Evidence map›Paper›PMID 39741349›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Genomic Patterns are Associated with Different Sequelae of Patients with Long-Term COVID-19.

Nan Zhang, Xizi Luo, Xiangwen Ji, Tian Tian, Runze Wu, Shishun Zhao, Guoqing Wang

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Genomic Patterns are Associated with Different Sequelae of Patients with Long-Term COVID-19.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    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

7 authors.

Nan ZhangState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory of Pathobiology Ministry of Education, China-Japan Union Hospital of Jilin University, Changchun, 130033, China.
Xizi LuoState Key Laboratory for Zoonotic Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, College of Veterinary Medicine, Jilin University, Changchun, 130062, China.
Xiangwen JiDepartment of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, 49 Huayuanbei Road, Beijing, 100191, China.
Tian TianCollege of Basic Medical Sciences, Jilin University, Changchun, 130021, China.
Runze WuCollege of Mathematics, Jilin University, Changchun, 130012, China.
Shishun ZhaoCollege of Mathematics, Jilin University, Changchun, 130012, China.
Guoqing WangState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory of Pathobiology Ministry of Education, China-Japan Union Hospital of Jilin University, Changchun, 130033, China.ORCID https://orcid.org/0000-0001-9326-3755

Funding

Graduate Innovation Fund of Jilin University 2024CX043National Key R&D Program of China 2022YFF1203204Natural Science Foundation of China 82072330Natural Science Foundation of China U23A20269
6 · The paper itself

Abstract

In the post-large era, various COVID-19 sequelae are getting more and more attention to health problems. Although the mortality rate of the COVID-19 infection is now declining, it is often accompanied by new clinical sequelae with different symptoms such as fatigue after infection, loss of smell. The degree of age, gender, virus infection seems to be weakly correlated with clinical symptoms. Human genetic variation plays a significant role in the sequelae of the COVID-19 infection. This study aims to analyze the genomic differences between individuals with different COVID-19 sequelae. In this study, the exomes of 97 patients with Omicron with 8 unique clinical manifestations are sequenced, and conducted a systematic analysis. Based on non-negative matrix factorization algorithms, the trinucleotide mutation spectrum of four long-term COVID-19 genomes is summarized and found that individuals with different clinical symptoms have unique DNA mutation patterns and indel patterns. By constructing a Genomic Fingerprinting Framework, the driver genes of variation in each symptomatic population are deciphered and analyzed. This study showed that population-specific mutational fingerprint differences are the main cause of heterogeneity in long-term COVID-19 sequelae. This study provides new ideas and insights into the causes of the long-term COVID-19 sequelae.

Indexed as

COVID-19SARS-CoV-2AdultAgedFemaleGenome, ViralGenomicsHumansMaleMiddle AgedMutationexon sequencinggenome mutation patterngenomic fingerprinting frameworklong‐term COVID‐19non‐negative matrix factorization

Identifiers

PMID39741349
PMCPMC11848565

What OpenQuestion holds

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Registered trials

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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.