Evidence map›Paper›PMID 36002455›Full record

ArticleNature communications2022

Splicing QTL analysis focusing on coding sequences reveals mechanisms for disease susceptibility loci.

Kensuke Yamaguchi, Kazuyoshi Ishigaki, Akari Suzuki, Yumi Tsuchida, Haruka Tsuchiya, Shuji Sumitomo, Yasuo Nagafuchi, Fuyuki Miya, Tatsuhiko Tsunoda, Hirofumi Shoda and 3 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
4.6field-weighted citation impact, top 4% 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

37 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 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

13 authors at 4 institutions in 1 country.

Kensuke YamaguchiBiomedical Engineering Research Innovation Center, Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University, Tokyo, Japan.ORCID 0000-0001-8288-1240
Kazuyoshi IshigakiLaboratory for Human Immunogenetics, RIKEN Center for Integrative Medical Sciences, Okohama City, Kanagawa, 230-0045, Japan.ORCID 0000-0003-2881-0657
Akari SuzukiLaboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Okohama City, Kanagawa, 230-0045, Japan.
Yumi TsuchidaDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.ORCID 0000-0003-3236-6157
Haruka TsuchiyaDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Shuji SumitomoDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Yasuo NagafuchiDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.ORCID 0000-0002-1316-8035
Fuyuki MiyaCenter for Medical Genetics, Keio University School of Medicine, Tokyo, Japan.
Tatsuhiko TsunodaLaboratory for Medical Science Mathematics, Department of Biological Sciences, School of Science, The University of Tokyo, Tokyo, Japan.ORCID 0000-0002-5439-7918
Hirofumi ShodaDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Keishi FujioDepartment of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Kazuhiko YamamotoLaboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Okohama City, Kanagawa, 230-0045, Japan.
Yuta KochiGenomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan. y-kochi.gfd@mri.tmd.ac.jp.ORCID 0000-0002-8012-5078
The University of Tokyo · JPRIKEN Center for Integrative Medical Sciences · JPTokyo Medical and Dental University · JPKeio University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Splicing quantitative trait loci (sQTLs) are one of the major causal mechanisms in genome-wide association study (GWAS) loci, but their role in disease pathogenesis is poorly understood. One reason is the complexity of alternative splicing events producing many unknown isoforms. Here, we propose two approaches, namely integration and selection, for this complexity by focusing on protein-structure of isoforms. First, we integrate isoforms with the same coding sequence (CDS) and identify 369-601 integrated-isoform ratio QTLs (i

Indexed as

Genome-Wide Association StudyQuantitative Trait LociAlternative SplicingDisease SusceptibilityHumansPolymorphism, Single NucleotideProtein IsoformsProtein Isoforms

Identifiers

PMID36002455
PMCPMC9402578
OpenAlexW4292883548

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.