Evidence map›Paper›PMID 29081791›Full record

ArticleFrontiers in genetics2017

Physical Interactions and Expression Quantitative Traits Loci Identify Regulatory Connections for Obesity and Type 2 Diabetes Associated SNPs.

Tayaza Fadason, Cameron Ekblad, John R Ingram, William S Schierding, Justin M O'Sullivan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
9.7field-weighted citation impact, top 2% 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

33 citing papers in PubMed, 98 citations in OpenAlex.

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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 1 country.

Tayaza FadasonLiggins Institute, University of Auckland, Auckland, New Zealand.
Cameron EkbladLiggins Institute, University of Auckland, Auckland, New Zealand.
John R IngramPlant & Food Research, Auckland, New Zealand.
William S SchierdingLiggins Institute, University of Auckland, Auckland, New Zealand.
Justin M O'SullivanLiggins Institute, University of Auckland, Auckland, New Zealand.
University of Auckland · NZPlant & Food Research · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mechanisms that underlie the association between obesity and type 2 diabetes are not fully understood. Here, we investigated the role of the 3D genome organization in the pathogeneses of obesity and type-2 diabetes. We interpreted the combined and differential impacts of 196 diabetes and 390 obesity associated single nucleotide polymorphisms (SNPs) by integrating data on the genes with which they physically interact (as captured by Hi-C) and the functional [i.e., expression quantitative trait loci (eQTL)] outcomes associated with these interactions. We identified 861 spatially regulated genes (e.g.,

Indexed as

eQTLsGWAS risk variantsHi-CObesity and type-2 diabetes co-morbidityspatial gene regulation

Identifiers

PMID29081791
PMCPMC5645506
OpenAlexW2756639495

What OpenQuestion holds

Textmetadata
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.