Evidence map›Paper›PMID 25283508›Full record

SynthesisActa pharmacologica Sinica2014

Serum uric acid levels are associated with polymorphisms in the SLC2A9, SF1, and GCKR genes in a Chinese population.

Xue Sun, Feng Jiang, Rong Zhang, Shan-shan Tang, Miao Chen, Dan-feng Peng, Jing Yan, Tao Wang, Shi-yun Wang, Yu-qian Bao and 2 more

Open access · bronzeAbstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Acta pharmacologica Sinica, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

13 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. International journal of endocrinology · 2022
    Article
  7. Article
  8. Sex Differences in Urate Handling.International journal of molecular sciences · 2020
    Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. 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

12 authors at 2 institutions in 1 country.

Xue SunShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Feng JiangShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Rong ZhangShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Shan-shan TangShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Miao ChenShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Dan-feng PengShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Jing YanShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Tao WangShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Shi-yun WangShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Yu-qian BaoShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Cheng Hu1] Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China [2] Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai 201400, China.
Wei-ping JiaShanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Shanghai Jiao Tong University · CNShanghai Sixth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimGenome-wide association studies have identified several novel loci associated with serum uric acid concentrations in individuals of European descent. In the current study, we aimed to evaluate the associations between these loci and serum uric acid concentrations in a Chinese population.

methodsFourteen single nucleotide polymorphisms (SNPs) mapped in or near 11 loci (PDZK1, GCKR, LRP2, SLC2A9, ABCG2, LRRC16A, SLC17A1, SLC17A3, SLC22A11, SLC22A12 and SF1) were genotyped in 2329 Chinese subjects in Shanghai. Serum biochemical parameters including uric acid concentrations were determined. All the variants were analyzed for gender differences since uric acid metabolism differed between genders.

resultsIn males after adjustments for age and BMI, GCKR rs780094, SLC2A9 rs11722228 and SF1 rs606458 were associated with the uric acid concentrations, which were statistically significant (P=0.016, 0.001 and 0.03, respectively), whereas SLC2A9 rs3775948 was marginally associated with the uric acid concentrations (P=0.071). In females, SLC22A12 rs506338 was also marginally associated with the uric acid concentrations (P=0.057). The meta-analysis for combined data from both males and females revealed that rs3775948 and rs606458 were associated with the uric acid concentrations (P=0.036 and 0.043, respectively). Furthermore, the gender significantly affected the association of rs11722228 with serum uric acid levels (P=0.012).

conclusionThe SLC2A9 rs11722228, SF1 rs606458 and GCKR rs780094 variants modulate uric acid concentrations in Chinese males, while SF1 rs606458 and SLC2A9 rs3775948 are associated with the uric acid concentrations in both Chinese males and females.

Indexed as

Polymorphism, Single NucleotideAdaptor Proteins, Signal TransducingAdultAgedAsian PeopleChinaDNA-Binding ProteinsFemaleGene FrequencyGenome-Wide Association StudyGenotypeGlucose Transport Proteins, FacilitativeHumansMaleMiddle AgedPhenotypeAdaptor Proteins, Signal TransducingDNA-Binding ProteinsGCKR protein, humanGlucose Transport Proteins, FacilitativeRNA Splicing FactorsSF1 protein, humanSLC2A9 protein, humanTranscription FactorsUric Acid

Identifiers

PMID25283508
PMCPMC4220079
OpenAlexW1987215808

What OpenQuestion holds

Textmetadata
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.