Tracking the clonal dynamics of SARS-CoV-2-specific T cells in children and adults with mild/asymptomatic COVID-19

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Abstract

Children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop less severe coronavirus disease 2019 (COVID-19) than adults. The mechanisms for the age-specific differences and the implications for infection-induced immunity are beginning to be uncovered. We show by longitudinal multimodal analysis that SARS-CoV-2 leaves a small footprint in the circulating T cell compartment in children with mild/asymptomatic COVID-19 compared to adult household contacts with the same disease severity who had more evidence of systemic T cell interferon activation, cytotoxicity and exhaustion. Children harbored diverse polyclonal SARS-CoV-2-specific naïve T cells whereas adults harbored clonally expanded SARS-CoV-2-specific memory T cells. A novel population of naïve interferon-activated T cells is expanded in acute COVID-19 and is recruited into the memory compartment during convalescence in adults but not children. This was associated with the development of robust CD4 ⁺ memory T cell responses in adults but not children. These data suggest that rapid clearance of SARS-CoV-2 in children may compromise their cellular immunity and ability to resist reinfection.

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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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STAR: ultrafast universal RNA-seq aligner.

Alexander Dobin, Carrie A. Davis, Felix Schlesinger … (2013)

Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

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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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Author and article information

Journal

Journal ID (nlm-ta): Clin Immunol

Journal ID (iso-abbrev): Clin Immunol

Title: Clinical Immunology (Orlando, Fla.)

Publisher: The Author(s). Published by Elsevier Inc.

ISSN (Print): 1521-6616

ISSN (Electronic): 1521-7035

Publication date PMC-release: 17 December 2022

Publication date (Electronic): 17 December 2022

Electronic Location Identifier: 109209

Affiliations

[a ]Garvan Institute of Medical Research, Sydney, Australia

[b ]St Vincent's Clinical School, Faculty of Medicine, UNSW Sydney, Sydney, Australia

[c ]Kirby Institute, UNSW Sydney, Sydney, Australia

[d ]Centre for Applied Medical Research, St Vincent's Hospital, Sydney, Australia

[e ]Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Sydney, Australia

[f ]Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia

[g ]Brain Autoimmunity Group, Kids Neuroscience Centre, Kids Research at the Children's Hospital at Westmead, Sydney, Australia

[h ]Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia

[i ]Kids Research, The Children's Hospital at Westmead, Sydney, Australia

[j ]Discipline of Child and Adolescent Health, The University of Sydney, Sydney, Australia

[k ]Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia

[l ]Centre for Immunology and Allergy Research, The Westmead Institute for Medical Research, Sydney, Australia

[m ]Respiratory Tract Infection Research Node, Marie Bashir Institute for Infectious Diseases and Biosecurity, Sydney, Australia

[n ]Systems Biology and Data Science, Menzies Health Institute QLD, Griffith University, Parklands, Australia

[o ]Departments of Emergency Medicine and Children's Critical Care, Gold Coast University Hospital, Southport, QLD, Australia

[p ]School of Medicine and Menzies Health Institute Queensland, Griffith University, Southport, QLD, Australia

[q ]Department of Infectious Diseases and Immunology, Gold Coast University Hospital, Southport, QLD, Australia,

[r ]UNSW Cellular Genomics Futures Institute, UNSW Sydney, Sydney, Australia

[s ]Sydney Institute for Infectious Diseases, The University of Sydney, Sydney, Australia

[t ]Brain and Mind Centre, The University of Sydney, Sydney, Australia

[u ]Charles Perkins Centre Nepean, University of Sydney, Sydney, Australia

[v ]Faculty of Medicine, UNSW Sydney, Sydney, Australia

[w ]The Children's Hospital at Westmead, Sydney Children's Hospitals Network, Sydney, Australia

Author notes

[* ]Corresponding author at: Garvan Institute of Medical Research, 384 Victoria St., Darlinghurst, NSW 2010, Australia.

Article

Publisher Item ID: S1521-6616(22)00290-X Publisher ID: 109209

DOI: 10.1016/j.clim.2022.109209

PMC ID: 9758763

PubMed ID: 36539107

SO-VID: b005ed40-4b04-419e-9331-e80c6a584eda

License:

Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

History

Date received : 7 September 2022

Date revision received : 28 October 2022

Date accepted : 11 December 2022

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Tracking the clonal dynamics of SARS-CoV-2-specific T cells in children and adults with mild/asymptomatic COVID-19

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Abstract

Graphical abstract

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Novel Coronavirus Disease COVID-19

Most cited references 107

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

STAR: ultrafast universal RNA-seq aligner.

Clinical Characteristics of Coronavirus Disease 2019 in China

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