Evidence map›Paper›PMID 32258131›Full record

Observational studyBioMed research international2020

Association of Serum Uric Acid with Metabolic Syndrome and Its Components: A Mendelian Randomization Analysis.

Lu Wang, Tao Zhang, Yafei Liu, Fang Tang, Fuzhong Xue

Open access · hybridAbstract readObservational Study
In one paragraph

Observational study in BioMed research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.8field-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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.

  1. Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2021
    Pooled it
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  17. Polymorphisms of the genesF1000Research · 2021
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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

5 authors at 1 institution in 1 country.

Lu WangHealthcare Big Data Institute of Shandong University, Jinan 250000, China.ORCID https://orcid.org/0000-0003-1361-5146
Tao ZhangHealthcare Big Data Institute of Shandong University, Jinan 250000, China.ORCID https://orcid.org/0000-0003-1048-4443
Yafei LiuCenter for Data Science in Health and Medicine, Shandong Provincial Qianfoshan Hospital, The First Affiliated Hospital of Shandong First Medical University, Jingshi Road 16766, Jinan 250014, China.
Fang TangCenter for Data Science in Health and Medicine, Shandong Provincial Qianfoshan Hospital, The First Affiliated Hospital of Shandong First Medical University, Jingshi Road 16766, Jinan 250014, China.ORCID https://orcid.org/0000-0002-4378-594X
Fuzhong XueHealthcare Big Data Institute of Shandong University, Jinan 250000, China.ORCID https://orcid.org/0000-0003-0378-7956
Shandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe role of uric acid on metabolic syndrome (MetS) has always been controversial. This study aims to explore associations between uric acid with MetS and its components in Chinese female health check-up population.

methods1381 subjects constituted the longitudinal health check-up cohort. Health examination and genotyping were performed. Unadjusted and adjusted observational analyses were implemented to evaluate observational associations between uric acid with MetS and its components. Mendelian randomization analysis was performed to estimate the causal effect using variation at rs11722228 (

resultsAn increase of 65% in risk of MetS per standard deviation increase in uric acid was found using unadjusted observational analyses. This association attenuated on adjustment for potential confounders. Similar patterns were found in the association analyses of uric acid with hyperglycemia, hypertension, and dyslipidemia. Neither by performing unadjusted nor adjusted analysis did we see evidence for association of uric acid on overweight and obesity. Mendelian randomization analyses showed no evidence of causal association between uric acid and MetS and MetS components.

conclusionsWe found no causal evidence to support that increased serum uric acid is a causal risk factor for MetS or its components. Hence, there remains no strong evidence for the effeteness of undergoing urate-lowering therapy to prevent the onset of MetS or cardiovascular disease in health management.

Indexed as

Glucose Transport Proteins, FacilitativeMetabolic SyndromePolymorphism, GeneticUric AcidAdultAgedAged, 80 and overFemaleHumansMendelian Randomization AnalysisMiddle AgedProspective StudiesGlucose Transport Proteins, FacilitativeSLC2A9 protein, humanUric Acid

Identifiers

PMID32258131
PMCPMC7063870
OpenAlexW3007897866

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.