Evidence map›Paper›PMID 34076249›Full record

ArticleBriefings in bioinformatics2021

Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions.

Zulkar Nain, Shital K Barman, Md Moinuddin Sheam, Shifath Bin Syed, Abdus Samad, Julian M W Quinn, Mohammad Minnatul Karim, Mahbubul Kabir Himel, Rajib Kanti Roy, Mohammad Ali Moni and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.5field-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

11 citing papers in PubMed, 24 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

11 authors at 4 institutions in 2 countries.

Zulkar NainDepartment of Biotechnology and Genetic Engineering, Islamic University, Bangladesh.ORCID 0000-0003-0819-3137
Shital K BarmanIslamic University, Bangladesh.
Md Moinuddin SheamDepartment of Biotechnology and Genetic Engineering, Islamic University, Bangladesh.ORCID 0000-0003-1769-4806
Shifath Bin SyedDepartment of Biotechnology and Genetic Engineering, Islamic University, Bangladesh.ORCID 0000-0002-4786-0337
Abdus SamadDepartment of Genetic Engineering and Biotechnology at the Jashore University of Science and Technology, Bangladesh.ORCID 0000-0003-4336-5600
Julian M W QuinnGarvan Institute of Medical Research, Australia.
Mohammad Minnatul KarimIslamic University, Bangladesh.ORCID 0000-0002-5383-6288
Mahbubul Kabir HimelJahangirnagar University, Bangladesh.
Rajib Kanti RoyJashore University of Science and Technology, Bangladesh.
Mohammad Ali MoniUniversity of New South Wales, Australia.ORCID 0000-0003-0756-1006
Sudhangshu Kumar BiswasIslamic University, Bangladesh.ORCID 0000-0002-3590-0960
Islamic University · BDGarvan Institute of Medical Research · AUJahangirnagar University · BDUNSW Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the association of prevalent health conditions with coronavirus disease 2019 (COVID-19) severity, the disease-modifying biomolecules and their pathogenetic mechanisms remain unclear. This study aimed to understand the influences of COVID-19 on different comorbidities and vice versa through network-based gene expression analyses. Using the shared dysregulated genes, we identified key genetic determinants and signaling pathways that may involve in their shared pathogenesis. The COVID-19 showed significant upregulation of 93 genes and downregulation of 15 genes. Interestingly, it shares 28, 17, 6 and 7 genes with diabetes mellitus (DM), lung cancer (LC), myocardial infarction and hypertension, respectively. Importantly, COVID-19 shared three upregulated genes (i.e. MX2, IRF7 and ADAM8) with DM and LC. Conversely, downregulation of two genes (i.e. PPARGC1A and METTL7A) was found in COVID-19 and LC. Besides, most of the shared pathways were related to inflammatory responses. Furthermore, we identified six potential biomarkers and several important regulatory factors, e.g. transcription factors and microRNAs, while notable drug candidates included captopril, rilonacept and canakinumab. Moreover, prognostic analysis suggests concomitant COVID-19 may result in poor outcome of LC patients. This study provides the molecular basis and routes of the COVID-19 progression due to comorbidities. We believe these findings might be useful to further understand the intricate association of these diseases as well as for the therapeutic development.

Indexed as

ADAM ProteinsComputational BiologyCOVID-19Diabetes MellitusHumansHypertensionInterferon Regulatory Factor-7Lung NeoplasmsMembrane ProteinsMyocardial InfarctionMyxovirus Resistance ProteinsPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaSARS-CoV-2Transcription FactorsTranscriptomeADAM8 protein, humanADAM ProteinsInterferon Regulatory Factor-7IRF7 protein, humanMembrane ProteinsMX2 protein, humanMyxovirus Resistance ProteinsPeroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alphaPPARGC1A protein, humanTranscription FactorscomorbiditiesCOVID-19 pandemichypertensionmicroarrayRNA-SeqSARS-CoV-2

Identifiers

PMID34076249
PMCPMC8194991
OpenAlexW3164956781

What OpenQuestion holds

Textmetadata
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.