Changes in dementia risk along with onset age of depression: A longitudinal cohort study of elderly depressed patients

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Previous research typically dichotomized depression onset age between 55 and 65 years; however, the specific age at which depression onset increases AD risk in older adults remains unclear. In this study, we aimed to investigate the relationship between depression onset age and AD risk and compare characteristics between different onset age groups. Methods A longitudinal cohort of 251 elderly patients diagnosed with major depressive disorder was followed for up to 22 years. Participants were categorized into four groups based on depression onset age: ≤ 54 years, 55–64, 65–74, and ≥ 75 years. Annual cognitive assessments were conducted using the Korean Mini-Mental State Examination, with further neuropsychological testing when cognitive decline was suspected. Cox proportional hazards models were used to assess AD conversion risk across groups, adjusting for covariates. Results During follow-up, 75 patients (29.88%) converted to AD. Depression onset after age 75 was significantly associated with a higher risk of AD conversion (hazard ratio [HR], 8.95; 95% confidence interval [CI], 3.41–23.48; p < 0.0001) and a shorter time to conversion compared to onset before age 55 (40.93 vs. 83.40 months). After adjusting for covariates, depression onset after age 75 remained significantly associated with AD conversion (adjusted HR, 6.07; 95% CI, 1.26–29.34; p = 0.0189). This group also had milder depressive symptoms and a higher prevalence of hypertension and cerebrovascular disease than those with depression onset before age 55. Conclusions Depression onset after age 75 is strongly associated with an increased risk of AD and a shorter time to dementia onset. Individuals with depression onset after age 75 appear more closely linked to vascular comorbidities, while those with depression onset before age 55 are characterized by severe and recurrent depressive episodes. The mechanisms leading to AD in individuals with depression may differ from those without prior depression. Trial registration: The study is registered (NCT01237275, 1994-10-14, Development of A Technique to Predict Antidepressant Responsiveness in Depressive Patients) in ClinicalTrials.gov. Depression in late-life Onset age of depression Dementia Alzheimer’s disease Alzheimer’s Dementia Figures Figure 1 Figure 2 Background A large-than-expected number of patients with depression have converted to Alzheimer's dementia (AD) in real-world settings ( 1 ). We previously demonstrated that depression is an independent risk factor for dementia in a nationwide cohort, with an adjusted hazard ratio (HR) of 2.35 (95% confidence interval [CI] 2.21–2.49) ( 2 ). Depressive symptoms frequently precede or co-occur with neurodegenerative conditions in many patients with dementia ( 3 ). Extensive research has explored the link between late-life depression and AD ( 1 , 3 – 7 ); however, the heterogeneity of late-life depression complicates understanding of the pathways through which depression contributes to dementia risk ( 8 , 9 ). One factor that may explain this heterogeneity is the onset age of depression ( 10 ). Depression that begins early in life often has a familial history and a stronger genetic predisposition to mood disorders ( 11 ), contributing to cognitive dysfunction through mechanisms such as chronic stress, dysregulation of the hypothalamic-pituitary-adrenal axis and neuroinflammation ( 12 ). In contrast, depression that occurs later in life is thought to result from brain damage ( 8 ), and may be an early sign of dementia. A notable example is vascular depression ( 13 ), a subtype of late-life depression linked to cerebrovascular disease. If depression onset at different ages reflects distinct characteristics and mechanisms, there may be a specific age interval where the risk of dementia significantly diverges. In particular, later-onset depression may signal a higher dementia risk and a shorter time to onset. Despite this rationale, previous studies have typically dichotomized depression onset between ages 55 and 65 without establishing a precise age criterion ( 14 ). While prior research has explored the link between late-life depression and dementia, the relationship between depression onset age and dementia risk remains underexplored. To address this, we conducted a longitudinal study of a hospital cohort of patients with depression, with up to 22 years of follow-up to examine the relationship between depression onset age and dementia risk. We also compared characteristics between different onset-age groups to explore variations in dementia risk. Methods Participants We screened clinically referred Korean outpatients aged 55 or older who visited a geropsychiatry clinic at a university hospital between June 1995 and January 2012. All participants met the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for major depressive disorder ( 15 ). Participants were included if they were experiencing a current unipolar major depressive episode (based on DSM-IV criteria) and had a baseline 17-item Hamilton Depression Rating Scale (HAM-D) score of at least 15 ( 16 ). Patients scoring below 28/30 on the Korean version of the Mini-Mental State Examination (K-MMSE) ( 17 ) were excluded due to memory or cognitive impairment. We also excluded individuals with psychotic disorders (e.g., schizophrenia, delusional disorder), bipolar disorder, neurological illnesses (e.g., Parkinson’s disease, epilepsy), intellectual developmental disability, major medical conditions, history of alcohol or drug dependence, personality disorders, head trauma with loss of consciousness, malignancy, abnormal baseline laboratory findings, or unstable psychiatric conditions (e.g., recent suicide attempt during the current episode). The final analyses included 251 participants with late-life depression who met the inclusion criteria. The study was approved by the ethics review board of Samsung Medical Center (IRB No. 1999-10-14), and written informed consent was obtained from all participants. Study protocol Study protocol This study was conducted in a naturalistic clinical setting, building on our previous research on antidepressant responses in major depression ( 18 – 20 ). All participants underwent a structured research interview using the Samsung Psychiatric Evaluation Schedule (SPES) ( 21 ). The SPES collected data on psychiatric symptoms, cognitive screening, comorbid physical diagnoses (hypertension, diabetes mellitus, dyslipidemia, cardiac disease, and cerebrovascular disease), and psychosocial factors (age, sex, onset age of depression, duration of current episode, number of depressive episodes, family history of depression, and initial HAM-D score). Each diagnostic interview involved the patient and at least one family member. A board-certified psychiatrist confirmed all diagnoses using SPES, clinical observations, and medical records. Peripheral blood samples were collected at baseline for apolipoprotein E (ApoE) genotyping and plasma biomarker analyses. Participants were followed up every three months until December 31, 2023, or until dementia onset, patient death, or the end of the follow-up period. The K-MMSE was administered annually, and if cognitive decline was reported by the patient, caregivers, or clinician, we performed further neuropsychological assessments, brain magnetic resonance imaging (MRI), and laboratory tests. Neuropsychological assessments included the K-MMSE, clinical dementia rating (CDR) scale ( 22 ), Seoul neuropsychological screening battery-dementia version ( 23 ), Seoul-activities of daily living ( 23 ), Seoul-instrumental activities of daily living ( 24 ), Korean version of the neuropsychiatric inventory ( 25 ), and Korean version of the geriatric depression scale ( 26 ). All tests were repeated annually during the follow-up period of up to 22 years. Brain MRI results were interpreted by board-certified neuroradiologists and served as an auxiliary measure to differentiate other diseases that may cause dementia syndromes. To ensure clarity in clinical diagnosis, we excluded patients exhibiting signs of degenerative non-Alzheimer’s disease dementia, including Parkinsonian features or behavioral and personality changes. At our geropsychiatry clinic, inter-observer diagnostic reliability for distinguishing between AD and non-AD was 91.4% ( 27 ). Onset age of depression At enrollment, participants reported the age of their first depressive episode, primarily based on patient and caregiver recall, and cross-referenced with medical records when available. We hypothesized that depression onset at different life stages may exhibit distinct characteristics and arise from different mechanisms ( 28 ), with a specific age interval where dementia risk diverges. To identify this potential inflection point, we categorized the onset age of depression into 10-year intervals and calculated AD risks for each group. Participants were categorized into four groups based on the age of their first depressive episode: 54 years or earlier, 55 to 64 years, 65 to 74 years, and 75 years or later. Characteristics of depression Baseline clinical data on depression were collected at enrollment through interviews, with additional information gathered during follow-up. This included a family history of depression, multiple tendency, chronicity of depression, and comorbid medical conditions (e.g., hypertension, diabetes, dyslipidemia, cardiac disease, cerebrovascular disease). Patients with three or more lifetime depressive episodes were classified as having multiple tendencies ( 29 ), while chronicity of depression was defined as episodes lasting 24 months or longer at any point in the patient’s life ( 15 ). During follow-up, antidepressant treatment response and remission were assessed using the HAM-D score. The response was defined as a 50% or greater reduction in the HAM-D score at six weeks, while remission was defined as a HAM-D score of 7 or lower at twelve weeks of treatment ( 30 ). Conversion to AD The primary outcome was conversion to AD as defined by the DSM-IV. Participants with a CDR score greater than 1 had their diagnoses confirmed by a clinician using DSM-IV criteria, neuropsychological testing, and impairments in activities of daily living. Probable AD was diagnosed according to the National Institute of Neurological and Communicative Diseases and the Stroke-Alzheimer’s Disease and Related Disorders Association criteria ( 31 ). Participants with newly diagnosed dementia underwent annual follow-up examinations to confirm dementia status and subtype, with the date of dementia onset recorded as the first confirmed diagnosis. Biomarkers of AD At baseline, we measured the ApoE4 genotype and plasma levels of amyloid-beta 40 (Aβ40), amyloid-beta 42 (Aβ42), total Tau, and Interleukin-1β (IL-1β) to assess their predictive value for future dementia risk, as these biomarkers are relevant to AD ( 32 ). Notably, IL-1β has been associated with AD development in patients with depression ( 33 ). Due to the significant time elapsed since cohort recruitment, only 68 usable blood specimens were available, collected at enrollment rather than at the time of AD diagnosis. Despite this limitation, these biomarkers can provide predictive value for AD risk, as pathological changes often begin decades before clinical symptoms appear ( 34 , 35 ). While this analysis is constrained and exploratory, it serves as a preliminary investigation to inform future studies. Further details on the biomarker measurement methods are provided in the Additional Material (see Additional file 1). Statistical analysis All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC), with statistical significance set at p < 0.05. Clinical and demographic characteristics of participants were presented as categorical variables (frequencies and proportions) or continuous variables (mean ± standard deviation [SD]). Univariable Cox proportional hazards regression was used to estimate HRs and 95% CIs for depression onset age, as well as other clinical and demographic characteristics. Multivariable Cox proportional hazards regression assessed AD conversion risk based on depression onset age, adjusting for variables with p < 0.05 in the univariable analysis. The proportional hazard assumption was verified using Schoenfeld residuals, and collinearity was evaluated with the variance inflation factor to ensure independent contributions of predictors. Bonferroni's correction was applied to account for multiple comparisons among the four depression-onset-age groups. Cross-sectional comparisons between onset-age groups were conducted using the Wilcoxon rank-sum test for non-normally distributed continuous variables and Fisher's exact test or chi-square test for categorical variables, as appropriate. In a subset with available plasma biomarker data to evaluate their association with dementia risk, univariable and multivariable Cox proportional hazards regression analyses were performed. To choose the variables in the multivariable model, forward stepwise variable selection with entry and exit criteria of 0.05 was employed and the adequate number of variables was limited to 2 to minimize overfitting. Results Participants characteristics Table 1 presents the baseline clinical and demographic characteristics of participants, along with the univariable Cox proportional hazard regression results. Among the 251 participants, 75 (29.88%) converted to AD during the follow-up period. Age was significantly associated with a higher risk of AD conversion, with participants who converted being older (71.47 ± 6.92 years) than those who did not (69.64 ± 6.93 years) (HR, 1.09; 95% CI, 1.05–1.13; p < 0.0001). Furthermore, participants who responded to antidepressant treatment had an increased risk of AD conversion (HR, 2.40; 95% CI, 1.37–4.18; p = 0.0021). A family history of depression was linked to a reduced risk of AD conversion (HR, 0.38; 95% CI, 0.17–0.83; p = 0.0158), while those with a multiple tendency (three or more lifetime depressive episodes) had a lower risk of conversion (HR, 0.56; 95% CI, 0.32–0.97; p = 0.0390). Chronicity of depression, defined as episodes lasting 24 months or longer, was associated with a higher risk (HR, 1.85; 95% CI, 1.16–2.96; p = 0.0101). In addition, participants with cerebrovascular disease exhibited a significantly higher risk of AD conversion (HR, 2.59; 95% CI, 1.52–4.43; p = 0.0005). However, the presence of the ApoE4 allele was not significantly linked to AD conversion (HR, 1.27; 95% CI, 0.75–2.12, p = 0.3713). Table 1 Demographic and Clinical Characteristics of Participants Total Converted to AD Hazard Ratio p -value (n = 251) No (n = 176) Yes (n = 75) (95% CI) Baseline Demographics Sex (Female) 203 (80.88) 140 (79.55) 63 (84.00) 1.16 (0.62–2.15) 0.6455 Age 70.18 ± 6.96 69.64 ± 6.93 71.47 ± 6.92 1.09 (1.05–1.13) < .0001 Onset Age of Depression < .0001 54 Years or Earlier 57 (22.71) 47 (26.70) 10 (13.33) 1 (Reference) 55 to 64 Years 61 (24.30) 42 (23.86) 19 (25.33) 2.29 (0.89–5.85) 0.1068 65 to 74 Years 93 (37.05) 68 (38.64) 25 (33.33) 2.67 (1.07–6.66) 0.0310 75 Years or Later 40 (15.94) 19 (10.80) 21 (28.00) 8.95 (3.41–23.48) < .0001 Characteristics of Depression Initial HAM-D 19.52 ± 4.42 19.58 ± 4.32 19.29 ± 4.79 0.96 (0.90–1.03) 0.2820 Response 162 (64.54) 103 (58.52) 59 (78.67) 2.40 (1.37–4.18) 0.0021 Remission 90 (35.86) 60 (34.09) 30 (40.00) 1.27 (0.80–2.01) 0.3170 Family History of Depression 42 (16.73) 35 (19.89) 7 (9.33) 0.38 (0.17–0.83) 0.0158 Multiple Tendency* 63 (25.10) 47 (26.70) 16 (21.33) 0.56 (0.32–0.97) 0.0390 Chronicity** 62 (24.70) 33 (18.75) 29 (38.67) 1.85 (1.16–2.96) 0.0101 Comorbidities Hypertension 115 (45.82) 74 (42.05) 41 (54.67) 1.42 (0.90–2.24) 0.1300 Diabetes Mellitus 46 (18.33) 34 (19.32) 12 (16.00) 1.13 (0.61–2.10) 0.6984 Dyslipidemia 26 (10.36) 19 (10.80) 7 (9.33) 0.83 (0.38–1.82) 0.6499 Cardiac Disease 22 (8.76) 14 (7.95) 8 (10.67) 1.30 (0.62–2.73) 0.4870 Cerebrovascular Disease 28 (11.16) 10 (5.68) 18 (24.00) 2.59 (1.52–4.43) 0.0005 Biomarker of AD ApoE4 allele, 0 199 (79.28) 144 (81.82) 55 (73.33) ApoE4 allele, 1 or 2 52 (20.72) 32 (18.18) 20 (26.67) 1.27 (0.75–2.12) 0.3713 Neuropsychological Test on Diagnosis of AD MMSE 24.60 ± 5.75 27.53 ± 2.40 18.00 ± 5.64 CDR 0.48 ± 0.66 0.12 ± 0.22 1.28 ± 0.61 CDR-SB 2.70 ± 3.56 0.81 ± 0.76 7.06 ± 3.66 GDS 2.52 ± 1.53 1.64 ± 0.75 4.47 ± 0.86 HAM-D, 17-item Hamilton Rating Scale for Depression; AD, Alzheimer’s dementia; ApoE4, apolipoprotein E4; MMSE, Mini Mental State Examination; CDR, Clinical Dementia Rating; CDR-SB, Sum of Boxes of CDR; GDS, Global Deterioration Scale; CI, confidence interval. * Multiple tendency refers to patients with three or more lifetime depressive episodes. ** Chronicity is defined as depressive episodes lasting 24 months or longer at any point in the patient's life. Data are presented as mean ± standard deviation for continuous variables and as frequency (percentage) for categorical variables. Cox proportional hazards regression analysis was performed to determine the association between demographic and clinical factors and conversion to AD. Association between onset age of depression and AD conversion In the univariable analysis (Table 1 , Fig. 1 , Additional file 2), participants with depression onset after age 75 exhibited the highest risk of AD conversion (HR, 8.95; 95% CI, 3.41–23.48; p < 0.0001) compared to those with onset before age 55 (reference group), with a shortest average time to conversion of 40.93 months (SD, 32.15). Participants with onset between ages 65 and 74 had a significantly elevated risk (HR, 2.67; 95% CI, 1.07–6.66; p = 0.0310), with an average time to conversion of 60.07 months (SD, 45.97). The group with onset between ages 55 and 64 showed no significant increase in AD risk (HR, 2.29; 95% CI, 0.89–5.85; p = 0.1068); however, their average time to AD conversion gradually increased to 72.59 months (SD, 54.54), while the reference group had an average of 83.40 months (SD, 57.42). For the multivariable analysis, covariates were selected based on a p-value < 0.05 from the univariable analysis. In addition, sex was defined as a covariate due to its clinical significance, regardless of statistical significance. After adjusting for sex, age, antidepressant treatment response, family history of depression, multiple tendency, chronicity, and cerebrovascular disease, the age of depression onset remained significantly associated with AD conversion risk (p = 0.0119, Table 2 , and Fig. 2 ). Participants with depression onset after age 75 had a significantly higher adjusted risk of AD conversion (adjusted HR, 6.07; 95% CI, 1.26–29.34; p = 0.0189) compared to those with onset before age 55. In contrast, onset between ages 65 and 74 showed a non-significant trend toward increased risk (adjusted HR, 1.86; 95% CI, 0.57–6.06; p = 0.6371). Onset between ages 55 and 64 was not significantly associated with AD conversion (adjusted HR, 1.96; 95% CI, 0.72–5.35; p = 0.3295). The estimated survival curves from the multivariable Cox proportional hazards model, adjusted for male gender, age of 70 years, no treatment response, no family history of depression, no cerebrovascular disease, no chronicity of depression, and no multiple tendency, are depicted in Fig. 2 . Participants with depression onset at age 75 or later had the lowest AD-free survival rate, indicating the highest risk of AD conversion. Conversely, participants with depression onset before age 55 exhibited the highest AD-free survival rate. Those with depression onset between ages 55 and 74 exhibited intermediate survival rates, with survival curves for the 55–64 and 65–74 age groups closely aligned, indicating similar risk profiles. Table 2 Association between Onset Age of Depression and Alzheimer's Dementia Risk Multivariable Analysis adjusted HR (95% CI) p-value Onset Age of Depression 0.0119 54 Years or Earlier 1 (Reference) 55 to 64 Years 1.96 (0.72–5.35) 0.3295 65 to 74 Years 1.86 (0.57–6.06) 0.6371 75 Years or Later 6.07 (1.26–29.34) 0.0189 Sex (Female) 1.32 (0.68–2.58) 0.4106 Age 1.03 (0.97–1.09) 0.3623 Response 1.87 (1.03–3.38) 0.0403 Family History of Depression 0.54 (0.24–1.22) 0.1359 Multiple Tendency* 0.94 (0.48–1.85) 0.8562 Chronicity** 2.15 (1.31–3.50) 0.0023 Cerebrovascular Disease 1.50 (0.83–2.70) 0.1795 HR, hazard ratio; CI, confidence interval. * Multiple tendency refers to patients with three or more lifetime depressive episodes. ** Chronicity is defined as depressive episodes lasting 24 months or longer at any point in the patient's life. Cox proportional hazard regression analysis was used to determine the association between the onset age of depression and conversion to AD after adjusting for covariates. Covariates were selected based on a p-value < 0.05 in the univariable analysis. Comparison of onset age before 55 and after 75 We specifically compared patients with depression onset before age 55 and those with onset at or after age 75, as these groups exhibited the most significant differences in dementia risk. Including other onset-age groups that did not show significant differences could dilute the effects of depression onset age on dementia risk; therefore, we excluded them to ensure clearer distinctions between the groups with the most pronounced risk differences. Participants with depression onset at or after 75 were significantly older (median age, 79.00 years; interquartile range [IQR], [76.00, 81.00]) than those with onset before age 55 (median age, 64.00 years; IQR, [59.00, 71.00]; p < 0.0001). Initial depression severity was lower in the group with onset at or after age 75 (median HAM-D score, 18.00; IQR, [15.50, 20.00]) compared to the group with onset before age 55 (median HAM-D score, 19.50; IQR, [17.00, 23.00]; p = 0.0264). A greater proportion of participants with depression onset at or after age 75 responded to treatment (75.00% vs. 52.63%; p = 0.0256). Furthermore, 64.91% of participants with depression onset before age 55 had a higher prevalence of multiple depressive episodes, experiencing three or more lifetime episodes. In comparison, only 2.50% of those with onset at or after age 75 had this history (p < 0.0001). Regarding comorbidities, hypertension (55.00% vs. 29.82%; p = 0.0128) and cerebrovascular disease (25.00% vs. 3.51%; p = 0.0031) were more common in the group with depression onset at or after age 75. Association between biomarkers and AD conversion An Additional table file presents the results of both univariable and multivariable analyses assessing the association between biomarkers and the risk of AD conversion in 68 participants (see Additional file 3). Due to the smaller sample size in the subset, we simplified the classification to two groups—depression onset before age 75 and after age 75—aligning with the main analysis findings, instead of using the original four groups. The analysis indicated that participants with depression onset after age 75 had a significantly higher risk of AD conversion compared to those with onset before age 75, consistent with the main analysis. In the univariable analysis, the HR for the after-75-group was 3.90 (95% CI: 1.16–13.08; p = 0.0278), which further increased in the multivariable analysis to an adjusted HR of 7.39 (95% CI: 1.87–29.18; p = 0.0043). In the univariable analysis, Aβ42 levels were lower in those who converted to AD (HR, 0.83; 95% CI, 0.69–0.99; p = 0.0432). No significant associations were found for ApoE4 allele status, Aβ40 levels, Aβ42/Aβ40 ratio, or total Tau protein levels. Elevated plasma levels of the inflammatory marker IL-1β were strongly associated with an increased risk of AD conversion (log-transformed; HR, 5.48; 95% CI, 2.06–14.60; p = 0.0007). After adjusting for depression onset after age 75, this association strengthened, yielding an adjusted HR of 8.68 (95% CI: 2.83–26.63; p = 0.0002). Discussion In this longitudinal cohort study, we identified significant changes in dementia hazard ratios based on the age of depression onset. Patients with depression onset at age 75 or later had a significantly higher risk of developing AD and experienced a faster dementia progression compared to those with onset before age 55. Individuals with depression onset after age 75 had less severe depressive symptoms and a higher prevalence of hypertension and cerebrovascular disease than those with depression onset before age 55. Our results align with findings from previous studies reporting an increased likelihood of dementia in patients with late-life depression ( 6 , 7 , 36 , 37 ). The onset age of depression significantly influences dementia risk. Depression occurring later in life appeared to signal impending dementia, with a higher risk and shorter time to AD conversion (Table 2 , Fig. 1 ). This increased risk may be due to an "age-by-disease interaction effect," where the impact of depression on dementia varies by age ( 10 ). In other words, depression later in life may have a more detrimental impact on cognitive decline. However, our cohort was limited to patients aged 55 and older, meaning most of our comparison group (onset before age 55) consisted of individuals with early-onset 'recurrent' depression, some of whom may have had recurrent episodes after the age of 75. Even after adjusting for age, the association between depression onset age and dementia risk remained significant, suggesting that the age-by-disease interaction alone does not fully account for our findings. If depression in older adults had a greater impact on cognitive function regardless of initial onset, we would expect recurrent depression later in life to be a significant dementia risk factor. However, our multivariable analysis did not support this, as late-life recurrent depression (indicated by "multiple tendency") did not independently increase dementia risk beyond the age of depression onset (Table 2 ). A plausible explanation is that depression onset after age 75 may result from pre-existing brain damage or neurodegeneration. The higher prevalence of vascular-related comorbidities, such as hypertension and cerebrovascular disease, supports this hypothesis (Table 3 ). In our previous nationwide cohort study, we observed an additive interaction between depression and cerebrovascular disease in relation to AD risk ( 2 ). Furthermor, mounting biological evidence suggests that cerebrovascular disease ( 38 , 39 ) and hypertension ( 40 ) contribute to increased amyloid burden in the brain, potentially linking late-life depression to Alzheimer-related pathology. Future research should examine how vascular damage accelerates neurodegeneration and triggers depressive symptoms, focusing on the interplay between vascular comorbidities and Alzheimer's disease-related pathology. Table 3 Comparison of Depression Onset Age Before 55 and After 75 Onset Age of Depression p -value < 55 Years (n = 57) ≥ 75 Years (n = 40) Baseline Demographics Sex (Female) 48 (84.21) 29 (72.50) 0.1605 Age 64.00 [59.00, 71.00] 79.00 [76.00, 81.00] < .0001 Characteristics of Depression Initial HAM-D 19.50 [17.00, 23.00] 18.00 [15.50, 20.00] 0.0264 Response 30 (52.63) 30 (75.00) 0.0256 Remission 20 (35.09) 14 (35.00) 0.9929 Family History of Depression 14 (24.56) 5 (12.50) 0.1406 Multiple Tendency* 37 (64.91) 1 (2.50) < .0001 Chronicity** 15 (26.32) 5 (12.50) 0.0978 Comorbidities Hypertension 17 (29.82) 22 (55.00) 0.0128 Diabetes Mellitus 7 (12.28) 5 (12.50) 1.0000† Dyslipidemia 4 (7.02) 5 (12.50) 0.4814† Cardiac Disease 2 (3.51) 4 (10.00) 0.2262† Cerebrovascular Disease 2 (3.51) 10 (25.00) 0.0031† Biomarkers of AD ApoE4 allele, 0 46 (80.70) 33 (82.50) ApoE4 allele, 1 or 2 11 (19.30) 7 (17.50) 0.8226 HAM-D, 17-item Hamilton Rating Scale for Depression; AD, Alzheimer’s dementia; ApoE4, apolipoprotein E4. * Multiple tendency refers to patients with three or more lifetime depressive episodes. ** Chronicity is defined as depressive episodes lasting 24 months or longer at any point in the patient's life. Data are presented as median [first quartile, third quartile] for continuous variables, and as frequency (percentage) for categorical variables. Wilcoxon rank sum test was used to compare continuous variables. Fisher's exact test(†) or chi-square test was used for comparisons of categorical variables, depending on expected frequency distributions. Our study suggests that age 75 may serve as an important indicator for distinguishing between early- and late-onset depression, as dementia risk increases significantly beyond this age (Table 2 ). As the global population ages, researchers have increasingly subdivided the older population into more specific age groups. Individuals aged 75 and older are often referred to as the "old-old," while those aged 65 to 74 are considered the "young-old" ( 41 , 42 ). The old-old group experiences more chronic health conditions, functional impairments, and cognitive decline compared to the young-old ( 41 ). Although age 65 is typically used to define older adulthood, our study supports the evidence that significant neuropsychiatric changes, including increased AD risk, may occur around age 75. In our cohort, depression onset after age 75 was characterized by milder depressive symptoms, fewer recurrent episodes, and a higher prevalence of hypertension and cerebrovascular disease compared to onset before age 55 (Table 3 ). These findings are consistent with previous studies using a lower threshold of 60 years, which also linked later-onset depression to older age, less severe depression, and poorer cognitive functioning ( 28 ). Although we used a higher threshold of 75 years, the findings were comparable. However, our results diverge from previous reports suggesting that severe, recurrent depression is a significant contributor to dementia risk ( 43 , 44 ). This discrepancy may arise from not accounting for the onset age of depression. For instance, Dotson et al . ( 43 ) reported a mean depression onset in the mid-to-late 50s, with likely few patients whose depression began after age 75. Since depression onset after age 75 constitutes a very small subset of the overall depression population, its unique characteristics may not have been fully captured in studies focusing on earlier-onset cases. This could help explain why depressive symptoms in later life might have a different association with dementia risk compared to earlier-onset depression, further emphasizing the need for onset-age-specific analysis in understanding the link between depression and dementia. Given the distinct characteristics and minority status of depression onset after age 75, our findings suggest that the factors influencing dementia risk may differ between those with depression before and after this age. Although analyzing the longitudinal association with dementia risk in both groups was not within the scope of our study, exploring these differences could offer valuable insights into group-specific dementia risk factors. In our cohort, chronic depression—defined as depressive episodes lasting 2 years or more—was linked to an increased risk of AD, even after adjusting for covariates including age of depression onset (Table 2 ). While depressive symptoms were less severe in the high-risk group with depression onset after age 75, chronic depressive episodes may still contribute to dementia risk in the earlier-onset group, which comprised 84% of the cohort. Future research should focus on identifying distinct risk factors through longitudinal studies that examine the pathways linking depression and dementia in individuals with depression onset before and after age 75. In the subset analysis, established AD biomarkers such as Aβ42/Aβ40 ratio, total Tau, and ApoE status were not significantly associated with AD risk. Howeveer, the inflammatory marker IL-1β was a significant factor promoting AD conversion, regardless of depression onset age (see Additional file 3). These results suggest that dementia following depression may develop through mechanisms distinct from those seen in non-depressed populations, as previously suggested ( 37 , 45 – 47 ). Our findings indicate that the inflammatory process, marked by elevated IL-1β, may drive dementia pathogenesis across the broader depression cohort. However, given the limitation of sample size and the timing of biomarker collection, these findings should be interpreted cautiously and considered preliminary groundwork for future research. Limitations This study has certain limitations that should be acknowledged. First, the naturalistic setting, which lacked a healthy control group, limited our ability to confirm the specific association between depression and dementia. Without a non-depressed comparison group, it was difficult to isolate the direct impact of depression on AD risk. However, rather than using healthy controls, we compared depression onset at age 75 or later with depression onset before age 55 to explore whether later-onset depression was more closely linked to AD conversion. This approach highlighted depression onset after age 75 as a potential dementia indicator, supporting the hypothesis that specific phenotypes of late-life depression are more strongly associated with AD progression. Furthermor, the naturalistic setting allowed for the observation of real-world clinical outcomes, enhancing external validity by providing valuable insights into how depression and AD interact in typical clinical practice. Second, the cohort was drawn from a single geropsychiatry clinic, consisting of clinically referred patients, which may have introduced selection bias, limiting the generalizability of the findings to community-dwelling older individuals with depression. Furthermore, all participants were of Korean descent, and unique genetic, cultural, or environmental factors may have influenced the relationship between depression and dementia. Therefore, caution is needed when applying these findings to other ethnic groups or settings. Third, our use of stringent baseline cognitive criteria (K-MMSE ≥ 28) may have selectively included individuals with higher cognitive reserve. This could introduce bias especially in older participants, as cognitive decline is more common with aging. Consequently, we may have overrepresented individuals with exceptionally preserved cognition for their age. However, we employed these stringent criteria to isolate the specific effects of depression on AD risk. While this approach may have limited the generalizability of our findings, it was necessary to establish a clear temporal relationship between depression and cognitive decline. Fourth, recall bias may have affected the accuracy of the reported age of depression onset, potentially leading to misclassification within onset age categories. This could influence the observed relationship between depression onset and dementia risk. To mitigate this, we cross-referenced patient and caregiver reports with available medical records to enhance data accuracy. Moreover, we grouped the onset age into broad 10-year categories (≤ 54 years, 55–64, 65–74, and ≥ 75 years), which likely reduced recall bias, as individuals tend to more reliably recall the approximate decade of their depression onset ( 48 ). Lastly, while plasma biomarkers are less invasive and more affordable than cerebrospinal fluid biomarkers or positron emission tomography imaging, they may be less precise for detecting Alzheimer’s pathology. Plasma biomarkers can be influenced by peripheral factors, potentially reducing their sensitivity and specificity compared to cerebrospinal fluid measures ( 32 ). This limitation may have impacted the accuracy of our findings regarding the biological markers associated with AD risk. Conclusions Our study demonstrates that depression occurring after age 75 is associated with the highest risk of AD conversion and the shortest time to dementia onset. Depression that begins after age 75 is more closely linked to vascular comorbidities, whereas depression with onset before age 55 is associated with severe, recurrent depression. The physiological pathways leading to AD in depressed individuals may differ from those without prior depression. Further research is needed to clarify these mechanisms and explore targeted interventions to mitigate dementia risk in these populations. Abbreviations AD Alzheimer's dementia HR Hazard ratio CI Confidence interval DSM-IV Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition HAM-D Hamilton Depression Rating Scale K-MMSE Korean Mini-Mental State Examination ApoE Apolipoprotein E MRI Magnetic resonance imaging CDR Clinical dementia rating Aβ Amyloid-beta IL Interleukin SD Standard deviation Declarations Ethics approval and consent to participate The protocol was approved by the ethics review board of the Samsung Medical Center (IRB No. 1999-10-14). All research procedures were performed in accordance with relevant guidelines. Signed informed consent was obtained from all participants. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding This study was supported by grants from the National Research Foundation funded by the Korean government (Ministry of Science and ICT; 2020R1A2C2101276 to DKK and 2022R1A2C1092186 to SWL), Republic of Korea. The authors report no biomedical financial interests or potential conflicts of interest. Role of funding source The funders had no role in study design, data collection, data analysis, data interpretation, writing of the report, or the decision to submit this paper for publication. Availability of data and materials The dataset supporting the conclusions of this article is included within the article and its additional files. Author contribution YJJ, MJK, YKM, SWL, and DKK have full access to all data of this study and take responsibility for the integrity of the data and accuracy of the data analysis. YJJ, MJK, YKM, SWL, and DKK conceived and designed the study. MJK performed statistical analyses. YJJ drafted the manuscript. SWL and DKK supervised the entire study. All authors contributed to the interpretation of the data and have read and approved the final draft for submission. Acknowledgements We would like to thank Editage (www.editage.co.kr) for the English language editing. References Herbert J, Lucassen PJ. Depression as a risk factor for Alzheimer's disease: Genes, steroids, cytokines and neurogenesis - What do we need to know? Front Neuroendocrinol. 2016;41:153–71. Jang YJ, Kang C, Myung W, Lim SW, Moon YK, Kim H, et al. Additive interaction of mid- to late-life depression and cerebrovascular disease on the risk of dementia: a nationwide population-based cohort study. Alzheimers Res Ther. 2021;13(1):61. Huang YY, Gan YH, Yang L, Cheng W, Yu JT. Depression in Alzheimer's Disease: Epidemiology, Mechanisms, and Treatment. Biol Psychiatry. 2024;95(11):992–1005. Chi S, Yu JT, Tan MS, Tan L. Depression in Alzheimer's disease: epidemiology, mechanisms, and management. J Alzheimers Dis. 2014;42(3):739–55. 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The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 1993;43(11):2412–4. Ahn HJ, Chin J, Park A, Lee BH, Suh MK, Seo SW, et al. Seoul Neuropsychological Screening Battery-dementia version (SNSB-D): a useful tool for assessing and monitoring cognitive impairments in dementia patients. J Korean Med Sci. 2010;25(7):1071–6. Ahn IS, Kim JH, Kim S, Chung JW, Kim H, Kang HS, et al. Impairment of instrumental activities of daily living in patients with mild cognitive impairment. Psychiatry Investig. 2009;6(3):180–4. Kang HS, Ahn IS, Kim JH, Kim DK. Neuropsychiatric symptoms in korean patients with Alzheimer's disease: exploratory factor analysis and confirmatory factor analysis of the neuropsychiatric inventory. Dement Geriatr Cogn Disord. 2010;29(1):82–7. Bae JN, Cho MJ. Development of the Korean version of the Geriatric Depression Scale and its short form among elderly psychiatric patients. J Psychosom Res. 2004;57(3):297–305. Pyo JH, Han SS, Kim M-J, Moon YK, Lee SJ, Lee C et al. Potential Inflammatory Markers Related to the Conversion to Alzheimer’s Disease in Female Patients with Late-Life Depression. Biol Psychiatry Global Open Sci. 2024:100356. Olgiati P, Fanelli G, Serretti A. Age or age of onset: which is the best criterion to classify late-life depression? Int Clin Psychopharmacol. 2023;38(4):223–30. Lee Y, Lim SW, Kim SY, Chung JW, Kim J, Myung W, et al. Association between the BDNF Val66Met Polymorphism and Chronicity of Depression. Psychiatry Investig. 2013;10(1):56–61. Rush AJ, Kraemer HC, Sackeim HA, Fava M, Trivedi MH, Frank E, et al. Report by the ACNP Task Force on response and remission in major depressive disorder. Neuropsychopharmacology. 2006;31(9):1841–53. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology. 1984;34(7):939–44. d'Abramo C, D'Adamio L, Giliberto L. Significance of Blood and Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: Sensitivity, Specificity and Potential for Clinical Use. J Pers Med. 2020;10(3). Pyo JH, Han SS, Kim MJ, Moon YK, Lee SJ, Lee C, et al. Potential Inflammatory Markers Related to the Conversion to Alzheimer's Disease in Female Patients With Late-Life Depression. Biol Psychiatry Glob Open Sci. 2024;4(5):100356. Moffat G, Zhukovsky P, Coughlan G, Voineskos AN. Unravelling the relationship between amyloid accumulation and brain network function in normal aging and very mild cognitive decline: a longitudinal analysis. Brain Commun. 2022;4(6):fcac282. Parent C, Rousseau LS, Predovan D, Duchesne S, Hudon C. Longitudinal association between ß-amyloid accumulation and cognitive decline in cognitively healthy older adults: A systematic review. Aging Brain. 2023;3:100074. Linnemann C, Lang UE. Pathways Connecting Late-Life Depression and Dementia. Front Pharmacol. 2020;11:279. Mackin RS, Insel PS, Landau S, Bickford D, Morin R, Rhodes E, et al. Late-Life Depression Is Associated With Reduced Cortical Amyloid Burden: Findings From the Alzheimer's Disease Neuroimaging Initiative Depression Project. Biol Psychiatry. 2021;89(8):757–65. Pluta R, Ułamek-Kozioł M, Januszewski S, Czuczwar S. Amyloid pathology in the brain after ischemia. Folia Neuropathol. 2019;57(3):220–6. Garcia-Alloza M, Gregory J, Kuchibhotla KV, Fine S, Wei Y, Ayata C, et al. Cerebrovascular lesions induce transient β-amyloid deposition. Brain. 2011;134(Pt 12):3697–707. Fungwe TV, Ngwa JS, Johnson SP, Turner JV, Ramirez Ruiz MI, Ogunlana OO, et al. Systolic Blood Pressure Is Associated with Increased Brain Amyloid Load in Mild Cognitively Impaired Participants: Alzheimer's Disease Neuroimaging Initiatives Study. Dement Geriatr Cogn Disord. 2023;52(1):39–46. Chung E, Lee SH, Lee HJ, Kim YH. Comparative study of young-old and old-old people using functional evaluation, gait characteristics, and cardiopulmonary metabolic energy consumption. BMC Geriatr. 2023;23(1):400. Ouchi Y, Rakugi H, Arai H, Akishita M, Ito H, Toba K, et al. Redefining the elderly as aged 75 years and older: Proposal from the Joint Committee of Japan Gerontological Society and the Japan Geriatrics Society. Geriatr Gerontol Int. 2017;17(7):1045–7. Dotson VM, Beydoun MA, Zonderman AB. Recurrent depressive symptoms and the incidence of dementia and mild cognitive impairment. Neurology. 2010;75(1):27–34. Saczynski JS, Beiser A, Seshadri S, Auerbach S, Wolf PA, Au R. Depressive symptoms and risk of dementia. Neurology. 2010;75(1):35–41. Kim K, Jang YJ, Shin J-H, Park MJ, Kim HS, Seong J-K et al. Amyloid deposition and its association with depressive symptoms and cognitive functions in late-life depression: A longitudinal study using amyloid-β PET images and neuropsychological measurements. 2024. Wu KY, Lin KJ, Chen CH, Liu CY, Wu YM, Chen CS, et al. Decreased Cerebral Amyloid-β Depositions in Patients With a Lifetime History of Major Depression With Suspected Non-Alzheimer Pathophysiology. Front Aging Neurosci. 2022;14:857940. Sinclair LI, Mohr A, Morisaki M, Edmondson M, Chan S, Bone-Connaughton A, et al. Is later-life depression a risk factor for Alzheimer’s disease or a prodromal symptom: a study using post-mortem human brain tissue? Alzheimers Res Ther. 2023;15(1):153. Pachana NA, Brilleman SL, Dobson AJ. Reporting of life events over time: methodological issues in a longitudinal sample of women. Psychol Assess. 2011;23(1):277–81. Additional Declarations No competing interests reported. Supplementary Files 241023Additionalfile1.docx 241023Additionalfile2.docx 241023Additionalfile3.docx 241023Additionalfile4.xlsx Cite Share Download PDF Status: Published Journal Publication published 17 Mar, 2025 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Revision requested 18 Nov, 2024 Editor assigned by journal 15 Nov, 2024 Submission checks completed at journal 15 Nov, 2024 First submitted to journal 15 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5458019","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":379374702,"identity":"9f47dda2-00ba-4377-a535-952c90ea2a6f","order_by":0,"name":"Yoo Jin Jang","email":"","orcid":"","institution":"Samsung Medical Center, Sungkyunkwan University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yoo","middleName":"Jin","lastName":"Jang","suffix":""},{"id":379374703,"identity":"c61f6add-a31d-40f6-b034-6655f8413679","order_by":1,"name":"Min-Ji Kim","email":"","orcid":"","institution":"Samsung Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Min-Ji","middleName":"","lastName":"Kim","suffix":""},{"id":379374704,"identity":"0e8885f2-df30-48d5-8eca-22e8239aa251","order_by":2,"name":"Young Kyung Moon","email":"","orcid":"","institution":"Veteran Health Service Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Young","middleName":"Kyung","lastName":"Moon","suffix":""},{"id":379374705,"identity":"82912fbb-39f5-4046-be25-8f291a0a8c23","order_by":3,"name":"Shinn-Won Lim","email":"","orcid":"","institution":"Samsung Advanced Institute for Health Sciences \u0026 Technology (SAIHST), Sungkyunkwan University","correspondingAuthor":false,"prefix":"","firstName":"Shinn-Won","middleName":"","lastName":"Lim","suffix":""},{"id":379374706,"identity":"a836c749-901f-4c20-9875-5c63869a556e","order_by":4,"name":"Doh Kwan Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYHACxoMNBgxyDDxsIA4zcXpAWoxJ1cLAkNhAtBZz9jMGB2cUbEuf33MsTYKhwjqxgZAWy54cg4MbDG7nbjjbdkyC4Uw6YS0GB4BaHoC08LO3STC2HSZCy/k3YC3p8v0gLf+I0XID4rAEBpDDGBuI0GI541nBwRkGtw03nDmWbJFwLN2YoBZz/uSND3v+3JaX70kzvPGhxlqWsMNQeAmElGNqGQWjYBSMglGADQAAYLFE2gUHAw4AAAAASUVORK5CYII=","orcid":"","institution":"Samsung Medical Center, Sungkyunkwan University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Doh","middleName":"Kwan","lastName":"Kim","suffix":""}],"badges":[],"createdAt":"2024-11-15 06:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5458019/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5458019/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-025-06683-w","type":"published","date":"2025-03-17T15:57:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":71805871,"identity":"a9ec5895-680f-45a8-9575-1a8453002229","added_by":"auto","created_at":"2024-12-18 17:32:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1284684,"visible":true,"origin":"","legend":"\u003cp\u003eHazard Ratio for Alzheimer’s Dementia and Average Conversion Time Based on Onset Age of Depression\u003c/p\u003e\n\u003cp\u003eHazard ratios (HRs) for Alzheimer’s dementia (AD) according to the onset age of depression in the univariable analysis, along with the average months of conversion to AD. The solid line represents the HR for each onset-age group, with the corresponding confidence intervals displayed as dotted error bars. The grey bars indicate the average months of conversion to AD for each onset-age group. Onset-age groups include onset of depression at \u0026lt;55 years, 55–64 years, 65–74 years, and ≥75 years.\u003c/p\u003e","description":"","filename":"241106Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5458019/v1/3a81ac89697199a8b51ffa46.png"},{"id":71805870,"identity":"a7e83e29-2832-48b3-bdfb-dca122e1fea2","added_by":"auto","created_at":"2024-12-18 17:32:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1067233,"visible":true,"origin":"","legend":"\u003cp\u003eEstimated Alzheimer’s Dementia-Free Survival Curves Based on Onset Age of Depression\u003c/p\u003e\n\u003cp\u003eEstimated Alzheimer’s dementia (AD)-free survival curves based on onset age of depression using Cox proportional hazards regression, adjusted for covariates. The onset age of depression is divided into four categories: \u0026lt;55 years, 55–64 years, 65–74 years, and ≥75 years. The x-axis represents time in months, and the y-axis represents the estimated AD-free survival rate after adjustment for covariates. The covariates were set by male gender, age of 70 years, no response, no family history of depression, no cerebrovascular disease, no chronicity of depression and single depressive episodes. The group with depression onset at ≥75 years shows a markedly lower AD-free survival rate compared to the groups with earlier onset, indicating a higher risk of AD conversion in this latest onset group.\u003c/p\u003e","description":"","filename":"241106Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5458019/v1/311f2907b0b85bf7b007e48f.png"},{"id":79120455,"identity":"d17720ee-45c9-4f1e-9f9a-c8d876e953f5","added_by":"auto","created_at":"2025-03-24 16:08:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3161026,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5458019/v1/0be19845-1a96-4295-9533-144940b03832.pdf"},{"id":71805867,"identity":"dc76283d-77c9-4c58-98f8-e383427a80ce","added_by":"auto","created_at":"2024-12-18 17:32:07","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":23740,"visible":true,"origin":"","legend":"","description":"","filename":"241023Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5458019/v1/8db67ef0586ba68d869d315c.docx"},{"id":71805868,"identity":"fdfcfb4e-9089-4aff-a13d-f927627ca10c","added_by":"auto","created_at":"2024-12-18 17:32:07","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":76072,"visible":true,"origin":"","legend":"","description":"","filename":"241023Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-5458019/v1/f8f1ce821950c3bb17913629.docx"},{"id":71805872,"identity":"356cd1a8-c6d3-4358-a0e7-9ff10a5268a7","added_by":"auto","created_at":"2024-12-18 17:32:08","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":18472,"visible":true,"origin":"","legend":"","description":"","filename":"241023Additionalfile3.docx","url":"https://assets-eu.researchsquare.com/files/rs-5458019/v1/01b268e965e3b1d3c73eb0d8.docx"},{"id":71806793,"identity":"a9d7ab5c-8a67-4645-9f7c-16303382bc62","added_by":"auto","created_at":"2024-12-18 17:40:07","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":43666,"visible":true,"origin":"","legend":"","description":"","filename":"241023Additionalfile4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5458019/v1/c1aa10b26784617e7a9befac.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Changes in dementia risk along with onset age of depression: A longitudinal cohort study of elderly depressed patients","fulltext":[{"header":"Background","content":"\u003cp\u003eA large-than-expected number of patients with depression have converted to Alzheimer's dementia (AD) in real-world settings (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). We previously demonstrated that depression is an independent risk factor for dementia in a nationwide cohort, with an adjusted hazard ratio (HR) of 2.35 (95% confidence interval [CI] 2.21\u0026ndash;2.49) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Depressive symptoms frequently precede or co-occur with neurodegenerative conditions in many patients with dementia (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Extensive research has explored the link between late-life depression and AD (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR4 CR5 CR6\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e); however, the heterogeneity of late-life depression complicates understanding of the pathways through which depression contributes to dementia risk (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne factor that may explain this heterogeneity is the onset age of depression (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Depression that begins early in life often has a familial history and a stronger genetic predisposition to mood disorders (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), contributing to cognitive dysfunction through mechanisms such as chronic stress, dysregulation of the hypothalamic-pituitary-adrenal axis and neuroinflammation (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In contrast, depression that occurs later in life is thought to result from brain damage (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), and may be an early sign of dementia. A notable example is vascular depression (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), a subtype of late-life depression linked to cerebrovascular disease.\u003c/p\u003e \u003cp\u003eIf depression onset at different ages reflects distinct characteristics and mechanisms, there may be a specific age interval where the risk of dementia significantly diverges. In particular, later-onset depression may signal a higher dementia risk and a shorter time to onset. Despite this rationale, previous studies have typically dichotomized depression onset between ages 55 and 65 without establishing a precise age criterion (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). While prior research has explored the link between late-life depression and dementia, the relationship between depression onset age and dementia risk remains underexplored.\u003c/p\u003e \u003cp\u003eTo address this, we conducted a longitudinal study of a hospital cohort of patients with depression, with up to 22 years of follow-up to examine the relationship between depression onset age and dementia risk. We also compared characteristics between different onset-age groups to explore variations in dementia risk.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eWe screened clinically referred Korean outpatients aged 55 or older who visited a geropsychiatry clinic at a university hospital between June 1995 and January 2012. All participants met the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for major depressive disorder (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eParticipants were included if they were experiencing a current unipolar major depressive episode (based on DSM-IV criteria) and had a baseline 17-item Hamilton Depression Rating Scale (HAM-D) score of at least 15 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Patients scoring below 28/30 on the Korean version of the Mini-Mental State Examination (K-MMSE) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) were excluded due to memory or cognitive impairment. We also excluded individuals with psychotic disorders (e.g., schizophrenia, delusional disorder), bipolar disorder, neurological illnesses (e.g., Parkinson\u0026rsquo;s disease, epilepsy), intellectual developmental disability, major medical conditions, history of alcohol or drug dependence, personality disorders, head trauma with loss of consciousness, malignancy, abnormal baseline laboratory findings, or unstable psychiatric conditions (e.g., recent suicide attempt during the current episode).\u003c/p\u003e \u003cp\u003eThe final analyses included 251 participants with late-life depression who met the inclusion criteria. The study was approved by the ethics review board of Samsung Medical Center (IRB No. 1999-10-14), and written informed consent was obtained from all participants.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy protocol\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eStudy protocol\u003c/div\u003e \u003cp\u003eThis study was conducted in a naturalistic clinical setting, building on our previous research on antidepressant responses in major depression (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). All participants underwent a structured research interview using the Samsung Psychiatric Evaluation Schedule (SPES) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The SPES collected data on psychiatric symptoms, cognitive screening, comorbid physical diagnoses (hypertension, diabetes mellitus, dyslipidemia, cardiac disease, and cerebrovascular disease), and psychosocial factors (age, sex, onset age of depression, duration of current episode, number of depressive episodes, family history of depression, and initial HAM-D score). Each diagnostic interview involved the patient and at least one family member. A board-certified psychiatrist confirmed all diagnoses using SPES, clinical observations, and medical records. Peripheral blood samples were collected at baseline for apolipoprotein E (ApoE) genotyping and plasma biomarker analyses.\u003c/p\u003e \u003cp\u003eParticipants were followed up every three months until December 31, 2023, or until dementia onset, patient death, or the end of the follow-up period. The K-MMSE was administered annually, and if cognitive decline was reported by the patient, caregivers, or clinician, we performed further neuropsychological assessments, brain magnetic resonance imaging (MRI), and laboratory tests. Neuropsychological assessments included the K-MMSE, clinical dementia rating (CDR) scale (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), Seoul neuropsychological screening battery-dementia version (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), Seoul-activities of daily living (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), Seoul-instrumental activities of daily living (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), Korean version of the neuropsychiatric inventory (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), and Korean version of the geriatric depression scale (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). All tests were repeated annually during the follow-up period of up to 22 years. Brain MRI results were interpreted by board-certified neuroradiologists and served as an auxiliary measure to differentiate other diseases that may cause dementia syndromes. To ensure clarity in clinical diagnosis, we excluded patients exhibiting signs of degenerative non-Alzheimer\u0026rsquo;s disease dementia, including Parkinsonian features or behavioral and personality changes. At our geropsychiatry clinic, inter-observer diagnostic reliability for distinguishing between AD and non-AD was 91.4% (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eOnset age of depression\u003c/h3\u003e\n\u003cp\u003eAt enrollment, participants reported the age of their first depressive episode, primarily based on patient and caregiver recall, and cross-referenced with medical records when available. We hypothesized that depression onset at different life stages may exhibit distinct characteristics and arise from different mechanisms (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), with a specific age interval where dementia risk diverges. To identify this potential inflection point, we categorized the onset age of depression into 10-year intervals and calculated AD risks for each group. Participants were categorized into four groups based on the age of their first depressive episode: 54 years or earlier, 55 to 64 years, 65 to 74 years, and 75 years or later.\u003c/p\u003e\n\u003ch3\u003eCharacteristics of depression\u003c/h3\u003e\n\u003cp\u003eBaseline clinical data on depression were collected at enrollment through interviews, with additional information gathered during follow-up. This included a family history of depression, multiple tendency, chronicity of depression, and comorbid medical conditions (e.g., hypertension, diabetes, dyslipidemia, cardiac disease, cerebrovascular disease). Patients with three or more lifetime depressive episodes were classified as having multiple tendencies (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), while chronicity of depression was defined as episodes lasting 24 months or longer at any point in the patient\u0026rsquo;s life (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). During follow-up, antidepressant treatment response and remission were assessed using the HAM-D score. The response was defined as a 50% or greater reduction in the HAM-D score at six weeks, while remission was defined as a HAM-D score of 7 or lower at twelve weeks of treatment (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eConversion to AD\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was conversion to AD as defined by the DSM-IV. Participants with a CDR score greater than 1 had their diagnoses confirmed by a clinician using DSM-IV criteria, neuropsychological testing, and impairments in activities of daily living. Probable AD was diagnosed according to the National Institute of Neurological and Communicative Diseases and the Stroke-Alzheimer\u0026rsquo;s Disease and Related Disorders Association criteria (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Participants with newly diagnosed dementia underwent annual follow-up examinations to confirm dementia status and subtype, with the date of dementia onset recorded as the first confirmed diagnosis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBiomarkers of AD\u003c/h2\u003e \u003cp\u003eAt baseline, we measured the ApoE4 genotype and plasma levels of amyloid-beta 40 (Aβ40), amyloid-beta 42 (Aβ42), total Tau, and Interleukin-1β (IL-1β) to assess their predictive value for future dementia risk, as these biomarkers are relevant to AD (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Notably, IL-1β has been associated with AD development in patients with depression (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Due to the significant time elapsed since cohort recruitment, only 68 usable blood specimens were available, collected at enrollment rather than at the time of AD diagnosis. Despite this limitation, these biomarkers can provide predictive value for AD risk, as pathological changes often begin decades before clinical symptoms appear (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). While this analysis is constrained and exploratory, it serves as a preliminary investigation to inform future studies. Further details on the biomarker measurement methods are provided in the Additional Material (see Additional file 1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC), with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Clinical and demographic characteristics of participants were presented as categorical variables (frequencies and proportions) or continuous variables (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation [SD]). Univariable Cox proportional hazards regression was used to estimate HRs and 95% CIs for depression onset age, as well as other clinical and demographic characteristics. Multivariable Cox proportional hazards regression assessed AD conversion risk based on depression onset age, adjusting for variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the univariable analysis. The proportional hazard assumption was verified using Schoenfeld residuals, and collinearity was evaluated with the variance inflation factor to ensure independent contributions of predictors. Bonferroni's correction was applied to account for multiple comparisons among the four depression-onset-age groups. Cross-sectional comparisons between onset-age groups were conducted using the Wilcoxon rank-sum test for non-normally distributed continuous variables and Fisher's exact test or chi-square test for categorical variables, as appropriate.\u003c/p\u003e \u003cp\u003eIn a subset with available plasma biomarker data to evaluate their association with dementia risk, univariable and multivariable Cox proportional hazards regression analyses were performed. To choose the variables in the multivariable model, forward stepwise variable selection with entry and exit criteria of 0.05 was employed and the adequate number of variables was limited to 2 to minimize overfitting.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eParticipants characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the baseline clinical and demographic characteristics of participants, along with the univariable Cox proportional hazard regression results. Among the 251 participants, 75 (29.88%) converted to AD during the follow-up period. Age was significantly associated with a higher risk of AD conversion, with participants who converted being older (71.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.92 years) than those who did not (69.64\u0026thinsp;\u0026plusmn;\u0026thinsp;6.93 years) (HR, 1.09; 95% CI, 1.05\u0026ndash;1.13; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Furthermore, participants who responded to antidepressant treatment had an increased risk of AD conversion (HR, 2.40; 95% CI, 1.37\u0026ndash;4.18; p\u0026thinsp;=\u0026thinsp;0.0021). A family history of depression was linked to a reduced risk of AD conversion (HR, 0.38; 95% CI, 0.17\u0026ndash;0.83; p\u0026thinsp;=\u0026thinsp;0.0158), while those with a multiple tendency (three or more lifetime depressive episodes) had a lower risk of conversion (HR, 0.56; 95% CI, 0.32\u0026ndash;0.97; p\u0026thinsp;=\u0026thinsp;0.0390). Chronicity of depression, defined as episodes lasting 24 months or longer, was associated with a higher risk (HR, 1.85; 95% CI, 1.16\u0026ndash;2.96; p\u0026thinsp;=\u0026thinsp;0.0101). In addition, participants with cerebrovascular disease exhibited a significantly higher risk of AD conversion (HR, 2.59; 95% CI, 1.52\u0026ndash;4.43; p\u0026thinsp;=\u0026thinsp;0.0005). However, the presence of the ApoE4 allele was not significantly linked to AD conversion (HR, 1.27; 95% CI, 0.75\u0026ndash;2.12, p\u0026thinsp;=\u0026thinsp;0.3713).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and Clinical Characteristics of Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eConverted to AD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;251)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo (n\u0026thinsp;=\u0026thinsp;176)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes (n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eBaseline Demographics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e203 (80.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140 (79.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63 (84.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.16 (0.62\u0026ndash;2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6455\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.18\u0026thinsp;\u0026plusmn;\u0026thinsp;6.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.64\u0026thinsp;\u0026plusmn;\u0026thinsp;6.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09 (1.05\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOnset Age of Depression\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e54 Years or Earlier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (22.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (26.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (13.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55 to 64 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (24.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (23.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (25.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.29 (0.89\u0026ndash;5.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65 to 74 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (37.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (38.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (33.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.67 (1.07\u0026ndash;6.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.0310\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75 Years or Later\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (15.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (10.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (28.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.95 (3.41\u0026ndash;23.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharacteristics of Depression\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial HAM-D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.52\u0026thinsp;\u0026plusmn;\u0026thinsp;4.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.58\u0026thinsp;\u0026plusmn;\u0026thinsp;4.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.29\u0026thinsp;\u0026plusmn;\u0026thinsp;4.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.96 (0.90\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2820\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162 (64.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103 (58.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59 (78.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.40 (1.37\u0026ndash;4.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.0021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 (35.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (34.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (40.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27 (0.80\u0026ndash;2.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3170\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily History of Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (16.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (19.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (9.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38 (0.17\u0026ndash;0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.0158\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple Tendency*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (25.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (26.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (21.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.56 (0.32\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.0390\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronicity**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (24.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (18.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (38.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.85 (1.16\u0026ndash;2.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.0101\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (45.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (42.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (54.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.42 (0.90\u0026ndash;2.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (18.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (19.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (16.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.13 (0.61\u0026ndash;2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6984\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (10.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (10.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (9.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83 (0.38\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (8.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (7.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (10.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.30 (0.62\u0026ndash;2.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4870\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (11.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (5.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (24.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.59 (1.52\u0026ndash;4.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.0005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBiomarker of AD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eApoE4\u003c/em\u003e allele, 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e199 (79.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144 (81.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55 (73.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eApoE4\u003c/em\u003e allele, 1 or 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (20.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (18.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (26.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27 (0.75\u0026ndash;2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3713\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeuropsychological Test on Diagnosis of AD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.60\u0026thinsp;\u0026plusmn;\u0026thinsp;5.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDR-SB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.70\u0026thinsp;\u0026plusmn;\u0026thinsp;3.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.06\u0026thinsp;\u0026plusmn;\u0026thinsp;3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eHAM-D, 17-item Hamilton Rating Scale for Depression; AD, Alzheimer\u0026rsquo;s dementia; ApoE4, apolipoprotein E4; MMSE, Mini Mental State Examination; CDR, Clinical Dementia Rating; CDR-SB, Sum of Boxes of CDR; GDS, Global Deterioration Scale; CI, confidence interval.\u003c/p\u003e \u003cp\u003e* Multiple tendency refers to patients with three or more lifetime depressive episodes.\u003c/p\u003e \u003cp\u003e** Chronicity is defined as depressive episodes lasting 24 months or longer at any point in the patient's life.\u003c/p\u003e \u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation for continuous variables and as frequency (percentage) for categorical variables. Cox proportional hazards regression analysis was performed to determine the association between demographic and clinical factors and conversion to AD.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between onset age of depression and AD conversion\u003c/h2\u003e \u003cp\u003eIn the univariable analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Additional file 2), participants with depression onset after age 75 exhibited the highest risk of AD conversion (HR, 8.95; 95% CI, 3.41\u0026ndash;23.48; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) compared to those with onset before age 55 (reference group), with a shortest average time to conversion of 40.93 months (SD, 32.15). Participants with onset between ages 65 and 74 had a significantly elevated risk (HR, 2.67; 95% CI, 1.07\u0026ndash;6.66; p\u0026thinsp;=\u0026thinsp;0.0310), with an average time to conversion of 60.07 months (SD, 45.97). The group with onset between ages 55 and 64 showed no significant increase in AD risk (HR, 2.29; 95% CI, 0.89\u0026ndash;5.85; p\u0026thinsp;=\u0026thinsp;0.1068); however, their average time to AD conversion gradually increased to 72.59 months (SD, 54.54), while the reference group had an average of 83.40 months (SD, 57.42).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor the multivariable analysis, covariates were selected based on a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 from the univariable analysis. In addition, sex was defined as a covariate due to its clinical significance, regardless of statistical significance. After adjusting for sex, age, antidepressant treatment response, family history of depression, multiple tendency, chronicity, and cerebrovascular disease, the age of depression onset remained significantly associated with AD conversion risk (p\u0026thinsp;=\u0026thinsp;0.0119, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Participants with depression onset after age 75 had a significantly higher adjusted risk of AD conversion (adjusted HR, 6.07; 95% CI, 1.26\u0026ndash;29.34; p\u0026thinsp;=\u0026thinsp;0.0189) compared to those with onset before age 55. In contrast, onset between ages 65 and 74 showed a non-significant trend toward increased risk (adjusted HR, 1.86; 95% CI, 0.57\u0026ndash;6.06; p\u0026thinsp;=\u0026thinsp;0.6371). Onset between ages 55 and 64 was not significantly associated with AD conversion (adjusted HR, 1.96; 95% CI, 0.72\u0026ndash;5.35; p\u0026thinsp;=\u0026thinsp;0.3295). The estimated survival curves from the multivariable Cox proportional hazards model, adjusted for male gender, age of 70 years, no treatment response, no family history of depression, no cerebrovascular disease, no chronicity of depression, and no multiple tendency, are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Participants with depression onset at age 75 or later had the lowest AD-free survival rate, indicating the highest risk of AD conversion. Conversely, participants with depression onset before age 55 exhibited the highest AD-free survival rate. Those with depression onset between ages 55 and 74 exhibited intermediate survival rates, with survival curves for the 55\u0026ndash;64 and 65\u0026ndash;74 age groups closely aligned, indicating similar risk profiles.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between Onset Age of Depression and Alzheimer's Dementia Risk\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMultivariable Analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eadjusted HR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnset Age of Depression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0119\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e54 Years or Earlier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55 to 64 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.96 (0.72\u0026ndash;5.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65 to 74 Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.86 (0.57\u0026ndash;6.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6371\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75 Years or Later\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.07 (1.26\u0026ndash;29.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.0189\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32 (0.68\u0026ndash;2.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03 (0.97\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3623\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.87 (1.03\u0026ndash;3.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.0403\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily History of Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.54 (0.24\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple Tendency*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94 (0.48\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronicity**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.15 (1.31\u0026ndash;3.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.0023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.50 (0.83\u0026ndash;2.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1795\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eHR, hazard ratio; CI, confidence interval. \u003c/p\u003e \u003cp\u003e* Multiple tendency refers to patients with three or more lifetime depressive episodes.\u003c/p\u003e \u003cp\u003e** Chronicity is defined as depressive episodes lasting 24 months or longer at any point in the patient's life.\u003c/p\u003e \u003cp\u003eCox proportional hazard regression analysis was used to determine the association between the onset age of depression and conversion to AD after adjusting for covariates. Covariates were selected based on a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the univariable analysis.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eComparison of onset age before 55 and after 75\u003c/h2\u003e \u003cp\u003eWe specifically compared patients with depression onset before age 55 and those with onset at or after age 75, as these groups exhibited the most significant differences in dementia risk. Including other onset-age groups that did not show significant differences could dilute the effects of depression onset age on dementia risk; therefore, we excluded them to ensure clearer distinctions between the groups with the most pronounced risk differences.\u003c/p\u003e \u003cp\u003eParticipants with depression onset at or after 75 were significantly older (median age, 79.00 years; interquartile range [IQR], [76.00, 81.00]) than those with onset before age 55 (median age, 64.00 years; IQR, [59.00, 71.00]; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Initial depression severity was lower in the group with onset at or after age 75 (median HAM-D score, 18.00; IQR, [15.50, 20.00]) compared to the group with onset before age 55 (median HAM-D score, 19.50; IQR, [17.00, 23.00]; p\u0026thinsp;=\u0026thinsp;0.0264). A greater proportion of participants with depression onset at or after age 75 responded to treatment (75.00% vs. 52.63%; p\u0026thinsp;=\u0026thinsp;0.0256). Furthermore, 64.91% of participants with depression onset before age 55 had a higher prevalence of multiple depressive episodes, experiencing three or more lifetime episodes. In comparison, only 2.50% of those with onset at or after age 75 had this history (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Regarding comorbidities, hypertension (55.00% vs. 29.82%; p\u0026thinsp;=\u0026thinsp;0.0128) and cerebrovascular disease (25.00% vs. 3.51%; p\u0026thinsp;=\u0026thinsp;0.0031) were more common in the group with depression onset at or after age 75.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between biomarkers and AD conversion\u003c/h2\u003e \u003cp\u003eAn Additional table file presents the results of both univariable and multivariable analyses assessing the association between biomarkers and the risk of AD conversion in 68 participants (see Additional file 3). Due to the smaller sample size in the subset, we simplified the classification to two groups\u0026mdash;depression onset before age 75 and after age 75\u0026mdash;aligning with the main analysis findings, instead of using the original four groups. The analysis indicated that participants with depression onset after age 75 had a significantly higher risk of AD conversion compared to those with onset before age 75, consistent with the main analysis. In the univariable analysis, the HR for the after-75-group was 3.90 (95% CI: 1.16\u0026ndash;13.08; p\u0026thinsp;=\u0026thinsp;0.0278), which further increased in the multivariable analysis to an adjusted HR of 7.39 (95% CI: 1.87\u0026ndash;29.18; p\u0026thinsp;=\u0026thinsp;0.0043).\u003c/p\u003e \u003cp\u003eIn the univariable analysis, Aβ42 levels were lower in those who converted to AD (HR, 0.83; 95% CI, 0.69\u0026ndash;0.99; p\u0026thinsp;=\u0026thinsp;0.0432). No significant associations were found for ApoE4 allele status, Aβ40 levels, Aβ42/Aβ40 ratio, or total Tau protein levels. Elevated plasma levels of the inflammatory marker IL-1β were strongly associated with an increased risk of AD conversion (log-transformed; HR, 5.48; 95% CI, 2.06\u0026ndash;14.60; p\u0026thinsp;=\u0026thinsp;0.0007). After adjusting for depression onset after age 75, this association strengthened, yielding an adjusted HR of 8.68 (95% CI: 2.83\u0026ndash;26.63; p\u0026thinsp;=\u0026thinsp;0.0002).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this longitudinal cohort study, we identified significant changes in dementia hazard ratios based on the age of depression onset. Patients with depression onset at age 75 or later had a significantly higher risk of developing AD and experienced a faster dementia progression compared to those with onset before age 55. Individuals with depression onset after age 75 had less severe depressive symptoms and a higher prevalence of hypertension and cerebrovascular disease than those with depression onset before age 55.\u003c/p\u003e \u003cp\u003eOur results align with findings from previous studies reporting an increased likelihood of dementia in patients with late-life depression (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). The onset age of depression significantly influences dementia risk. Depression occurring later in life appeared to signal impending dementia, with a higher risk and shorter time to AD conversion (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This increased risk may be due to an \"age-by-disease interaction effect,\" where the impact of depression on dementia varies by age (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In other words, depression later in life may have a more detrimental impact on cognitive decline. However, our cohort was limited to patients aged 55 and older, meaning most of our comparison group (onset before age 55) consisted of individuals with early-onset 'recurrent' depression, some of whom may have had recurrent episodes after the age of 75. Even after adjusting for age, the association between depression onset age and dementia risk remained significant, suggesting that the age-by-disease interaction alone does not fully account for our findings. If depression in older adults had a greater impact on cognitive function regardless of initial onset, we would expect recurrent depression later in life to be a significant dementia risk factor. However, our multivariable analysis did not support this, as late-life recurrent depression (indicated by \"multiple tendency\") did not independently increase dementia risk beyond the age of depression onset (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA plausible explanation is that depression onset after age 75 may result from pre-existing brain damage or neurodegeneration. The higher prevalence of vascular-related comorbidities, such as hypertension and cerebrovascular disease, supports this hypothesis (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In our previous nationwide cohort study, we observed an additive interaction between depression and cerebrovascular disease in relation to AD risk (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Furthermor, mounting biological evidence suggests that cerebrovascular disease (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) and hypertension (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e) contribute to increased amyloid burden in the brain, potentially linking late-life depression to Alzheimer-related pathology. Future research should examine how vascular damage accelerates neurodegeneration and triggers depressive symptoms, focusing on the interplay between vascular comorbidities and Alzheimer's disease-related pathology.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Depression Onset Age Before 55 and After 75\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eOnset Age of Depression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;55 Years (n\u0026thinsp;=\u0026thinsp;57)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;75 Years (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline Demographics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (84.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (72.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1605\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.00 [59.00, 71.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.00 [76.00, 81.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharacteristics of Depression\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInitial HAM-D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.50 [17.00, 23.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.00 [15.50, 20.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0264\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (52.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (75.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0256\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (35.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (35.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9929\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily History of Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (24.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (12.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1406\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple Tendency*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (64.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronicity**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (26.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (12.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (29.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (55.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0128\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (12.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (12.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0000\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (7.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (12.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4814\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2262\u0026dagger;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (3.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (25.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0031\u0026dagger;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBiomarkers of AD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eApoE4\u003c/em\u003e allele, 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (80.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (82.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eApoE4\u003c/em\u003e allele, 1 or 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (19.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (17.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eHAM-D, 17-item Hamilton Rating Scale for Depression; AD, Alzheimer\u0026rsquo;s dementia; ApoE4, apolipoprotein E4.\u003c/p\u003e \u003cp\u003e* Multiple tendency refers to patients with three or more lifetime depressive episodes.\u003c/p\u003e \u003cp\u003e** Chronicity is defined as depressive episodes lasting 24 months or longer at any point in the patient's life.\u003c/p\u003e \u003cp\u003eData are presented as median [first quartile, third quartile] for continuous variables, and as frequency (percentage) for categorical variables. Wilcoxon rank sum test was used to compare continuous variables. Fisher's exact test(\u0026dagger;) or chi-square test was used for comparisons of categorical variables, depending on expected frequency distributions.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOur study suggests that age 75 may serve as an important indicator for distinguishing between early- and late-onset depression, as dementia risk increases significantly beyond this age (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). As the global population ages, researchers have increasingly subdivided the older population into more specific age groups. Individuals aged 75 and older are often referred to as the \"old-old,\" while those aged 65 to 74 are considered the \"young-old\" (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). The old-old group experiences more chronic health conditions, functional impairments, and cognitive decline compared to the young-old (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Although age 65 is typically used to define older adulthood, our study supports the evidence that significant neuropsychiatric changes, including increased AD risk, may occur around age 75.\u003c/p\u003e \u003cp\u003eIn our cohort, depression onset after age 75 was characterized by milder depressive symptoms, fewer recurrent episodes, and a higher prevalence of hypertension and cerebrovascular disease compared to onset before age 55 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). These findings are consistent with previous studies using a lower threshold of 60 years, which also linked later-onset depression to older age, less severe depression, and poorer cognitive functioning (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Although we used a higher threshold of 75 years, the findings were comparable. However, our results diverge from previous reports suggesting that severe, recurrent depression is a significant contributor to dementia risk (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). This discrepancy may arise from not accounting for the onset age of depression. For instance, Dotson \u003cem\u003eet al\u003c/em\u003e. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) reported a mean depression onset in the mid-to-late 50s, with likely few patients whose depression began after age 75. Since depression onset after age 75 constitutes a very small subset of the overall depression population, its unique characteristics may not have been fully captured in studies focusing on earlier-onset cases. This could help explain why depressive symptoms in later life might have a different association with dementia risk compared to earlier-onset depression, further emphasizing the need for onset-age-specific analysis in understanding the link between depression and dementia.\u003c/p\u003e \u003cp\u003eGiven the distinct characteristics and minority status of depression onset after age 75, our findings suggest that the factors influencing dementia risk may differ between those with depression before and after this age. Although analyzing the longitudinal association with dementia risk in both groups was not within the scope of our study, exploring these differences could offer valuable insights into group-specific dementia risk factors. In our cohort, chronic depression\u0026mdash;defined as depressive episodes lasting 2 years or more\u0026mdash;was linked to an increased risk of AD, even after adjusting for covariates including age of depression onset (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). While depressive symptoms were less severe in the high-risk group with depression onset after age 75, chronic depressive episodes may still contribute to dementia risk in the earlier-onset group, which comprised 84% of the cohort. Future research should focus on identifying distinct risk factors through longitudinal studies that examine the pathways linking depression and dementia in individuals with depression onset before and after age 75.\u003c/p\u003e \u003cp\u003eIn the subset analysis, established AD biomarkers such as Aβ42/Aβ40 ratio, total Tau, and ApoE status were not significantly associated with AD risk. Howeveer, the inflammatory marker IL-1β was a significant factor promoting AD conversion, regardless of depression onset age (see Additional file 3). These results suggest that dementia following depression may develop through mechanisms distinct from those seen in non-depressed populations, as previously suggested (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Our findings indicate that the inflammatory process, marked by elevated IL-1β, may drive dementia pathogenesis across the broader depression cohort. However, given the limitation of sample size and the timing of biomarker collection, these findings should be interpreted cautiously and considered preliminary groundwork for future research.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has certain limitations that should be acknowledged. First, the naturalistic setting, which lacked a healthy control group, limited our ability to confirm the specific association between depression and dementia. Without a non-depressed comparison group, it was difficult to isolate the direct impact of depression on AD risk. However, rather than using healthy controls, we compared depression onset at age 75 or later with depression onset before age 55 to explore whether later-onset depression was more closely linked to AD conversion. This approach highlighted depression onset after age 75 as a potential dementia indicator, supporting the hypothesis that specific phenotypes of late-life depression are more strongly associated with AD progression. Furthermor, the naturalistic setting allowed for the observation of real-world clinical outcomes, enhancing external validity by providing valuable insights into how depression and AD interact in typical clinical practice.\u003c/p\u003e \u003cp\u003eSecond, the cohort was drawn from a single geropsychiatry clinic, consisting of clinically referred patients, which may have introduced selection bias, limiting the generalizability of the findings to community-dwelling older individuals with depression. Furthermore, all participants were of Korean descent, and unique genetic, cultural, or environmental factors may have influenced the relationship between depression and dementia. Therefore, caution is needed when applying these findings to other ethnic groups or settings.\u003c/p\u003e \u003cp\u003eThird, our use of stringent baseline cognitive criteria (K-MMSE\u0026thinsp;\u0026ge;\u0026thinsp;28) may have selectively included individuals with higher cognitive reserve. This could introduce bias especially in older participants, as cognitive decline is more common with aging. Consequently, we may have overrepresented individuals with exceptionally preserved cognition for their age. However, we employed these stringent criteria to isolate the specific effects of depression on AD risk. While this approach may have limited the generalizability of our findings, it was necessary to establish a clear temporal relationship between depression and cognitive decline.\u003c/p\u003e \u003cp\u003eFourth, recall bias may have affected the accuracy of the reported age of depression onset, potentially leading to misclassification within onset age categories. This could influence the observed relationship between depression onset and dementia risk. To mitigate this, we cross-referenced patient and caregiver reports with available medical records to enhance data accuracy. Moreover, we grouped the onset age into broad 10-year categories (\u0026le;\u0026thinsp;54 years, 55\u0026ndash;64, 65\u0026ndash;74, and \u0026ge;\u0026thinsp;75 years), which likely reduced recall bias, as individuals tend to more reliably recall the approximate decade of their depression onset (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLastly, while plasma biomarkers are less invasive and more affordable than cerebrospinal fluid biomarkers or positron emission tomography imaging, they may be less precise for detecting Alzheimer\u0026rsquo;s pathology. Plasma biomarkers can be influenced by peripheral factors, potentially reducing their sensitivity and specificity compared to cerebrospinal fluid measures (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). This limitation may have impacted the accuracy of our findings regarding the biological markers associated with AD risk.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study demonstrates that depression occurring after age 75 is associated with the highest risk of AD conversion and the shortest time to dementia onset. Depression that begins after age 75 is more closely linked to vascular comorbidities, whereas depression with onset before age 55 is associated with severe, recurrent depression. The physiological pathways leading to AD in depressed individuals may differ from those without prior depression. Further research is needed to clarify these mechanisms and explore targeted interventions to mitigate dementia risk in these populations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAD \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Alzheimer\u0026apos;s dementia\u003c/p\u003e\n\u003cp\u003eHR \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Hazard ratio\u003c/p\u003e\n\u003cp\u003eCI \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Confidence interval\u003c/p\u003e\n\u003cp\u003eDSM-IV \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition\u003c/p\u003e\n\u003cp\u003eHAM-D \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Hamilton Depression Rating Scale\u003c/p\u003e\n\u003cp\u003eK-MMSE \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Korean Mini-Mental State Examination\u003c/p\u003e\n\u003cp\u003eApoE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Apolipoprotein E\u003c/p\u003e\n\u003cp\u003eMRI \u0026nbsp; \u0026nbsp;\u0026nbsp;Magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eCDR \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Clinical dementia rating\u003c/p\u003e\n\u003cp\u003eA\u0026beta;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Amyloid-beta\u003c/p\u003e\n\u003cp\u003eIL \u0026nbsp; \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Interleukin\u003c/p\u003e\n\u003cp\u003eSD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Standard deviation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe protocol was approved by the ethics review board of the Samsung Medical Center (IRB No. 1999-10-14). All research procedures were performed in accordance with relevant guidelines. Signed informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the National Research Foundation funded by the Korean government (Ministry of Science and ICT; 2020R1A2C2101276 to DKK and 2022R1A2C1092186 to SWL), Republic of Korea.\u003c/p\u003e\n\u003cp\u003eThe authors report no biomedical financial interests or potential conflicts of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eRole of funding source\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe funders had no role in study design, data collection, data analysis, data interpretation, writing of the report, or the decision to submit this paper for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset supporting the conclusions of this article is included within the article and its additional files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor contribution\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYJJ, MJK, YKM, SWL, and DKK have full access to all data of this study and take responsibility for the integrity of the data and accuracy of the data analysis. YJJ, MJK, YKM, SWL, and DKK conceived and designed the study. MJK performed statistical analyses. YJJ drafted the manuscript. SWL and DKK supervised the entire study. All authors contributed to the interpretation of the data and have read and approved the final draft for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Editage (www.editage.co.kr) for the English language editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHerbert J, Lucassen PJ. Depression as a risk factor for Alzheimer's disease: Genes, steroids, cytokines and neurogenesis - What do we need to know? Front Neuroendocrinol. 2016;41:153\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJang YJ, Kang C, Myung W, Lim SW, Moon YK, Kim H, et al. 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Reporting of life events over time: methodological issues in a longitudinal sample of women. Psychol Assess. 2011;23(1):277\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Depression in late-life, Onset age of depression, Dementia, Alzheimer’s disease, Alzheimer’s Dementia","lastPublishedDoi":"10.21203/rs.3.rs-5458019/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5458019/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDepression in late-life is linked to an increased risk of Alzheimer's dementia (AD), with the risk potentially varying based on the onset age of depression. Previous research typically dichotomized depression onset age between 55 and 65 years; however, the specific age at which depression onset increases AD risk in older adults remains unclear. In this study, we aimed to investigate the relationship between depression onset age and AD risk and compare characteristics between different onset age groups.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA longitudinal cohort of 251 elderly patients diagnosed with major depressive disorder was followed for up to 22 years. Participants were categorized into four groups based on depression onset age: \u0026le; 54 years, 55\u0026ndash;64, 65\u0026ndash;74, and \u0026ge;\u0026thinsp;75 years. Annual cognitive assessments were conducted using the Korean Mini-Mental State Examination, with further neuropsychological testing when cognitive decline was suspected. Cox proportional hazards models were used to assess AD conversion risk across groups, adjusting for covariates.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDuring follow-up, 75 patients (29.88%) converted to AD. Depression onset after age 75 was significantly associated with a higher risk of AD conversion (hazard ratio [HR], 8.95; 95% confidence interval [CI], 3.41\u0026ndash;23.48; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and a shorter time to conversion compared to onset before age 55 (40.93 vs. 83.40 months). After adjusting for covariates, depression onset after age 75 remained significantly associated with AD conversion (adjusted HR, 6.07; 95% CI, 1.26\u0026ndash;29.34; p\u0026thinsp;=\u0026thinsp;0.0189). This group also had milder depressive symptoms and a higher prevalence of hypertension and cerebrovascular disease than those with depression onset before age 55.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eDepression onset after age 75 is strongly associated with an increased risk of AD and a shorter time to dementia onset. Individuals with depression onset after age 75 appear more closely linked to vascular comorbidities, while those with depression onset before age 55 are characterized by severe and recurrent depressive episodes. The mechanisms leading to AD in individuals with depression may differ from those without prior depression.\u003c/p\u003e\u003ch2\u003eTrial registration:\u003c/h2\u003e \u003cp\u003eThe study is registered (NCT01237275, 1994-10-14, Development of A Technique to Predict Antidepressant Responsiveness in Depressive Patients) in ClinicalTrials.gov.\u003c/p\u003e","manuscriptTitle":"Changes in dementia risk along with onset age of depression: A longitudinal cohort study of elderly depressed patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-18 17:32:02","doi":"10.21203/rs.3.rs-5458019/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-18T09:48:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-16T00:46:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-16T00:45:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2024-11-15T06:08:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e436ba55-42f5-4149-a7ad-9b80e90f3ba0","owner":[],"postedDate":"December 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-24T16:01:36+00:00","versionOfRecord":{"articleIdentity":"rs-5458019","link":"https://doi.org/10.1186/s12888-025-06683-w","journal":{"identity":"bmc-psychiatry","isVorOnly":false,"title":"BMC Psychiatry"},"publishedOn":"2025-03-17 15:57:36","publishedOnDateReadable":"March 17th, 2025"},"versionCreatedAt":"2024-12-18 17:32:02","video":"","vorDoi":"10.1186/s12888-025-06683-w","vorDoiUrl":"https://doi.org/10.1186/s12888-025-06683-w","workflowStages":[]},"version":"v1","identity":"rs-5458019","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5458019","identity":"rs-5458019","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}