Evidence map›Paper›PMID 33763119›Full record

ArticleFrontiers in genetics2021

Genome-Wide Identification of Rare and Common Variants Driving Triglyceride Levels in a Nevada Population.

Robert W Read, Karen A Schlauch, Vincent C Lombardi, Elizabeth T Cirulli, Nicole L Washington, James T Lu, Joseph J Grzymski

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.1field-weighted citation impact, top 13% 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, 16 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

7 authors at 4 institutions in 1 country.

Robert W ReadCenter for Genomic Medicine, Desert Research Institute, Reno, NV, United States.
Karen A SchlauchCenter for Genomic Medicine, Desert Research Institute, Reno, NV, United States.
Vincent C LombardiDepartment of Microbiology and Immunology, School of Medicine, University of Nevada, Reno, Reno, NV, United States.
Elizabeth T CirulliHelix Opco, LLC., San Mateo, CA, United States.
Nicole L WashingtonHelix Opco, LLC., San Mateo, CA, United States.
James T LuHelix Opco, LLC., San Mateo, CA, United States.
Joseph J GrzymskiCenter for Genomic Medicine, Desert Research Institute, Reno, NV, United States.
Helix (United States) · USDesert Research Institute · USRenown Health · USUniversity of Nevada, Reno · US

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_QA137853
6 · The paper itself

Abstract

Clinical conditions correlated with elevated triglyceride levels are well-known: coronary heart disease, hypertension, and diabetes. Underlying genetic and phenotypic mechanisms are not fully understood, partially due to lack of coordinated genotypic-phenotypic data. Here we use a subset of the Healthy Nevada Project, a population of 9,183 sequenced participants with longitudinal electronic health records to examine consequences of altered triglyceride levels. Specifically, Healthy Nevada Project participants sequenced by the Helix Exome+ platform were cross-referenced to their electronic medical records to identify: (1) rare and common single-variant genome-wide associations; (2) gene-based associations using a Sequence Kernel Association Test; (3) phenome-wide associations with triglyceride levels; and (4) pleiotropic variants linked to triglyceride levels. The study identified 549 significant single-variant associations (

Indexed as

GWASPheWASrare variant analysistriglycerideswhole exome sequencing

Identifiers

PMID33763119
PMCPMC7982958
OpenAlexW3133838692

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.