Advancing deep variant phenotyping of mitochondrial enzyme complexes for precision medicine in allogeneic hematopoietic stem-cell transplantation

Abstract

Allogeneic hematopoietic stem-cell transplantation (allo-HCT), an early developed methodology for precision medicine, remains the only curative therapy for myelodysplastic syndromes (MDS). However, allo-HCT carries significant risks of morbidity and mortality due to relapse and transplant-related complications. Recurrent mutations in mitochondrial DNA (mtDNA) have been identified as significant prognostic indicators for MDS outcomes following allo-HCT. However, the biological mechanisms of mtDNA mutations remain unclear. Thus, here we performed deep variant phenotyping by integrating computational biophysics and structural genomics approaches to reveal the molecular mechanisms underlying mtDNA variant dysfunction. This emerging genomics discipline employs structural models, molecular mechanic calculations, and accelerated molecular dynamic simulations to analyze gene products, focusing on their structures and motions that determine their function. We applied this methodology on the variants in the mitochondria-encoded complex I genes that are associated with MDS pathobiology and prognosis after allo-HCT. Our results demonstrate that this approach significantly outperforms conventional analytical methods, providing enhanced and more accurate information to support the potential pathogenicity of these variants and better infer their dysfunctional mechanisms. We conclude that the adoption and further expansion of computational structural genomics approaches, as applied to the mitochondrial genome, have the potential to significantly increase our understanding of molecular mechanisms underlying the disease. Our study lays a foundation for translating mitochondrial biology into clinical applications, which will advance the integration of precision medicine with allo-HCT.