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Narbutas, J.

Publications and source records attributed to Narbutas, J..

4 recordsLinked to original sources

Cognitive Fitness in Ageing (COFITAGE): A Multimodal and Longitudinal Neuroimaging Dataset

Purpose: Brain aging involves interrelated changes in molecular processes, neuroinflammatory mechanisms, brain macro- and microstructure, sleep physiology, and cognition. The 50 to 70 years age range represents a critical transition period, in which these subtle alterations may precede measurable cognitive decline and the onset of clinical neurodegenerative disease. To allow systematic investigation of these early alterations and the subsequent progression in brain aging, we provide an open-access data resource from a multidisciplinary longitudinal study integrating neuroimaging, genetics, sleep, and neuropsychological phenotyping with assessments at baseline and at 2-year follow-up. Acquisition and Validation Methods: The baseline cohort comprises 101 community-dwelling participants (50-69 years old) who underwent magnetic resonance imaging (MRI) using a 3T protocol that included high-resolution structural imaging (T1- and T2-weighted), quantitative multi-parametric acquisitions with B1 mapping, and multi-shell diffusion-weighted imaging. Moreover, positron emission tomography (PET) imaging was performed using [18F]Flutemetamol or [18F]Florbetapir (amyloid-beta tracers) in all participants, with a subset also undergoing [18F]THK-5351 PET (tau-related/neuroinflammation). The dataset was complemented by extensive phenotypic data, including sleep and neuropsychological assessments, and by genotype data through genetic analysis. 66 participants underwent a 2-year cognitive follow-up, enabling longitudinal analyses of cognitive trajectories. Data acquisition and curation were performed using standardized procedures, with systematic quality control to support reliable cross-sectional and longitudinal analyses. Data Format and Usage Notes: All data are distributed in a BIDS-compliant format, and released in open-access (EBRAINS). Potential Applications: This dataset supports multimodal analyses, allowing the identification of interpretable patterns characterizing brain aging from multiple perspectives. It enables the comparison of different models to derive (semi)quantitative MRI parameters, the discovery of imaging biomarkers associated with early cognitive decline, and the monitoring or prediction of brain aging progression. In addition, it offers focused coverage of adults aged 50-70 years, which is often underrepresented in existing healthy subjects public datasets.

neuroscience↗

Global brain maintenance predicts well-preserved cognitive function: A pooled analysis of three longitudinal population-based Swedish cohorts

Substantial heterogeneity in cognitive ageing is well documented. Such heterogeneity has been attributed to individual differences in brain maintenance - i.e., the relative preservation of neural resources in ageing. However, large-scale longitudinal evidence is lacking. We pooled data from three population-based Swedish cohorts (Betula, N = 196; SNAC-K, N = 472; H70, N = 688; aged 60-93 years at baseline, follow-up duration up to 7 years) to assess whether global brain maintenance is associated with better preserved cognition in ageing, and to identify lifestyle predictors of brain maintenance. In each cohort, global brain integrity was indexed by the volume of the lateral ventricles (adjusted for total intracranial volume), and general cognitive function based on a principal component analysis of four age-sensitive cognitive domains. Participants were classified into subgroups of low (i.e., aged) versus high (i.e., youth-like) brain integrity based on ventricular volume estimates available for a younger reference sample in one of the cohorts (Betula, 25-55 years, N = 60). Subgroup differences in cognition at baseline and over the follow-up were assessed with ANCOVAs and linear mixed effects models. Logistic regressions were used to examine lifestyle predictors of brain maintenance. Across cohorts, 881 individuals (64.97%) were classified into the high brain integrity subgroup at baseline and 409 individuals (49.82%) over the follow-up. Maintenance of more youth-like brain integrity was associated with better baseline cognition (p < .001) and less cognitive decline longitudinally (p < .001). Moreover, lower cardiovascular disease (CVD) risk and the absence of diabetes predicted brain maintenance at baseline (CVD risk, OR = 0.80, 95% CI [0.68, 0.93]; diabetes, OR = 0.39, 95% CI [0.26, 0.59]) and over the follow-up (CVD risk, OR = 0.79, 95% CI [0.64, 0.96]; diabetes, OR = 0.53, 95% CI [0.29, 0.94]). These findings underscore brain maintenance as a key determinant of cognitive ageing and highlight the importance of managing cardiovascular and metabolic disease risk factors for promotion of brain and cognitive health in later life.

neuroscience↗

Timely sleep coupling: spindle-slow wave synchrony is linked to early amyloid-β burden and predicts memory decline

Sleep alteration is a hallmark of ageing and emerges as a risk factor for Alzheimers disease (AD). While the fine-tuned coalescence of sleep microstructure elements may influence age-related cognitive trajectories, its association with AD processes is not fully established. Here, we investigated whether the coupling of spindles and slow waves is associated with early amyloid-beta (A{beta}) brain burden, a hallmark of AD neuropathology, and cognitive change over 2 years in 100 healthy individuals in late-midlife (50-70y; 68 women). We found that, in contrast to other sleep metrics, earlier occurrence of spindles on slow-depolarisation slow waves is associated with higher medial prefrontal cortex A{beta} burden (p=0.014, r2{beta}*=0.06), and is predictive of greater longitudinal memory decline (p=0.032, r2{beta}*=0.07). These findings unravel early links between sleep, AD-related processes and cognition and suggest that altered coupling of sleep microstructure elements, key to its mnesic function, contributes to poorer brain and cognitive trajectories in ageing.

neuroscience↗

Preserved wake-dependent cortical excitability dynamics predict cognitive fitness beyond age-related brain alterations

Age-related cognitive decline arises from alterations in brain integrity as well as in sleep-wake regulation. Here, we investigated whether preserved sleep-wake regulation of cortical function during wakefulness could represent a positive factor for cognitive fitness in aging, independently of early age-related changes in brain structure. We quantified cortical excitability dynamics during prolonged wakefulness as a sensitive marker of age-related alteration in sleep-wake regulation in 60 healthy older individuals (50-69y; 42 women). Brain structural integrity was assessed with amyloid-beta- and tau-PET, and with MRI. Participants cognition was extensively investigated. We show that individuals with preserved cortical excitability dynamics exhibit better cognitive performance, particularly in the executive domain, which is essential to successful cognitive aging. Critically, this association remained significant after accounting for brain integrity measures. Preserved dynamics of basic brain function during wakefulness could be essential to cognitive fitness in aging, independently from age-related brain structural modifications that can ultimately lead to dementia.

neuroscience↗