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Evaluating the impact of modeling choices on the performance of integrated genetic and clinical models.

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Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN. Electronic address:

Purpose: The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results. We performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) with genetic data to understand which decisions may affect performance.

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Germline inactivating mutations of the SLC25A1 gene contribute to various human disorders, including Velocardiofacial (VCFS), DiGeorge (DGS) syndromes and combined D/L-2-hydroxyglutaric aciduria (D/L-2HGA), a severe systemic disease characterized by the accumulation of 2-hydroxyglutaric acid (2HG). The mechanisms by which SLC25A1 loss leads to these syndromes remain largely unclear. Here, we describe a mouse model of SLC25A1 deficiency that mimics human VCFS/DGS and D/L-2HGA.

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The overexpression of Polo-like kinase 1 (PLK1) is associated with poor clinical outcomes in various malignancies, making it an attractive target for anticancer therapies. Although recent studies suggest PLK1's involvement in homologous recombination (HR), the impact of its overexpression on HR remains unclear. In this study, we investigated the effect of PLK1 overexpression on HR using bioinformatics and experimental approaches.

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Background: Endoscopic ultrasound-guided tissue acquisition (EUS-TA) has become essential for diagnosing pancreatic ductal adenocarcinoma (PDAC) and is increasingly utilized for comprehensive genome profiling (CGP) to advance precision medicine. This systematic review and meta-analysis assess the feasibility and clinical utility of EUS-TA samples for CGP in PDAC.

Methods: We conducted a thorough systematic literature search in PubMed, EMBASE, and the Cochrane Library up to October 2023.

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