A Primer on Chimerism Analysis: A Straightforward, Thorough Review.

Short tandem repeat (STR) analysis to assess chimerism is a critical aspect of routine care particularly in patients facing stem cell transplants but is also relevant in other clinical scenarios. STR analysis provides a means to assess donor and recipient cellular origins in a patient, and, as such, can inform engraftment, rejection, and relapse status in stem cell transplant recipients. In this review of STR testing, the most commonly used method to assess chimerism, its background, procedural details, and clinical utility are discussed.

The utility of imputation for molecular mismatch analysis in solid organ transplantation.

HLA genotyping has undergone a rapid progression in resolution since the development of DNA-based typing methods. Despite the advent of high-resolution next-generation sequencing, the bulk of solid organ genotyping is performed at intermediate resolution, which provides multiple possible two-field results for each classical HLA loci. As a result, several methodologies have been developed to impute the most likely allele-level (two-field) HLA genotype for the purposes of donor-recipient compatibility analysis. The advent of molecular mismatch analysis, however, has placed a new emphasis on the accuracy of imputation. While seminal molecular mismatch studies have relied on the imputation of intermediate resolution genotyping, several recent studies have performed analysis showing that imputation generates inaccuracies in epitope identification. While the clinical impact of these errors is not clear, it is important that these concerns do not preclude future progress in understanding the utility of molecular mismatch analysis in transplantation. In the future, advances in genotyping methods will result in routine two-field resolution that will abrogate these concerns. In the meantime, however, studies are needed in order to address the role of molecular mismatch in diverse patient populations and to carefully address the potential of molecular mismatch analysis in the context of imputation.

hlaR: A rapid and reproducible tool to identify eplet mismatches between transplant donors and recipients.

Eplet mismatch load, both overall and at the single molecule level, correlates with transplant recipient outcomes. However, precise eplet assessment requires high-resolution HLA typing of both the donor and recipient. Anything less than high-resolution typing requires imputation of HLA types. The currently available methods to identify eplet mismatch are both tedious and demanding. Therefore, we developed a software package and user-friendly web application (hlaR), that simplifies the workflow of eplet analysis, provides functions to impute high-resolution from low-resolution data and calculates both overall and single molecule eplet mismatch for single or multiple donor recipient pairs. Compared to manual assessments using currently available tools (namely, HLAMatchMaker), hlaR resulted in only minimal discrepancy in eplet mismatches (mean absolute difference of 0.56 for class I and 0.86 for class II for unique sum across loci). Additionally, output of the single molecule eplet function compared well to manual calculation, with an average single antigen count increase of 0.19. Importantly, the hlaR tool permits rapid and reproducible imputation and eplet mismatch including comparison between eplet reference tables (e.g. HLAMatchMaker version 2 or 3). Users can import data from a spreadsheet rather than relying on keystroke entry of individual donor and recipient data, thus reducing the risk of data entry errors. The resulting improved scalability of the hlaR tool is highlighted by plotting analysis time against the size of the input dataset. The new hlaR tool can provide eplet mismatch data with a streamlined workflow. With decreased effort from the end user, eplet matching and mismatch load data can be further incorporated into both research and clinical use.