Abstract

Circular RNAs (circRNAs) are highly stable non-coding RNAs enriched in brain that can cross the blood-brain-barrier. Detection of Alzheimer’s disease (AD) prior to the development of clinical symptoms is critical due to new treatments for symptomatic AD. Larger sample sizes are needed to fully understand the role of circRNA in AD. Therefore, I thus used three brain AD-cohorts and the current largest whole blood transcriptomic dataset. To compare the role of circRNA in AD with traditional linear mRNA, I first analyzed mRNA genes in AD and cognitively normal control samples based on multiple AD phenotypes. A total of 4,317 mRNA in cortical tissue were significantly associated with AD and 1,047 mRNA in blood were significant in clinical AD status. Compared to the identified genes in brain being enriched for synaptic pathways, blood genes associated with AD were enriched for lysosomal pathways. Next, I identified 129 cortical circRNAs correlated with AD phenotypes, replicating the previously identified circHOMER1 and circMAN2A1 and identifying novel brain circRNA such as circGSE1. A total of 34 blood circRNAs were significantly associated with clinical AD status, including several from genes known to be implicated in neurodegeneration such as circDNAJC6 and circPICALM. These circRNAs co-expressed with mRNA transcripts enriched for synaptic pathways, highlighting the utility of AD transcriptomics across tissues. Moreover, a single-cutoff predictive model including these 34 blood circRNAs was comparable to plasma pTau217 in classifying AD based on biomarker-confirmed (A+T+) status and replicated in the independent samples from the Knight ADRC and A4 dataset. The circRNAs (Hazard Ratio (HR): 2.92) outperformed pTau217 (HR: 1.81) and amyloid-PET when predicting progression to symptomatic AD. Taken together, these results highlight the synaptic enrichment of AD circRNA across the blood-brain barrier and establish blood circRNAs as robust biomarkers in AD diagnosis and disease progression.

Committee Chair

Carlos Cruchaga

Committee Members

Celeste Karch; Chun-Kan Chen; Laura Ibáñez; Nancy Saccone

Degree

Doctor of Philosophy (PhD)

Author's Department

Biology & Biomedical Sciences (Computational & Systems Biology)

Author's School

Graduate School of Arts and Sciences

Document Type

Dissertation

Date of Award

4-27-2026

Language

English (en)

Author's ORCID

https://orcid.org/0000-0002-5261-689X

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Available for download on Friday, April 23, 2027

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