Computational Analysis of Fenofibrate’s Influence on PGC-1α in RPE Cells, and AMD-Related Pathways

Suarau Akanmu

Mentor: Dr. Nady Golestaneh, The Golestaneh Lab, Director of Research, Department of Ophthalmology Tenure Associate Professor, Departments of Ophthalmology, Neurology, Biochemistry.

Date/Time: December 9th, 2025 at 12:00 PM.

Abstract: Age-related macular degeneration (AMD) remains a leading cause of irreversible vision loss in the elderly, driven in part by dysfunction of the retinal pigment epithelium (RPE), mitochondrial impairment, and chronic oxidative stress. Central to these processes is PGC-1α, a master regulator of mitochondrial biogenesis, lipid homeostasis, and antioxidant defense. Reduced PGC-1α activity, observed both in AMD patient tissue and in iPSC-derived RPE models from Dr. Golestaneh’s lab, has been linked to mitochondrial fragmentation, impaired metabolic resilience, and pathological lipid accumulation. These insights raise a critical mechanistic question: Can fenofibrate, a PPARα agonist traditionally used to treat dyslipidemia, modulate PGC-1α dependent pathways in RPE cells and potentially influence AMD-related biology?_

This internship addresses that question through a multi-phase computational analysis framework integrating systems biology, drug–target mining, transcriptomics, query optimization, and network modeling. First, drug interaction databases (DrugBank, ChEMBL, PubChem) and literature mining were used to map fenofibrate’s known mechanisms, including PPARα activation and downstream metabolic gene programs, and to determine how these networks overlap with pathways relevant to mitochondrial quality control, autophagy, oxidative stress, and AMD pathology. Structural analysis of the PPARα–fenofibric acid complex further anchored the mechanistic framework by illustrating ligand–receptor interactions at atomic resolution. During this phase, a predicted network of fenofibrate-driven PGC-1α modulation in RPE cells using literature-based inference was also constructed. This was needed because direct experimental data on fenofibrate in RPE is limited, a curated review of metabolic, retinal, and mitochondrial biology studies was conducted to identify regulatory relationships, such as PPARα–PGC-1α co-activation, transcriptional induction of biogenesis factors (NRF1, TFAM), mitophagy regulators (PINK1, PRKN), and antioxidant pathways (SOD2, CAT)._

Next, GEO gene-expression datasets involving fenofibrate treatment were identified, cleaned, and evaluated to extract regulatory signatures. In the absence of RPE-specific datasets, alternative bioinformatic strategies, including pathway inference, predictive modeling, and simulation of downstream signaling, were applied to approximate fenofibrate’s potential transcriptional impact on AMD-related targets. Pathway and gene-set enrichment analyses (GSEA) were then performed to evaluate whether fenofibrate-responsive signatures converge on key PGC-1α regulatory modules, including mitochondrial biogenesis, mitophagy (PINK1–PRKN axis), lipid metabolism, and antioxidant responses._

Finally, network-based visualization models were developed to integrate findings across structural, transcriptomic, and systems-level scales, producing a coherent mechanistic map of how fenofibrate may influence PGC-1α activity within RPE cells_

Together, these computational analyses provide a foundational, hypothesis-generating framework for understanding fenofibrate’s potential to modulate mitochondrial and AMD-relevant pathways in RPE cells that we hope can aid future research.