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Grant Proposal

With professional guidence from Dr. Geoffrey F. Woodman, I constructed this grant proposal that aims to understand ipRGC Vulnerability Through Metabolic and Aging Mechanisms.

(2025 Spring)

Specific Aims:

  1. To identify if different ipRGC subtypes show different vulnerability to aging by separating M1 versus non-M1 functional signals using chromatic pupillometry.

  2. To determine if blocking mitochondria function acutely harms melanopsin signaling by measuring the post-illumination pupil response (PIPR) during controlled low oxygen (hypoxia).

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Innovation

  1. This project explores two fundamental but unstudied areas of ipRGC function: 1. their subtype-specific vulnerability in aging and 2. how they handle metabolic stress. Previous work mapped ipRGCs and their basic light responses, but no studies have directly tested how these cells withstand low energy supply in vivo (Aim 2) or if aging functionally affects specific ipRGC subtypes differently, as measured by pupil responses (Aim 1). My approach is innovative in three ways:

  2. Subtype-Specific Aging Dissected via Pupillometry (Aim 1): By comparing pupil responses driven by stimuli thought to rely more on M1 cells (PIPR) versus those potentially relying more on non-M1 cells (responses to low-contrast motion), I can functionally test if aging affects these pathways differently. This could explain real-world observations, like why some older individuals maintain good circadian timing (M1 function) even if other aspects of visual processing decline.

  3. First In Vivo Test of ipRGC Metabolic Dependence (Aim 2): I use mild, temporary low oxygen (hypoxia) to create controlled mitochondrial stress while measuring the PIPR. This provides a non-invasive way to check ipRGC metabolic sensitivity in humans. If PIPR weakens during hypoxia, it reveals an energy limit relevant to diseases like glaucoma and Alzheimer’s. If PIPR stays strong, it suggests ipRGCs have special ways to keep working (like using glycolysis more).

  4. Unified Mechanism: Linking Vulnerability Patterns: The two aims connect through the question: What makes ipRGCs vulnerable or resilient? If older adults show mainly non-M1 functional decline (Aim 1, alternative hypothesis) and the PIPR resists hypoxia (Aim 2, my hypothesis), it might mean M1 resilience is linked to special metabolic adaptations. If PIPR declines with age (Aim 1, alternative hypothesis) and is sensitive to hypoxia (Aim 2, alternative hypothesis), it would suggest mitochondrial health is key to both aging and disease vulnerability in these cells.

  5. This work shifts our view of ipRGCs from simple light detectors to dynamic, metabolically specialized cells with different subtype roles, relevant to retinal diseases and circadian health. No previous study has combined in vivo metabolic stress tests with subtype-targeting pupillometry to explore ipRGC mechanisms.

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Figure 1: Number of ipRGC subtypes in the human retina with aging.

Image obtained from Esquiva et al., 2017

General Research Design and Methods

  1. This study uses a combination of comparing groups (cross-sectional, Aim 1) and testing individuals under different conditions (within-subjects, Aim 2), using chromatic pupillometry with specific stimuli and protocols.

  2. Study Population

  3. Aim 1: Approximately 30 healthy Young Adults (YA, 20-30 years) and 30 healthy Older Adults (OA, ≥ 65 years).

  4. Aim 2: Approximately 20 YA participants (can be from the Aim 1 YA group).

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Procedure

Aim 1: Participants (YA, OA) attend one session including screening, consent, lens check, dark adaptation, and pupillometry tests using M1-biased, non-M1-biased, and red control stimuli (order mixed).

Aim 2: Participants (YA) attend a separate session. After screening/consent, baseline pupillometry (M1-biased stimulus) done while breathing normal air. Then, they breathe 15% O₂ for 10 minutes while pupillometry is repeated. Finally, pupillometry is measured again at intervals (e.g., 0, 30, 60 min) after returning to normal air. Safety is monitored throughout.

Data Analysis Preview

Pupil data cleaned (removing blinks etc.) and adjusted for baseline (Kret & Sjak-Shie, 2019).

Aim 1: Compare YA vs. OA on PIPR results and motion-driven results using statistical tests that account for baseline pupil size and lens density. Look for an interaction: does age affect the two response types differently?

Aim 2: Compare PIPR results during normal air vs. low oxygen vs. recovery using repeated measures tests. Calculate percentage change during hypoxia.

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Writing Example (Aim 1)

Aim 1: Characterize subtype-specific ipRGC vulnerability in healthy aging by dissociating M1 versus non-M1 functional contributions using chromatic pupillometry

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Rationale:

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Structural studies suggest non-M1 ipRGC subtypes might be more vulnerable to aging than M1 cells in humans (Esquiva et al., 2017; La Morgia et al., 2017). Functionally, M1 cells are thought to mainly signal overall light levels (driving PIPR), while non-M1 cells may contribute more to processing dynamic visual information (Zhao et al., 2022). This raises a key untested question: does healthy aging cause a specific functional decline in these non-M1 pathways while sparing M1 function? Or is any functional decline more general across subtypes? Aim 1 uses specific pupil tests designed to probe these potentially different pathways to find out.

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Research Design

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I will compare Young Adults (YA) and Older Adults (OA) using two main pupillometry tests: 1) the M1-biased bright blue flash measuring PIPR, and 2) the potentially non-M1-biased low-contrast moving grating measuring transient pupil constriction. A red flash test controls for general cone pathway function. The main comparison is whether the effect of age differs between the PIPR result and the moving grating result, after accounting for lens changes.

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Expected Outcome

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My primary hypothesis favors uniform functional decline or resilience across pathways relevant to pupillary control. The predicted outcome is that the results show either no significant age effects on either measure, or a similar amount of decline for both the PIPR and the motion-driven response, after accounting for lens density. Seeing similar age effects on the two measures would support the hypothesis. This would suggest that, for pupil control, ipRGC functional aging appears uniform across these tests, pointing towards general retinal aging factors rather than specific subtype vulnerability driving functional changes detectable by these pupillometric methods.

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Alternative Outcome

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Alternatively, aging might affect subtypes differently, impacting function selectively. If the results show a significant age-related reduction (OA < YA) in the pupil response to the moving grating stimulus, while the PIPR amplitude shows little or no significant age difference between the groups (after accounting for lens density), this pattern would support the alternative hypothesis. This would tell us that healthy aging functionally affects ipRGC pathways differently, possibly weakening the processing of dynamic information (non-M1 function) more than basic light detection (M1 function), matching hints from structural studies and suggesting a subtype-specific functional vulnerability.

Work Cited:

  1. Adhikari, P., Zele, A. J., Thomas, R., Feigl, B., Rukmini, A. V., & Milea, D. (2019). Effects of low and moderate refractive errors on chromatic pupillometry. Scientific Reports, 9(1), 4945.

  2. Adhikari, P., Zele, A. J., & Feigl, B. (2015). The post-illumination pupil response (PIPR). Investigative Ophthalmology & Visual Science, 56(7), 3838–3849.

  3. Esquiva, G., Lax, P., Pérez-Santonja, J. J., García-Fernández, J. M., & Cuenca, N. (2017). Loss of Melanopsin-Expressing Ganglion Cell Subtypes and Dendritic Degeneration in the Aging Human Retina. Frontiers in Aging Neuroscience, 9, 79.

  4. Estevez, M. E., Fogerson, P. M., Ilardi, M. C., et al. (2012). Form and function of the M4 cell, an intrinsically photosensitive retinal ganglion cell type. Journal of Neuroscience, 32(42), 14703-14717.

  5. Feigl, B., & Zele, A. J. (2016). Melanopsin-mediated post-illumination pupil response in the peripheral retina. Journal of Vision, 16(8), 5.

  6. Feigl, B., Dumpala, S., Kerr, G. K., & Zele, A. J. (2020). Melanopsin cell dysfunction is involved in sleep disruption in Parkinson's disease. Journal of Parkinson's Disease, 10(4), 1467–1476.

  7. Fu, Y., Zhong, H., Wang, M. H., Luo, D. G., Liao, H. W., Maeda, H., Hattar, S., Frishman, L. J., & Yau, K. W. (2005). Non-image-forming ocular photoreception in vertebrates. Current Biology, 15(24), R1001–R1008.

  8. Hannibal, J., Christiansen, A. T., Heegaard, S., Fahrenkrug, J., & Kiilgaard, J. F. (2017). Melanopsin expressing human retinal ganglion cells: subtypes, distribution, and intraretinal connectivity. Journal of Comparative Neurology, 525(8), 1934–1961.

  9. Hattar, S., Liao, H. W., Takao, M., Berson, D. M., & Yau, K. W. (2002). Melanopsin-containing retinal ganglion cells: architecture, projections, and intrinsic photosensitivity. Science, 295(5557), 1065–1070.

  10. Jain, I. H., Calvo, S. E., Markhard, M. K., et al. (2020). Genetic screen for cell fitness in high or low oxygen highlights mitochondrial metabolism. Cell Reports, 30(5), 1417-1430.e5.

  11. Joo, Y. E., Lee, H. J., Allen, A. E., et al. (2022). Diurnal variation in human pupillary light reflex regulated by the interplay between melanopsin and cones. Journal of Biological Rhythms, 37(4), 425-438.

  12. Joyce, D. S., Feigl, B., Kerr, G., Roeder, L., & Zele, A. J. (2018). Melanopsin-mediated pupil function is impaired in Parkinson's disease. Scientific Reports, 8(1), 7796.

  13. Kankipati, L., Girkin, C. A., & Gamlin, P. D. (2011). Intrinsically photosensitive (melanopsin) retinal ganglion cell function in glaucoma. Investigative Ophthalmology & Visual Science, 52(6), 3702–3707.

  14. Kardon, R. H., Anderson, S. C., Damarjian, T. G., Grace, E. M., Motzko, E., & Tobin, E. (2009). Post-illumination pupil response in subjects without ocular disease. Investigative Ophthalmology & Visual Science, 50(11), 5087–5093.

  15. Kret, M. E., & Sjak-Shie, E. E. (2019). Preprocessing pupil size data: Guidelines and code. Behavior Research Methods, 51(3), 1336–1342.

  16. La Morgia, C., Ross-Cisneros, F. N., Sadun, A. A., Hannibal, J., Munarini, A., Mantovani, V., ... & Carelli, V. (2010). Melanopsin retinal ganglion cells are resistant to neurodegeneration in mitochondrial optic neuropathies. Brain, 133(8), 2426-2438.

  17. La Morgia, C., Ross-Cisneros, F. N., Koronyo, Y., Hannibal, J., Gallassi, R., Cantalupo, G., ... & Carelli, V. (2016). Melanopsin retinal ganglion cell loss in Alzheimer disease. Annals of Neurology, 79(1), 90–109.

  18. La Morgia, C., Ross-Cisneros, F. N., Sadun, A. A., & Carelli, V. (2017). Retinal ganglion cells and circadian rhythms in Alzheimer's disease, Parkinson's disease, and beyond. Frontiers in Neurology, 8, 162.

  19. La Morgia, C., Romagnoli, M., Pizza, F., Biscarini, F., Filardi, M., Donadio, V., ... & Carelli, V. (2022). Chromatic Pupillometry in isolated rapid eye movement sleep behavior disorder. Movement Disorders, 37(1), 205–210.

  20. Oosterman, J. M., van Someren, E. J., Vogels, R. L., Van Harten, B., & Scherder, E. J. (2009). Fragmentation of the rest-activity rhythm correlates with age-related cognitive deficits. Journal of Sleep Research, 18(1), 129–135.

  21. Park, J. C., Moura, A. L., Raza, A. S., Rhee, D. W., Kardon, R. H., & Hood, D. C. (2011). Toward a clinical protocol for assessing rod, cone, and melanopsin contributions to the human pupil response. Investigative Ophthalmology & Visual Science, 52(9), 6624–6635.

  22. Renna, J. M., St. Hilaire, M. A., & Czeisler, C. A. (2021). Melanopsin may be the cycling photoreceptor that calibrates the circadian clock to seasonal changes in photoperiod. PNAS, 118(16), e2018484118.

  23. Romagnoli, M., Amore, G., Avanzini, P., Carelli, V., & La Morgia, C. (2024). Chromatic pupillometry for evaluating melanopsin retinal ganglion cell function in Alzheimer's disease and other neurodegenerative disorders: a review. Frontiers in Psychology, 14, 1295129.

  24. Romagnoli, M., Stanzani Maserati, M., De Matteis, M., Capellari, S., Carbonelli, M., Amore, G., ... & La Morgia, C. (2020). Chromatic Pupillometry findings in Alzheimer's disease. Frontiers in Neuroscience, 14, 780.

  25. Rukmini, A. V., Milea, D., & Gooley, J. J. (2019). Chromatic Pupillometry methods for assessing photoreceptor health in retinal and optic nerve diseases. Frontiers in Neurology, 10, 76.

  26. Steiner, O., de Zeeuw, J., Stotz, S., Bes, F., & Kunz, D. (2022). Post-illumination pupil response as a biomarker for cognition in alpha-Synucleinopathies. Journal of Parkinson's Disease, 12(2), 593–598.

  27. Weng, S., Wong, K. Y., & Berson, D. M. (2009). Circadian modulation of melanopsin-driven light response in rat ganglion-cell photoreceptors. PLoS ONE, 4(5), e5469.

  28. Wu, Y. H., & Swaab, D. F. (2007). Disturbance and strategies for reactivation of the circadian rhythm system in aging and Alzheimer's disease. Sleep Medicine, 8(6), 623–636.

  29. Zhao, X., et al. (2022). Intrinsically photosensitive retinal ganglion cells mediate spatial contrast perception. Nature Communications, 13, 749.

  30. Zele, A. J., Feigl, B., Smith, S. S., & Markwell, E. L. (2011). The circadian response of intrinsically photosensitive retinal ganglion cells. PLoS ONE, 6(3), e17860.

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