Research Overview

Glaucoma is a complex, multifactorial disease affecting an estimated 80 million people worldwide and is the leading cause of irreversible blindness (1). It is a significant health and economic burden. Age, genetics, and high intraocular pressure (IOP) are all considerable risk factors. Glaucoma is characterised by progressive dysfunction and loss of retinal ganglion cells (RGCs). RGCs are the output neurons of the retina, the axons of which become the optic nerve before integrating with key visual centres in the brain. RGCs sit on a metabolic knife-edge during times of stress that may be exacerbated by aging and genetic impairment (2–4). During these periods the viability of RGCs is reliant on mitochondria to maintain cellular homeostasis and bioenergetic needs. Emerging research suggests that a systemic vulnerability to mitochondrial abnormalities exists in glaucoma patients. Genomic analysis has demonstrated increased mitochondrial DNA content and a spectrum of mitochondrial DNA mutations in glaucoma patients (5, 6). These abnormalities are also present in leukocytes (7), suggesting a systemic susceptibility to metabolic defects (as opposed to mitochondrial changes in the eye as a consequence of high IOP). Such systemic susceptibility is expected to increase glaucoma susceptibility with age. However, the role of mitochondrial health in glaucoma is yet to be fully elucidated.

Glaucoma is not a unique neurodegeneration in having a mitochondrial component. Glaucoma shares a slowly degenerating pathophysiology with other common age-related neurodegenerations such as Parkinson’s and Alzheimer’s disease and similarities between glaucoma and other neurodegenerations have already been studied (e.g. progressive synaptic and dendritic atrophy preceding cell loss (8–11)). Thus, discoveries in the field of glaucoma are likely to be of benefit to other common neurodegenerations. So far only strategies to alleviate elevated IOP have been taken to the clinic. These therapeutics do not treat the neurodegenerative component of glaucoma. Neuroprotective strategies are of great therapeutic need. Strategies that increase neuronal resilience to disease-related stresses are likely to be of therapeutic benefit in glaucoma and possibly other age-related neurodegenerations and ophthalmic diseases.

We have previously discovered metabolic dysfunction and mitochondrial abnormalities occurring prior to neurodegeneration in a mouse model of inherited glaucoma (12). Importantly, many of these changes are age-dependent and may sensitise RGCs leaving them vulnerable to the insults of elevated IOP. One such molecule is the essential REDOX cofactor and metabolite NAD, which declines in the retina in an age-dependent manner. NAD is well established to be a potent mediator of axon (and thus neuronal) survival following damaging disease-related insults (12–14), and is thus an ideal target for neuroprotection in glaucoma. To this end, supplementing NAD by administration of nicotinamide (the amide form of vitamin B3, an early precursor for NAD) or through gene therapy (Nmnat1, a terminal enzyme for NAD production in the soma) robustly protects from age-related neuronal metabolic decline and prevents glaucoma in a chronic mouse model of glaucoma (DBA/2J mouse).


The finding that NAD can modulate both disease- and age- related changes in RGCs highlights the importance of testing other genetic factors that influence NAD levels in RGCs. We are extending these findings by elucidating to what degree RGC vulnerability lies in NAD metabolism in normal RGC health and during disease.

Our goal-term aim of my group is to develop clinically translatable neuroprotective strategies by studying the neurobiology of complex diseases.

1. Y.-C. Tham et al., Ophthalmology. 121, 2081–2090 (2014).
2. P. A. Williams et al., Brain. 135, 493–505 (2012).
3. P. A. Williams et al., Brain. 133, 2942–2951 (2010).
4. M. P. Mattson, T. Magnus, Nat. Rev. Neurosci. 7, 278–294 (2006).
5. V. Chrysostomou et al., Curr. Opin. Pharmacol. 13, 12–15 (2013).
6. P. Sundaresan et al., Genet. Med. 17, 279–284 (2014).
7. N. J. Van Bergen et al., PLoS One. 10, e0140919 (2015).
8. P. A. Williams et al., Mol. Neurodegener. 11, 26 (2016).
9. P. A. Williams et al., PLoS One. 8, e72282 (2013).
10. P. A. Williams et al., Neurobiol. Aging. 34, 1799–1806 (2013).
11. F. Z. Javaid et al., Front. Neurol. 7, 55 (2016).
12. P. A. Williams et al., Science. 355, 756–760 (2017).