Applying data science methodologies with artificial intelligence variant reinterpretation to map and estimate genetic disorder prevalence utilizing clinical data.

Data science methodologies can be utilized to ascertain and analyze clinical genetic data that is often unstructured and rarely used outside of patient encounters. Genetic variants from all genetic testing resulting to a large pediatric healthcare system for a 5-year period were obtained and reinterpreted utilizing the previously validated Franklin© Artificial Intelligence (AI). Using PowerBI©, the data were further matched to patients in the electronic healthcare record to associate with demographic data to generate a variant data table and mapped by ZIP codes.

Bi-allelic variants in RNF170 are associated with hereditary spastic paraplegia.

Alterations of Ca homeostasis have been implicated in a wide range of neurodegenerative diseases. Ca efflux from the endoplasmic reticulum into the cytoplasm is controlled by binding of inositol 1,4,5-trisphosphate to its receptor. Activated inositol 1,4,5-trisphosphate receptors are then rapidly degraded by the endoplasmic reticulum-associated degradation pathway.

Gene Expression Profiling and Assessment of Vitamin D and Serotonin Pathway Variations in Patients With Irritable Bowel Syndrome.

Background/aims: Irritable bowel syndrome (IBS) is a multifaceted disorder that afflicts millions of individuals worldwide. IBS is currently diagnosed based on the presence/duration of symptoms and systematic exclusion of other conditions. A more direct manner to identify IBS is needed to reduce healthcare costs and the time required for accurate diagnosis.