| 1. |
- Jansen, Willemijn J, et al.
(author)
-
Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.
- 2022
-
In: JAMA neurology. - : American Medical Association (AMA). - 2168-6157 .- 2168-6149. ; 79:3, s. 228-243
-
Journal article (peer-reviewed)abstract
- One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Alzheimer disease biomarkers detected on PET or in CSF.Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Among the 19097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P=.04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P=.004), subjective cognitive decline (9%; 95% CI, 3%-15%; P=.005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P=.004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P=.18).This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.
|
|
| 2. |
- Bos, Isabelle, et al.
(author)
-
Cerebrovascular and amyloid pathology in predementia stages : the relationship with neurodegeneration and cognitive decline
- 2017
-
In: Alzheimer's Research & Therapy. - : BioMed Central. - 1758-9193. ; 9:1
-
Journal article (peer-reviewed)abstract
- BACKGROUND: Cerebrovascular disease (CVD) and amyloid-β (Aβ) often coexist, but their influence on neurodegeneration and cognition in predementia stages remains unclear. We investigated the association between CVD and Aβ on neurodegenerative markers and cognition in patients without dementia.METHODS: We included 271 memory clinic patients with subjective or objective cognitive deficits but without dementia from the BioBank Alzheimer Center Limburg cohort (n = 99) and the LeARN (n = 50) and DESCRIPA (n = 122) multicenter studies. CSF Aβ1-42 and white matter hyperintensities (WMH) on magnetic resonance imaging (MRI) scans were used as measures of Aβ and CVD, respectively. Individuals were classified into four groups based on the presence (+) or absence (-) of Aβ and WMH. We investigated differences in phosphorylated tau, total tau (t-tau), and medial temporal lobe atrophy (MTA) between groups using general linear models. We examined cognitive decline and progression to dementia using linear mixed models and Cox proportional hazards models. All analyses were adjusted for study and demographics.RESULTS: MTA and t-tau were elevated in the Aβ - WMH+, Aβ + WMH-, and Aβ + WMH+ groups. MTA was most severe in the Aβ + WMH+ group compared with the groups with a single pathology. Both WMH and Aβ were associated with cognitive decline, but having both pathologies simultaneously was not associated with faster decline.CONCLUSIONS: In the present study, we found an additive association of Aβ and CVD pathology with baseline MTA but not with cognitive decline. Because our findings may have implications for diagnosis and prognosis of memory clinic patients and for future scientific research, they should be validated in a larger sample with longer follow-up.
|
|
| 3. |
- Bos, Isabelle, et al.
(author)
-
Correction to : Cerebrovascular and amyloid pathology in predementia stages
- 2018
-
In: Alzheimer's Research & Therapy. - : BioMed Central. - 1758-9193. ; 10:56
-
Journal article (peer-reviewed)abstract
- Upon publication of this article [1], it was noticed that there were some inconsistencies in Tables 1, 2 and 3. Some of the superscript letters were incorrectly assigned. Please see below the correct tables.
|
|
| 4. |
- Haaksma, Miriam L., et al.
(author)
-
The Impact of Frailty and Comorbidity on Institutionalization and Mortality in Persons With Dementia : A Prospective Cohort Study
- 2019
-
In: Journal of the American Medical Directors Association. - : Elsevier BV. - 1525-8610 .- 1538-9375. ; 20:2, s. 165-170
-
Journal article (peer-reviewed)abstract
- Objectives: The predictive value of frailty and comorbidity, in addition to more readily available information, is not widely studied. We determined the incremental predictive value of frailty and comorbidity for mortality and institutionalization across both short and long prediction periods in persons with dementia.Design: Longitudinal clinical cohort study with a follow-up of institutionalization and mortality occurrence across 7 years after baseline.Setting and Participants: 331 newly diagnosed dementia patients, originating from 3 Alzheimer centers (Amsterdam, Maastricht, and Nijmegen) in the Netherlands, contributed to the Clinical Course of Cognition and Comorbidity (4C) Study.Measures: We measured comorbidity burden using the Cumulative Illness Rating Scale for Geriatrics (CIRS-G) and constructed a Frailty Index (FI) based on 35 items. Time-to-death and time-to-institutionalization from dementia diagnosis onward were verified through linkage to the Dutch population registry.Results: After 7 years, 131 patients were institutionalized and 160 patients had died. Compared with a previously developed prediction model for survival in dementia, our Cox regression model showed a significant improvement in model concordance (U) after the addition of baseline CIRS-G or FI when examining mortality across 3 years (FI: U = 0.178, P = .005, CIRS-G: U = 0.180, P = .012), but not for mortality across 6 years (FI: U = 0.068, P = .176, CIRS-G: U = 0.084, P = .119). In a competing risk regression model for time-to-institutionalization, baseline CIRS-G and FI did not improve the prediction across any of the periods.Conclusions: Characteristics such as frailty and comorbidity change over time and therefore their predictive value is likely maximized in the short term. These results call for a shift in our approach to prognostic modeling for chronic diseases, focusing on yearly predictions rather than a single prediction across multiple years. Our findings underline the importance of considering possible fluctuations in predictors over time by performing regular longitudinal assessments in future studies as well as in clinical practice.
|
|
| 5. |
- Damian, Marinella, et al.
(author)
-
Single-Domain Amnestic Mild Cognitive Impairment Identified by Cluster Analysis Predicts Alzheimer's Disease in the European Prospective DESCRIPA Study
- 2013
-
In: Dementia and Geriatric Cognitive Disorders. - : S. Karger AG. - 1420-8008 .- 1421-9824. ; 36:1-2, s. 1-19
-
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
|
|
| 6. |
- Haaksma, Miriam L., et al.
(author)
-
Cognitive and functional progression in Alzheimer disease : A prediction model of latent classes
- 2018
-
In: International Journal of Geriatric Psychiatry. - : Wiley. - 0885-6230 .- 1099-1166. ; 33:8, s. 1057-1064
-
Journal article (peer-reviewed)abstract
- Objective: We sought to replicate a previously published prediction model for progression, developed in the Cache County Dementia Progression Study, using a clinical cohort from the National Alzheimer's Coordinating Center.Methods: We included 1120 incident Alzheimer disease (AD) cases with at least one assessment after diagnosis, originating from 31 AD centres from the United States. Trajectories of the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating sum of boxes (CDR-sb) were modelled jointly over time using parallel-process growth mixture models in order to identify latent classes of trajectories. Bias-corrected multinomial logistic regression was used to identify baseline predictors of class membership and compare these with the predictors found in the Cache County Dementia Progression Study.Results: The best-fitting model contained 3 classes: Class 1 was the largest (63%) and showed the slowest progression on both MMSE and CDR-sb; classes 2 (22%) and 3 (15%) showed moderate and rapid worsening, respectively. Significant predictors of membership in classes 2 and 3, relative to class 1, were worse baseline MMSE and CDR-sb, higher education, and lack of hypertension. Combining all previously mentioned predictors yielded areas under the receiver operating characteristic curve of 0.70 and 0.75 for classes 2 and 3, respectively, relative to class 1.Conclusions: Our replication study confirmed that it is possible to predict trajectories of progression in AD with relatively good accuracy. The class distribution was comparable with that of the original study, with most individuals being members of a class with stable or slow progression. This is important for informing newly diagnosed AD patients and their caregivers.
|
|
| 7. |
- Haaksma, Miriam L., et al.
(author)
-
Comorbidity and progression of late onset Alzheimer's disease : A systematic review
- 2017
-
In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:5
-
Research review (peer-reviewed)abstract
- BackgroundAlzheimer's disease is a neurodegenerative syndrome characterized by multiple dimensions including cognitive decline, decreased daily functioning and psychiatric symptoms. This systematic review aims to investigate the relation between somatic comorbidity burden and progression in late-onset Alzheimer's disease (LOAD).MethodsWe searched four databases for observational studies that examined cross-sectional or longitudinal associations of cognitive or functional or neuropsychiatric outcomes with comorbidity in individuals with LOAD. From the 7966 articles identified originally, 11 studies were included in this review. The Newcastle-Ottawa quality assessment was used. The large variation in progression measures, comorbidity indexes and study designs hampered the ability to perform a meta-analysis. This review was registered with PROSPERO under DIO: 10.15124/CRD42015027046.ResultsNine studies indicated that comorbidity burden was associated with deterioration in at least one of the three dimensions of LOAD examined. Seven out of ten studies investigating cognition found comorbidities to be related to decreased cognitive performance. Five out of the seven studies investigating daily functioning showed an association between comorbidity burden and decreased daily functioning. Neuropsychiatric symptoms (NPS) increased with increasing comorbidity burden in two out of three studies investigating NPS. Associations were predominantly found in studies analyzing the association cross-sectionally, in a time-varying manner or across short follow-up (<= 2 years). Rarely baseline comorbidity burden appeared to be associated with outcomes in studies analyzing progression over longer follow-up periods (>2 years).Conclusion This review provides evidence of an association between somatic comorbidities and multifaceted LOAD progression. Given that time-varying comorbidity burden, but much less so baseline comorbidity burden, was associated with the three dimensions prospectively, this relationship cannot be reduced to a simple cause-effect relation and is more likely to be dynamic. Therefore, both future studies and clinical practice may benefit from regarding comorbidity as a modifiable factor with a possibly fluctuating influence on LOAD.
|
|
| 8. |
- Haaksma, Miriam L., et al.
(author)
-
Predicting Cognitive and Functional Trajectories in People With Late-Onset Dementia : 2 Population-Based Studies
- 2019
-
In: Journal of the American Medical Directors Association. - : Elsevier BV. - 1525-8610 .- 1538-9375. ; 20:11, s. 1444-1450
-
Journal article (peer-reviewed)abstract
- Objectives: Previous studies have shown large heterogeneity in the progression of dementia, both within and between patients. This heterogeneity offers an opportunity to limit the global and individual burden of dementia through the identification of factors associated with slow disease progression in dementia. We explored the heterogeneity in dementia progression to detect disease, patient, and social context factors related to slow progression. Design: Two longitudinal population-based cohort studies with follow-up across 12 years. Setting and Participants: 512 people with incident dementia from Stockholm (Sweden) contributed to the Kungsholmen Project and the Swedish National Study of Aging and Care in Kungsholmen. Methods: We measured cognition using the Mini-Mental State Examination and daily functioning using the Katz Activities of Daily Living Scale. Latent classes of trajectories were identified using a bivariate growth mixture model. We then used bias-corrected logistic regression to identify predictors of slower progression. Results: Two distinct groups of progression were identified; 76% (n = 394) of the people with dementia exhibited relatively slow progression on both cognition and daily functioning, whereas 24% (n = 118) demonstrated more rapid worsening on both outcomes. Predictors of slower disease progression were Alzheimer's disease (AD) dementia type [odds ratio (OR) 2.07, 95% confidence interval (CI) 1.15-3.71], lower age (OR 0.88, 95% CI 0.83-0.94), fewer comorbidities (OR 0.77, 95% CI 0.66-0.90), and a stronger social network (OR 1.72, 95% CI 1.01-2.93). Conclusions/Implications: Lower age, AD dementia type, fewer comorbidities, and a good social network appear to be associated with slow cognitive and functional decline. These factors may help to improve the counseling of patients and caregivers and to optimize the planning of care in dementia.
|
|
| 9. |
- Vermeiren, Angelique P. A., et al.
(author)
-
The Association Between APOE epsilon 4 and Alzheimer-type Dementia Among Memory Clinic Patients is Confined to those with a Higher Education. The DESCRIPA Study
- 2013
-
In: Journal of Alzheimer's Disease. - 1387-2877 .- 1875-8908. ; 35:2, s. 241-246
-
Journal article (peer-reviewed)abstract
- We assessed the interaction between the APOE epsilon 4 allele and education level in the etiology of Alzheimer's disease (AD) among memory clinic patients from the multicenter DESCRIPA study. Subjects (n = 544) were followed for 1 to 5 years. We used Cox's stratified survival modeling, adjusted for age, gender, and center. APOE epsilon 4 predicted the onset of AD-type dementia in middle (HR 3.45 95% CI 1.79-6.65, n = 222) and high (HR 3.67 95% CI 1.36-9.89, n = 139) but not in low educated subjects (HR 0.81, 95% CI 0.38-1.72, n = 183). This suggests that mechanisms in developing Alzheimer-type dementia may differ between educational groups that raises questions related to Alzheimer-type dementia prevention.
|
|
