Myopia progression following 0.01% atropine cessation in Australian children: Findings from the Western Australia - Atropine for the Treatment of Myopia (WA-ATOM) study.

BACKGROUND: A rebound in myopia progression following cessation of atropine eyedrops has been reported, yet there is limited data on the effects of stopping 0.01% atropine compared to placebo control. This study tested the hypothesis that there is minimal rebound myopia progression after cessation of 0.01% atropine eyedrops, compared to a placebo. METHODS: Children with myopia (n = 153) were randomised to receive 0.01% atropine eyedrops or a placebo (2:1 ratio) daily at bedtime during the 2-year treatment phase of the study. In the third year (wash-out phase), all participants ceased eyedrop instillation. Participants underwent an eye examination every 6 months, including measurements of spherical equivalent (SphE) after cycloplegia and axial length (AL). Changes in the SphE and AL during the wash-out phase and throughout the 3 years of the study (treatment + wash-out phase) were compared between the treatment and control groups. RESULTS: During the 1-year wash-out phase, SphE and AL progressed by -0.41D (95% CI = -0.33 to -0.22) and +0.20 mm (95% CI = -0.46 to -0.36) in the treatment group compared to -0.28D (95% CI = 0.11 to 0.16) and +0.13 mm (95% CI = 0.18 to 0.21) in the control group. Progression in the treatment group was significantly faster than in the control group (p = 0.016 for SphE and <0.001 for AL). Over the 3-year study period, the cumulative myopia progression was similar between the atropine and the control groups. CONCLUSIONS: These findings showed evidence of rapid myopia progression following cessation of 0.01% atropine. Further investigations are warranted to ascertain the long-term effects of atropine eyedrops.

Associations of 12-year sleep behaviour trajectories from childhood to adolescence with myopia and ocular biometry during young adulthood.

PURPOSE: Cross-sectional studies have variably reported that poor sleep quality may be associated with myopia in children. Longitudinal data, collected over the ages when myopia develops and progresses, could provide new insights into the sleep-myopia paradigm. This study tested the hypothesis that 12-year trajectories of sleep behaviour from childhood to adolescence is associated with myopia during young adulthood. METHODS: At the 5-, 8-, 10-, 14- and 17-year follow-ups of the longitudinal Raine Study, which has been following a cohort since their birth in 1989-1992, participants' parents/guardians completed the Child Behaviour Checklist questionnaire (CBCL), which collected information on their child's sleep behaviour and quality. The CBCL includes six questions measuring sleep behaviour, which parents rated as 0 = not true, 1 = somewhat/sometimes true, or 2 = very/often true. Scores were summed at each follow-up to form a composite "sleep behaviour score". Latent Class Growth Analysis (LCGA) was used to classify participants according to their 12-year trajectory of sleep behaviour. At the 20-year follow-up, an eye examination was performed which included cycloplegic autorefraction and axial length measurement. RESULTS: The LCGA identified three clusters of participants based on their trajectory of sleep behaviour: those with minimal' (43.6% of the total Raine Study sample), 'declining' (48.9%), or 'persistent' (7.5%) sleep problems. A total of 1194 participants had ophthalmic data and longitudinal sleep data available for analysis (47.2% female, 85.6% Caucasian). No significant differences were observed in regards to age, sex, ethnicity or ocular parameters between trajectory groups. Unadjusted and fully adjusted analyses demonstrated that sleep problem behaviour was not significantly associated with changes in refractive error, axial length or corneal radius. CONCLUSIONS: Our findings do not support the hypothesis that there is an association between sleep behaviour and myopia. Future longitudinal studies should explore sleep trajectory data pre- and post-myopia diagnosis to confirm our results.

Low-concentration atropine eyedrops for myopia control in a multi-racial cohort of Australian children: A randomised clinical trial.

BACKGROUND: To test the hypothesis that 0.01% atropine eyedrops are a safe and effective myopia-control approach in Australian children. METHODS: Children (6-16 years; 49% Europeans, 18% East Asian, 22% South Asian, and 12% other/mixed ancestry) with documented myopia progression were enrolled into this single-centre randomised, parallel, double-masked, placebo-controlled trial and randomised to receive 0.01% atropine (n = 104) or placebo (n = 49) eyedrops (2:1 ratio) instilled nightly over 24 months (mean index age = 12.2 ± 2.5 and 11.2 ± 2.8 years, respectively). Outcome measures were the changes in spherical equivalent (SE) and axial length (AL) from baseline. RESULTS: At 12 months, the mean SE and AL change from baseline were -0.31D (95% confidence interval [CI] = -0.39 to -0.22) and 0.16 mm (95%CI = 0.13-0.20) in the atropine group and -0.53D (95%CI = -0.66 to -0.40) and 0.25 mm (95%CI = 0.20-0.30) in the placebo group (group difference p ≤ 0.01). At 24 months, the mean SE and AL change from baseline was -0.64D (95%CI = -0.73 to -0.56) and 0.34 mm (95%CI = 0.30-0.37) in the atropine group, and -0.78D (95%CI = -0.91 to -0.65) and 0.38 mm (95%CI = 0.33-0.43) in the placebo group. Group difference at 24 months was not statistically significant (p = 0.10). At 24 months, the atropine group had reduced accommodative amplitude and pupillary light response compared to the placebo group. CONCLUSIONS: In Australian children, 0.01% atropine eyedrops were safe, well-tolerated, and had a modest myopia-control effect, although there was an apparent decrease in efficacy between 18 and 24 months, which is likely driven by a higher dropout rate in the placebo group.

Associations of sleep apnoea with glaucoma and age-related macular degeneration: an analysis in the United Kingdom Biobank and the Canadian Longitudinal Study on Aging.

BACKGROUND: Sleep apnoea, a common sleep-disordered breathing condition, is characterised by upper airway collapse during sleep resulting in transient hypoxia, hypoperfusion of the optic nerve, and spike in intracranial pressure. Previous studies have reported conflicting findings on the association of sleep apnoea with glaucoma, and there are limited reports on the link between sleep apnoea and age-related macular degeneration (AMD). METHODS: Middle-aged and older participants from the longitudinal United Kingdom (UK) Biobank (n = 502,505) and the Canadian Longitudinal Study on Aging (CLSA; n = 24,073) were included in this analysis. Participants in the UK Biobank and the CLSA were followed for 8 and 3 years, respectively. Participants with diagnosed glaucoma or AMD at baseline were excluded from the analysis. In the UK Biobank, sleep apnoea and incident cases of glaucoma and AMD were identified through hospital inpatient admission, primary care records, and self-reported data. Multivariable Cox proportional hazards models were used to explore associations of sleep apnoea with incidence of glaucoma or AMD. RESULTS: During the 8-year follow-up in the UK Biobank, glaucoma incidence rates per 1000 person-years were 2.46 and 1.59 for participants with and without sleep apnoea, and the AMD incidence rates per 1000 person-years were 2.27 and 1.42 for participants with and without sleep apnoea, respectively. Multivariable adjusted hazard ratios of glaucoma and AMD risk for sleep apnoea were 1.33 (95% confidence interval [CI] 1.10-1.60, P = 0.003) and 1.39 (95% CI 1.15-1.68, P <  0.001) relative to participants without sleep apnoea. In the CLSA cohort, disease information was collected through in-person interview questionnaires. During the 3-year follow-up, glaucoma incidence rates per 1000 person-years for those with and without sleep apnoea were 9.31 and 6.97, and the AMD incidence rates per 1000 person-years were 8.44 and 6.67, respectively. In the CLSA, similar associations were identified, with glaucoma and AMD odds ratios of 1.43 (95% CI 1.13-1.79) and 1.39 (95% CI 1.08-1.77), respectively, in participants with sleep apnoea compared to those without sleep apnoea (both P <  0.001). CONCLUSIONS: In two large-scale prospective cohort studies, sleep apnoea is associated with a higher risk of both glaucoma and AMD. These findings indicate that patients with sleep apnoea might benefit from regular ophthalmologic examinations.

Change in the prevalence of myopia in Australian middle-aged adults across 20 years.

BACKGROUND: The prevalence of myopia is increasing globally including in Europe and parts of Asia but Australian data are lacking. This study aim described the change in myopia prevalence in middle-aged Australian adults over approximately a 20-year period. METHODS: Two contemporary Western Australian studies (conducted in mid-late 2010s): the coastal-regional Busselton Healthy Ageing Study (BHAS) and the urban Gen1 of the Raine Study (G1RS) were compared to two earlier studies (early-mid 1990s) in Australia: the urban Blue Mountains Eye Study (BMES) and urban/regional Melbourne Visual Impairment Project (MVIP). Refractive error was measured by autorefraction, vertometry, or subjective refraction. Participants (49-70 years) of European descent without self-reported/diagnosed cataract, corneal disease, or refractive or corneal surgery were included. RESULTS: After exclusions, data were available from 2217, 1760, 700, 2987 and 756 participants from BMES, urban MVIP, regional MVIP, BHAS, and G1RS, respectively. The mean age ranged from 57.1 ± 4.6 years in the G1RS to 60.1 ± 6.0 years in the BMES; 44-48% of participants were male. When stratified by location, the contemporary urban G1RS cohort had a higher age-standardised myopia prevalence than the urban MVIP and BMES cohorts (29.2%, 16.4%, and 23.9%, p < 0.001). The contemporary coastal-regional BHAS had a higher age-standardised myopia prevalence than the regional MVIP cohort (19.4% vs. 13.8%, p = 0.001). CONCLUSIONS: We report an increase in myopia prevalence in older adults in Australia born after World War ll compared to cohorts born before, accounting for urban/regional location. The prevalence of myopia remains relatively low in middle-aged Australian adults.

Re-engaging an inactive cohort of young adults: evaluating recruitment for the Kidskin Young Adult Myopia Study.

BACKGROUND: Recent changes in communication technologies, including increased reliance on mobile phones and the internet, may present challenges and/or opportunities to re-engaging inactive study cohorts. We evaluate our ability to recruit participants for the Kidskin Young Adult Myopia Study (KYAMS), a follow-up of the Kidskin Study. METHODS: KYAMS participants were recruited from the Kidskin Study, a sun exposure-intervention study for 5-6 year-olds running from 1995 to 1999 with most recent follow-up in 2005. From 2015 to 2019, the KYAMS used mail-outs, phone calls and social media to contact Kidskin Study participants. Multivariable logistic regression was used to identify variables associated with successful contact of a Kidskin Study participant or family member and KYAMS participation. RESULTS: Of 1695 eligible participants, 599 (35.5%) participants (or a family member) were contacted and 303 (17.9%) participated in the KYAMS. KYAMS participation was more likely in those who participated in the 2005 follow-up (odds ratio [OR] = 5.09, 95% confidence interval [CI]: 3.67-7.06) and had a mobile phone number on record (OR = 2.25, CI: 1.57-3.23). Of those contacted, participants who were the first point of contact (OR = 4.84, CI: 2.89-8.10) and who were contacted by letter in the first (OR = 6.53, CI: 3.35-12.75) or second (OR = 5.77, CI: 2.85-11.67) round were more likely to participate in the KYAMS, compared to contact by landline phone. CONCLUSIONS: We recruited approximately one-fifth of Kidskin Study participants for the KYAMS. Participants were more likely to participate in the KYAMS if they were contacted directly, rather than through a family member, and if they were contacted by invitation letter. TRIAL REGISTRATION: ACTRN12617000812392.

Impact of glaucoma on executive function and visual search.

PURPOSE: Executive function and visual search are linked to a number of activities of daily living including driving and mobility. Using a computerised version of the Trail Making Test B (TMT-B), we compared the executive function and visual search ability of older adults with glaucoma to age-similar controls and identified which visual function tests best predict TMT-B performance. Novel low-contrast and shifting-target variations of the test were incorporated to explore the effects of different levels of test complexity. METHODS: Thirty-one older adults with mild to moderate glaucoma (mean age = 71.2 years [SD 6.9]; better-eye mean deviation [MD]: median = -1.9 dB [IQR = -1.2 to 0.4], worse-eye MD: median = -11.1 dB [IQR = -14.0 to -7.7]) and 24 age-similar controls (mean age = 71.9 years [SD 6.6]) with normal vision participated. The groups were matched in age, sex, and cognitive status (mini-mental state examination [MMSE]). Participants underwent measurements of visual acuity, contrast sensitivity (CS), visual fields, and visual processing speeds using the useful field-of-view (UFoV). Participants then completed four variations of a computerised TMT-B test, with different levels of complexity based on target contrast (high/low-contrast) and shifts in target position (fixed/shifting locations). Linear mixed-effect models were used to explore the effects of group, target contrast and shift on TMT-B completion time. RESULTS: The glaucoma group took 17.3s longer than controls to complete the TMT-B (P = 0.028). All participants took 6.5s longer to complete the low- compared to the high-contrast tests (P = 0.012), and 10.6s longer for the shifting TMT-B compared to the fixed version (P < 0.001). There was no interaction effect between group, contrast, or target shift on completion time. Across all tests and participant groups, longer completion time was associated with slower UFoV processing speeds (divided attention: P = 0.003; selective attention: P = 0.006). Poorer CS was associated with longer completion times for the low (P = 0.007), but not the high-contrast tests. CONCLUSIONS: Our findings suggest that older adults with mild to moderate glaucoma have poorer visual search ability and executive function relative to controls. However, decreasing target contrast or shifting target position did not exacerbate the effects of glaucomatous visual impairment on performance. The UFoV was a strong predictor of TMT-B performance.

Eye Movements of Drivers with Glaucoma on a Visual Recognition Slide Test.

SIGNIFICANCE: Glaucoma has been shown to impair hazard detection ability and increase crash risk compared to controls. Differences in visual search behavior of the driving scene may explain these differences; however, there has been limited investigation of this issue with inconsistent findings. PURPOSE: Through eye movement tracking of older drivers with glaucoma, we explored their visual search behavior in comparison with controls while performing the DriveSafe, a slide recognition test purported to predict fitness to drive. METHODS: Thirty-one drivers with glaucoma (mean age, 71.7 ± 6.3 years; average better-eye mean defect,-3 dB; average worse-eye mean defect,-12 dB) and 25 age-matched controls underwent measurements of their visual acuity, contrast sensitivity, visual fields, and useful field of view (visual processing speeds). Participants' eye movements were recorded while they completed the DriveSafe test, which consists of brief presentations of static, real-world driving scenes containing various road users (pedestrians, bicycles, vehicles). Participants reported the types, positions, and direction of travel of road users in each image; the score was the total number of correctly reported items (maximum, 128). RESULTS: Drivers with glaucoma had significantly worse DriveSafe scores (P = .03), fixated on road users for shorter durations (P < .001), and exhibited smaller saccades (P = .02) compared with controls. For all participants, longer fixation times on road users (P < .001) was the eye movement measure most strongly associated with better DriveSafe scores; this relationship was not significantly different between groups. Useful field-of-view divided attention was the strongest visual predictor of DriveSafe scores. CONCLUSIONS: Eye movement changes in the glaucoma group may reflect increased difficulty in identifying relevant objects in the visual scene, which may be related to their lower DriveSafe scores. Given the DriveSafe's potential utility in assessing drivers with visual impairment before on-road testing, further investigations on how DriveSafe performance and eye movement patterns compare to those during on-road driving are warranted.

Eye Movements and Road Hazard Detection: Effects of Blur and Distractors.

PURPOSE: To examine the effects of optical blur, auditory distractors, and age on eye movement patterns while performing a driving hazard perception test (HPT). METHODS: Twenty young (mean age 27.1 ± 4.6 years) and 20 older (73.3 ± 5.7 years) drivers with normal vision completed a HPT in a repeated-measures counterbalanced design while their eye movements were recorded. Testing was performed under two visual (best-corrected vision and with +2.00DS blur) and two distractor (with and without auditory distraction) conditions. Participants were required to respond to road hazards appearing in the HPT videos of real-world driving scenes and their hazard response times were recorded. RESULTS: Blur and distractors each significantly delayed hazard response time by 0.42 and 0.76 s, respectively (p < 0.05). A significant interaction between age and distractors indicated that older drivers were more affected by distractors than young drivers (response with distractors delayed by 0.96 and 0.60 s, respectively). There were no other two- or three-way interaction effects on response time. With blur, for example, both groups fixated significantly longer on hazards before responding compared to best-corrected vision. In the presence of distractors, both groups exhibited delayed first fixation on the hazards and spent less time fixating on the hazards. There were also significant differences in eye movement characteristics between groups, where older drivers exhibited smaller saccades, delayed first fixation on hazards, and shorter fixation duration on hazards compared to the young drivers. CONCLUSIONS: Collectively, the findings of delayed hazard response times and alterations in eye movement patterns with blur and distractors provide further evidence that visual impairment and distractors are independently detrimental to driving safety given that delayed hazard response times are linked to increased crash risk.

Blur, eye movements and performance on a driving visual recognition slide test.

PURPOSE: Optical blur and ageing are known to affect driving performance but their effects on drivers' eye movements are poorly understood. This study examined the effects of optical blur and age on eye movement patterns and performance on the DriveSafe slide recognition test which is purported to predict fitness to drive. METHODS: Twenty young (27.1 ± 4.6 years) and 20 older (73.3 ± 5.7 years) visually normal drivers performed the DriveSafe under two visual conditions: best-corrected vision and with +2.00 DS blur. The DriveSafe is a Visual Recognition Slide Test that consists of brief presentations of static, real-world driving scenes containing different road users (pedestrians, bicycles and vehicles). Participants reported the types, relative positions and direction of travel of the road users in each image; the score was the number of correctly reported items (maximum score of 128). Eye movements were recorded while participants performed the DriveSafe test using a Tobii TX300 eye tracking system. RESULTS: There was a significant main effect of blur on DriveSafe scores (best-corrected: 114.9 vs blur: 93.2; p < 0.001). There was also a significant age and blur interaction on the DriveSafe scores (p < 0.001) such that the young drivers were more negatively affected by blur than the older drivers (reductions of 22% and 13% respectively; p < 0.001): with best-corrected vision, the young drivers performed better than the older drivers (DriveSafe scores: 118.4 vs 111.5; p = 0.001), while with blur, the young drivers performed worse than the older drivers (88.6 vs 95.9; p = 0.009). For the eye movement patterns, blur significantly reduced the number of fixations on road users (best-corrected: 5.1 vs blur: 4.5; p < 0.001), fixation duration on road users (2.0 s vs 1.8 s; p < 0.001) and saccade amplitudes (7.4° vs 6.7°; p < 0.001). A main effect of age on eye movements was also found where older drivers made smaller saccades than the young drivers (6.7° vs 7.4°; p < 0.001). CONCLUSIONS: Blur reduced DriveSafe scores for both age groups and this effect was greater for the young drivers. The decrease in number of fixations and fixation duration on road users, as well as the reduction in saccade amplitudes under the blurred condition, highlight the difficulty experienced in performing the task in the presence of optical blur, which suggests that uncorrected refractive errors may have a detrimental impact on aspects of driving performance.

Polygenic Prediction of Keratoconus and its Measures: Cross-Sectional and Longitudinal Analyses in Community-Based Young Adults.

AIM: This study evaluates the performance of a multitrait polygenic risk score (PRS) in an independent cohort to predict incident or progression of keratoconus. DESIGN: Prospective cross-sectional and cohort study METHODS: Setting: Single-center; Study population: 1478 community-based young adults (18-30 years; 51% female), including 609 (52% female) who returned for an 8-year follow-up; Observation procedures: Scheimpflug imaging (Pentacam, Oculus), genotyping and development of a multitrait PRS previously validated to predict keratoconus in older adults.; Main outcome measure: Belin/Ambrόsio enhanced ectasia display (BAD-D) score and keratoconus, defined as BAD-D ≥2.6, were each analyzed against the PRS using linear and logistic regression, respectively. RESULTS: Prevalence of keratoconus was 2.5% (95% confidence interval [CI] = 1.9-3.6) in the cross-sectional cohort. Each z-score increase in PRS was associated with worse BAD-D z-score by 0.13 (95%CI = 0.08-0.18) and 1.6 increased odds of keratoconus. The 8-year keratoconus incidence was 2.6% (95%CI = 1.3-4.0). Participants in the highest PRS decile were more likely to have incident keratoconus compared to the rest of the cohort (odds ratio = 3.85, 95%CI = 1.21-12.22). For each z-score increase in PRS, 8-year change in BAD-D z-score worsened by 0.11 (95%CI = 0.04-0.17). CONCLUSIONS: A PRS for keratoconus could be useful in predicting incident keratoconus and progression, demonstrating its potential utility in clinical settings to identify patients at high risk of postsurgery ectasia or those who may benefit most from keratoconus intervention.

Distribution of Axial Length in Australians of Different Age Groups, Ethnicities, and Refractive Errors.

Purpose: Treatments are available to slow myopic axial elongation. Understanding normal axial length (AL) distributions will assist clinicians in choosing appropriate treatment for myopia. We report the distribution of AL in Australians of different age groups and refractive errors. Methods: Retrospectively collected spherical equivalent refraction (SER) and AL data of 5938 individuals aged 5 to 89 years from 8 Australian studies were included. Based on the SER, participants were classified as emmetropes, myopes, and hyperopes. Two regression model parameterizations (piece-wise and restricted cubic splines [RCS]) were applied to the cross-sectional data to analyze the association between age and AL. These results were compared with longitudinal data from the Raine Study where the AL was measured at age 20 (baseline) and 28 years. Results: A piece-wise regression model (with 1 knot) showed that myopes had a greater increase in AL before 18 years by 0.119 mm/year (P < 0.001) and after 18 years by 0.011 mm/year (P < 0.001) compared to emmetropes and hyperopes, with the RCS model (with 3 knots) showing similar results. The longitudinal data from the Raine Study revealed that, when compared to emmetropes, only myopes showed a significant change in the AL in young adulthood (by 0.016 mm/year, P < 0.001). Conclusions: The AL of myopic eyes increases more rapidly in childhood and slightly in early adulthood. Further studies of longitudinal changes in AL, particularly in childhood, are required to guide myopia interventions. Translational Relevance: The axial length of myopic eyes increases rapidly in childhood, and there is a minimal increase in the axial length in non-myopic eyes after 18 years of age.

IMI-Onset and Progression of Myopia in Young Adults.

Myopia typically starts and progresses during childhood, but onset and progression can occur during adulthood. The goals of this review are to summarize published data on myopia onset and progression in young adults, aged 18 to 40 years, to characterize myopia in this age group, to assess what is currently known, and to highlight the gaps in the current understanding. Specifically, the peer-reviewed literature was reviewed to: characterize the timeline and age of stabilization of juvenile-onset myopia; estimate the frequency of adult-onset myopia; evaluate the rate of myopia progression in adults, regardless of age of onset, both during the college years and later; describe the rate of axial elongation in myopic adults; identify risk factors for adult onset and progression; report myopia progression and axial elongation in adults who have undergone refractive surgery; and discuss myopia management and research study design. Adult-onset myopia is common, representing a third or more of all myopia in western populations, but less in East Asia, where onset during childhood is high. Clinically meaningful myopia progression continues in early adulthood and may average 1.00 diopters (D) between 20 and 30 years. Higher levels of myopia are associated with greater absolute risk of myopia-related ocular disease and visual impairment, and thus myopia in this age group requires ongoing management. Modalities established for myopia control in children would be options for adults, but it is difficult to predict their efficacy. The feasibility of studies of myopia control in adults is limited by the long duration required.

Changes in Refractive Error During Young Adulthood: The Effects of Longitudinal Screen Time, Ocular Sun Exposure, and Genetic Predisposition.

Purpose: Changes in refractive error during young adulthood is common yet risk factors at this age are largely unexplored. This study explored risk factors for these changes, including gene-environmental interactions. Methods: Spherical equivalent refraction (SER) and axial length (AL) for 624 community-based adults were measured at 20 (baseline) and 28 years old. Participants were genotyped and their polygenic scores (PGS) for refractive error calculated. Self-reported screen time (computer, television, and mobile devices) from 20 to 28 years old were collected prospectively and longitudinal trajectories were generated. Past sun exposure was quantified using conjunctival ultraviolet autofluorescence (CUVAF) area. Results: Median change in SER and AL were -0.023 diopters (D)/year (interquartile range [IQR] = -0.062 to -0.008) and +0.01 mm/year (IQR = 0.000 to 0.026), respectively. Sex, baseline myopia, parental myopia, screen time, CUVAF, and PGS were significantly associated with myopic shift. Collectively, these factors accounted for approximately 20% of the variance in refractive error change, with screen time, CUVAF, and PGS each explaining approximately 1% of the variance. Four trajectories for total screen time were found: "consistently low" (n = 148), "consistently high" (n = 250), "consistently very high" (n = 76), and "increasing" (n = 150). Myopic shift was faster in those with "consistently high" or "consistently very high" screen time compared to "consistently-low" (P ≤ 0.031). For each z-score increase in PGS, changes in SER and AL increased by -0.005 D/year and 0.002 mm/year (P ≤ 0.045). Of the three types of screen time, only computer time was associated with myopic shift (P ≤ 0.040). There was no two- or three-way interaction effect between PGS, CUVAF, or screen time (P ≥ 0.26). Conclusions: Higher total or computer screen time, less sun exposure, and genetic predisposition are each independently associated with greater myopic shifts during young adulthood. Given that these factors explained only a small amount of the variance, there are likely other factors driving refractive error change during young adulthood.

A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration.

BACKGROUND: High myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ -6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER. METHODS: The PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression. FINDINGS: In independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17-21%), 2% (1-3%), 8% (7-10%) and 6% (3-9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75-0.81), 0.58 (0.53-0.64), 0.71 (0.69-0.74) and 0.67 (0.62-0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92-1.24). INTERPRETATION: Performance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted for. FUNDING: Supported by the Welsh Government and Fight for Sight (24WG201).

Prevalence and Risk Factors of Myopia in Young Adults: Review of Findings From the Raine Study.

Myopia tends to develop and progress fastest during childhood, and the age of stabilization has been reported to be 15-16 years old. Thus, most studies on myopia have centered on children. Data on the refractive error profile in young adulthood - a time in life when myopia is thought to have stabilized and refractive error is unaffected by age-related pathology such as cataract - are limited. The Raine Study has been following a community-based cohort of young adults representative of the general Western Australia population since their prenatal periods in 1989-1991, with eye examinations performed when participants were 20 and 28 years old. At 20 years old, prevalence of myopia in the cohort was 25.8%. Using long-term trajectory of serum vitamin D levels and conjunctival ultraviolet autofluorescence (CUVAF) area to objectively quantify sun exposure, the Raine Study confirmed a negative relationship between time spent outdoors and myopia prevalence. However, prospective studies are required to determine the amount of CUVAF area or serum vitamin D levels associated with time duration. Combining data from the Raine Study and several other cohorts, Mendelian randomization studies have confirmed a link between myopia and a genetic predisposition toward higher education. Several novel potential associations of myopia or ocular biometry were investigated, including fetal growth trajectory, which was found to be significantly associated with corneal curvature at 20 years. By age 28, myopia prevalence had increased to 33.2%. Between 20 and 28 years old, myopia progressed and axial length elongated, on average, by -0.041D/year and 0.02 mm/year, respectively. Smaller CUVAF area at follow-up, female sex, and parental myopia were significant risk factors for myopia incidence and progression between 20 and 28 years. Given the limited research in young adults, further investigations are warranted to confirm the Raine Study findings, as well as identify novel genetic or environmental factors of myopia incidence and progression in this age group.

Glaucoma - risk factors and current challenges in the diagnosis of a leading cause of visual impairment.

Worldwide, glaucoma affects about 3% of the population over the age of 50 years and is a leading cause of irreversible visual impairment among older people. Because glaucoma is asymptomatic in its early stages and can be challenging to diagnose clinically, it often remains undiagnosed until substantial vision loss has occurred. Efficient methods of glaucoma screening are therefore warranted for early detection of disease. Identification of risk factors for glaucoma - family history of glaucoma, older age, African or Asian ethnicities, raised intraocular pressure, and thin corneas - have helped inform guidelines on the recommended age at commencement and frequency of glaucoma screenings. A genetic predisposition or family history of glaucoma is one of the most important risk factors for the disease. However, an accurate family history cannot always be ascertained. Genetic testing for genes such as myocilin could help to identify high-risk individuals and, with further research, could even provide insight into individual patients' response to treatment. With the ongoing discovery of glaucoma-associated genes and the advent of polygenic risk scores to identify individuals at high risk of glaucoma, gene-based screening for glaucoma is becoming closer to realisation. In the meantime, regularly screening family members of people with existing glaucoma is an efficient way of detecting early glaucoma. Raising public awareness of glaucoma is also necessary to educate the general public on the key role of routine eye examinations and early disease detection. Future studies should be undertaken to explore efficient public health campaign methods for improving glaucoma awareness.

Choroidal Thickening During Young Adulthood and Baseline Choroidal Thickness Predicts Refractive Error Change.

Purpose: The purpose of this study was to explore the age-related change in choroidal thickness (ChT) and test the hypothesis that baseline ChT is predictive of refractive error change in healthy young adults. Methods: Participants underwent spectral-domain optical coherence tomography (SD-OCT) imaging and autorefraction at 20 (baseline) and 28 years old. The enhanced depth imaging mode on the SD-OCT was used to obtain images of the choroid. Scans were exported from the SD-OCT and analyzed with a custom software that automatically measures the central ChT. The longitudinal change in subfoveal ChT and association between baseline subfoveal ChT and 8-year change in refractive error (spherical equivalent) were determined using linear mixed models. Results: In total, 395 eyes of 198 participants (44% men; 18-22 years at baseline) were included. Over 8 years, mean spherical equivalent decreased by 0.25 diopters (D) and axial length increased by 0.09 mm. Subfoveal choroid thickened by 1.3 µm/year (95% confidence interval [CI] = 0.6-2.0), but this was reduced by 0.9 µm/year (95% CI = 1.6-0.2) for every 1 mm increase in axial length. For every 10 µm increase in baseline ChT, average annual change in spherical equivalent and axial length reduced by 0.006 D/year and 0.003 mm/year, respectively. Conclusions: In a community-based cohort of young adults, the choroid continued to change during early adulthood. Choroidal thickening was less in eyes that were longer at baseline, and the choroid thinned in eyes that showed myopia progression. The association between baseline ChT and longitudinal changes in spherical equivalent and axial length supports the hypothesis that ChT may be predictive of refractive error development and/or myopia progression.