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In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 3-Day Livestream Seminar Taught by Lauren Gaydosh, Ph.D.

Chronological time passes at the same pace for all of us. However, the rate at which our biology ages differs, with some aging biologically more slowly and others more rapidly. Biological aging refers to the gradual decline in integrity across biological systems that occurs with advancing chronological age, and is the cause of age-related chronic disease and disability. With advances in the collection of biological data, there are now many approaches to measuring biological age, including leading edge methods such as epigenetic clocks. The implementation of established methods for measuring and analyzing biological age is the focus of this course.

The goal of this seminar is to provide you with a thorough conceptual understanding of the geroscience hypothesis and biological aging, and to equip you with the technical skills to estimate and analyze biological aging. Topics covered include: identifying biomarkers of aging, using DNA methylation data to train machine learning algorithms to predict biological age, blood-protein based measures of biological age, innovations in the measurement of biological age using omics data, the management and manipulation of high-dimension omics datasets, and an overview of the key software tools and packages.

The integration of biological data into the study of health and health disparities provides exciting opportunities to evaluate models of biological embedding, better understand the role of social influences, and test interventions designed to improve health. Many social and behavioral studies, such as the National Health and Nutrition Examination Survey (NHANES), National Longitudinal Study of Adolescent to Adult Health (Add Health), and the Health and Retirement Study (HRS), now include the collection of biomarkers that allow for the measurement of biological age. This includes new “omics” data on the epigenome, transcriptome, microbiome, proteome, and metabolome. Yet the size and complexity of “omics” data can be challenging for new users.

This course will provide you with methods for managing, cleaning, and modeling “omics” data, and applying the leading algorithms for the estimation of biological age. After completing the course, you will be able to construct measures of biological age across different data sources and understand how to analyze these measures.

This seminar will introduce biological aging and the geroscience hypothesis, considering the conceptualization and measurement with respect to reference populations and the selection of biomarkers. We will use the computing environment of R and RStudio, as well as multiple packages available from scientists who developed algorithms for biological age, including methylCIPHER, PCClocks, and BioAge.

The seminar will provide an overview of common machine learning techniques used to train measures of biological age, including lasso and ridge regression. We will then discuss a large group of measures of biological age derived from DNA methylation data, referred to as epigenetic clocks. After a brief overview of DNA methylation, we will cover the first iteration of epigenetic clocks that were trained to predict chronological age. Then, we will discuss new advances in the field that train epigenetic clocks using phenotypic measures of biological risk or function. We will close our discussion of epigenetic clocks with an exercise creating clocks from randomly selected sites in the epigenome. Finally, we will move beyond epigenetic clocks to consider other sources of data used in the construction of biological age, including blood-based protein markers and RNA. We will also consider measures of biological age that focus on specific age-related changes of senescence and inflammation. Throughout the course, you will gain experience with these methods through hands-on exercises.