Browsing by Author "Miller, Justin B."

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    Assembly of 809 whole mitochondrial genomes with clinical, imaging, and fluid biomarker phenotyping
    (Elsevier, 2018-04) Ridge, Perry G.; Wadsworth, Mark E.; Miller, Justin B.; Saykin, Andrew J.; Green, Robert C.; Alzheimer’s Disease Neuroimaging Initiative; Kauwe, John S. K.; Radiology and Imaging Sciences, School of Medicine
    INTRODUCTION: Mitochondrial genetics are an important but largely neglected area of research in Alzheimer's disease. A major impediment is the lack of data sets. METHODS: We used an innovative, rigorous approach, combining several existing tools with our own, to accurately assemble and call variants in 809 whole mitochondrial genomes. RESULTS: To help address this impediment, we prepared a data set that consists of 809 complete and annotated mitochondrial genomes with samples from the Alzheimer's Disease Neuroimaging Initiative. These whole mitochondrial genomes include rich phenotyping, such as clinical, fluid biomarker, and imaging data, all of which is available through the Alzheimer's Disease Neuroimaging Initiative website. Genomes are cleaned, annotated, and prepared for analysis. DISCUSSION: These data provide an important resource for investigating the impact of mitochondrial genetic variation on risk for Alzheimer's disease and other phenotypes that have been measured in the Alzheimer's Disease Neuroimaging Initiative samples.
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    The Polygenic Risk Score Knowledge Base offers a centralized online repository for calculating and contextualizing polygenic risk scores
    (Springer Nature, 2022-09-02) Page, Madeline L.; Vance, Elizabeth L.; Cloward, Matthew E.; Ringger, Ed; Dayton, Louisa; Ebbert, Mark T. W.; Alzheimer’s Disease Neuroimaging Initiative; Miller, Justin B.; Kauwe, John S. K.; Radiology and Imaging Sciences, School of Medicine
    The process of identifying suitable genome-wide association (GWA) studies and formatting the data to calculate multiple polygenic risk scores on a single genome can be laborious. Here, we present a centralized polygenic risk score calculator currently containing over 250,000 genetic variant associations from the NHGRI-EBI GWAS Catalog for users to easily calculate sample-specific polygenic risk scores with comparable results to other available tools. Polygenic risk scores are calculated either online through the Polygenic Risk Score Knowledge Base (PRSKB; https://prs.byu.edu ) or via a command-line interface. We report study-specific polygenic risk scores across the UK Biobank, 1000 Genomes, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), contextualize computed scores, and identify potentially confounding genetic risk factors in ADNI. We introduce a streamlined analysis tool and web interface to calculate and contextualize polygenic risk scores across various studies, which we anticipate will facilitate a wider adaptation of polygenic risk scores in future disease research.