Abstract:Importance: Cognitive skills are known to decline through the lifespan with large individual differences. The molecular mechanisms for this decline are incompletely understood. Although leukocyte telomere length provides an index of cellular age that predicts the incidence of age-related diseases, it is unclear whether there is an association between cognitive decline and leukocyte telomere length.Objective: To examine the association between changes in cognitive function during adult life and leukocyte telome… Show more
“…We considered depressive symptoms and the completed level of formal education as potential covariates; although there was no group difference regarding depression, the participants' education was introduced as a covariate. This is well in accordance with a previous related study that has considered the influence of potential covariates associated with cognitive decline (Rask et al, 2016).…”
Summary
Disrupted sleep is a contributing factor to cognitive ageing, while also being associated with neurodegenerative disorders. Little is known, however, about the relation of sleep and the gradual cognitive changes over the adult life course. Sleep electroencephalogram (EEG) patterns are potential markers of the cognitive progress. To test this hypothesis, we assessed sleep architecture and EEG of 167 men born in the Copenhagen Metropolitan Area in 1953, who, based on individual cognitive testing from early (~18 years) to late adulthood (~58 years), were divided into 85 subjects with negative and 82 with positive cognitive change over their adult life. Participants underwent standard polysomnography, including manual sleep scoring at age ~58 years. Features of sleep macrostructure were combined with a number of EEG features to distinguish between the two groups. EEG rhythmicity was assessed by spectral power analysis in frontal, central and occipital sites. Functional connectivity was measured by inter‐hemispheric EEG coherence. Group differences were assessed by analysis of covariance (p < 0.05), including education and severity of depression as potential covariates. Subjects with cognitive decline exhibited lower sleep efficiency, reduced inter‐hemispheric connectivity during rapid eye movement (REM) sleep, and slower EEG rhythms during stage 2 non‐REM sleep. Individually, none of these tendencies remained significant after multiple test correction; however, by combining them in a machine learning approach, the groups were separated with 72% accuracy (75% sensitivity, 67% specificity). Ongoing medical screenings are required to confirm the potential of sleep efficiency and sleep EEG patterns as signs of individual cognitive progress.
“…We considered depressive symptoms and the completed level of formal education as potential covariates; although there was no group difference regarding depression, the participants' education was introduced as a covariate. This is well in accordance with a previous related study that has considered the influence of potential covariates associated with cognitive decline (Rask et al, 2016).…”
Summary
Disrupted sleep is a contributing factor to cognitive ageing, while also being associated with neurodegenerative disorders. Little is known, however, about the relation of sleep and the gradual cognitive changes over the adult life course. Sleep electroencephalogram (EEG) patterns are potential markers of the cognitive progress. To test this hypothesis, we assessed sleep architecture and EEG of 167 men born in the Copenhagen Metropolitan Area in 1953, who, based on individual cognitive testing from early (~18 years) to late adulthood (~58 years), were divided into 85 subjects with negative and 82 with positive cognitive change over their adult life. Participants underwent standard polysomnography, including manual sleep scoring at age ~58 years. Features of sleep macrostructure were combined with a number of EEG features to distinguish between the two groups. EEG rhythmicity was assessed by spectral power analysis in frontal, central and occipital sites. Functional connectivity was measured by inter‐hemispheric EEG coherence. Group differences were assessed by analysis of covariance (p < 0.05), including education and severity of depression as potential covariates. Subjects with cognitive decline exhibited lower sleep efficiency, reduced inter‐hemispheric connectivity during rapid eye movement (REM) sleep, and slower EEG rhythms during stage 2 non‐REM sleep. Individually, none of these tendencies remained significant after multiple test correction; however, by combining them in a machine learning approach, the groups were separated with 72% accuracy (75% sensitivity, 67% specificity). Ongoing medical screenings are required to confirm the potential of sleep efficiency and sleep EEG patterns as signs of individual cognitive progress.
“…The strengths of this study include the longitudinal nature, with repeated measurements of general cognitive ability up to seven times in four Swedish and US cohorts. An observed significant association should not be due to the reverse causation in this study because TL was assessed before cognition, although early-life intelligence and cognitive changes have been shown to be predictive of TL in mid-later life (Rask et al, 2016; Schaefer et al, 2016). A further strength is that our combined analytic longitudinal study samples are the largest collection tested thus far and the age periods span from 50 to 100 years and beyond, which is representative of the underlying general aging population.…”
To investigate the association of telomere length (TL) with trajectories of general cognitive abilities, we used data on 5955 participants from the Sex Differences in Health and Aging Study and the Swedish Adoption/Twin Study of Aging in Sweden, and the Mayo Clinic Study of Aging, and the Health and Retirement Study in the United States. TL was measured at baseline, while general cognitive ability was assessed repeatedly up to 7 occasions. Latent growth curve models were used to examine the associations. One standard deviation increase of TL was associated with 0.021 unit increase (95% confidence interval [CI]: 0.001, 0.042) of standardized mean general cognitive ability. After controlling for sex, the point estimate remained similar (0.019) with a wider CI (95% CI: -0.002, 0.039). The association was attenuated with adjustment for educational attainment (0.009, 95% CI: -0.009, 0.028). No strong evidence was observed for the association of TL and decline in general cognitive ability. Longer TL was associated with higher general cognitive ability levels in the age-adjusted models but not in the models including all covariates, nor with cognitive decline.
“…assessment (Mather, Jorm, Parslow, & Christensen, 2011). Further, LTL changes may depend on different factors that vary across the lifespan (Rask et al, 2016). Divergent findings between the Yaffe et al (2011) study and our own investigation may be a consequence of differing study designs and the fact that the former comprises an ethnically diverse population of community residents, while the latter comprises individuals solely of European ancestry, who were selected based on exceptional survival attributes.…”
mentioning
confidence: 57%
“…Age-related cognitive decline is caused by oxidative stress triggering neuroinflammation, and subsequent neurodegeneration and cell apoptosis (Ma et al, 2013). In this way, it relates to telomere attrition, which can arise from the cumulative burden of inflammation and oxidative stress through the lifecourse (Ma et al, 2013;Rask et al, 2016). Yet, the extent to which LTL relates to typical and/or pathologic cognitive aging is still largely unknown; it is uncertain whether shortened telomeres are a cause, consequence, or both for deteriorating cognitive ability (Hagg et al, 2017).…”
Objective:
Leukocyte telomere length (LTL) is a widely hypothesized biomarker of biological aging. Persons with shorter LTL may have a greater likelihood of developing dementia. We investigate whether LTL is associated with cognitive function, differently for individuals without cognitive impairment versus individuals with dementia or incipient dementia.
Method:
Enrolled subjects belong to the Long Life Family Study (LLFS), a multi-generational cohort study, where enrollment was predicated upon exceptional family longevity. Included subjects had valid cognitive and telomere data at baseline. Exclusion criteria were age ≤ 60 years, outlying LTL, and missing sociodemographic/clinical information. Analyses were performed using linear regression with generalized estimating equations, adjusting for sex, age, education, country, generation, and lymphocyte percentage.
Results:
Older age and male gender were associated with shorter LTL, and LTL was significantly longer in family members than spouse controls (p < 0.005). LTL was not associated with working or episodic memory, semantic processing, and information processing speed for 1613 cognitively unimpaired individuals as well as 597 individuals with dementia or incipient dementia (p < 0.005), who scored significantly lower on all cognitive domains (p < 0.005).
Conclusions:
Within this unique LLFS cohort, a group of families assembled on the basis of exceptional survival, LTL is unrelated to cognitive ability for individuals with and without cognitive impairment. LTL does not change in the context of degenerative disease for these individuals who are biologically younger than the general population.
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