Evidence map›Paper›PMID 21441441›Full record

ArticleDiabetes2011

Associations of common genetic variants with age-related changes in fasting and postload glucose: evidence from 18 years of follow-up of the Whitehall II cohort.

Anders C Jensen, Adam Barker, Meena Kumari, Eric J Brunner, Mika Kivimäki, Aroon D Hingorani, Nicholas J Wareham, Adam G Tabák, Daniel R Witte, Claudia Langenberg

Abstract read
In one paragraph

Article in Diabetes, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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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3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Anders C JensenSteno Diabetes Center, Gentofte, Denmark.
Adam Barker
Meena Kumari
Eric J Brunner
Mika Kivimäki
Aroon D Hingorani
Nicholas J Wareham
Adam G Tabák
Daniel R Witte
Claudia Langenberg

Funding

British Heart Foundation RG/07/008/23674Medical Research Council G0100222Medical Research Council G0902037Medical Research Council G19/35Medical Research Council G8802774Medical Research Council MC_U106179471
6 · The paper itself

Abstract

objectiveIn the general, nondiabetic population, fasting glucose increases only slightly over time, whereas 2-h postload glucose shows a much steeper age-related rise. The reasons underlying these different age trajectories are unknown. We investigated whether common genetic variants associated with fasting and 2-h glucose contribute to age-related changes of these traits. RESEARCH DESIGN AND

methodsWe studied 5,196 nondiabetic participants of the Whitehall II cohort (aged 40-78 years) attending up to four 5-yearly oral glucose tolerance tests. A genetic score was calculated separately for fasting and 2-h glucose, including 16 and 5 single nucleotide polymorphisms, respectively. Longitudinal modeling with age centered at 55 years was used to study the effects of each genotype and genetic score on fasting and 2-h glucose and their interactions with age, adjusting for sex and time-varying BMI.

resultsThe fasting glucose genetic score was significantly associated with fasting glucose with a 0.029 mmol/L (95% CI 0.023-0.034) difference (P = 2.76 × 10(-21)) per genetic score point, an association that remained constant over time (age interaction P = 0.17). Two-hour glucose levels differed by 0.076 mmol/L (0.047-0.105) per genetic score point (P = 3.1 × 10(-7)); notably, this effect became stronger with increasing age by 0.006 mmol/L (0.003-0.009) per genetic score point per year (age interaction P = 3.0 × 10(-5)), resulting in diverging age trajectories by genetic score.

conclusionsCommon genetic variants contribute to the age-related rise of 2-h glucose levels, whereas associations of variants for fasting glucose are constant over time, in line with stable age trajectories of fasting glucose.

Indexed as

AdultAgedAge FactorsBlood GlucoseBody Mass IndexDiabetes Mellitus, Type 2FastingFemaleGenotypeGlucose IntoleranceHumansMaleMiddle AgedPolymorphism, Single NucleotideBlood Glucose

Identifiers

PMID21441441
PMCPMC3292338

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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.