Publications by authors named "G N Cooper"

Background: Psychiatric disease burden in patients with Inflammatory bowel disease (IBD) has risen substantially over the past few decades. However, there is limited data on the relationship between IBD disease activity and the incidence of psychiatric comorbidities. We sought to conduct a population-based study to investigate the impact of early onset disease activity in newly diagnosed IBD patients on psychiatric disease diagnoses and medication usage.

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Pharmacogenomics is central to precision medicine, informing medication safety and efficacy. Pharmacogenomic diplotyping of complex genes requires full-length DNA sequences and detection of structural rearrangements. We introduce StarPhase, a tool that leverages PacBio HiFi sequence data to diplotype 21 CPIC Level A pharmacogenes and provides detailed haplotypes and supporting visualizations for , , and .

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Background Inpatient bowel preparation is often suboptimal. Few interventions have been effective at improving its success rate. We determined the clinical features associated with suboptimal inpatient bowel preparation and analyzed the ability of an easily implementable set of instructions inserted into the electronic health record to improve the success of bowel preparation.

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The mechanism by which chondrocytes respond to reduced mechanical loading environments and the subsequent risk of developing osteoarthritis remains unclear. This is of particular concern for astronauts. In space the reduced joint loading forces during prolonged microgravity (10 g) exposure could lead to osteoarthritis (OA), compromising quality of life post-spaceflight.

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Purpose: Clinical variant analysis pipelines likely have poor sensitivity to the effects on splicing from variants beyond 10 to 20 bases of exon-intron boundaries. Here, we demonstrate the value of SpliceAI to inform curation of rare variants previously classified as benign/likely benign (B/LB) under current guidelines.

Methods: Exome sequencing data from 576 pediatric cancer patients enrolled in the Texas KidsCanSeq study were filtered for intronic or synonymous variants absent from population databases, predicted to alter splicing via SpliceAI (>0.

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