Evidence map›Paper›PMID 26824674›Full record

ArticlePloS one2016

Interactions of Environmental Factors and APOA1-APOC3-APOA4-APOA5 Gene Cluster Gene Polymorphisms with Metabolic Syndrome.

Yanhua Wu, Yaqin Yu, Tiancheng Zhao, Shibin Wang, Yingli Fu, Yue Qi, Guang Yang, Wenwang Yao, Yingying Su, Yue Ma and 3 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 5 pooled it
7.2field-weighted citation impact, top 2% 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

28 citing papers in PubMed, 5 syntheses or guidelines pooled it, 60 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 2 institutions in 1 country.

Yanhua WuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Yaqin YuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Tiancheng ZhaoDepartment of Endoscopy Center, China-Japan Union Hospital of Jilin University, Changchun, Jilin, 130021, China.
Shibin WangDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Yingli FuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Yue QiDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Guang YangDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Wenwang YaoDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Yingying SuDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Yue MaDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Jieping ShiDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Jing JiangDivision of Clinical Epidemiology, First Hospital of Jilin University, Changchun, Jilin, 130021, China.
Changgui KouDepartment of Epidemiology and Biostatistics, School of Public Health, Jilin University, 1163 Xinmin Street, Changchun, 130021, Jilin province, China.
Jilin University · CNUnion Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe present study investigated the prevalence and risk factors for Metabolic syndrome. We evaluated the association between single nucleotide polymorphisms (SNPs) in the apolipoprotein APOA1/C3/A4/A5 gene cluster and the MetS risk and analyzed the interactions of environmental factors and APOA1/C3/A4/A5 gene cluster polymorphisms with MetS.

methodsA study on the prevalence and risk factors for MetS was conducted using data from a large cross-sectional survey representative of the population of Jilin Province situated in northeastern China. A total of 16,831 participations were randomly chosen by multistage stratified cluster sampling of residents aged from 18 to 79 years in all nine administrative areas of the province. Environmental factors associated with MetS were examined using univariate and multivariate logistic regression analyses based on the weighted sample data. A sub-sample of 1813 survey subjects who met the criteria for MetS patients and 2037 controls from this case-control study were used to evaluate the association between SNPs and MetS risk. Genomic DNA was extracted from peripheral blood lymphocytes, and SNP genotyping was determined by MALDI-TOF-MS. The associations between SNPs and MetS were examined using a case-control study design. The interactions of environmental factors and APOA1/C3/A4/A5 gene cluster polymorphisms with MetS were assessed using multivariate logistic regression analysis.

resultsThe overall adjusted prevalence of MetS was 32.86% in Jilin province. The prevalence of MetS in men was 36.64%, which was significantly higher than the prevalence in women (29.66%). MetS was more common in urban areas (33.86%) than in rural areas (31.80%). The prevalence of MetS significantly increased with age (OR = 8.621, 95%CI = 6.594-11.272). Mental labor (OR = 1.098, 95%CI = 1.008-1.195), current smoking (OR = 1.259, 95%CI = 1.108-1.429), excess salt intake (OR = 1.252, 95%CI = 1.149-1.363), and a fruit and dairy intake less than 2 servings a week were positively associated with MetS (P<0.05). A family history of diabetes (OR = 1.630, 95%CI = 1.484-1.791), cardiovascular disease or cerebral diseases (OR = 1.297, 95%CI = 1.211-1.389) was associated with MetS. APOA1 rs670, APOA5 rs662799 and rs651821 revealed significant differences in genotype distributions between the MetS patients and control subjects. The minor alleles of APOA1 rs670, APOA5 rs662799 and rs651821, and APOA5 rs2075291 were associated with MetS (P<0.0016). APOA1 rs5072 and APOC3 rs5128, APOA5 rs651821 and rs662799 were in strong linkage disequilibrium to each other with r2 greater than 0.8. Five haplotypes were associated with an increased risk of MetS (OR = 1.23, 1.58, 1.80, 1.90, and 1.98). When we investigated the interactions of environmental factors and APOA1/C3/A4/A5 gene cluster gene polymorphisms, we found that APOA5 rs662799 had interactions with tobacco use and alcohol consumption (PGE<0.05).

conclusionsThere was a high prevalence of MetS in the northeast of China. Male gender, increasing age, mental labor, family history of diabetes, cardiovascular disease or cerebral diseases, current smoking, excess salt intake, fruit and dairy intake less than 2 servings a week, and drinking were associated with MetS. The APOA1/C3/A4/A5 gene cluster was associated with MetS in the Han Chinese. APOA5 rs662799 had interactions with the environmental factors associated with MetS.

Indexed as

Polymorphism, Single NucleotideAdolescentAdultAgedAge FactorsAllelesApolipoprotein A-IApolipoprotein A-VApolipoprotein C-IIIApolipoproteins ACase-Control StudiesChinaCross-Sectional StudiesFemaleGene-Environment InteractionGene ExpressionAPOA1 protein, humanAPOA5 protein, humanApolipoprotein A-Iapolipoprotein A-IVApolipoprotein A-VApolipoprotein C-IIIApolipoproteins A

Identifiers

PMID26824674
PMCPMC4732668
OpenAlexW2254405082

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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.