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Background: Genotype-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., Methods: First, 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., Results: After 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"., Conclusions: This 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 Registration: For the clinical dataset: Clinicaltrials.gov: NCT01257854. https://clinicaltrials.gov/ct2/history/NCT01257854., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Waespe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Human adenovirus (HAdV) is recognized as a serious pathogen after allogeneic hematopoietic stem cell transplantation (HSCT), causing morbidity and mortality. Currently, there is no universal agreement regarding routine HAdV surveillance after HSCT. We assessed the impact of HAdV weekly monitoring by polymerase chain reaction (PCR) on HAdV viremia rates and the risk factors that influence survival. Three-hundred and fifty-six pediatric allogeneic HSCT were done between 2007 and 2015. Until July 2011, HAdV testing was performed based on clinical suspicion (cohort 1, n  = 175) and from August 2011, weekly blood-HAdV monitoring was done (cohort 2, n  = 181) until day +100. Twenty-three patients (4 [2.3%] from cohort 1 and 19 [10.5%] from cohort 2, p  = .001) were found with HAdV viremia and seven of them died. Both cohorts had a similar incidence of HAdV-associated mortality (3/175; 1.7% in cohort 1 and 4/181; 2.2% in cohort 2). Respiratory failure was the cause of death in all patients. Clinical symptoms appeared prior to or within 5 days of HAdV detection in cohort 2. In summary, weekly monitoring was associated with higher detection of HAdV. The study could not assess survival benefit due to small numbers of HAdV-positive cases. In many instances, symptoms occurred with the development of positive HAdV blood PCR results and hence, symptomatology could have triggered the test. Future studies are needed to provide data that help establishing a uniform approach for regular monitoring of HAdV post-transplant.