Evidence map›Paper›PMID 25646961›Full record

ArticlePloS one2015

Identification of an interaction between VWF rs7965413 and platelet count as a novel risk marker for metabolic syndrome: an extensive search of candidate polymorphisms in a case-control study.

Masahiro Nakatochi, Yasunori Ushida, Yoshinari Yasuda, Yasuko Yoshida, Shun Kawai, Ryuji Kato, Toru Nakashima, Masamitsu Iwata, Yachiyo Kuwatsuka, Masahiko Ando and 9 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 16% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Review
  5. Article
  6. 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

19 authors at 4 institutions in 1 country.

Masahiro NakatochiCenter for Advanced Medicine and Clinical Research, Nagoya University Hospital, Nagoya, Japan.
Yasunori UshidaDepartment of Biotechnology, Graduate School of Engineering, Nagoya University, Nagoya, Japan.
Yoshinari YasudaDepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya, Japan; Department of CKD Initiatives, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Yasuko YoshidaInnovative Research Center for Preventive Medical Engineering, Nagoya University, Nagoya, Japan.
Shun KawaiDepartment of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, Japan.
Ryuji KatoDepartment of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, Japan.
Toru NakashimaSafety & Health Promotion Division, Toyota Motor Corporation, Toyota, Japan.
Masamitsu IwataSafety & Health Promotion Division, Toyota Motor Corporation, Toyota, Japan.
Yachiyo KuwatsukaCenter for Advanced Medicine and Clinical Research, Nagoya University Hospital, Nagoya, Japan.
Masahiko AndoCenter for Advanced Medicine and Clinical Research, Nagoya University Hospital, Nagoya, Japan.
Nobuyuki HamajimaDepartment of Healthcare Administration, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Takaaki KondoProgram in Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Hiroaki OdaDepartment of Applied Molecular Biosciences, Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan.
Mutsuharu HayashiDepartment of Cardiology, Fujita Health University Second Hospital, Nagoya, Japan.
Sawako KatoDepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Makoto YamaguchiDepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Shoichi MaruyamaDepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Seiichi MatsuoDepartment of Nephrology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Hiroyuki HondaDepartment of Biotechnology, Graduate School of Engineering, Nagoya University, Nagoya, Japan; Innovative Research Center for Preventive Medical Engineering, Nagoya University, Nagoya, Japan.
Nagoya University · JPNagoya University Hospital · JPToyota Motor Corporation (Japan) · JPFujita Health University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although many single nucleotide polymorphisms (SNPs) have been identified to be associated with metabolic syndrome (MetS), there was only a slight improvement in the ability to predict future MetS by the simply addition of SNPs to clinical risk markers. To improve the ability to predict future MetS, combinational effects, such as SNP-SNP interaction, SNP-environment interaction, and SNP-clinical parameter (SNP × CP) interaction should be also considered. We performed a case-control study to explore novel SNP × CP interactions as risk markers for MetS based on health check-up data of Japanese male employees. We selected 99 SNPs that were previously reported to be associated with MetS and components of MetS; subsequently, we genotyped these SNPs from 360 cases and 1983 control subjects. First, we performed logistic regression analyses to assess the association of each SNP with MetS. Of these SNPs, five SNPs were significantly associated with MetS (P < 0.05): LRP2 rs2544390, rs1800592 between UCP1 and TBC1D9, APOA5 rs662799, VWF rs7965413, and rs1411766 between MYO16 and IRS2. Furthermore, we performed multiple logistic regression analyses, including an SNP term, a CP term, and an SNP × CP interaction term for each CP and SNP that was significantly associated with MetS. We identified a novel SNP × CP interaction between rs7965413 and platelet count that was significantly associated with MetS [SNP term: odds ratio (OR) = 0.78, P = 0.004; SNP × CP interaction term: OR = 1.33, P = 0.001]. This association of the SNP × CP interaction with MetS remained nominally significant in multiple logistic regression analysis after adjustment for either the number of MetS components or MetS components excluding obesity. Our results reveal new insight into platelet count as a risk marker for MetS.

Indexed as

Platelet CountPolymorphism, Single NucleotideAdultCase-Control StudiesGene FrequencyGenetic Predisposition to DiseaseGenotypeHumansMaleMetabolic SyndromeMiddle AgedRisk Factorsvon Willebrand Factorvon Willebrand Factor

Identifiers

PMID25646961
PMCPMC4315519
OpenAlexW2081985482

What OpenQuestion holds

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LicenceCC BY
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.