Evidence map›Paper›PMID 30003442›Full record

SynthesisClinical rheumatology2018

Assessing the causal association between smoking behavior and risk of gout using a Mendelian randomization study.

Young Ho Lee

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Clinical rheumatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

1 author.

Young Ho LeeDepartment of Rheumatology, Korea University Anam Hospital, Korea University College of Medicine, 73, Inchon-ro, Seongbuk-gu, Seoul, 02841, South Korea. lyhcgh@korea.ac.kr.ORCID http://orcid.org/0000-0003-4213-1909

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to examine whether smoking behavior is causally related to gout. Summary statistics of publicly available data from genome-wide association studies (GWAS) of smoking behavior (n = 85,997) served as the exposure dataset, while meta-analysis results of 14 studies including 2115 cases and 67,259 controls of European descent served as the outcome dataset. The data were subjected to two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. Five single-nucleotide polymorphisms (SNPs) from GWAS of smoking behavior were selected as instrumental variables (IVs) to improve inference: CHRNA3 (rs1051730), PDE1C (rs215614), CYP2A6 (rs4105144), CHRNB3 (rs6474412), and CYP2B6 (rs7260329). The IVW data did not support a causal association between smoking behavior and gout (beta = - 0.035, SE = 0.036, p = 0.333). MR-Egger regression indicated that directional pleiotropy did not bias the result (intercept = 0.021; p = 0.560). MR-Egger analysis revealed no causal association between smoking behavior and gout (beta = - 0.074, SE = 0.070, p = 0.366). The weighted median approach did not support a causal association between smoking behavior and gout (beta = - 0.043, SE = 0.040, p = 0.279). Cochran's Q test indicated no evidence of heterogeneity between IV estimates based on individual variants. The results of "leave one out" analysis demonstrated that no single SNP drove the IVW point estimate. MR estimates using IVW, weighted median, and MR-Egger analysis were consistent and did not support a causal inverse association between smoking behavior and gout.

Indexed as

Polymorphism, Single NucleotideCase-Control StudiesEuropeGenome-Wide Association StudyGoutHumansMendelian Randomization AnalysisRegression AnalysisSmokingGoutMendelian randomizationSmoking

Identifiers

What OpenQuestion holds

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Registered trials

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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.