Endocrine Abstracts

Ornithine transcarbamylase deficiency (OTCD) is the most common urea cycle disorder (UCD) with a prevalence of one in 60-70,000 in humans. It is mainly caused by mutations in the OTC gene, which encodes the enzyme ornithine transcarbamylase. Patients with OTCD present disturbed urea cycle function and ammonia accumulation in the bloodstream, downstream leading to a range of symptoms, including developmental delay, cerebral oedema, coma, and death. We developed a human hepatocyte model recapitulating the OTCD phenotype in-a-dish. In healthy induced pluripotent stem cells (iPSCs), the OTC mutation D175V (Asp175Val) was introduced by CRISPR gene editing. Genotype confirmation was performed by Sanger sequencing, whilst iPSC pluripotency and differentiation of iPSCs towards hepatocyte-like cells (HLCs) by qPCR and immunocytochemistry. Expression of urea cycle-related markers were determined by qPCR and western blotting, whilst urea secretion by biochemical assays. Following direct iPSC differentiation, we generated iPSC-derived HLCs expressing comparable levels of the hepatocyte maturity markers albumin, alpha-1-antitrypsin, and HNF4alpha to primary human hepatocytes. To characterise our HLC model, expression of the urea cycle-related enzymes OTC, ASS1, ASL, CPS1, and ARG were measured, revealing higher expression levels compared to iPSCs (negative control) and HepG2 hepatocellular carcinoma cells. Supporting these data, stimulation of urea cycle with NH4Cl and ornithine resulted in increasing urea secretion in a time-dependent manner, and this was significantly higher when compared to HepG2 cells. Consistent with successful confirmation of D175V mutation in CRISPR-derived HLCs, mRNA and protein levels of OTC were significantly lower compared to their wild-type isogenic controls, accompanied by decreased urea secretion. In conclusion, we have developed an iPSC-derived hepatocyte model that recapitulates human OTCD phenotype in vitro. This technology provides a framework for the development of human metabolic disease models and highlights the superiority of iPSCs as an effective platform for metabolic disease modelling and hit-lead drug screening.