Biology subjects

Cyr, D.

Publications and source records attributed to Cyr, D..

3 recordsLinked to original sources

bioRxiv2025

NTBC dosing and outcomes in hereditary tyrosinemia type 1: insights from a representative human model and 99 patients

Hereditary tyrosinemia type 1 (HT1) is a rare and severe metabolic liver disorder caused by fumarylacetoacetate hydrolase (FAH) deficiency. The optimal dose and long-term effects of the only available treatment, nitisinone (NTBC), remain unclear due to the absence of clinical trial data. Here, we generated a representative human in vitro model of HT1 using iPSC-derived hepatocytes, which faithfully recapitulated key disease features. We investigated the mechanisms of FAH deficiency-induced hepatocellular injury and evaluated the effects of NTBC treatment. We confirmed treatment efficacy and identified 50 {micro}mol/L as the minimal effective NTBC concentration to prevent cellular damage. This protective dose was subsequently validated in a large cohort of 99 HT1 patients, providing compelling evidence for establishing minimal therapeutic NTBC levels. Notably, approximately 10% of disease-associated genes, many implicated in hepatocellular carcinoma, remained dysregulated despite treatment, raising concerns that NTBC may not fully eliminate long-term oncogenic risk.

genetics↗

bioRxiv2023

In vivo dissection of the mouse tyrosine catabolic pathway with CRISPR-Cas9 identifies modifier genes affecting hereditary tyrosinemia type 1

Hereditary tyrosinemia type 1 is an autosomal recessive disorder caused by mutations (pathogenic variants) in fumarylacetoacetate hydrolase, an enzyme involved in tyrosine degradation. Its loss results in the accumulation of toxic metabolites that mainly affect the liver and kidneys and can lead to severe liver disease and liver cancer. Tyrosinemia type 1 has a global prevalence of approximately 1 in 100,000 births but can reach up to 1 in 1,500 births in some regions of Quebec, Canada. Mutating functionally related modifier genes (i.e., genes that, when mutated, affect the phenotypic impacts of mutations in other genes) is an emerging strategy for treating human genetic diseases. In vivo somatic genome editing in animal models of these diseases is a powerful means to identify modifier genes and fuel treatment development. In this study, we demonstrate that mutating additional enzymes in the tyrosine catabolic pathway through liver-specific genome editing can relieve or worsen the phenotypic severity of a murine model of tyrosinemia type 1. Neonatal gene delivery using recombinant adeno-associated viral vectors expressing Staphylococcus aureus Cas9 under the control of a liver-specific promoter led to efficient gene disruption and metabolic rewiring of the pathway, with systemic effects that were distinct from the phenotypes observed in whole-body knockout models. Our work illustrates the value of using in vivo genome editing in model organisms to study the direct effects of combining pathological mutations with modifier gene mutations in isogenic settings.

genetics↗

bioRxiv2021

Temporal derivative computation in the dorsal raphe network revealed by an experimentally-driven augmented integrate-and-fire modeling framework

By means of an expansive innervation, the serotonin (5-HT) neurons of the dorsal raphe nucleus (DRN) are positioned to enact coordinated modulation of circuits distributed across the entire brain in order to adaptively regulate behavior. Yet the network computations that emerge from the excitability and connectivity features of the DRN are still poorly understood. To gain insight into these computations, we began by carrying out a detailed electrophysiological characterization of genetically-identified mouse 5-HT and somatostatin (SOM) neurons. We next developed a single-neuron modeling framework that combines the realism of Hodgkin-Huxley models with the simplicity and predictive power of generalized integrate-and-fire (GIF) models. We found that feedforward inhibition of 5-HT neurons by heterogeneous SOM neurons implemented divisive inhibition, while endocannabinoid-mediated modulation of excitatory drive to the DRN increased the gain of 5-HT output. Our most striking finding was that the output of the DRN encodes a mixture of the intensity and temporal derivative of its input, and that the temporal derivative component dominates this mixture precisely when the input is increasing rapidly. This network computation primarily emerged from prominent adaptation mechanisms found in 5-HT neurons, including a previously undescribed dynamic threshold. By applying a bottom-up neural network modeling approach, our results suggest that the DRN is particularly apt to encode input changes over short timescales, reflecting one of the salient emerging computations that dominate its output to regulate behavior.

neuroscience↗