Evidence map›Paper›PMID 39259723›Full record

ArticlePLoS genetics2024

Evolutionary rate covariation is pervasive between glycosylation pathways and points to potential disease modifiers.

Holly J Thorpe, Raghavendran Partha, Jordan Little, Nathan L Clark, Clement Y Chow

Abstract read
In one paragraph

Article in PLoS genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Holly J ThorpeDepartment of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah, United States of America.ORCID https://orcid.org/0000-0003-2136-0235
Raghavendran ParthaDepartment of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.ORCID https://orcid.org/0000-0002-7900-4375
Jordan LittleDepartment of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah, United States of America.ORCID https://orcid.org/0000-0002-8590-9357
Nathan L ClarkDepartment of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Clement Y ChowDepartment of Human Genetics, University of Utah School of Medicine, Salt Lake City, Utah, United States of America.ORCID https://orcid.org/0000-0002-3104-7923

Funding

Title: Functional Annotation of Genomes via Phenotypic Convergence within Large Multi-species AlignmentsR01HG009299 · NHGRI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Maria D Chikina, Nathaniel L Clark · 2017 to 2026
$4.1M
Investigating the impact of genetic variation on the ER stress response, protein folding, and diseaseR35GM124780 · NIGMS · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Clement Chow · 2017 to 2026
$4.0M
University of Utah Interdisciplinary Training Program in Computational Approaches to Diabetes and Metabolism ResearchT32DK110966 · NIDDK · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck, Marcus Guy Pezzolesi · 2016 to 2026
$2.6M
NHGRI NIH HHS R01 HG009299NIDDK NIH HHS T32 DK110966NIGMS NIH HHS R35 GM124780
6 · The paper itself

Abstract

Mutations in glycosylation pathways, such as N-linked glycosylation, O-linked glycosylation, and GPI anchor synthesis, lead to Congenital Disorders of Glycosylation (CDG). CDG typically present with seizures, hypotonia, and developmental delay but display large clinical variability with symptoms affecting every system in the body. This variability suggests modifier genes might influence the phenotypes. Because of the similar physiology and clinical symptoms, there are likely common genetic modifiers between CDG. Here, we use evolution as a tool to identify common modifiers between CDG and glycosylation genes. Protein glycosylation is evolutionarily conserved from yeast to mammals. Evolutionary rate covariation (ERC) identifies proteins with similar evolutionary rates that indicate shared biological functions and pathways. Using ERC, we identified strong evolutionary rate signatures between proteins in the same and different glycosylation pathways. Genome-wide analysis of proteins showing significant ERC with GPI anchor synthesis proteins revealed strong signatures with ncRNA modification proteins and DNA repair proteins. We also identified strong patterns of ERC based on cellular sub-localization of the GPI anchor synthesis enzymes. Functional testing of the highest scoring candidates validated genetic interactions and identified novel genetic modifiers of CDG genes. ERC analysis of disease genes and biological pathways allows for rapid prioritization of potential genetic modifiers, which can provide a better understanding of disease pathophysiology and novel therapeutic targets.

Indexed as

Congenital Disorders of GlycosylationEvolution, MolecularAnimalsGlycosylationGlycosylphosphatidylinositolsHumansMutationPhenotypeGlycosylphosphatidylinositols

Identifiers

PMID39259723
PMCPMC11419382

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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.