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- Reynish, E, et al.
(författare)
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The ICTUS Study: A Prospective longitudinal observational study of 1,380 AD patients in Europe. Study design and baseline characteristics of the cohort
- 2007
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Ingår i: Neuroepidemiology. - : S. Karger AG. - 1423-0208 .- 0251-5350. ; 29:1-2, s. 29-38
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Tidskriftsartikel (refereegranskat)abstract
- The long-term objective of the ICTUS study is to identify milestones in Alzheimer’s disease (AD) progression and to develop a model to predict disease course in individual AD patients in Europe. The secondary objectives are to describe the patterns of prescribing, and the socioeconomic impact of AD in Europe. Between 2003 and 2005 1,380 patients with probable AD were recruited in specialised (secondary care) clinics in 12 European countries. Their mean age was 76 years and they had a mean of 8.0 ± (SD) 4.6 years of education. Thirty-five percent were male. The mean MMSE score was 20.4 ± (SD) 4.0. Forty-three percent had very mild dementia (CDR 0.5) and 44% had mild dementia (CDR 1). All patients completed baseline evaluation and biannual follow-up is ongoing. The goals of the current study are to describe the specific methods for recruitment in this crosscultural setting and the characteristics of the inception ICTUS cohort, including clinical features, co-morbidity, neuropsychological performance, neuropsychiatric symptoms, functional impairment and social burden.
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- Banning, LCP, et al.
(författare)
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Determinants of Cross-Sectional and Longitudinal Health-Related Quality of Life in Memory Clinic Patients Without Dementia
- 2020
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Ingår i: Journal of geriatric psychiatry and neurology. - : SAGE Publications. - 0891-9887 .- 1552-5708. ; 33:5, s. 256-264
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Tidskriftsartikel (refereegranskat)abstract
- To identify determinants within 3 different domains (ie, somatic comorbidities, cognitive functioning, and neuropsychiatric symptoms [NPS]) of health-related quality of life (HRQoL) over time in memory clinic patients without dementia. Methods: This longitudinal multicenter cohort study with a 3-year observation period recruited 315 individuals (age: 69.8 ± 8.6, 64.4% males, Mini-Mental State Examination score 26.9 ± 2.6). A multivariable explanatory model was built using linear mixed effects models (forward selection per domain) to select determinants for self-perceived HRQoL over time, as measured by the EuroQoL-5D visual analogue scale (EQ VAS). Results: Mean HRQoL at study entry was 69.4 ± 15.6. The presence of agitation, appetite and eating abnormalities, and eyes/ears/nose (ie, sensory impairment) comorbidities were associated with a change in HRQoL over time. Agitation was most strongly associated with HRQoL over time. Conclusions: The association of somatic comorbidities and NPS in memory clinic patients with course of HRQoL shows that these should receive more awareness, detection, and monitoring by clinicians.
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- Bauermeister, S, et al.
(författare)
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The Dementias Platform UK (DPUK) Data Portal
- 2020
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Ingår i: European journal of epidemiology. - : Springer Science and Business Media LLC. - 1573-7284 .- 0393-2990. ; 35:6, s. 601-611
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Tidskriftsartikel (refereegranskat)abstract
- The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure ‘lab’ using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.
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- Bose, N, et al.
(författare)
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Data and sample sharing as an enabler for large-scale biomarker research and development: The EPND perspective
- 2022
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Ingår i: Frontiers in neurology. - : Frontiers Media SA. - 1664-2295. ; 13, s. 1031091-
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Tidskriftsartikel (refereegranskat)abstract
- Biomarker discovery, development, and validation are reliant on large-scale analyses of high-quality samples and data. Currently, significant quantities of data and samples have been generated by European studies on Alzheimer's disease (AD) and other neurodegenerative diseases (NDD), representing a valuable resource for developing biomarkers to support early detection of disease, treatment monitoring, and patient stratification. However, discovery of, access to, and sharing of data and samples from AD and NDD research are hindered both by silos that limit collaboration, and by the array of complex requirements for secure, legal, and ethical sharing. In this Perspective article, we examine key challenges currently hampering large-scale biomarker research, and outline how the European Platform for Neurodegenerative Diseases (EPND) plans to address them. The first such challenge is a fragmented landscape filled with technical barriers that make it difficult to discover and access high-quality samples and data in one location. A second challenge is related to the complex array of legal and ethical requirements that must be navigated by researchers when sharing data and samples, to ensure compliance with data protection regulations and research ethics. Another challenge is the lack of broad-scale collaboration and opportunities to facilitate partnerships between data and sample contributors and researchers, in addition to a lack of regulatory engagement early in the research process to enable validation of potential biomarkers. A further challenge facing projects is the need to remain sustainable beyond initial funding periods, ensuring data and samples are shared and reused, thereby driving further research and innovation. In addressing these challenges, EPND will enable an environment of faster and more disruptive research on diagnostics and disease-modifying therapies for Alzheimer's disease and other neurodegenerative diseases.
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- Dubbelman, MA, et al.
(författare)
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Decline in cognitively complex everyday activities accelerates along the Alzheimer's disease continuum
- 2020
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Ingår i: Alzheimer's research & therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 12:1, s. 138-
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundImpairment in daily functioning is a clinical hallmark of dementia. Difficulties with “instrumental activities of daily living” (IADL) seem to increase gradually over the course of Alzheimer’s disease (AD), before dementia onset. However, it is currently not well established how difficulties develop along the preclinical and prodromal stages of AD. We aimed to investigate the trajectories of decline in IADL performance, as reported by a study partner, along the early stages of AD.MethodsIn a longitudinal multicenter study, combining data from community-based and memory clinic cohorts, we included 1555 individuals (mean age 72.5 ± 7.8 years; 50% female) based on availability of amyloid biomarkers, longitudinal IADL data, and clinical information at baseline. Median follow-up duration was 2.1 years. All amyloid-positive participants (n = 982) were classified into the National Institute on Aging–Alzheimer’s Association (NIA-AA) clinical stages ranging from preclinical AD (1) to overt dementia (4+). Cognitively normal amyloid-negative individuals (n = 573) served as a comparison group. The total scores of three study-partner reported IADL questionnaires were standardized.ResultsThe rate of decline in cognitively normal (stage 1) individuals with and without abnormal amyloid did not differ (p = .453). However, from stage 2 onwards, decline was significantly faster in individuals on the AD continuum (B [95%CI] = − 0.32 [− 0.55, − 0.09],p = .007). The rate of decline increased with each successive stage: one standard deviation (SD) unit per year in stage 3 (− 1.06 [− 1.27, − 0.85],p < .001) and nearly two SD units per year in stage 4+ (1.93 [− 2.19, − 1.67],p < .001). Overall, results were similar between community-based and memory clinic study cohorts.ConclusionsOur results suggest that the rate of functional decline accelerates along the AD continuum, as shown by steeper rates of decline in each successive NIA-AA clinical stage. These results imply that incremental changes in function are a meaningful measure for early disease monitoring. Combined with the low-cost assessment, this advocates the use of these functional questionnaires for capturing the effects of early AD-related cognitive decline on daily life.
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- Hagenbeek, FA, et al.
(författare)
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Heritability estimates for 361 blood metabolites across 40 genome-wide association studies
- 2020
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1, s. 39-
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Tidskriftsartikel (refereegranskat)abstract
- Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2total), and the proportion of heritability captured by known metabolite loci (h2Metabolite-hits) for 309 lipids and 52 organic acids. Our study reveals significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h2Metabolite-hits estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.
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- Jongs, N, et al.
(författare)
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A framework for assessing neuropsychiatric phenotypes by using smartphone-based location data
- 2020
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Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1, s. 211-
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Tidskriftsartikel (refereegranskat)abstract
- The use of smartphone-based location data to quantify behavior longitudinally and passively is rapidly gaining traction in neuropsychiatric research. However, a standardized and validated preprocessing framework for deriving behavioral phenotypes from smartphone-based location data is currently lacking. Here, we present a preprocessing framework consisting of methods that are validated in the context of geospatial data. This framework aims to generate context-enriched location data by identifying stationary, non-stationary, and recurrent stationary states in movement patterns. Subsequently, this context-enriched data is used to derive a series of behavioral phenotypes that are related to movement. By using smartphone-based location data collected from 245 subjects, including patients with schizophrenia, we show that the proposed framework is effective and accurate in generating context-enriched location data. This data was subsequently used to derive behavioral readouts that were sensitive in detecting behavioral nuances related to schizophrenia and aging, such as the time spent at home and the number of unique places visited. Overall, our results indicate that the proposed framework reliably preprocesses raw smartphone-based location data in such a manner that relevant behavioral phenotypes of interest can be derived.
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