Evidence map›Paper›PMID 38191623›Full record

ArticleNature communications2024

Estimating the heritability of SARS-CoV-2 susceptibility and COVID-19 severity.

Kathleen LaRow Brown, Vijendra Ramlall, Michael Zietz, Undina Gisladottir, Nicholas P Tatonetti

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  3. Review
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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.

Kathleen LaRow BrownDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.ORCID 0000-0002-6625-4156
Vijendra RamlallDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.
Michael ZietzDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.ORCID 0000-0003-0539-630X
Undina GisladottirDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.ORCID 0000-0001-5892-0852
Nicholas P TatonettiDepartment of Biomedical Informatics, Columbia University, New York, NY, USA. nicholas.tatonetti@cshs.org.ORCID 0000-0002-2700-2597

Funding

Training in Biomedical Informatics at Columbia UniversityT15LM007079 · NLM · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI NOEMIE ELHADAD, GEORGE M HRIPCSAK · 1992 to 2026
$28.9M
Precision Pharmacology and Pharmacovigilance: Leveraging AI to address drug safety knowledge gapsR35GM131905 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Nicholas P Tatonetti · 2019 to 2026
$3.3M
NIGMS NIH HHS R35 GM131905NLM NIH HHS T15 LM007079
6 · The paper itself

Abstract

SARS-CoV-2 has infected over 340 million people, prompting therapeutic research. While genetic studies can highlight potential drug targets, understanding the heritability of SARS-CoV-2 susceptibility and COVID-19 severity can contextualize their results. To date, loci from meta-analyses explain 1.2% and 5.8% of variation in susceptibility and severity respectively. Here we estimate the importance of shared environment and additive genetic variation to SARS-CoV-2 susceptibility and COVID-19 severity using pedigree data, PCR results, and hospitalization information. The relative importance of genetics and shared environment for susceptibility shifted during the study, with heritability ranging from 33% (95% CI: 20%-46%) to 70% (95% CI: 63%-74%). Heritability was greater for days hospitalized with COVID-19 (41%, 95% CI: 33%-57%) compared to shared environment (33%, 95% CI: 24%-38%). While our estimates suggest these genetic architectures are not fully understood, the shift in susceptibility estimates highlights the challenge of estimation during a pandemic, given environmental fluctuations and vaccine introduction.

Indexed as

COVID-19SARS-CoV-2Drug Delivery SystemsHospitalizationHumansPandemics

Identifiers

PMID38191623
PMCPMC10774300

What OpenQuestion holds

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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.