Presentation description

Mitochondrial DNA (mtDNA) copy number (mtCN) is a critical biomarker reflecting mitochondrial function, metabolic status, and disease susceptibility. Understanding the factors that influence mtCN can offer valuable insight into cellular energy balance, aging, and the progression of complex diseases such as cancer, neurodegenerative disorders, and metabolic syndromes. In this study, we developed and implemented a computational pipeline to estimate mtCN from whole-genome sequencing (WGS) data. Utilizing average mitochondrial and autosomal sequencing depth, we seek to prove the hypothesis that there is a genetic contribution to mtDNA copy number in CEPH pedigrees provided by the University of Utah. Our pipeline integrates parallel processing and internal threading for high-throughput computation, while incorporating clinically relevant hematological and metabolic covariates. We applied a generalized linear model and Pearson correlation coefficients to identify key biological variables influencing copy number in individuals. Our findings reveal that immune-related cell types exhibit significant correlations with mtCN, with adaptive immune components (eosinophils, basophils) showing positive associations, while blood biomarkers such as hemoglobin display strong negative correlations. This enables associations between mtDNA copy number and immune system dynamics. We seek to quantitatively determine if there is heritability of mitochondrial copy number across potentially 44 large multigenerational pedigrees. This work provides computational and statistical evidence for both environmental and genetic contributions to mtDNA regulation and offers a scalable framework for future studies exploring mitochondrial dynamics in population cohorts.