Moroi, Sayoko E

Purpose: To identify reasons for variable intraocular pressure (IOP) responses to latanoprost and timolol in healthy volunteers and to generate the control group as part of Eye Dynamics and Engineering Network. Methods: In this multicenter, randomized, crossover study (NCT01677507), both eyes of 106 healthy subjects (212 eyes) were treated with latanoprost or timolol for 7 days, with a 6-week washout between treatments. Ocular biometrics, tonometry, and aqueous humor dynamics (AHD) were assessed at baseline and day 8 of each treatment. Subjects were divided into responders and nonresponders using cutoffs of >15% or >10% IOP reduction. Treatment effects and correlations were analyzed with paired t-tests. Results: More subjects responded to latanoprost (54%) than timolol (27%) at >15% cutoff ( p < 0.01). Responders had higher mean baseline IOP than nonresponders for both drugs at both cutoffs ( p < 0.01). Among timolol nonresponders ( n = 56), 39% responded to latanoprost in both eyes, 20% in one eye, and 41% in neither. Among latanoprost nonresponders ( n = 31), 13% responded to timolol in both eyes, 13% in one eye, and 74% in neither. Latanoprost increased uveoscleral outflow, while timolol reduced aqueous flow and outflow facility. Low baseline uveoscleral outflow was associated with latanoprost response. Conclusions: Higher baseline IOP predicted better responses to both drugs. Higher baseline uveoscleral outflow predicted nonresponse to latanoprost. No AHD differences were linked to the timolol response. Timolol nonresponders were often responsive to latanoprost, but not vice versa.

Abstract Objective: Several attributes of female reproductive history, including age at natural menopause (ANM), have been related to primary open-angle glaucoma (POAG). We assembled 18 previously reported common genetic variants that predict ANM to determine their association with ANM or POAG. Methods: Using data from the Nurses’ Health Study (7,143 women), we validated the ANM weighted genetic risk score in relation to self-reported ANM. Subsequently, to assess the relation with POAG, we used data from 2,160 female POAG cases and 29,110 controls in the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database (NEIGHBORHOOD), which consists of 8 datasets with imputed genotypes to 5.6+ million markers. Associations with POAG were assessed in each dataset, and site-specific results were meta-analyzed using the inverse weighted variance method. Results: The genetic risk score was associated with self-reported ANM (P = 2.2 × 10–77) and predicted 4.8% of the variance in ANM. The ANM genetic risk score was not associated with POAG (Odds Ratio (OR) = 1.002; 95% Confidence Interval (CI): 0.998, 1.007; P = 0.28). No single genetic variant in the panel achieved nominal association with POAG (P ≥0.20). Compared to the middle 80 percent, there was also no association with the lowest 10th percentile or highest 90th percentile of genetic risk score with POAG (OR = 0.75; 95% CI: 0.47, 1.21; P = 0.23 and OR = 1.10; 95% CI: 0.72, 1.69; P = 0.65, respectively). Conclusions: A genetic risk score predicting 4.8% of ANM variation was not related to POAG; thus, genetic determinants of ANM are unlikely to explain the previously reported association between the two phenotypes.