Evidence map›Paper›PMID 38403000›Full record

ArticleVirus research2024

Exploring COVID-19 causal genes through disease-specific Cis-eQTLs.

Sainan Zhang, Ping Wang, Lei Shi, Chao Wang, Zijun Zhu, Changlu Qi, Yubin Xie, Shuofeng Yuan, Liang Cheng, Xin Yin and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Virus research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

11 authors at 3 institutions in 2 countries.

Sainan ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Ping WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Lei ShiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Chao WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Zijun ZhuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Changlu QiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Yubin XieDepartment of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam 999077, Hong Kong Special Administrative Region of China; State Key Laboratory of Emerging Infectious Diseases, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Pokfulam 999077, Hong Kong Special Administrative Region of China.
Shuofeng YuanDepartment of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam 999077, Hong Kong Special Administrative Region of China; State Key Laboratory of Emerging Infectious Diseases, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Pokfulam 999077, Hong Kong Special Administrative Region of China.
Liang ChengCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China; NHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, Heilongjiang 150028, China. Electronic address: liangcheng@hrbmu.edu.cn.
Xin YinState Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150040, China.
Xue ZhangNHC Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, Heilongjiang 150028, China; McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China.
Harbin Medical University · CNUniversity of Hong Kong · HKChinese Academy of Agricultural Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association study (GWAS) analysis has exposed that genetic factors play important roles in COVID-19. Whereas a deeper understanding of the underlying mechanism of COVID-19 was hindered by the lack of expression of quantitative trait loci (eQTL) data specific for disease. To this end, we identified COVID-19-specific cis-eQTLs by integrating nucleotide sequence variations and RNA-Seq data from COVID-19 samples. These identified eQTLs have different regulatory effect on genes between patients and controls, indicating that SARS-CoV-2 infection may cause alterations in the human body's internal environment. Individuals with the TT genotype in the rs1128320 region seemed more susceptible to SARS-CoV-2 infection and developed into severe COVID-19 due to the abnormal expression of IFITM1. We subsequently discovered potential causal genes, of the result, a total of 48 genes from six tissues were identified. siRNA-mediated depletion assays in SARS-CoV-2 infection proved that 14 causal genes were directly associated with SARS-CoV-2 infection. These results enriched existing research on COVID-19 causal genes and provided a new sight in the mechanism exploration for COVID-19.

Indexed as

COVID-19Genome-Wide Association StudyHumansRNA-SeqRNA, Small InterferingSARS-CoV-2RNA, Small InterferingCOVID-19Expression quantitative trait locisiRNA transfectionSummary data-based mendelian randomization

Identifiers

PMID38403000
PMCPMC10904281
OpenAlexW4392136679

What Socratic 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 Socratic graph.