a structured literature review. Infection 2021;49:15–28. doi: 10.1007/s15010-020-01509-1 WolffD NeeS HickeyNS MarschollekM Risk factors for Covid-19 severity and fatality: a structured literature review Infection 2021 49 15 28 10.1007/s15010-020-01509-1 Open DOISearch in Google Scholar

8. Skalny AV, Lima TRR, Ke T, Zhou JC, Bornhorst J, Alekseenko SI, Aaseth J, Anesti O, Sarigiannis DA, Tsatsakis A, Aschner M, Tinkov AA. Toxic metal exposure as a possible risk factor for COVID-19 and other respiratory infectious diseases. Food Chem Toxicol 2020;146:111809. doi: 10.1016/j.fct.2020.111809 SkalnyAV LimaTRR KeT ZhouJC BornhorstJ AlekseenkoSI AasethJ AnestiO SarigiannisDA TsatsakisA AschnerM TinkovAA Toxic metal exposure as a possible risk factor for COVID-19 and other respiratory infectious diseases Food Chem Toxicol 2020 146 111809 10.1016/j.fct.2020.111809 Open DOISearch in Google Scholar

9. Nordberg GF, Costa M, editors. Handbook on the Toxicology of Metals. Volume I and II. 5th ed. New York (NY): Academic Press; 2022. NordbergGF CostaM editors. Handbook on the Toxicology of Metals I and II 5th ed. New York (NY) Academic Press 2022 Search in Google Scholar

10. ATSDR. ATSDR’s Substance Priority List, 2022 [displayed 27 May 2024]. Available at https://www.atsdr.cdc.gov/spl/index.html ATSDR ATSDR’s Substance Priority List 2022 [displayed 27 May 2024]. Available at https://www.atsdr.cdc.gov/spl/index.html Search in Google Scholar

11. International Agency for Research on Cancer (IARC). Arsenic and arsenic compounds. In: Arsenic, metals, fibres, and dusts. Volume 100C. IARC monographs on the evaluation of carcinogenic risks to humans. Lyon: IARC; 2012. p. 41–93. International Agency for Research on Cancer (IARC) Arsenic and arsenic compounds In: Arsenic, metals, fibres, and dusts. Volume 100C. IARC monographs on the evaluation of carcinogenic risks to humans Lyon IARC 2012 41 93 Search in Google Scholar

12. International Agency for Research on Cancer (IARC). Chromium (VI) compounds. In: Arsenic, metals, fibres, and dusts. Volume 100C. IARC monographs on the evaluation of carcinogenic risks to humans. Lyon: IARC; 2012. p. 147–68. International Agency for Research on Cancer (IARC) Chromium (VI) compounds In: Arsenic, metals, fibres, and dusts. Volume 100C. IARC monographs on the evaluation of carcinogenic risks to humans Lyon IARC 2012 147 68 Search in Google Scholar

13. International Agency for Research on Cancer (IARC). Cadmium and cadmium compounds. In: Arsenic, metals, fibres, and dusts. Volume 100C. IARC monographs on the evaluation of carcinogenic risks to humans. Lyon: IARC; 2012. p. 121–45. International Agency for Research on Cancer (IARC) Cadmium and cadmium compounds In: Arsenic, metals, fibres, and dusts. Volume 100C. IARC monographs on the evaluation of carcinogenic risks to humans Lyon IARC 2012 121 45 Search in Google Scholar

14. International Agency for Research on Cancer (IARC). Nickel and nickel compounds. In: Arsenic, metals, fibres, and dusts. Volume 100C. IARC monographs on the evaluation of carcinogenic risks to humans. Lyon: IARC; 2012. p. 169–218. International Agency for Research on Cancer (IARC) Nickel and nickel compounds In: Arsenic, metals, fibres, and dusts. Volume 100C. IARC monographs on the evaluation of carcinogenic risks to humans Lyon IARC 2012 169 218 Search in Google Scholar

15. Harris SM, Jin Y, Loch-Caruso R, Padilla IY, Meeker JD, Bakulski KM. Identification of environmental chemicals targeting miscarriage genes and pathways using the comparative toxicogenomics database. Environ Res 2020;184:109259. doi: 10.1016/j.envres.2020.109259 HarrisSM JinY Loch-CarusoR PadillaIY MeekerJD BakulskiKM Identification of environmental chemicals targeting miscarriage genes and pathways using the comparative toxicogenomics database Environ Res 2020 184 109259 10.1016/j.envres.2020.109259 Open DOISearch in Google Scholar

16. Baralić K, Živančević K, Božić D, Jennen D, Buha Djordjevic A, Antonijević Miljaković E, Đukić-Ćosić D. Potential genomic biomarkers of obesity and its comorbidities for phthalates and bisphenol A mixture: In silico toxicogenomic approach. BIOCELL 2022;46:519–33. doi: 10.32604/biocell.2022.018271 BaralićK ŽivančevićK BožićD JennenD Buha DjordjevicA Antonijević MiljakovićE Đukić-ĆosićD Potential genomic biomarkers of obesity and its comorbidities for phthalates and bisphenol A mixture: In silico toxicogenomic approach BIOCELL 2022 46 519 33 10.32604/biocell.2022.018271 Open DOISearch in Google Scholar

17. Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ. Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks. Nucleic Acids Res 2009;37(Database issue):D786–92. doi: 10.1093/nar/gkn580 DavisAP MurphyCG Saraceni-RichardsCA RosensteinMC WiegersTC MattinglyCJ Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks Nucleic Acids Res 2009 37 Database issue D786 92 10.1093/nar/gkn580 Open DOISearch in Google Scholar

18. Wiegers TC, Davis AP, Cohen KB, Hirschman L, Mattingly CJ. Text mining and manual curation of chemical-gene-disease networks for the Comparative Toxicogenomics Database (CTD). BMC Bioinformatics 2009;10:326. doi: 10.1186/1471-2105-10-326 WiegersTC DavisAP CohenKB HirschmanL MattinglyCJ Text mining and manual curation of chemical-gene-disease networks for the Comparative Toxicogenomics Database (CTD) BMC Bioinformatics 2009 10 326 10.1186/1471-2105-10-326 Open DOISearch in Google Scholar

19. Montojo J, Zuberi K, Rodriguez H, Bader GD, Morris Q. GeneMANIA: Fast gene network construction and function prediction for Cytoscape. F1000Res 2014;3:153. doi: 10.12688/f1000research.4572.1 MontojoJ ZuberiK RodriguezH BaderGD MorrisQ GeneMANIA: Fast gene network construction and function prediction for Cytoscape F1000Res 2014 3 153 10.12688/f1000research.4572.1 Open DOISearch in Google Scholar

20. Warde-Farley D, Donaldson SL, Comes O, Zuberi K, Badrawi R, Chao P, Franz M, Grouios C, Kazi F, Lopes CT, Maitland A, Mostafavi S, Montojo J, Shao Q, Wright G, Bader GD, Morris Q. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res 2010;38(Web Server issue):W214–20. doi: 10.1093/nar/gkq537 Warde-FarleyD DonaldsonSL ComesO ZuberiK BadrawiR ChaoP FranzM GrouiosC KaziF LopesCT MaitlandA MostafaviS MontojoJ ShaoQ WrightG BaderGD MorrisQ The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function Nucleic Acids Res 2010 38 Web Server issue W214 20 10.1093/nar/gkq537 Open DOISearch in Google Scholar

21. Zuberi K, Franz M, Rodriguez H, Montojo J, Lopes CT, Bader GD, Morris Q. GeneMANIA Prediction Server 2013 Update. Nucleic Acids Res 2013;41(Web Server issue):W115–22. doi: 10.1093/nar/gkt533 ZuberiK FranzM RodriguezH MontojoJ LopesCT BaderGD MorrisQ GeneMANIA Prediction Server 2013 Update Nucleic Acids Res 2013 41 Web Server issue W115 22 10.1093/nar/gkt533 Open DOISearch in Google Scholar

22. Chen J, Bardes EE, Aronow BJ, Jegga AG. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Res 2009;37(Web Server issue):W305–11. doi: 10.1093/nar/gkp427 ChenJ BardesEE AronowBJ JeggaAG ToppGene Suite for gene list enrichment analysis and candidate gene prioritization Nucleic Acids Res 2009 37 Web Server issue W305 11 10.1093/nar/gkp427 Open DOISearch in Google Scholar

23. Landvik NE, Hart K, Skaug V, Stangeland LB, Haugen A, Zienolddiny S. A specific interleukin-1B haplotype correlates with high levels of IL1B mRNA in the lung and increased risk of non-small cell lung cancer. Carcinogenesis 2009;30:1186–92. doi: 10.1093/carcin/bgp122 LandvikNE HartK SkaugV StangelandLB HaugenA ZienolddinyS A specific interleukin-1B haplotype correlates with high levels of IL1B mRNA in the lung and increased risk of non-small cell lung cancer Carcinogenesis 2009 30 1186 92 10.1093/carcin/bgp122 Open DOISearch in Google Scholar

24. Cavalli G, De Luca G, Campochiaro C, Della-Torre E, Ripa M, Canetti D, Oltolini C, Castiglioni B, Tassan Din C, Boffini N, Tomelleri A, Farina N, Ruggeri A, Rovere-Querini P, Di Lucca G, Martinenghi S, Scotti R, Tresoldi M, Ciceri F, Landoni G, Zangrillo A, Scarpellini P, Dagna L. Interleukin-1 blockade with high-dose anakinra in patients with COVID-19, acute respiratory distress syndrome, and hyperinflammation: a retrospective cohort study. Lancet Rheumatol 2020;2(6):e325–31. doi: 10.1016/S2665-9913(20)30127-2 CavalliG De LucaG CampochiaroC Della-TorreE RipaM CanettiD OltoliniC CastiglioniB Tassan DinC BoffiniN TomelleriA FarinaN RuggeriA Rovere-QueriniP Di LuccaG MartinenghiS ScottiR TresoldiM CiceriF LandoniG ZangrilloA ScarpelliniP DagnaL Interleukin-1 blockade with high-dose anakinra in patients with COVID-19, acute respiratory distress syndrome, and hyperinflammation: a retrospective cohort study Lancet Rheumatol 2020 2 6 e325 31 10.1016/S2665-9913(20)30127-2 Open DOISearch in Google Scholar

25. Thomson EM, Williams A, Yauk CL, Vincent R. Overexpression of tumor necrosis factor-α in the lungs alters immune response, matrix remodeling, and repair and maintenance pathways. Am J Pathol 2012;180:1413–30. doi: 10.1016/j.ajpath.2011.12.020 ThomsonEM WilliamsA YaukCL VincentR Overexpression of tumor necrosis factor-α in the lungs alters immune response, matrix remodeling, and repair and maintenance pathways Am J Pathol 2012 180 1413 30 10.1016/j.ajpath.2011.12.020 Open DOISearch in Google Scholar

26. Robinson PC, Richards D, Tanner HL, Feldmann M. Accumulating evidence suggests anti-TNF therapy needs to be given trial priority in COVID-19 treatment. Lancet Rheumatol 2020;2(11):e653–5. doi: 10.1016/S2665-9913(20)30309-X RobinsonPC RichardsD TannerHL FeldmannM Accumulating evidence suggests anti-TNF therapy needs to be given trial priority in COVID-19 treatment Lancet Rheumatol 2020 2 11 e653 5 10.1016/S2665-9913(20)30309-X Open DOISearch in Google Scholar

27. Huaux F, Louahed J, Hudspith B, Meredith C, Delos M, Renauld JC, Lison D. Role of interleukin-10 in the lung response to silica in mice. Am J Respir Cell Mol Biol 1998;18:51–9. doi: 10.1165/ajrcmb.18.1.2911 HuauxF LouahedJ HudspithB MeredithC DelosM RenauldJC LisonD Role of interleukin-10 in the lung response to silica in mice Am J Respir Cell Mol Biol 1998 18 51 9 10.1165/ajrcmb.18.1.2911 Open DOISearch in Google Scholar

28. Chen H, Liu W, Wang Y, Liu D, Zhao L, Yu J. SARS-CoV-2 activates lung epithelial cell proinflammatory signaling and leads to immune dysregulation in COVID-19 patients. EBioMedicine 2021;70:103500. doi: 10.1016/j.ebiom.2021.103500 ChenH LiuW WangY LiuD ZhaoL YuJ SARS-CoV-2 activates lung epithelial cell proinflammatory signaling and leads to immune dysregulation in COVID-19 patients EBioMedicine 2021 70 103500 10.1016/j.ebiom.2021.103500 Open DOISearch in Google Scholar

29. Han H, Ma Q, Li C, Liu R, Zhao L, Wang W, Zhang P, Liu X, Gao G, Liu F, Jiang Y, Cheng X, Zhu C, Xia Y. Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors. Emerg Microb Infect 2020;9:1123–30. doi: 10.1080/22221751.2020.1770129 HanH MaQ LiC LiuR ZhaoL WangW ZhangP LiuX GaoG LiuF JiangY ChengX ZhuC XiaY Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors Emerg Microb Infect 2020 9 1123 30 10.1080/22221751.2020.1770129 Open DOISearch in Google Scholar

30. Polidoro RB, Hagan RS, De Santis Santiago R, Schmidt NW. Overview: systemic inflammatory response derived from lung injury caused by SARS-CoV-2 infection explains severe outcomes in COVID-19. Front Immunol 2020;11:1626. doi: 10.3389/fimmu.2020.01626 PolidoroRB HaganRS De Santis SantiagoR SchmidtNW Overview: systemic inflammatory response derived from lung injury caused by SARS-CoV-2 infection explains severe outcomes in COVID-19 Front Immunol 2020 11 1626 10.3389/fimmu.2020.01626 Open DOISearch in Google Scholar

31. Jain R, Ramaswamy S, Harilal D, Uddin M, Loney T, Nowotny N, Alsuwaidi H, Varghese R, Deesi Z, Alkhajeh A, Khansaheb H, Alsheikh-Ali A, Abou Tayoun A. Host transcriptomic profiling of COVID-19 patients with mild, moderate, and severe clinical outcomes. Comput Struct Biotechnol J 2021;19:153–60. doi: 10.1016/j.csbj.2020.12.016 JainR RamaswamyS HarilalD UddinM LoneyT NowotnyN AlsuwaidiH VargheseR DeesiZ AlkhajehA KhansahebH Alsheikh-AliA Abou TayounA Host transcriptomic profiling of COVID-19 patients with mild, moderate, and severe clinical outcomes Comput Struct Biotechnol J 2021 19 153 60 10.1016/j.csbj.2020.12.016 Open DOISearch in Google Scholar

32. Chatterjee SK, Saha S, Munoz MNM. Molecular pathogenesis, immunopathogenesis and novel therapeutic strategy against COVID-19. Front Mol Biosci 2020;7:196. doi: 10.3389/fmolb.2020.00196 ChatterjeeSK SahaS MunozMNM Molecular pathogenesis, immunopathogenesis and novel therapeutic strategy against COVID-19 Front Mol Biosci 2020 7 196 10.3389/fmolb.2020.00196 Open DOISearch in Google Scholar

33. Kishimoto T, Taga T, Akira S. Cytokine signal transduction. Cell 1994;76:253–62. doi: 10.1016/0092-8674(94)90333-6 KishimotoT TagaT AkiraS Cytokine signal transduction Cell 1994 76 253 62 10.1016/0092-8674(94)90333-6 Open DOISearch in Google Scholar

34. Mangalmurti N, Hunter CA. Cytokine storms: understanding COVID-19. Immunity 2020;53:19–25. doi: 10.1016/j.immuni.2020.06.017 MangalmurtiN HunterCA Cytokine storms: understanding COVID-19 Immunity 2020 53 19 25 10.1016/j.immuni.2020.06.017 Open DOISearch in Google Scholar

35. Maxwell AJ, Ding J, You Y, Dong Z, Chehade H, Alvero A, Mor Y, Draghici S, Mor G. Identification of key signaling pathways induced by SARS-CoV2 that underlie thrombosis and vascular injury in COVID-19 patients. J Leukoc Biol 2021;109:35–47. doi: 10.1002/JLB.4COVR0920-552RR MaxwellAJ DingJ YouY DongZ ChehadeH AlveroA MorY DraghiciS MorG Identification of key signaling pathways induced by SARS-CoV2 that underlie thrombosis and vascular injury in COVID-19 patients J Leukoc Biol 2021 109 35 47 10.1002/JLB.4COVR0920-552RR Open DOISearch in Google Scholar

36. Moore JB, June CH. Cytokine release syndrome in severe COVID-19. Science 2020;368:473–4. doi: 10.1126/science.abb8925 MooreJB JuneCH Cytokine release syndrome in severe COVID-19 Science 2020 368 473 4 10.1126/science.abb8925 Open DOISearch in Google Scholar

37. Dong Y, Li Z, Ding S, Liu S, Tang Z, Jia L, Liu J, Liu Y. HIV infection and risk of COVID-19 mortality: A meta-analysis. Medicine (Baltimore) 2021;100(26):e26573. doi: 10.1097/MD.0000000000026573 DongY LiZ DingS LiuS TangZ JiaL LiuJ LiuY HIV infection and risk of COVID-19 mortality: A meta-analysis Medicine (Baltimore) 2021 100 26 e26573 10.1097/MD.0000000000026573 Open DOISearch in Google Scholar

38. Ssentongo P, Heilbrunn ES, Ssentongo AE, Advani S, Chinchilli VM, Nunez JJ, Du P. Epidemiology and outcomes of COVID-19 in HIV-infected individuals: a systematic review and meta-analysis. Sci Rep 2021;11(1):6283. doi: 10.1038/s41598-021-85359-3 SsentongoP HeilbrunnES SsentongoAE AdvaniS ChinchilliVM NunezJJ DuP Epidemiology and outcomes of COVID-19 in HIV-infected individuals: a systematic review and meta-analysis Sci Rep 2021 11 1 6283 10.1038/s41598-021-85359-3 Open DOISearch in Google Scholar

39. Zawawi A, Alghanmi M, Alsaady I, Gattan H, Zakai H, Couper K. The impact of COVID-19 pandemic on malaria elimination. Parasite Epidemiol Control 202;11:e00187. doi: 10.1016/j.parepi.2020.e00187 ZawawiA AlghanmiM AlsaadyI GattanH ZakaiH CouperK The impact of COVID-19 pandemic on malaria elimination Parasite Epidemiol Control 2020 11 e00187 10.1016/j.parepi.2020.e00187 Open DOISearch in Google Scholar

40. Hussein MIH, Albashir AAD, Elawad OAMA, Homeida A. Malaria and COVID-19: unmasking their ties. Malar J 2020;19(1):457. doi: 10.1186/s12936-020-03541-w HusseinMIH AlbashirAAD ElawadOAMA HomeidaA Malaria and COVID-19: unmasking their ties Malar J 2020 19 1 457 10.1186/s12936-020-03541-w Open DOISearch in Google Scholar

41. Davis AP, Murphy CG, Rosenstein MC, Wiegers TC, Mattingly CJ. The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study. BMC Med Genomics 2008;1:48. doi: 10.1186/1755-8794-1-48 DavisAP MurphyCG RosensteinMC WiegersTC MattinglyCJ The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study BMC Med Genomics 2008 1 48 10.1186/1755-8794-1-48 Open DOISearch in Google Scholar