| 1. |
- Turunen, Merita, et al.
(författare)
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Computer-based cognitive training for older adults : Determinants of adherence
- 2019
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Ingår i: PLOS ONE. - San Fransisco, USA : Public Library Science. - 1932-6203. ; 14:7, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- The possibilities of computer-based cognitive training (CCT) in postponing the onset of dementia are currently unclear, but promising. Our aim is to investigate older adults ' adherence to a long-term CCT program, and which participant characteristics are associated with adherence to the CCT. This study was part of the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER). Participants were 60-77-year-old individuals with increased dementia risk, recruited from previous population-based studies. The participants included in this study (n = 631) had been randomized to receive a multi-domain lifestyle intervention, including CCT. The measure of adherence was the number of completed CCT sessions (max = 144) as continuous measure. Due to a substantial proportion of participants with 0 sessions, the zero inflated negative binomial regression analyses were used to enable assessment of both predictors of starting the training and predictors of completing a higher number of training sessions. Several cognitive, demographic, lifestyle, and health-related variables were examined as potential predictors of adherence to CCT. Altogether, 63% of the participants participated in the CCT at least once, 20% completed at least half of the training, and 12% completed all sessions. Previous experience with computers, being married or cohabiting, better memory performance, and positive expectations toward the study predicted greater odds for starting CCT. Previous computer use was the only factor associated with a greater number of training sessions completed. Our study shows that there is a large variation in adherence to a long-lasting CCT among older adults with an increased risk of dementia. The results indicate that encouraging computer use, and taking into account the level of cognitive functioning, may help boost adherence to CCT.
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| 2. |
- Ngandu, Tiia, et al.
(författare)
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Recruitment and Baseline Characteristics of Participants in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) : A Randomized Controlled Lifestyle Trial
- 2014
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI AG. - 1661-7827 .- 1660-4601. ; 11:9, s. 9345-9360
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Tidskriftsartikel (refereegranskat)abstract
- Our aim is to describe the study recruitment and baseline characteristics of the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) study population. Potential study participants (age 60-77 years, the dementia risk score >= 6) were identified from previous population-based survey cohorts and invited to the screening visit. To be eligible, cognitive performance measured at the screening visit had to be at the mean level or slightly lower than expected for age. Of those invited (n = 5496), 48% (n = 2654) attended the screening visit, and finally 1260 eligible participants were randomized to the intervention and control groups (1: 1). The screening visit non-attendees were slightly older, less educated, and had more vascular risk factors and diseases present. The mean (SD) age of the randomized participants was 69.4 (4.7) years, Mini-Mental State Examination 26.7 (2.0) points, systolic blood pressure 140.1 (16.2) mmHg, total serum cholesterol 5.2 (1.0) mmol/L for, and fasting glucose 6.1 (0.9) mmol/L for, with no difference between intervention and control groups. Several modifiable risk factors were present at baseline indicating an opportunity for the intervention. The FINGER study will provide important information on the effect of lifestyle intervention to prevent cognitive impairment among at risk persons.
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| 3. |
- Antila, Kari, et al.
(författare)
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The PredictAD project : development of novel biomarkers and analysis software for early diagnosis of the Alzheimer's disease
- 2013
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Ingår i: Interface Focus. - : The Royal Society Publishing. - 2042-8898 .- 2042-8901. ; 3:2
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Tidskriftsartikel (refereegranskat)abstract
- Alzheimer's disease (AD) is the most common cause of dementia affecting 36 million people worldwide. As the demographic transition in the developed countries progresses towards older population, the worsening ratio of workers per retirees and the growing number of patients with age-related illnesses such as AD will challenge the current healthcare systems and national economies. For these reasons AD has been identified as a health priority, and various methods for diagnosis and many candidates for therapies are under intense research. Even though there is currently no cure for AD, its effects can be managed. Today the significance of early and precise diagnosis of AD is emphasized in order to minimize its irreversible effects on the nervous system. When new drugs and therapies enter the market it is also vital to effectively identify the right candidates to benefit from these. The main objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data, electrophysiological measurements of the brain and structural, functional and molecular brain images. We also designed and built a statistical model and a framework for exploiting these biomarkers with other available patient history and background data. We were able to discover several potential novel biomarker candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials.
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| 4. |
- Hibar, Derrek P., et al.
(författare)
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Novel genetic loci associated with hippocampal volume
- 2017
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (r(g) = -0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
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| 5. |
- Oresic, Matej, 1967-, et al.
(författare)
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Systems medicine and the integration of bioinformatic tools for the diagnosis of Alzheimer's disease
- 2010
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Ingår i: Genome Medicine. - : BioMed Central. - 1756-994X. ; 2:11
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Tidskriftsartikel (refereegranskat)abstract
- Because of the changes in demographic structure, the prevalence of Alzheimer's disease is expected to rise dramatically over the next decades. The progression of this degenerative and terminal disease is gradual, with the subclinical stage of illness believed to span several decades. Despite this, no therapy to prevent or cure Alzheimer's disease is currently available. Early disease detection is still important for delaying the onset of the disease with pharmacological treatment and/or lifestyle changes, assessing the efficacy of potential therapeutic agents, or monitoring disease progression more closely using medical imaging. Sensitive cerebrospinal-fluid-derived marker candidates exist, but given the invasiveness of sample collection their use in routine diagnostics may be limited. The pathogenesis of Alzheimer's disease is complex and poorly understood. There is thus a strong case for integrating information across multiple physiological levels, from molecular profiling (metabolomics, lipidomics, proteomics and transcriptomics) and brain imaging to cognitive assessments. To facilitate the integration of heterogeneous data, such as molecular and image data, sophisticated statistical approaches are needed to segment the image data and study their dependencies on molecular changes in the same individuals. Molecular profiling, combined with biophysical modeling of molecular assemblies associated with the disease, offer an opportunity to link the molecular pathway changes with cell- and tissue-level physiology and structure. Given that data acquired at different levels can carry complementary information about early Alzheimer's disease pathology, it is expected that their integration will improve early detection as well as our understanding of the disease.
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| 6. |
- van Wanrooij, Lennard L., et al.
(författare)
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Pooling individual participant data from randomized controlled trials : Exploring potential loss of information
- 2020
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:5
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Tidskriftsartikel (refereegranskat)abstract
- Background 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. Methods 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. Results 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. Conclusions 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.
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