Evidence map›Paper›PMID 29504915›Full record

ArticleBMC medical genomics2018

Novel candidate genes important for asthma and hypertension comorbidity revealed from associative gene networks.

Olga V Saik, Pavel S Demenkov, Timofey V Ivanisenko, Elena Yu Bragina, Maxim B Freidin, Irina A Goncharova, Victor E Dosenko, Olga I Zolotareva, Ralf Hofestaedt, Inna N Lavrik and 2 more

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

25 citing papers in PubMed, 50 citations in OpenAlex.

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  5. Association of the Toll-like receptor 4 and NOX4 gene and protein levels in asthmatic patients with metabolic syndrome: A case-control study.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2023
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  20. Bioinformatics research at BGRS-2018.BMC bioinformatics · 2019
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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

12 authors at 5 institutions in 5 countries.

Olga V SaikInstitute of Cytology and Genetics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia. saik@bionet.nsc.ru.
Pavel S DemenkovInstitute of Cytology and Genetics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia.
Timofey V IvanisenkoInstitute of Cytology and Genetics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia.
Elena Yu BraginaResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.
Maxim B FreidinResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.
Irina A GoncharovaResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.
Victor E DosenkoBogomoletz Institute of Physiology, Kiev, Ukraine.
Olga I ZolotarevaBielefeld University, International Research Training Group "Computational Methods for the Analysis of the Diversity and Dynamics of Genomes", Bielefeld, Germany.
Ralf HofestaedtBielefeld University, Technical Faculty, AG Bioinformatics and Medical Informatics, Bielefeld, Germany.
Inna N LavrikDepartment of Translational Inflammation, Institute of Experimental Internal Medicine, Otto von Guericke University, Magdeburg, Germany.
Evgeny I RogaevInstitute of Cytology and Genetics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia.
Vladimir A IvanisenkoInstitute of Cytology and Genetics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia.
Institute of Cytology and Genetics · RUResearch Institute of Medical Genetics of Russian Academy of Medical Sciences · RUBielefeld University · DEBogomoletz Institute of Physiology · UAOtto-von-Guericke University Magdeburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypertension and bronchial asthma are a major issue for people's health. As of 2014, approximately one billion adults, or ~ 22% of the world population, have had hypertension. As of 2011, 235-330 million people globally have been affected by asthma and approximately 250,000-345,000 people have died each year from the disease. The development of the effective treatment therapies against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and their treatment. Hence, in this study the bioinformatical methodology for the analysis of the comorbidity of these two diseases have been developed. As such, the search for candidate genes related to the comorbid conditions of asthma and hypertension can help in elucidating the molecular mechanisms underlying the comorbid condition of these two diseases, and can also be useful for genotyping and identifying new drug targets.

resultsUsing ANDSystem, the reconstruction and analysis of gene networks associated with asthma and hypertension was carried out. The gene network of asthma included 755 genes/proteins and 62,603 interactions, while the gene network of hypertension - 713 genes/proteins and 45,479 interactions. Two hundred and five genes/proteins and 9638 interactions were shared between asthma and hypertension. An approach for ranking genes implicated in the comorbid condition of two diseases was proposed. The approach is based on nine criteria for ranking genes by their importance, including standard methods of gene prioritization (Endeavor, ToppGene) as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analysed genes. According to the proposed approach, the genes IL10, TLR4, and CAT had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the list of top genes is enriched with apoptotic genes and genes involved in biological processes related to the functioning of central nervous system.

conclusionsThe application of methods of reconstruction and analysis of gene networks is a productive tool for studying the molecular mechanisms of comorbid conditions. The method put forth to rank genes by their importance to the comorbid condition of asthma and hypertension was employed that resulted in prediction of 10 genes, playing the key role in the development of the comorbid condition. The results can be utilised to plan experiments for identification of novel candidate genes along with searching for novel pharmacological targets.

Indexed as

Gene Regulatory NetworksAsthmaBiomarkersCatalaseCentral Nervous System DiseasesComorbidityComputational BiologyData MiningGene Expression ProfilingHumansHypertensionInterleukin-10SoftwareToll-Like Receptor 4BiomarkersCatalaseCAT protein, humanIL10 protein, humanInterleukin-10TLR4 protein, humanToll-Like Receptor 4ANDSystemApoptosisAssociative gene networksAsthmaCentral nervous systemComorbidityGene prioritizationHypertension

Identifiers

PMID29504915
PMCPMC6389037
OpenAlexW2772032611

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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.