Evidence map›Paper›PMID 23029515›Full record

SynthesisPloS one2012

Can genetic pleiotropy replicate common clinical constellations of cardiovascular disease and risk?

Omri Gottesman, Esther Drill, Vaneet Lotay, Erwin Bottinger, Inga Peter

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.

  1. Pooled it
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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.

Omri GottesmanThe Charles Bronfman Institute for Personalized Medicine, Mount Sinai School of Medicine, New York, New York, United States of America. omri.gottesman@mssm.edu
Esther Drill
Vaneet Lotay
Erwin Bottinger
Inga Peter
Icahn School of Medicine at Mount Sinai · USColumbia University · US

Funding

MOUNT SINAI INSTITUTES FOR CLINICAL AND TRANSLATIONAL SCIENCESUL1RR029887 · NCRR · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SAMPSON, HUGH A · 2009 to 2011
$19.2M
Mount Sinai Institutes for Clinical and Translational SciencesUL1TR000067 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SAMPSON, HUGH A · 2012 to 2014
$16.5M
Biorepository for Genomic Medicine in diverse CommunitiesU01HG006380 · NHGRI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BOTTINGER, ERWIN P. · 2011 to 2015
$4.5M
Genetic Markers of GIK Effect in Acute Coronary Syndrome in the IMMEDIATE TrialR01HL090997 · NHLBI · TUFTS MEDICAL CENTER · PI PETER, INGA · 2007 to 2012
$1.5M
NCATS NIH HHS UL1 TR000067NCATS NIH HHS UL1TR000067NCRR NIH HHS UL1 RR029887NHGRI NIH HHS U01 HG006380NHLBI NIH HHS R01 HL090997
6 · The paper itself

Abstract

The relationship between obesity, diabetes, hyperlipidemia, hypertension, kidney disease and cardiovascular disease (CVD) is established when looked at from a clinical, epidemiological or pathophysiological perspective. Yet, when viewed from a genetic perspective, there is comparatively little data synthesis that these conditions have an underlying relationship. We sought to investigate the overlap of genetic variants independently associated with each of these commonly co-existing conditions from the NHGRI genome-wide association study (GWAS) catalog, in an attempt to replicate the established notion of shared pathophysiology and risk. We used pathway-based analyses to detect subsets of pleiotropic genes involved in similar biological processes. We identified 107 eligible GWAS studies related to CVD and its established comorbidities and risk factors and assigned genes that correspond to the associated signals based on their position. We found 44 positional genes shared across at least two CVD-related phenotypes that independently recreated the established relationship between the six phenotypes, but only if studies representing non-European populations were included. Seven genes revealed pleiotropy across three or more phenotypes, mostly related to lipid transport and metabolism. Yet, many genes had no relationship to each other or to genes with established functional connection. Whilst we successfully reproduced established relationships between CVD risk factors using GWAS findings, interpretation of biological pathways involved in the observed pleiotropy was limited. Further studies linking genetic variation to gene expression, as well as describing novel biological pathways will be needed to take full advantage of GWAS results.

Indexed as

Genetic PleiotropyBlack or African AmericanBlack PeopleCoronary Artery DiseaseData MiningDiabetes MellitusGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansHyperlipidemiasHypertensionKidney DiseasesObesityPolymorphism, Single NucleotideRisk FactorsUnited States

Identifiers

PMID23029515
PMCPMC3460880
OpenAlexW2077277357

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.