Does human leukocyte antigen gene polymorphism affect management of COVID-19 Patients? A review article

Raslan, Mohamed; Alshahawey, Mona; Shehata, Eslam Mansour; Sabri, Nagwa A.

doi:10.17352/sjggt.000018

Cited by 4 publications

(5 citation statements)

References 14 publications

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“…HLA‐DQA1 may induce the production of anti‐drug antibodies against anti‐TNF drugs like infliximab, and adalimumab; which are used as options in the management of COVID‐19, and therefore might result in management failure. Also, HLA‐B*46:01 carrier individuals are more vulnerable to COVID‐19 14 …”

Section: Introductionmentioning

confidence: 99%

“…Also, HLA-B*46:01 carrier individuals are more vulnerable to COVID-19. 14 Several genetic mutations were discovered in several gene locations; c.222G>C (p.Leu74Leu) in the E structural protein and c.213C>T(p.Tyr71Tyr) in the M structural protein, D614 G, and other additional variants have been found which might decrease the main host antibody response. The probability of fast generation of treatment-resistant strains, including antiviral resistance, is highly possible and consequently is an important raised issue concerning vaccine effectiveness and its benefits in immunization against SARS-COV-2.…”

Section: Introductionmentioning

confidence: 99%

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Molecular evolution of SARS‐CoV‐2 from December 2019 to August 2022

Wolf

Bello³

et al. 2022

Journal of Medical Virology

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Severe acute respiratorysyndrome coronavirus‐2 (SARS‐CoV‐2) pandemic spread rapidly and this scenario is concerning worldwide, presenting more than 590 million coronavirus disease 2019 cases and 6.4 million deaths. The emergence of novel lineages carrying several mutations in the spike protein has raised additional public health concerns worldwide during the pandemic. The present study review and summarizes the temporal spreading and molecular evolution of SARS‐CoV‐2 clades and variants worldwide. The evaluation of these data is important for understanding the evolutionary histories of SARSCoV‐2 lineages, allowing us to identify the origins of each lineage of this virus responsible for one of the biggest pandemics in history. A total of 2897 SARS‐CoV‐2 whole‐genome sequences with available information from the country and sampling date (December 2019 to August 2022), were obtained and were evaluated by Bayesian approach. The results demonstrated that the SARS‐CoV‐2 the time to the most recent common ancestor (tMRCA) in Asia was 2019‐12‐26 (highest posterior density 95% [HPD95%]: 2019‐12‐18; 2019‐12‐29), in Oceania 2020‐01‐24 (HPD95%: 2020‐01‐15; 2020‐01‐30), in Africa 2020‐02‐27 (HPD95%: 2020‐02‐21; 2020‐03‐04), in Europe 2020‐02‐27 (HPD95%: 2020‐02‐20; 2020‐03‐06), in North America 2020‐03‐12 (HPD95%: 2020‐03‐05; 2020‐03‐18), and in South America 2020‐03‐15 (HPD95%: 2020‐03‐09; 2020‐03‐28). Between December 2019 and June 2020, 11 clades were detected (20I [Alpha] and 19A, 19B, 20B, 20C, 20A, 20D, 20E [EU1], 20F, 20H [Beta]). From July to December 2020, 4 clades were identified (20J [Gamma, V3], 21 C [Epsilon], 21D [Eta], and 21G [Lambda]). Between January and June 2021, 3 clades of the Delta variant were detected (21A, 21I, and 21J). Between July and December 2021, two variants were detected, Delta (21A, 21I, and 21J) and Omicron (21K, 21L, 22B, and 22C). Between January and June 2022, the Delta (21I and 21J) and Omicron (21K, 21L, and 22A) variants were detected. Finally, between July and August 2022, 3 clades of Omicron were detected (22B, 22C, and 22D). Clade 19A was first detected in the SARS‐CoV‐2 pandemic (Wuhan strain) with origin in 2019‐12‐16 (HPD95%: 2019‐12‐15; 2019‐12‐25); 20I (Alpha) in 2020‐11‐24 (HPD95%: 2020‐11‐15; 2021‐12‐02); 20H (Beta) in 2020‐11‐25 (HPD95%: 2020‐11‐13; 2020‐11‐29); 20J (Gamma) was 2020‐12‐21 (HPD95%: 2020‐11‐05; 2021‐01‐15); 21A (Delta) in 2020‐09‐20 (HPD95%: 2020‐05‐17; 2021‐02‐03); 21J (Delta) in 2021‐02‐26 (2020‐11‐02; 2021‐04‐24); 21M (Omicron) in 2021‐01‐25 (HPD95%: 2020‐09‐16; 2021‐08‐08); 21K (Omicron) in 2021‐07‐30 (HPD95%: 2021‐05‐30; 2021‐10‐19); 21L (Omicron) in 2021‐10‐03 (HPD95%: 2021‐04‐16; 2021‐12‐23); 22B (Omicron) in 2022‐01‐25 (HPD95%: 2022‐01‐10; 2022‐02‐05); 21L in 2021‐12‐20 (HPD95%: 2021‐05‐16; 2021‐12‐31). Currently, the Omicron variant predominates worldwide, with the 21L clade branching into 3 (22A, 22B, and 22C). Phylogeographic data showed that Alpha variant originated in the United Kingdom, Beta in South Africa, Gamma in Brazil, Delta in I...

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Molecular evolution of SARS‐CoV‐2 from December 2019 to August 2022

Wolf

Bello³

et al. 2022

Journal of Medical Virology

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“…In the case of HLA-DQ, data regarding the incidence are available, but not regarding the development of the disease. Some data indicate that HLA-DQ1 can be associated with a higher incidence of COVID-19 ( 41 ). It is also important to note that, in a group of almost 2,000 patients from Italy and Spain, the correlation of HLA alleles with the incidence of COVID-19 was not proven ( 42 ).…”

Section: Discussionmentioning

confidence: 99%

The Role of HLA Antigens and Steroid Dose on the Course of COVID-19 of Patients After Kidney Transplantation

et al. 2021

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Background: Kidney transplant recipients appear to be at higher risk for critical COVID-19. Our analysis aimed to identify the possible risk factors for a severe course of the COVID-19 disease and to determine the influence of selected human leukocyte antigens (HLAs) on the course of the disease.Methods: This is a retrospective, multicenter analysis that included patients that were confirmed to be severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) positive after kidney transplantation (KT). The group of patients was divided into two subgroups according to the course of the infection, as follows: non-hospitalized and hospitalized.Results: A total of 186 patients (men, 69.4%) with confirmed SARS-CoV-2 positivity were included in the group. The following independent risk factors for the outcome of hospitalization were identified: the age at the time of infection [odds ratio (OR) = 1.19, P < 0.0001], a body mass index (BMI) >29.9 kg/m2 (OR = 7.21, P < 0.0001), <7.5-mg prednisone dose/day (OR = 2.29, P = 0.0008), and HLA-DQ2 with a protective nature (OR = 0.05, P = 0.0034).Conclusions: Higher doses of corticosteroids (>7.5 mg/kg) in standard immunosuppressive regimes and HLA-DQ2 appear to be protective factors in our analysis.

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“…Also, HLA-B*46:01 carrier individuals were found to be more vulnerable to COVID-19. 20 Understanding viral entrance processes, host-virus interactions at the molecular level, and the viral-specific host components Additionally, PHG was able to give insight into the variations in immune responses between individuals with severe disease and those with mild disease, and the disease's natural history. Being able to define more precisely which populations were most at risk of infection through genomic risk prediction allowed preventative measures to be targeted to the most at-risk subgroups, thereby significantly impacting population health.…”

Section: Uses Of Phg During the Covid-19 Pandemicmentioning

confidence: 99%

“…HLA‐DQA1 may induce the production of anti‐drug antibodies against anti‐TNF drugs like infliximab and adalimumab, which are used as options in the management of COVID‐19, and therefore might result in management failure. Also, HLA‐B*46:01 carrier individuals were found to be more vulnerable to COVID‐19 20 …”

Section: Uses Of Phg During the Covid‐19 Pandemicmentioning

confidence: 99%

Implementation of Public Health Genomics in Africa: Lessons from the COVID‐19 pandemic, challenges, and recommendations

Moyo

Mashe

et al. 2022

Journal of Medical Virology

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Public Health Genomics (PHG) is a relatively new field. The wide application of genomic technologies played a pivotal role in elucidating the full genomic sequence of the SARS‐CoV‐2 virus. This breakthrough proved to be the starting point in the manufacture of diagnostic kits and the subsequent making of vaccines. Beyond the COVID‐19 pandemic, many African countries can take advantage of the various investments in genomic technologies to introduce and intensify the use of genomics for public health gain. Public Health Genomics effectively monitors, prevents, and manages non‐communicable and infectious diseases. However, there are several challenges to implementing PHG in Africa. In this perspective article, we discuss the utilization of PHG during the COVID‐19 pandemic, the lessons learned from using PHG to manage and contain the COVID‐19 pandemic, as well as potential challenges Africa may face when putting PHG into practice compared to challenges of other regions. We also discuss our recommendations for overcoming these challenges.

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Does human leukocyte antigen gene polymorphism affect management of COVID-19 Patients? A review article

Cited by 4 publications

References 14 publications

Molecular evolution of SARS‐CoV‐2 from December 2019 to August 2022

Molecular evolution of SARS‐CoV‐2 from December 2019 to August 2022

The Role of HLA Antigens and Steroid Dose on the Course of COVID-19 of Patients After Kidney Transplantation

Implementation of Public Health Genomics in Africa: Lessons from the COVID‐19 pandemic, challenges, and recommendations

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