Introduction: Vascular factors have been shown to be associated with increased risk of dementia. However, clinical trials have so far been unsuccessful, suggesting new approaches are needed. The aim of this study was to use population-based real-world data to investigate risk factors and preventive factors for dementia, including the effects of traditional Chinese medicine (TCM). Methods: This is a retrospective cohort study using LHID2000, a dataset randomly selected from Taiwan’s National Health Insurance Research Database. Subjects with occlusion and stenosis of precerebral and cerebral arteries, cerebral atherosclerosis without mention of cerebral infarction, and transient cerebral ischemia were included. Subjects with dementia at baseline were excluded. The primary endpoint was dementia. Data for demographic and clinical comorbid status and treatments administered at baseline in 2000 and at the end of follow-up in 2013 were included. Results: A total of 4,207 subjects with cerebral vascular disease and no cognitive impairment were included, of whom 392 converted to dementia during an average 5.15-year (SD: 3.79) follow-up. Depression (adjusted HR: 1.54, 95% confidence interval [CI]: 1.13–2.09), osteoporosis (adjusted HR: 1.34, 95% CI: 1.04–1.74), and the use of enalapril (adjusted HR: 1.37, 95% CI: 1.09–1.73) were risk factors for dementia, while nitroglycerin (adjusted HR: 0.67, 95% CI: 0.53–0.85) was a protecting factor, in subjects with cerebrovascular diseases without mention of cerebral infarction. In total, statins were shown to be associated with decreased risk of dementia (HR: 0.73, 95% CI: 0.59–0.91); however, no one statin subtype or TCM had such an effect. Conclusion: Depression, osteoporosis, and the use of enalapril were associated with a higher risk of dementia, while nitroglycerin might be a protecting factor for dementia, in subjects with cerebrovascular diseases without mention of cerebral infarction.

Alzheimer’s disease (AD) is a neurodegenerative condition with progressive impairment of memory and cognition. There is no effective treatment at present, although there has been much progress recently in understanding the science behind the pathogenesis of AD. The negative results from the clinical trials on AD imply that new ways of thinking or hypotheses for intervention and network modeling analytics are necessary to overcome the issues involved. Although there are many potential reasons, the lack of success in these trials suggests that novel approaches are needed in both pathogenesis research and drug development. The increasing awareness of population-based data has provided a better exploratory pathway to generate hypotheses for disease pathogenesis and to find potential approaches for prevention of AD.

Research into vascular factors associated with the increased risk of vascular dementia and AD suggests that cerebral hypoperfusion and blood-brain barrier (BBB) leakiness contribute to brain damage [1, 3]. A combination of arteriolosclerosis and Aβ-, tau-, and endothelin-related vascular dysfunction contributed to abnormalities in cerebral perfusion and BBB function in common types of dementia [3]. If we were able to find factors that mediated the association of vascular factors with the risk of dementia using real-world data, it would enable us to establish methods of prevention.

The National Health Insurance program in Taiwan is a voluntary and single-payer medical program that was launched in 1995 and currently covers almost the entire population (99.6%) of Taiwan [4]. The National Health Insurance Administration performs an expert review of random samples for every 50–100 outpatient and inpatient claims in each hospital every 3 months; a disease diagnosis without valid supporting clinical findings is considered medical fraud and carries a penalty of 100 times the amount claimed by the treating physician or hospital.

Vascular diseases or vascular factors are risk factors of dementia, no matter whether it is AD or vascular dementia. Dementia etiology research is entering the puzzle stage. We hope to find some novel clues for dementia treatment, including risk and protective factors. Traditional Chinese medicine (TCM) is also covered to explore the potential protective medicines based on the literature [5, 6]. Taiwan National Health Insurance data, real-world data, provided an opportunity to explore such factors. We included subjects with occlusion and stenosis of precerebral and cerebral arteries, cerebral atherosclerosis without mention of cerebral infarction, and transient cerebral ischemia, as we know that vascular factors are risk factors for Alzheimer’s and vascular dementia from the National Health Insurance data to investigate the risk factors for dementia.

This is a prospective cohort study with subjects from Taiwan’s National Health Insurance Research Database (NHIRD).

Data

LHID2000 is a subset database of Taiwan’s NHIRD. The NHIRD was provided by the Bureau of National Health Insurance (BNHI) in Taiwan and contained records from 99% of the inpatient and outpatient recipients of medical benefits from the Taiwanese population of 23 million individuals. The LHID2000 included 1 million beneficiaries randomly selected from the NHIRD in the year 2000 for research purposes [4].

Data Availability Statement

The datasets analyzed in this article are not publicly available. Requests to access the datasets should be directed to the Taiwan Ministry of Health and Welfare (MOHW). The MOHW must approve any application to access these data. Any researcher interested in accessing this dataset can submit an application form to the MOHW requesting access. Please contact the staff of MOHW (email: stcarolwu@mohw.gov.tw) for further assistance. All relevant data are included within the paper.

Ethics Statement

In the NHIRD in Taiwan, patients’ personal information is encrypted to protect individuals’ privacy. Researchers are provided with anonymous identification numbers associated with relevant claims information. The study involving human participants was reviewed and approved by the Research Ethics Committee of China Medical University Hospital in Taiwan (CMUH104-REC2-115(CR-5). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Subjects

Subjects with occlusion and stenosis of the precerebral and cerebral arteries, cerebral atherosclerosis without mention of symptoms of acute focal neurological deficit, and transient cerebral ischemia, for which the ICD-9-CM codes are 433.00 (occlusion and stenosis of basilar artery without mention of cerebral infarction), 433.10 (occlusion and stenosis of the carotid Artery without cerebral infarction), 433.20 (occlusion and stenosis of vertebral artery without cerebral infarction), 433.30 (occlusion and stenosis of multiple and bilateral precerebral arteries without cerebral infarction), 433.80 (occlusion and stenosis of other specified precerebral artery without cerebral infarction), 433.90 (occlusion and stenosis of unspecified precerebral artery without cerebral infarction), 434.00 (occlusion and stenosis of unspecified middle cerebral artery), 434.10 (cerebral embolism without cerebral infarction), 434.90 (cerebral artery occlusion, unspecified without mention of cerebral infarction), 435.0 (basilar artery syndrome), 435.1 (vertebral artery syndrome), 435.2 (subclavian steal syndrome), 435.3 (vertebrobasilar artery syndrome), 435.8 (carotid artery syndrome [hemispheric]), 435.9 (unspecified transient cerebral ischemia), and 437.0 (cerebral atherosclerosis), were included. Subjects with dementia (ICD-9 code 290, 294.1, 294.2, 331.0) at baseline were excluded.

Endpoint

The primary endpoint of outcome is dementia (ICD-9 code 290, 294.1, 294.2, 331.0). Because the data of AD, vascular dementia, and other type of dementia are not sufficient, dementia is used to measure the outcome of follow-up.

Data Included in Analysis

Demographics of age; sex; comorbidities including diabetes mellitus (ICD-9 250), hypertension (401–405), hyperlipidemia (272), coronary heart disease (410–414), osteoporosis (733), head injury (310.2, 800, 801, 803, 804, 850–854, and 959.01), depression (296.2, 296.3, 300.4, and 311), sleep disorder (307.4 and 780.5), and cancer at baseline diagnosis; treatment with Western medicine and Chinese medicine targeting corresponding comorbidities and used before the index date were included. The primary endpoint was dementia, which was diagnosed in the follow-up period, for which the ICD-9-CM code is 290, 294.1, 294.2; Alzheimer’s dementia (ICD-9-CM 331.0) and vascular dementia (ICD-9-CM 290.4) were also recorded. The follow-up time is the length of time from the first diagnosis of vascular disease to the diagnosis of dementia.

Statistical Analysis

The stepwise selection process consisted of a series of alternating forward selection and backward elimination steps. The variable had to be significant at the 0.25 level before it could be entered into the Cox proportional hazards model, and a variable in the model had to be significant at the 0.15 level for it to remain in the model. Kaplan-Meier curve of dementia incidence was stratified by patients with or without risk factors of depression and osteoporosis. Subgroup analysis was performed to explore the effect of some Chinese medicine which showed significance in univariate Cox regression analysis stratified by risk groups. Univariable and multivariable competing-risks regression models were used to estimate the sub-hazard ratios and 95% confidence intervals (CIs) for dementia. The significance criteria used a 2-tailed p value < 0.05. To address the concern of constant proportionality, we examined the proportional model assumption using a test of scaled Schoenfeld residuals. All statistical analyses were performed using SAS statistical software, version 9.4 (SAS Institute Inc., Cary, NC, USA). The cumulative incidence curve was plotted by R software.

Demographics and Clinical Comorbidities of Study Cohort

A total of 4,207 subjects with occlusion and stenosis of precerebral and cerebral arteries, cerebral atherosclerosis without mention of cerebral infarction, and transient cerebral ischemia, but without dementia, were included (Table 1; online suppl. Table 1; for all online suppl. material, see https://doi.org/10.1159/000530102). The mean age was 68.1 (SD: 12.0) years, and the mean follow-up period was 5.15 (SD: 3.79) years. The number of female subjects was 1,861 (44.2%). Of the 4,207 subjects, 392 developed dementia, including 39 with AD and 92 with vascular dementia; in 261, the subtype of dementia was not available.

Table 1.

Distribution of demographic and clinical comorbid status in study cohorts

VariableSubjectsp value
all (N = 4,207)conversion (N = 392)non-conversion (N = 3,815)
N (%)n(%)n(%)
Subtype 
 Occlusion and stenosis of precerebral arteries 914 (21.7) 66 (16.8) 848 (22.2) 0.01 
 Occlusion of cerebral arteries 243 (5.78) 26 (6.69) 217 (5.69) 0.45 
 Transient cerebral ischemia 2,645 (62.9) 270 (68.9) 2,375 (62.3) 0.01 
 Cerebral atherosclerosis 405 (9.63) 30 (7.65) 375 (9.83) 0.16 
Sex 
 Female 1,861 (44.2) 190 (48.5) 1,671 (43.8) 0.08 
 Male 2,346 (55.8) 202 (51.5) 2,144 (56.2) 
Age group, years 
 40–64 1,623 (38.6) 56 (14.3) 1,567 (41.1) <0.001 
 65–74 1,199 (28.5) 137 (35.0) 1,062 (27.8) 
 ≥75 1,385 (32.9) 199 (50.8) 1,186 (31.1) 
Mean age (standard deviation) 68.1 (12.0) 74.4 (8.73) 67.5 (12.2) <0.001 
Mean years of follow-up (standard deviation) 5.15 (3.79) 3.50 (2.80) 5.32 (3.83) <0.001 
Comorbidities before index date 
Diabetes mellitus 1,125 (26.7) 102 (26.0) 1,023 (26.8) 0.73 
Hypertension 3,430 (81.5) 336 (85.7) 3,094 (81.1) 0.03 
Hyperlipidemia 2,186 (52.0) 186 (47.5) 2,000 (52.4) 0.06 
Coronary heart disease 2,298 (54.6) 233 (59.4) 2,065 (54.1) 0.04 
Osteoporosis 851 (20.2) 121 (30.9) 730 (19.1) <0.001 
Head injury 431 (10.2) 42 (10.7) 389 (10.2) 0.75 
Depression 460 (10.9) 62 (15.8) 398 (10.4) 0.001 
Sleep disorder 1,580 (37.6) 161 (41.1) 1,419 (37.2) 0.13 
Cancer 231 (5.5) 19 (4.8) 212 (5.6) 0.55 
VariableSubjectsp value
all (N = 4,207)conversion (N = 392)non-conversion (N = 3,815)
N (%)n(%)n(%)
Subtype 
 Occlusion and stenosis of precerebral arteries 914 (21.7) 66 (16.8) 848 (22.2) 0.01 
 Occlusion of cerebral arteries 243 (5.78) 26 (6.69) 217 (5.69) 0.45 
 Transient cerebral ischemia 2,645 (62.9) 270 (68.9) 2,375 (62.3) 0.01 
 Cerebral atherosclerosis 405 (9.63) 30 (7.65) 375 (9.83) 0.16 
Sex 
 Female 1,861 (44.2) 190 (48.5) 1,671 (43.8) 0.08 
 Male 2,346 (55.8) 202 (51.5) 2,144 (56.2) 
Age group, years 
 40–64 1,623 (38.6) 56 (14.3) 1,567 (41.1) <0.001 
 65–74 1,199 (28.5) 137 (35.0) 1,062 (27.8) 
 ≥75 1,385 (32.9) 199 (50.8) 1,186 (31.1) 
Mean age (standard deviation) 68.1 (12.0) 74.4 (8.73) 67.5 (12.2) <0.001 
Mean years of follow-up (standard deviation) 5.15 (3.79) 3.50 (2.80) 5.32 (3.83) <0.001 
Comorbidities before index date 
Diabetes mellitus 1,125 (26.7) 102 (26.0) 1,023 (26.8) 0.73 
Hypertension 3,430 (81.5) 336 (85.7) 3,094 (81.1) 0.03 
Hyperlipidemia 2,186 (52.0) 186 (47.5) 2,000 (52.4) 0.06 
Coronary heart disease 2,298 (54.6) 233 (59.4) 2,065 (54.1) 0.04 
Osteoporosis 851 (20.2) 121 (30.9) 730 (19.1) <0.001 
Head injury 431 (10.2) 42 (10.7) 389 (10.2) 0.75 
Depression 460 (10.9) 62 (15.8) 398 (10.4) 0.001 
Sleep disorder 1,580 (37.6) 161 (41.1) 1,419 (37.2) 0.13 
Cancer 231 (5.5) 19 (4.8) 212 (5.6) 0.55 

Compared to those who did not convert to a dementia diagnosis, converted subjects were older, had more comorbidities of hypertension, coronary heart disease, osteoporosis, or depression, and were more likely to have been treated with enalapril. The use of statins and nitroglycerin was higher in the non-converted group (Table 1; online suppl. Table 1).

Risk and Protective Factors Associated with Dementia in Subjects with Cerebral Vascular Diseases

Multiple variable Cox regression models showed that older age, medical history of osteoporosis (adjusted HR: 1.34, 95% CI: 1.04–1.74), depression (adjusted HR: 1.54, 95% CI: 1.13–2.09), and use of enalapril (adjusted HR: 1.37, 95% CI: 1.09–1.73) increased the risk of dementia (Table 2; Fig. 1). However, the use of nitroglycerin (adjusted HR: 0.67, 95% CI: 0.53–0.85) and statins (HR: 0.73, 95% CI: 0.59–0.91) decreased the risk of dementia in subjects with cerebral vascular diseases without mention of cerebral infarction symptoms or dementia (Table 2; Fig. 1).

Table 2.

Factors associated with dementia in univariate and multivariable Cox regression models

FactorsCrudeAdjustedaCrudeAdjusteda
HR95% CIHR95% CISHR95% CISHR95% CI
Subtype 
 Occlusion and stenosis of precerebral arteries 1.19 (0.77, 1.83) 1.13 (0.73, 1.76) 1.14 (0.74, 1.76) 1.09 (0.69, 1.70) 
 Occlusion of cerebral arteries 1.31 (0.77, 2.21) 1.11 (0.65, 1.88) 1.25 (0.74, 2.13) 1.09 (0.63, 1.88) 
 Transient cerebral ischemia 1.06 (0.72, 1.54) 1.04 (0.71, 1.52) 1.07 (0.74, 1.57) 1.08 (0.74, 1.59) 
 Cerebral atherosclerosis 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) 
Age group, years 
 40–64 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) 
 65–74 3.82 (2.80, 5.21)* 3.46 (2.51, 4.77)* 3.65 (2.68, 4.98)* 3.34 (2.42, 4.62)* 
 ≥75 6.55 (4.86, 8.83)* 5.47 (3.98, 7.53)* 5.69 (4.24, 7.64)* 4.81 (3.48, 6.63)* 
Comorbidities before index date 
Hypertension 1.60 (1.20, 2.12)* 0.93 (0.67, 1.29) 1.53 (1.15, 2.03)* 0.92 (0.66, 1.28) 
Coronary heart disease 1.33 (1.09, 1.62)* 1.04 (0.81, 1.33) 1.30 (1.06, 1.59)* 1.04 (0.81, 1.34) 
Osteoporosis 2.01 (1.62, 2.49)* 1.34 (1.04, 1.74)* 2.00 (1.62, 2.48)* 1.39 (1.07, 1.80)* 
Depression 1.70 (1.30, 2.23)* 1.54 (1.13, 2.09)* 1.69 (1.28, 2.21)* 1.49 (1.06, 2.09)* 
Sleep disorder 1.30 (1.06, 1.59)* 1.03 (0.82, 1.28) 1.30 (1.06, 1.59)* 1.04 (0.84, 1.30) 
Medications 
 Statin 0.58 (0.48, 0.71)* 0.73 (0.59, 0.91)* 0.61 (0.50, 0.74)* 0.78 (0.62, 0.96)* 
 Hydralazine 1.30 (1.06, 1.59)* 1.00 (0.79, 1.26) 1.29 (1.05, 1.57)* 0.99 (0.79, 1.25) 
 Nitroglycerin 0.82 (0.67, 0.99)* 0.67 (0.53, 0.85)* 0.80 (0.66, 0.98)* 0.67 (0.53, 0.85)* 
 Thrombolysis 0.53 (0.35, 0.81)* 0.68 (0.39, 1.18) 0.54 (0.35, 0.82)* 0.68 (0.37, 1.25) 
 Stent 0.57 (0.36, 0.91)* 0.88 (0.48, 1.61) 0.58 (0.37, 0.91)* 0.93 (0.48, 1.81) 
 AGI (acarbose, miglitol) 0.78 (0.49, 1.23) 0.88 (0.55, 1.41) 0.75 (0.47, 1.19) 0.84 (0.52, 1.36) 
 SSRIs 1.45 (1.04, 2.03)* 1.25 (0.86, 1.83) 1.45 (1.03, 2.04)* 1.22 (0.80, 1.85) 
 Calcium 1.84 (1.46, 2.32)* 1.24 (0.95, 1.62) 1.79 (1.41, 2.26)* 1.20 (0.91, 1.58) 
 Atenolol 1.33 (1.09, 1.63)* 0.99 (0.79, 1.25) 1.33 (1.09, 1.62)* 1.02 (0.81, 1.28) 
 Enalapril 1.72 (1.40, 2.10)* 1.37 (1.09, 1.73)* 1.66 (1.35, 2.03)* 1.35 (1.07, 1.69)* 
 Isosorbide 1.27 (1.03, 1.57)* 1.02 (0.79, 1.32) 1.22 (0.99, 1.50) 1.00 (0.78, 1.29) 
 Amlodipine 1.49 (1.22, 1.82)* 1.17 (0.93, 1.48) 1.43 (1.17, 1.74)* 1.12 (0.88, 1.42) 
 Hydrochlorothiazide 1.70 (1.39, 2.07)* 1.22 (0.96, 1.55) 1.65 (1.35, 2.01)* 1.22 (0.96, 1.55) 
Single herbal TCM 
Panax ginseng 0.49 (0.07, 3.49) 0.55 (0.08, 3.96) 0.52 (0.07, 3.78) 0.60 (0.08, 4.68) 
Pueraria lobata 0.92 (0.66, 1.29) 0.91 (0.64, 1.31) 0.95 (0.68, 1.33) 0.97 (0.69, 1.37) 
Cnidium officinale 0.78 (0.49, 1.24) 0.88 (0.54, 1.44) 0.79 (0.50, 1.25) 0.89 (0.54, 1.46) 
Cistanche deserticola 0.62 (0.20, 1.94) 0.67 (0.20, 2.22) 0.62 (0.20, 1.92) 0.69 (0.24, 2.04) 
Ophiopogon japonicus 0.99 (0.69, 1.42) 0.93 (0.63, 1.38) 0.98 (0.69, 1.41) 0.94 (0.62, 1.43) 
Evodiae fructus 0.89 (0.28, 2.76) 1.35 (0.41, 4.44) 0.86 (0.28, 2.65) 1.30 (0.45, 3.77) 
Astragalus spp. 0.80 (0.50, 1.28) 0.82 (0.49, 1.36) 0.78 (0.49, 1.25) 0.80 (0.48, 1.34) 
Pheretima aspergillum Perrier 0.90 (0.56, 1.44) 0.89 (0.54, 1.47) 0.89 (0.55, 1.42) 0.87 (0.52, 1.43) 
Epimedium brevicornum 0.80 (0.43, 1.50) 1.00 (0.52, 1.92) 0.83 (0.45, 1.55) 1.07 (0.55, 2.08) 
Compound TCM 
 Shu-Jin-Huo-Xue-Tang 0.89 (0.70, 1.14) 0.94 (0.71, 1.23) 0.90 (0.70, 1.15) 0.95 (0.72, 1.24) 
 Ji Sheng Shen Qi Wan 1.12 (0.74, 1.69) 1.04 (0.67, 1.61) 1.10 (0.72, 1.66) 1.02 (0.65, 1.62) 
 Xue-Fu-Zhu-Yu-Tang 0.91 (0.66, 1.26) 0.94 (0.66, 1.33) 0.93 (0.67, 1.28) 0.96 (0.66, 1.39) 
Peony-glycyrrhiza decoction 0.83 (0.61, 1.13) 0.91 (0.65, 1.28) 0.83 (0.61, 1.14) 0.89 (0.63, 1.26) 
 Danggui-Shaoyao-San 0.70 (0.35, 1.41) 0.89 (0.43, 1.81) 0.72 (0.36, 1.45) 0.90 (0.44, 1.86) 
FactorsCrudeAdjustedaCrudeAdjusteda
HR95% CIHR95% CISHR95% CISHR95% CI
Subtype 
 Occlusion and stenosis of precerebral arteries 1.19 (0.77, 1.83) 1.13 (0.73, 1.76) 1.14 (0.74, 1.76) 1.09 (0.69, 1.70) 
 Occlusion of cerebral arteries 1.31 (0.77, 2.21) 1.11 (0.65, 1.88) 1.25 (0.74, 2.13) 1.09 (0.63, 1.88) 
 Transient cerebral ischemia 1.06 (0.72, 1.54) 1.04 (0.71, 1.52) 1.07 (0.74, 1.57) 1.08 (0.74, 1.59) 
 Cerebral atherosclerosis 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) 
Age group, years 
 40–64 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) 1.00 (Reference) 
 65–74 3.82 (2.80, 5.21)* 3.46 (2.51, 4.77)* 3.65 (2.68, 4.98)* 3.34 (2.42, 4.62)* 
 ≥75 6.55 (4.86, 8.83)* 5.47 (3.98, 7.53)* 5.69 (4.24, 7.64)* 4.81 (3.48, 6.63)* 
Comorbidities before index date 
Hypertension 1.60 (1.20, 2.12)* 0.93 (0.67, 1.29) 1.53 (1.15, 2.03)* 0.92 (0.66, 1.28) 
Coronary heart disease 1.33 (1.09, 1.62)* 1.04 (0.81, 1.33) 1.30 (1.06, 1.59)* 1.04 (0.81, 1.34) 
Osteoporosis 2.01 (1.62, 2.49)* 1.34 (1.04, 1.74)* 2.00 (1.62, 2.48)* 1.39 (1.07, 1.80)* 
Depression 1.70 (1.30, 2.23)* 1.54 (1.13, 2.09)* 1.69 (1.28, 2.21)* 1.49 (1.06, 2.09)* 
Sleep disorder 1.30 (1.06, 1.59)* 1.03 (0.82, 1.28) 1.30 (1.06, 1.59)* 1.04 (0.84, 1.30) 
Medications 
 Statin 0.58 (0.48, 0.71)* 0.73 (0.59, 0.91)* 0.61 (0.50, 0.74)* 0.78 (0.62, 0.96)* 
 Hydralazine 1.30 (1.06, 1.59)* 1.00 (0.79, 1.26) 1.29 (1.05, 1.57)* 0.99 (0.79, 1.25) 
 Nitroglycerin 0.82 (0.67, 0.99)* 0.67 (0.53, 0.85)* 0.80 (0.66, 0.98)* 0.67 (0.53, 0.85)* 
 Thrombolysis 0.53 (0.35, 0.81)* 0.68 (0.39, 1.18) 0.54 (0.35, 0.82)* 0.68 (0.37, 1.25) 
 Stent 0.57 (0.36, 0.91)* 0.88 (0.48, 1.61) 0.58 (0.37, 0.91)* 0.93 (0.48, 1.81) 
 AGI (acarbose, miglitol) 0.78 (0.49, 1.23) 0.88 (0.55, 1.41) 0.75 (0.47, 1.19) 0.84 (0.52, 1.36) 
 SSRIs 1.45 (1.04, 2.03)* 1.25 (0.86, 1.83) 1.45 (1.03, 2.04)* 1.22 (0.80, 1.85) 
 Calcium 1.84 (1.46, 2.32)* 1.24 (0.95, 1.62) 1.79 (1.41, 2.26)* 1.20 (0.91, 1.58) 
 Atenolol 1.33 (1.09, 1.63)* 0.99 (0.79, 1.25) 1.33 (1.09, 1.62)* 1.02 (0.81, 1.28) 
 Enalapril 1.72 (1.40, 2.10)* 1.37 (1.09, 1.73)* 1.66 (1.35, 2.03)* 1.35 (1.07, 1.69)* 
 Isosorbide 1.27 (1.03, 1.57)* 1.02 (0.79, 1.32) 1.22 (0.99, 1.50) 1.00 (0.78, 1.29) 
 Amlodipine 1.49 (1.22, 1.82)* 1.17 (0.93, 1.48) 1.43 (1.17, 1.74)* 1.12 (0.88, 1.42) 
 Hydrochlorothiazide 1.70 (1.39, 2.07)* 1.22 (0.96, 1.55) 1.65 (1.35, 2.01)* 1.22 (0.96, 1.55) 
Single herbal TCM 
Panax ginseng 0.49 (0.07, 3.49) 0.55 (0.08, 3.96) 0.52 (0.07, 3.78) 0.60 (0.08, 4.68) 
Pueraria lobata 0.92 (0.66, 1.29) 0.91 (0.64, 1.31) 0.95 (0.68, 1.33) 0.97 (0.69, 1.37) 
Cnidium officinale 0.78 (0.49, 1.24) 0.88 (0.54, 1.44) 0.79 (0.50, 1.25) 0.89 (0.54, 1.46) 
Cistanche deserticola 0.62 (0.20, 1.94) 0.67 (0.20, 2.22) 0.62 (0.20, 1.92) 0.69 (0.24, 2.04) 
Ophiopogon japonicus 0.99 (0.69, 1.42) 0.93 (0.63, 1.38) 0.98 (0.69, 1.41) 0.94 (0.62, 1.43) 
Evodiae fructus 0.89 (0.28, 2.76) 1.35 (0.41, 4.44) 0.86 (0.28, 2.65) 1.30 (0.45, 3.77) 
Astragalus spp. 0.80 (0.50, 1.28) 0.82 (0.49, 1.36) 0.78 (0.49, 1.25) 0.80 (0.48, 1.34) 
Pheretima aspergillum Perrier 0.90 (0.56, 1.44) 0.89 (0.54, 1.47) 0.89 (0.55, 1.42) 0.87 (0.52, 1.43) 
Epimedium brevicornum 0.80 (0.43, 1.50) 1.00 (0.52, 1.92) 0.83 (0.45, 1.55) 1.07 (0.55, 2.08) 
Compound TCM 
 Shu-Jin-Huo-Xue-Tang 0.89 (0.70, 1.14) 0.94 (0.71, 1.23) 0.90 (0.70, 1.15) 0.95 (0.72, 1.24) 
 Ji Sheng Shen Qi Wan 1.12 (0.74, 1.69) 1.04 (0.67, 1.61) 1.10 (0.72, 1.66) 1.02 (0.65, 1.62) 
 Xue-Fu-Zhu-Yu-Tang 0.91 (0.66, 1.26) 0.94 (0.66, 1.33) 0.93 (0.67, 1.28) 0.96 (0.66, 1.39) 
Peony-glycyrrhiza decoction 0.83 (0.61, 1.13) 0.91 (0.65, 1.28) 0.83 (0.61, 1.14) 0.89 (0.63, 1.26) 
 Danggui-Shaoyao-San 0.70 (0.35, 1.41) 0.89 (0.43, 1.81) 0.72 (0.36, 1.45) 0.90 (0.44, 1.86) 

AGI, alpha-glucosidase inhibitors; SSRI, selective serotonin reuptake inhibitors; TCM, traditional Chinese medicine; SHR, sub-hazard ratios.

*p < 0.05.

aAdjusted factors are age and gender.

Fig. 1.

Cumulative incidence of dementia stratified by the presence or absence of depression and osteoporosis in patients with cerebral vascular diseases with no mention of infarction.

Fig. 1.

Cumulative incidence of dementia stratified by the presence or absence of depression and osteoporosis in patients with cerebral vascular diseases with no mention of infarction.

Close modal

Effects of Chinese Medicine on Prevention of Dementia by Risk Group

Table 3 shows the effects of different TCMs on the development of dementia by risk group. The proportion of use of the single Chinese herbal medicines Astragalus spp. and Peony-glycyrrhiza decoction were lower in the group of subjects who converted to dementia than in the non-converted group (online suppl. Table 1). Peony-glycyrrhiza decoction decreased the risk of dementia in subjects who had neither depression nor osteoporosis and in subjects with depression. Astragalus spp. decreased the risk of dementia in subjects with depression. Ophiopogon japonicus decreased the risk in subjects with osteoporosis (Table 3).

Table 3.

Effect of Chinese medicines on prevention of dementia by risk group

Medicine factorsAdministrationOsteoporosis and depressionDepressionOsteoporosisNo risk factor
dementia/No. at risk (%)dementia/No. at risk (%)dementia/No. at risk (%)dementia/No. at risk (%)
Total  22/153 (14.4) 40/307 (13.0) 99/698 (14.2) 231/3,049 (7.6) 
Cnidium officinale Yes 2/26 (7.7) 2/28 (7.1) 5/64 (7.8) 10/166 (6.0) 
No 20/127 (15.7) 38/279 (13.6) 94/634 (14.8) 221/2,883 (7.7) 
p value  0.29 0.13 0.33 0.44 
Ophiopogon japonicus Yes 2/29 (6.9) 1/38 (2.6) 11/87 (12.6) 18/232 (7.8) 
No 20/124 (16.1) 39/269 (14.5) 88/611 (14.4) 213/2,817 (7.6) 
p value  0.20 0.66 0.04 0.91 
Astragalus spp. Yes 3/21 (14.3) 1/35 (2.9) 3/65 (4.6) 11/184 (6.0) 
No 19/132 (14.4) 39/272 (14.3) 96/633 (15.2) 220/2,865 (7.7) 
p value  0.99 0.02 0.06 0.40 
Peony-glycyrrhiza decoction Yes 7/36 (19.4) 5/52 (9.6) 15/161 (9.3) 18/425 (4.2) 
No 15/117 (12.8) 35/255 (13.7) 84/537 (15.6) 213/2,624 (8.1) 
p value  0.32 0.04 0.42 0.01 
Pueraria lobata Yes 5/35 (14.3) 6/40 (15.0) 12/120 (10.0) 15/285 (5.26) 
No 17/118 (14.4) 34/267 (12.7) 87/578 (15.1) 216/2,764 (7.81) 
p value  0.99 0.69 0.15 0.12 
Medicine factorsAdministrationOsteoporosis and depressionDepressionOsteoporosisNo risk factor
dementia/No. at risk (%)dementia/No. at risk (%)dementia/No. at risk (%)dementia/No. at risk (%)
Total  22/153 (14.4) 40/307 (13.0) 99/698 (14.2) 231/3,049 (7.6) 
Cnidium officinale Yes 2/26 (7.7) 2/28 (7.1) 5/64 (7.8) 10/166 (6.0) 
No 20/127 (15.7) 38/279 (13.6) 94/634 (14.8) 221/2,883 (7.7) 
p value  0.29 0.13 0.33 0.44 
Ophiopogon japonicus Yes 2/29 (6.9) 1/38 (2.6) 11/87 (12.6) 18/232 (7.8) 
No 20/124 (16.1) 39/269 (14.5) 88/611 (14.4) 213/2,817 (7.6) 
p value  0.20 0.66 0.04 0.91 
Astragalus spp. Yes 3/21 (14.3) 1/35 (2.9) 3/65 (4.6) 11/184 (6.0) 
No 19/132 (14.4) 39/272 (14.3) 96/633 (15.2) 220/2,865 (7.7) 
p value  0.99 0.02 0.06 0.40 
Peony-glycyrrhiza decoction Yes 7/36 (19.4) 5/52 (9.6) 15/161 (9.3) 18/425 (4.2) 
No 15/117 (12.8) 35/255 (13.7) 84/537 (15.6) 213/2,624 (8.1) 
p value  0.32 0.04 0.42 0.01 
Pueraria lobata Yes 5/35 (14.3) 6/40 (15.0) 12/120 (10.0) 15/285 (5.26) 
No 17/118 (14.4) 34/267 (12.7) 87/578 (15.1) 216/2,764 (7.81) 
p value  0.99 0.69 0.15 0.12 

Effect of Statins on the Prevention of Dementia

Cox regression analysis indicated that statins can reduce the risk of dementia in subjects with cerebral vascular disease (Table 2). However, when we carried out further analysis, we did not find a preventive effect for any subtype of statin on dementia (data not shown).

This research investigated the risk factors for dementia in subjects with cerebral vascular diseases and without dementia, based on Taiwan National Health Insurance data available from Taiwan’s National Health Insurance program. We found that a medical history of depression, osteoporosis, and use of enalapril increased the risk of dementia, while administration of statins and nitroglycerin decreased the risk of dementia.

Because the data for diagnosis of the subtype of dementia were incomplete, we used the endpoint of dementia in this cohort study. Osteoporosis [7, 10] and depression [11] have been shown to be associated with an increased risk of dementia. Karel Kostev et al. [7] reported that osteoporosis was associated with a 1.2-fold increase in the risk of being diagnosed with dementia in women and a 1.3-fold increase in the risk of being diagnosed with dementia in men. Chang et al. [8], who included subjects with osteoporosis from NHIRD, found that osteoporosis patients exhibited a 1.46-fold and 1.39-fold higher risk of dementia (95% CI = 1.37–1.56) and AD (95% CI = 0.95–2.02), respectively, which is consistent with our results. In answer to the question of whether osteoporosis drugs have an impact on dementia, individuals with no dementia diagnosis were dispensed medication significantly more often than those with a diagnosis of dementia (p < 0.001) [12]. In our study, several osteoporosis drugs were included in the analysis; however, none of these drugs were shown to decrease the risk of dementia. Osteoporosis can increase the risk of dementia, but a preventive effect of osteoporosis treatment on dementia has not yet been determined.

The relationship between depression and dementia is complex, and researchers are still trying to tease it out. Some evidence suggests that depression can be a risk factor [11, 15]. Clinically relevant depression was associated with an increased risk of dementia and AD in the community [13]. Depression was an associated factor for dementia, especially among people aged 45–64 years (midlife) [14]. Depression was a major risk factor for the onset of subsequent dementia in patients with lower urinary tract symptoms [11]. Those who had a history of depression earlier in life had a higher risk of dementia than those who did not. Late-life depression should be considered an early sign of dementia not a modifiable risk factor [15]. In contrast, depressive symptoms in midlife were not associated with an increased risk of dementia. Participants with depressive symptoms later in life had a higher risk of dementia. Depressive symptoms appear to be a prodromal feature of dementia or do not appear to increase the risk of dementia [16]. Depression in early life is a risk factor for dementia, while depression later in life can be a prodrome of dementia; however, this needs further confirmation.

Previous studies on the effects of medication have shown higher cumulative anticholinergic use to be associated with an increased risk of dementia [17, 18]. However, treatment with antidepressants did not decrease the risk of depression-associated dementia, leading the authors to conclude that late-life depression should be considered an early sign of dementia not a modifiable risk factor [15]. Selective serotonin reuptake inhibitors use did not increase or decrease the risk of dementia in our study.

The association between the brain (dementia and depression) and bone is a bidirectional communication that is evidenced by several clinical observations [7, 11, 19, 22] and experimental studies [23, 30]. Two bone cell-derived modulators, osteoblast-derived osteocalcin and lipocalin 2, can affect behavioral and cognitive function. Osteocalcin was shown to enter the central nervous system to promote spatial learning and memory while preventing anxiety-like behavior or even depression [23]. Lipocalin 2 regulates energy metabolism by mediating insulin secretion and improving glucose tolerance as well as insulin sensitivity [24] and was shown to cross the BBB to activate the anorexigenic pathway by binding to the melanocortin 4 receptor (MC4R) in the hypothalamus [25]. Osteocyte-specific sclerostin was demonstrated to affect brain function by antagonizing Wnt signaling, which is essential for neurogenesis, neuronal survival, synaptic plasticity, and BBB integrity [31] and is further associated with the pathophysiology of AD [26]. Further research is needed to clarify the role of bone cell-derived modulators in the pathogenesis of AD and investigate potential treatment targets.

In this population study, administration of nitroglycerin decreased the risk of dementia. Nitroglycerin, also known as glyceryl trinitrate (GTN), is an old medication used for heart failure, high blood pressure, painful periods, and to treat and prevent chest pain caused by decreased blood flow to the heart (angina) [32, 34]. Research into the preventive effect of GTN on dementia is rare. One study from the efficacy of nitric oxide in stroke (ENOS) trial showed that GTN improved disability (Barthel Index), quality of life (EuroQol-Visual Analogue Scale), cognition (telephone Mini-Mental State Examination), and mood (Zung Depression Scale) in patients with acute stroke at day 90 after treatment [35]. GTN is a strong preventive factor for dementia in subjects with cerebral vascular diseases in our population-based study, after adjustment for many covariates.

Some Chinese herbal medicines showed a tendency to decrease the risk of dementia in our study, but the effects were not statistically significant. Statins as a whole were also associated with a lower risk of dementia; however, we did not see this effect with any subtype of statin. Several studies from Taiwan based on the NHIRD reported that the use of TCM was associated with a lower risk of dementia in subjects with hypertension [36] and migraine [37]. TCM Dan-Shen, Tian-Ma-Gou-Teng-Yin, Ge-Gen, Jia-Wei-Xiao-Yao-San, and Jue-Ming-Zi were shown to decrease the risk of dementia. In our research, Chinese medicine Peony-glycyrrhiza decoction was associated with a lower risk of dementia in subjects with the risk of only depression or without the risk factors both of osteoporosis and depression. Astragalus spp. decreased the risk of dementia in subjects with depression.

The limitations of this research are similar to those discussed by Chen and Liu [36, 37]. First, the outcomes are based on ICD-9-CM categories, and dementia subtype was not available for some subjects, resulting in an inaccurate diagnosis. We used dementia as the primary outcome. To avoid the possibility that dementia developed before baseline, dementia was recorded 1 year after enrollment in subjects who had had at least 2 outpatient visits. The second limitation is that survival outcomes are not available in this database. Because all hospitals and all practices were covered, reasons for loss to follow-up were emigration abroad or death. We used competing risk model to resolve the potential issues, data showed in Table 2. Third, lifestyle factors such as physical exercise were unavailable from the claims data. It makes the judgment difficult sometimes. For instance, the protective effect of nitroglycerin is related to drugs or lifestyle needs further research. As for the association of certain health conditions and the need for a drug to dementia risk, the analysis methods took the potential confounders into consideration. An example is osteoporosis and calcium use. In univariate analysis, the use of calcium was associated with the risk of dementia significantly, which is contrary to common sense. In multivariate Cox analyses, calcium was not significantly associated with dementia risk, whereas osteoporosis was. Based on the entire analysis, we know that calcium use is a confounding factor, while osteoporosis is a risk factor. In the univariate Cox proportional hazard regression, we covered the comorbidities and the corresponding medications as much as possible or TCM. The diseases and treatments which showed significant association with higher/lower risks of dementia were included in the multivariate Cox proportional hazard regression analysis. Although the analysis methods took the potential confounders into consideration, residual confounding is still likely.

As stated in the introduction, the main purpose of this study was to explore novel risk and protective factors (including TCM) of dementia. This study is mainly data driven in Taiwan real-world data. Future research, for instance, the protective effect of nitroglycerin, needs validation in other populations.

In conclusion, depression is a complicated factor in dementia because it may be an early sign of the disease. Osteoporosis is associated with a higher risk, while nitroglycerin is associated with a lower risk of dementia, suggesting that potential approaches to prevention of dementia would be to target osteoporosis and to use nitroglycerin to treat patients with cerebral vascular diseases who are at high risk of dementia. Randomized controlled trials are needed to confirm these findings, and the effects of some TCM also warrant further research.

We would like to thank all the subjects who participated in this study.

In the National Health Insurance Research Database in Taiwan, patients’ personal information is encrypted to protect individuals’ privacy. Researchers are provided with anonymous identification numbers associated with relevant claims information. The study involving human participants was reviewed and approved by the Research Ethics Committee of China Medical University Hospital in Taiwan (CMUH104-REC2-115[CR-5]). An exemption from requiring written informed consent has been granted. In Japan, according to the “Ethical Guidelines for Medical and Health Research Involving Human Subjects,” the guidelines do not apply to research utilizing only specimens and information that have already been anonymized and that cannot be linked to individuals. Ethical review was not required.

The authors declare no conflict of interest.

The project was supported in part by the Foundation of Biomedicine Research and Innovation and by Taiwan Ministry of Health and Welfare Clinical Trial Center (MOHW109-TDU-B-212-114004).

B.Z. and M.F. contributed to the study conceptualization and interpretation. C-.L.L. contributed to data collection and the statistical analysis. B.Z., S.K., and C-.L.L. made the draft manuscript. M.F. and C.Y.H. revised it critically. All authors critically reviewed and revised the manuscript draft and approved the final version for submission.

All data generated or analyzed during this study are included in this article and its online supplementary material files. Further inquiries can be directed to the corresponding author.

1.
Lamar
M
,
Boots
EA
,
Arfanakis
K
,
Barnes
LL
,
Schneider
JA
.
Common brain structural alterations associated with cardiovascular disease risk factors and Alzheimer's dementia: future directions and implications
.
Neuropsychol Rev
.
2020
;
30
(
4
):
546
57
.
2.
Tayler
H
,
Miners
JS
,
Güzel
Ö
,
MacLachlan
R
,
Love
S
.
Mediators of cerebral hypoperfusion and blood–brain barrier leakiness in Alzheimer’s disease, vascular dementia and mixed dementia
.
Brain Pathol
.
2021
;
31
(
4
):
e12935
.
3.
Salminen
A
.
Hypoperfusion is a potential inducer of immunosuppressive network in Alzheimer’s disease
.
Neurochem Int
.
2021
;
142
:
104919
.
4.
National Health Insurance Research Database
Taiwan
2021
. Available from: https://nhird.nhri.edu.tw/talk_07.
5.
Li
S
,
Wu
Z
,
Le
W
.
Traditional Chinese medicine for dementia
.
Alzheimers Dement
.
2021
;
17
(
6
):
1066
71
.
6.
National Health Insurance Research Database
Taiwan
2021
. Available from: https://nhird.nhri.org.tw/en/Mar.1,2021.
7.
Kostev
K
,
Hadji
P
,
Jacob
L
.
Impact of osteoporosis on the risk of dementia in almost 60,000 patients followed in general practices in Germany
.
J Alzheimers Dis
.
2018
;
65
(
2
):
401
7
.
8.
Chang
KH
,
Chung
CJ
,
Lin
CL
,
Sung
FC
,
Wu
TN
,
Kao
CH
.
Increased risk of dementia in patients with osteoporosis: a population-based retrospective cohort analysis
.
Age
.
2014
;
36
(
2
):
967
75
.
9.
Sipilä
PN
,
Lindbohm
JV
,
Singh-Manoux
A
,
Shipley
MJ
,
Kiiskinen
T
,
Havulinna
AS
.
Long-term risk of dementia following hospitalization due to physical diseases: a multicohort study
.
Alzheimers Dement
.
2020
;
16
(
12
):
1686
95
.
10.
Otto
E
,
Knapstein
PR
,
Jahn
D
,
Appelt
J
,
Frosch
KH
,
Tsitsilonis
S
.
Crosstalk of brain and bone-clinical observations and their molecular bases
.
Int J Mol Sci
.
2020
;
21
(
14
):
4946
.
11.
Ou
MJ
,
Huang
CC
,
Wang
YC
,
Chen
YL
,
Ho
CH
,
Wu
MP
.
Depression is a major risk factor for the development of dementia in people with lower urinary tract symptoms: a nationwide population-based study
.
PLoS One
.
2019
;
14
(
6
):
e0217984
.
12.
Knopp-Sihota
JA
,
Cummings
GG
,
Newburn-Cook
CV
,
Homik
J
,
Voaklander
D
.
Dementia diagnosis and osteoporosis treatment propensity: a population-based nested case-control study
.
Geriatr Gerontol Int
.
2014
;
14
(
1
):
121
9
.
13.
Santabárbara Serrano
J
,
Sevil-Perez
A
,
Olaya
B
,
Gracia-Garcia
P
,
Lopez-Anton
R
.
Clinically relevant late-life depression as risk factor of dementia: a systematic review and meta-analysis of prospective cohort studies
.
Rev Neurol
.
2019
;
68
(
12
):
493
502
.
14.
Yu
OC
,
Jung
B
,
Go
H
,
Park
M
,
Ha
IH
.
Association between dementia and depression: a retrospective study using the Korean National Health Insurance Service-national sample cohort database
.
BMJ Open
.
2020
;
10
(
10
):
e034924
.
15.
Almeida
OP
,
Hankey
GJ
,
Yeap
BB
,
Golledge
J
,
Flicker
L
.
Depression as a modifiable factor to decrease the risk of dementia
.
Transl Psychiatry
.
2017
;
7
(
5
):
e1117
.
16.
Singh-Manoux
A
,
Dugravot
A
,
Fournier
A
,
Abell
J
,
Ebmeier
K
,
Kivimäki
M
.
Trajectories of depressive symptoms before diagnosis of dementia: a 28-year follow-up study
.
JAMA Psychiatry
.
2017
;
74
(
7
):
712
8
.
17.
Gray
SL
,
Anderson
ML
,
Dublin
S
,
Hanlon
JT
,
Hubbard
R
,
Walker
R
.
Cumulative use of strong anticholinergics and incident dementia: a prospective cohort study
.
JAMA Intern Med
.
2015
;
175
(
3
):
401
7
.
18.
Heath
L
,
Gray
SL
,
Boudreau
DM
,
Thummel
K
,
Edwards
KL
,
Fullerton
SM
.
Cumulative antidepressant use and risk of dementia in a prospective cohort study
.
J Am Geriatr Soc
.
2018
;
66
(
10
):
1948
55
.
19.
Liu
D
,
Zhou
H
,
Tao
Y
,
Tan
J
,
Chen
L
,
Huang
H
.
Alzheimer’s disease is associated with increased risk of osteoporosis: the Chongqing aging study
.
Curr Alzheimer Res
.
2016
;
13
(
10
):
1165
72
.
20.
Baker
NL
,
Cook
MN
,
Arrighi
HM
,
Bullock
R
.
Hip fracture risk and subsequent mortality among Alzheimer’s disease patients in the United Kingdom, 1988–2007
.
Age Ageing
.
2011
;
40
(
1
):
49
54
.
21.
Loskutova
N
,
Honea
RA
,
Vidoni
ED
,
Brooks
WM
,
Burns
JM
.
Bone density and brain atrophy in early Alzheimer’s disease
.
J Alzheimers Dis
.
2009
;
18
(
4
):
777
85
.
22.
Bradburn
S
,
McPhee
JS
,
Bagley
L
,
Sipila
S
,
Stenroth
L
,
Narici
MV
.
Association between osteocalcin and cognitive performance in healthy older adults
.
Age Ageing
.
2016
;
45
(
6
):
844
9
.
23.
Obri
A
,
Khrimian
L
,
Karsenty
G
,
Oury
F
.
Osteocalcin in the brain: from embryonic development to age-related decline in cognition
.
Nat Rev Endocrinol
.
2018
;
14
(
3
):
174
82
.
24.
Mera
P
,
Ferron
M
,
Mosialou
I
.
Regulation of energy metabolism by bone-derived hormones
.
Cold Spring Harb Perspect Med
.
2018
8
6
a031666
.
25.
Mosialou
I
,
Shikhel
S
,
Liu
JM
,
Maurizi
A
,
Luo
N
,
He
Z
.
MC4R-dependent suppression of appetite by bone-derived lipocalin 2
.
Nature
.
2017
;
543
(
7645
):
385
90
.
26.
Inestrosa
NC
,
Varela-Nallar
L
.
Wnt signaling in the nervous system and in Alzheimer’s disease
.
J Mol Cell Biol
.
2014
;
6
(
1
):
64
74
.
27.
Dengler-Crish
CM
,
Ball
HC
,
Lin
L
,
Novak
KM
,
Cooper
LN
.
Evidence of Wnt/β-catenin alterations in brain and bone of a tauopathy mouse model of Alzheimer’s disease
.
Neurobiol Aging
.
2018
;
67
:
148
58
.
28.
Oury
F
,
Khrimian
L
,
Denny
CA
,
Gardin
A
,
Chamouni
A
,
Goeden
N
.
Maternal and offspring pools of osteocalcin influence brain development and functions
.
Cell
.
2013
;
155
(
1
):
228
41
.
29.
Shan
C
,
Ghosh
A
,
Guo
XZ
,
Wang
SM
,
Hou
YF
,
Li
ST
.
Roles for osteocalcin in brain signalling: implications in cognition- and motor-related disorders
.
Mol Brain
.
2019
;
12
(
1
):
23
.
30.
Purro
SA
,
Dickins
EM
,
Salinas
PC
.
The secreted Wnt antagonist dickkopf-1 is required for amyloid β-mediated synaptic loss
.
J Neurosci
.
2012
;
32
(
10
):
3492
8
.
31.
Jia
L
,
Piña-Crespo
J
,
Li
Y
.
Restoring Wnt/β-catenin signaling is a promising therapeutic strategy for Alzheimer’s disease
.
Mol Brain
.
2019
;
12
(
1
):
104
.
32.
Solfrizzi
V
,
Scafato
E
,
Frisardi
V
,
Sancarlo
D
,
Seripa
D
,
Logroscino
G
.
Frailty syndrome and all-cause mortality in demented patients: the Italian Longitudinal Study on Aging
.
Age
.
2012
;
34
(
2
):
507
17
.
33.
Forette
F
,
Seux
ML
,
Staessen
JA
,
Thijs
L
,
Babarskiene
MR
,
Babeanu
S
.
The prevention of dementia with antihypertensive treatment: new evidence from the Systolic Hypertension in Europe (Syst-Eur) study
.
Arch Intern Med
.
2002
;
162
(
18
):
2046
52
.
34.
Ongali
B
,
Nicolakakis
N
,
Tong
XK
,
Aboulkassim
T
,
Imboden
H
,
Hamel
E
.
Enalapril alone or co-administered with losartan rescues cerebrovascular dysfunction, but not mnemonic deficits or amyloidosis in a mouse model of Alzheimer’s disease
.
J Alzheimers Dis
.
2016
;
51
(
4
):
1183
95
.
35.
Woodhouse
L
,
Scutt
P
,
Krishnan
K
,
Berge
E
,
Gommans
J
,
Ntaios
G
.
Effect of hyperacute administration (within 6 hours) of transdermal glyceryl trinitrate, a nitric oxide donor, on outcome after stroke: subgroup analysis of the Efficacy of Nitric Oxide in Stroke (ENOS) trial
.
Stroke
.
2015
;
46
(
11
):
3194
201
.
36.
Chen
KH
,
Yeh
MH
,
Livneh
H
,
Chen
BC
,
Lin
IH
,
Lu
MC
.
Association of traditional Chinese medicine therapy and the risk of dementia in patients with hypertension: a nationwide population-based cohort study
.
BMC Complement Altern Med
.
2017
;
17
(
1
):
178
.
37.
Liu
CT
,
Wu
BY
,
Hung
YC
,
Wang
LY
,
Lee
YY
,
Lin
TK
.
Decreased risk of dementia in migraine patients with traditional Chinese medicine use: a population-based cohort study
.
Oncotarget
.
2017
;
8
(
45
):
79680
92
.