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Harnessing Change: Human Health through the Lense of Evolution and Dynamical Systems Theory

Abstract

Over 2000 years ago, Heraclitus noted, "Everything changes and nothing stands still ." While this truth has long been evident to the wise, we have only recently developed the tools necessary to scientifically characterize sweeping patterns of change in large dynamical systems. Despite rapid progress, new methods and data sources are still sorely needed to further illuminate the intricate and dynamic nature of reality. In this dissertation, we will focus our investigations on understanding patterns of change with direct relevance to human health. In the first two chapters, we develop novel methodologies that lend insight into the evolutionary history of the human race and the genetic basis of human-specific traits and disease. Chapter 2 presents MOSAIC, a new python package for improved detection of genetically related genes between species. This inference is a foundational step towards understanding the function of proteins and the evolutionary pressures they have faced. This tool, along with a combination of other methods, facilitates our analysis in Chapter 3. In this section, we use the patterns of mutations along the human lineage to discover genes and even specific mutations that may play important roles in intelligence, obesity, mental health, as well as a variety of basic biological functions. These findings provide insight into the genetic architecture of health and disease. At the same time, they leave open questions about how genetic factors interact with the broad array of environmental and ecological variables that fundamentally shape downstream phenotypes. In Chapter 4, we introduce CauseMap, a tool I built to understand causal relationships within complex dynamical systems using time series data. It is our hope that this method will help us to interpret human health and disease as states of the bodily dynamical system embedded inextricably within an evolving social, economic, and environmental network. This perspective, we hope, will allow us to understand the characteristics of human health that emerge from an time-hewn dynamic equilibrium with the world within and around us.

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