| 11. |
- Frisoni, G. B., et al.
(författare)
-
Strategic roadmap for an early diagnosis of Alzheimer's disease based on biomarkers
- 2017
-
Ingår i: Lancet Neurology. - 1474-4422 .- 1474-4465. ; 16:8, s. 661-676
-
Tidskriftsartikel (refereegranskat)abstract
- The diagnosis of Alzheimer's disease can be improved by the use of biological measures. Biomarkers of functional impairment, neuronal loss, and protein deposition that can be assessed by neuroimaging (ie, MRI and PET) or CSF analysis are increasingly being used to diagnose Alzheimer's disease in research studies and specialist clinical settings. However, the validation of the clinical usefulness of these biomarkers is incomplete, and that is hampering reimbursement for these tests by health insurance providers, their widespread clinical implementation, and improvements in quality of health care. We have developed a strategic five-phase roadmap to foster the clinical validation of biomarkers in Alzheimer's disease, adapted from the approach for cancer biomarkers. Sufficient evidence of analytical validity (phase 1 of a structured framework adapted from oncology) is available for all biomarkers, but their clinical validity (phases 2 and 3) and clinical utility (phases 4 and 5) are incomplete. To complete these phases, research priorities include the standardisation of the readout of these assays and thresholds for normality, the evaluation of their performance in detecting early disease, the development of diagnostic algorithms comprising combinations of biomarkers, and the development of clinical guidelines for the use of biomarkers in qualified memory clinics.
|
|
| 12. |
- Neumann, A., et al.
(författare)
-
Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer's disease CSF profile of neuronal injury and inflammation
- 2022
-
Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 27, s. 1990-1999
-
Tidskriftsartikel (refereegranskat)abstract
- Alzheimer's disease (AD) biomarkers represent several neurodegenerative processes, such as synaptic dysfunction, neuronal inflammation and injury, as well as amyloid pathology. We performed an exome-wide rare variant analysis of six AD biomarkers (beta-amyloid, total/phosphorylated tau, NfL, YKL-40, and Neurogranin) to discover genes associated with these markers. Genetic and biomarker information was available for 480 participants from two studies: EMIF-AD and ADNI. We applied a principal component (PC) analysis to derive biomarkers combinations, which represent statistically independent biological processes. We then tested whether rare variants in 9576 protein-coding genes associate with these PCs using a Meta-SKAT test. We also tested whether the PCs are intermediary to gene effects on AD symptoms with a SMUT test. One PC loaded on NfL and YKL-40, indicators of neuronal injury and inflammation. Four genes were associated with this PC: IFFO1, DTNB, NLRC3, and SLC22A10. Mediation tests suggest, that these genes also affect dementia symptoms via inflammation/injury. We also observed an association between a PC loading on Neurogranin, a marker for synaptic functioning, with GABBR2 and CASZ1, but no mediation effects. The results suggest that rare variants in IFFO1, DTNB, NLRC3, and SLC22A10 heighten susceptibility to neuronal injury and inflammation, potentially by altering cytoskeleton structure and immune activity disinhibition, resulting in an elevated dementia risk. GABBR2 and CASZ1 were associated with synaptic functioning, but mediation analyses suggest that the effect of these two genes on synaptic functioning is not consequential for AD development.
|
|
| 13. |
|
|
| 14. |
- Ranson, J. M., et al.
(författare)
-
Modifiable risk factors for dementia and dementia risk profiling. A user manual for Brain Health Services-part 2 of 6
- 2021
-
Ingår i: Alzheimers Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 13:1
-
Tidskriftsartikel (refereegranskat)abstract
- We envisage the development of new Brain Health Services to achieve primary and secondary dementia prevention. These services will complement existing memory clinics by targeting cognitively unimpaired individuals, where the focus is on risk profiling and personalized risk reduction interventions rather than diagnosing and treating late-stage disease. In this article, we review key potentially modifiable risk factors and genetic risk factors and discuss assessment of risk factors as well as additional fluid and imaging biomarkers that may enhance risk profiling. We then outline multidomain measures and risk profiling and provide practical guidelines for Brain Health Services, with consideration of outstanding uncertainties and challenges. Users of Brain Health Services should undergo risk profiling tailored to their age, level of risk, and availability of local resources. Initial risk assessment should incorporate a multidomain risk profiling measure. For users aged 39-64, we recommend the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) Dementia Risk Score, whereas for users aged 65 and older, we recommend the Brief Dementia Screening Indicator (BDSI) and the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI). The initial assessment should also include potentially modifiable risk factors including sociodemographic, lifestyle, and health factors. If resources allow, apolipoprotein E e4 status testing and structural magnetic resonance imaging should be conducted. If this initial assessment indicates a low dementia risk, then low intensity interventions can be implemented. If the user has a high dementia risk, additional investigations should be considered if local resources allow. Common variant polygenic risk of late-onset AD can be tested in middle-aged or older adults. Rare variants should only be investigated in users with a family history of early-onset dementia in a first degree relative. Advanced imaging with 18-fluorodeoxyglucose positron emission tomography (FDG-PET) or amyloid PET may be informative in high risk users to clarify the nature and burden of their underlying pathologies. Cerebrospinal fluid biomarkers are not recommended for this setting, and blood-based biomarkers need further validation before clinical use. As new technologies become available, advances in artificial intelligence are likely to improve our ability to combine diverse data to further enhance risk profiling. Ultimately, Brain Health Services have the potential to reduce the future burden of dementia through risk profiling, risk communication, personalized risk reduction, and cognitive enhancement interventions.
|
|
| 15. |
- Scheltens, P, et al.
(författare)
-
White matter changes on CT and MRI: an overview of visual rating scales. European Task Force on Age-Related White Matter Changes
- 1998
-
Ingår i: European neurology. - : S. Karger AG. - 0014-3022 .- 1421-9913. ; 39:2, s. 80-89
-
Tidskriftsartikel (refereegranskat)abstract
- Since the recognition of white matter changes on CT (leukoaraiosis), rating scales for the location and severity of white matter changes have been developed, mainly for research purposes, to investigate factors such as the relation with cognition, risk factors, and pathology. The main purpose of rating scales is to provide scores that can be used in statistical analyses. The development of the NINDS-AIREN criteria for vascular dementia have introduced a new application for these rating scales in investigating and delineating the amount of white matter changes on CT/MRI sufficient to fulfill the criteria. Furthermore, in Alzheimer’s disease, recognition of white matter changes may serve to delineate homogeneous groups and help to identify patients with different symptomatology. We reviewed the existing rating scales for CT and MRI and judged their properties and reliability. The ideal rating scale does not yet exist, but different rating scales may serve different purposes, for which some recommendations are made.
|
|
| 16. |
- ten Kate, M., et al.
(författare)
-
MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study
- 2018
-
Ingår i: Alzheimers Research & Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 10
-
Tidskriftsartikel (refereegranskat)abstract
- Background: With the shift of research focus towards the pre-dementia stage of Alzheimer's disease (AD), there is an urgent need for reliable, non-invasive biomarkers to predict amyloid pathology. The aim of this study was to assess whether easily obtainable measures from structural MRI, combined with demographic data, cognitive data and apolipoprotein E (APOE) epsilon 4 genotype, can be used to predict amyloid pathology using machine-learning classification. Methods: We examined 810 subjects with structural MRI data and amyloid markers from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, including subjects with normal cognition (CN, n = 337, age 66.5 +/- 72, 50% female, 27% amyloid positive), mild cognitive impairment (MCI, n = 375, age 69. 1 +/- 7.5, 53% female, 63% amyloid positive) and AD dementia (n = 98, age 67.0 +/- 7.7, 48% female, 97% amyloid positive). Structural MRI scans were visually assessed and Freesurfer was used to obtain subcortical volumes, cortical thickness and surface area measures. We first assessed univariate associations between MRI measures and amyloid pathology using mixed models. Next, we developed and tested an automated classifier using demographic, cognitive, MRI and APOE epsilon 4 information to predict amyloid pathology. A support vector machine (SVM) with nested 10-fold cross-validation was applied to identify a set of markers best discriminating between amyloid positive and amyloid negative subjects. Results: In univariate associations, amyloid pathology was associated with lower subcortical volumes and thinner cortex in AD-signature regions in CN and MCI. The multi-variable SVM classifier provided an area under the curve (AUC) of 0.81 +/- O. 07 in MCI and an AUC of 0.74 +/- 0.08 in CN. In CN, selected features for the classifier included APOE epsilon 4, age, memory scores and several MRI measures such as hippocampus, amygdala and accumbens volumes and cortical thickness in temporal and parahippocampal regions. In MCI, the classifier including demographic and APOE epsilon 4 information did not improve after additionally adding imaging measures. Conclusions: Amyloid pathology is associated with changes in structural MRI measures in CN and MCI. An automated classifier based on clinical, imaging and APOE epsilon 4 data can identify the presence of amyloid pathology with a moderate level of accuracy. These results could be used in clinical trials to pre-screen subjects for anti-amyloid therapies.
|
|
| 17. |
- Tijms, B. M., et al.
(författare)
-
Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics
- 2020
-
Ingår i: Brain. - : Oxford University Press (OUP). - 0006-8950 .- 1460-2156. ; 143, s. 3776-3792
-
Tidskriftsartikel (refereegranskat)abstract
- Alzheimer's disease is biologically heterogeneous, and detailed understanding of the processes involved in patients is critical for development of treatments. CSF contains hundreds of proteins, with concentrations reflecting ongoing (patho)physiological processes. This provides the opportunity to study many biological processes at the same time in patients. We studied whether Alzheimer's disease biological subtypes can be detected in CSF proteomics using the dual clustering technique non-negative matrix factorization. In two independent cohorts (EMIF-AD MBD and ADNI) we found that 705 (77% of 911 tested) proteins differed between Alzheimer's disease (defined as having abnormal amyloid, n=425) and controls (defined as having normal CSF amyloid and tau and normal cognition, n=127). Using these proteins for data-driven clustering, we identified three robust pathophysiological Alzheimer's disease subtypes within each cohort showing (i) hyperplasticity and increased BACE1 levels; (ii) innate immune activation; and (iii) blood-brain barrier dysfunction with low BACE1 levels. In both cohorts, the majority of individuals were labelled as having subtype 1 (80, 36% in EMIF-AD MBD; 117, 59% in ADNI), 71 (32%) in EMIF-AD MBD and 41 (21%) in ADNI were labelled as subtype 2, and 72 (32%) in EMIF-AD MBD and 39 (20%) individuals in ADNI were labelled as subtype 3. Genetic analyses showed that all subtypes had an excess of genetic risk for Alzheimer's disease (all P>0.01). Additional pathological comparisons that were available for a subset in ADNI suggested that subtypes showed similar severity of Alzheimer's disease pathology, and did not differ in the frequencies of co-pathologies, providing further support that found subtypes truly reflect Alzheimer's disease heterogeneity. Compared to controls, all non-demented Alzheimer's disease individuals had increased risk of showing clinical progression (all P<0.01). Compared to subtype 1, subtype 2 showed faster clinical progression after correcting for age, sex, level of education and tau levels (hazard ratio = 2.5; 95% confidence interval = 1.2, 5.1; P=0.01), and subtype 3 at trend level (hazard ratio = 2.1; 95% confidence interval = 1.0, 4.4; P=0.06). Together, these results demonstrate the value of CSF proteomics in studying the biological heterogeneity in Alzheimer's disease patients, and suggest that subtypes may require tailored therapy.
|
|
| 18. |
- van de Pol, L. A., et al.
(författare)
-
White matter hyperintensities and medial temporal lobe atrophy in clinical subtypes of mild cognitive impairment: the DESCRIPA study
- 2009
-
Ingår i: Journal of Neurology, Neurosurgery and Psychiatry. - : BMJ. - 1468-330X .- 0022-3050. ; 80:10, s. 1069-1074
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Clinical subtypes of mild cognitive impairment (MCI) may represent different underlying aetiologies. Methods: This European, multicentre, memory clinic based study (DESCRIPA) of non-demented subjects investigated whether MCI subtypes have different brain correlates on MRI and whether the relation between subtypes and brain pathology is modified by age. Using visual rating scales, medial temporal lobe atrophy (MTA) (0-4) and white matter hyperintensities (WMH) (0-30) were assessed. Results: Severity of MTA differed between MCI subtypes (p < 0.001), increasing from a mean of 0.8 (SD 0.7) in subjective complaints (n = 77) to 1.3 (0.8) in non-amnestic MCI (n = 93), and from 1.4 (0.9) in single domain amnestic MCI (n = 70) to 1.7 (0.9) in multiple domain amnestic MCI (n = 89). The association between MCI subtype and MTA was modified by age and mainly present in subjects >70 years of age. Severity of WMH did not differ between MCI subtypes (p = 0.21). However, the combination of MTA and WMH differed between MCI subtypes (p = 0.02) Conclusion: We conclude that MCI subtypes may have different brain substrates, especially in older subjects. Isolated MTA was mainly associated with amnestic MCI subtypes, suggesting AD as the underlying cause. In non-amnestic MCI, the relatively higher prevalence of MTA in combination with WMH may suggest a different pathophysiological origin.
|
|
| 19. |
|
|
| 20. |
|
|
