The Association Between Age and Systemic Variables and the Longitudinal Trend of Intraocular Pressure in a Large-Scale Health Examination Cohort

Biological Age Acceleration, Genetic Susceptibility, and Incident Glaucoma Risk

Purpose

To evaluate the association of biological age acceleration with incident glaucoma risk and examine whether genetic predisposition modifies it.

Methods

We included 318,556 UK Biobank participants without baseline glaucoma. Biological age was calculated using the Klemera-Doubal method Biological Age (KDM-BA) and PhenoAge algorithms. Hazard ratios (HRs) and 95% confidence intervals (CIs) of the association between biological age acceleration and incident glaucoma, and their interaction with genetic risk were analyzed by Cox regression models. Mendelian randomization analyses investigated causal associations.

Results

After a median follow-up of 13.5 years, 6553 participants developed glaucoma. Biological age acceleration was associated with an increased glaucoma risk. Each 5-year increment in biological age acceleration was linked to higher glaucoma risk (KDM-BA acceleration: HR, 1.12, 95% CI, 1.07-1.16; PhenoAge acceleration, HR, 1.09, 95% CI, 1.06-1.13). Biologically older participants had a higher glaucoma risk than younger participants (KDM-BA acceleration, HR, 1.10, 95% CI, 1.05-1.16; PhenoAge acceleration, HR, 1.07, 95% CI, 1.02-1.13). Genetic risk modified these relationships (all P for interactions < 0.05). Biologically older participants with high genetic risk had the highest glaucoma risk (KDM-BA acceleration, HR, 2.33, 95% CI, 2.15-2.52; PhenoAge acceleration, HR, 2.21, 95% CI, 2.05-2.38). No causal relationships were found in the Mendelian randomization analysis.

Conclusions

Biological age acceleration was associated with an increased glaucoma risk, and this relationship was modified by genetic risk. However, no causal relationship was established, and further research is needed to investigate the nature of the association.

Longitudinal changes in the intraocular pressure and their related factors among adults aged 40 to 64 years

To determine the five-year changes in intraocular pressure (IOP) and their related factors among individuals aged 40 to 64 years. The present report is part of the Shahroud Eye Cohort study. The sampling process for this study utilized a multi-stage cluster sampling method within Shahroud, Iran. Optometric and ophthalmologic examinations included measurement of uncorrected and best-corrected visual acuity, non-cycloplegic autorefraction and slit-lamp biomicroscope. IOP was measured using a Goldman tonometer. A total of 7384 eyes from 3855 individuals were examined in this report. The average five-year change in IOP was -0.06±2.23 mmHg (95% confidence interval: -0.14 to 0.02). The 25, 75, 95, and 99th percentiles of five-year IOP changes were -1, 1, 4, and 5 mmHg, respectively. According to the multivariate generalized estimating equation (GEE) model, the five-year changes in IOP were positively associated with female gender (coefficients(β)=0.139; P=0.036), blood pressure (β=0.40; P<0.001), diabetes (β=0.539; P<0.001), body mass index (β=0.023; P<0.001), axial length (β=0.104;P<0.007), central corneal thickness (β=0.010; P<0.001), mean keratometry (β=0.0067; P<0.001), and lens thickness at baseline (β=0.182; P<0.047). Moreover, baseline IOP exhibited an inverse association with five-year changes in IOP (β=-0.808; P<0.001). Despite a 4 mmHg increase in IOP observed in 5% of the study participants, the average change in IOP over five years was deemed not clinically or statistically significant. Nevertheless, biometric indices are important for anticipating variations in IOP.

Fundus-Derived Predicted Age Acceleration in Glaucoma Patients Using Deep Learning and Propensity Score-Matched Controls

Background/Objectives: Glaucoma, a leading cause of irreversible blindness, has been associated with systemic and ocular aging processes. This study aimed to investigate the relationship between glaucoma and accelerated biological aging using fundus-derived age prediction. Additionally, the role of systemic factors and retinal vascular changes in this association was explored. Methods: A total of 6023 participants, including 547 glaucoma patients and 547 matched controls, were analyzed. Fundus-derived predicted age was assessed using a deep learning model (EfficientNet). Systemic factors such as BMI, blood pressure, lipid profiles, liver function markers, glucose levels, and retinal vascular changes (Scheie classifications) were analyzed. Statistical comparisons and multivariate regression analyses were performed to evaluate the impact of glaucoma on predicted age acceleration, adjusting for age, gender, and systemic factors. Results: Glaucoma was significantly associated with higher predicted age acceleration (prediction difference: -1.5 ± 4.5 vs. -2.1 ± 4.5 years; p = 0.040). Multivariate regression confirmed that glaucoma independently influenced predicted age (p = 0.021) and prediction difference (p = 0.021). Among systemic factors, γ-GTP was positively associated with prediction difference (p = 0.036), while other factors, such as BMI, blood pressure, and glucose levels, showed no significant association. Retinal vascular changes, including hypertensive and sclerotic changes (Scheie classifications), were significantly more prevalent in glaucoma patients and correlated with predicted age acceleration. Conclusions: Glaucoma is associated with accelerated biological aging, as indicated by fundus-derived predicted age. Systemic factors such as γ-GTP and retinal vascular changes may play contributory roles. Fundus-derived predicted age holds promise as a non-invasive biomarker for monitoring systemic aging. Further longitudinal studies are warranted to establish causal relationships and enhance clinical applications.

Link Between Metabolic Syndrome, Inflammation, and Eye Diseases

Metabolic syndrome (MetS)-a cluster of conditions including obesity, hypertension, dyslipidemia, and insulin resistance-is increasingly recognized as a key risk factor for the development of various eye diseases. The metabolic dysfunctions associated with this syndrome contribute to vascular and neurodegenerative damage within the eye, influencing disease onset and progression. Understanding these links highlights the importance of early diagnosis and management of metabolic syndrome to prevent vision loss and improve ocular health outcomes. This review explores the intricate interplay between metabolic syndrome, chronic low-grade inflammation, and eye diseases such as diabetic retinopathy, age-related macular degeneration, glaucoma, and dry eye syndrome. It highlights how inflammatory mediators, oxidative damage, and metabolic dysregulation converge to compromise ocular structures, including the retina, optic nerve, and ocular surface. We discuss the molecular and cellular mechanisms underpinning these associations and examine evidence from clinical and experimental studies. Given the rising global prevalence of metabolic syndrome, addressing this connection is crucial for improving overall patient outcomes and quality of life. Future research should focus on delineating the precise mechanisms linking these diseases as well as exploring targeted interventions that address both metabolic and ocular health.

Does Age Modify the Relation Between Genetic Predisposition to Glaucoma and Various Glaucoma Traits in the UK Biobank?

Purpose

Glaucoma polygenic risk scores could guide glaucoma public health screening initiatives. We investigated how age influences the relationship between a multitrait glaucoma polygenic risk score (mtGPRS) and primary open-angle glaucoma indicators, including intraocular pressure (IOP), retinal structure, and glaucoma prevalence.

Methods

We analyzed UK Biobank participants with demographic and genetic data, assessing IOP (n = 118,153), macular retinal nerve fiber layer thickness (mRNFL; n = 42,132), macular ganglion cell inner plexiform layer thickness (mGCIPL; n = 42,042), and prevalent glaucoma status (8982 cases among 192,283 participants). An mtGPRS was constructed using 2673 genetic variants. We used multivariable linear regression to assess how age modifies the relationship between mtGPRS and glaucoma traits (IOP, mRFNL, and mGCIPL) and multivariable logistic regression for prevalent glaucoma risk. We analyzed age quartiles (Q1 = <51, Q2 = 51-57, Q3 = 58-62, and Q4 = ≥63 years) - glaucoma trait interaction tests with the Wald test. All analyses were adjusted for confounders, including nonlinear age effects.

Results

Age significantly modified the relationship between the mtGPRS and IOP (Pinteraction = 2.7e-27). Mean IOP differences (millimeters of mercury [mm Hg]) per standard deviation (SD) of mtGPRS were 0.95, 1.02, 1.18, and 1.24 across age quartiles. Similar trends were observed for glaucoma risk (odds ratio per SD of mtGPRS = 2.38, 2.57, 2.80, and 2.75; Pinteraction = 1.0e-06). Relationships between mtGPRS and inner retinal thickness (mRNFL and mGCIPL) across age strata were inconsistently modified by age (Pinteraction ≥ 0.01).

Conclusions

With increasing age, an mtGPRS was a better predictor of higher IOP and glaucoma prevalence. It is useful to consider chronological age with genetic information in designing glaucoma screening strategies.

The Relationship Between Serum Biochemical Variables and Corneal Biomechanics Measured by Corvis ST Among Healthy Young Adults

Purpose

To investigate the relationship between serum biochemical variables and corneal biomechanics in healthy young adults.

Methods

A total of 1645 healthy university students were included. Every student underwent an ophthalmologic examination by Corvis ST to measure the corneal biomechanics and a blood examination to evaluate the alanine aminotransferase (ALT), aspartate aminotransferase (AST), urea, creatinine, and uric acid (UA) levels. Canonical correlation analysis (CCA) was conducted to assess their relationship.

Results

A significant relationship between serum biochemical variables and corneal biomechanics was found in both men and women. For men, the canonical correlation identified an association between the time of the first applanation (A1t), time of the second applanation (A2t), time of the highest concavity (HC-t), deflection amplitude of the highest concavity (HC-DeflA), and biomechanically corrected intraocular pressure (bIOP) with ALT, AST, urea, and UA (r = 0.235, P = 0.03). For women, a significant relationship between A1t, A2t, and bIOP with ALT and UA was found (r = 0.187, P < 0.01).

Conclusions

Elevated levels of ALT and UA were associated with softer corneas with greater elasticity and viscidity. The study provides novel evidence for the relationship between serum biochemical variables and ocular changes.

Translational Relevance

These findings may help clinicians perform adequate preoperative evaluations when performing corneal surgery on patients with liver or kidney disorders, as well as helping public health practitioners understand serum biochemical variables of corneal changes in healthy people.

Effects of ambient atmospheric pressure on intraocular pressure measured using a Goldman applanation tonometer in normal eyes under ordinary conditions

PURPOSE

Little is known about the effects of ambient atmospheric pressure (AP) on intraocular pressure (IOP) under ordinary conditions. This study aimed to investigate the effects of AP on Goldmann applanation tonometer-measured IOP (GAT-IOP) in normal eyes under everyday atmospheric conditions adjusting for effects of possible confounding factors including other climatic factors.

METHODS

Data obtained from 2,431 normal healthy eyes of 2,431 subjects (mean age: 56.9 years) who participated in this population-based glaucoma survey in Japan were analyzed via multivariable linear regression analysis, where the GAT-IOP was the response variable; explanatory variables were the ocular and systemic factors and calendar factors reportedly correlated with GAT-IOP as well as AP, relative humidity, temperature, wind speed, and weather. The Bonferroni correction was adopted to obtain P values.

RESULTS

Only AP of the outside air when each subject was examined was positively correlated with GAT-IOP (regression coefficient (RC) = 0.0460; P = 0.0051). Central corneal thickness, body mass index, and systolic blood pressure were positively correlated (RC = 0.0133, 0.0754, 0.0131; P < 0.0001, P < 0.0001, P = 0.0016, respectively), and corneal curvature radius and age were negatively correlated (RC=-0.7017, -0.0225; P = 0.0144, P = 0.0111, respectively) with GAT-IOP. The seasonal effect on GAT-IOP was also significant (P < 0.0001), and in reference to winter, summer was correlated with lower GAT-IOP and spring was correlated with higher GAT-IOP (RC=-0.5133, 0.4590; P = 0.0087, P = 0.0001, respectively).

CONCLUSIONS

AP was found to have a significantly positive correlation with GAT-IOP in normal healthy eyes under ordinary conditions, though the actual impact of AP on IOP in normal individuals under ordinary conditions would be minimal.

Influence of meteorological factors on intraocular pressure variability using a large-scale cohort

The effects of meteorological conditions on IOP using a large-scale health examination cohort were investigated. There were a total of 811,854 measurements from 126,630 eyes of 63,839 subjects in 9 years from a health checkup cohort followed up annually for age, sex, body height, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and IOP. The effects of these variables and the meteorological data of daily average temperature (TP), daily average local atmospheric pressure (AP), daily average volumetric humidity (VH), and daily amount of rainfall (RF) on the day of IOP measurement on IOP were investigated. Several variables were significantly associated with IOP, including sex, age, body height, BMI, SBP, DBP, average TP, average AP, average VH, RF, white blood cell count, red blood cell count, hemoglobin, aspartate aminotransferase, alanine aminotransferase, guanosine triphosphate, calcium, and HbA1c. This study indicated a correlation between meteorological factors and IOP. Higher AP and RF were associated with elevated IOP, whereas higher TP and VH were associated with decreased IOP.

High Intraocular Pressure Is Independently Associated With New-Onset Systemic Hypertension Over a 10-Year Period

BACKGROUND

Systemic hypertension (HT) is associated with the development of increased intraocular pressure (IOP), a risk factor for glaucoma. However, it remains unclear whether high IOP is a risk factor for HT.

METHODS AND RESULTS

We investigated 7,487 Japanese individuals (4,714 men, 2,773 women; mean [±SD] age 49±9 years) who underwent annual health checkups in 2006. Over the 10-year follow-up period, 1,232 (24.3%) men and 370 (11.5%) women developed new-onset HT, defined as initiation of antihypertensive drug treatment or blood pressure ≥140/90 mmHg. After dividing IOP into tertiles (T1-T3), Cox proportional hazards analysis (adjusted for age, sex, systolic blood pressure, obesity, current smoking, alcohol consumption, family history of HT, estimated glomerular filtration rate, and diabetes and dyslipidemia diagnoses at baseline) revealed a significantly higher risk of newly developed HT in T3 (IOP ≥14 mmHg; hazard ratio 1.14; 95% confidence interval 1.01-1.29; P=0.038) using T1 (IOP ≤11 mmHg) as the reference group. There was no significant interaction between sex and IOP tertile (P=0.153). A restricted cubic spline model showed a gradual but robust increase in the hazard ratio for new-onset HT with increasing IOP.

CONCLUSIONS

High IOP is an independent risk factor for the development of HT over a 10-year period.

Intraocular pressure across the lifespan of Tg-MYOCY437H mice

Transgenic C57BL/6 mice expressing human myocilinY437 (Tg-MYOCY437H) are a well-established model for primary open-angle glaucoma (POAG). While the reduced trabecular meshwork (TM) cellularity due to severe endoplasmic reticulum (ER) stress has been characterized as the etiology of this model, there is a limited understanding of how glaucomatous phenotypes evolve over the lifespan of Tg-MyocY437H mice. In this study, we compiled the model's intraocular pressure (IOP) data recorded in our laboratory from 2017 to 2023 and selected representative eyes to measure the outflow facility (Cr), a critical parameter indicating the condition of the conventional TM pathway. We found that Tg-MYOCY437H mice aged 4-12 months exhibited significantly higher IOPs than age-matched C57BL/6 mice. Notably, a decline in IOP was observed in Tg-MYOCY437H mice at 17-24 months of age, a phenomenon not attributable to the gene dosage of mutant myocilin. Measurements of the Cr of Tg-MYOCY437H mice indicated that the age-related IOP reduction was not a result of ongoing TM damage. Instead, Hematoxylin and Eosin staining, immunohistochemistry analysis, and transmission electron microscopic examination revealed that this reduction might be induced by degenerations of the non-pigmented epithelium in the ciliary body of aged Tg-MYOCY437H mice. Overall, our findings provide a comprehensive profile of mutant myocilin-induced ocular changes over the Tg-MYOCY437H mouse lifespan and suggest a specific temporal window of elevated IOP that may be ideal for experimental purposes.

Nonhuman Primate Eyes Display Variable Growth and Aging Rates in Alignment With Human Eyes

Purpose

To assess age-related biometric changes of the eye in nonhuman primates (NHPs), to and decipher the growth and aging rates and their comparability with humans.

Methods

Ocular anatomic measurements were performed on 341 macaca fascicularis aged 0.5 to 23 years via multimodal approaches including IOLMaster 700. Linear or polynomial regression models were simulated to determine the best fitted age-related function. The metrics were compared with human equivalents in published reports.

Results

Macaques exhibited a postnatal eye growth pattern similar to humans, characterized by continuous eye extension coordinated with dramatic reshaping of the lens but not the cornea. The age-related growth of lens thickness (LT), anterior chamber depth (ACD), and axis length (AL) exhibited nonlinear and bipolar patterns. The inflection points were 10 to 12 years old for LT and ACD and 13 to 15 years old for AL in macaques, which were comparable in chronological age at a ratio of ∼1: ratio with that in humans. In contrast, the speed of aging, including the increase in lens density and the decrease in retinal nerve fiber layer thickness, was comparable in relative age at a ratio of ∼1:3 according to the differences in lifespan between macaques and humans. Lens density was a robust indicator for the aging process.

Conclusions

Macaque eyes recapitulated the age-related process of human eyes to varying extents with different growth and aging rates. Chronological age or relative age should be considered in different scenarios when macaques are included in preclinical studies.

Microbiome Dysbiosis: A Pathological Mechanism at the Intersection of Obesity and Glaucoma

The rate at which obesity is becoming an epidemic in many countries is alarming. Obese individuals have a high risk of developing elevated intraocular pressure and glaucoma. Additionally, glaucoma is a disease of epidemic proportions. It is characterized by neurodegeneration and neuroinflammation with optic neuropathy and the death of retinal ganglion cells (RGC). On the other hand, there is growing interest in microbiome dysbiosis, particularly in the gut, which has been widely acknowledged to play a prominent role in the etiology of metabolic illnesses such as obesity. Recently, studies have begun to highlight the fact that microbiome dysbiosis could play a critical role in the onset and progression of several neurodegenerative diseases, as well as in the development and progression of several ocular disorders. In obese individuals, gut microbiome dysbiosis can induce endotoxemia and systemic inflammation by causing intestinal barrier malfunction. As a result, bacteria and their metabolites could be delivered via the bloodstream or mesenteric lymphatic vessels to ocular regions at the level of the retina and optic nerve, causing tissue degeneration and neuroinflammation. Nowadays, there is preliminary evidence for the existence of brain and intraocular microbiomes. The altered microbiome of the gut could perturb the resident brain-ocular microbiome ecosystem which, in turn, could exacerbate the local inflammation. All these processes, finally, could lead to the death of RGC and neurodegeneration. The purpose of this literature review is to explore the recent evidence on the role of gut microbiome dysbiosis and related inflammation as common mechanisms underlying obesity and glaucoma.

Distribution and associated factors of intraocular pressure in the older population: Tehran Geriatric Eye Study

AIM

To determine the distribution and associated factors of intraocular pressure (IOP) in an Iranian elderly population 60 years of age and above.

METHODS

The present report is part of the Tehran Geriatric Eye study (TGES), a population-based cross-sectional study that was conducted on the residents of Tehran 60 years of age and above. The sampling was performed using multistage stratified random cluster sampling methods from 22 districts of Tehran, Iran. Demographic and history information, blood samples, and blood pressure were collected from all participants. Ocular examinations included measurement of uncorrected and best-corrected visual acuity, objective and subjective refraction, and slit-lamp biomicroscopy. The IOP was measured using Goldmann applanation tonometry (GAT). Corneal imaging and ocular biometry were performed using Pentacam AXL.

RESULTS

The data of 3892 eyes of 2124 individuals were analyzed for this report. The mean age of the study participants was 66.49±5.31y (range: 60 to 95y). The mean IOP was 15.2 mm Hg (95%CI: 15.1 to 15.4), 15.3 mm Hg (95%CI: 15.1 to 15.5) and 15.1 mm Hg (95%CI: 15.0 to 15.3) in all participants, males, and females, respectively. Of the study participants, 1.3% had an IOP of ≥20 mm Hg. The mean IOP increased from 15.1 mm Hg in the age group 60-64y to 16.3 mm Hg in the age group ≥80y. According to the final multiple GEE model, the IOP was statistically significantly higher in men than in women. All the studied age groups, except for the 75-79-year-old age group, had significantly higher IOP compared to the 60-64-year-old age group. The IOP was significantly higher in underweight compared to other body mass index groups. Moreover, the IOP had a statistically significant direct relationship with the mean corneal power (mean CP), central corneal thickness (CCT), and systolic blood pressure.

CONCLUSION

The present study presents the distribution of IOP in an Iranian elderly population. A higher IOP (within the range 14 to 17 mm Hg) is significantly associated with older age, male sex, high systolic blood pressure, increased mean CP, and CCT. These factors should be considered in the clinical interpretation of IOP.