DNA methylation-based measures of accelerated biological ageing and the risk of dementia in the oldest-old: a study of the Lothian Birth Cohort 1921.

BACKGROUND: Previous studies have demonstrated an association between DNA methylation-based measures of accelerated ageing and age-related health outcomes and mortality. As a disease closely associated with advancing age, we hypothesized that DNA methylation-based measures of accelerated ageing might be associated with risk for dementia. This study therefore aimed to examine the association between four recognised measures of age acceleration and subsequent dementia. METHODS: Study subjects (n = 488) were members of the Lothian Birth Cohort 1921. Dementia case ascertainment used data from death certificates, electronic hospital records, and clinical reviews. Venous blood samples were taken at baseline, at age 79 years. DNA methylation and measures of epigenetic age were calculated in accordance with Horvath's epigenetic clock tutorial, using the online calculator (https://dnamage.genetics.ucla.edu/). From these values, four measures of accelerated ageing were calculated: extrinsic epigenetic age acceleration (EEAA), intrinsic epigenetic age acceleration (IEAA), AgeAccelPheno and AgeAccelGrim. Competing risk regression models - with death as a competing risk - were performed to examine the association between each measure of accelerated ageing and incident dementia. APOE ɛ4 status, sex, age, smoking status, history of cardiovascular disease, cerebrovascular disease, hypertension, and diabetes were included as covariates. RESULTS: None of the multivariate models revealed a positive association between increased epigenetic age acceleration and dementia risk. Across all included models, never-smoking increased risk for dementia (HR 1.69 [1.06, 2.71], p = 0.03), and having no APOE ɛ4 alleles reduced risk for dementia (HR 0.44 [0.29, 0.67], p < 0.001). CONCLUSIONS: The present study did not demonstrate any consistent association between DNA methylation-based measures of accelerated ageing and dementia in subjects aged over 79 years. Further, larger studies - including separate analyses of dementia subtypes - are required to further investigate the potential association between DNA methylation-based measures of accelerated ageing and dementia.

Physical fitness and dementia risk in the very old: a study of the Lothian Birth Cohort 1921.

BACKGROUND: Previous studies have demonstrated that individual measures of fitness - such as reduced pulmonary function, slow walking speed and weak handgrip - are associated with an increased risk of dementia. Only a minority of participants included in these studies were aged over 80. The aim of this study was therefore to investigate the association between physical fitness and dementia in the oldest old. METHODS: Subjects (n = 488) were enrolled in the Lothian Birth Cohort 1921 and aged 79 at baseline. Dementia cases arising after enrolment were determined using data from death certificates, electronic patient records and clinical reviews. Fitness measures included grip strength, forced expiratory volume in 1 s (FEV1) and walking speed over 6 m, measured at 79 years. Dementia risk associated with each fitness variable was initially determined by logistic regression analysis, followed by Cox regression analysis, where death was considered as a competing risk. APOE ε4 status, age, sex, height, childhood IQ, smoking, history of cardiovascular or cerebrovascular disease, hypertension and diabetes were included as additional variables. Cumulative incidence graphs were calculated using Aalen-Johansen Estimator. RESULTS: Although initial results indicated that greater FEV1 was associated with an increased risk of dementia (OR (odds ratio per unit increase) 1.93, p = 0.03, n = 416), taking into account the competing risk of mortality, none of the fitness measures were found to be associated with dementia; FEV1 (HR (hazard ratio per unit increase) 1.30, p = 0.37, n = 416), grip strength (HR 0.98, p = 0.35, n = 416), walking speed (HR 0.99, p = 0.90, n = 416). The presence of an APOE ɛ4 allele was however an important predictor for dementia (HR 2.85, p < 0.001, n = 416). Cumulative incidence graphs supported these findings, with an increased risk of dementia for APOE ɛ4 carriers compared with non-carriers. While increased FEV1 was associated with reduced risk of death, there was no reduction in risk for dementia. CONCLUSIONS: In contrast to previous studies, this study found that lower fitness beyond age 79 was not a risk factor for subsequent dementia. This finding is not explained by those with poorer physical fitness, who would have been more likely to develop dementia, having died before onset of dementia symptoms.

Risk factors for dementia in the ninth decade of life and beyond: a study of the Lothian birth cohort 1921.

BACKGROUND: With increasing numbers of people surviving beyond eighty years, this section of the population demands attention to reduce the impact of dementia. In order to develop effective preventative strategies, it is essential to understand age-specific risk factor profiles for dementia: do risk factors for dementia in those in their sixties and seventies persist into oldest age? The aims of this study were to determine incident dementia and to investigate the risk profile for dementia from age 79 to 95 years in a well-characterised cohort. METHODS: Participants underwent intelligence testing at age 11 and were followed-up from at 79 years of age. Variables included: age, sex, age 11 IQ, APOE ɛ4, education, diabetes, hypertension, statin use, physical activity at leisure and in occupation, symptoms of depression, height, number of teeth, body mass index, blood pressure, cholesterol and HbA1c. Dementia cases were ascertained from death certificates, electronic patient records and clinical reviews. Logistic regression analysis determined the degree of risk for dementia associated with each variable. Analyses were completed both with and without the physical activity variables due to the significant number of missing data for these variables. RESULTS: Of the eligible cohort, n = 410 participants remained dementia-free and n = 110 had developed probable dementia. When logistic regression analyses contained all variables, complete data was available for n = 234 (n = 48 with dementia). Results demonstrated that positive APOE ɛ4 carrier status (OR: 2.15, 95% CI: 1.04, 4.42) and greater lifetime physical activity (OR: 1.14, 95% CI: 1.02, 1.28) increased the risk for dementia. A reduction in risk for dementia was seen for hypertension (OR: 0.47, 95% CI: 0.23, 0.98). When physical activity variables were excluded, the number with complete data increased to n = 377 (n = 80 with dementia). APOE ɛ4 remained significant (OR: 2.37; 95% CI: 1.37, 4.07), as did hypertension (OR: 0.55; 95% CI: 0.32, 0.93). CONCLUSIONS: Dementia incidence was consistent with expected rates. The risk profile for dementia in this cohort of participants aged 79-95 confirmed previous findings that risk factors differ for those over 79 years. Further evidence is recommended in order that the risk profile for this age group can be accurately determined.

Dementia ascertainment using existing data in UK longitudinal and cohort studies: a systematic review of methodology.

BACKGROUND: Studies investigating the risk factors for or causation of dementia must consider subjects prior to disease onset. To overcome the limitations of prospective studies and self-reported recall of information, the use of existing data is key. This review provides a narrative account of dementia ascertainment methods using sources of existing data. METHODS: The literature search was performed using: MEDLINE, EMBASE, PsychInfo and Web of Science. Included articles reported a UK-based study of dementia in which cases were ascertained using existing data. Existing data included that which was routinely collected and that which was collected for previous research. After removing duplicates, abstracts were screened and the remaining articles were included for full-text review. A quality tool was used to evaluate the description of the ascertainment methodology. RESULTS: Of the 3545 abstracts screened, 360 articles were selected for full-text review. 47 articles were included for final consideration. Data sources for ascertainment included: death records, national datasets, research databases and hospital records among others. 36 articles used existing data alone for ascertainment, of which 27 used only a single data source. The most frequently used source was a research database. Quality scores ranged from 7/16 to 16/16. Quality scores were better for articles with dementia ascertainment as an outcome. Some papers performed validation studies of dementia ascertainment and most indicated that observed rates of dementia were lower than expected. CONCLUSIONS: We identified a lack of consistency in dementia ascertainment methodology using existing data. With no data source identified as a "gold-standard", we suggest the use of multiple sources. Where possible, studies should access records with evidence to confirm the diagnosis. Studies should also calculate the dementia ascertainment rate for the population being studied to enable a comparison with an expected rate.

Predictors of ageing-related decline across multiple cognitive functions.

It is critical to discover why some people's cognitive abilities age better than others'. We applied multivariate growth curve models to data from a narrow-age cohort measured on a multi-domain IQ measure at age 11 years and a comprehensive battery of thirteen measures of visuospatial, memory, crystallized, and processing speed abilities at ages 70, 73, and 76 years (n = 1091 at age 70). We found that 48% of the variance in change in performance on the thirteen cognitive measures was shared across all measures, an additional 26% was specific to the four ability domains, and 26% was test-specific. We tested the association of a wide variety of sociodemographic, fitness, health, and genetic variables with each of these cognitive change factors. Models that simultaneously included all covariates accounted for appreciable proportions of variance in the cognitive change factors (e.g. approximately one third of the variance in general cognitive change). However, beyond physical fitness and possession of the APOE e4 allele, very few predictors were incrementally associated with cognitive change at statistically significant levels. The results highlight a small number of factors that predict differences in cognitive ageing, and underscore that correlates of cognitive level are not necessarily predictors of decline. Even larger samples will likely be required to identify additional variables with more modest associations with normal-range heterogeneity in aging-related cognitive declines.

Brain volumetric changes and cognitive ageing during the eighth decade of life.

Later-life changes in brain tissue volumes--decreases in the volume of healthy grey and white matter and increases in the volume of white matter hyperintensities (WMH)--are strong candidates to explain some of the variation in ageing-related cognitive decline. We assessed fluid intelligence, memory, processing speed, and brain volumes (from structural MRI) at mean age 73 years, and at mean age 76 in a narrow-age sample of older individuals (n = 657 with brain volumetric data at the initial wave, n = 465 at follow-up). We used latent variable modeling to extract error-free cognitive levels and slopes. Initial levels of cognitive ability were predictive of subsequent brain tissue volume changes. Initial brain volumes were not predictive of subsequent cognitive changes. Brain volume changes, especially increases in WMH, were associated with declines in each of the cognitive abilities. All statistically significant results were modest in size (absolute r-values ranged from 0.114 to 0.334). These results build a comprehensive picture of macrostructural brain volume changes and declines in important cognitive faculties during the eighth decade of life.

Does incipient dementia explain normal cognitive decline determinants? Lothian birth cohort 1921.

The presence of an apolipoprotein E (APOE) ε4 allele, lower physical fitness, smoking, and lower serum vitamin B-12 have been reported as contributing to poorer cognitive function in LBC1921 at age 79, after adjusting for childhood intelligence. Because incident dementia was not previously ascertained within LBC1921, it is possible that preclinical or unrecognized cases at age 79 influenced findings. Dementia cases arising over approximately 16 years of follow-up were determined by a consensus using evidence from electronic medical records, death certificates, and clinical reviews. The analyses from the original reports were repeated after the exclusion of those who had developed dementia. In a subsequent set of analyses, the authors considered the potential impact of terminal decline, excluding those participants who died within 4 years of baseline testing. Positive APOE ε4 status was found to be associated with poorer Logical Memory (Wechsler, 1987) at age 79 (F(1, 355) = 8.16, p = .005, ηp2 = 0.022; n = 359) and lower Moray House Test (Scottish Council for Research in Education, 1933) score at age 79 (F(1, 357) = 4.27, p = .04, ηp2 = 0.012; n = 363). Lower age 79 IQ was associated with smoking (F(2, 360) = 3.67, p = .026, ηp2 = 0.020; n = 367), lower vitamin B-12 (Sß = 0.11, p = .014; n = 367), and poorer physical fitness (Sß = 0.21, p < .001; n = 359). Only the relationship with physical fitness remained significant after excluding those who died within 4 years of baseline (Sß = 0.203, p < .001; n = 310). Unrecognized dementia had little or no effect on determinants of lifetime cognitive ageing in LBC1921. Terminal decline may have accounted for the associations with age 11 to age 79 cognitive change. (PsycINFO Database Record

Brain structural differences between 73- and 92-year olds matched for childhood intelligence, social background, and intracranial volume.

Fully characterizing age differences in the brain is a key task for combating aging-related cognitive decline. Using propensity score matching on 2 independent, narrow-age cohorts, we used data on childhood cognitive ability, socioeconomic background, and intracranial volume to match participants at mean age of 92 years (n = 42) to very similar participants at mean age of 73 years (n = 126). Examining a variety of global and regional structural neuroimaging variables, there were large differences in gray and white matter volumes, cortical surface area, cortical thickness, and white matter hyperintensity volume and spatial extent. In a mediation analysis, the total volume of white matter hyperintensities and total cortical surface area jointly mediated 24.9% of the relation between age and general cognitive ability (tissue volumes and cortical thickness were not significant mediators in this analysis). These findings provide an unusual and valuable perspective on neurostructural aging, in which brains from the 8th and 10th decades of life differ widely despite the same cognitive, socioeconomic, and brain-volumetric starting points.