What causes glaucoma? Are there new treatments? Why don't the treatments work for me? Will I go blind [from glaucoma]? Will my children get glaucoma? These questions from my patients and their family members motivate me to provide answers based on evidence from clinical experience and research. Having worked at the same institution since completing fellowship training, I am privileged to have been a part of the health care experience of many patients who range in age from infancy to over 100 years old and whose clinical findings span the spectrum of suspected glaucoma to end-stage disease. My weakness is seeing every patient as a unique in vivo laboratory. Each represents an opportunity for me to gain wisdom and make progress toward answering the aforementioned questions. At the Kellogg Eye Center, I have been able to identify unusual drug reactions, wound healing problems, and interesting comorbid diseases. These discoveries have led to publications that not only helped to advance my career but, more importantly, augmented the knowledge of the ophthalmic community.,/p>
In the daily clinical care of patients with glaucoma, physicians assess individual patients' IOP response to an intervention via a trial-and-error approach to achieve a desired target range based on limited data points obtained during office hours. As a result, clinicians have yet to identify sensitive and specific biomarkers that predict the IOP-based outcomes of glaucoma therapeutic response and progression. The inability to predict IOP response is a critical barrier to improving glaucoma treatment outcomes.
I have begun to address this obstacle by taking a quantitative trait approach to studying IOP. Specifically, I aim to answer the following two questions. First, among patients who adhere to prescribed medical therapy, who are the nonresponders? Predictive biomarkers for drug response would greatly reduce the time wasted on ineffective therapies, which increase health care costs through the changing of treatment and repeated office visits to assess those alterations. Second, are there biomarkers that characterize patients who experience large IOP fluctuations under treatment? More detailed measurements of aqueous humor dynamics will identify these factors' contribution to large variations in IOP. After determining these details, I will be able to model IOP fluctuation.
In undertaking this integrated quantitative trait approach, I am fortunate to have the support and collaborative effort of colleagues who are experts in glaucoma genetics and aqueous humor dynamics, including Janey Wiggs, MD, PhD; Arthur Sit, MD; and Carol Toris, PhD. My research focus builds on my earlier results showing that the b-2 adrenoreceptor gene is not a glaucoma disease gene but does show population frequency differences.1 My work is further informed by past heritability studies of IOP, earlier epidemiology studies, and the more recent genome-wide association study designs. With the amazing resources of both clinical data and genotypes, I am excited that our team effort will address physicians' inability to predict IOP response to interventions. I anticipate that our results will promote the identification of the biomarkers of IOP-based treatment outcomes.
Section Editor Tony Realini, MD, MPH, is an associate professor of ophthalmology at West Virginia University Eye Institute in Morgantown. Dr. Realini may be reached at (304) 598-6884; realinia@wvuh.com.
Sayoko E. Moroi, MD, PhD, is a professor, glaucoma service chief, and glaucoma fellowship director at the W. K. Kellogg Eye Center, University of Michigan Hospital and Health Systems, in Ann Arbor, Michigan. Dr. Moroi may be reached at (734) 763-3732; smoroi@med.umich.edu.
- McLaren N, Reed DM, Musch DC, et al. Evaluation of the beta2-adrenergic receptor gene as a candidate glaucoma gene in 2 ancestral populations. Arch Ophthalmol. 2007;125(1):105-111.
