Thioredoxin-80 (Trx80) is a cleavage product from the redox-active protein Thioredoxin-1 and has been previously described as a pro-inflammatory cytokine secreted by immune cells. Previous studies in ...our group reported that Trx80 levels are depleted in Alzheimer's disease (AD) brains. However, no studies so far have investigated peripheral Trx80 levels in the context of AD pathology and whether could be associated with the main known AD risk factors and biomarkers.
Trx80 was measured in serum samples from participants from two different cohorts: the observational memory clinic biobank (GEDOC) (N = 99) with AD CSF biomarker data was available and the population-based lifestyle multidomain intervention trial Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) (N = 47), with neuroimaging data and blood markers of inflammation available. The GEDOC cohort consists of participants diagnosed with subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD, whereas the FINGER participants are older adults at-risk of dementia, but without substantial cognitive impairment. One-way ANOVA and multiple comparison tests were used to assess the levels of Trx80 between groups. Linear regression models were used to explore associations of Trx80 with cognition, AD CSF biomarkers (Aβ42, t-tau, p-tau and p-tau/t-tau ratio), inflammatory cytokines, and neuroimaging markers.
In the GEDOC cohort, Trx80 was associated to p-tau/t-tau ratio in the MCI group. In the FINGER cohort, serum Trx80 levels correlated with lower hippocampal volume and higher pro-inflammatory cytokine levels. In both GEDOC and FINGER cohorts, ApoE4 carriers had significantly higher serum Trx80 levels compared to non-ApoE4 carriers. However, Trx80 levels in the brain were further decreased in AD patients with ApoE4 genotype.
We report that serum Trx80 levels are associated to AD disease stage as well as to several risk factors for AD such as age and ApoE4 genotype, which suggests that Trx80 could have potential as serum AD biomarker. Increased serum Trx80 and decreased brain Trx80 levels was particularly seen in ApoE4 carriers. Whether this could contribute to the mechanism by which ApoE4 show increased vulnerability to develop AD would need to be further investigated.
ClinicalTrials.gov NCT01041989 . Registered on 4 January 2010-retrospectively registered.
The COVID-19 pandemic and its related restrictions have affected the everyday life of older people. Advanced age is a significant predisposing factor for a more severe COVID-19 infection, increasing ...the risk for hospitalization and mortality. Even though restrictions have been, thus, well-grounded, they may also have had detrimental effects on the social well-being of older people. Personal networks and social activity are known protective factors against the premature decline in health and functioning, and it is widely acknowledged that social isolation increases feelings of loneliness, poor quality of life, and even the risk for diseases and disabilities among older adults. This qualitative study investigated changes in personal networks among community-dwelling oldest-old individuals (persons aged 80 and over) during the first and second waves of the COVID-19 pandemic in Finland. The data is part of the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE85+) study, which is an ongoing large longitudinal population-based study in Finland. In this qualitative sub-study, we analyzed fifteen in-depth telephone interviews using directed content analyses and identified five types of changes in personal social networks during the pandemic. In type 1, all social contacts were significantly reduced due to official recommendations and fear of the virus. Type 2 included modified ways of being socially active i.e., by deploying new technology, and in type 3, social contacts increased during the lockdown. In type 4, personal social networks were changed unexpectedly or dramatically due to a death of a spouse, for example. In type 5, we observed stable social networks, which had not been affected by the pandemic. At an individual level, one person could have had different types of changes during the pandemic. These results highlight the heterogeneity of the oldest olds' personal social networks and changes related to them during the exceptional times of the COVID-19 pandemic. Social activity and personal networks play an important role in the well-being of the oldest old, but individual situations, needs, and preferences toward personal social networks should be taken into account when planning social activities, policies, and interventions.
Background:
β-hydroxybutyrate (BHB) can upregulate brain-derived neurotrophic factor (BDNF) in mice, but little is known about the associations between BHB and BDNF in humans. The primary aim here ...was to investigate whether ketosis (i.e., raised BHB levels), induced by a ketogenic supplement, influences serum levels of mature BDNF (mBDNF) and its precursor proBDNF in healthy older adults. A secondary aim was to determine the intra-individual stability (repeatability) of those biomarkers, measured as intra-class correlation coefficients (ICC).
Method:
Three of the arms in a 6-arm randomized cross-over trial were used for the current sub-study. Fifteen healthy volunteers, 65–75 y, 53% women, were tested once a week. Test oils, mixed in coffee and cream, were ingested after a 12-h fast. Labeled by their level of ketosis, the arms provided: sunflower oil (lowK); coconut oil (midK); caprylic acid + coconut oil (highK). Repeated blood samples were collected for 4 h after ingestion. Serum BDNF levels were analyzed for changes from baseline to 1, 2 and 4 h to compare the arms. Individual associations between BHB and BDNF were analyzed cross-sectionally and for a delayed response (changes in BHB 0–2 h to changes in BDNF at 0–4 h). ICC estimates were calculated from baseline levels from the three study days.
Results:
proBDNF increased more in
highK
vs.
lowK
between 0 and 4 h (z-score: β = 0.25, 95% CI 0.07–0.44;
p
= 0.007). Individual change in BHB 0–2 h, predicted change in proBDNF 0–4 h, (β = 0.40, CI 0.12–0.67;
p
= 0.006). Change in mBDNF was lower in
highK
vs.
lowK
at 0–2 h (β = −0.88, CI −1.37 to −0.40;
p
< 0.001) and cumulatively 0–4 h (β = −1.01, CI −1.75 to −0.27;
p
= 0.01), but this could not be predicted by BHB levels. ICC was 0.96 (95% CI 0.92–0.99) for proBDNF, and 0.72 (CI 0.47–0.89) for mBDNF.
Conclusions:
The findings support a link between changes in peripheral BHB and proBDNF in healthy older adults. For mBDNF, changes differed between arms but independent to BHB levels. Replication is warranted due to the small sample. Excellent repeatability encourages future investigations on proBDNF as a predictor of brain health.
Clinical Trial Registration:
ClinicalTrials.gov
, NCT03904433.
We aimed to evaluate the feasibility of using real-world register data for identifying persons with mild Alzheimer’s disease (AD) and to describe their cognitive performance at the time of diagnosis. ...Patients diagnosed with AD during 2010–2013 (aged 60–81 years) were identified from the Finnish national health registers and enlarged with a smaller private sector sample (total
n
= 1,268). Patients with other disorders impacting cognition were excluded. Detailed clinical and cognitive screening data (the Consortium to Establish a Registry for Alzheimer’s Disease neuropsychological battery CERAD-nb) were obtained from local health records. Adequate cognitive data were available for 389 patients with mild AD (31%) of the entire AD group. The main reasons for not including patients in analyses of cognitive performance were AD diagnosis at a moderate/severe stage (
n
= 266, 21%), AD diagnosis given before full register coverage (
n
= 152, 12%), and missing CERAD-nb data (
n
= 139, 11%). The cognitive performance of persons with late-onset AD (
n
= 284), mixed cerebrovascular disease and AD (
n
= 51), and other AD subtypes (
n
= 54) was compared with that of a non-demented sample (
n
= 1980) from the general population. Compared with the other AD groups, patients with late-onset AD performed the worst in word list recognition, while patients with mixed cerebrovascular disease and AD performed the worst in constructional praxis and clock drawing tests. A combination of national registers and local health records can be used to collect data relevant for cognitive screening; today, the process is laborious, but it could be improved in the future with refined search algorithms and electronic data.
Pooling individual participant data to enable pooled analyses is often complicated by diversity in variables across available datasets. Therefore, recoding original variables is often necessary to ...build a pooled dataset. We aimed to quantify how much information is lost in this process and to what extent this jeopardizes validity of analyses results.
Data were derived from a platform that was developed to pool data from three randomized controlled trials on the effect of treatment of cardiovascular risk factors on cognitive decline or dementia. We quantified loss of information using the R-squared of linear regression models with pooled variables as a function of their original variable(s). In case the R-squared was below 0.8, we additionally explored the potential impact of loss of information for future analyses. We did this second step by comparing whether the Beta coefficient of the predictor differed more than 10% when adding original or recoded variables as a confounder in a linear regression model. In a simulation we randomly sampled numbers, recoded those < = 1000 to 0 and those >1000 to 1 and varied the range of the continuous variable, the ratio of recoded zeroes to recoded ones, or both, and again extracted the R-squared from linear models to quantify information loss.
The R-squared was below 0.8 for 8 out of 91 recoded variables. In 4 cases this had a substantial impact on the regression models, particularly when a continuous variable was recoded into a discrete variable. Our simulation showed that the least information is lost when the ratio of recoded zeroes to ones is 1:1.
Large, pooled datasets provide great opportunities, justifying the efforts for data harmonization. Still, caution is warranted when using recoded variables which variance is explained limitedly by their original variables as this may jeopardize the validity of study results.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background Multimodal lifestyle interventions can benefit overall health, including cognition, in populations at-risk for dementia. However, little is known about the effect of lifestyle ...interventions in patients with prodromal Alzheimer's disease (AD). Even less is known about dietary intake and adherence to dietary recommendations within this population making it difficult to design tailored interventions for them. Method A 6-month MIND-AD.sub.mini pilot randomized controlled trial (RCT) was conducted among 93 participants with prodromal AD in Sweden, Finland, Germany, and France. Three arms were included in the RCT: 1) multimodal lifestyle intervention (nutritional guidance, exercise, cognitive training, vascular/metabolic risk management, and social stimulation); 2) multimodal lifestyle intervention + medical food product; and 3) regular health advice (control group). Adherence to dietary advice was assessed with a brief food intake questionnaire by using the Healthy Diet Index (HDI) and Mediterranean Diet Adherence Screener (MEDAS). The intake of macro- and micronutrients were analyzed on a subsample using 3-day food records. Results The dietary quality in the intervention groups, pooled together, improved compared to that of the control group at the end of the study, as measured with by HDI (p = 0.026) and MEDAS (p = 0.008). The lifestyle-only group improved significantly more in MEDAS (p = 0.046) and almost significantly in HDI (p = 0.052) compared to the control group, while the lifestyle + medical food group improved in both HDI (p = 0.042) and MEDAS (p = 0.007) during the study. There were no changes in macro- or micronutrient intake for the intervention groups at follow-up; however, the intakes in the control group declined in several vitamins and minerals when adjusted for energy intake. Conclusion These results suggest that dietary intervention as part of multimodal lifestyle interventions is feasible and results in improved dietary quality in a population with prodromal AD. Nutrient intakes remained unchanged in the intervention groups while the control group showed a decreasing nutrient density. Trial registration ClinicalTrials.gov NCT03249688, 2017-07-08. Keywords: Nutrition, Alzheimer's disease, Dementia, Multimodal trial, Lifestyle, Prodromal Alzheimer's disease
Abstract Background The CAIDE (Cardiovascular Risk Factors, Aging, and Incidence of Dementia) Dementia Risk Score is a validated tool to predict late-life dementia risk (20 years later), based on ...midlife vascular risk factors. The goal was to render this prediction tool widely accessible. Methods The CAIDE Risk Score (mobile application) App was developed based on the CAIDE Dementia Risk Score, involving information on age, educational level, hypertension, hypercholesterolemia, obesity, and physical inactivity. Results The CAIDE Risk Score App is an evidence-based practical tool, which allows users to detect their individual risk, provides guidance for risk modification, and suggests consulting a health care practitioner if needed. Moreover, it allows practitioners to discuss preventive measures and monitor risk reduction. Conclusions The CAIDE Risk Score App is the first to predict the risk for dementia through an important evidence-based tool. The App can encourage users to actively decrease their modifiable risk factors and postpone cognitive impairment and dementia.
Individuals with early phase cognitive impairment are frequently affected by existential distress, social avoidance and associated health issues (including symptoms of stress, anxiety, and ...depression). The demand for efficient psychological support is crucial from both an individual and a societal perspective. We have developed a novel psychological intervention (Psychological Intervention tailored for Patients with Cognitive Impairment, PIPCI) manual for providing a non-medical path to enhanced psychological health in the cognitively impaired population. The current article provides specific information on the randomized controlled trial (RCT)-design and methods. The main hypothesis is that participants receiving PIPCI will increase their psychological flexibility (the ability to notice and accept interfering thoughts, emotions, and bodily sensations without acting on them, when this serves action in line with personal values) compared to participants in the active control (cognitive training) group and the waiting list control group. The secondary hypotheses are that participants receiving PIPCI will improve psychological health (stress measures, quality of life, depression, and general health) compared to participants in the active control group and the waiting list control group.
This three-arm RCT will recruit participants from the cognitive centers at Karolinska University Hospital in Stockholm and randomize approximately 120 individuals in the early phase of cognitive impairment to either an experimental group (psychological intervention once a week for 10 weeks), an active control group (cognitive training once a week for 10 weeks) or a waiting list control group. Intervention outcome will be evaluated with self-report questionnaires on physical and psychological aspects of health, cognitive assessment, biological markers (obtained from blood and saliva) and health care costs. Assessments will be performed at pre- (1 week before the interventions) and post-intervention (1 week after the interventions), as well as at a 6-month follow-up.
The development of a potentially feasible and effective psychological intervention tailored for early phase cognitive impairment (PIPCI) has the potential to advance the non-pharmacological intervention field. This is especially important given the extensive burden for many affected individuals and their families and the current lack of effective treatments. If the psychological intervention discussed here shows feasibility and efficacy, there is potential for far-reaching healthcare implications for patients with early cognitive impairment at risk of developing dementia.
ClinicalTrials.gov: NCT04356924. Date of registration: April 22, 2020. URL: https://clinicaltrials.gov/ct2/show/NCT04356924.
Research into dementia prevention is of paramount importance if the dementia epidemic is to be halted. Observational studies have identified several potentially modifiable risk factors for dementia, ...including hypertension, dyslipidaemia and obesity at midlife, diabetes mellitus, smoking, physical inactivity, depression and low levels of education. Randomized clinical trials are needed that investigate whether interventions targeting these risk factors can reduce the risk of cognitive decline and dementia in elderly adults, but such trials are methodologically challenging. To date, most preventive interventions have been tested in small groups, have focused on a single lifestyle factor and have yielded negative or modest results. Given the multifactorial aetiology of dementia and late-onset Alzheimer disease, multidomain interventions that target several risk factors and mechanisms simultaneously might be necessary for an optimal preventive effect. In the past few years, three large multidomain trials (FINGER, MAPT and PreDIVA) have been completed. The FINGER trial showed that a multidomain lifestyle intervention can benefit cognition in elderly people with an elevated risk of dementia. The primary results from the other trials did not show a statistically significant benefit of preventive interventions, but additional analyses among participants at risk of dementia showed beneficial effects of intervention. Overall, results from these three trials suggest that targeting of preventive interventions to at-risk individuals is an effective strategy. This Review discusses the current knowledge of lifestyle-related risk factors and results from novel trials aiming to prevent cognitive decline and dementia. Global initiatives are presented, including the World Wide FINGERS network, which aims to harmonize studies on dementia prevention, generate high-quality scientific evidence and promote its implementation.
The importance of early interventions in Alzheimer’s disease (AD) emphasizes the need to accurately and efficiently identify at-risk individuals. Although many dementia prediction models have been ...developed, there are fewer studies focusing on detection of brain pathology. We developed a model for identification of amyloid-PET positivity using data on demographics, vascular factors, cognition, APOE genotype, and structural MRI, including regional brain volumes, cortical thickness and a visual medial temporal lobe atrophy (MTA) rating. We also analyzed the relative importance of different factors when added to the overall model. The model used baseline data from the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) exploratory PET sub-study. Participants were at risk for dementia, but without dementia or cognitive impairment. Their mean age was 71 years. Participants underwent a brain 3T MRI and PiB-PET imaging. PiB images were visually determined as positive or negative. Cognition was measured using a modified version of the Neuropsychological Test Battery. Body mass index (BMI) and hypertension were used as cardiovascular risk factors in the model. Demographic factors included age, gender and years of education. The model was built using the Disease State Index (DSI) machine learning algorithm. Of the 48 participants, 20 (42%) were rated as Aβ positive. Compared with the Aβ negative group, the Aβ positive group had a higher proportion of APOE 4 carriers (53% vs. 14%), lower executive functioning, lower brain volumes, and higher visual MTA rating. AUC 95% CI for the complete model was 0.78 0.65–0.91. MRI was the most effective factor, especially brain volumes and visual MTA rating but not cortical thickness. APOE was nearly as effective as MRI in improving detection of amyloid positivity. The model with the best performance (AUC 0.82 0.71–0.93) was achieved by combining APOE and MRI. Our findings suggest that combining demographic data, vascular risk factors, cognitive performance, APOE genotype, and brain MRI measures can help identify Aβ positivity. Detecting amyloid positivity could reduce invasive and costly assessments during the screening process in clinical trials.
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