Evidence map›Paper›PMID 35168826›Full record

ArticleNutrition, metabolism, and cardiovascular diseases : NMCD2022

Identification of genetic loci simultaneously associated with multiple cardiometabolic traits.

Alexis C Wood, Amit Arora, Michelle Newell, Victoria L Bland, Jin Zhou, Nicola Pirastu, Jose M Ordovas, Yann C Klimentidis

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PubMed Full text at PMC Publisher
In one paragraph

Article in Nutrition, metabolism, and cardiovascular diseases : NMCD, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
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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

8 authors.

Alexis C WoodUSDA/ARS Children's Nutrition Research Center, 1100 Bates Avenue, Houston, TX, USA. Electronic address: lekkiwood@gmail.com.
Amit AroraDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA.
Michelle NewellDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA.
Victoria L BlandDivision of Geriatric Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Jin ZhouDepartment of Biostatistics, University of California, Los Angeles, CA, USA.
Nicola PirastuCentre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, Scotland, UK.
Jose M OrdovasNutrition and Genomics Laboratory, Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA; IMDEA-Food, Madrid, Spain.
Yann C KlimentidisDepartment of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA; BIO5 Institute, University of Arizona, Tucson, AZ, USA.

Funding

Genomics, GPUs, and Next Generation Computational StatisticsR01HG006139 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SOBEL, ERIC · 2011 to 2023
$5.1M
Genetics at the Interface of Lipid and Glycemic TraitsR01HL136528 · NHLBI · UNIVERSITY OF ARIZONA · PI KLIMENTIDIS, YANN CHARLES · 2018 to 2020
$1.1M
Overcoming Obstacles in Epigenetic Analysis of Human TwinsR21HD087860 · NICHD · BAYLOR COLLEGE OF MEDICINE · PI WATERLAND, ROBERT A, WOOD, ALEXIS CAROLINE · 2016 to 2017
$389k
NHGRI NIH HHS R01 HG006139NHLBI NIH HHS R01 HL136528NICHD NIH HHS R21 HD087860
6 · The paper itself

Abstract

BACKGROUND AND

aimsCardiometabolic disorders (CMD) arise from a constellation of features such as increased adiposity, hyperlipidemia, hypertension and compromised glucose control. Many genetic loci have shown associations with individual CMD-related traits, but no investigations have focused on simultaneously identifying loci showing associations across all domains. We therefore sought to identify loci associated with risk across seven continuous CMD-related traits. METHODS AND

resultsWe conducted separate genome-wide association studies (GWAS) for systolic and diastolic blood pressure (SBP/DBP), hemoglobin A1c (HbA1c), low- and high- density lipoprotein cholesterol (LDL-C/HDL-C), waist-to-hip-ratio (WHR), and triglycerides (TGs) in the UK Biobank (N = 356,574-456,823). Multiple loci reached genome-wide levels of significance (N = 145-333) for each trait, but only four loci (in/near VEGFA, GRB14-COBLL1, KLF14, and RGS19-OPRL1) were associated with risk across all seven traits (P < 5 × 10

conclusionsOur analyses suggest that very few loci are associated in the same direction of risk with traits representing the full spectrum of CMD features. We identified four such loci, and an understanding of the pathways between these loci and CMD risk may eventually identify factors that can be used to identify pathologic disturbances that represent broadly beneficial therapeutic targets.

Indexed as

Genome-Wide Association StudyHypertensionAdiposityCholesterol, HDLGenetic LociHumansPolymorphism, Single NucleotideWaist-Hip RatioCholesterol, HDLCardiometabolic diseaseEpidemiologyFat distributionGWASPleiotropyRisk allelesRisk factors

Identifiers

PMID35168826
PMCPMC9275655

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Registered trials

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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.