Evidence map›Paper›PMID 33793566›Full record

ArticlePloS one2021

Baseline cardiometabolic profiles and SARS-CoV-2 infection in the UK Biobank.

Ryan J Scalsky, Yi-Ju Chen, Karan Desai, Jeffery R O'Connell, James A Perry, Charles C Hong

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
6.9field-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

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.

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  17. The Social and Natural Environment's Impact on SARS-CoV-2 Infections in the UK Biobank.International journal of environmental research and public health · 2022
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Ryan J ScalskyMedical Scientist Training Program, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.ORCID 0000-0003-4321-1740
Yi-Ju ChenDepartment of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.
Karan DesaiDepartment of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.
Jeffery R O'ConnellDepartment of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.
James A PerryDepartment of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.ORCID 0000-0001-5050-2074
Charles C HongDepartment of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America.ORCID 0000-0002-0424-8252
University of Maryland, Baltimore · US

Funding

Medical Scientist Training ProgramT32GM092237 · NIGMS · UNIVERSITY OF MARYLAND BALTIMORE · PI ROGHMANN, MARY-CLAIRE · 2010 to 2019
$3.0M
Chemical Genetic Analysis of Vertebrate DevelopmentR01GM118557 · NIGMS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HONG, CHARLES C · 2016 to 2019
$2.0M
High-performance mixed model toolset for integrative omics analysis of big dataU01HL137181 · NHLBI · UNIVERSITY OF MARYLAND BALTIMORE · PI O'CONNELL, JEFFREY R · 2017 to 2019
$1.8M
Novel Approach to Enhance Myocardial Performance and Improve Heart Failure OutcomeR01HL135129 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HONG, CHARLES C · 2018 to 2021
$1.6M
British Heart Foundation CH/1996001/9454Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NHLBI NIH HHS R01 HL135129NHLBI NIH HHS U01 HL137181NIGMS NIH HHS R01 GM118557NIGMS NIH HHS T32 GM092237NIH HHS 1U01HL137181NIH HHS 5T32GM092237
6 · The paper itself

Abstract

backgroundSARS-CoV-2 is a rapidly spreading coronavirus responsible for the Covid-19 pandemic, which is characterized by severe respiratory infection. Many factors have been identified as risk factors for SARS-CoV-2, with much early attention being paid to body mass index (BMI), which is a well-known cardiometabolic risk factor.

objectiveThis study seeks to examine the impact of additional baseline cardiometabolic risk factors including high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), Apolipoprotein A-I (ApoA-I), Apolipoprotein B (ApoB), triglycerides, hemoglobin A1c (HbA1c) and diabetes on the odds of testing positive for SARS-CoV-2 in UK Biobank (UKB) study participants.

methodsWe examined the effect of BMI, lipid profiles, diabetes and alcohol intake on the odds of testing positive for SARS-Cov-2 among 9,005 UKB participants tested for SARS-CoV-2 from March 16 through July 14, 2020. Odds ratios and 95% confidence intervals were computed using logistic regression adjusted for age, sex and ancestry.

resultsHigher BMI, Type II diabetes and HbA1c were associated with increased SARS-CoV-2 odds (p < 0.05) while HDL-C and ApoA-I were associated with decreased odds (p < 0.001). Though the effect of BMI, Type II diabetes and HbA1c were eliminated when HDL-C was controlled, the effect of HDL-C remained significant when BMI was controlled for. LDL-C, ApoB and triglyceride levels were not found to be significantly associated with increased odds.

conclusionElevated HDL-C and ApoA-I levels were associated with reduced odds of testing positive for SARS-CoV-2, while higher BMI, type II diabetes and HbA1c were associated with increased odds. The effects of BMI, type II diabetes and HbA1c levels were no longer significant after controlling for HDL-C, suggesting that these effects may be mediated in part through regulation of HDL-C levels. In summary, our study suggests that baseline HDL-C level may be useful for stratifying SARS-CoV-2 infection risk and corroborates the emerging picture that HDL-C may confer protection against sepsis in general and SARS-CoV-2 in particular.

Indexed as

Cardiometabolic Risk FactorsAgedApolipoprotein A-IApolipoprotein B-100Biological Specimen BanksBiomarkersBody Mass IndexCholesterol, HDLCholesterol, LDLCOVID-19Diabetes Mellitus, Type 2FemaleGlycated HemoglobinHumansMaleMiddle AgedAPOA1 protein, humanAPOB protein, humanApolipoprotein A-IApolipoprotein B-100BiomarkersCholesterol, HDLCholesterol, LDLGlycated Hemoglobinhemoglobin A1c protein, humanTriglycerides

Identifiers

PMID33793566
PMCPMC8016301
OpenAlexW3142311783

What OpenQuestion holds

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LicenceCC BY
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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.