Evidence map›Paper›PMID 39632930›Full record

ArticleScientific reports2024

Identification of rare disease genes as drivers of common diseases through tissue-specific gene regulatory networks.

Olivier B Bakker, Annique Claringbould, Harm-Jan Westra, Henry Wiersma, Floranne Boulogne, Urmo Võsa, Carlos G Urzúa-Traslaviña, Sophie Mulcahy Symmons, Mahmoud M M Zidan, Marie C Sadler and 4 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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
–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

3 citing papers in PubMed.

  1. Article
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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

14 authors.

Olivier B Bakker *Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Annique Claringbould *Structural and Computational Biology Unit, EMBL, Heidelberg, Germany.
Harm-Jan WestraDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Henry WiersmaDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Floranne BoulogneDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Urmo VõsaEstonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Carlos G Urzúa-TraslaviñaDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Sophie Mulcahy SymmonsDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Mahmoud M M ZidanDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Marie C SadlerUniversity Center for Primary Care and Public Health, 1010, Lausanne, Switzerland.
Zoltán KutalikUniversity Center for Primary Care and Public Health, 1010, Lausanne, Switzerland.
Iris H JonkersDepartment of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Lude Franke *Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. l.h.franke@umcg.nl.
Patrick Deelen *Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. p.deelen@umcg.nl.

Funding

European Research Council 637640Nederlandse Organisatie voor Wetenschappelijk Onderzoek 016.171.047Nederlandse Organisatie voor Wetenschappelijk Onderzoek 9150161910057Nederlandse Organisatie voor Wetenschappelijk Onderzoek 917.14.374Nierstichting 18OKG19
6 · The paper itself

Abstract

Genetic variants identified through genome-wide association studies (GWAS) are typically non-coding, exerting small regulatory effects on downstream genes. However, which downstream genes are ultimately impacted and how they confer risk remains mostly unclear. By contrast, variants that cause rare Mendelian diseases are often coding and have a more direct impact on disease development. Here we demonstrate that common and rare genetic diseases can be linked by studying how common disease-associated variants influence gene co-expression in 57 different tissues and cell types. We implemented this method in a framework called Downstreamer and applied it to 88 GWAS traits. We find that predicted downstream "genes" are enriched with Mendelian disease genes, e.g. key genes for height are enriched for genes that cause skeletal abnormalities and Ehlers-Danlos syndromes. 78% of these key genes are located outside of GWAS loci, suggesting that they result from complex trans regulation rather than being impacted by disease-associated variants in cis. Based on our findings, we discuss the challenges in reconstructing gene regulatory networks and provide a roadmap to improve the identification of these highly connected genes linked to common traits and diseases.

Indexed as

Gene Regulatory NetworksGenetic Predisposition to DiseaseGenome-Wide Association StudyRare DiseasesHumansOrgan SpecificityPolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID39632930
PMCPMC11618476

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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.