Modeling rare genetic disease with patient-derived induced pluripotent stem cells: reassessment of the minimum numbers of lines needed.

Induced pluripotent stem cells (iPSCs) are widely used to model human genetic diseases. The most common strategy involves collecting cells from relevant individuals and then reprogramming them into iPSCs. This strategy is very powerful, but finding enough individuals with a specific genetic disease can be challenging, especially since most are rare. In addition, making numerous iPSC lines is time-consuming and expensive. As a result, most studies have included relatively small numbers of iPSC lines, sometimes from the same individual. Considering the experimental variability obtained using different iPSC lines, there has been great interest in delineating the most efficient number of lines needed to achieve a robust and reproducible result. Several recommendations have been published, although most conclusions have been based on methods where experimental variance from individual cases is difficult to separate from technical issues related to the preparation of iPSCs. The current study used gene expression profiles determined by RNA sequencing (RNAseq) to empirically evaluate the impact of the number of unique individuals and the number of replicate iPSC lines from each individual for modeling Lesch-Nyhan disease (LND). This disease is caused by mutations in the HPRT1 gene, which encodes the enzyme hypoxanthine-guanine phosphoribosyltransferase. Results for detecting disease-relevant changes in gene expression depended on the analytical method employed, and whether or not statistical procedures were used to address multiple iPSC lines from the same individual. In keeping with prior studies, the best results were obtained with iPSC lines from 3-4 unique individuals per group. In contrast to prior studies, results were improved with 2 lines per individual, without statistical corrections for duplicate lines from the same individual. In the current study where all lines were produced in parallel using the same methods, most variance in gene expression came from technical factors unrelated to the individual from whom the iPSC lines were prepared.