iGeneTRAiN awarded a U01 from NIH/NIAID for MHC and KIR sequencing

iGeneTRAiN awarded a U01 from NIH/NIAID for MHC and KIR sequencing

Oct 09, 2020

iGeneTRAiN investigators have been awarded a U01 grant from the NIAID/NIH “MHC and KIR Sequencing and Association Analyses in the iGeneTRAiN Studies”. (PD/PI Brendan Keating – contact bkeating@upenn.edu)

HLA donor-recipient (D-R) matching is critical for graft outcomes following Kidney, Heart, Lung and hematopoietic cell transplantation. Genetic association studies in large well-characterized transplant cohorts are lacking and there is a clear need to characterize how MHC and KIR genetic variants underpin transplantation outcomes. The International Genetics & Translational Research in Transplantation Network (iGeneTRAiN) was formed to increase the understanding of the genetic architecture of transplant outcomes, by bringing together transplantation studies with genome-wide association study (GWAS) datasets from >52,600 recipients/donors across well-curated heart, kidney, liver and lung transplant phenotype datasets. This constitutes the largest solid-organ transplant consortium ever assembled. We are sequencing key HLA Class I and II loci in the majority of iGeneTRAiN studies, and additional MHC/KIR regions in subsets of studies, are facilitating ample statistical power to assess association studies of MHC and KIR with key transplant-related outcomes. A large portion of the iGeneTRAiN database is derived from non-European ancestry samples, which greatly addresses the lack of adequate MHC/KIR genetic data in these populations.

Public Health Relevance: Our overarching aim of this grant is to accelerate the discovery of MHC and KIR genetic variants underpinning transplant-related phenotypes/outcomes. To achieve this we are using complementary genomic approaches (short-read and amplicon-based HLA Class I/II second generation sequencing, and long-read sequencing approaches). We are also employing a number of innovative analyses pipelines to maximize the associative potential of very large genetic (genotyping and sequencing) and phenotypic datasets that are derived from well-curated solid organ samples.

Posted on: October 9, 2020, by :
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