Evidence map›Paper›PMID 35996834›Full record

ArticleBMB reports2022

Establishment of the large-scale longitudinal multi-omics dataset in COVID-19 patients: data profile and biospecimen.

Hye-Yeong Jo, Sang Cheol Kim, Do-Hwan Ahn, Siyoung Lee, Se-Hyun Chang, So-Young Jung, Young-Jin Kim, Eugene Kim, Jung-Eun Kim, Yeon-Sook Kim and 5 more

Open access · goldAbstract readNews
In one paragraph

Article in BMB reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 5 institutions in 1 country.

Hye-Yeong JoDivision of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Sang Cheol KimDivision of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Do-Hwan AhnDivision of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Siyoung LeeGeninus Inc, Seoul 05836, Korea.
Se-Hyun ChangDivision of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
So-Young JungDivision of Biobank, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Young-Jin KimDivision of Genome Science, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Eugene KimDivision of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Jung-Eun KimDivision of Bio Bigdata, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Yeon-Sook KimDivision of Infectious Disease, Department of Internal Medicine, Chungnam National University School of Medicine, Daejeon 35015, Korea.
Woong-Yang ParkGeninus Inc, Seoul 05836; Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea.
Nam-Hyuk ChoDepartment of Microbiology and Immunology, College of Medicine, Seoul National University, Seoul 08826, Korea.
Donghyun ParkGeninus Inc, Seoul 05836, Korea.
Ju-Hee LeeDivision of Healthcare and Artificial Intelligence, Department of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Hyun-Young ParkDepartment of Precision Medicine, Korea National Institute of Health, Korea Disease Control and Prevention Agency, Cheongju 28159, Korea.
Korea National Institute of Health · KRKorea Disease Control and Prevention Agency · KRChungnam National University · KRSamsung Medical Center · KRSeoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of largescale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment. [BMB Reports 2022; 55(9): 465-471].

Indexed as

COVID-19CytokinesHumansPandemicsReceptors, Antigen, B-CellReceptors, Antigen, T-CellCytokinesReceptors, Antigen, B-CellReceptors, Antigen, T-Cell

Identifiers

PMID35996834
PMCPMC9537027
OpenAlexW4297459672

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.