Trial reportPloS one2023
A novel integrative multi-omics approach to unravel the genetic determinants of rare diseases with application in sinusoidal obstruction syndrome.
Trial report in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01257854 (Polymorphisms and Busulfan Pharmacokinetic Study in Pediatric Transplnatation), which is not on this map. Cited by 1 paper.
What it found
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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.
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.
Polymorphisms and Busulfan Pharmacokinetic Study in Pediatric Transplnatation
Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Machine Learning and Experiments Revealed Key Genes Related to PANoptosis Linked to Drug Prediction and Immune Landscape in Spinal Cord Injury.Molecular neurobiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenotype-phenotype analyses of rare diseases often suffer from a lack of power, due to small sample size, which makes identifying significant associations difficult. Sinusoidal obstruction syndrome (SOS) of the liver is a rare but life-threatening complication of hematopoietic stem cell transplantation (HSCT). The alkylating agent busulfan is commonly used in HSCT and known to trigger SOS. We developed a novel pipeline to identify genetic determinants in rare diseases by combining in vitro information with clinical whole-exome sequencing (WES) data and applied it in SOS patients and controls.
methodsFirst, we analysed differential gene expression in six lymphoblastoid cell lines (LCLs) before and after incubation with busulfan. Second, we used WES data from 87 HSCT patients and estimated the association with SOS at the SNP and the gene levels. We then combined the results of the expression and the association analyses into an association statistic at the gene level. We used an over-representation analysis to functionally characterize the genes that were associated with a significant combined test statistic.
resultsAfter treatment of LCLs with busulfan, 1708 genes were significantly up-, and 1385 down-regulated. The combination of the expression experiment and the association analysis of WES data into a single test statistic revealed 35 genes associated with the outcome. These genes are involved in various biological functions and processes, such as "Cell growth and death", "Signalling molecules and interaction", "Cancer", and "Infectious disease".
conclusionsThis novel data analysis pipeline integrates two independent omics datasets and increases statistical power for identifying genotype-phenotype associations. The analysis of the transcriptomics profile of cell lines treated with busulfan and WES data from HSCT patients allowed us to identify potential genetic contributors to SOS. Our pipeline could be useful for identifying genetic contributors to other rare diseases where limited power renders genome-wide analyses unpromising.
trial registrationFor the clinical dataset: Clinicaltrials.gov: NCT01257854. https://clinicaltrials.gov/ct2/history/NCT01257854.
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Registered trials
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.