Evidence map›Paper›PMID 32274260›Full record

ArticleCurrent genetic medicine reports2019

DNA Methylation and Type 2 Diabetes: the Use of Mendelian Randomization to Assess Causality.

Diana L Juvinao-Quintero, Marie-France Hivert, Gemma C Sharp, Caroline L Relton, Hannah R Elliott

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Current genetic medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 37% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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  4. Review
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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 2 countries.

Diana L Juvinao-QuinteroMRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Marie-France HivertDivision of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care, Boston, USA.
Gemma C SharpMRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Caroline L ReltonMRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
Hannah R ElliottMRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
University of Bristol · GBHarvard Pilgrim Health Care · US

Funding

Medical Research Council MC_UU_00011/5Medical Research Council MC_UU_12013/2Medical Research Council MR/S009310/1Medical Research Council MR/S036520/1
6 · The paper itself

Abstract

purpose of reviewThis review summarises recent advances in the field of epigenetics in order to understand the aetiology of type 2 diabetes (T2D). RECENT

findingsDNA methylation at a number of loci has been shown to be robustly associated with T2D, including SUMMARY: Epidemiological studies have been fruitful in identifying epigenetic markers of T2D. Triangulation of evidence including utilisation of MR is essential to delineate causal from non-causal biomarkers of disease. Understanding the causality of epigenetic markers in T2D more fully will aid prioritisation of CpG sites as early biomarkers to detect disease or in drug development to target epigenetic mechanisms in order to treat patients.

Indexed as

BiomarkersCausal inference methodsDNA methylationMendelian randomisationType 2 diabetes

Identifiers

PMID32274260
PMCPMC7145450
OpenAlexW2989420084

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.