Decoding Human Depression Through Genomics
CSEF · 2026 Biochemistry/ Molecular Biology (Senior Division)
Overview
Depression is a serious mental health disorder that affects individuals of all ages, including high school students. Social stress and ongoing emotional development contribute to a growing risk of depression and suicide among adolescents. This project investigates how major depressive disorder (MDD) alters cell-type-specific gene expression and molecular pathways in the human brain. I hypothesize that MDD is associated with distinct molecular changes in specific brain cell types, particularly in pathways related to stress response, inflammation, and neurotransmission. To address this question, I analyzed genomic data from post-mortem human brain tissue in collaboration with a neuroscience research team at the University of California, Irvine. Samples were grouped into four cohorts: controls (no MDD, no suicide), MDD without suicide, MDD with suicide, and suicide without an MDD diagnosis. Using single-cell RNA sequencing and computational analysis, I compared gene expression patterns across cell types and conditions. Computational analysis of single-cell RNA-seq data was used to compare gene expression and activity across specific brain cell types and conditions. The analysis revealed consistent molecular alterations in inhibitory neurons and glial cells in MDD, as well as disruptions in circadian rhythm regulation, cellular stress responses, and neurotransmitter balance. The findings support the hypothesis that depression is associated with cell-type-specific molecular dysregulation in the prefrontal cortex. Importantly, this work contributes to a deeper understanding of the biological basis of depression and may inform future efforts to identify risk factors and improve mental health outcomes for adolescents and other vulnerable populations.
Competition history
- CSEF 2026
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