Christopher Arehart

Research Interests:

I am working to apply a broad range of computational tools and modeling methods to advance our understanding of human biology and improve health outcomes. My interdisciplinary background spans applied mathematics, biology, and computer science, enabling me to tackle complex questions at the intersection of these fields.

My research journey began with modeling the prevalence and transmission rates of infectious diseases, such as whooping cough and COVID-19. As my interests evolved, I joined the labs of Dr. Kathleen Barnes and Dr. Chris Gignoux at the University of Colorado Anschutz, where I led bioinformatics projects exploring the genomic, transcriptomic, and metabolomic underpinnings of allergic traits, including atopic dermatitis and asthma.

In 2021, I entered graduate school at the University of Colorado Boulder through the Interdisciplinary Quantitative Biology program at the BioFrontiers Institute. Following four research rotations, I joined the Institute for Behavioral Genetics and Dr. Luke Evans’ lab, where my work has centered on disentangling the shared and distinct biological etiologies underlying human traits and diseases. Addressing the challenges posed by phenotypic heterogeneity and complex biological and environmental interactions, my research aims to inform forward-thinking approaches to personalized medicine by integrating diverse biological datasets and developing robust methods to triangulate reproducible results.

• Project 1: Evaluates the predictive utility of four -omics data types (metabolomics, metagenomics, metatranscriptomics, and viromics) individually and in combination for predicting inflammatory bowel disease.
• Project 2: Disentangles the genetic architectures underlying birth size, abdominal size, adipose distribution, and adiposity; characterization of these genetic factors yields a novel and comprehensive understanding of the primary genomic features associated with adverse health outcomes.
• Project 3: Utilizes interaction networks of biological molecules to identify mechanistic links between drugs and their adverse side effects.
• Project 4: Explores how the efficacy of prescription drugs to mitigate substance use is mediated by a multi-ancestry polygenic score.

Together, these projects implement a wide range of computational frameworks to bridge gaps between human biology, complex phenotypes, and effective therapeutics. I am passionate about inclusive team science, mentorship, data visualization, and science communication.

Mentors:

Luke Evans, Chris Gignoux

Starting Year:

2021

Other Interests:

In my free time, I enjoy playing the piano, trail running, basketball, disc golf, backpacking, and snowboarding.