Evidence map›Paper›PMID 38752789›Full record

ArticlemSystems2024

Comparative analysis of dynamic transcriptomes reveals specific COVID-19 features and pathogenesis of immunocompromised populations.

Xiaodi Yang, Jialin Zhu, Qingyun Wang, Bo Tang, Ye Shen, Bingjie Wang, Li Ji, Huihui Liu, Stefan Wuchty, Ziding Zhang and 2 more

Abstract readComparative Study
In one paragraph

Article in mSystems, 2024. 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. 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

12 authors.

Xiaodi Yang *Department of Hematology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-3229-5865
Jialin Zhu *Department of Hematology, Peking University First Hospital, Beijing, China.
Qingyun Wang *Department of Hematology, Peking University First Hospital, Beijing, China.
Bo TangDepartment of Hematology, Peking University First Hospital, Beijing, China.
Ye ShenDepartment of Hematology, Peking University First Hospital, Beijing, China.
Bingjie WangDepartment of Hematology, Peking University First Hospital, Beijing, China.
Li JiDepartment of Hematology, Peking University First Hospital, Beijing, China.
Huihui LiuDepartment of Hematology, Peking University First Hospital, Beijing, China.
Stefan WuchtyDepartment of Computer Science, University of Miami, Miami, Florida, USA.ORCID 0000-0001-8916-6522
Ziding ZhangCollege of Biological Sciences, China Agricultural University, Beijing, China.ORCID 0000-0002-9296-571X
Yujun DongDepartment of Hematology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-7935-6194
Zeyin LiangDepartment of Hematology, Peking University First Hospital, Beijing, China.ORCID 0009-0006-9884-5846

Funding

the National High Level Hospital Clinical Research Funding (Interdisciplinary Clinical Research Project of Peking University First Hospital) 2022CR38the National High Level Hospital Clinical Research Funding (Scientific Research Seed Fund of Peking University First Hospital) 2023SF50
6 · The paper itself

Abstract

A dysfunction of human host genes and proteins in coronavirus infectious disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a key factor impacting clinical symptoms and outcomes. Yet, a detailed understanding of human host immune responses is still incomplete. Here, we applied RNA sequencing to 94 samples of COVID-19 patients with and without hematological tumors as well as COVID-19 uninfected non-tumor individuals to obtain a comprehensive transcriptome landscape of both hematological tumor patients and non-tumor individuals. In our analysis, we further accounted for the human-SARS-CoV-2 protein interactome, human protein interactome, and human protein complex subnetworks to understand the mechanisms of SARS-CoV-2 infection and host immune responses. Our data sets enabled us to identify important SARS-CoV-2 (non-)targeted differentially expressed genes and complexes post-SARS-CoV-2 infection in both hematological tumor and non-tumor individuals. We found several unique differentially expressed genes, complexes, and functions/pathways such as blood coagulation (APOE, SERPINE1, SERPINE2, and TFPI), lipoprotein particle remodeling (APOC2, APOE, and CETP), and pro-B cell differentiation (IGHM, VPREB1, and IGLL1) during COVID-19 infection in patients with hematological tumors. In particular, APOE, a gene that is associated with both blood coagulation and lipoprotein particle remodeling, is not only upregulated in hematological tumor patients post-SARS-CoV-2 infection but also significantly expressed in acute dead patients with hematological tumors, providing clues for the design of future therapeutic strategies specifically targeting COVID-19 in patients with hematological tumors. Our data provide a rich resource for understanding the specific pathogenesis of COVID-19 in immunocompromised patients, such as those with hematological malignancies, and developing effective therapeutics for COVID-19. IMPORTANCE: A majority of previous studies focused on the characterization of coronavirus infectious disease 2019 (COVID-19) disease severity in people with normal immunity, while the characterization of COVID-19 in immunocompromised populations is still limited. Our study profiles changes in the transcriptome landscape post-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in hematological tumor patients and non-tumor individuals. Furthermore, our integrative and comparative systems biology analysis of the interactome, complexome, and transcriptome provides new insights into the tumor-specific pathogenesis of COVID-19. Our findings confirm that SARS-CoV-2 potentially tends to target more non-functional host proteins to indirectly affect host immune responses in hematological tumor patients. The identified unique genes, complexes, functions/pathways, and expression patterns post-SARS-CoV-2 infection in patients with hematological tumors increase our understanding of how SARS-CoV-2 manipulates the host molecular mechanism. Our observed differential genes/complexes and clinical indicators of normal/long infection and deceased COVID-19 patients provide clues for understanding the mechanism of COVID-19 progression in hematological tumors. Finally, our study provides an important data resource that supports the increasing value of the application of publicly accessible data sets to public health.

Indexed as

COVID-19Immunocompromised HostSARS-CoV-2TranscriptomeFemaleGene Expression ProfilingHematologic NeoplasmsHumansMaleMiddle AgedProtein Interaction Mapshematological malignanciesinfectionprotein complexprotein-protein interactionSARS-CoV-2transcriptome

Identifiers

PMID38752789
PMCPMC11237560

What OpenQuestion holds

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LicenceCC BY
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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.