| 1. |
- Damian, Marinella, et al.
(author)
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Single-Domain Amnestic Mild Cognitive Impairment Identified by Cluster Analysis Predicts Alzheimer's Disease in the European Prospective DESCRIPA Study
- 2013
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In: Dementia and Geriatric Cognitive Disorders. - : S. Karger AG. - 1420-8008 .- 1421-9824. ; 36:1-2, s. 1-19
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Journal article (peer-reviewed)abstract
- Background/Aims: To identify prodromal Alzheimer's disease (AD) subjects using a data-driven approach to determine cognitive profiles in mild cognitive impairment (MCI). Methods: A total of 881 MCI subjects were recruited from 20 memory clinics and followed for up to 5 years. Outcome measures included cognitive variables, conversion to AD, and biomarkers (e. g. CSF, and MRI markers). Two hierarchical cluster analyses (HCA) were performed to identify clusters of subjects with distinct cognitive profiles. The first HCA included all subjects with complete cognitive data, whereas the second one selected subjects with very mild MCI (MMSE >= 28). ANOVAs and ANCOVAs were computed to examine whether the clusters differed with regard to conversion to AD, and to AD-specific biomarkers. Results: The HCAs identified 4-cluster solutions that best reflected the sample structure. One cluster (aMCIsingle) had a significantly higher conversion rate (19%), compared to subjective cognitive impairment (SCI, p < 0.0001), and non-amnestic MCI (naMCI, p = 0.012). This cluster was the only one showing a significantly different biomarker profile (A beta(42), t-tau, APOE epsilon 4, and medial temporal atrophy), compared to SCI or naMCI. Conclusion: In subjects with mild MCI, the single-domain amnestic MCI profile was associated with the highest risk of conversion, even if memory impairment did not necessarily cross specific cut-off points. A cognitive profile characterized by isolated memory deficits may be sufficient to warrant applying prevention strategies in MCI, whether or not memory performance lies below specific z-scores. This is supported by our preliminary biomarker analyses. However, further analyses with bigger samples are needed to corroborate these findings. Copyright (C) 2013 S. Karger AG, Basel
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| 2. |
- Handels, Ron L. H., et al.
(author)
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Predicting progression to dementia in persons with mild cognitive impairment using cerebrospinal fluid markers
- 2017
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In: Alzheimer's & Dementia. - : Elsevier. - 1552-5260 .- 1552-5279. ; 13:8, s. 903-912
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Journal article (peer-reviewed)abstract
- INTRODUCTION: We aimed to determine the added value of cerebrospinal fluid (CSF) to clinical and imaging tests to predict progression from mild cognitive impairment (MCI) to any type of dementia.METHODS: The risk of progression to dementia was estimated using two logistic regression models based on 250 MCI participants: the first included standard clinical measures (demographic, clinical, and imaging test information) without CSF biomarkers, and the second included standard clinical measures with CSF biomarkers.RESULTS: Adding CSF improved predictive accuracy with 0.11 (scale from 0-1). Of all participants, 136 (54%) had a change in risk score of 0.10 or higher (which was considered clinically relevant), of whom in 101, it was in agreement with their dementia status at follow-up.DISCUSSION: An individual person's risk of progression from MCI to dementia can be improved by relying on CSF biomarkers in addition to recommended clinical and imaging tests for usual care.
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| 3. |
- Jekel, Katrin, et al.
(author)
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Mild cognitive impairment and deficits in instrumental activities of daily living: a systematic review.
- 2015
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In: Alzheimer's Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 7:1
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Research review (peer-reviewed)abstract
- Introduction: There is a growing body of evidence that subtle deficits in instrumental activities of daily living (IADL) may be present in mild cognitive impairment (MCI). However, it is not clear if there are IADL domains that are consistently affected across patients with MCI. In this systematic review, therefore, we aimed to summarize research results regarding the performance of MCI patients in specific IADL (sub)domains compared with persons who are cognitively normal and/or patients with dementia. Methods: The databases PsycINFO, PubMed and Web of Science were searched for relevant literature in December 2013. Publications from 1999 onward were considered for inclusion. Altogether, 497 articles were retrieved. Reference lists of selected articles were searched for potentially relevant articles. After screening the abstracts of these 497 articles, 37 articles were included in this review. Results: In 35 studies, IADL deficits (such as problems with medication intake, telephone use, keeping appointments, finding things at home and using everyday technology) were documented in patients with MCI. Financial capacity in patients with MCI was affected in the majority of studies. Effect sizes for group differences between patients with MCI and healthy controls were predominantly moderate to large. Performance-based instruments showed slight advantages (in terms of effect sizes) in detecting group differences in IADL functioning between patients with MCI, patients with Alzheimer’s disease and healthy controls. Conclusion: IADL requiring higher neuropsychological functioning seem to be most severely affected in patients with MCI. A reliable identification of such deficits is necessary, as patients with MCI with IADL deficits seem to have a higher risk of converting to dementia than patients with MCI without IADL deficits. The use of assessment tools specifically designed and validated for patients with MCI is therefore strongly recommended. Furthermore, the development of performance-based assessment instruments should be intensified, as they allow a valid and reliable assessment of subtle IADL deficits in MCI, even if a proxy is not available. Another important point to consider when designing new scales is the inclusion of technology-associated IADL. Novel instruments for clinical practice should be time-efficient and easy to administer.
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| 4. |
- Lleó, Alberto, et al.
(author)
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Cerebrospinal fluid biomarkers in trials for Alzheimer and Parkinson diseases.
- 2015
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In: Nature reviews. Neurology. - : Springer Science and Business Media LLC. - 1759-4766 .- 1759-4758. ; 11
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Research review (peer-reviewed)abstract
- Alzheimer disease (AD) and Parkinson disease (PD) are the most common neurodegenerative disorders. For both diseases, early intervention is thought to be essential to the success of disease-modifying treatments. Cerebrospinal fluid (CSF) can reflect some of the pathophysiological changes that occur in the brain, and the number of CSF biomarkers under investigation in neurodegenerative conditions has grown rapidly in the past 20 years. In AD, CSF biomarkers are increasingly being used in clinical practice, and have been incorporated into the majority of clinical trials to demonstrate target engagement, to enrich or stratify patient groups, and to find evidence of disease modification. In PD, CSF biomarkers have not yet reached the clinic, but are being studied in patients with parkinsonism, and are being used in clinical trials either to monitor progression or to demonstrate target engagement and downstream effects of drugs. CSF biomarkers might also serve as surrogate markers of clinical benefit after a specific therapeutic intervention, although additional data are required. It is anticipated that CSF biomarkers will have an important role in trials aimed at disease modification in the near future. In this Review, we provide an overview of CSF biomarkers in AD and PD, and discuss their role in clinical trials.
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| 5. |
- Mattsson, Niklas, 1979, et al.
(author)
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CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment.
- 2009
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In: JAMA : the journal of the American Medical Association. - : American Medical Association (AMA). - 1538-3598 .- 0098-7484. ; 302:4, s. 385-93
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Journal article (peer-reviewed)abstract
- CONTEXT: Small single-center studies have shown that cerebrospinal fluid (CSF) biomarkers may be useful to identify incipient Alzheimer disease (AD) in patients with mild cognitive impairment (MCI), but large-scale multicenter studies have not been conducted. OBJECTIVE: To determine the diagnostic accuracy of CSF beta-amyloid(1-42) (Abeta42), total tau protein (T-tau), and tau phosphorylated at position threonine 181 (P-tau) for predicting incipient AD in patients with MCI. DESIGN, SETTING, AND PARTICIPANTS: The study had 2 parts: a cross-sectional study involving patients with AD and controls to identify cut points, followed by a prospective cohort study involving patients with MCI, conducted 1990-2007. A total of 750 individuals with MCI, 529 with AD, and 304 controls were recruited by 12 centers in Europe and the United States. Individuals with MCI were followed up for at least 2 years or until symptoms had progressed to clinical dementia. MAIN OUTCOME MEASURES: Sensitivity, specificity, positive and negative likelihood ratios (LRs) of CSF Abeta42, T-tau, and P-tau for identifying incipient AD. RESULTS: During follow-up, 271 participants with MCI were diagnosed with AD and 59 with other dementias. The Abeta42 assay in particular had considerable intersite variability. Patients who developed AD had lower median Abeta42 (356; range, 96-1075 ng/L) and higher P-tau (81; range, 15-183 ng/L) and T-tau (582; range, 83-2174 ng/L) levels than MCI patients who did not develop AD during follow-up (579; range, 121-1420 ng/L for Abeta42; 53; range, 15-163 ng/L for P-tau; and 294; range, 31-2483 ng/L for T-tau, P < .001). The area under the receiver operating characteristic curve was 0.78 (95% confidence interval [CI], 0.75-0.82) for Abeta42, 0.76 (95% CI, 0.72-0.80) for P-tau, and 0.79 (95% CI, 0.76-0.83) for T-tau. Cut-offs with sensitivity set to 85% were defined in the AD and control groups and tested in the MCI group, where the combination of Abeta42/P-tau ratio and T-tau identified incipient AD with a sensitivity of 83% (95% CI, 78%-88%), specificity 72% (95% CI, 68%-76%), positive LR, 3.0 (95% CI, 2.5-3.4), and negative LR, 0.24 (95% CI, 0.21-0.28). The positive predictive value was 62% and the negative predictive value was 88%. CONCLUSIONS: This multicenter study found that CSF Abeta42, T-tau, and P-tau identify incipient AD with good accuracy, but less accurately than reported from single-center studies. Intersite assay variability highlights a need for standardization of analytical techniques and clinical procedures.
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| 6. |
- Reijs, Babette L R, et al.
(author)
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The Central Biobank and Virtual Biobank of BIOMARKAPD: A Resource for Studies on Neurodegenerative Diseases.
- 2015
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In: Frontiers in neurology. - : Frontiers Media SA. - 1664-2295. ; 6
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Journal article (peer-reviewed)abstract
- Biobanks are important resources for biomarker discovery and assay development. Biomarkers for Alzheimer's and Parkinson's disease (BIOMARKAPD) is a European multicenter study, funded by the EU Joint Programme-Neurodegenerative Disease Research, which aims to improve the clinical use of body fluid markers for the diagnosis and prognosis of Alzheimer's disease (AD) and Parkinson's disease (PD). The objective was to standardize the assessment of existing assays and to validate novel fluid biomarkers for AD and PD. To support the validation of novel biomarkers and assays, a central and a virtual biobank for body fluids and associated data from subjects with neurodegenerative diseases have been established. In the central biobank, cerebrospinal fluid (CSF) and blood samples were collected according to the BIOMARKAPD standardized pre-analytical procedures and stored at Integrated BioBank of Luxembourg. The virtual biobank provides an overview of available CSF, plasma, serum, and DNA samples at each site. Currently, at the central biobank of BIOMARKAPD samples are available from over 400 subjects with normal cognition, mild cognitive impairment (MCI), AD, frontotemporal dementia (FTD), vascular dementia, multiple system atrophy, progressive supranuclear palsy, PD, PD with dementia, and dementia with Lewy bodies. The virtual biobank contains information on over 8,600 subjects with varying diagnoses from 21 local biobanks. A website has been launched to enable sample requests from the central biobank and virtual biobank.
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