Evidence map›Paper›PMID 23522429›Full record

ArticleLipids in health and disease2013

Associations of SAA1 gene polymorphism with lipid lelvels and osteoporosis in Chinese women.

Zheng-Ping Feng, Xiao-Yu Li, Rong Jiang, Hua-Cong Deng, Mei Yang, Qin Zhou, Wen-Jun Que, Jia Du

Open access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

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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

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Relationship Between Serum Amyloid A1 (Diabetes, metabolic syndrome and obesity : targets and therapy · 2021
    Article
  3. Article
  4. Bioscience reports · 2019
    Article
  5. Article
  6. Review
  7. Article
  8. Article
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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

8 authors at 2 institutions in 1 country.

Zheng-Ping FengDepartment of Endocrinology, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China. fengzhengping_f@yeah.net
Xiao-Yu Li
Rong Jiang
Hua-Cong Deng
Mei Yang
Qin Zhou
Wen-Jun Que
Jia Du
Chongqing Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe development of osteoporosis is associated with several risk factors, such as genetic polymorphisms and enviromental factors. This study assessed the correlation between SAA1 gene rs12218 polymorphism and HDL-C lelvels and osteoporosis in a population of Chinese women.

methodsA total of 387 postmenopausal female patients who were diagnosed with osteoporosis (case group) based on bone mineral density measurements via dual-energy x-ray absorptiometry and 307 females with no osteoporosis (control group) were included in this study. Correlations between SAA1 gene rs12218 polymorphism and osteoporosis and HDL-C level were investigated through the identification of SAA1 gene rs12218 polymorphism genotypes using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP).

resultsThe TT genotype of rs12218 was more frequently in osteoporosis patients than in control subjects (P <0.001). And the rs12218 was found to be associated with plasma TG, HDL-C, LDL-C, and BMD levels in osteoporosis patients (P<0.05).

conclusionsThe present results indicate that both osteoporosis and lipids levels are associated with the TT genotype of rs12218 in the human SAA1 gene.

Indexed as

Bone DensityChinaCholesterol, HDLFemaleGenetic Association StudiesHumansLipidsMiddle AgedOsteoporosis, PostmenopausalPolymorphism, Single NucleotideRisk FactorsSerum Amyloid A ProteinCholesterol, HDLLipidsSAA1 protein, humanSerum Amyloid A Protein

Identifiers

PMID23522429
PMCPMC3702468
OpenAlexW2147820262

What OpenQuestion holds

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LicenceCC BY
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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.