Abstract

Depression is a highly prevalent mental health disorder that often requires treatment. While current treatments are effective for a large portion of patients generally, the exact medication that works for any specific person is unclear, leading to large delays in symptom remittance if at all. This hurdle has motivated substantial efforts to identify markers of depression that might predict treatment outcomes. However, large sources of heterogeneity in depression have stymied progress on identifying robust and replicable neuroimaging markers. Parsing this heterogeneity is crucial but mired with challenges. My dissertation work has elucidated several key barriers in parsing the heterogeneity of depression. In chapter 2, we identified small but replicable biomarkers of depression in the UK Biobank. In chapter 3, we found these small effect sizes for biomarkers of depression can be increased by parsing clinical sources of heterogeneity. We also verified the presence of many-to-one mapping relationships between symptoms and the brain, providing novel insights into the mechanism of depression. This finding strongly indicates future work ought to relinquish the notion that clinical subtypes will explain neurobiological heterogeneity and vice versa. Both symptoms and neuroimaging must be accounted for when identifying subtypes or clinically relevant markers of depression. In chapter 3, we identified the impact of methodological variability on subtyping efforts, identifying subtyping techniques to avoid and validation analyses to include. For example, we recommend future work compare their findings to null data and to previous subtyping approaches. These advancements will hopefully allow the field to successfully identify and parse the sources of heterogeneity in depression. Such progress should allow for more robust biomarkers of depression and therefore treatment guidelines, ultimately improving patient care.

Committee Chair

Janine Bijsterbosch

Committee Members

Daniel Marcus; Deanna Barch; Katherine Narr; Ryan Bogdan

Degree

Doctor of Philosophy (PhD)

Author's Department

Biology & Biomedical Sciences (Neurosciences)

Author's School

Graduate School of Arts and Sciences

Document Type

Dissertation

Date of Award

5-2-2025

Language

English (en)

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