Evidence map›Paper›PMID 29712557›Full record

ArticleLipids in health and disease2018

Association of apolipoprotein E gene polymorphisms with blood lipids and their interaction with dietary factors.

Israa M Shatwan, Kristian Hillert Winther, Basma Ellahi, Peter Elwood, Yoav Ben-Shlomo, Ian Givens, Margaret P Rayman, Julie A Lovegrove, Karani S Vimaleswaran

Open access · goldAbstract read
In one paragraph

Article in Lipids in health and disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

17 citing papers in PubMed, 26 citations in OpenAlex.

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  16. Impact ofPharmacogenomics and personalized medicine · 2020
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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

9 authors at 7 institutions in 3 countries.

Israa M ShatwanHugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK.
Kristian Hillert WintherDepartment of Endocrinology and Metabolism Odense, University Hospital Denmark, Aarhus, Denmark.
Basma EllahiFaculty of Health and Social Care, University of Chester, Chester, CH1 1SL, UK.
Peter ElwoodDepartment of Epidemiology, Statistics and Public Health, Cardiff University, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK.
Yoav Ben-ShlomoPopulation Health Sciences, University of Bristol, Bristol, BS8 2PS, UK.
Ian GivensInstitute for Food, Nutrition and Health, University of Reading, Earley Gate, Reading, RG6 6AR, UK.
Margaret P RaymanDepartment of Nutritional Sciences Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK.
Julie A LovegroveHugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK.
Karani S VimaleswaranHugh Sinclair Unit of Human Nutrition and Institute for Cardiovascular and Metabolic Research (ICMR), Department of Food and Nutritional Sciences, University of Reading, Whiteknights, PO Box 226, Reading, RG6 6AP, UK. v.karani@reading.ac.uk.
University of Reading · GBCardiff University · GBKing Abdulaziz University · SAOdense University Hospital · DKUniversity of Bristol · GBUniversity of Chester · GBUniversity of Surrey · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral candidate genes have been identified in relation to lipid metabolism, and among these, lipoprotein lipase (LPL) and apolipoprotein E (APOE) gene polymorphisms are major sources of genetically determined variation in lipid concentrations. This study investigated the association of two single nucleotide polymorphisms (SNPs) at LPL, seven tagging SNPs at the APOE gene, and a common APOE haplotype (two SNPs) with blood lipids, and examined the interaction of these SNPs with dietary factors.

methodsThe population studied for this investigation included 660 individuals from the Prevention of Cancer by Intervention with Selenium (PRECISE) study who supplied baseline data. The findings of the PRECISE study were further replicated using 1238 individuals from the Caerphilly Prospective cohort (CaPS). Dietary intake was assessed using a validated food-frequency questionnaire (FFQ) in PRECISE and a validated semi-quantitative FFQ in the CaPS. Interaction analyses were performed by including the interaction term in the linear regression model adjusted for age, body mass index, sex and country.

resultsThere was no association between dietary factors and blood lipids after Bonferroni correction and adjustment for confounding factors in either cohort. In the PRECISE study, after correction for multiple testing, there was a statistically significant association of the APOE haplotype (rs7412 and rs429358; E2, E3, and E4) and APOE tagSNP rs445925 with total cholesterol (P = 4 × 10

conclusionIn summary, our findings from the two cohorts confirm that genetic variations at the APOE locus influence plasma total cholesterol concentrations, however, the gene-diet interactions on lipids require further investigation in larger cohorts.

Indexed as

DietAllelesApolipoproteins EBody Mass IndexCardiovascular DiseasesCholesterol, HDLCholesterol, LDLFemaleGenetic Association StudiesGenetic Predisposition to DiseaseGenotypeHumansLipidsMaleMiddle AgedPolymorphism, Single NucleotideApoE protein, humanApolipoproteins ECholesterol, HDLCholesterol, LDLLipidsTriglyceridesAPOE geneCaerphilly prospective studiesLDL-CPRECISETotal cholesterol

Identifiers

PMID29712557
PMCPMC5928585
OpenAlexW2801127804

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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.