Evidence map›Paper›PMID 26017687›Full record

ArticleNature communications2015

A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease.

Omar S Ahmad, John A Morris, Muhammad Mujammami, Vincenzo Forgetta, Aaron Leong, Rui Li, Maxime Turgeon, Celia M T Greenwood, George Thanassoulis, James B Meigs and 2 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 2 pooled it
11.1field-weighted citation impact, top 1% 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

65 citing papers in PubMed, 2 syntheses or guidelines pooled it, 129 citations in OpenAlex.

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5 more citing papers are in PubMed but not listed here.

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

12 authors at 4 institutions in 2 countries.

Omar S Ahmad1] Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec H3A 0G4, Canada [2] Department of Medicine, McGill University, Montreal, Quebec H3A 0G4, Canada.
John A Morris1] Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec H3A 0G4, Canada [2] Department of Human Genetics, McGill University, Montréal, Québec H3A 0G4, Canada.
Muhammad Mujammami1] Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec H3A 0G4, Canada [2] Department of Medicine, McGill University, Montreal, Quebec H3A 0G4, Canada.
Vincenzo Forgetta1] Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec H3A 0G4, Canada [2] Department of Medicine, McGill University, Montreal, Quebec H3A 0G4, Canada.
Aaron LeongDivision of General Internal Medicine, Massachusetts General Hospital and Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA.
Rui Li1] Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec H3A 0G4, Canada [2] Department of Medicine, McGill University, Montreal, Quebec H3A 0G4, Canada [3] Department of Human Genetics, McGill University, Montréal, Québec H3A 0G4, Canada.
Maxime TurgeonDepartment of Oncology, Epidemiology, Biostatistics and Occupational Health, and Human Genetics, McGill University, Montreal, Quebec H3A 0G4, Canada.
Celia M T GreenwoodDepartment of Oncology, Epidemiology, Biostatistics and Occupational Health, and Human Genetics, McGill University, Montreal, Quebec H3A 0G4, Canada.
George Thanassoulis1] Department of Medicine, McGill University, Montreal, Quebec H3A 0G4, Canada [2] Department of Human Genetics, McGill University, Montréal, Québec H3A 0G4, Canada.
James B MeigsDivision of General Internal Medicine, Massachusetts General Hospital and Department of Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA.
Robert Sladek1] Department of Medicine, McGill University, Montreal, Quebec H3A 0G4, Canada [2] Department of Human Genetics, McGill University, Montréal, Québec H3A 0G4, Canada.
J Brent Richards1] Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec H3A 0G4, Canada [2] Department of Medicine, McGill University, Montreal, Quebec H3A 0G4, Canada [3] Department of Human Genetics, McGill University, Montréal, Québec H3A 0G4, Canada [4] Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK.
McGill University · CAJewish General Hospital · CAHarvard University · USMassachusetts General Hospital · US

Funding

Rare Sequence Variation and Diabetes Quantitative TraitsU01DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2015 to 2019
$3.6M
Epidemiology of Precursors to Type 2 DiabetesK24DK080140 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI MEIGS, JAMES B · 2007 to 2016
$1.9M
Canadian Institutes of Health ResearchNIDDK NIH HHS K24 DK080140NIDDK NIH HHS U01 DK078616
6 · The paper itself

Abstract

In observational studies, type-2 diabetes (T2D) is associated with an increased risk of coronary heart disease (CHD), yet interventional trials have shown no clear effect of glucose-lowering on CHD. Confounding may have therefore influenced these observational estimates. Here we use Mendelian randomization to obtain unconfounded estimates of the influence of T2D and fasting glucose (FG) on CHD risk. Using multiple genetic variants associated with T2D and FG, we find that risk of T2D increases CHD risk (odds ratio (OR)=1.11 (1.05-1.17), per unit increase in odds of T2D, P=8.8 × 10(-5); using data from 34,840/114,981 T2D cases/controls and 63,746/130,681 CHD cases/controls). FG in non-diabetic individuals tends to increase CHD risk (OR=1.15 (1.00-1.32), per mmol·per l, P=0.05; 133,010 non-diabetic individuals and 63,746/130,681 CHD cases/controls). These findings provide evidence supporting a causal relationship between T2D and CHD and suggest that long-term trials may be required to discern the effects of T2D therapies on CHD risk.

Indexed as

AdultAgedBlood GlucoseCase-Control StudiesCausalityCoronary DiseaseDiabetes Mellitus, Type 2Glycated HemoglobinHumansMendelian Randomization AnalysisMiddle AgedOdds RatioPolymorphism, Single NucleotideRisk FactorsBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID26017687
PMCPMC4458864
OpenAlexW1848757588

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.