Evidence map›Paper›PMID 18853134›Full record

ArticleDiabetologia2008

The search for putative unifying genetic factors for components of the metabolic syndrome.

M Sjögren, V Lyssenko, A Jonsson, G Berglund, P Nilsson, L Groop, M Orho-Melander

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Diabetologia, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 4 pooled it
3.5field-weighted citation impact, top 7% 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

23 citing papers in PubMed, 4 syntheses or guidelines pooled it, 69 citations in OpenAlex.

  1. Pooled it
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  7. Transcription factor 7-like 2 polymorphism and context-specific risk of metabolic syndrome, type 2 diabetes, and dyslipidemia.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2017
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  16. Metabolic syndrome in South Asians.Indian journal of endocrinology and metabolism · 2012
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  20. IGF2BP1, IGF2BP2 and IGF2BP3 genotype, haplotype and genetic model studies in metabolic syndrome traits and diabetes.Growth hormone & IGF research : official journal of the Growth Hormone Research Society and the International IGF Research Society · 2010
    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

7 authors at 2 institutions in 2 countries.

M SjögrenDepartment of Clinical Sciences, Diabetes and Endocrinology, Lund University, CRC house 91, Malmö, Sweden. marketa.sjogren@med.lu.se
V Lyssenko
A Jonsson
G Berglund
P Nilsson
L Groop
M Orho-Melander
Lund University · SEUniversity of Helsinki · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aims/hypothesisThe metabolic syndrome is a cluster of factors contributing to increased risk of cardiovascular disease and type 2 diabetes but unifying mechanisms have not been identified. Our aim was to study whether common variations in 17 genes previously associated with type 2 diabetes or components of the metabolic syndrome and variants in nine genes with inconsistent association with at least two components of the metabolic syndrome would also predict future development of components of the metabolic syndrome, individually or in combination.

methodsGenetic variants were studied in a large prospective study of 16,143 non-diabetic individuals (mean follow-up time 23 years) from the Malmö Preventive Project. In this study, development of at least three of obesity (BMI >or= 30 kg/m(2)), dyslipidaemia (triacylglycerol >or= 1.7 mmol/l and/or lipid-lowering treatment), hypertension (blood pressure >or= 140/90 mmHg and/or antihypertensive medication) and hyperglycaemia (fasting plasma glucose >or= 5.6 mmol/l and/or known diabetes) was defined as development of the metabolic syndrome. The risk of developing at least three components of the metabolic syndrome or the individual components was calculated by logistic regression adjusted for age at baseline, follow-up time and sex.

resultsPolymorphisms in TCF7L2 (rs7903146, OR 1.10, 95% CI 1.04-1.17, p = 0.00097), FTO (rs9939609, OR 1.08, 95% CI 1.02-1.14, p = 0.0065), WFS1 (rs10010131, OR 1.07, 95% CI 1.02-1.13, p = 0.0078) and IGF2BP2 (rs4402960, OR 1.07, 95% CI 1.01-1.13, p = 0.021) predicted the development of at least three components of the metabolic syndrome in both univariate and multivariate analysis; in the case of TCF7L2, WFS1 and IGF2BP this was due to their association with hyperglycaemia (p < 0.00001, p = 0.0033 and p = 0.027, respectively) and for FTO it was due to its association with obesity (p = 0.004). A polymorphism in the GCKR gene predicted dyslipidaemia (rs1260326, OR 1.15, 95% CI 1.09-1.22, p < 0.00001) but not the metabolic syndrome. None of the studied polymorphisms was associated with more than two components of the metabolic syndrome. A composite genotype score of the 17 polymorphisms associated with type 2 diabetes predicted the development of at least three components of the metabolic syndrome (OR 1.04, p < 0.00001) and the development of hyperglycaemia (OR 1.06, p < 0.00001). Carriers of >or=19 risk alleles had 51 and 72% increased risk of developing at least three components of the metabolic syndrome and hyperglycaemia, respectively, compared with carriers of <or=12 risk alleles (p < 0.00001 for both). CONCLUSIONS/

interpretationPolymorphisms in susceptibility genes for type 2 diabetes (TCF7L2, WFS1, IGF2BP2) and obesity (FTO) predispose to the metabolic syndrome by increasing the risk of one specific component of the metabolic syndrome. The findings argue against a unifying genetic component for the metabolic syndrome.

Indexed as

Diabetes Mellitus, Type 2FemaleFollow-Up StudiesGenotypeHumansMaleMiddle AgedPolymorphism, Single NucleotideRisk Factors

Identifiers

PMID18853134
OpenAlexW2062340367

What OpenQuestion holds

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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.