Evidence map›Paper›PMID 36205462›Full record

ArticleCurrent protocols2022

Genome Reporting for Healthy Populations-Pipeline for Genomic Screening from the GENCOV COVID-19 Study.

Erika Frangione, Monica Chung, Selina Casalino, Georgia MacDonald, Sunakshi Chowdhary, Chloe Mighton, Hanna Faghfoury, Yvonne Bombard, Lisa Strug, Trevor Pugh and 7 more

Open access · greenAbstract read
In one paragraph

Article in Current protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 50% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Genomic newborn screening for rare diseases.Nature reviews. Genetics · 2023
    Review
  3. Article
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

17 authors at 9 institutions in 2 countries.

Erika FrangioneMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
Monica ChungMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
Selina CasalinoMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
Georgia MacDonaldMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
Sunakshi ChowdharyMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
Chloe MightonMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
Hanna FaghfouryUniversity Health Network, Toronto, Ontario, Canada.
Yvonne BombardUniversity of Toronto, Toronto, Ontario, Canada.
Lisa StrugThe Hospital for Sick Children, Toronto, Ontario, Canada.
Trevor PughUniversity Health Network, Toronto, Ontario, Canada.
Jared SimpsonOntario Institute for Cancer Research, Toronto, Ontario, Canada.
Limin HaoLaboratory of Molecular Medicine, Partners Personalized Medicine, Boston, Massachusetts.
Matthew LeboLaboratory of Molecular Medicine, Partners Personalized Medicine, Boston, Massachusetts.
William J LaneHarvard Medical School & Brigham and Women's Hospital, Boston, Massachusetts.
Jennifer TaherMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
Jordan Lerner-EllisMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
GENCOV Study WorkgroupMount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada.
Mount Sinai Hospital · CAOntario Institute for Cancer Research · CAUniversity of Toronto · CABrigham and Women's Hospital · USHarvard University · USHospital for Sick Children · CALunenfeld-Tanenbaum Research Institute · CAMass General Brigham · USUniversity Health Network · CA

Funding

CIHR 461170CIHR 461304CIHR VR4-172753
6 · The paper itself

Abstract

Genome sequencing holds the promise for great public health benefits. It is currently being used in the context of rare disease diagnosis and novel gene identification, but also has the potential to identify genetic disease risk factors in healthy individuals. Genome sequencing technologies are currently being used to identify genetic factors that may influence variability in symptom severity and immune response among patients infected by SARS-CoV-2. The GENCOV study aims to look at the relationship between genetic, serological, and biochemical factors and variability of SARS-CoV-2 symptom severity, and to evaluate the utility of returning genome screening results to study participants. Study participants select which results they wish to receive with a decision aid. Medically actionable information for diagnosis, disease risk estimation, disease prevention, and patient management are provided in a comprehensive genome report. Using a combination of bioinformatics software and custom tools, this article describes a pipeline for the analysis and reporting of genetic results to individuals with COVID-19, including HLA genotyping, large-scale continental ancestry estimation, and pharmacogenomic analysis to determine metabolizer status and drug response. In addition, this pipeline includes reporting of medically actionable conditions from comprehensive gene panels for Cardiology, Neurology, Metabolism, Hereditary Cancer, and Hereditary Kidney, and carrier screening for reproductive planning. Incorporated into the genome report are polygenic risk scores for six diseases-coronary artery disease; atrial fibrillation; type-2 diabetes; and breast, prostate, and colon cancer-as well as blood group genotyping analysis for ABO and Rh blood types and genotyping for other antigens of clinical relevance. The genome report summarizes the findings of these analyses in a way that extensively communicates clinically relevant results to patients and their physicians. © 2022 Wiley Periodicals LLC. Basic Protocol 1: HLA genotyping and disease association Basic Protocol 2: Large-scale continental ancestry estimation Basic Protocol 3: Dosage recommendations for pharmacogenomic gene variants associated with drug response Support Protocol: System setup.

Indexed as

Blood Group AntigensCOVID-19Computational BiologyGenomicsHumansMaleSARS-CoV-2Blood Group AntigensbioinformaticsCOVID-19genome reportinggenomicsnext generation sequencing (NGS)

Identifiers

PMID36205462
PMCPMC9874607
OpenAlexW4303423400

What Socratic holds

Textmetadata
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 Socratic graph.