Evidence map›Paper›PMID 24382995›Full record

ArticleCholesterol2013

APOA2 Polymorphism in Relation to Obesity and Lipid Metabolism.

Moushira Erfan Zaki, Khalda Sayed Amr, Mohamed Abdel-Hamid

Open access · hybridAbstract read
In one paragraph

Article in Cholesterol, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
1.2field-weighted citation impact, top 22% 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 29 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

3 authors at 1 institution in 1 country.

Moushira Erfan ZakiMedical Research Division, Biological Anthropology Department, National Research Centre, Cairo 12622, Egypt.
Khalda Sayed AmrHuman Genetics and Genome Research Division, Medical Molecular Genetics Department, National Research Centre, Cairo 12622, Egypt.
Mohamed Abdel-HamidHuman Genetics and Genome Research Division, Medical Molecular Genetics Department, National Research Centre, Cairo 12622, Egypt.
National Research Centre · EG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives. This study aims to analysis the relationship between c.-492T>C polymorphism in APOA2 gene and the risk for obesity in a sample of Egyptian adolescents and investigates its effect on body fat distribution and lipid metabolism. Material and Methods. A descriptive, cross-sectional study was conducted on 303 adolescents. They were 196 obese and 107 nonobese, aged 16-19 years old. Variables examined included body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), systolic and diastolic blood pressure (BP), body fat percentage (BF%), abdominal visceral fat layer, and dietary intake. Abdominal visceral fat thickness was determined by ultrasonography. The polymorphism in the APOA2 c.-492T>C was analyzed by PCR amplification. Results. Genotype frequencies were in Hardy-Weinberg equilibrium. The frequency of the mutant C allele was significantly higher in obese cases compared to nonobese. After multivariate adjustment, waist, BF% and visceral adipose layer, food consumption, and HDL-C were significantly higher in homozygous allele CC carriers than TT+TC carriers. Conclusions. Homozygous individuals for the C allele had higher obesity risk than carriers of the T allele and had elevated levels of visceral adipose tissue and serum HDL-C. Moreover, the study shows association between the APOA2 c.-492T>C polymorphism and food consumption.

Identifiers

PMID24382995
PMCPMC3872025
OpenAlexW2022976639

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.