Dry eye disease (DED) is among the most common eye diseases and is becoming increasingly prevalent. Its symptoms cause a long-term decline in patients’ health-related quality of life (HRQL). Inconsistencies often occur between the clinical findings and the subjective symptoms of DED. Therefore, a holistic, balanced, and quantitative evaluation of the subjective symptoms and HRQL using patient-reported outcome questionnaires, in addition to clinical findings, is crucial for accurate DED assessment in patients. This paper reviewed the characteristics of current dry eye questionnaires, including their objectives, number of questions, inclusion of HRQL-related items, and whether they were properly evaluated for psychometric properties. Twenty-four questionnaires were identified; among them, the following six questionnaires that included items assessing HRQL and were properly evaluated for psychometric properties are recommended: the Ocular Surface Disease Index, Impact of Dry Eye in Everyday Life, Dry Eye-Related Quality-of-life Score, University of North Carolina Dry Eye Management Scale, Chinese version of Dry Eye-Related Quality of Life, and 25-Item National Eye Institute Visual Function Questionnaire. Dry eye questionnaires have different objectives and are available in different languages. Therefore, medical practitioners should confirm the characteristics of applicable questionnaires before selecting the most appropriate ones.

The prevalence of dry eye disease (DED) is increasing worldwide, and its diagnosis often needs dedicated reagents and machines. We investigated the usefulness of maximum blink interval (MBI) (the length of time that participants could keep their eyes open) in screening for DED. This cross-sectional study included 292 patients (194 with DED and 98 without DED) recruited between September 2016 and September 2017. We compared the MBI between patients with and without DED; examined correlations between MBI and other clinical features of DED, including subjective symptoms (Dry Eye-Related Quality-of-Life Score), tear film breakup time (TFBUT), cornea fluorescence score (CFS), and Schirmer test I value; and determined the optimal cutoff value of MBI to suspect DED using a receiver operating characteristic (ROC) analysis. The MBI was significantly shortened in DED group compared to the non-DED group (10.0 ± 9.1 vs. 24.3 ± 38.2 seconds, p < 0.001). TFBUT was strongly positively correlated with MBI (r = 0.464), whereas CFS was negatively correlated with MBI (r = −0.273). The area under the ROC curve was 0.677, and the optimal MBI cutoff value was 12.4 seconds, providing a sensitivity of 82.5% and specificity of 51.0% to suspect DED. In conclusion, MBI may be a simple, useful test for screening DED.

Multidimensional integrative data analysis of digital phenotyping is crucial for elucidating the pathologies of multifactorial and heterogeneous diseases, such as the dry eye (DE). This crowdsourced cross-sectional study explored a novel smartphone-based digital phenotyping strategy to stratify and visualize the heterogenous DE symptoms into distinct subgroups. Multidimensional integrative data were collected from 3,593 participants between November 2016 and September 2019. Dimension reduction via Uniform Manifold Approximation and Projection stratified the collected data into seven clusters of symptomatic DE. Symptom profiles and risk factors in each cluster were identified by hierarchical heatmaps and multivariate logistic regressions. Stratified DE subgroups were visualized by chord diagrams, co-occurrence networks, and Circos plot analyses to improve interpretability. Maximum blink interval was reduced in clusters 1, 2, and 5 compared to non-symptomatic DE. Clusters 1 and 5 had severe DE symptoms. A data-driven multidimensional analysis with digital phenotyping may establish predictive, preventive, personalized, and participatory medicine.

Background: Discontinuation of contact lens use is mainly caused by contact lens–associated dry eye. It is crucial to delineate contact lens–associated dry eye's multifaceted nature to tailor treatment to each patient’s individual needs for future personalized medicine. Objective: This paper aims to quantify and stratify individual subjective symptoms of contact lens–associated dry eye and clarify its risk factors for future personalized medicine using the smartphone app DryEyeRhythm (Juntendo University). Methods: This cross-sectional study included iPhone (Apple Inc) users in Japan who downloaded DryEyeRhythm. DryEyeRhythm was used to collect medical big data related to contact lens–associated dry eye between November 2016 and January 2018. The main outcome measure was the incidence of contact lens–associated dry eye. Univariate and multivariate adjusted odds ratios of risk factors for contact lens–associated dry eye were determined by logistic regression analyses. The t-distributed Stochastic Neighbor Embedding algorithm was used to depict the stratification of subjective symptoms of contact lens–associated dry eye. Results: The records of 4454 individuals (median age 27.9 years, SD 12.6), including 2972 female participants (66.73%), who completed all surveys were included in this study. Among the included participants, 1844 (41.40%) were using contact lenses, and among those who used contact lenses, 1447 (78.47%) had contact lens–associated dry eye. Multivariate adjusted odds ratios of risk factors for contact lens–associated dry eye were as follows: younger age, 0.98 (95% CI 0.96-0.99); female sex, 1.53 (95% CI 1.05-2.24); hay fever, 1.38 (95% CI 1.10-1.74); mental illness other than depression or schizophrenia, 2.51 (95% CI 1.13-5.57); past diagnosis of dry eye, 2.21 (95% CI 1.63-2.99); extended screen exposure time >8 hours, 1.61 (95% CI 1.13-2.28); and smoking, 2.07 (95% CI 1.49-2.88). The t-distributed Stochastic Neighbor Embedding analysis visualized and stratified 14 groups based on the subjective symptoms of contact lens–associated dry eye. Conclusions: This study identified and stratified individuals with contact lens–associated dry eye and its risk factors. Data on subjective symptoms of contact lens–associated dry eye could be used for prospective prevention of contact lens–associated dry eye progression.

Hereditary retinal degenerations (HRDs) are Mendelian diseases characterized by progressive blindness and caused by ultra-rare mutations. In a genomic screen of 331 unrelated Japanese patients, we identify a disruptive Alu insertion and a nonsense variant (p.Arg1933*) in the ciliary gene RP1, neither of which are rare alleles in Japan. p.Arg1933* is almost polymorphic (frequency = 0.6%, amongst 12,000 individuals), does not cause disease in homozygosis or heterozygosis, and yet is significantly enriched in HRD patients (frequency = 2.1%, i.e., a 3.5-fold enrichment; p-value = 9.2 × 10⁻⁵). Familial co-segregation and association analyses show that p.Arg1933* can act as a Mendelian mutation in trans with the Alu insertion, but might also associate with disease in combination with two alleles in the EYS gene in a non-Mendelian pattern of heredity. Our results suggest that rare conditions such as HRDs can be paradoxically determined by relatively common variants, following a quasi-Mendelian model linking monogenic and complex inheritance.