Evidence map›Paper›PMID 38260283›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Lethal phenotypes in Mendelian disorders.

Pilar Cacheiro, Samantha Lawson, Ignatia B Van den Veyver, Gabriel Marengo, David Zocche, Stephen A Murray, Michael Duyzend, Peter N Robinson, Damian Smedley

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 6 institutions in 3 countries.

Pilar CacheiroWilliam Harvey Research Institute, Queen Mary University of London, London, UK.ORCID 0000-0002-6335-8208
Samantha LawsonITS Research, Queen Mary University of London, London, UK.ORCID 0000-0002-2563-2923
Ignatia B Van den VeyverDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.ORCID 0000-0002-0651-5924
Gabriel MarengoWilliam Harvey Research Institute, Queen Mary University of London, London, UK.ORCID 0009-0004-9420-8239
David ZoccheNorth West Thames Regional Genetics Service, Northwick Park & St Mark's Hospitals, London, UK.ORCID 0000-0003-1390-0334
Stephen A MurrayThe Jackson Laboratory, Bar Harbor, ME, USA.ORCID 0000-0002-0594-1702
Michael DuyzendMassachusetts General Hospital, Boston, MA, USA.ORCID 0000-0002-3941-6447
Peter N RobinsonBerlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0002-0736-9199
Damian SmedleyWilliam Harvey Research Institute, Queen Mary University of London, London, UK.ORCID 0000-0002-5836-9850
Queen Mary University of London · GBBaylor College of Medicine · USBerlin Institute of Health at Charité - Universitätsmedizin Berlin · DEJackson Laboratory · USMassachusetts General Hospital · USSt Mark's Hospital · GB

Funding

The Jackson Laboratory Knockout Mouse Production and Phenotyping Project (JAX KOMP2)UM1OD023222 · OD · JACKSON LABORATORY · PI ROBERT E BRAUN, Stephen A Murray · 2016 to 2026
$47.2M
Mouse Phenotyping Informatics Infrastructure - MP12UM1HG006370 · NHGRI · EUROPEAN MOLECULAR BIOLOGY LABORATORY · PI Pilar Cacheiro Martinez, Helen Elizabeth Parkinson · 2016 to 2026
$20.4M
Prenatal Genetic Diagnosis by Genomic Sequencing: A Prospective EvaluationR01HD055651 · NICHD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Wendy K Chung, Vaidehi Jobanputra · 2007 to 2026
$16.5M
Preclinical and Clincial OutcomesP50HD103555 · NICHD · BAYLOR COLLEGE OF MEDICINE · PI Sandesh Chakravarthy Sreenath Nagamani, David Loren Nelson · 2020 to 2026
$9.9M
The Human Phenotype Ontology: Accelerating Computational Integration of Clinical Data for GenomicsU24HG011449 · NHGRI · JACKSON LABORATORY · PI Peter Nicholas Robinson · 2021 to 2026
$6.7M
Increasing the Yield and Utility of Pediatric Genomic Medicine with ExomiserR01HD103805 · NICHD · JACKSON LABORATORY · PI Valentina Cipriani, CHRISTOPHER J MUNGALL · 2021 to 2026
$4.3M
Comprehensive and non-invasive prenatal screening of coding variationF32HD112084 · NICHD · MASSACHUSETTS GENERAL HOSPITAL · PI DUYZEND, MICHAEL H · 2023 to 2024
$167k
NHGRI NIH HHS U24 HG011449NHGRI NIH HHS UM1 HG006370NICHD NIH HHS F32 HD112084NICHD NIH HHS P50 HD103555NICHD NIH HHS R01 HD055651NICHD NIH HHS R01 HD103805NIH HHS UM1 OD023222
6 · The paper itself

Abstract

Essential genes are those whose function is required for cell proliferation and/or organism survival. A gene's intolerance to loss-of-function can be allocated within a spectrum, as opposed to being considered a binary feature, since this function might be essential at different stages of development, genetic backgrounds or other contexts. Existing resources that collect and characterise the essentiality status of genes are based on either proliferation assessment in human cell lines, embryonic and postnatal viability evaluation in different model organisms, and gene metrics such as intolerance to variation scores derived from human population sequencing studies. There are also several repositories available that document phenotypic annotations for rare disorders in humans such as the Online Mendelian Inheritance in Man (OMIM) and the Human Phenotype Ontology (HPO) knowledgebases. This raises the prospect of being able to use clinical data, including lethality as the most severe phenotypic manifestation, to further our characterisation of gene essentiality. Here we queried OMIM for terms related to lethality and classified all Mendelian genes into categories, according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. To showcase this curated catalogue of human essential genes, we developed the Lethal Phenotypes Portal (https://lethalphenotypes.research.its.qmul.ac.uk), where we also explore the relationships between these lethality categories, constraint metrics and viability in cell lines and mouse. Further analysis of the genes in these categories reveals differences in the mode of inheritance of the associated disorders, physiological systems affected and disease class. We highlight how the phenotypic similarity between genes in the same lethality category combined with gene family/group information can be used for novel disease gene discovery. Finally, we explore the overlaps and discrepancies between the lethal phenotypes observed in mouse and human and discuss potential explanations that include differences in transcriptional regulation, functional compensation and molecular disease mechanisms. We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.

Identifiers

PMID38260283
PMCPMC10802756
OpenAlexW4390837338

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.