Combined genomic transplant and pharmacogenomic risk assessment for pediatric renal patients using Oxford Nanopore Adaptive Sampling

Aim: Transplantation is a life-saving therapy but carries major risks including rejection, graft-versus-host disease, infection, and malignancy, that can lead to graft failure or death. These complications stem from interactions between the recipient’s immune system and the graft, necessitating lifelong immunosuppression. Individual variability in drug metabolism can influence efficacy and toxicity. Pharmacogenomics (PGx), which links genetic profiles to drug response, enables therapy optimization for safety and effectiveness. Whereas traditional pre-transplant testing focuses on 11 HLA genes, modern technologies now allow assessment of many more loci relevant to transplant outcomes, including PGx variants.
Methods: Using Oxford Nanopore Technology’s (ONT) adaptive sampling, we developed a comprehensive transplant and PGx risk assessment panel. This proof-of-principle assay requires no DNA preamplification, enrichment, or enzymatic conversion and enriches 280 genomic regions of interest (ROIs), including the full HLA locus (5.5 Mb), immune cell receptor (ICR) and inborn errors of immunity (IEI) genes, 50 ISBT blood group genes, and 125 non-HLA PGx loci (22 currently actionable). Having shown concordance for HLA, ABO, and FUT typing with gold standard assays (Grasedieck et al., Hum Immunol, 2026), we integrated simultaneous PGx profiling for a unified workflow. A pilot cohort of 12 pediatric samples with suspected tacrolimus (TAC) metabolism abnormalities and available TAC pharmacokinetic (PK) data (AUC/C0 ratio and AUC30 dosing in mg/m²/dose) was analyzed.
Results: The all-in-one test achieved up to 370× (median ~250×) ROI coverage within four days, producing high-quality data for small and structural variant calling, allele phasing, HLA and blood group typing (GenDx, RBCeq2), DNA methylation in all ROIs, and whole-genome copy number analysis (Epi2me). Variants for 26 CPIC Level-A PGx star alleles were interpreted using PharmCAT, including key TAC-related CYP3A51/3/6/7 and CYP3A4*22, allowing phenotype confirmation and dose recommendations. Ongoing analyses target additional TAC metabolism genes (ABCB1, ABCC2, POR) using CytoPGx or manual star allele assignment to better predict TAC clearance, AUC/C0 ratios, and dosing needs. A unified algorithm to infer common and rare TAC PGx alleles is under development.
Conclusion: We demonstrate proof-of-concept for an integrated, rapid genomic assay enabling polygenic prediction of transplant outcomes and pharmacogenomic variants with PK confirmation. This approach advances precision medicine by enhancing drug optimization, reducing healthcare costs, and improving quality of life for transplant recipients.