Publications by authors named "A Hilliard"
Coronary arteries have a specific branching pattern crucial for oxygenating heart muscle. Among humans, there is natural variation in coronary anatomy with respect to perfusion of the inferior/posterior left heart, which can branch from either the right arterial tree, the left, or both-a phenotype known as coronary dominance. Using angiographic data for >60,000 US veterans of diverse ancestry, we conducted a genome-wide association study of coronary dominance, revealing moderate heritability and identifying ten significant loci.
View Article and Find Full Text PDFPolygenic risk scores (PRS) hold prognostic value for identifying individuals at higher risk of type 2 diabetes (T2D). However, further characterization is needed to understand the generalizability of T2D PRS in diverse populations across various contexts. We characterized a multi-ancestry T2D PRS among 244,637 cases and 637,891 controls across eight populations from the Population Architecture Genomics and Epidemiology (PAGE) Study and 13 additional biobanks and cohorts.
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- Whole genome sequencing (WGS) helps identify rare genetic variants that may explain the missing heritability of coronary artery disease (CAD) by analyzing 4,949 cases and 17,494 controls from the NHLBI TOPMed program.
- The study estimates that the heritability of CAD is around 34.3%, with ultra-rare variants contributing about 50%, especially those with low linkage disequilibrium.
- Functional annotations show significant enrichment of CAD heritability, highlighting the importance of ultra-rare variants and specific regulatory mechanisms in different cells as major factors influencing genetic risk for the disease.
Background: While risk stratification for atherosclerotic cardiovascular disease (ASCVD) is essential for primary prevention, current clinical risk algorithms demonstrate variability and leave room for further improvement. The plasma proteome holds promise as a future diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of plasma proteins to predict ASCVD.
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- The study evaluates the potential of plasma proteins to predict the risk of type 2 diabetes mellitus (T2DM) and related traits using data from UK Biobank participants.
- Different analysis methods, like LASSO regression, were employed to compare the effectiveness of proteomic data against traditional clinical and genetic data for predicting traits like truncal fat and fitness levels.
- Results showed that integrating proteomic signatures enhanced prediction accuracy for T2DM and other traits beyond existing clinical risk scores, indicating their value in disease prognostics.