Administrative Core
Committees Chairs: Chris Amos and Rayjean Hung
Aim 1: Maintain and further develop a database for epidemiological, genetic and biomarker data.
Aim 2: Provide Integrative support for U19 Activities
Aim 3: Ensure Compliance with regulatory requirements.
Aim 4: Provide Fiscal Oversight.
Biostatistics Core
Committee Chair: Xihong Lin
Aim 1: Ensure rigor of biostatistical and bioinformatics approaches.
Aim 2: Provide expertise in design and analysis in statistical genetics, genomics, bioinformatics and machine learning for all projects.
Aim 3: Conduct mission related statistical methods (pathway analysis, mediation, and support mendelian randomization, also give guidance in genomics).
Aim 4: Disseminate statistical methodology via articles and web based software.
Aim 5: Provide education to students and researchers.
Project 1: Genomic Predictors of Smoking Lung Cancer Risk
Committee Chairs: Paul Brennan and Mattias Johansson
Aim 1: Characterize contributions of common genetic variation to lung cancer etiology.
Aim 2: Investigate role of rare variants in lung cancer susceptibility
Aim 3: Identify genetic effects on smoking behavior
Aim 4: Characterize joint effects of environmental and genetic interactions on lung cancer risk.
Project 2: Biomarkers of Lung Cancer Risk
Committee Chairs: Paul Brennan and Mattias Johansson
Aim 1: To organize the LC3, to study 2,300 former and current smoking LC cases that were diagnosed within five years of donating their blood sample along with one smoking-matched control per case.
Aim 2: To replicate a comprehensive panel of promising risk biomarkers and identify those that may be useful for risk prediction.
Aim 3: To extensively evaluate all replicated risk biomarkers from Aim 2, identifying a minimum set of validated risk biomarkers, and ultimately evaluate the extent to which they improve risk prediction models.
Project 3: Translating Molecular and Clinical Data to Population Lung Cancer Risk Assessment
Committees: Rayjean Hung
Specific Aim 1: To establish an integrated risk prediction model to identify individuals at high risk of lung cancer,
Specific Aim 2: To establish a comprehensive LC probability models for individuals with LDCT-detected non-calcified pulmonary nodules.
