PROJECT SUMMARY Atherosclerotic cardiovascular disease remains the leading cause of death in humans despite significant advances in diagnosis and treatment. Familial hypercholesterolemia (FH) is a genetic disorder that leads to markedly increased levels of low-density lipoprotein cholesterol (LDL-C) in the blood that are present from birth and predispose affected individuals to early cardiovascular disease. FH affects 1 in 200-250 individuals, making FH the most common potentially fatal genetic disease in humans. Half of all untreated men with FH die of cardiovascular disease by age 55 and 15% of untreated women with FH die before 60 years of age. In the United States, most individuals with FH are diagnosed based on their blood levels of LDL-C alone, although genetic testing showing a disease-causing mutation in one of the genes known to cause FH is another way to make the diagnosis. Despite widespread use of cholesterol testing, FH remains profoundly underdiagnosed with less than 10% of individuals with FH identified in most countries, including the United States. The development of a tool to detect FH in the newborn represents an unprecedented opportunity to initiate early treatment. Early diagnosis and treatment of FH is effective at preventing premature morbidity and mortality. Additionally, identification of a young child with FH often leads to diagnosis of parents and other first-degree relatives at risk, creating a positive cascade effect. For these reasons, multiple different screening strategies have been designed to identify both children and adults with FH, but they have been of limited success. Screening newborns for FH presents a potential opportunity for population-wide detection but has not been systematically studied to date. The aim of this study is to design a testing algorithm that can detect FH in the newborn population. Using biochemical and molecular genetic tests and existing dried blood spots from discarded Wisconsin newborn screening specimens, this study will assess a large group (10,000) of newborns for FH biochemical markers and genetic mutations that cause FH. The biochemical markers, genetic data, and newborn demographic information will be used to create a multifactorial model to predict FH in a given individual. Effective diagnosis of FH in the newborn period, using an already existing and highly effective population screening tool, has the real potential to dramatically change the natural history of a disease that currently exerts a devastating toll on our population.