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Sökning: WFRF:(Walhovd Kristine Beate)

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2.
  • Fjell, Anders Martin, et al. (författare)
  • Neuroinflammation and Tau Interact with Amyloid in Predicting Sleep Problems in Aging Independently of Atrophy.
  • 2018
  • Ingår i: Cerebral cortex (New York, N.Y. : 1991). - 1460-2199. ; 28:8
  • Tidskriftsartikel (refereegranskat)abstract
    • Sleep problems relate to brain changes in aging and disease, but the mechanisms are unknown. Studies suggest a relationship between β-amyloid (Aβ) accumulation and sleep, which is likely augmented by interactions with multiple variables. Here, we tested how different cerebrospinal fluid (CSF) biomarkers for brain pathophysiology, brain atrophy, memory function, and depressive symptoms predicted self-reported sleep patterns in 91 cognitively healthy older adults over a 3-year period. The results showed that CSF levels of total- and phosphorylated (P) tau, and YKL-40-a marker of neuroinflammation/astroglial activation-predicted poor sleep in Aβ positive older adults. Interestingly, although brain atrophy was strongly predictive of poor sleep, the relationships between CSF biomarkers and sleep were completely independent of atrophy. A joint analysis showed that unique variance in sleep was explained by P-tau and the P-tau × Aβ interaction, memory function, depressive symptoms, and brain atrophy. The results demonstrate that sleep relates to a range of different pathophysiological processes, underscoring the importance of understanding its impact on neurocognitive changes in aging and people with increased risk of Alzheimer's disease.
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3.
  • Idland, Ane-Victoria, et al. (författare)
  • CSF neurofilament light levels predict hippocampal atrophy in cognitively healthy older adults.
  • 2017
  • Ingår i: Neurobiology of aging. - 1558-1497. ; 49, s. 138-144
  • Tidskriftsartikel (refereegranskat)abstract
    • Cerebrospinal fluid (CSF) neurofilament light (NFL) is a marker of axonal degeneration. We tested whether CSF NFL levels predict hippocampal atrophy rate in cognitively healthy older adults independently of the established CSF Alzheimer's disease (AD) biomarkers, β-amyloid 1-42, and phosphorylated tau (P-tau). We included 144 participants in a 2-year longitudinal study with baseline CSF measures and 2 magnetic resonance images. Eighty-eight participants had full data available. A subgroup of 36 participants with very low AD risk was also studied. NFL predicted hippocampal atrophy rate independently of age, β-amyloid 1-42, and P-tau. Including NFL, P-tau, and age in the same model, higher NFL and lower P-tau predicted higher hippocampal atrophy (R(2) = 0.20, NFL: β = -0.34; p = 0.003; P-tau: β = 0.27; p = 0.009). The results were upheld in the participants with very low AD risk. NFL predicted neurodegeneration in older adults with very low AD probability. We suggest that factors previously shown to be important for brain degeneration in mild cognitive impairment may also impact changes in normal aging, demonstrating that NFL is likely to indicate AD-independent, age-expected neurodegeneration.
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  • Sala-Llonch, Roser, et al. (författare)
  • Inflammation, Amyloid, and Atrophy in The Aging Brain: Relationships with Longitudinal Changes in Cognition.
  • 2017
  • Ingår i: Journal of Alzheimer's disease : JAD. - 1875-8908. ; 58:3, s. 829-840
  • Tidskriftsartikel (refereegranskat)abstract
    • Amyloid deposition occurs in aging, even in individuals free from cognitive symptoms, and is often interpreted as preclinical Alzheimer's disease (AD) pathophysiology. YKL-40 is a marker of neuroinflammation, being increased in AD, and hypothesized to interact with amyloid-β (Aβ) in causing cognitive decline early in the cascade of AD pathophysiology. Whether and how Aβ and YKL-40 affect brain and cognitive changes in cognitively healthy older adults is still unknown. We studied 89 participants (mean age: 73.1 years) with cerebrospinal fluid samples at baseline, and both MRI and cognitive assessments from two time-points separated by two years. We tested how baseline levels of Aβ42 and YKL-40 correlated with changes in cortical thickness and cognition. Thickness change correlated with Aβ42 only in Aβ42+ participants (<600 pg/mL, n = 27) in the left motor and premotor cortices. Aβ42 was unrelated to cognitive change. Increased YKL-40 was associated with less preservation of scores on the animal naming test in the total sample (r = -0.28, p = 0.012) and less preservation of a score reflecting global cognitive function for Aβ42+ participants (r = -0.58, p = 0.004). Our results suggest a role for inflammation in brain atrophy and cognitive changes in cognitively normal older adults, which partly depended on Aβ accumulation.
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6.
  • Vidal-Pineiro, Didac, et al. (författare)
  • Individual variations in 'brain age' relate to early-life factors more than to longitudinal brain change
  • 2021
  • Ingår i: eLIFE. - : eLife Sciences Publications. - 2050-084X. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • Brain age is a widely used index for quantifying individuals’ brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two indepen-dent large test datasets (UK Biobank [main] and Lifebrain [replication]; longitudinal observations ≈ 2750 and 4200) by assessing the relationship between cross-sectional and longitudinal estimates of brain age. Brain age models were estimated in two different training datasets (n ≈ 38,000 [main] and 1800 individuals [replication]) based on brain structural features. The results showed no association between cross-sectional brain age and the rate of brain change measured longitudinally. Rather, brain age in adulthood was associated with the congenital factors of birth weight and polygenic scores of brain age, assumed to reflect a constant, lifelong influence on brain structure from early life. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging.
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