In kidney transplantation, precision medicine has already entered clinical practice. Donor and recipient human leucocyte antigen (HLA) regions are genotyped in two class 1 and usually three class 2 loci, and the individual degree of sensitization against alloimmune antigens is evaluated by the detection of anti-HLA donor-specific antibodies. Recently, the contribution of non-HLA mismatches to outcomes such as acute T- and B-cell-mediated rejection and even long-term graft survival was described. Tracking of specific alloimmune T- and B-cell clones by next generation sequencing and refinement of the immunogenicity of allo-epitopes specifically in the interaction with HLA and T- and B-cell receptors may further support individualized therapy. Although the choices of maintenance immunosuppression are rather limited, individualization can be accomplished by adjustment of dosing based on these risk predictors. Finally, supplementing histopathology by a transcriptomics analysis allows for a biological interpretation of the histological findings and avoids interobserver variability of results. In contrast to transplantation, the prescription of hemodialysis therapy is far from precise. Guidelines do not consider modifications by age, diet or many comorbid conditions. Patients with residual kidney function routinely receive the same treatment as those without. A major barrier hitherto is the definition of 'adequate' treatment based on urea removal. Kt/Vurea and related parameters neither reflect the severity of uremic symptoms nor predict long-term outcomes. Urea is poorly representative for numerous other compounds that accumulate in the body when the kidneys fail, yet clinicians prescribe treatment based on its measurement. Modern technology has provided the means to identify other solutes responsible for specific features of uremic illness and their measurement will be a necessary step in moving beyond the standardized prescription of hemodialysis.
Keywords: genomics; hemodialysis; kidney transplantation; precision medicine; urea modeling.
© The Author(s) 2021. Published by Oxford University Press on behalf of ERA-EDTA.