Comparison of Associations with Different Macular Inner Retinal Thickness Parameters in a Large Cohort: The UK Biobank

Automated Detection of Glaucoma With Interpretable Machine Learning Using Clinical Data and Multimodal Retinal Images

PURPOSE

To develop a multimodal model to automate glaucoma detection DESIGN: Development of a machine-learning glaucoma detection model METHODS: We selected a study cohort from the UK Biobank data set with 1193 eyes of 863 healthy subjects and 1283 eyes of 771 subjects with glaucoma. We trained a multimodal model that combines multiple deep neural nets, trained on macular optical coherence tomography volumes and color fundus photographs, with demographic and clinical data. We performed an interpretability analysis to identify features the model relied on to detect glaucoma. We determined the importance of different features in detecting glaucoma using interpretable machine learning methods. We also evaluated the model on subjects who did not have a diagnosis of glaucoma on the day of imaging but were later diagnosed (progress-to-glaucoma [PTG]).

RESULTS

Results show that a multimodal model that combines imaging with demographic and clinical features is highly accurate (area under the curve 0.97). Interpretation of this model highlights biological features known to be related to the disease, such as age, intraocular pressure, and optic disc morphology. Our model also points to previously unknown or disputed features, such as pulmonary function and retinal outer layers. Accurate prediction in PTG highlights variables that change with progression to glaucoma-age and pulmonary function.

CONCLUSIONS

The accuracy of our model suggests distinct sources of information in each imaging modality and in the different clinical and demographic variables. Interpretable machine learning methods elucidate subject-level prediction and help uncover the factors that lead to accurate predictions, pointing to potential disease mechanisms or variables related to the disease.

Detecting retinal neurodegeneration in people with diabetes: Findings from the UK Biobank

Importance

Efforts are underway to incorporate retinal neurodegeneration in the diabetic retinopathy severity scale. However, there is no established measure to quantify diabetic retinal neurodegeneration (DRN).

Objective

We compared total retinal, macular retinal nerve fiber layer (mRNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness among participants with and without diabetes (DM) in a population-based cohort.

Design/setting/participants

Cross-sectional analysis, using the UK Biobank data resource. Separate general linear mixed models (GLMM) were created using DM and glycated hemoglobin as predictor variables for retinal thickness. Sub-analyses included comparing thickness measurements for patients with no/mild diabetic retinopathy (DR) and evaluating factors associated with retinal thickness in participants with and without diabetes. Factors found to be significantly associated with DM or thickness were included in a multiple GLMM.

Exposure

Diagnosis of DM was determined via self-report of diagnosis, medication use, DM-related complications or glycated hemoglobin level of ≥ 6.5%.

Main outcomes and measures

Total retinal, mRNFL and GC-IPL thickness.

Results

74,422 participants (69,985 with no DM; 4,437 with DM) were included. Median age was 59 years, 46% were men and 92% were white. Participants with DM had lower total retinal thickness (-4.57 μm, 95% CI: -5.00, -4.14; p<0.001), GC-IPL thickness (-1.73 μm, 95% CI: -1.86, -1.59; p<0.001) and mRNFL thickness (-0.68 μm, 95% CI: -0.81, -0.54; p<0.001) compared to those without DM. After adjusting for co-variates, in the GLMM, total retinal thickness was 1.99 um lower (95% CI: -2.47, -1.50; p<0.001) and GC-IPL was 1.02 μm lower (95% CI: -1.18, -0.87; p<0.001) among those with DM compared to without. mRNFL was no longer significantly different (p = 0.369). GC-IPL remained significantly lower, after adjusting for co-variates, among those with DM compared to those without DM when including only participants with no/mild DR (-0.80 μm, 95% CI: -0.98, -0.62; p<0.001). Total retinal thickness decreased 0.40 μm (95% CI: -0.61, -0.20; p<0.001), mRNFL thickness increased 0.20 μm (95% CI: 0.14, 0.27; p<0.001) and GC-IPL decreased 0.26 μm (95% CI: -0.33, -0.20; p<0.001) per unit increase in A1c after adjusting for co-variates. Among participants with diabetes, age, DR grade, ethnicity, body mass index, glaucoma, spherical equivalent, and visual acuity were significantly associated with GC-IPL thickness.

Conclusion

GC-IPL was thinner among participants with DM, compared to without DM. This difference persisted after adjusting for confounding variables and when considering only those with no/mild DR. This confirms that GC-IPL thinning occurs early in DM and can serve as a useful marker of DRN.

Three "Red Lines" for Pattern Recognition-Based Differential Diagnosis Using Optical Coherence Tomography in Clinical Practice

BACKGROUND

Optical coherence tomography (OCT) devices for imaging of the eye are broadly available. The test is noninvasive, rapid, and well-tolerated by patients. This creates a large number of OCT images and patient referrals. Interpretation of OCT findings at the interface between neurological and ophthalmologic conditions has become a key skill in the neuro-ophthalmology service. Similar to the interpretation of visual fields, recogntion of the vertical and horizontal medians are helpful. A third "red line" is added, which will be reviewed here.

EVIDENCE

Levels 1a to 5 evidence.

ACQUISITION

Literature research.

RESULTS

There is level 1a evidence that neurodegeneration of the brain is associated with inner retinal layer atrophy. Predominantly, this is driven by retrograde (trans-synaptic) axonal degeneration from the brain to the eye. This process typically stops at the level of the inner nuclear layer (INL). Anterograde (Wallerian) axonal degeneration from the eye to the brain can trespass the INL. The geography of atrophy and swelling of individual macular retinal layers distinguishes prechiasmal from postchiasmal pathology. The emerging patterns are a front-back "red line" at the INL; a vertical "red line" through the macula for chiasmal/postchiasmal pathology; and a horizontal "red line" through the macular for pathology pointing to the optic disc. This is summarized by illustrative case vignettes.

CONCLUSIONS

The interpretation of patterns of individual retinal layer atrophy (3 "red lines") needs to be combined with recognition of localized layer thickening (edema, structural) at the macula. Certain macular patterns point to pathology at the level of the optic disc. This requires revision of the optic disc OCT and will guide need for further investigations. The 3 "red lines" proposed here may be found useful in clinical practice and the related mnemonics ("half moon," "sunset," "rainbow") for teaching.

An analysis of macular ganglion cell complex in 7-year-old children in China: the Anyang Childhood Eye Study

BACKGROUND

This study used spectral-domain optical coherence tomography (SD-OCT) imaging to describe the distribution of macular ganglion cell complex (GCC) thickness and its association with ocular and systemic parameters in 7-year-old children in China.

METHODS

The study involved a school-based, cross-sectional analysis of the Anyang Childhood Eye Study (ACES) and included 2,505 first-grade students from urban areas in Anyang, Henan Province, Central China. All participants underwent systemic and ocular examinations. Both GCC and retinal nerve fiber layer (RNFL) thickness were measured using the iVue-100 OCT (Optovue, Fremont, CA, USA). Intraocular pressure (IOP) was recorded with noncontact tonometer (Huvitz, HNT-7000). Axial length (AL) was measured using optical biometry (Lenstar LS 900, Haag-Streit Diagnostics, Koniz, Switzerland).

RESULTS

The mean GCC thickness was 95.31±7.67 µm. GCC thickness had negative associations with AL (r=-0.124, P<0.001), cup-to-disc (C-D) area ratio (r=-0.068, P=0.0033), horizontal C-D (H C-D) ratio (r=-0.048, P=0.0384), and vertical C-D (V C-D) ratio (r=-0.074, P=0.0013). Positive correlations were found with spherical equivalent (SE) (r=0.080, P=0.0001), RNFL thickness (r=0.363, P<0.001), height (r=0.059, P=0.0036), fovea parameters, disc area (r=0.078, P=0.0007), rim area (r=0.115, P<0.001), rim volume (r=0.119, P<0.001), and optic nerve head volume (r=0.097, P<0.001). GCC thickness had no significant association with IOP, age, sex, or weight, waist, or head circumference.

CONCLUSIONS

This study provides normative GCC data for 7-year-old healthy children in China. The findings support an association between GCC and AL, SE, RNFL, height, and C-D ratio in children.

Large-scale machine-learning-based phenotyping significantly improves genomic discovery for optic nerve head morphology

Genome-wide association studies (GWASs) require accurate cohort phenotyping, but expert labeling can be costly, time intensive, and variable. Here, we develop a machine learning (ML) model to predict glaucomatous optic nerve head features from color fundus photographs. We used the model to predict vertical cup-to-disc ratio (VCDR), a diagnostic parameter and cardinal endophenotype for glaucoma, in 65,680 Europeans in the UK Biobank (UKB). A GWAS of ML-based VCDR identified 299 independent genome-wide significant (GWS; p ≤ 5 × 10-8) hits in 156 loci. The ML-based GWAS replicated 62 of 65 GWS loci from a recent VCDR GWAS in the UKB for which two ophthalmologists manually labeled images for 67,040 Europeans. The ML-based GWAS also identified 93 novel loci, significantly expanding our understanding of the genetic etiologies of glaucoma and VCDR. Pathway analyses support the biological significance of the novel hits to VCDR: select loci near genes involved in neuronal and synaptic biology or harboring variants are known to cause severe Mendelian ophthalmic disease. Finally, the ML-based GWAS results significantly improve polygenic prediction of VCDR and primary open-angle glaucoma in the independent EPIC-Norfolk cohort.

Association of Macular Thickness With Age and Age-Related Macular Degeneration in the Carotenoids in Age-Related Eye Disease Study 2 (CAREDS2), An Ancillary Study of the Women's Health Initiative

Purpose

To evaluate the relationship of retinal layer thickness with age and age-related macular degeneration (AMD) in the Carotenoids in Age-Related Eye Disease Study 2.

Methods

Total retinal thickness within the macular area, and individual layer thickness was determined for CAREDS2 participants (n = 906 eyes, 473 women) from the Women's Health Initiative using Heidelberg optical coherence tomography (OCT). Mean measurements within the OCT grid were compared across age tertiles (69–78, 78–83, and 83–101 years) and AMD outcomes.

Results

Mean retinal thickness in the central circle, inner ring, and outer ring were 277 ± 34 µm, 326 ± 20 µm, and 282 ± 15 µm, respectively. Thickness did not vary by age in the central circle, but decreased with age in the inner and outer circles (P ≤ 0.004). Specifically, ganglion cell (GCL), inner plexiform, and outer nuclear (ONL) layer thickness decreased with age (P ≤ 0.003). Age-adjusted retinal thickness in all three circles did not vary by AMD outcomes (486 without AMD and 413 with AMD). However, individual layers showed changes with GCL and photoreceptor thinning and retinal pigment epithelial thicknening in eyes with late AMD. After controlling for age and AMD, higher ONL thickness was associated with better visual acuity.

Conclusions

In this cohort of older women, a decrease in perifoveal thickness was associated with increasing age, particularly in the inner retinal layers. Variabilty in thickness in AMD eyes was primarily due to outer retinal layers. Among all retinal layers, the ONL plays an important role in preserving visual acuity.

Translational Relevance

The study provides a deeper understanding of age related changes to the retinal layers and their effect on visual loss.

Genetic variation affects morphological retinal phenotypes extracted from UK Biobank optical coherence tomography images

Optical Coherence Tomography (OCT) enables non-invasive imaging of the retina and is used to diagnose and manage ophthalmic diseases including glaucoma. We present the first large-scale genome-wide association study of inner retinal morphology using phenotypes derived from OCT images of 31,434 UK Biobank participants. We identify 46 loci associated with thickness of the retinal nerve fibre layer or ganglion cell inner plexiform layer. Only one of these loci has been associated with glaucoma, and despite its clear role as a biomarker for the disease, Mendelian randomisation does not support inner retinal thickness being on the same genetic causal pathway as glaucoma. We extracted overall retinal thickness at the fovea, representative of foveal hypoplasia, with which three of the 46 SNPs were associated. We additionally associate these three loci with visual acuity. In contrast to the Mendelian causes of severe foveal hypoplasia, our results suggest a spectrum of foveal hypoplasia, in part genetically determined, with consequences on visual function.

Retinal asymmetry in multiple sclerosis

The diagnosis of multiple sclerosis is based on a combination of clinical and paraclinical tests. The potential contribution of retinal optical coherence tomography (OCT) has been recognized. We tested the feasibility of OCT measures of retinal asymmetry as a diagnostic test for multiple sclerosis at the community level. In this community-based study of 72 120 subjects, we examined the diagnostic potential of the inter-eye difference of inner retinal OCT data for multiple sclerosis using the UK Biobank data collected at 22 sites between 2007 and 2010. OCT reporting and quality control guidelines were followed. The inter-eye percentage difference (IEPD) and inter-eye absolute difference (IEAD) were calculated for the macular retinal nerve fibre layer (RNFL), ganglion cell inner plexiform layer (GCIPL) complex and ganglion cell complex. Area under the receiver operating characteristic curve (AUROC) comparisons were followed by univariate and multivariable comparisons accounting for a large range of diseases and co-morbidities. Cut-off levels were optimized by ROC and the Youden index. The prevalence of multiple sclerosis was 0.0023 [95% confidence interval (CI) 0.00229–0.00231]. Overall the discriminatory power of diagnosing multiple sclerosis with the IEPD AUROC curve (0.71, 95% CI 0.67–0.76) and IEAD (0.71, 95% CI 0.67–0.75) for the macular GCIPL complex were significantly higher if compared to the macular ganglion cell complex IEPD AUROC curve (0.64, 95% CI 0.59–0.69, P = 0.0017); IEAD AUROC curve (0.63, 95% CI 0.58–0.68, P < 0.0001) and macular RNFL IEPD AUROC curve (0.59, 95% CI 0.54–0.63, P < 0.0001); IEAD AUROC curve (0.55, 95% CI 0.50–0.59, P < 0.0001). Screening sensitivity levels for the macular GCIPL complex IEPD (4% cut-off) were 51.7% and for the IEAD (4 μm cut-off) 43.5%. Specificity levels were 82.8% and 86.8%, respectively. The number of co-morbidities was important. There was a stepwise decrease of the AUROC curve from 0.72 in control subjects to 0.66 in more than nine co-morbidities or presence of neuromyelitis optica spectrum disease. In the multivariable analyses greater age, diabetes mellitus, other eye disease and a non-white ethnic background were relevant confounders. For most interactions, the effect sizes were large (partial ω² > 0.14) with narrow confidence intervals. In conclusion, the OCT macular GCIPL complex IEPD and IEAD may be considered as supportive measurements for multiple sclerosis diagnostic criteria in a young patient without relevant co-morbidity. The metric does not allow separation of multiple sclerosis from neuromyelitis optica. Retinal OCT imaging is accurate, rapid, non-invasive, widely available and may therefore help to reduce need for invasive and more costly procedures. To be viable, higher sensitivity and specificity levels are needed.

Factors Associated with the Macular Ganglion Cell-Inner Plexiform Layer Thickness in a Cohort of Middle-aged U.S. Adults

SIGNIFICANCE

The macular ganglion cell-inner plexiform layer (mGCIPL) may serve as a quick and easily obtained measure of generalized neurodegeneration. Investigating factors associated with this thickness could help to understand neurodegenerative processes.

PURPOSE

This study aimed to characterize and identify associated factors of the mGCIPL thickness in a Beaver Dam Offspring Study cohort of middle-aged U.S. adults.

METHODS

Baseline examinations occurred from 2005 to 2008, with follow-up examinations every 5 years. Included participants had baseline data and measured mGCIPL at 10-year follow-up (N = 1848). The mGCIPL was measured using the Cirrus 5000 HD-OCT Macular Cube Scan. Associations between mean mGCIPL thickness and thin mGCIPL, defined as 1 standard deviation (SD) below the population mean, and baseline risk factors were investigated using generalized estimating equations.

RESULTS

Participants (mean [SD] baseline age, 48.9 [9.3] years; 54.4% women) had mean (SD) mGCIPL thicknesses of 78.4 (8.1) μm in the right eye and 78.1 (8.5) μm in the left (correlation coefficient = 0.76). In multivariable models, age (-1.07 μm per 5 years; 95% confidence interval [CI], -1.28 to -0.86 μm), high alcohol consumption (-1.44 μm; 95% CI, -2.72 to -0.16 μm), higher interleukin 6 levels (50% increase in level: -0.23 μm; 95% CI, -0.45 to 0.00 μm), myopia (-2.55 μm; 95% CI, -3.17 to -1.94 μm), and glaucoma (-1.74 μm; 95% CI, -2.77 to -0.70 μm) were associated with thinner mGCIPL. Age (per 5 years: odds ratio [OR], 1.38; 95% CI, 1.24 to 1.53), diabetes (OR, 1.89, 95% CI, 1.09 to 3.27), myopia (OR, 2.11; 95% CI, 1.63 to 2.73), and increasing and long-term high C-reactive protein (ORs, 1.46 [95% CI, 1.01 to 2.11] and 1.74 [95% CI, 1.14 to 2.65], respectively) were associated with increased odds of thin mGCIPL.

CONCLUSIONS

Factors associated cross-sectionally with mGCIPL thickness, older age, high alcohol consumption, inflammation, diabetes, myopia, and glaucoma may be important to neural retina structure and health and neuronal health system-wide.

Association of ambient air pollution with age-related macular degeneration and retinal thickness in UK Biobank

AIM

To examine the associations of air pollution with both self-reported age-related macular degeneration (AMD), and in vivo measures of retinal sublayer thicknesses.

METHODS

We included 115 954 UK Biobank participants aged 40-69 years old in this cross-sectional study. Ambient air pollution measures included particulate matter, nitrogen dioxide (NO₂) and nitrogen oxides (NO_x). Participants with self-reported ocular conditions, high refractive error (< -6 or > +6 diopters) and poor spectral-domain optical coherence tomography (SD-OCT) image were excluded. Self-reported AMD was used to identify overt disease. SD-OCT imaging derived photoreceptor sublayer thickness and retinal pigment epithelium (RPE) layer thickness were used as structural biomarkers of AMD for 52 602 participants. We examined the associations of ambient air pollution with self-reported AMD and both photoreceptor sublayers and RPE layer thicknesses.

RESULTS

After adjusting for covariates, people who were exposed to higher fine ambient particulate matter with an aerodynamic diameter <2.5 µm (PM_2.5, per IQR increase) had higher odds of self-reported AMD (OR=1.08, p=0.036), thinner photoreceptor synaptic region (β=-0.16 µm, p=2.0 × 10^-5), thicker photoreceptor inner segment layer (β=0.04 µm, p=0.001) and thinner RPE (β=-0.13 µm, p=0.002). Higher levels of PM_2.5 absorbance and NO₂ were associated with thicker photoreceptor inner and outer segment layers, and a thinner RPE layer. Higher levels of PM₁₀ (PM with an aerodynamic diameter <10 µm) was associated with thicker photoreceptor outer segment and thinner RPE, while higher exposure to NO_x was associated with thinner photoreceptor synaptic region.

CONCLUSION

Greater exposure to PM_2.5 was associated with self-reported AMD, while PM_2.5, PM_2.5 absorbance, PM₁₀, NO₂ and NO_x were all associated with differences in retinal layer thickness.

Retinal layer thicknesses retrieved with different segmentation algorithms from optical coherence tomography scans acquired under different signal-to-noise ratio conditions

Glaucomatous damage can be quantified by measuring the thickness of different retinal layers. However, poor image quality may hamper the accuracy of the layer thickness measurement. We determined the effect of poor image quality (low signal-to-noise ratio) on the different layer thicknesses and compared different segmentation algorithms regarding their robustness against this degrading effect. For this purpose, we performed OCT measurements in the macular area of healthy subjects and degraded the image quality by employing neutral density filters. We also analysed OCT scans from glaucoma patients with different disease severity. The algorithms used were: The Canon HS-100's built-in algorithm, DOCTRAP, IOWA, and FWHM, an approach we developed. We showed that the four algorithms used were all susceptible to noise at a varying degree, depending on the retinal layer assessed, and the results between different algorithms were not interchangeable. The algorithms also differed in their ability to differentiate between young healthy eyes and older glaucoma eyes and failed to accurately separate different glaucoma stages from each other.

Alcohol consumption is associated with glaucoma severity regardless of ALDH2 polymorphism

The present study investigated the effect of aldehyde dehydrogenase2 (ALDH2) rs671 polymorphism and alcohol consumption on the severity of primary open-angle glaucoma (POAG). The questionnaire for alcohol consumption pattern and targeted genotyping for ALDH2 rs671 polymorphism was performed from 445 Korean POAG patients. Retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thicknesses were measured and compared according to alcohol consumption and ALDH2 rs671 genotype. Heavy drinking group eyes had thinner RNFL thickness than did abstinence group eyes (65.0 ± 10.9 vs. 70.9 ± 11.5 µm, P = 0.023). Both mild (65.8 ± 9.6 µm) and heavy (63.8 ± 8.4 µm) drinking group eyes had significantly thinner macular GCIPL thickness than did abstinence group eyes (68.1 ± 8.2 µm, P = 0.003). However, ALDH2 rs671 polymorphism did not show any significant association with RNFL or GCIPL thickness. Alcohol consumption was significantly associated with GCIPL thinning (β = –0.446, P = 0.035) after adjustment for multiple confounding factors. As excessive alcohol consumption was significantly associated with thinner GCIPL thickness while ALDH2 polymorphism had no significant effect on RNFL or GCIPL thickness, glaucoma patients should avoid excessive alcohol consumption regardless of ALDH2 polymorphism.

Ambient Air Pollution Associations with Retinal Morphology in the UK Biobank

Purpose

Because air pollution has been linked to glaucoma and AMD, we characterized the relationship between pollution and retinal structure.

Methods

We examined data from 51,710 UK Biobank participants aged 40 to 69 years old. Ambient air pollution measures included particulates and nitrogen oxides. SD-OCT imaging measured seven retinal layers: retinal nerve fiber layer, ganglion cell–inner plexiform layer, inner nuclear layer, outer plexiform layer + outer nuclear layer, photoreceptor inner segments, photoreceptor outer segments, and RPE. Multivariable regression was used to evaluate associations between pollutants (per interquartile range increase) and retinal thickness, adjusting for age, sex, race, Townsend deprivation index, body mass index, smoking status, and refractive error.

Results

Participants exposed to greater particulate matter with an aerodynamic diameter of <2.5 µm (PM_2.5) and higher nitrogen oxides were more likely to have thicker retinal nerve fiber layer (β = 0.28 µm; 95% CI, 0.22–0.34; P = 3.3 × 10⁻²⁰ and β = 0.09 µm; 95% CI, 0.04–0.14; P = 2.4 × 10⁻⁴, respectively), and thinner ganglion cell–inner plexiform layer, inner nuclear layer, and outer plexiform layer + outer nuclear layer thicknesses (P < 0.001). Participants resident in areas of higher levels of PM_2.5 absorbance were more likely to have thinner retinal nerve fiber layer, inner nuclear layer, and outer plexiform layer + outer nuclear layers (β = –0.16 [95% CI, –0.22 to –0.10; P = 5.7 × 10⁻⁸]; β = –0.09 [95% CI, –0.12 to –0.06; P = 2.2 × 10⁻¹²]; and β = –0.12 [95% CI, –0.19 to –0.05; P = 8.3 × 10⁻⁴], respectively).

Conclusions

Greater exposure to PM_2.5, PM_2.5 absorbance, and nitrogen oxides were all associated with apparently adverse retinal structural features.

Macular Ganglion Cell-Inner Plexiform Layer as a Marker of Cognitive and Sensory Function in Midlife

BACKGROUND

Neurodegenerative diseases are public health challenges in aging populations. Early identification of people at risk for neurodegeneration might improve targeted treatment. Noninvasive, inexpensive screening tools are lacking but are of great potential. Optical coherence tomography (OCT) measures the thickness of nerve cell layers in the retina, which is an anatomical extension of the brain and might be indicative of common underlying neurodegeneration. We aimed to determine the association of macular ganglion cell-inner plexiform layer (mGCIPL) thickness with cognitive and sensorineural function in midlife.

METHOD

This cross-sectional study included 1,880 Beaver Dam Offspring Study participants (aged 27-93 years, mean 58) who participated in the 10-year follow-up examination. We assessed cognitive function and impairment, hearing sensitivity thresholds and impairment, central auditory processing, visual impairment, and olfactory impairment. We measured mGCIPL using the Cirrus 5000 HD-OCT Macular Cube Scan. Multivariable linear and logistic regression models adjusted for potential confounders were used to determine associations between mGCIPL thickness and cognitive and sensorineural functions, as well as for comparing participants with a thin mGCIPL (1 SD below average) to the remainder in those functions.

RESULTS

Thinner mGCIPL was associated with worse cognitive function, worse central auditory function, and visual impairment. We found an association of mGCIPL thickness with hearing sensitivity in women only and no association with impairment in hearing, olfaction, and cognition. Results on the thin group comparisons were consistent.

CONCLUSIONS

mGCIPL thickness is associated with cognitive and sensorineural function and has the potential as a marker for neurodegeneration in middle-aged adults.

The Relationship Between Ambient Atmospheric Fine Particulate Matter (PM2.5) and Glaucoma in a Large Community Cohort

Purpose

Glaucoma is more common in urban populations than in others. Ninety percent of the world's population are exposed to air pollution above World Health Organization (WHO) recommended limits. Few studies have examined the association between air pollution and glaucoma.

Methods

Questionnaire data, ophthalmic measures, and ambient residential area air quality data for 111,370 UK Biobank participants were analyzed. Particulate matter with an aerodynamic diameter < 2.5 μm (PM2.5) was selected as the air quality exposure of interest. Eye measures included self-reported glaucoma, intraocular pressure (IOP), and average thickness of macular ganglion cell-inner plexiform layer (GCIPL) across nine Early Treatment Diabetic Retinopathy Study (ETDRS) retinal subfields as obtained from spectral-domain optical coherence tomography. We examined the associations of PM2.5 concentration with self-reported glaucoma, IOP, and GCIPL.

Results

Participants resident in areas with higher PM2.5 concentration were more likely to report a diagnosis of glaucoma (odds ratio = 1.06, 95% confidence interval [CI] = 1.01-1.12, per interquartile range [IQR] increase P = 0.02). Higher PM2.5 concentration was also associated with thinner GCIPL (β = -0.56 μm, 95% CI = -0.63 to -0.49, per IQR increase, P = 1.2 × 10-53). A dose-response relationship was observed between higher levels of PM2.5 and thinner GCIPL (P < 0.001). There was no clinically relevant relationship between PM2.5 concentration and IOP.

Conclusions

Greater exposure to PM2.5 is associated with both self-reported glaucoma and adverse structural characteristics of the disease. The absence of an association between PM2.5 and IOP suggests the relationship may occur through a non-pressure-dependent mechanism, possibly neurotoxic and/or vascular effects.