RESUMEN
BACKGROUND: Retinitis pigmentosa is the prevailing genetic cause of blindness in developed nations with no effective treatments. In the pursuit of unraveling the intricate dynamics underlying this complex disease, mechanistic models emerge as a tool of proven efficiency rooted in systems biology, to elucidate the interplay between RP genes and their mechanisms. The integration of mechanistic models and drug-target interactions under the umbrella of machine learning methodologies provides a multifaceted approach that can boost the discovery of novel therapeutic targets, facilitating further drug repurposing in RP. METHODS: By mapping Retinitis Pigmentosa-related genes (obtained from Orphanet, OMIM and HPO databases) onto KEGG signaling pathways, a collection of signaling functional circuits encompassing Retinitis Pigmentosa molecular mechanisms was defined. Next, a mechanistic model of the so-defined disease map, where the effects of interventions can be simulated, was built. Then, an explainable multi-output random forest regressor was trained using normal tissue transcriptomic data to learn causal connections between targets of approved drugs from DrugBank and the functional circuits of the mechanistic disease map. Selected target genes involvement were validated on rd10 mice, a murine model of Retinitis Pigmentosa. RESULTS: A mechanistic functional map of Retinitis Pigmentosa was constructed resulting in 226 functional circuits belonging to 40 KEGG signaling pathways. The method predicted 109 targets of approved drugs in use with a potential effect over circuits corresponding to nine hallmarks identified. Five of those targets were selected and experimentally validated in rd10 mice: Gabre, Gabra1 (GABARα1 protein), Slc12a5 (KCC2 protein), Grin1 (NR1 protein) and Glr2a. As a result, we provide a resource to evaluate the potential impact of drug target genes in Retinitis Pigmentosa. CONCLUSIONS: The possibility of building actionable disease models in combination with machine learning algorithms to learn causal drug-disease interactions opens new avenues for boosting drug discovery. Such mechanistically-based hypotheses can guide and accelerate the experimental validations prioritizing drug target candidates. In this work, a mechanistic model describing the functional disease map of Retinitis Pigmentosa was developed, identifying five promising therapeutic candidates targeted by approved drug. Further experimental validation will demonstrate the efficiency of this approach for a systematic application to other rare diseases.
Asunto(s)
Retinitis Pigmentosa , Ratones , Animales , Retinitis Pigmentosa/tratamiento farmacológico , Retinitis Pigmentosa/genética , Retinitis Pigmentosa/metabolismo , Transducción de SeñalRESUMEN
Objetivo : Comparar las características anatómicas del CNP en pacientes dentados y desdentados mediante Tomografía Computarizada de Haz Cónico (TCHC) del Servicio de Radiología Bucomaxilofacial realizadas en el Centro Dental Docente de la Universidad Peruana Cayetano Heredia. Material y métodos : Se evaluaron todas las TCHC adquiridas entre los años 2018 y 2020, que cumplan con ciertos criterios; donde se comparó las características anatómicas del CNP. Los datos fueron registrados en una base de datos, luego representados en tablas. Resultados : Se evaluaron 216 volúmenes tomográficos (VT), divididos en dos grupos: dentados y desdentados. La forma cilíndrica y la forma de canal único fueron las más encontradas en ambos grupos. La longitud y la distancia fueron mayores en pacientes dentados, no se encontró asociación con relación al diámetro; la inclinación fue mayor en pacientes desdentados, encontrándose asociación con relación a la inclinación entre los grupos comparados. Conclusiones : Se encontraron múltiples diferencias anatómicas del CNP entre los pacientes dentados y desdentados evaluados con TCHC con relación al sexo y la edad.
Objective : To compare the anatomical characteristics of the NPC in dentate and edentulous patients using Cone Beam Computed Tomography (CBCT) of the Bucomaxillofacial Radiology Service performed at the Centro Dental Docente of the Universidad Peruana Cayetano Heredia. Material and methods : All TCHC acquired between the years 2018 and 2020, which meet certain criteria, were evaluated; where the anatomicals characteristics of the CNP were compared. The data were recorded in a database, then represented in tables. Results : 216 tomographic volumes were evaluated, divided into two groups: dentate and edentulous. The single cylindrical shape and the single channel shape were the most found in both groups. The length and distance were greater in dentate patients, no association was found in relation to the diameter, the inclination was greater in edentulous patients, finding an association in relation to the inclination between the compared groups. Conclusions : Multiple anatomical differences of the CNP were found between the dentate and edentulous patients evaluated with TCHC in relation to sex and age.