Apolipoprotein E epsilon 4 genotype and a physically active lifestyle in late life: analysis of gene-environment interaction for the risk of dementia and Alzheimer's disease dementia.

BACKGROUND: As physical activity may modify the effect of the apolipoprotein E (APOE) ε4 allele on the risk of dementia and Alzheimer's disease (AD) dementia, we tested for such a gene-environment interaction in a sample of general practice patients aged ⩾75 years. METHOD: Data were derived from follow-up waves I-IV of the longitudinal German study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe). The Kaplan-Meier survival method was used to estimate dementia- and AD-free survival times. Multivariable Cox regression was used to assess individual associations of APOE ε4 and physical activity with risk for dementia and AD, controlling for covariates. We tested for gene-environment interaction by calculating three indices of additive interaction. RESULTS: Among the randomly selected sample of 6619 patients, 3327 (50.3%) individuals participated in the study at baseline and 2810 (42.5%) at follow-up I. Of the 2492 patients without dementia included at follow-up I, 278 developed dementia (184 AD) over the subsequent follow-up interval of 4.5 years. The presence of the APOE ε4 allele significantly increased and higher physical activity significantly decreased risk for dementia and AD. The co-presence of APOE ε4 with low physical activity was associated with higher risk for dementia and AD and shorter dementia- and AD-free survival time than the presence of APOE ε4 or low physical activity alone. Indices of interaction indicated no significant interaction between low physical activity and the APOE ε4 allele for general dementia risk, but a possible additive interaction for AD risk. CONCLUSIONS: Physical activity even in late life may be effective in reducing conversion to dementia and AD or in delaying the onset of clinical manifestations. APOE ε4 carriers may particularly benefit from increasing physical activity with regard to their risk for AD.

A hierarchy of predictors for dementia-free survival in old-age: results of the AgeCoDe study.

OBJECTIVE: Progression from cognitive impairment (CI) to dementia is predicted by several factors, but their relative importance and interaction are unclear. METHOD: We investigated numerous such factors in the AgeCoDe study, a longitudinal study of general practice patients aged 75+. We used recursive partitioning analysis (RPA) to identify hierarchical patterns of baseline covariates that predicted dementia-free survival. RESULTS: Among 784 non-demented patients with CI, 157 (20.0%) developed dementia over a follow-up interval of 4.5 years. RPA showed that more severe cognitive compromise, revealed by a Mini-Mental State Examination (MMSE) score < 27.47, was the strongest predictor of imminent dementia. Dementia-free survival time was shortest (mean 2.4 years) in such low-scoring patients who also had impaired instrumental activities of daily living (iADL) and subjective memory impairment with related worry (SMI-w). Patients with identical characteristics but without SMI-w had an estimated mean dementia-free survival time of 3.8 years, which was still shorter than in patients who had subthreshold MMSE scores but intact iADL (4.2-5.2 years). CONCLUSION: Hierarchical patterns of readily available covariates can predict dementia-free survival in older general practice patients with CI. Although less widely appreciated than other variables, iADL impairment appears to be an especially noteworthy predictor of progression to dementia.

Age of major depression onset, depressive symptoms, and risk for subsequent dementia: results of the German study on Ageing, Cognition, and Dementia in Primary Care Patients (AgeCoDe).

BACKGROUND: Whether late-onset depression is a risk factor for or a prodrome of dementia remains unclear. We investigated the impact of depressive symptoms and early- v. late-onset depression on subsequent dementia in a cohort of elderly general-practitioner patients (n = 2663, mean age = 81.2 years). METHOD: Risk for subsequent dementia was estimated over three follow-ups (each 18 months apart) depending on history of depression, particularly age of depression onset, and current depressive symptoms using proportional hazard models. We also examined the additive prediction of incident dementia by depression beyond cognitive impairment. RESULTS: An increase of dementia risk for higher age cut-offs of late-onset depression was found. In analyses controlling for age, sex, education, and apolipoprotein E4 genotype, we found that very late-onset depression (aged ≥ 70 years) and current depressive symptoms separately predicted all-cause dementia. Combined very late-onset depression with current depressive symptoms was specifically predictive for later Alzheimer's disease (AD; adjusted hazard ratio 5.48, 95% confidence interval 2.41-12.46, p < 0.001). This association was still significant after controlling for cognitive measures, but further analyses suggested that it was mediated by subjective memory impairment with worries. CONCLUSIONS: Depression might be a prodrome of AD but not of dementia of other aetiology as very late-onset depression in combination with current depressive symptoms, possibly emerging as a consequence of subjectively perceived worrisome cognitive deterioration, was most predictive. As depression parameters and subjective memory impairment predicted AD independently of objective cognition, clinicians should take this into account.

Assessing cognitive changes in the elderly: reliable change indices for the Mini-Mental State Examination.

OBJECTIVE: The diagnosis of dementia includes evidence of decline in cognitive functioning over time measured by objective cognitive tasks. Normative data for changes adjusted for the impact of socio-demographic factors on cognitive test performance are lacking to interpret changes in Mini-Mental State Examination (MMSE) test scores. METHOD: As part of the German Study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe Study), a sample of 1090 cognitively healthy individuals, aged 75 years and older, was assessed at 1.5-year intervals over a period of 4.5 years using the MMSE. Age- and education-specific Reliable Change Indices (RCIs) were computed. RESULTS: Age and education were significantly associated with MMSE test performance, and gender indicated no impact. Across different age and education subgroups, changes from at least 2 up to 3 points indicated significant (i.e., reliable) changes in MMSE test scores at the 90% confidence level. Furthermore, the calculation of RCIs for individual patients is demonstrated. CONCLUSION: This study provides age- and education-specific MMSE norms based upon RCI methods to interpret cognitive changes in older age groups. The computation of RCI scores improves the interpretation of changes in MMSE test scores by controlling for measurement error, practice effects, or regression to the mean.