This is a resubmission of the application for a Mentored Research Scientist Development Award (Parent K01) for Dr. Sharon Lutz, an Assistant Professor of Biostatistics at the Colorado School of Public Health (CSPH) at the University of Colorado, Anschutz Medical Campus. Dr. Lutz is establishing herself as a young investigator in the genetic overlap of Chronic Obstructive Pulmonary Disease (COPD) and Cardio Vascular Disease (CVD). This K01 award will provide Dr. Lutz with the support necessary to acquire a solid foundational knowledge of the pathophysiology and epidemiology of the overlap between COPD and CVD through formal training in order to become an independent investigator studying common genetic susceptibility for COPD and CVD. To achieve this goal, Dr. Lutz has assembled a mentoring team comprised of an Epidemiology mentor, Dr. John Hokanson, and a Biostatistics mentor, Dr. Tasha Fingerlin. Dr. Hokanson is a Professor of Epidemiology at CSPH and Director of the Epidemiology Center for the National Heart, Lung, and Blood Institute (NHLBI) funded COPDGene study. Dr. Fingerlin is an Associate Professor of Biostatistics at CSPH and director of the Center for Gene, Environment, and Health at National Jewish Health. In addition to Dr. Lutz's primary mentors, two consultants will serve on this project: Dr. Christoph Lange, a Professor of Biostatistics at Harvard School of Public Health who specializes in the statistical genetics of COPD and Dr. Matthew Budoff, a Professor of Cardiology at Harbor-UCLA Medical Center who is the chairman of the American Heart Association (AHA) Scientific Statement on EBT and Multi-slice CT Scanner. CVD is one of two most common causes of death in patients with COPD. However, the inflammatory and genetic basis for the uniquely high CVD risk in subjects with COPD remains unknown. Dr. Lutz's research will examine the genetic overlap of COPD as measured by FEV1 and FEV1/FVC and CVD as measured by coronary artery calcium (CAC) and thoracic aortic calcium (TAC) in the COPDGene study (AIM 1). Dr. Lutz will develop statistical methodology to quantify genetic overlap amongst binary phenotypes, more than 2 phenotypes, and rare variants.
(AIM 1) Since smoking may influence the genetic overlap between COPD and CVD, Dr. Lutz will examine gene by smoking interactions in both measures of pulmonary function (FEV1 and FEV1/FVC) and vascular calcification (CAC and TAC).
(AIM 2) Because standard methods for gene by environment interactions tend to be underpowered, Dr. Lutz proposes a Bayesian method for gene by environment interactions that leverages known genetic information and maintains the hierarchical principle.
(AIM 2) To determine the path from gene to disease through smoking, Dr. Lutz will develop a statistical method to determine if rare variants are associated indirectly with pulmonary function (FEV1 and FEV1/FVC) and vascular calcification (CAC and TAC) through smoking.
(AIM 3)

Public Health Relevance

Identification of shared susceptibility genes for COPD and CVD has the potential to lead to new biological understanding, and eventually to improved treatments for both conditions, thereby improving public health.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Scientist Development Award - Research & Training (K01)
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NHLBI Mentored Clinical and Basic Science Review Committee (MCBS)
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Papanicolaou, George
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University of Colorado Denver
Biostatistics & Other Math Sci
Schools of Public Health
United States
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Kinney, Gregory L; Santorico, Stephanie A; Young, Kendra A et al. (2018) Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study. Am J Epidemiol 187:2109-2116
Budoff, Matthew J; Lutz, Sharon M; Kinney, Gregory L et al. (2018) Coronary Artery Calcium on Noncontrast Thoracic Computerized Tomography Scans and All-Cause Mortality. Circulation 138:2437-2438
Lutz, Sharon M; Frederiksen, Brittni; Begum, Ferdouse et al. (2018) Common and rare variants genetic association analysis of cigarettes per day among ever smokers in COPD cases and controls. Nicotine Tob Res :
Hartz, Sarah M; Horton, Amy C; Hancock, Dana B et al. (2018) Genetic correlation between smoking behaviors and schizophrenia. Schizophr Res 194:86-90
Jiang, Yu; Chen, Sai; McGuire, Daniel et al. (2018) Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes. PLoS Genet 14:e1007452
Hancock, D B; Guo, Y; Reginsson, G W et al. (2018) Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence. Mol Psychiatry 23:1-9
Boueiz, Adel; Lutz, Sharon M; Cho, Michael H et al. (2017) Genome-Wide Association Study of the Genetic Determinants of Emphysema Distribution. Am J Respir Crit Care Med 195:757-771
Hoogendoorn, Martine; Feenstra, Talitha L; Boland, Melinde et al. (2017) Prediction models for exacerbations in different COPD patient populations: comparing results of five large data sources. Int J Chron Obstruct Pulmon Dis 12:3183-3194
Lutz, Sharon M; Thwing, Annie; Schmiege, Sarah et al. (2017) Examining the role of unmeasured confounding in mediation analysis with genetic and genomic applications. BMC Bioinformatics 18:344
Qiao, Dandi; Lange, Christoph; Laird, Nan M et al. (2017) Gene-based segregation method for identifying rare variants in family-based sequencing studies. Genet Epidemiol 41:309-319

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