Association between open angle glaucoma and early onset Alzheimer's disease

Abstract

Background

The association between open-angle glaucoma (OAG) and early-onset Alzheimer's disease (EOAD) remains unclear.

Objective

To investigate the association between OAG and EOAD.

Methods

We conducted a case-control study using a Japanese nationwide administrative claims database. Individuals aged 40–64 with a diagnosis of Alzheimer's disease (AD) and a prescription for AD medications were defined as EOAD cases (n = 2344). The index date was the first AD medication prescription. Controls (n = 9376) were matched to cases in a 4:1 ratio by age and sex using risk set sampling. OAG exposure was defined as a diagnosis ≥12 months before the index date. Conditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).

Results

OAG was present in 15.8% of EOAD cases and 12.5% of controls. A significant association was observed between OAG and EOAD (OR, 1.22; 95% CI, 1.06–1.40; p = 0.006). EOAD was associated with diabetes (OR, 1.56; 95% CI, 1.37–1.77; p < 0.001), hypertension (OR, 1.15; 95% CI, 1.02–1.29; p = 0.021), depression (OR, 7.81; 95% CI, 6.76–9.02; p < 0.001), and excessive alcohol use (OR, 2.35; 95% CI, 1.72–3.21; p < 0.001). In sex-stratified analyses, the association between OAG and EOAD was significant in males (OR, 1.32; 95% CI, 1.09–1.60; p = 0.005) but not in females (OR, 1.11; 95% CI, 0.90–1.37; p = 0.321).

Conclusions

Individuals with OAG may be associated with an increased risk of EOAD, and careful monitoring of cognitive symptoms may help facilitate early detection and intervention.

Keywords

Alzheimer's disease dementia early-onset Alzheimer's disease open-angle glaucoma

Introduction

Dementia currently affects more than 55 million individuals worldwide, projected to reach 152 million by 2050.¹ Despite the ongoing efforts to develop clinically effective treatments for dementia, no curative therapy is available.^2,3 Consequently, the priority has shifted toward implementing preventive strategies to reduce the risk of dementia.⁴

Recently, an increasing interest has been observed in understanding the relationship between vision impairment and dementia. In a population-based cross-sectional study of older adults, the population attributable fraction of dementia in vision impairments has been estimated to range from 4.9% to 19.0%.⁵ In addition, a meta-analysis revealed that vision impairment is associated with a 38% increased risk of dementia.⁶ Based on a wide range of research findings, the 2024 report by the Lancet Commission on Dementia identified vision loss as a modifiable risk factor for dementia.⁴

Among the various causes of vision impairment, glaucoma has been suggested to be associated with dementia, especially Alzheimer's disease (AD). Glaucoma shares several neurodegenerative characteristics with AD, including the accumulation of amyloid-β^7–10 and phosphorylated tau (p-tau).^7,8,11 Additionally, the apolipoprotein E gene, a known genetic risk factor of AD, is associated with an increased risk of open-angle glaucoma (OAG).^7,12,13 Moreover, several meta-analyses of observational cohort studies have reported that OAG significantly increases the risk of AD.^14,15

While previous epidemiological studies^16–20 have primarily focused on AD in older adults, no evidence supports the potential association between OAG and early-onset AD (EOAD), defined as AD with onset before 65 years of age. To address this knowledge gap, this study investigated the relationship between OAG and EOAD using a large-scale administrative database in Japan.

Methods

Data source

We conducted a case-control study using the administrative claims database provided by the JMDC (Tokyo, Japan). The JMDC database contains longitudinal healthcare information, including demographics and medical, pharmacy, and dental insurance claims, as well as insurance eligibility data. All these data are derived from health insurance societies and thus cover corporate employees and their dependents, spanning the period from April 2006 to March 2022. The database included approximately 9.8 million insured persons as of June 2020, corresponding to about 8% of the Japanese population.²¹ The database includes the following data: year and month of birth, sex, diagnosis, month and year of medical services administered, and prescribed medications. Diagnoses were coded according to the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) codes, and procedures were identified based on the coding system used in the Japanese healthcare system. Prescribed medications were identified using the Anatomical Therapeutic Chemical codes by the World Health Organization. The study was performed in accordance with the recommendations of the Declaration of Helsinki and approved by the Institutional Review Board of the University of Tokyo (Ethics approval ID: 10862-(1)). The requirement for informed consent was waived due to the use of anonymized data sources.

Study population

Patients aged 40–64 years were included in the case group (EOAD group) based on the following criteria: (1) diagnosis of AD using ICD-10 codes (F00, G30), and (2) prescription of medications for AD identified by the Anatomical Therapeutic Chemical code (N07), including donepezil, memantine, rivastigmine, and galantamine. The index date was defined as the date of the first prescription of the AD medication. The control group (non-EOAD group) was matched to the cases in a 4:1 ratio by age (±1 year) and sex using risk set sampling, selecting up to four controls per case from individuals at risk at the index date. Exposure was defined as a diagnosis of OAG in the JMDC database ≥12 months prior to the index date to reduce the risk of reverse causation, as similarly applied in previous studies.^22,23 OAG diagnoses were confirmed using ICD-10 codes, as detailed in Supplemental Table 1.

Covariates

The following information was collected at the index date for each group: age, sex, and comorbidities, including hypertension (I10-I15), diabetes (E10-E14), dyslipidemia (E78.0-E78.5), depression (F32, F33), hearing loss (H90, H91), excessive alcohol consumption (F10 and K70), obesity (E66), and glaucoma surgery.

Statistical analysis

Student's t-test or the Chi-square test was performed to compare patient characteristics between the AD and non-AD groups. Conditional logistic regression analysis was used to estimate the association between OAG and EOAD. The odds ratios (OR) and 95% confidence intervals (CI) were calculated for both univariable and multivariable analyses. In these analyses, age and sex were adjusted for by matching. Based on previously reported risk factors, the multivariable model was adjusted for the following covariates: hypertension,²⁴ diabetes,^22,25 dyslipidemia,^24,26 depression,^25,27 hearing loss,²⁵ excessive alcohol consumption,^25,26 and obesity.²⁴ The ORs were also estimated and stratified by sex. All statistical analyses were conducted using STATA/SE 15.0, for Mac (Stata Corp, College Station, TX, USA), and a p-value of less than 0.05 was considered to be statistically significant.

Results

As shown in Figure 1, the present study included 2344 EOAD cases and 9376 matched non-EOAD controls. Table 1 describes the patient characteristics during the index month. The mean age was 58.4 ± 5.1 years in both the EOAD and non-EOAD groups. In both groups, 46.5% were female. 370 patients (15.8%) had OAG in the EOAD group, whereas 1169 patients (12.5%) had OAG in the control group. Figure 2 shows the proportion of individuals diagnosed with glaucoma at least one year before the onset of EOAD. Across most age groups, the EOAD group exhibited a higher proportion of prior glaucoma diagnoses than the non-EOAD group, with the exception of women aged 40–44 years.

Figure 1.

Flow chart. AD: Alzheimer's disease; ICD-10: International Statistical Classification of Diseases and Related Health Problems, 10th revision; EOAD: early-onset Alzheimer's disease.

Figure 2.

Proportion of glaucoma diagnosed ≥ one year before EOAD, stratified by sex and age group. The figure shows the proportion of glaucoma diagnosed at least one year before early-onset Alzheimer's disease (EOAD) diagnosis across different age groups. (A) Overall: comparison of glaucoma diagnosis proportions between EOAD and non-EOAD individuals across all age groups. (B) Male: the proportion of glaucoma diagnoses in male patients with EOAD and non-EOAD. (C) Female: the proportion of glaucoma diagnoses in female patients with EOAD and non-EOAD.

Table 1.

Patient characteristics during the index month.

Characteristics	EOAD group (n = 2344)	Non-EOAD group (n = 9376)	p
Age, mean ± SD	58.4 ± 5.1	58.4 ± 5.1	0.85
Female, %	1089 (46.5%)	4356 (46.5%)	1.00
Hypertension, %	846 (36.1%)	2685 (28.6%)	<0.001
Diabetes, %	611 (26.1%)	1565 (16.7%)	<0.001
Dyslipidemia, %	875 (37.3%)	2702 (28.8%)	<0.001
Depression, %	670 (28.6%)	448 (4.8%)	<0.001
Hearing loss, %	144 (6.1%)	461 (4.9%)	0.016
Excessive alcohol consumption, %	104 (4.4%)	117 (1.2%)	<0.001
Obesity, %	23 (1.0%)	53 (0.6%)	0.025
Glaucoma surgery, %	1 (0.0%)	6 (0.1%)	0.71
Open angle glaucoma, %	370 (15.8%)	1169 (12.5%)	<0.001

EOAD: early-onset Alzheimer's disease; SD: standard deviation.

The association between OAG and EOAD is shown in Table 2. In the multivariable analysis, a significant association was observed between OAG and EOAD (OR, 1.22; 95% CI, 1.06–1.40). Additionally, EOAD was significantly associated with the following covariates: diabetes (OR, 1.56; 95% CI, 1.37–1.77); hypertension (OR, 1.15; 95% CI, 1.02–1.29); depression (OR, 7.81; 95% CI, 6.76–9.02); and excessive alcohol consumption (OR, 2.35; 95% CI, 1.72–3.21). There was no significant association of EOAD with dyslipidemia, hearing loss, or obesity. When analyzed in accordance with sex, a significant association was observed between OAG and EOAD in male patients (OR, 1.32; 95% CI, 1.09–1.60), whereas no significant association was found in female patients (OR, 1.11; 95% CI, 0.90–1.37). The adjusted ORs for male patients were as follows: diabetes, 1.42 (95% CI, 1.20–1.68); hypertension, 1.29 (95% CI, 1.11–1.50); depression, 8.16 (95% CI, 6.63–10.04); and excessive alcohol consumption, 2.45 (95% CI, 1.73–3.47). For female patients, the adjusted ORs were 1.78 (95% CI, 1.45–2.18) for diabetes and 7.69 (95% CI, 6.28–9.40) for depression (Table 3).

Table 2.

Association between early-onset Alzheimer's disease and other factors.

Variables	Unadjusted OR (95% CI)	Adjusted OR (95% CI)
Open angle glaucoma	1.32 (1.16, 1.51)	1.22 (1.06, 1.40)
Diabetes	1.80 (1.61, 2.00)	1.56 (1.37, 1.77)
Hypertension	1.43 (1.30, 1.58)	1.15 (1.02, 1.29)
Dyslipidemia	1.50 (1.36, 1.65)	1.06 (0.94, 1.19)
Depression	8.41 (7.30, 9.69)	7.81 (6.76, 9.02)
Hearing loss	1.28 (1.05, 1.56)	1.00 (0.80, 1.26)
Excessive alcohol consumption	3.76 (2.86, 4.94)	2.35 (1.72, 3.21)
Obesity	1.75 (1.07, 2.87)	0.94 (0.53, 1.65)

Multivariable model was adjusted for OAG, hypertension, diabetes, dyslipidemia, depression, hearing loss, excessive alcohol consumption, obesity.

OAG: open-angle glaucoma; OR: odds ratio; CI: confidence interval.

Table 3.

Sex-stratified conditional logistic regression model.

	Male (n = 6275)		Female (n = 5445)
Variables	OR (95% CI)^a	p	OR (95% CI)^a	p
Open angle glaucoma	1.32 (1.09, 1.60)	0.005	1.11 (0.90, 1.37)	0.321
Diabetes	1.42 (1.20, 1.68)	<0.001	1.78 (1.45, 2.18)	<0.001
Hypertension	1.29 (1.11, 1.50)	0.001	0.97 (0.81, 1.16)	0.742
Dyslipidemia	1.11 (0.95, 1.30)	0.186	0.99 (0.83, 1.19)	0.937
Depression	8.16 (6.63, 10.04)	<0.001	7.69 (6.28, 9.40)	<0.001
Hearing loss	1.21 (0.89, 1.65)	0.221	0.81 (0.58, 1.13)	0.212
Excessive alcohol consumption	2.45 (1.73, 3.47)	<0.001	1.75 (0.85, 3.60)	0.132
Obesity	0.70 (0.27, 1.83)	0.463	1.15 (0.57, 2.34)	0.685

Adjusted for OAG, hypertension, diabetes, dyslipidemia, depression, hearing loss, excessive alcohol consumption, obesity.

OAG: open-angle glaucoma; OR: odds ratio; CI: confidence interval.

Discussion

The present case-control study including 2344 patients with EOAD and 9376 matched controls showed a significant association between OAG and EOAD. To the best of our knowledge, this is the first study to investigate the relationship between OAG and EOAD using a large-scale database.

Our findings are consistent with those of previous studies that have reported an association between glaucoma and the risk of AD in older age groups. A recent meta-analysis demonstrated a significant association, with glaucoma being linked to a higher risk of AD (OR, 1.46; 95%CI, 1.20–1.76) and primary OAG showing a similarly increased risk of AD (OR, 1.29; 95%CI, 1.11–1.49).¹⁵ Our study identified a significant association between OAG and EOAD (OR, 1.22; 95% CI, 1.06–1.40). Therefore, this study suggests that OAG may be associated with the development of AD not only in older individuals but also in middle-aged adults.

In this study, exposure was defined as a diagnosis of OAG that occurred more than 12 months prior to the index date. A multivariable model revealed a significant association between OAG and EOAD, suggesting that OAG contributes to the development of EOAD. However, a recent large-scale cohort study in Sweden demonstrated that the association between glaucoma and dementia was observed among older individuals, whereas there was no significant association in those younger than 60 years.²⁸ As evidence regarding the relationship between OAG and EOAD remains limited, future cohort studies are warranted to elucidate the effect of OAG on EOAD onset.

The present study showed a significant association between OAG and EOAD in male patients, but not in female patients. In contrast, some previous studies on glaucoma and AD in older populations have reported significant associations in women,^29,30 suggesting that hormonal factors may influence these associations. One possible explanation is the neuroprotective role of estrogen. Estrogen has been suggested to potentially exert neuroprotective effects.^31,32 A recent meta-analysis reported that midlife estrogen therapy is associated with a 32% reduced risk of dementia.³³ Another previous study demonstrated that an early onset of natural menopause adversely affected cognitive function.³⁴ Given that the present study focused on individuals aged 40 to 64 years, the protective effects of estrogen, particularly among premenopausal or perimenopausal women, may have influenced the lack of association between OAG and EOAD in female patients. Future studies should consider the menopausal status and hormonal profiles to examine this relationship.

Several pathophysiological mechanisms underlie the association between OAG and EOAD. Similar to late-onset AD, glaucoma and EOAD exhibit common neurodegenerative features, including the accumulation of amyloid-β and p-tau. A previous study demonstrated that the plasma p-tau181 concentration, which is associated with brain atrophy, was higher in the EOAD group than in the late-onset AD group,³⁵ suggesting a higher pathological burden of Alzheimer's disease in EOAD. EOAD exhibits amyloid deposition at levels comparable to those in late-onset AD.^36,37 Another study showed that apolipoprotein E is linked to a higher risk of early-onset dementia.²⁵ Considering these findings, both OAG and EOAD share common neurodegenerative biomarkers, suggesting a potential association between OAG and EOAD. Additionally, patients with EOAD exhibit a significant association with retinal biomarkers, including the peripapillary retinal nerve fiber layer (pRNFL), retinal nerve fiber layer (RNFL), and ganglion cell complex (GCC) thickness, all of which are well-established features of glaucoma progression. Patients with EOAD demonstrated significantly thinner pRNFL, RNFL, and GCC,³⁸ indicating a potential overlap in the pathophysiology of EOAD and glaucoma. Clinically, both EOAD and late-onset AD presented with widespread cognitive impairments compared to their age-matched healthy peers. Notably, EOAD demonstrates more severe deficits in visuospatial abilities, executive functioning, and processing speed/attention than late-onset AD.³⁹ Given the limited research on EOAD, further investigation is urgently required to clarify the potential link between OAG and EOAD.

The factors associated with EOAD remain unclear, and examining associations with covariates may provide important additional insight. In this study, EOAD was significantly associated with not only OAG but also diabetes, hypertension, depression, and excessive alcohol consumption. These findings align with the risk factors for dementia identified by the Lancet Commission on dementia.⁴ Additionally, a recent cohort study reported that early-onset dementia is associated with alcohol consumption, diabetes, and depression.²⁵ A previous study demonstrated that the prevalence of depression was significantly higher in EOAD (26.1%) compared to late-onset AD (19.2%).⁴⁰ Similar to our study, a previous study reported that EOAD patients with hypertension exhibited significantly accelerated cognitive decline²⁴; however, another study demonstrated that orthostatic hypotension increased the risk of early-onset dementia.²⁵ Further studies are required to elucidate the relationship between blood pressure variability and EOAD. In contrast, our study found no significant associations of EOAD with dyslipidemia, hearing loss, or obesity. This may be due to the fact that these diagnoses were based on ICD-10 codes rather than detailed clinical assessments. Future studies should use more comprehensive diagnostic data to further investigate these associations.

The strength of this study lies in its investigation of the association between OAG and EOAD using a large-scale database, which allowed for the inclusion of a sufficient number of EOAD cases despite its low prevalence. In Japan, the prevalence of early-onset dementia has been estimated at 50.9 per 100,000 persons aged 18–64,⁴¹ and although somewhat lower than the global estimate of 119.0 per 100,000 persons aged 30–64,⁴² both indicate that early-onset dementia is rare. Therefore, this study offers valuable insights by enabling the investigation of such an association through a large-scale dataset. The JMDC database predominantly includes working-age adults (20–74 years), providing an ideal cohort for investigating early-onset dementia. Additionally, this database provided a unique opportunity to extract a control group from a relatively healthy segment of the general population. This control group enhanced the validity of the findings by offering a clear comparison with the case group, thereby ensuring that the potential impact of exposure on disease risk could be accurately assessed. However, this study had several limitations. First, the diagnosis of OAG was derived from ICD-10 codes in the JMDC database rather than being confirmed through detailed clinical records. These ICD-10 codes may have been utilized for reimbursement purposes and may not accurately reflect actual diagnoses. Second, the definition of EOAD has certain methodological limitations regarding diagnostic accuracy. Specifically, we defined EOAD cases based on the presence of both ICD-10 diagnosis codes and prescriptions for AD medications. Although this approach may lead to under-ascertainment of untreated or mildly affected individuals, previous studies^43,44 have shown that combining diagnostic codes with prescription data improves the positive predictive value (PPV) compared to using diagnostic codes alone. However, these findings are based on studies conducted across all age groups with AD, and the PPV of ICD-10 codes specifically for younger individuals with AD remains unclear. Therefore, further research using clinical records and biomarker data is needed to validate the diagnostic accuracy for EOAD. Third, other unmeasured confounders may have influenced our findings. These include socioeconomic status factors such as lower educational level, occupation, and income, as well as lifestyle and environmental factors (e.g., smoking, physical inactivity, air pollution, and social isolation). In addition, several risk factors for EOAD, such as traumatic brain injuries, heart disease, stroke, and high cholesterol, were not captured in our dataset. Fourth, a causal relationship between OAG and EOAD could not be established owing to the case-control study design. Fifth, the findings may not be generalizable to populations outside of Japan.

In conclusion, Individuals with OAG exhibit a modestly increased risk of developing EOAD and should be monitored for cognitive symptoms to facilitate early detection and timely intervention. Further research is required to better understand the underlying mechanisms linking OAG and EOAD.

Supplemental Material

sj-docx-1-alz-10.1177_13872877251410501 - Supplemental material for Association between open angle glaucoma and early onset Alzheimer's disease

Supplemental material, sj-docx-1-alz-10.1177_13872877251410501 for Association between open angle glaucoma and early onset Alzheimer's disease by Yuto Yoshida, Nobuaki Michihata, Masaki Tanito, Yoshimune Hiratsuka, Shintaro Nakao and Hideo Yasunaga in Journal of Alzheimer's Disease

Footnotes

Acknowledgements

The authors have no acknowledgments to report.

Ethical considerations

This study was conducted in accordance with the recommendations of the Declaration of Helsinki and approved by the Institutional Review Board of the University of Tokyo (Ethics approval ID: 10862-(1)).

Consent to participate

The requirement for informed consent was waived due to the use of anonymized data sources.

Consent for publication

Not applicable

Author contribution(s)

Yuto Yoshida: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Software; Writing – original draft.

Nobuaki Michihata: Conceptualization; Data curation; Formal analysis; Investigation; Software; Writing – original draft.

Masaki Tanito: Writing – review & editing.

Yoshimune Hiratsuka: Conceptualization; Methodology; Supervision; Writing – review & editing.

Shintaro Nakao: Writing – review & editing.

Hideo Yasunaga: Writing – review & editing.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The datasets are not publicly available due to contractual restrictions with the data provider.

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

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