Data Management and Statistics Core

University Of Pittsburgh At Pittsburgh, Pittsburgh PA

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY CORE C Late sleep timing, short sleep duration and circadian misalignment are associated with increased substance use (SU) in teenagers and young adults. The central hypothesis for the Center for Adolescent Rhythms, Reward, and Sleep (CARRS) is that changes in sleep and circadian rhythms associated with adolescent development impact cortico-limbic functions critical to SU use risk (e.g., reward and cognitive control). We further hypothesize that: 1) Sex and other biological, social, and environmental factors influence these relationships; and 2) Screening algorithms and biomarkers reflecting sleep-circadian function can identify adolescents at risk for SU and substance use disorders (SUDs). Our findings will ultimately inform novel SUD prevention and intervention strategies based on sleep and circadian function. Core C: Data Management and Statistics will support the 5 projects in CARRS by managing data (e.g., developing protocols, forms, and databases and assuring data quality and security) and performing statistical analyses (e.g., preliminary, primary, secondary, and exploratory analyses). In this way, Core C will guarantee high-quality, transparent, and consistent standards for data management and statistical analyses across projects and will maximize rigor and reproducibility within CARRS. Core C will also develop and adapt analytic methods that take full advantage of the translational and high- dimensional data captured across the 5 projects within CARRS. Areas of focus will include machine-learning (ML) approaches for predicting SU; high-throughput “-omics” data analysis; novel ML-based processing pipelines for activity and other sleep-circadian data; and methods for integrating findings across projects and species, using data from from Projects 1-5. Finally, we will establish CARRS as a national resource by providing data to national databanks, publishing code and methods, and providing national education opportunities. Topics will include rigor and reproducibility, analysis of sleep and circadian data, analysis of RNA sequencing and proteomic data, and the innovative statistical methods developed and applied within Core C.