| 1. |
- Altomare, Daniele, et al.
(author)
-
Prognostic value of Alzheimer’s biomarkers in mild cognitive impairment : the effect of age at onset
- 2019
-
In: Journal of Neurology. - : Springer Science and Business Media LLC. - 0340-5354 .- 1432-1459. ; 266:10, s. 2535-2545
-
Journal article (peer-reviewed)abstract
- Objective: The aim of this study is to assess the impact of age at onset on the prognostic value of Alzheimer’s biomarkers in a large sample of patients with mild cognitive impairment (MCI). Methods: We measured Aβ42, t-tau, hippocampal volume on magnetic resonance imaging (MRI) and cortical metabolism on fluorodeoxyglucose–positron emission tomography (FDG-PET) in 188 MCI patients followed for at least 1 year. We categorised patients into earlier and later onset (EO/LO). Receiver operating characteristic curves and corresponding areas under the curve (AUCs) were performed to assess and compar the biomarker prognostic performances in EO and LO groups. Linear Model was adopted for estimating the time-to-progression in relation with earlier/later onset MCI groups and biomarkers. Results: In earlier onset patients, all the assessed biomarkers were able to predict cognitive decline (p < 0.05), with FDG-PET showing the best performance. In later onset patients, all biomarkers but t-tau predicted cognitive decline (p < 0.05). Moreover, FDG-PET alone in earlier onset patients showed a higher prognostic value than the one resulting from the combination of all the biomarkers in later onset patients (earlier onset AUC 0.935 vs later onset AUC 0.753, p < 0.001). Finally, FDG-PET showed a different prognostic value between earlier and later onset patients (p = 0.040) in time-to-progression allowing an estimate of the time free from disease. Discussion: FDG-PET may represent the most universal tool for the establishment of a prognosis in MCI patients and may be used for obtaining an onset-related estimate of the time free from disease.
|
|
| 2. |
- Caroli, Anna, et al.
(author)
-
Mild cognitive impairment with suspected nonamyloid pathology (SNAP) Prediction of progression
- 2015
-
In: Neurology. - 0028-3878 .- 1526-632X. ; 84:5, s. 508-515
-
Journal article (peer-reviewed)abstract
- Objectives:The aim of this study was to investigate predictors of progressive cognitive deterioration in patients with suspected non-Alzheimer disease pathology (SNAP) and mild cognitive impairment (MCI).Methods:We measured markers of amyloid pathology (CSF -amyloid 42) and neurodegeneration (hippocampal volume on MRI and cortical metabolism on [F-18]-fluorodeoxyglucose-PET) in 201 patients with MCI clinically followed for up to 6 years to detect progressive cognitive deterioration. We categorized patients with MCI as A+/A- and N+/N- based on presence/absence of amyloid pathology and neurodegeneration. SNAPs were A-N+ cases.Results:The proportion of progressors was 11% (8/41), 34% (14/41), 56% (19/34), and 71% (60/85) in A-N-, A+N-, SNAP, and A+N+, respectively; the proportion of APOE epsilon 4 carriers was 29%, 70%, 31%, and 71%, respectively, with the SNAP group featuring a significantly different proportion than both A+N- and A+N+ groups (p 0.005). Hypometabolism in SNAP patients was comparable to A+N+ patients (p = 0.154), while hippocampal atrophy was more severe in SNAP patients (p = 0.002). Compared with A-N-, SNAP and A+N+ patients had significant risk of progressive cognitive deterioration (hazard ratio = 2.7 and 3.8, p = 0.016 and p < 0.001), while A+N- patients did not (hazard ratio = 1.13, p = 0.771). In A+N- and A+N+ groups, none of the biomarkers predicted time to progression. In the SNAP group, lower time to progression was correlated with greater hypometabolism (r = 0.42, p = 0.073).Conclusions:Our findings support the notion that patients with SNAP MCI feature a specific risk progression profile.
|
|
| 3. |
- Chertkow, H., et al.
(author)
-
An Action Plan to Face the Challenge of Dementia : INTERNATIONAL STATEMENT ON DEMENTIA from IAP for Health
- 2018
-
In: The Journal of Prevention of Alzheimer's Disease. - : EDITIONS SERDI. - 2274-5807 .- 2426-0266. ; 5:3, s. 207-212
-
Journal article (peer-reviewed)abstract
- An international committee set up through the IAP for Health met to develop an action plan for dementia. Comprehensive international and national initiatives should move forward with calls for action that include increased public awareness regarding brain health and dementia, support for a broad range of dementia research objectives, and investment in national health care systems to ensure timely competent person-centred care for individuals with dementia. The elements of such action plans should include: 1) Development of national plans including assessment of relevant lifecourse risk and protective factors; 2) Increased investments in national research programs on dementia with approximately 1% of the national annual cost of the disease invested; 3) Allocating funds to support a broad range of biomedical, clinical, and health service and systems research; 4) Institution of risk reduction strategies; 5) Building the required trained workforce (health care workers, teachers, and others) to deal with the dementia crisis; 6) Ensuring that it is possible to live well with dementia; and 7) Ensuring that all have access to prevention programs, care, and supportive living environments.
|
|
| 4. |
- Collij, Lyduine E., et al.
(author)
-
Spatial-Temporal Patterns of beta-Amyloid Accumulation A Subtype and Stage Inference Model Analysis
- 2022
-
In: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 0028-3878 .- 1526-632X. ; 98:17, s. E1692-E1703
-
Journal article (peer-reviewed)abstract
- Background and Objectives beta-amyloid (A beta) staging models assume a single spatial-temporal progression of amyloid accumulation. We assessed evidence for A beta accumulation subtypes by applying the data-driven Subtype and Stage Inference (SuStaIn) model to amyloid-PET data. Methods Amyloid-PET data of 3,010 participants were pooled from 6 cohorts (ALFA+, EMIF-AD, ABIDE, OASIS, and ADNI). Standardized uptake value ratios were calculated for 17 regions. We applied the SuStaIn algorithm to identify consistent subtypes in the pooled dataset based on the cross-validation information criterion and the most probable subtype/stage classification per scan. The effects of demographics and risk factors on subtype assignment were assessed using multinomial logistic regression. Results Participants were mostly cognitively unimpaired (n = 1890 [62.8%]), had a mean age of 68.72 (SD 9.1) years, 42.1% were APOE epsilon 4 carriers, and 51.8% were female. A 1-subtype model recovered the traditional amyloid accumulation trajectory, but SuStaIn identified 3 optimal subtypes, referred to as frontal, parietal, and occipital based on the first regions to show abnormality. Of the 788 (26.2%) with strong subtype assignment (>50% probability), the majority was assigned to frontal (n = 415 [52.5%]), followed by parietal (n = 199 [25.3%]) and occipital subtypes (n = 175 [22.2%]). Significant differences across subtypes included distinct proportions of APOE epsilon 4 carriers (frontal 61.8%, parietal 57.1%, occipital 49.4%), participants with dementia (frontal 19.7%, parietal 19.1%, occipital 31.0%), and lower age for the parietal subtype (frontal/occipital 72.1 years, parietal 69.3 years). Higher amyloid (Centiloid) and CSF p-tau burden was observed for the frontal subtype; parietal and occipital subtypes did not differ. At follow-up, most participants (81.1%) maintained baseline subtype assignment and 25.6% progressed to a later stage. Discussion Whereas a 1-trajectory model recovers the established pattern of amyloid accumulation, SuStaIn determined that 3 subtypes were optimal, showing distinct associations with Alzheimer disease risk factors. Further analyses to determine clinical utility are warranted.
|
|
| 5. |
|
|
| 6. |
- Jansen, Iris E, et al.
(author)
-
Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers.
- 2022
-
In: Acta neuropathologica. - : Springer Science and Business Media LLC. - 1432-0533 .- 0001-6322. ; 144:5, s. 821-842
-
Journal article (peer-reviewed)abstract
- Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n=8074; replication n=5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume.
|
|
| 7. |
|
|
| 8. |
- Le Guen, Yann, et al.
(author)
-
Multiancestry analysis of the HLA locus in Alzheimer's and Parkinson's diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes.
- 2023
-
In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences (PNAS). - 1091-6490 .- 0027-8424. ; 120:36
-
Journal article (peer-reviewed)abstract
- Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's disease (PD) and Alzheimer's disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.
|
|
| 9. |
- Prestia, Annapaola, et al.
(author)
-
Prediction of AD dementia by biomarkers following the NIA-AA and IWG diagnostic criteria in MCI patients from three European memory clinics
- 2015
-
In: Alzheimer's & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 11:10, s. 1191-1201
-
Journal article (peer-reviewed)abstract
- Introduction: Proposed diagnostic criteria (international working group and National Institute on Aging and Alzheimer's Association) for Alzheimer's disease (AD) include markers of amyloidosis (abnormal cerebrospinal fluid [CSF] amyloid beta [A beta]42) and neurodegeneration (hippocampal atrophy, temporo-parietal hypometabolism on [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET), and abnormal CSF tau). We aim to compare the accuracy of these biomarkers, individually and in combination, in predicting AD among mild cognitive impairment (MCI) patients. Methods: In 73 MCI patients, followed to ascertain AD progression, markers were measured. Sensitivity and specificity, positive (LR+) and negative (LR-) likelihood ratios, and crude and adjusted hazard ratios were computed. Results: Twenty-nine MCI patients progressed and 44 remained stable. Positivity to any marker achieved the lowest LR- (0.0), whereas the combination A beta 42 plus FDG-PET achieved the highest LR+ (6.45). In a survival analysis, positivity to any marker was associated with 100% conversion rate, whereas negativity to all markers was associated with 100% stability. Discussion: The best criteria combined amyloidosis and neurodegeneration biomarkers, whereas the individual biomarker with the best performance was FDG-PET.
|
|
| 10. |
- Prestia, Annapaola, et al.
(author)
-
Prediction of dementia in MCI patients based on core diagnostic markers for Alzheimer disease
- 2013
-
In: Neurology. - 0028-3878 .- 1526-632X. ; 80:11, s. 1048-1056
-
Journal article (peer-reviewed)abstract
- Objectives: The current model of Alzheimer disease (AD) stipulates that brain amyloidosis biomarkers turn abnormal earliest, followed by cortical hypometabolism, and finally brain atrophy ones. The aim of this study is to provide clinical evidence of the model in patients with mild cognitive impairment (MCI). Methods: A total of 73 patients with MCI from 3 European memory clinics were included. Brain amyloidosis was assessed by CSF A beta 42 concentration, cortical metabolism by an index of temporoparietal hypometabolism on FDG-PET, and brain atrophy by automated hippocampal volume. Patients were divided into groups based on biomarker positivity: 1) A beta 422- FDG-PET- Hippo-, 2) A beta 42+ FDG-PET- Hippo-, 3) A beta 42+ FDG-PET + Hippo-, 4) A beta 42+ FDG-PET+ Hippo+, and 5) any other combination not in line with the model. Measures of validity were prevalence of group 5, increasing incidence of progression to dementia with increasing biological severity, and decreasing conversion time. Results: When patients with MCI underwent clinical follow-up, 29 progressed to dementia, while 44 remained stable. A total of 26% of patients were in group 5. Incident dementia was increasing with greater biological severity in groups 1 to 5 from 4% to 27%, 64%, and 100% (p for trend, 0.0001), and occurred increasingly earlier (p for trend = 0.024). Conclusions: The core biomarker pattern is in line with the current pathophysiologic model of AD. Fully normal and fully abnormal pattern is associated with exceptional and universal development of dementia. Cases not in line might be due to atypical neurobiology or inaccurate thresholds for biomarker (ab) normality.
|
|
