Genomic Studies in Blood and Marrow Transplantation (GS-BMT): An NCI-CIBMTR genomic medicine initiative in hematopoietic cell transplantation
- 1Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
Abstract
Background: Genomic studies in hematopoietic cell transplantation (HCT) are limited by sample sizes and targeted approaches. Methods: The Genomic Studies in Blood and Marrow Transplantation (GS-BMT) project is a collaboration between the National Cancer Institute (NCI) and the CIBMTR designed to investigate recipient and donor determinants of HCT outcomes. We are generating genome-wide SNP-array genotyping for all samples, and sequencing and methylation profiling for selected subsets. We report study design and cohort characteristics and present two proof-of-concept analyses: comparison of conventional and machine learning prediction of overall survival after HCT in 9,262 patients with acute myeloid leukemia (AML), and assessment of inherited susceptibility to clonal hematopoiesis of indeterminate potential (CHIP) among 19,750 HCT donors using polygenic scores (PGS). Results: GS-BMT includes 30,718 donor-recipient pairs who received allogeneic HCT in the United States between 2000 and 2019. In AML, clinical variables alone provided modest prediction for post-transplant survival, with similar performance for Cox proportional hazards, random survival forest, and deep neural network survival models (C-index=0.63, 0.62, and 0.62, respectively). In donors, CHIP-PGS did not differ by age (p=0.76) but was modestly lower in unrelated vs. related donors (-0.06 standard deviation [SD]; p=0.002). In an illustrative analysis assuming risk of event increases by 50% or 80% per PGS-SD, the top 5.2% and 12.3% of the donors, respectively, would have at least twice the risk of a donor with the average PGS. Conclusions: GS-BMT establishes a large genomic platform aiming to improve individualized risk prediction, donor selection, and precision medicine in HCT.
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BibTeX
@misc{gadalla2026genomic,
title = {{Genomic Studies in Blood and Marrow Transplantation (GS-BMT): An NCI-CIBMTR genomic medicine initiative in hematopoietic cell transplantation}},
author = {S. M. Gadalla and N. Lee and X. Wu and F. Pirsl and G. Schmidt and M. Rafati and A. Hutchinson and A. Vogt and B. Hicks and J. Liu and J. Wang and S. Gaddam and S. Li and W. Saber and S. Chanock and P. Kraft and S. A. Savage and H. G. Hong and S. R. Spellman},
howpublished = {medRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.06.26367367},
url = {https://www.medrxiv.org/content/10.64898/2026.11.06.26367367v1},
note = {CC0},
}
RIS
TY - UNPB
TI - Genomic Studies in Blood and Marrow Transplantation (GS-BMT): An NCI-CIBMTR genomic medicine initiative in hematopoietic cell transplantation
AU - S. M. Gadalla
AU - N. Lee
AU - X. Wu
AU - F. Pirsl
AU - G. Schmidt
AU - M. Rafati
AU - A. Hutchinson
AU - A. Vogt
AU - B. Hicks
AU - J. Liu
AU - J. Wang
AU - S. Gaddam
AU - S. Li
AU - W. Saber
AU - S. Chanock
AU - P. Kraft
AU - S. A. Savage
AU - H. G. Hong
AU - S. R. Spellman
PY - 2026
DA - 2026/11/06
PB - medRxiv
DO - 10.64898/2026.11.06.26367367
UR - https://www.medrxiv.org/content/10.64898/2026.11.06.26367367v1
AB - Background: Genomic studies in hematopoietic cell transplantation (HCT) are limited by sample sizes and targeted approaches. Methods: The Genomic Studies in Blood and Marrow Transplantation (GS-BMT) project is a collaboration between the National Cancer Institute (NCI) and the CIBMTR designed to investigate recipient and donor determinants of HCT outcomes. We are generating genome-wide SNP-array genotyping for all samples, and sequencing and methylation profiling for selected subsets. We report study design and cohort characteristics and present two proof-of-concept analyses: comparison of conventional and machine learning prediction of overall survival after HCT in 9,262 patients with acute myeloid leukemia (AML), and assessment of inherited susceptibility to clonal hematopoiesis of indeterminate potential (CHIP) among 19,750 HCT donors using polygenic scores (PGS). Results: GS-BMT includes 30,718 donor-recipient pairs who received allogeneic HCT in the United States between 2000 and 2019. In AML, clinical variables alone provided modest prediction for post-transplant survival, with similar performance for Cox proportional hazards, random survival forest, and deep neural network survival models (C-index=0.63, 0.62, and 0.62, respectively). In donors, CHIP-PGS did not differ by age (p=0.76) but was modestly lower in unrelated vs. related donors (-0.06 standard deviation [SD]; p=0.002). In an illustrative analysis assuming risk of event increases by 50% or 80% per PGS-SD, the top 5.2% and 12.3% of the donors, respectively, would have at least twice the risk of a donor with the average PGS. Conclusions: GS-BMT establishes a large genomic platform aiming to improve individualized risk prediction, donor selection, and precision medicine in HCT.
ER -