Whole Genome Association Analysis of Hematopoietic Cell Transplant Outcome

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DESCRIPTION (provided by applicant): Previous studies have demonstrated that allogeneic hematopoietic cell transplant (HCT) outcome may be affected by genetic variation. The goals of the studies proposed in this research project are to characterize by genome-wide association analysis the donor and recipient genetic components responsible for these differences. Specific objectives are to identify genotypes that affect the risks of the clinically significant post-transplant complications and syndromes including acute and chronic GHVD, liver and renal toxicity, pulmonary syndromes, bacterial, viral and fungal infections, and also the genetic factors that affect the development of immunological tolerance. The HCT population proposed for this study represents a relatively large number of patients who have undergone intense protocol-controlled therapy in a structured environment with detailed monitoring and recording of critical data. The dataset is rich in clinically relevant phenotypes. The complications that are the subject of this study affect morbidity and mortality, and they have over the years proven to represent informative model systems of disease relevant to populations other than HCT recipients. A unique feature of this HCT study is the opportunity to analyze both patient and donor genotype, and the effect this interaction has on disease phenotype and transplant outcome. The first aim is to perform a whole genome scan of single nucleotide polymorphisms (SNP) in a cohort consisting of 1,000 HCT cases (patient-donor pairs, 2,000 samples), randomly selected from a larger population of patients transplanted according to uniform protocols at a single Center. The primary phenotype-defined transplant outcomes are acute GVHD, chronic GVHD, HCT-related airflow obstruction (AFO) and immunological tolerance. Secondary phenotypes include idiopathic pneumonia syndrome, acute liver disease, impaired renal function and infections diseases (bacterial, viral and fungal). The second specific aim is to apply critical bioinformatics tools and innovative statistical methods to the analysis of whole genome data and HCT outcomes, and determine interactions between different genes and between donor and recipient genetic variants. We propose a 3-stage approach to defining genetic polymorphism and identifying functional variants. First, genomic variation will be defined in transplant patients and donors. The second stage will explore genetic associations (SNPs/Haplotypes) with complex phenotypes, analyzing associations of genes and gene-gene interactions with time-to-event phenotypes and quantitative traits. The third stage will explore genome-genome interactions between recipient and donor.