Genetic variants are identified to increase risk of COVID-19 related mortality from UK Biobank data

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Abstract

Background

The severity of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly heterogeneous. Studies have reported that males and some ethnic groups are at increased risk of death from COVID-19, which implies that individual risk of death might be influenced by host genetic factors.

Methods

In this project, we consider the mortality as the trait of interest and perform a genome-wide association study (GWAS) of data for 1778 infected cases (445 deaths, 25.03%) distributed by the UK Biobank. Traditional GWAS fails to identify any genome-wide significant genetic variants from this dataset. To enhance the power of GWAS and account for possible multi-loci interactions, we adopt the concept of super variant for the detection of genetic factors. A discovery-validation procedure is used for verifying the potential associations.

Results

We find 8 super variants that are consistently identified across multiple replications as susceptibility loci for COVID-19 mortality. The identified risk factors on chromosomes 2, 6, 7, 8, 10, 16, and 17 contain genetic variants and genes related to cilia dysfunctions ( DNAH7 and CLUAP1), cardiovascular diseases ( DES and SPEG), thromboembolic disease ( STXBP5), mitochondrial dysfunctions ( TOMM7), and innate immune system ( WSB1). It is noteworthy that DNAH7 has been reported recently as the most downregulated gene after infecting human bronchial epithelial cells with SARS-CoV-2.

Conclusions

Eight genetic variants are identified to significantly increase the risk of COVID-19 mortality among the patients with white British ancestry. These findings may provide timely clues and potential directions for better understanding the molecular pathogenesis of COVID-19 and the genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00306-7.

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Most cited references 55

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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Chaolin Huang, Yeming Wang, Xingwang Li … (2020)

Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.

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Clinical Characteristics of Coronavirus Disease 2019 in China

Wei-jie Guan, Zheng-yi Ni, Yu Hu … (2020)

Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)

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A Novel Coronavirus from Patients with Pneumonia in China, 2019

Na Zhu, Dingyu Zhang, Wenling Wang … (2020)

Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)

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Author and article information

Contributors

Heping Zhang:

ORCID: http://orcid.org/0000-0002-0688-4076

heping.zhang@yale.edu

Journal

Journal ID (nlm-ta): Hum Genomics

Journal ID (iso-abbrev): Hum Genomics

Title: Human Genomics

Publisher: BioMed Central (London )

ISSN (Print): 1473-9542

ISSN (Electronic): 1479-7364

Publication date (Electronic): 3 February 2021

Publication date PMC-release: 3 February 2021

Publication date Collection: 2021

Volume: 15

Electronic Location Identifier: 10

Affiliations

GRID grid.47100.32, ISNI 0000000419368710, Department of Biostatistics, , Yale University, ; 300 George Street, Ste 523, New Haven, CT 06511 USA

Author information

Heping Zhang http://orcid.org/0000-0002-0688-4076

Article

Publisher ID: 306

DOI: 10.1186/s40246-021-00306-7

PMC ID: 7856608

PubMed ID: 33536081

SO-VID: 70426d43-9704-4532-ac80-344eadb2e592

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 22 October 2020

Date accepted : 15 January 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000051, National Human Genome Research Institute;

Award ID: R01HG010171

Award Recipient : Heping Zhang

Funded by: FundRef http://dx.doi.org/10.13039/100000025, National Institute of Mental Health;

Award ID: R01MH116527

Award Recipient : Heping Zhang

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: covid-19,gwas,host genetic factors,mortality,sars-cov-2,uk biobank

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ScienceOpen disciplines: Genetics

Keywords: covid-19, gwas, host genetic factors, mortality, sars-cov-2, uk biobank

Genetic variants are identified to increase risk of COVID-19 related mortality from UK Biobank data

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Abstract

Background

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Supplementary Information

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Novel Coronavirus Disease COVID-19

Most cited references 55

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

Clinical Characteristics of Coronavirus Disease 2019 in China

A Novel Coronavirus from Patients with Pneumonia in China, 2019

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