Intraocular pressure (IOP) monitoring plays a critical role in the management of glaucoma, but traditionally relies on isolated measurements obtained during office hours. These measurements are a poor representation of dynamic IOP fluctuations occurring over a 24-hour period1 and this unrecognized variability may contribute to progressive glaucomatous neurodegeneration.2 Recent intraocular sensor device studies have demonstrated substantial long-term IOP variability in addition to short-term fluctuations.3
In this cross-sectional study, Qassim et al. used mixed-effects linear regression modeling to explore the association between a validated, weighted IOP polygenic risk score (PRS),4 derived from 146 statistically independent IOP-associated single nucleotide polymorphisms, and a variety of ambulatory diurnal IOP measurements, using the Icare HOME (Icare Oy, Vanda, Finland) rebound tonometer, to determine whether genetic markers of high IOP provide useful predictive information about out-of-office IOP measurements.
Eyes from participants in the highest IOP PRS quintile had significantly higher maximum early morning IOP (+4.3 mmHg) and mean out-of-office IOP (+2.7 mmHg) compared to those in the lowest quintile and after adjustment for central corneal thickness (CCT) and age. Additionally, the IOP PRS was able to identify individuals with early morning IOP spikes not otherwise detected during in-office hours.
There have been huge recent advances in our understanding of the genetic causes of IOP variation and glaucoma risk. Qassim et al. are to be commended for examining the potential clinical utility of these genetic findings. Genome-wide association studies are frequently criticized for their lack of translational impact and more studies like this are needed.
Genetic risk stratification may prove to be a useful tool in the identification of susceptibility to out-of-office IOP elevation and could guide additional interventions and aid IOP control in high-risk patients. However, the findings from this study require validation in non-European populations and replication in additional cohorts. Additionally, prospective studies will be needed to determine whether knowledge of an individual's PRS meaningfully impacts their disease trajectory using hard endpoints. It has previously been demonstrated that knowledge of a key IOP-influencing genetic variant in TMCO1 can improve prediction of which patients with ocular hypertension convert to glaucoma.5 This current study adds to the evidence supporting a role for more personalized glaucoma care being enabled by genomic prediction.