Identification of 2,2-Dimethylbutanoic Acid (HST5040), a Clinical Development Candidate for the Treatment of Propionic Acidemia and Methylmalonic Acidemia.

Propionic acidemia (PA) and methylmalonic acidemia (MMA) are rare autosomal recessive disorders of propionyl-CoA (P-CoA) catabolism, caused by a deficiency in the enzymes P-CoA carboxylase and methylmalonyl-CoA (M-CoA) mutase, respectively. PA and MMA are classified as intoxication-type inborn errors of metabolism because the intramitochondrial accumulation of P-CoA, M-CoA, and other metabolites results in secondary inhibition of multiple pathways of intermediary metabolism, leading to organ dysfunction and failure. Herein, we describe the structure-activity relationships of a series of short-chain carboxylic acids which reduce disease-related metabolites in PA and MMA primary hepatocyte disease models. These studies culminated in the identification of 2,2-dimethylbutanoic acid (10, HST5040) as a clinical candidate for the treatment of PA and MMA. Additionally, we describe the in vitro and in vivo absorption, distribution, metabolism, and excretion profile of HST5040, data from preclinical studies, and the synthesis of the sodium salt of HST5040 for clinical trials.

Gene Expression Predicts Histological Severity and Reveals Distinct Molecular Profiles of Nonalcoholic Fatty Liver Disease.

The heterogeneity of biological processes driving the severity of nonalcoholic fatty liver disease (NAFLD) as reflected in the transcriptome and the relationship between the pathways involved are not well established. Well-defined associations between gene expression profiles and disease progression would benefit efforts to develop novel therapies and to understand disease heterogeneity. We analyzed hepatic gene expression in controls and a cohort with the full histological spectrum of NAFLD. Protein-protein interaction and gene set variation analysis revealed distinct sets of coordinately regulated genes and pathways whose expression progressively change over the course of the disease. The progressive nature of these changes enabled us to develop a framework for calculating a disease progression score for individual genes. We show that, in aggregate, these scores correlate strongly with histological measures of disease progression and can thus themselves serve as a proxy for severity. Furthermore, we demonstrate that the expression levels of a small number of genes (~20) can be used to infer disease severity. Finally, we show that patient subgroups can be distinguished by the relative distribution of gene-level scores in specific gene sets. While future work is required to identify the specific disease characteristics that correspond to patient clusters identified on this basis, this work provides a general framework for the use of high-content molecular profiling to identify NAFLD patient subgroups.