Evidence map›Paper›PMID 21767357›Full record

ArticleLipids in health and disease2011

Genetic variants in lipid metabolism are independently associated with multiple features of the metabolic syndrome.

Cécile M Povel, Jolanda M A Boer, Sandra Imholz, Martijn E T Dollé, Edith J M Feskens

Open access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 27 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

5 authors at 2 institutions in 1 country.

Cécile M PovelCentre for Nutrition and Health, National Institute for Public Health and the Environment, Bilthoven, the Netherlands. cecile.povel@rivm.nl
Jolanda M A Boer
Sandra Imholz
Martijn E T Dollé
Edith J M Feskens
National Institute for Public Health and the Environment · NLWageningen University & Research · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOur objective was to find single nucleotide polymorphisms (SNPs), within transcriptional pathways of glucose and lipid metabolism, which are related to multiple features of the metabolic syndrome (MetS).

methods373 SNPs were measured in 3575 subjects of the Doetinchem cohort. Prevalence of MetS features, i.e. hyperglycemia, abdominal obesity, decreased HDL-cholesterol levels and hypertension, were measured twice in 6 years. Associations between the SNPs and the individual MetS features were analyzed by log-linear models. For SNPs related to multiple MetS features (P < 0.01), we investigated whether these associations were independent of each other.

resultsTwo SNPs, CETP Ile405Val and APOE Cys112Arg, were associated with both the prevalence of low HDL-cholesterol level (Ile405Val P = < .0001; Cys112Arg P = 0.001) and with the prevalence of abdominal obesity (Ile405Val P = 0.007; Cys112Arg P = 0.007). For both SNPs, the association with HDL-cholesterol was partly independent of the association with abdominal obesity and vice versa.

conclusionTwo SNPs, mainly known for their role in lipid metabolism, were associated with two MetS features i.e., low HDL-cholesterol concentration, as well as, independent of this association, abdominal obesity. These SNPs may help to explain why low HDL-cholesterol levels and abdominal obesity frequently co-occur.

Indexed as

Genetic Association StudiesGenetic VariationAdultAmino Acid SubstitutionApolipoproteins ECholesterol Ester Transfer ProteinsCohort StudiesFemaleHumansLipid MetabolismMaleMetabolic SyndromeMiddle AgedPolymorphism, Single NucleotideYoung AdultApolipoproteins ECETP protein, humanCholesterol Ester Transfer Proteins

Identifiers

PMID21767357
PMCPMC3156750
OpenAlexW2151599123

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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.