Evidence map›Paper›PMID 29181734›Full record

ArticleHuman genetics2018

Pleiotropy of cardiometabolic syndrome with obesity-related anthropometric traits determined using empirically derived kinships from the Busselton Health Study.

Gemma Cadby, Phillip E Melton, Nina S McCarthy, Marcio Almeida, Sarah Williams-Blangero, Joanne E Curran, John L VandeBerg, Jennie Hui, John Beilby, A W Musk and 4 more

Abstract read
PubMed Publisher
In one paragraph

Article in Human genetics, 2018. 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
0.7field-weighted citation impact, top 23% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 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

14 authors at 3 institutions in 2 countries.

Gemma CadbyCentre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia. gemma.cadby@uwa.edu.au.ORCID http://orcid.org/0000-0001-7317-6531
Phillip E MeltonCentre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia.
Nina S McCarthyCentre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia.
Marcio AlmeidaSouth Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, USA.
Sarah Williams-BlangeroSouth Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, USA.
Joanne E CurranSouth Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, USA.
John L VandeBergSouth Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, USA.
Jennie HuiBusselton Population Medical Research Institute Inc., Perth, Australia.
John BeilbyBusselton Population Medical Research Institute Inc., Perth, Australia.
A W MuskBusselton Population Medical Research Institute Inc., Perth, Australia.
Alan L JamesBusselton Population Medical Research Institute Inc., Perth, Australia.
Joseph HungSchool of Medicine, The University of Western Australia, Perth, Australia.
John BlangeroSouth Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, USA.
Eric K MosesCentre for Genetic Origins of Health and Disease, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Australia.
The University of Western Australia · AUThe University of Texas Rio Grande Valley · USPathwest Laboratory Medicine · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over two billion adults are overweight or obese and therefore at an increased risk of cardiometabolic syndrome (CMS). Obesity-related anthropometric traits genetically correlated with CMS may provide insight into CMS aetiology. The aim of this study was to utilise an empirically derived genetic relatedness matrix to calculate heritabilities and genetic correlations between CMS and anthropometric traits to determine whether they share genetic risk factors (pleiotropy). We used genome-wide single nucleotide polymorphism (SNP) data on 4671 Busselton Health Study participants. Exploiting both known and unknown relatedness, empirical kinship probabilities were estimated using these SNP data. General linear mixed models implemented in SOLAR were used to estimate narrow-sense heritabilities (h

Indexed as

AnthropometryGenetic PleiotropyAdultAgedBlood GlucoseCardiovascular DiseasesCholesterol, HDLCross-Sectional StudiesEmpirical ResearchFemaleHumansIliac ArteryInsulinMaleMetabolic SyndromeMiddle AgedBlood GlucoseCholesterol, HDLInsulinTriglycerides

Identifiers

PMID29181734
OpenAlexW2768797563

What Socratic holds

Textmetadata
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 Socratic graph.