Evidence map›Paper›PMID 39237660›Full record

ArticleScientific reports2024

Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT.

Jumamurat R Bayjanov, Cenna Doornbos, Ozan Ozisik, Woosub Shin, Núria Queralt-Rosinach, Daphne Wijnbergen, Jean-Sébastien Saulnier-Blache, Joost P Schanstra, Bénédicte Buffin-Meyer, Julie Klein and 5 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
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

15 authors.

Jumamurat R BayjanovDepartment of Medical BioSciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Cenna DoornbosDepartment of Medical BioSciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Ozan OzisikAix Marseille Univ, INSERM, MMG, Marseille, France.
Woosub ShinDepartment of Bioinformatics-BiGCaT, NUTRIM/MHeNs, Maastricht University, Maastricht, The Netherlands.
Núria Queralt-RosinachDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Daphne WijnbergenDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Jean-Sébastien Saulnier-BlacheInstitut National de la Santé et de la Recherche Médicale (INSERM), U1297, Institute of Cardiovascular and Metabolic Disease, Toulouse, France.
Joost P SchanstraInstitut National de la Santé et de la Recherche Médicale (INSERM), U1297, Institute of Cardiovascular and Metabolic Disease, Toulouse, France.
Bénédicte Buffin-MeyerInstitut National de la Santé et de la Recherche Médicale (INSERM), U1297, Institute of Cardiovascular and Metabolic Disease, Toulouse, France.
Julie KleinInstitut National de la Santé et de la Recherche Médicale (INSERM), U1297, Institute of Cardiovascular and Metabolic Disease, Toulouse, France.
José M FernándezBarcelona Supercomputing Center (BSC), Barcelona, Spain.
Rajaram KaliyaperumalDepartment of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
Anaïs BaudotAix Marseille Univ, INSERM, MMG, Marseille, France.
Peter A C 't HoenDepartment of Medical BioSciences, Radboud University Medical Centre, Nijmegen, The Netherlands.
Friederike EhrhartDepartment of Bioinformatics-BiGCaT, NUTRIM/MHeNs, Maastricht University, Maastricht, The Netherlands. friederike.ehrhart@maastrichtuniversity.nl.

Funding

Agence de la Biomédecine METAPhOR projectEuropean Commission Seventh Framework Programme (FP7/2007-2013) 305608European Union's Horizon 2020 research and innovation programme EJP RD COFUND-EJP N° 825575Fondation pour la Recherche Médicale DEQ20170336759Programme Hospitalier de Recherche Clinique N° 10 138 01-N° RCB 2010-AO1151-38
6 · The paper itself

Abstract

Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) is the leading cause of childhood chronic kidney failure and a significant cause of chronic kidney disease in adults. Genetic and environmental factors are known to influence CAKUT development, but the currently known disease mechanism remains incomplete. Our goal is to identify affected pathways and networks in CAKUT, and thereby aid in getting a better understanding of its pathophysiology. With this goal, the miRNome, peptidome, and proteome of over 30 amniotic fluid samples of patients with non-severe CAKUT was compared to patients with severe CAKUT. These omics data sets were made findable, accessible, interoperable, and reusable (FAIR) to facilitate their integration with external data resources. Furthermore, we analysed and integrated the omics data sets using three different bioinformatics strategies: integrative analysis with mixOmics, joint dimensionality reduction and pathway analysis. The three bioinformatics analyses provided complementary features, but all pointed towards an important role for collagen in CAKUT development and the PI3K-AKT signalling pathway. Additionally, several key genes (CSF1, IGF2, ITGB1, and RAC1) and microRNAs were identified. We published the three analysis strategies as containerized workflows. These workflows can be applied to other FAIR data sets and help gaining knowledge on other rare diseases.

Indexed as

CollagenPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktSignal TransductionAmniotic FluidComputational BiologyFemaleHumansMicroRNAsMultiomicsProteomeUrinary TractUrogenital AbnormalitiesVesico-Ureteral RefluxCollagenMicroRNAsPhosphatidylinositol 3-KinasesProteomeProto-Oncogene Proteins c-akt

Identifiers

PMID39237660
PMCPMC11377713

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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.