| 1. |
- Dintica, Christina S., et al.
(author)
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Tooth loss is associated with accelerated cognitive decline and volumetric brain differences : a population-based study
- 2018
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In: Neurobiology of Aging. - : Elsevier BV. - 0197-4580 .- 1558-1497. ; 67, s. 23-30
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Journal article (peer-reviewed)abstract
- Tooth loss has been related to cognitive impairment; however, its relation to structural brain differences in humans is unknown. Dementia-free participants (n = 2715) of age >= 60 years were followed up for up to 9 years. A subsample (n = 394) underwent magnetic resonance imaging at baseline. Information on tooth loss was collected at baseline, and cognitive function was assessed using the Mini-Mental State Examination at baseline and at follow-ups. Data were analyzed using linear mixed effects models and linear regression models. At baseline, 404 (14.9%) participants had partial tooth loss, and 206 (7.6%) had complete tooth loss. Tooth loss was significantly associated with a steeper cognitive decline (beta: -0.18, 95% confidence interval [CI]: -0.24 to -0.11) and remained significant after adjusting for or stratifying by potential confounders. In cross-sectional analyses, persons with complete or partial tooth loss had significantly lower total brain volume (beta: -28.89, 95% CI: -49.33 to -8.45) and gray matter volume (beta: -22.60, 95% CI: -38.26 to -6.94). Thus, tooth loss may be a risk factor for accelerated cognitive aging.
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| 2. |
- Gallo, Federico, et al.
(author)
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Cognitive Trajectories and Dementia Risk : A Comparison of Two Cognitive Reserve Measures.
- 2021
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In: Frontiers in Aging Neuroscience. - : Frontiers Media S.A.. - 1663-4365. ; 13
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Journal article (peer-reviewed)abstract
- Background and Objectives: Cognitive reserve (CR) is meant to account for the mismatch between brain damage and cognitive decline or dementia. Generally, CR has been operationalized using proxy variables indicating exposure to enriching activities (activity-based CR). An alternative approach defines CR as residual variance in cognition, not explained by the brain status (residual-based CR). The aim of this study is to compare activity-based and residual-based CR measures in their association with cognitive trajectories and dementia. Furthermore, we seek to examine if the two measures modify the impact of brain integrity on cognitive trajectories and if they predict dementia incidence independent of brain status.Methods: We used data on 430 older adults aged 60+ from the Swedish National Study on Aging and Care in Kungsholmen, followed for 12 years. Residual-based reserve was computed from a regression predicting episodic memory with a brain-integrity index incorporating six structural neuroimaging markers (white-matter hyperintensities volume, whole-brain gray matter volume, hippocampal volume, lateral ventricular volume, lacunes, and perivascular spaces), age, and sex. Activity-based reserve incorporated education, work complexity, social network, and leisure activities. Cognition was assessed with a composite of perceptual speed, semantic memory, letter-, and category fluency. Dementia was clinically diagnosed in accordance with DSM-IV criteria. Linear mixed models were used for cognitive change analyses. Interactions tested if reserve measures modified the association between brain-integrity and cognitive change. Cox proportional hazard models, adjusted for brain-integrity index, assessed dementia risk.Results: Both reserve measures were associated with cognitive trajectories [β × time (top tertile, ref.: bottom tertile) = 0.013; 95% CI: -0.126, -0.004 (residual-based) and 0.011; 95% CI: -0.001, 0.024, (activity-based)]. Residual-based, but not activity-based reserve mitigated the impact of brain integrity on cognitive decline [β (top tertile × time × brain integrity) = -0.021; 95% CI: -0.043, 0.001] and predicted 12-year dementia incidence, after accounting for the brain-integrity status [HR (top tertile) = 0.23; 95% CI: 0.09, 0.58].Interpretation: The operationalization of reserve based on residual cognitive performance may represent a more direct measure of CR than an activity-based approach. Ultimately, the two models of CR serve largely different aims. Accounting for brain integrity is essential in any model of reserve.
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| 3. |
- Grande, Giulia, et al.
(author)
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Brain Changes and Fast Cognitive and Motor Decline in Older Adults
- 2022
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In: The journals of gerontology. Series A, Biological sciences and medical sciences. - : Oxford University Press (OUP). - 1079-5006 .- 1758-535X. ; 78:2, s. 326-332
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Journal article (peer-reviewed)abstract
- Background: To identify brain magnetic resonance imaging (MRI) signatures characterizing people with different patterns of decline in cognition and motor function.Methods: In the Swedish National Study on Aging and Care in Kungsholmen, Stockholm, 385 participants had available repeated brain MRI examinations, where markers of brain volumes and white matter integrity were assessed. The speed of cognitive and motor decline was estimated as the rate of a Mini-Mental State Examination and gait speed decline over 12 years (linear mixed models), and further dichotomized into the upper (25% fastest rate of decline) versus the lower quartiles. Participants were grouped in slow/no decliners (reference), isolated motor decliners, isolated cognitive decliners, and cognitive and motor decliners. We estimated the associations between changes in brain markers (linear mixed models) and baseline diffusion tensor imaging measures (linear regression model) and the 4 decline patterns.Results: Individuals with concurrent cognitive and motor decline (n = 51) experienced the greatest loss in the total brain (β: −12.3; 95% confidence interval [CI]: −18.2; −6.38) and hippocampal (β: −0.25; 95% CI: −0.34; −0.16) volumes, the steepest accumulation of white matter hyperintensities (β: 1.61; 95% CI: 0.54; 2.68), and the greatest ventricular enlargement (β: 2.07; 95% CI: 0.67; 3.47). Compared to the reference, those only experiencing cognitive decline presented with steeper hippocampal volume loss, whereas those exhibiting only motor decline displayed a greater white matter hyperintensities burden. Lower microstructural white matter integrity was associated with concurrent cognitive and motor decline.Conclusion: Concurrent cognitive and motor decline is accompanied by rapidly evolving and complex brain pathology involving both gray and white matter. Isolated cognitive and motor declines seem to exhibit brain damage with different qualitative features.
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| 4. |
- Marseglia, Anna, et al.
(author)
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Can active life mitigate the impact of diabetes on dementia and brain aging?
- 2020
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In: Alzheimer's & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 16:11, s. 1534-1543
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Journal article (peer-reviewed)abstract
- Introduction: We investigated whether lifelong exposure to stimulating activities (active life, AL) mitigates diabetes-associated dementia risk and brain aging.Methods: In the Swedish National Study on Aging and Care-Kungsholmen, 2286 dementia-free older adults (407 with MRI volumetric measures) were followed over 12 years to detect incident dementia. AL index (low, moderate, high) combined education, work complexity, leisure activities, and social network.Results: Participants with diabetes and low AL had higher dementia risk (hazard ratio [HR] = 2.36, 95% confidence interval [CI] 1.45-3.87) than patients who were diabetes-free with moderate-to-high AL (reference). Dementia risk in participants with diabetes and moderate-to-high AL did not differ from the reference. People with diabetes and low AL had the smallest brain volume, but those with diabetes and moderate-to-high AL exhibited total brain and gray-matter volumes that were similar to those of diabetes-free participants. AL did not modify the diabetes microvascular lesions association.Discussion: AL could mitigate the deleterious impact of diabetes on dementia, potentially by limiting the loss of brain tissue volume.
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| 5. |
- Marseglia, Anna, et al.
(author)
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Prediabetes and diabetes accelerate cognitive decline and predict microvascular lesions : A population-based cohort study
- 2019
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In: Alzheimer's & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 15:1, s. 25-33
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Journal article (peer-reviewed)abstract
- Introduction: The impact of prediabetes and diabetes on cognitive decline and the potential underlying mechanisms remain unclear. We investigated whether prediabetes and diabetes accelerate cognitive decline and brain aging, and the initial pathological changes linked to microvascular processes.Methods: Nine-year longitudinal data from the Swedish National Study on Aging and Care-Kungsholmen (n = 2746, age >= 60 years) and the magnetic resonance imaging subsample (n = 455) were used. Cognitive function was assessed with Mini-Mental State Examination. Brain magnetic resonance imaging markers included total brain tissue, white matter, gray matter, white matter hyperintensities, and hippocampal volumes.Results: Compared with diabetes-free status, prediabetes and diabetes were independently associated with accelerated cognitive decline. Prediabetes was cross-sectionally associated with smaller total brain tissue volume (P < .01), particularly smaller white matter volume. Diabetes was associated with larger white matter hyperintensities volume. Longitudinally, diabetes was associated with faster white matter hyperintensities accumulation. No associations between prediabetes or diabetes and hippocampal volume were found.Discussion: Diabetes and prediabetes accelerate cognitive decline and might predict microvascular lesions among dementia-free older adults.
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| 6. |
- Marseglia, Anna, et al.
(author)
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Social Health and Cognitive Change in Old Age : Role of Brain Reserve
- 2023
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In: Annals of Neurology. - : John Wiley & Sons. - 0364-5134 .- 1531-8249. ; 93:4, s. 844-855
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Journal article (peer-reviewed)abstract
- Objective: Individual aspects of social health (SH; eg, network, engagement, support) have been linked to cognitive health. However, their combined effect and the role of the structural properties of the brain (brain reserve [BR]) remain unclear. We investigated the interplay of SH and BR on cognitive change in older adults.Methods: Within the Swedish National Study on Aging and Care–Kungsholmen, 368 dementia-free adults aged ≥60 years with baseline brain magnetic resonance imaging were followed over 12 years to assess cognitive change. A measure of global cognition was computed at each of the 5 waves of assessment by averaging domain-specific Z scores for episodic memory, perceptual speed, semantic memory, and letter and category fluency. An SH composite score was computed at baseline by combining leisure activities and social network. BR was proxied by total brain tissue volume (TBTV). Linear mixed models (adjusted for sociodemographic, vascular, and genetic factors) were used to estimate cognitive trajectories in relation to SH and TBTV. Interaction analysis and stratification were used to examine the interplay between SH and TBTV.Results: Moderate–good SH (n = 245; vs poor, β-slope = 0.01, 95% confidence interval [CI] = 0.002–0.02, p = 0.018) and moderate-to-large TBTV (n = 245; vs small, β-slope = 0.03, 95% CI = 0.02–0.04, p < 0.001) were separately associated with slower cognitive decline. In stratified analysis, moderate–good SH was associated with higher cognitive levels (but not change) only in participants with moderate-to-large TBTV (β-intercept = 0.21, 95% CI = 0.06–0.37, p < 0.01; interaction SH * TBTV, p < 0.05).Interpretation: Our findings highlight the interplay between SH and BR that likely unfolds throughout the entire life course to shape old-age cognitive outcomes. ANN NEUROL 2023
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| 7. |
- Prinelli, Federica, et al.
(author)
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Specific nutrient patterns are associated with higher structural brain integrity in dementia-free older adults
- 2019
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In: NeuroImage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 199, s. 281-288
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Journal article (peer-reviewed)abstract
- Optimal nutrition may play a beneficial role in maintaining a healthy brain. However, the relationship between nutrient intake and brain integrity is largely unknown. We investigated the association of specific nutrient dietary patterns with structural characteristics of the brain. Within the population-based Swedish National study on Aging and Care-Kungsholmen (SNAC-K), a cross-sectional study of 417 dementia-free participants aged >= 60 years who underwent structural magnetic resonance imaging (MRI) scans during 2001-2003, was carried-out. Data on dietary intake were collected using a food frequency questionnaire, from which intake of 21 nutrients was estimated. By principal component analysis, five nutrient patterns were extracted: (1) NP1 was characterized by fiber, vitamin C, E, beta-carotene, and folate [Fiber&Antioxidants], (2) NP2 by eicosapentaenoic (EPA, 20:5 omega-3) and docosahexaenoic (DHA, 22:6 omega-3) polyunsaturated fatty acids (PUFAs), proteins, cholesterol, vitamin B3, B12, and D [long chain (LC) omega-3PUFAs&Proteins], (3) NP3 by alpha-linoleic (18:2 omega-6) and alpha-linolenic (18:3 omega-3) PUFAs, monounsaturated fatty acids (MUFAs), and vitamin E [MUFAs &omega-3,6PUFAs], (4) NP4 by saturated fatty acids (SFAs), trans fats, MUFAs, and cholesterol [SFAs&Trans fats], (5) NP5 by B-vitamins, retinol, and proteins [B-Vitamins&Retinol]. Nutrient patterns scores were tertiled with the lowest tertile as reference, and were related to total brain volume (TBV) and white matter hyperintensities volume (WMHV) using linear regression models adjusting for potential confounders. In the multi-adjusted model, compared to the lowest intake for each pattern, the highest intake of NP1 (beta = 11.11, P = 0.009), NP2 (beta = 7.47, P = 0.052), and NP3 (beta = 10.54, P = 0.005) was associated with larger TBV whereas NP5 was related to smaller TBV (beta = -12.82, P = 0.001). The highest intake of NP1 was associated with lower WMHV (beta = -0.32, P = 0.049), whereas NP4 was associated with greater WMHV (beta = 0.31, P = 0.036). In sum, our results suggest that the identified brain-health specific nutrient combinations characterized by higher intake of fruit, vegetables, legumes, olive and seed oils, fish, lean red meat, poultry and low in milk and dairy products, cream, butter, processed meat and offal, were strongly associated with greater brain integrity among older adults.
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