Evidence map›Paper›PMID 30530896›Full record

ArticleJournal of integrative bioinformatics2018

Molecular Relationships between Bronchial Asthma and Hypertension as Comorbid Diseases.

Elena Yu Bragina, Irina A Goncharova, Anna F Garaeva, Evgeniy V Nemerov, Anastasija A Babovskaya, Andrey B Karpov, Yulia V Semenova, Irina Z Zhalsanova, Densema E Gomboeva, Olga V Saik and 5 more

Open access · diamondAbstract read
In one paragraph

Article in Journal of integrative bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Observational
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. The association of asthma and its subgroups with osteoporosis: a cross-sectional study using KoGES HEXA data.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2020
    Article
  10. 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

15 authors at 6 institutions in 3 countries.

Elena Yu BraginaResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.ORCID https://orcid.org/0000-0002-1103-3073
Irina A GoncharovaResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.ORCID https://orcid.org/0000-0002-9527-7015
Anna F GaraevaResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.
Evgeniy V NemerovSiberian State Medical University, Tomsk, Russia.
Anastasija A BabovskayaSiberian State Medical University, Tomsk, Russia.
Andrey B KarpovSeversk Biophysical Research Centre of the Federal Medico-Biological Agency, Seversk, Russia.
Yulia V SemenovaSeversk Clinical Hospital, Siberian Federal Research and Clinical Centre of the Federal Medico-Biological Agency, Seversk, Russia.
Irina Z ZhalsanovaResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.
Densema E GomboevaResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.
Olga V SaikThe Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.
Olga I ZolotarevaBielefeld University, Bioinformatics/Medical Informatics Department, Bielefeld, Germany.ORCID https://orcid.org/0000-0002-9424-8052
Vladimir A IvanisenkoThe Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.
Victor E DosenkoBogomoletz Institute of Physiology, National Academy of Science, Kiev, Ukraine.
Ralf HofestaedtBielefeld University, Bioinformatics/Medical Informatics Department, Bielefeld, Germany.
Maxim B FreidinResearch Institute of Medical Genetics, Tomsk NRMC, Tomsk, Russia.ORCID https://orcid.org/0000-0002-1439-6259
Research Institute of Medical Genetics of Russian Academy of Medical Sciences · RUSiberian State Medical University · RUBielefeld University · DEFederal Medical-Biological Agency · RUInstitute of Cytology and Genetics · RUBogomoletz Institute of Physiology · UA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Comorbidity, a co-incidence of several disorders in an individual, is a common phenomenon. Their development is governed by multiple factors, including genetic variation. The current study was set up to look at associations between isolated and comorbid diseases of bronchial asthma and hypertension, on one hand, and single nucleotide polymorphisms associated with regulation of gene expression (eQTL), on the other hand. A total of 96 eQTL SNPs were genotyped in 587 Russian individuals. Bronchial asthma alone was found to be associated with rs1927914 (TLR4), rs1928298 (intergenic variant), and rs1980616 (SERPINA1); hypertension alone was found to be associated with rs11065987 (intergenic variant); rs2284033 (IL2RB), rs11191582 (NT5C2), and rs11669386 (CARD8); comorbidity between asthma and hypertension was found to be associated with rs1010461 (ANG/RNASE4), rs7038716, rs7026297 (LOC105376244), rs7025144 (intergenic variant), and rs2022318 (intergenic variant). The results suggest that genetic background of comorbidity of asthma and hypertension is different from genetic backgrounds of both diseases manifesting isolated.

Indexed as

Gene Regulatory NetworksPolymorphism, Single NucleotideQuantitative Trait LociAdultAgedAsthmaComorbidityComputational BiologyEssential HypertensionFemaleGenome-Wide Association StudyHumansMaleMiddle AgedRussiaBronchial AsthmaComorbidityeQTLHypertensionSNP

Identifiers

PMID30530896
PMCPMC6348747
OpenAlexW2905035078

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.