Open AccessProceedings: Human Leukocyte Antigen Haplo‐Homozygous Induced Pluripotent Stem Cell Haplobank Modeled After the California Population: Evaluating Matching in a Multiethnic and Admixed Population
Author(s) -
Pappas Derek James,
Gourraud Pierre-Antoine,
Le Gall Caroline,
Laurent Julie,
Trounson Alan,
DeWitt Natalie,
Talib Sohel
Publication year - 2015
Publication title -
stem cells translational medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.781
H-Index - 71
eISSN - 2157-6580
pISSN - 2157-6564
DOI - 10.5966/sctm.2015-0052
Subject(s) - haplotype , population , human leukocyte antigen , induced pluripotent stem cell , biology , matching (statistics) , census , immunology , genetics , genotype , antigen , demography , medicine , gene , pathology , sociology , embryonic stem cell
Summary The development of a California‐based induced pluripotent stem cell (iPSC) bank based on human leukocyte antigen (HLA) haplotype matching represents a significant challenge and a valuable opportunity for the advancement of regenerative medicine. However, previously published models of iPSC banks have neither addressed the admixed nature of populations like that of California nor evaluated the benefit to the population as a whole. We developed a new model for evaluating an iPSC haplobank based on demographic and immunogenetic characteristics reflecting California. The model evaluates haplolines or cell lines from donors homozygous for a single HLA‐A , HLA‐B , HLA‐DRB1 haplotype. We generated estimates of the percentage of the population matched under various combinations of haplolines derived from six ancestries (black/African American, American Indian, Asian/Pacific Islander, Hispanic, and white/not Hispanic) and data available from the U.S. Census Bureau, the California Institute for Regenerative Medicine, and the National Marrow Donor Program. The model included both cis (haplotype‐level) and trans (genotype‐level) matching between a modeled iPSC haplobank and the recipient population following resampling simulations. We showed that serving a majority (>50%) of a simulated California population through cis matching would require the creation, redundant storage, and maintenance of almost 207 different haplolines representing the top 60 most frequent haplotypes from each ancestry group. Allowances for trans matching reduced the haplobank to fewer than 141 haplolines found among the top 40 most frequent haplotypes. Finally, we showed that a model optimized, custom haplobank was able to serve a majority of the California population with fewer than 80 haplolines.