Induced Pluripotent Stem Cell Differentiation Enables Functional Validation of GWAS Variants in Metabolic Disease

Genome-wide association studies (GWAS) have highlighted a large number of genetic variants with potential disease association, but functional analysis remains a challenge. Here we describe an approach to functionally validate identified variants through differentiation of induced pluripotent stem cells (iPSCs) to study cellular pathophysiology. We collected peripheral blood cells from Framingham Heart Study participants and reprogrammed them to iPSCs. We then differentiated 68 iPSC lines into hepatocytes and adipocytes to investigate the effect of the 1p13 rs12740374 variant on cardiometabolic disease phenotypes via transcriptomics and metabolomic signatures. We observed a clear association between rs12740374 and lipid accumulation and gene expression in differentiated hepatocytes, in particular, expression of SORT1, CELSR2, and PSRC1, consistent with previous analyses of this variant using other approaches. Initial investigation of additional SNPs also highlighted correlations with gene expression. These findings suggest that iPSC-based population studies hold promise as tools for the functional validation of GWAS variants

Proxe: A public repository of xenografts to facilitate studies of biology and expedite preclinical drug development in leukemia and lymphoma.

To expedite the translation of biologic discoveries into novel therapeutics, there is a pressing need for panels of in vivo models that capture the molecular complexity of human disease. While traditional cell lines and genetically engineered mouse models are useful tools, they are insufficient to assess the broad diversity of human tumors within a context that recapitulates in situ biology. Patient-derived xenografts (PDXs), generated by transplanting primary human tumor cells into immune-deficient NOD.Cg-Prkdcscid/Il2rgtm1Wjl/SzJ (NSG) mice, surmount some of the limitations of these traditional platforms and have been increasingly utilized as tools for preclinical investigation. However, the infrastructure required to generate, bank, and characterize PDX models limits their availability to only a few investigators. To address this issue, we established a repository of PDX models of leukemia and lymphoma, which we have named the Public Repository of Xenografts (PRoXe). At the time of this writing, PRoXe contains 213 independent lines that have been passaged through mice once (P0), 123 of which have been repassaged in a second generation (P1) or further repassaged. The repository encompasses AML, B- and T-ALL, and B- and T-cell non-Hodgkin lymphoma (NHL) across a range of cytogenetic- and molecularly-defined subtypes (Table 1). PRoXe is extensively annotated with patient-level information, including demographics, phase of treatment, prior therapies, tumor immunophenotye, cytogenetics, and molecular diagnostics. PDX lines available for distribution are characterized by immunophenotyping, whole transcriptome sequencing (RNAseq), and targeted exon sequencing of ~300 genes. To confirm fidelity of engrafted tumors to their corresponding clinical samples, lymphomas were morphologically assessed in P0 mice by H&E and, when pathologic adjudication was required, by immunohistochemistry. Xenografted leukemias were compared to their original tumors immunophenotypically. Unsupervised hierarchical clustering was performed on 132 of these lines based on transcriptome sequencing data and demonstrated 94% concordance between classification of the PDX lines by RNA expression and by the annotated clinical-pathologic diagnoses. Discordant cases highlighted unusual variants, such as B-ALL with aberrant expression of myeloid markers and a follicular lymphoma that underwent blastic transformation in the mouse. Multiple lines have been luciferized and confirmed to home to bone marrow, spleen, and liver. Existing lines from PRoXe have already been shared with more than ten academic laboratories and multiple industrial partners. All of the data referenced here are freely available through a customized web-based search application at http://proxe.org, and lines can be requested for in vitro or in vivo experiments. We are actively expanding the size of PRoXe to allow for large pre-clinical studies that are powered to detect differences across genetically defined subsets. Thus, we are happy to host additional lines from outside investigators on PRoXe and thereby expand the availability of these valuable reagents. Finally, we have made the source code for PRoXe (in R Shiny) open-access, so that other investigators can establish their own portals