Front. Med. Frontiers in Medicine Front. Med. 2296-858X Frontiers Media S.A. 10.3389/fmed.2024.1410607 Medicine Original Research A study exploring the causal relationship between glaucoma and anxiety disorders Lin Bin 1 2 3 4 5 6 † Xu Meng 1 2 3 4 5 6 † Chen Long-long 1 2 3 4 5 6 Li Dong-kan 1 2 3 4 5 6 * 1Xiamen Eye Center and Eye Institute of Xiamen University, Xiamen, China 2Xiamen Clinical Research Center for Eye Diseases, Xiamen, Fujian, China 3Xiamen Key Laboratory of Ophthalmology, Xiamen, Fujian, China 4Fujian Key Laboratory of Corneal and Ocular Surface Diseases, Xiamen, Fujian, China 5Xiamen Key Laboratory of Corneal and Ocular Surface Diseases, Xiamen, Fujian, China 6Translational Medicine Institute of Xiamen Eye Center of Xiamen University, Xiamen, Fujian, China

Edited by: Alessio Martucci, University of Rome Tor Vergata, Italy

Reviewed by: Ferdinando Cione, University of Salerno, Italy

Vanja Kopilaš, University of Zagreb, Croatia

 *Correspondence: Dong-kan Li, xmecldk@163.com

†These authors have contributed equally to this work and share first authorship

 07 08 2024 2024 11 1410607 01 04 2024 29 07 2024 Copyright © 2024 Lin, Xu, Chen and Li. 2024 Lin, Xu, Chen and Li

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

 Background

Glaucoma, a leading cause of global blindness, is characterized by optic nerve damage and visual field loss. Previous studies have suggested a potential association between glaucoma and anxiety disorders. However, the causal relationship between these two conditions remains unclear.

 Methods

In this study, we conducted a Mendelian Randomization analysis to investigate the causal relationship between glaucoma and anxiety disorders. We sourced Genome-Wide Association Study (GWAS) datasets for glaucoma and anxiety with the largest sample sizes from the Integrative Epidemiology Unit OpenGWAS (IEU OpenGWAS) project website. Instrumental variables were selected based on specific criteria, and statistical analyses were performed using the R programming language.

 Results

After filtering and merging the datasets, a total of 60 Single Nucleotide Polymorphisms (SNPs) were obtained for analysis. Regression models were applied to assess the causal relationship between glaucoma and anxiety disorders. The results from all four methods indicated that glaucoma does not cause anxiety disorders (p > 0.05).

 Conclusion

Through rigorous Mendelian Randomization analysis, our findings indicate that glaucoma is not a causative factor for anxiety, with minimal influence from confounding factors in this study. These findings enhance our understanding of the relationship between glaucoma and anxiety.

 glaucoma anxiety disorders causal relationship Mendelian Randomization GWAS datasets Xiamen Municipal Bureau of Science and Technology10.13039/100010166 section-at-acceptance Ophthalmology 1 Background

Glaucoma, a leading cause of global blindness, is characterized by optic nerve damage and visual field loss, often culminating in blindness (1). With multifactorial etiology, it affects approximately 5.2 million individuals worldwide, constituting 15% of the global burden of blindness (2). Moreover, due to population aging, its prevalence is expected to rise, projected to affect approximately 112 million people by 2040 (3).

Anxiety disorders represent the most prevalent mental health issues globally, significantly impacting individuals’ quality of life, work productivity, and societal well-being. Despite being distinct diagnostic entities, anxiety often coexist clinically, demonstrating high comorbidity (4). Globally, it is estimated that 3.7% of individuals will experience Generalized Anxiety Disorder (GAD) at some point in their lives (5). The impact of GAD on functioning and quality of life is comparable to, or even greater than, the effects associated with severe depression and substance abuse disorders (6).

In recent years, increasing attention has been directed toward the high prevalence of anxiety among individuals with glaucoma. These studies suggest that glaucoma is not solely a visually impairing ocular condition but may also be linked to patients’ psychological well-being, indicating a close interplay between the two (7–10).

In our research, we employed the two-sample Mendelian Randomization (MR) approach, leveraging Single Nucleotide Polymorphisms (SNPs) as instrumental variables derived from Genome-Wide Association Study (GWAS) summary statistics. This methodology was utilized to explore the potential causal linkage between Glaucoma and Anxiety. By conducting this gene-centric analysis, our goal was to surpass the constraints associated with conventional research methodologies, thereby furnishing more robust evidence in favor of a causal connection between Glaucoma and anxiety, as depicted in Figure 1.

The causal relationship between Glaucoma and anxiety can be further confirmed by Mendelian Randomization studies and the effect of confounding factors can be excluded.

 2 Materials and methods

We conducted a Mendelian Randomization investigation to elucidate the potential causal association between Glaucoma and the susceptibility to anxiety. The MR methodology employs genetic variants as instrumental variables to estimate the causal impact of the exposure (Glaucoma) on the outcome (risk of anxiety), while mitigating the influence of confounding factors. All statistical analyses were executed using the R programming language, employing specialized software packages tailored for MR studies such as TwoSampleMR and Mendelian Randomization.

2.1 Data source

We sourced GWAS datasets for Glaucoma (Pubmed ID: GCST90011766) and anxiety (Pubmed ID: GCST007710) with the largest sample sizes from the Integrative Epidemiology Unit OpenGWAS (IEU OpenGWAS) project website.1 Raw data can be accessed via the respective publications on the Pubmed website. Data retrieval occurred on March 21, 2024. Both datasets comprised European populations without gender restrictions. The Glaucoma dataset encompassed 14,219,919 SNPs, while the anxiety dataset comprised 18,485,882 SNPs.

 2.2 Instrumental variable criteria

Criteria for selecting SNPs as instrumental variables were as follows:

The instrumental variables exhibited high correlation with the exposure, with an F-statistic exceeding 10 indicating substantial correlation (11).

Instrumental variables were not directly associated with the outcome but influenced it solely through the exposure, indicating absence of genetic pleiotropy. A pleiotropy test was conducted, with a result of P ≥ 0.05 signifying no genetic pleiotropy.

Instrumental variables were unrelated to unmeasured confounding factors. Since MR-selected SNPs adhere to the genetic principle of random allele allocation from parents to offspring, their susceptibility to environmental and postnatal factors is minimal. Thus, it was theoretically assumed that instrumental variables remained independent of environmental factors such as socioeconomic and cultural influences (12).

 2.3 SNP selection

Meaningful SNPs were selected from the GWAS summary data of Glaucoma based on a screening criterion of P < 5 × 10–8. Each SNP’s independence was ensured by setting a linkage disequilibrium coefficient (r2) of 0.001 and a linkage disequilibrium region width of 10,000 kb, thereby mitigating the potential influence of genetic pleiotropy (13). Glaucoma-associated SNPs were then extracted from the anxiety GWAS summary data, with a minimum r2 > 0.8 to ensure result accuracy. Missing SNPs were directly excluded. The datasets were integrated, and SNPs directly associated with anxiety (P < 5 × 10–8) were filtered out.

 2.4 Causal relationship verification

To verify the causal relationship between Glaucoma exposure and anxiety outcome using SNPs as instrumental variables, we employed four regression models: MR-Egger regression, weighted median estimator (WME), inverse-variance weighted (IVW) random-effects model, and simple model. The IVW method directly calculates causal effect estimates using summary data, without the need for individual-level data. MR-Egger regression fits a linear function by assessing the correlation between each SNP and anxiety (Y) and between each SNP and Glaucoma (X). Sensitivity analysis utilized the leave-one-out method. All analyses were conducted using the TwoSampleMR package (version 0.5.11) in R Studio software (version 4.3.3), with a significance level of α = 0.05.

 3 Results 3.1 SNP information screening results

A total of 14,219,919 SNP information was obtained for Glaucoma. After filtering based on a criterion of P-value < 5 × 10–8, 4,358 SNPs remained. The file “exposure_GLA.csv” was exported and placed in the TwoSampleMR folder. After renaming the sequence names, SNPs were selected to ensure independence by setting a linkage disequilibrium coefficient (r2) of 0.001 and a linkage disequilibrium region width of 10,000 kb, excluding the influence of genetic pleiotropy. This resulted in the removal of 4,297 SNPs, leaving 61 SNP data. At this time, the SNP database of anxiety was imported, and the number of SNPs obtained was 18,485,882. Then, the anxiety data and Glaucoma data which just screened were merged, and 60 SNPs were finally obtained (Table 1). Heterogeneity test was carried out on these 60 SNP data, and three sets of outlier data were found, namely data No. 17, 45, and 49. No significant changes were found when they were removed. According to MR Egger regression model, p = 0.56, IVW regression model, p = 0.56, both of which are greater than 0.05, suggesting that glaucoma does not cause anxiety disorder.

Summary of the selected SNP information.

Number SNP CHR BP A1 Beta SE
1 rs10151220 14 34715465 T −0.0019 0.0015
2 rs10230941 7 117636111 C 0.0013 0.0015
3 rs10248136 7 39077397 T −0.0022 0.0015
4 rs10517281 4 54027595 A 9.00E−04 0.0015
5 rs10739689 9 129914147 C 6.00E−04 0.0015
6 rs111439095 13 76254433 A 0.0014 0.0015
7 rs1139795 22 19867771 T 0.0013 0.0016
8 rs11658334 17 58830188 A 6.00E−04 0.0017
9 rs11968883 6 158971411 T 0.0022 0.0015
10 rs12208086 6 36586070 A −0.0026 0.0015
11 rs12540035 7 116159526 A −0.004 0.0015
12 rs1336980 9 129377855 C 3.00E−04 0.0015
13 rs1649068 10 60304864 A 0.0036 0.0015
14 rs17125973 14 53415359 A 0.0014 0.0015
15 rs17527016 4 111963719 T −4.00E−04 0.0015
16 rs1972459 7 83287607 A −0.0021 0.0015
17 rs2113818 2 12890860 T −0.0016 0.0015
18 rs2472494 9 107695539 T −0.0022 0.0015
19 rs2514885 8 108277130 T 0.0014 0.0015
20 rs257336 16 65055840 T 0.0054 0.0015
21 rs2579989 6 51460154 T 0 0.0015
22 rs2627761 2 55933014 T 8.00E−04 0.0016
23 rs2667477 12 84023388 T 0.0022 0.0015
24 rs2735114 6 29910034 A 0.001 0.0015
25 rs2745572 6 1548369 A 0.0018 0.0015
26 rs2790049 1 165743523 A 0.0018 0.0015
27 rs2811688 6 134372150 C −6.00E−04 0.0015
28 rs31916 5 14814883 A 0.0024 0.0015
29 rs33912345 14 60976537 A 9.00E−04 0.0016
30 rs36039219 7 11704538 A 2.00E−04 0.0015
31 rs3753841 1 103379918 A 0.0031 0.0015
32 rs3825942 15 74219582 A −0.0026 0.0016
33 rs41283694 10 60156574 A 0.0029 0.0016
34 rs41543317 17 44087500 A −8.00E−04 0.0015
35 rs4414666 2 66537344 T 0 0.0015
36 rs4577906 7 82955177 C 0.0035 0.0015
37 rs4652964 1 38078300 A 0.0012 0.0015
38 rs4653159 1 36579215 A 0.0022 0.0015
39 rs4819641 22 18353630 C 0.0014 0.0015
40 rs55882252 2 153361700 T 0 0.0015
41 rs56233426 3 186128816 A −0.0028 0.0015
42 rs58073046 11 120248493 A −0.0011 0.0015
43 rs581796 11 86355565 T 0.003 0.0015
44 rs6117318 20 6507717 A −9.00E−04 0.0015
45 rs62283809 3 171820211 T −0.0015 0.0017
46 rs6475604 9 22052734 T 8.00E−04 0.0015
47 rs6490697 13 22679011 T −0.0017 0.0016
48 rs6602453 10 10840849 A −1.00E−04 0.0015
49 rs676015 6 2064648 T −7.00E−04 0.0015
50 rs6845653 4 7899379 T 0.0032 0.0015
51 rs7137828 12 111932800 T −0.0064 0.0015
52 rs72482850 1 101117684 A 4.00E−04 0.0015
53 rs7275118 20 18010447 T −5.00E−04 0.0015
54 rs7284245 22 29613441 T −4.00E−04 0.0016
55 rs7946009 11 128387422 T −0.0037 0.0015
56 rs7972874 12 28203245 A −3.00E−04 0.0015
57 rs935328 15 57538801 A −0.0022 0.0015
58 rs9494457 6 136474794 A −4.00E−04 0.0015
59 rs9819278 3 85144350 A −0.0052 0.0015
60 rs9913911 17 10031183 A 1.00E−04 0.0015

SNP, SNP number; CHR, chromosome number; BP: location, A1: effector allele.

 3.2 Causal relationship verification

The regression results of the four methods are shown in Table 2. And all the calculation result of the regression models are greater than 0.05. So this Mendelian randomization study tells us that glaucoma patients do not have a higher incidence of anxiety. The scatter plot is shown in Figure 2.

Regression model results of the four methods.

Four methods MR regression model results
Method β se OR (95% CI) P
MR-Egger 0.003 0.006 1.004(0.991∼1.016) 0.563
WME 0.000 0.003 1.000(0.995∼1.005) 1.000
IVW 0.002 0.003 0.998 (0.993∼1.004) 0.556
Simple mode 0.002 0.006 1.002 (0.992∼1.013) 0.725

WME, weighted median estimator; IVW, inverse-variance weighted.

Four Scatter plots of regression models are shown in the figure. Apart from the MR Egger regression line, all other regression lines pass through the origin, and the intercept of the MR Egger regression line with the y-axis has an absolute value of less than 0.001. This indicates that there is virtually no apparent confounding in this study.

 3.3 Sensitivity analysis

The sensitivity analysis was performed using the leave-one-out method, and the results showed that regardless of which SNP was removed, the conclusions have not changed. This suggests that removing any individual SNP would not have a significant impact on the results, indicating the robustness of the MR findings in this study. The funnel plot and detailed sensitivity analysis results can be found in Figures 3, 4, respectively.

Funnel plot distribution of 44 SNP information. The funnel plot displays good symmetry, suggesting that the SNP variations included in this study are consistent regarding the effect size and direction on the exposure factor, thus indicating low heterogeneity. This supports the reliability of the study results.

Sensitivity analysis results of the 44 SNP information. All markers observed span the coordinate zero, and excluding any single marker does not alter the conclusions. This demonstrates the robustness of the study findings.

 4 Discussion

Glaucoma is characterized by optic neuropathy with a hallmark of progressive loss of retinal ganglion cells (14). Currently, there are no effective treatments for the degeneration of these cells, and the primary goal of glaucoma management is to reduce the intraocular pressure (15) and prevent progression (16). Particularly since intraocular pressure is the only treatable risk factor (17) in clinical practice, both doctors and patients give it special attention, making it a chronic condition that requires lifelong care (18). However, chronic illnesses are often associated with psychological disorders such as anxiety (19, 20). Agorastos et al. (21) found that among glaucoma patients, the prevalence of anxiety in those with visual field defects was 44.8%, compared to 24.3% in those without visual field defects (21). However, DY Shin et al. found that patients with anxiety showed faster rates of Retinal Nerve Fiber Layer (RNFL) decline, as measured by Optical Coherence Tomography (OCT) (10).

There is a substantial body of research indicating high prevalence rates of anxiety among glaucoma patients (22, 23). These studies suggest that the heightened incidence of anxiety may stem from the diagnosis of glaucoma itself, driven by concerns over potential blindness, the financial burdens of treatment, and impaired daily activities (24, 25). Anxiety, as stress responses, are thought to originate in the amygdala (26), eliciting neurotransmitter release and stimulating the autonomic nervous system (ANS), which impacts multiple organs (27). The ANS’s response to emotional stress may play a significant role in the development or progression of glaucoma (28, 29). Furthermore, excessive retinal oxidative stress in glaucoma, leading to widespread loss of melanopsin-expressing retinal ganglion cells, plays a critical role in non-visual phototransduction, affecting circadian rhythm changes and melatonin production indirectly (30, 31). Additionally, some glaucoma medications may alter patients’ mood (32).

Despite the abundance of studies indicating a link between glaucoma and increased rates of anxiety, contrasting research from various global scholars suggests that glaucoma patients do not exhibit a heightened probability of suffering from these mental health conditions (33–35). All these clinical investigations have yet to definitively establish the causal relationship between glaucoma and anxiety.

Traditional epidemiological studies are hindered by confounding factors and reverse causality, complicating the determination of the true causal relationship between glaucoma and mental health issues. In this context, MR offers a unique approach, utilizing genetic variants as instrumental variables to estimate the causal effect of one factor on another, circumventing the limitations inherent in the aforementioned study designs (36).

Therefore, we decided to further explore the relationship between glaucoma and anxiety disorders using MR studies. Our findings across various models, including MR Egger regression, Inverse Variance Weighted (IVW) regression, and Weighted Median regression models, indicate that glaucoma does not cause anxiety disorders, with p-values of 0.56 for both MR Egger and IVW models, exceeding the threshold of 0.05. Even after excluding three outliers, the conclusion remained unchanged, and sensitivity analyses confirmed the stability of this conclusion. Pleiotropy analysis yielded a p-value of 0.38, suggesting that the trial results are reliable and not overly influenced by confounding factors. Additionally, the intercept of the MR-Egger regression line with the y-axis being less than 0.001 in Figure 2 also indicates a low likelihood of confounding factors. These MR study results suggest that there is no direct causal link between glaucoma and anxiety, and there are no significant confounding factors at the genetic level. It should be noted that even among Asians, studies have shown significant variability in the prevalence of anxiety among patients with glaucoma. Specifically, the prevalence of anxiety in Japanese glaucoma patients is 13.0% (8), while in Chinese patients, it is 22.9% (37). Notably, the prevalence in Singaporean glaucoma patients reaches as high as 64% (38). Scholars have found that these studies differ in terms of research design, sample size, and demographic characteristics (24). These findings contribute to a better understanding of the relationship between glaucoma and anxiety.

The availability of GWAS data for East Asian and African populations is limited. Although we found an East Asian Glaucoma SNP database through the IEU OpenGWAS project website (PubMed ID: GCST005388), a reliable database related to anxiety in the East Asian population was not found. To ensure the accuracy of our experimental results, we ultimately opted to use a European database. This decision also facilitates future comparisons with research conducted by other scholars. Finally, while this study explored the genetic association between glaucoma and anxiety within a European population database, it holds implications for the prevention and treatment of anxiety caused by glaucoma in other populations and nations. However, we must acknowledge that the lack of analysis of other ethnic groups represents a significant limitation of our research.

It is important to note that this study does not completely exclude the relationship between elevated intraocular pressure and anxiety. This indeed presents an interesting direction for research, which could further elucidate the interpretation of our results. We hope that our team can present findings in this area shortly.

 5 Conclusion

Through rigorous Mendelian Randomization analysis, our findings indicate that glaucoma is not a causative factor for anxiety, with minimal influence from confounding factors in this study. These findings enhance our understanding of the relationship between glaucoma and anxiety.

 Data availability statement

The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

 Author contributions

BL: Data curation, Formal analysis, Methodology, Software, Writing – original draft, Writing – review and editing. MX: Data curation, Formal analysis, Methodology, Writing – original draft. L-lC: Data curation, Formal analysis, Funding acquisition, Writing – original draft. D-kL: Funding acquisition, Supervision, Writing – review and editing.

 Funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was supported by the Xiamen Municipal Bureau of Science and Technology (3502Z202374104).

We thank Jing Tang for their help in data collection in this study.

 Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

 Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

https://gwas.mrcieu.ac.uk

 References Stamatiou M Kazantzis D Theodossiadis P Chatziralli I. Depression in glaucoma patients: A review of the literature. Semin Ophthalmol. (2022) 37:29–35. 10.1080/08820538.2021.1903945 33822676 Thylefors B Negrel A. The global impact of glaucoma. Bull World Health Organ. (1994) 72:323. Tham Y Li X Wong T Quigley H Aung T Cheng C. Global prevalence of glaucoma and projections of glaucoma burden through 2040: A systematic review and meta-analysis. Ophthalmology. (2014) 121:2081–90. 10.1016/j.ophtha.2014.05.013 24974815 Tiller J. Depression and anxiety. Med J Aust. (2013) 199:S28–31. 10.5694/mjao12.10628 32297660 Ruscio A Hallion L Lim C Aguilar-Gaxiola S Al-Hamzawi A Alonso J Cross-sectional comparison of the epidemiology of DSM-5 generalized anxiety disorder across the globe. JAMA Psychiatry. (2017) 74:465–75. 10.1001/jamapsychiatry.2017.0056 28297020 Hoffman D Dukes E Wittchen H. Human and economic burden of generalized anxiety disorder. Depress Anxiety. (2008) 25:72–90. 10.1002/da.20257 17146763 Cumurcu T Cumurcu B Celikel F Etikan I. Depression and anxiety in patients with pseudoexfoliative glaucoma. Gen Hosp Psychiatry. (2006) 28:509–15. 10.1016/j.genhosppsych.2006.09.004 17088167 Mabuchi F Yoshimura K Kashiwagi K Shioe K Yamagata Z Kanba S High prevalence of anxiety and depression in patients with primary open-angle glaucoma. J Glaucoma. (2008) 17:552–7. 10.1097/IJG.0b013e31816299d4 18854732 Skalicky S Goldberg I. Depression and quality of life in patients with glaucoma: A cross-sectional analysis using the geriatric depression scale-15, assessment of function related to vision, and the glaucoma quality of life-15. J Glaucoma. (2008) 17:546–51. 10.1097/IJG.0b013e318163bdd1 18854731 Shin D Jung K Park H Park C. The effect of anxiety and depression on progression of glaucoma. Sci Rep. (2021) 11:1769. 10.1038/s41598-021-81512-0 33469104 Boggs J Beck A Ritzwoller D Battaglia C Anderson H Lindrooth R. A quasi-experimental analysis of lethal means assessment and risk for subsequent suicide attempts and deaths. J Gen Intern Med. (2020) 35:1709–14. 10.1007/s11606-020-05641-4 32040838 Sanderson E Glymour M Holmes M Kang H Morrison J Munafò M Mendelian randomization. Nat Rev Methods Prim. (2022) 2:6. 10.1038/s43586-021-00092-5 37325194 Hemani G Zheng J Elsworth B Wade K Haberland V Baird D The MR-Base platform supports systematic causal inference across the human phenome. Elife. (2018) 7:e34408. 10.7554/eLife.34408 29846171 Weinreb R Aung T Medeiros F. The pathophysiology and treatment of glaucoma: A review. JAMA. (2014) 311:1901–11. 10.1001/jama.2014.3192 24825645 Heijl A Leske M Bengtsson B Hyman L Bengtsson B Hussein M Reduction of intraocular pressure and glaucoma progression: Results from the early manifest glaucoma trial. Arch Ophthalmol. (2002) 120:1268–79. 10.1001/archopht.120.10.1268 12365904 Khatib T Martin K. Protecting retinal ganglion cells. Eye. (2017) 31:218–24. 10.1038/eye.2016.299 28085136 De Bernardo M Casaburi C De Pascale I Capasso L Cione F Rosa N. Comparison between dynamic contour tonometry and Goldmann applanation tonometry correcting equations. Sci Rep. (2022) 12:20190. 10.1038/s41598-022-24318-y 36418360 Jindal V. Glaucoma: An extension of various chronic neurodegenerative disorders. Mol Neurobiol. (2013) 48:186–9. 10.1007/s12035-013-8416-8 23397135 Clarke D Currie K. Depression, anxiety and their relationship with chronic diseases: A review of the epidemiology, risk and treatment evidence. Med J Aust. (2009) 190:S54–60. 10.5694/j.1326-5377.2009.tb02471.x 19351294 Moussavi S Chatterji S Verdes E Tandon A Patel V Ustun B. Depression, chronic diseases, and decrements in health: Results from the world health surveys. Lancet. (2007) 370:851–8. 10.1016/S0140-6736(07)61415-9 17826170 Agorastos A Skevas C Matthaei M Otte C Klemm M Richard G Depression, anxiety, and disturbed sleep in glaucoma. J Neuropsychiatry Clin Neurosci. (2013) 25:205–13. 10.1176/appi.neuropsych.12020030 24026713 Zhang X Olson D Le P Lin F Fleischman D Davis R. The association between glaucoma, anxiety, and depression in a large population. Am J Ophthalmol. (2017) 183:37–41. 10.1016/j.ajo.2017.07.021 28760639 Wang S Singh K Lin S. Prevalence and predictors of depression among participants with glaucoma in a nationally representative population sample. Am J Ophthalmol. (2012) 154:436–444.e432. 10.1016/j.ajo.2012.03.039 22789562 Rezapour J Nickels S Schuster A Michal M Münzel T Wild P Prevalence of depression and anxiety among participants with glaucoma in a population-based cohort study: The Gutenberg health study. BMC Ophthalmol. (2018) 18:157. 10.1186/s12886-018-0831-1 29954361 Gelder M Gath D Mayou R. Oxford textbook of psychiatry. Oxford: Oxford university press (1989). Martin E Ressler K Binder E Nemeroff C. The neurobiology of anxiety disorders: Brain imaging, genetics, and psychoneuroendocrinology. Psychiatr Clin. (2009) 32:549–75. 10.1016/j.psc.2009.05.004 19716990 Hoehn-Saric R McLeod D Funderburk F Kowalski P. Somatic symptoms and physiologic responses in generalized anxiety disorderand panic disorder: An ambulatory monitor study. Arch Gen Psychiatry. (2004) 61:913–21. 10.1001/archpsyc.61.9.913 15351770 Shin D Jeon S Park H Park C. Posterior scleral deformation and autonomic dysfunction in normal tension glaucoma. Sci Rep. (2020) 10:8203. 10.1038/s41598-020-65037-6 32424225 Park H Jung S Park S Park C. Detecting autonomic dysfunction in patients with glaucoma using dynamic pupillometry. Medicine. (2019) 98:e14658. 10.1097/MD.0000000000014658 30882629 Jean-Louis G Zizi F Lazzaro D Wolintz A. Circadian rhythm dysfunction in glaucoma: A hypothesis. J Circadian Rhyth. (2008) 6:1. 10.1186/1740-3391-6-1 18186932 Drouyer E Dkhissi-Benyahya O Chiquet C WoldeMussie E Ruiz G Wheeler L Glaucoma alters the circadian timing system. PLoS One. (2008) 3:e3931. 10.1371/journal.pone.0003931 19079596 Weidenthal D. Charles Bonnet syndrome precipitated by brimonidine tartrate eye drops. J Pediatr. (2001) 138:441–3. Eramudugolla R Wood J Anstey K. Co-morbidity of depression and anxiety in common age-related eye diseases: A population-based study of 662 adults. Front Aging Neurosci. (2013) 5:56. 10.3389/fnagi.2013.00056 24106477 Jonas J Wei W Xu L Rietschel M Streit F Wang Y. Self-rated depression and eye diseases: The Beijing eye study. PLoS One. (2018) 13:e0202132. 10.1371/journal.pone.0202132 30096194 Weiss G Goldich Y Bartov E Burgansky-Eliash Z. Compliance with eye care in glaucoma patients with comorbid depression. IMAJ Israel Med Assoc J. (2011) 13:730. Richmond R Smith G. Mendelian randomization: Concepts and scope. Cold Spring Harb Perspect Med. (2022) 12:a040501. 10.1101/cshperspect.a040501 34426474 Zhou C Qian S Wu P Qiu C. Anxiety and depression in Chinese patients with glaucoma: Sociodemographic, clinical, and self-reported correlates. J Psychosom Res. (2013) 75:75–82. 10.1016/j.jpsychores.2013.03.005 23751243 Lim N Fan C Yong M Wong E Yip L. Assessment of depression, anxiety, and quality of life in Singaporean patients with glaucoma. J Glaucoma. (2016) 25:605–12. 10.1097/IJG.0000000000000393 26950574