Skip to content
2000
Volume 6, Issue 3
  • ISSN: 2666-7967
  • E-ISSN: 2666-7975

Abstract

Background

The rapid spread of the SARS-CoV-2 virus has had a global impact on various ethnic groups. In order to assess the genetic predisposition of the Indian population towards COVID-19, a comparative analysis was conducted using the Human Leukocyte Antigen (HLA) to investigate the frequencies of polymorphisms directly or potentially associated with COVID-19 susceptibility, severity, immune response, and fatal outcomes in comparison to other major populations.

Objectives

The objective of this study is to evaluate the genetic predisposition of the Indian population to COVID-19 by analyzing the frequencies and associations of Human Leukocyte Antigen (HLA) polymorphisms. In addition, by delineating the role of specific HLA variants in the Indian context, the study seeks to enhance our understanding of genetic factors influencing COVID-19 impact and contribute to personalized approaches for disease management and prevention across diverse ethnic groups.

Methods

We collected allelic information for DRB1 gene from 653 populations globally, as documented in The Allele Frequency Net Database (AFND). Data on COVID-19 susceptibility, severity, mortality, and protective factors were obtained from a previous global study. This study aimed to compare the specific frequencies of HLA-DRB1* in different ethnic groups, including other Indian populations with COVID-19-associated alleles and protective factors.

Results

HLA-DRB1*01 was identified as a significant determinant of COVID-19 susceptibility among patients in 28 states of Mexico, whereas DRB1*08 in Saudi Arabian populations, DRB1*09:01 in Japanese populations, and DRB1*15:01 in Italian populations also showed this association. Likewise, DRB1*04 in the Iranian population played a role in disease severity, and DRB1*08 in the Italian population was associated with mortality in COVID-19 patients. In addition, alleles DRB1*01:01 and DRB1*04:01 were found to exhibit a protective role in Northeast England, whereas DRB1*04 demonstrated protective effects in Saudi Arabian populations.

Conclusion

The involvement of HLA in COVID-19 requires further investigation, and epidemiological studies should focus on HLA profiles as determinants of the host immune system. Prolonged homozygosity in particular genomic regions could potentially increase susceptibility to COVID-19 infection. Therefore, prudent management strategies are recommended for this pandemic in isolated communities in India and worldwide.

Loading

Article metrics loading...

/content/journals/covid/10.2174/0126667975332701240920074118
2024-10-01
2025-09-27
Loading full text...

Full text loading...

References

  1. JoshiR.K. MehendaleS.M. Prevention and control of COVID-19 in India: Strategies and options.Med. J. Armed Forces India202177Suppl. 2S237S24110.1016/j.mjafi.2021.05.009 34334886
    [Google Scholar]
  2. ZhuN. ZhangD. WangW. A Novel Coronavirus from Patients with Pneumonia in China, 2019.N. Engl. J. Med.2020382872773310.1056/NEJMoa2001017 31978945
    [Google Scholar]
  3. ZhuZ. LianX. SuX. WuW. MarraroG.A. ZengY. From SARS and MERS to COVID-19: A brief summary and comparison of severe acute respiratory infections caused by three highly pathogenic human coronaviruses.Respir. Res.202021122410.1186/s12931‑020‑01479‑w 32854739
    [Google Scholar]
  4. GuoL. ShiZ. ZhangY. Comorbid diabetes and the risk of disease severity or death among 8807 COVID-19 patients in China: A meta-analysis.Diabetes Res. Clin. Pract.202016610834610.1016/j.diabres.2020.108346 32710998
    [Google Scholar]
  5. ZhangJ. CaoY. TanG. Clinical, radiological, and laboratory characteristics and risk factors for severity and mortality of 289 hospitalized COVID-19 patients.Allergy202176253355010.1111/all.14496 32662525
    [Google Scholar]
  6. RubinS.J.S. FalksonS.R. DegnerN.R. BlishC. Clinical characteristics associated with COVID-19 severity in California.J. Clin. Transl. Sci.202151e310.1017/cts.2020.40 34192044
    [Google Scholar]
  7. RiccardoF. AjelliM. AndrianouX.D. Epidemiological characteristics of COVID-19 cases and estimates of the reproductive numbers 1 month into the epidemic, Italy, 28 January to 31 March 2020.Euro Surveill.20202549200079010.2807/1560‑7917.ES.2020.25.49.2000790 33303064
    [Google Scholar]
  8. CaoM. ZhangD. WangY. Clinical Features of Patients Infected with the 2019 Novel Coronavirus (COVID-19) in Shanghai, China.medRxiv202010.1101/2020.03.04.20030395
    [Google Scholar]
  9. JinJ.M. BaiP. HeW. Gender Differences in Patients With COVID-19: Focus on Severity and Mortality.Front. Public Health2020815210.3389/fpubh.2020.00152 32411652
    [Google Scholar]
  10. Gallo MarinB. AghagoliG. LavineK. Predictors of COVID-19 severity: A literature review.Rev. Med. Virol.202131111010.1002/rmv.2146 32845042
    [Google Scholar]
  11. CDCCOVID-19 update for the United States.Available From: https://covid.cdc.gov/coviddata-tracker 2020
  12. BodeB. GarrettV. MesslerJ. Glycemic Characteristics and Clinical Outcomes of COVID-19 Patients Hospitalized in the United States.J. Diabetes Sci. Technol.202014481382110.1177/1932296820924469 32389027
    [Google Scholar]
  13. HuangC. WangY. LiX. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.Lancet20203951022349750610.1016/S0140‑6736(20)30183‑5 31986264
    [Google Scholar]
  14. WangS. MaP. ZhangS. Fasting blood glucose at admission is an independent predictor for 28-day mortality in patients with COVID-19 without previous diagnosis of diabetes: A multi-centre retrospective study.Diabetologia202063102102211110.1007/s00125‑020‑05209‑1 32647915
    [Google Scholar]
  15. RanL. WangW. AiM. KongY. ChenJ. KuangL. Psychological resilience, depression, anxiety, and somatization symptoms in response to COVID-19: A study of the general population in China at the peak of its epidemic.Soc. Sci. Med.202026211326110.1016/j.socscimed.2020.113261 32758794
    [Google Scholar]
  16. FresánU. GuevaraM. ElíaF. AlbénizE. BurguiC. CastillaJ. Independent Role of Severe Obesity as a Risk Factor for COVID-19 Hospitalization: A Spanish Population-Based Cohort Study.Obesity (Silver Spring)2021291293710.1002/oby.23029 32885905
    [Google Scholar]
  17. PouraliF. AfshariM. Alizadeh-NavaeiR. JavidniaJ. MoosazadehM. HessamiA. Relationship between blood group and risk of infection and death in COVID-19: A live meta-analysis.New Microbes New Infect.20203710074310.1016/j.nmni.2020.100743 32837730
    [Google Scholar]
  18. GargI. SrivastavaS. DograV. Potential association of COVID-19 and ABO blood group: An Indian study.Microb. Pathog.202115810500810.1016/j.micpath.2021.105008 34087389
    [Google Scholar]
  19. FilipR. Gheorghita PuscaseluR. Anchidin-NorocelL. DimianM. SavageW.K. Global challenges to public health care systems during the COVID-19 pandemic: A review of pandemic measures and problems.J. Pers. Med.2022128129510.3390/jpm12081295
    [Google Scholar]
  20. WangF. HuangS. GaoR. Initial whole-genome sequencing and analysis of the host genetic contribution to COVID-19 severity and susceptibility.Cell Discov.2020618310.1038/s41421‑020‑00231‑4 33298875
    [Google Scholar]
  21. LitteraR. CampagnaM. DeiddaS. Human leukocyte antigen complex and other immunogenetic and clinical factors influence susceptibility or protection to SARS-CoV-2 infection and severity of the disease course. The sardinian experience.Front. Immunol.20201160568810.3389/fimmu.2020.605688 33343579
    [Google Scholar]
  22. YungY.L. ChengC.K. ChanH.Y. Association of HLA-B22 serotype with SARS-CoV-2 susceptibility in Hong Kong Chinese patients.HLA202197212713210.1111/tan.14135 33179437
    [Google Scholar]
  23. AmorosoA. MagistroniP. VespasianoF. HLA and AB0 polymorphisms may influence SARS-CoV-2 infection and COVID-19 severity.Transplantation2021105119320010.1097/TP.0000000000003507 33141807
    [Google Scholar]
  24. SalehA. SultanA. ElashryM.A. Association of TNF-α G-308 a promoter polymorphism with the course and outcome of COVID-19 patients.Immunol. Invest.202251354655710.1080/08820139.2020.1851709 33228423
    [Google Scholar]
  25. ValentiL. GriffiniS. LamorteG. Chromosome 3 cluster rs11385942 variant links complement activation with severe COVID-19.J. Autoimmun.202111710259510.1016/j.jaut.2021.102595 33453462
    [Google Scholar]
  26. Sanchez-MazasA. HLA studies in the context of coronavirus outbreaks.Swiss Med. Wkly.20201501516w2024810.4414/smw.2020.20248 32297958
    [Google Scholar]
  27. SrivastavaA. BandopadhyayA. DasD. Genetic Association of ACE2 rs2285666 Polymorphism With COVID-19 Spatial Distribution in India.Front. Genet.20201156474110.3389/fgene.2020.564741 33101387
    [Google Scholar]
  28. RavikanthV. SasikalaM. NaveenV. A variant in TMPRSS2 is associated with decreased disease severity in COVID-19.Meta Gene20212910093010.1016/j.mgene.2021.100930 34075330
    [Google Scholar]
  29. SinghP.P. SrivastavaA. SultanaG.N.N. The major genetic risk factor for severe COVID-19 does not show any association among South Asian populations.Sci. Rep.20211111234610.1038/s41598‑021‑91711‑4 34117310
    [Google Scholar]
  30. ShkurnikovM. NersisyanS. JankevicT. Association of HLA class I genotypes with severity of corona-virus disease-19.Front. Immunol.20211264190010.3389/fimmu.2021.641900 33732261
    [Google Scholar]
  31. PisantiS. DeelenJ. GallinaA.M. Correlation of the two most frequent HLA haplotypes in the Italian population to the differential regional incidence of COVID-19.J. Transl. Med.202018135210.1186/s12967‑020‑02515‑5 32933522
    [Google Scholar]
  32. NovelliA. AndreaniM. BiancolellaM. HLA allele frequencies and susceptibility to COVID-19 in a group of 99 Italian patients.HLA202096561061410.1111/tan.14047 32827207
    [Google Scholar]
  33. CorrealeP. MuttiL. PentimalliF. HLA-B*44 and C*01 prevalence correlates with Covid19 spreading across Italy.Int. J. Mol. Sci.20202115520510.3390/ijms21155205 32717807
    [Google Scholar]
  34. LorenteL. MartínM.M. FrancoA. HLA genetic polymorphisms and prognosis of patients with COVID-19.Med Intensiva20214529610310.1016/j.medin.2020.08.004
    [Google Scholar]
  35. Iturrieta-ZuazoI. RitaC.G. García-SoidánA. Possible role of HLA class-I genotype in SARS-CoV-2 infection and progression: A pilot study in a cohort of Covid-19 Spanish patients.Clin. Immunol.202021910857210.1016/j.clim.2020.108572 32810602
    [Google Scholar]
  36. AnzurezA. NakaI. MikiS. Association of HLA-DRB1 *09:01 with severe COVID-19.HLA2021981374210.1111/tan.14256 33734601
    [Google Scholar]
  37. WarrenR.L. BirolI. HLA alleles measured from COVID-19 patient transcriptomes reveal associations with disease prognosis in a New York cohort.PeerJ20219e1236810.7717/peerj.12368 34722002
    [Google Scholar]
  38. KhorS.S. OmaeY. NishidaN. HLA-A*11:01:01:01, HLA-C*12:02:02:01-HLA-B*52:01:02:02, Age and sex are associated with severity of japanese COVID-19 with respiratory failure.Front. Immunol.20211265857010.3389/fimmu.2021.658570 33968060
    [Google Scholar]
  39. NaemiF.M.A. Al-adwaniS. Al-khatabiH. Al-nazawiA. Association between the HLA genotype and the severity of COVID-19 infection among South Asians.J. Med. Virol.20219374430443710.1002/jmv.27003 33830530
    [Google Scholar]
  40. LinM. TsengH.K. TrejautJ.A. Association of HLA class I with severe acute respiratory syndrome coronavirus infection.BMC Med. Genet.200341910.1186/1471‑2350‑4‑9 12969506
    [Google Scholar]
  41. OladejoB.O. AdeboboyeC.F. AdeboluT.T. Understanding the genetic determinant of severity in viral diseases: A case of SARS-Cov-2 infection.Egypt. J. Med. Hum. Genet.20202117710.1186/s43042‑020‑00122‑z 38624552
    [Google Scholar]
  42. Romero-LópezJ.P. Carnalla-CortésM. Pacheco-OlveraD.L. A bioinformatic prediction of antigen presentation from SARS-CoV-2 spike protein revealed a theoretical correlation of HLA-DRB1*01 with COVID-19 fatality in Mexican population: An ecological approach.J. Med. Virol.20219342029203810.1002/jmv.26561 32986250
    [Google Scholar]
  43. EbrahimiS. Ghasemi-BasirH.R. MajzoobiM.M. Rasouli-SaravaniA. HajilooiM. SolgiG. HLA-DRB1*04 may predict the severity of disease in a group of Iranian COVID-19 patients.Hum. Immunol.2021821071972510.1016/j.humimm.2021.07.004 34294460
    [Google Scholar]
  44. AbdelhafizA.S. AliA. FoudaM.A. HLA-B*15 predicts survival in Egyptian patients with COVID-19.Hum. Immunol.2022831101610.1016/j.humimm.2021.09.007 34607724
    [Google Scholar]
  45. LangtonS. DixonA. FarrellG. Six months in: Pandemic crime trends in England and Wales.Crime Sci.2021101610.1186/s40163‑021‑00142‑z 33686363
    [Google Scholar]
  46. GuanW. NiZ. HuY. LiangW. OuC. HeJ. Clinical Characteristics of Coronavirus Disease 2019 in China.J. Emerg. Med.202058471171210.1056/NEJMoa2002032
    [Google Scholar]
  47. RodJE Oviedo-TrespalaciosO Cortes-RamirezJ A brief-review of the risk factors for covid-19 severity.Rev Saude Pub2020541e1110.11606/s1518‑8787.2020054002481
    [Google Scholar]
  48. LavianoA. KoverechA. ZanettiM. Nutrition support in the time of SARS-CoV-2 (COVID-19).Nutrition20207411083410.1016/j.nut.2020.110834 32276799
    [Google Scholar]
  49. RomanoL. BilottaF. DauriM. Short Report-Medical nutrition therapy for critically ill patients with COVID-19.Eur. Rev. Med. Pharmacol. Sci.20202474035403910.26355/eurrev_202004_20874 32329880
    [Google Scholar]
  50. NgM.H.L. LauK.M. LiL. Association of human-leukocyte-antigen class I (B*0703) and class II (DRB1*0301) genotypes with susceptibility and resistance to the development of severe acute respiratory syndrome.J. Infect. Dis.2004190351551810.1086/421523 15243926
    [Google Scholar]
  51. BalakrishnanK. PitchappanR.M. SuzukiK. KumarU.S. SanthakumariR. TokunagaK. HLA affinities of Iyers, a Brahmin population of Tamil Nadu, South India.Hum. Biol.1996684523537 8754259
    [Google Scholar]
  52. BalakrishnanK. RathikaC. KamarajR. Gradients in distribution of HLA – DRB1 alleles in castes and tribes of south India.Int. J. Hum. Genet.2012121455510.1080/09723757.2012.11886162
    [Google Scholar]
  53. KamarajR. BalakrishnanK. DhivakarM. Distribution of HLA alleles and haplotypes in tamil-speaking south Indian populations: Affinities with Spanish and Austronesian.Russ. J. Genet.20205691139115010.1134/S1022795420090100
    [Google Scholar]
  54. RajuK. KaruppiahB. ChinniahR. The HLA profile and genetic affinities of three primitive Tamil-speaking endogamous groups: Kallars of Thanjavur, Piramalai Kallar and Vanniyar.Egypt. J. Med. Hum. Genet.202223116210.1186/s43042‑022‑00378‑7
    [Google Scholar]
  55. DiPiazzaA.T. GrahamB.S. RuckwardtT.J. T cell immunity to SARS-CoV-2 following natural infection and vaccination.Biochem. Biophys. Res. Commun.202153853821121710.1016/j.bbrc.2020.10.060 33190827
    [Google Scholar]
  56. Gonzalez-GalarzaF.F. McCabeA. SantosE.J.M. Allele frequency net database (AFND) 2020 update: Gold-standard data classification, open access genotype data and new query tools.Nucleic Acids Res.201948D1gkz102910.1093/nar/gkz1029 31722398
    [Google Scholar]
  57. SawikB. PłonkaJ. Project and Prototype of Mobile Application for Monitoring the Global COVID-19 Epidemiological Situation.Int. J. Environ. Res. Public Health2022193141610.3390/ijerph19031416 35162439
    [Google Scholar]
  58. RoszakM. SawikB. StańdoJ. BaumE. E-learning as a factor optimizing the amount of work time devoted to preparing an exam for medical program students during the COVID-19 epidemic situation.Healthcare (Basel)202199114710.3390/healthcare9091147 34574923
    [Google Scholar]
  59. AsraniP. EapenM.S. ChiaC. Diagnostic approaches in COVID-19: Clinical updates.Expert Rev. Respir. Med.202115219721210.1080/17476348.2021.1823833 32924671
    [Google Scholar]
/content/journals/covid/10.2174/0126667975332701240920074118
Loading
/content/journals/covid/10.2174/0126667975332701240920074118
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test