@article {41,
	title = {Genetics of the extracellular matrix in aortic aneurysmal diseases.},
	journal = {Matrix Biol},
	volume = {71-72},
	year = {2018},
	month = {2018 10},
	pages = {128-143},
	abstract = {<p>Aortic aneurysms are morbid conditions that can lead to rupture or dissection and are categorized as thoracic (TAA) or abdominal aortic aneurysms (AAA) depending on their location. While AAA shares overlapping risk factors with atherosclerotic cardiovascular disease, TAA exhibits strong heritability. Human genetic studies in the past two decades have successfully identified numerous genes involved in both familial and sporadic forms of aortic aneurysm. In this review we will discuss the genetic basis of aortic aneurysm, focusing on the extracellular matrix and how insights from these studies have informed our understanding of human biology and disease pathogenesis.</p>},
	issn = {1569-1802},
	doi = {10.1016/j.matbio.2018.04.005},
	author = {Lin, Chien-Jung and Lin, Chieh-Yu and Stitziel, Nathan O}
}
@article {29,
	title = {Genetic association studies in cardiovascular diseases: Do we have enough power?},
	journal = {Trends Cardiovasc Med},
	volume = {27},
	year = {2017},
	month = {2017 08},
	pages = {397-404},
	abstract = {<p>Genetic association studies have a long history of delivering insightful results for cardiovascular disease (CVD) research. Beginning with early candidate gene studies, to genome-wide association studies, and now on to newer whole-genome sequencing studies, research in human genetics has enriched our understanding of the pathobiology of CVD. As these studies continue to expand, the issue of statistical power plays an important role in study design as well as the interpretation of results. We provide an overview of the component parts that determine statistical power and preview the future of CVD genetic association studies through this lens.</p>},
	keywords = {Cardiovascular Diseases, Data Accuracy, Data Interpretation, Statistical, Genetic Association Studies, Genetic Markers, Genetic Predisposition to Disease, Genetic Variation, Humans, Phenotype, Reproducibility of Results, Research Design, Risk Assessment, Risk Factors},
	issn = {1873-2615},
	doi = {10.1016/j.tcm.2017.03.005},
	author = {Auer, Paul L and Stitziel, Nathan O}
}
