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Neurodegenerative, vascular, and dementia diseases are linked to dysregulations in cholesterol metabolism. Dietary plant sterols, or phytosterols, may interfere to neurodegeneration and cognitive decline, and have cholesterol-lowering, anti-inflammatory, and antioxidant qualities. Here, we investigated the potential associations between circulating cholesterol precursors and metabolites, triglycerides, and phytosterols with cognitive decline in older people by performing multivariate analysis on 246 participants engaged in a population-based prospective study. In our analysis we considered the potential effect of sex and APOEe4. We reveal particular dysregulations of diet-derived phytosterols and endogenous cholesterol synthesis and metabolism, and their variations over time linked to cognitive decline in the general population. These results are significant to the development of interventions to avoid cognitive decline in older adults and suggest that levels of circulating sterols should be taken into account when evaluating risk.
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OBJECTIVE: We aimed to assess the effect on cognitive function of adding dairy (total, fermented, non-fermented, full fat, low fat, and sugary) to the diet and of substituting some food groups for dairy. DESIGN: Secondary analysis of a prospective population-based cohort study. PARTICIPANTS: We analyzed data from 1334 cognitively healthy participants (median age 67 years at baseline) with a mean follow-up of 5.6 years from the CoLaus|PsyColaus cohort in Lausanne, Switzerland. MEASUREMENTS: The participants completed a food frequency questionnaire at baseline and cognitive tests at baseline and at follow-up. Clinical dementia rating was the primary outcome. Subjective cognitive decline, memory, verbal fluency, executive and motor functions were secondary outcomes. METHODS: Our exposure was the consumption of total and 5 sub-types of dairy products (g/d). We used marginal structural models to compute average causal effects of 1) increasing dairy consumption by 100 g/d and 2) substituting 100 g/d of meat, fish, eggs, fruits and vegetables with dairy on the outcomes. We used inverse probability of the treatment and lost to follow-up weighting to account for measured confounding and non-random loss to follow-up. RESULTS: Overall, the effects of adding dairy products to the diet on cognition were negligible and imprecise. No substitution had a substantial and consistent effect on clinical dementia rating. The substitution of fish [11.7% (-3% to 26.5%)] and eggs [18% (2.3%-33.7%)] for dairy products could negatively impact verbal memory and neurolinguistic processes. CONCLUSION: We found no effect of adding dairy to the diet or substituting meat, vegetables or fruit for dairy on cognitive function in this cohort of older adults. The substitution of fish and eggs for dairy could have a negative effect on some secondary outcomes, but more studies modeling food substitutions are needed to confirm these results.
Assuntos
Laticínios , Dieta , Animais , Humanos , Idoso , Estudos de Coortes , Estudos Prospectivos , Verduras , CogniçãoRESUMO
BACKGROUND: Neuropsychiatric symptoms (NPS) are common in older people, may occur early in the development of dementia disorders, and have been associated with faster cognitive decline. Here, our objectives were to investigate whether plasma levels of neurofilament light chain (NfL), glial fibrillary acid protein (GFAP), and tau phosphorylated at threonine 181 (pTau181) are associated with current NPS and predict future NPS in non-demented older people. Furthermore, we tested whether the presence of NPS combined with plasma biomarkers are useful to predict Alzheimer's disease (AD) pathology and cognitive decline. METHODS: One hundred and fifty-one participants with normal cognition (n=76) or mild cognitive impairment (n=75) were examined in a longitudinal brain aging study at the Memory Centers, University Hospital of Lausanne, Switzerland. Plasma levels of NfL, GFAP, and pTau181 along with CSF biomarkers of AD pathology were measured at baseline. NPS were assessed through the Neuropsychiatric Inventory Questionnaire (NPI-Q), along with the cognitive and functional performance at baseline and follow-up (mean: 20 months). Linear regression and ROC analyses were used to address the associations of interest. RESULTS: Higher GFAP levels were associated with NPS at baseline (ß=0.23, p=.008). Higher NfL and GFAP levels were associated with the presence of NPS at follow-up (ß=0.29, p=.007 and ß=0.28, p=.007, respectively) and with an increase in the NPI-Q severity score over time (ß=0.23, p=.035 and ß=0.27, p=.011, respectively). Adding NPS and the plasma biomarkers to a reference model improved the prediction of future NPS (AUC 0.73 to 0.84, p=.007) and AD pathology (AUC 0.79 to 0.86, p=.006), but not of cognitive decline (AUC 0.79 to 0.84, p=.068). CONCLUSION: Plasma GFAP is associated with NPS while NfL and GFAP are both associated with future NPS and NPS severity. Considering the presence of NPS along with blood-based AD-biomarkers may improve diagnosis and prediction of clinical progression of NPS and inform clinical decision-making in non-demented older people.
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BACKGROUND: Neuropsychiatric symptoms (NPS) are common in older people, may occur early in the development of dementia disorders, and have been associated with faster cognitive decline. Here, our objectives were to investigate whether plasma levels of neurofilament light chain (NfL), glial fibrillary acid protein (GFAP), and tau phosphorylated at threonine 181 (pTau181) are associated with current NPS and predict future NPS in non-demented older people. Furthermore, we tested whether the presence of NPS combined with plasma biomarkers are useful to predict Alzheimer's disease (AD) pathology and cognitive decline. METHODS: One hundred and fifty-one participants with normal cognition (n = 76) or mild cognitive impairment (n = 75) were examined in a longitudinal brain aging study at the Memory Centers, University Hospital of Lausanne, Switzerland. Plasma levels of NfL, GFAP, and pTau181 along with CSF biomarkers of AD pathology were measured at baseline. NPS were assessed through the Neuropsychiatric Inventory Questionnaire (NPI-Q), along with the cognitive and functional performance at baseline and follow-up (mean: 20 months). Different regression and ROC analyses were used to address the associations of interest. RESULTS: None of the three plasma biomarker was associated with NPS at baseline. Higher GFAP levels were associated with the presence of NPS at follow-up (OR = 2.8, p = .002) and both, higher NfL and higher GFAP with an increase in the NPI-Q severity score over time (ß = 0.25, p = .034 and ß = 0.30, p = .013, respectively). Adding NPS and the plasma biomarkers to a reference model improved the prediction of future NPS (AUC 0.72 to 0.88, p = .002) and AD pathology (AUC 0.78 to 0.87, p = .010), but not of cognitive decline (AUC 0.79 to 0.85, p = .081). CONCLUSION: Plasma NfL and GFAP are both associated with future NPS and NPS severity change. Considering the presence of NPS along with blood-based AD-biomarkers may improve the prediction of clinical progression of NPS over time and inform clinical decision-making in non-demented older people.