Publications by authors named "K L Lunetta"

To broaden our understanding of bradyarrhythmias and conduction disease, we performed common variant genome-wide association analyses in up to 1.3 million individuals and rare variant burden testing in 460,000 individuals for sinus node dysfunction (SND), distal conduction disease (DCD) and pacemaker (PM) implantation. We identified 13, 31 and 21 common variant loci for SND, DCD and PM, respectively.

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Article Synopsis
  • The Gaussian graphical model (GGM) helps analyze conditional dependencies in multi-omics data, which can reveal biological pathways related to diseases.
  • Existing methods for comparing GGMs typically focus on two groups and struggle with multiple testing issues, limiting insights across multiple conditions.
  • The proposed ONDSA framework enables comprehensive analysis across multiple groups, effectively controlling false discovery rates while uncovering structural differences and similarities in precision matrices, enhancing understanding of disease mechanisms.
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Background: Blood-derived mitochondrial DNA copy number (mtDNA-CN) is a proxy measurement of mitochondrial function in the peripheral and central systems. Abnormal mtDNA-CN not only indicates impaired mtDNA replication and transcription machinery but also dysregulated biological processes such as energy and lipid metabolism. However, the relationship between mtDNA-CN and Alzheimer disease (AD) is unclear.

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Polygenic scores (PGSs) are a promising tool for estimating individual-level genetic risk of disease based on the results of genome-wide association studies (GWASs). However, their promise has yet to be fully realized because most currently available PGSs were built with genetic data from predominantly European-ancestry populations, and PGS performance declines when scores are applied to target populations different from the populations from which they were derived. Thus, there is a great need to improve PGS performance in currently under-studied populations.

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Introduction: Brain magnetic resonance imaging (MRI) and inflammatory biomarkers are crucial for investigating preclinical neurocognitive disorders. Current investigations focus on a few inflammatory markers. The study aims to investigate the associations between inflammatory biomarkers and MRI measures and to examine sex differences among the associations in the Framingham Heart Study.

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