| 1. |
- Bos, Isabelle, et al.
(författare)
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Cerebrovascular and amyloid pathology in predementia stages : the relationship with neurodegeneration and cognitive decline
- 2017
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Ingår i: Alzheimer's Research & Therapy. - : BioMed Central. - 1758-9193. ; 9:1
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Tidskriftsartikel (refereegranskat)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.
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| 2. |
- Bos, Isabelle, et al.
(författare)
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Correction to : Cerebrovascular and amyloid pathology in predementia stages
- 2018
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Ingår i: Alzheimer's Research & Therapy. - : BioMed Central. - 1758-9193. ; 10:56
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Tidskriftsartikel (refereegranskat)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.
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| 3. |
- Bos, Isabelle, et al.
(författare)
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The frequency and influence of dementia risk factors in prodromal Alzheimer's disease
- 2017
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Ingår i: Neurobiology of Aging. - : Elsevier. - 0197-4580 .- 1558-1497. ; 56, s. 33-40
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Tidskriftsartikel (refereegranskat)abstract
- We investigated whether dementia risk factors were associated with prodromal Alzheimer's disease (AD) according to the International Working Group-2 and National Institute of Aging-Alzheimer's Association criteria, and with cognitive decline. A total of 1394 subjects with mild cognitive impairment from 14 different studies were classified according to these research criteria, based on cognitive performance and biomarkers. We compared the frequency of 10 risk factors between the subgroups, and used Cox-regression to examine the effect of risk factors on cognitive decline. Depression, obesity, and hypercholesterolemia occurred more often in individuals with low-AD-likelihood, compared with those with a high-AD-likelihood. Only alcohol use increased the risk of cognitive decline, regardless of AD pathology. These results suggest that traditional risk factors for AD are not associated with prodromal AD or with progression to dementia, among subjects with mild cognitive impairment. Future studies should validate these findings and determine whether risk factors might be of influence at an earlier stage (i.e., preclinical) of AD.
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| 4. |
- Kim, Min, et al.
(författare)
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Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort
- 2019
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Ingår i: Alzheimer's & Dementia. - : Elsevier. - 1552-5260 .- 1552-5279. ; 15:6, s. 817-827
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: A critical and as-yet unmet need in Alzheimer's disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers.METHODS: This study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis.RESULTS: Eight metabolites were associated with amyloid β and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory.DISCUSSION: PFAMs have been found increased and associated with amyloid β burden in CSF and clinical measures.
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| 5. |
- Küçükali, Fahri, et al.
(författare)
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Whole-exome rare-variant analysis of Alzheimer's disease and related biomarker traits
- 2023
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Ingår i: Alzheimer's & Dementia. - : John Wiley & Sons. - 1552-5260 .- 1552-5279. ; 19:6, s. 2317-2331
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Despite increasing evidence of a role of rare genetic variation in the risk of Alzheimer's disease (AD), limited attention has been paid to its contribution to AD-related biomarker traits indicative of AD-relevant pathophysiological processes.METHODS: We performed whole-exome gene-based rare-variant association studies (RVASs) of 17 AD-related traits on whole-exome sequencing (WES) data generated in the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study (n = 450) and whole-genome sequencing (WGS) data from ADNI (n = 808).RESULTS: Mutation screening revealed a novel probably pathogenic mutation (PSEN1 p.Leu232Phe). Gene-based RVAS revealed the exome-wide significant contribution of rare coding variation in RBKS and OR7A10 to cognitive performance and protection against left hippocampal atrophy, respectively.DISCUSSION: The identification of these novel gene-trait associations offers new perspectives into the role of rare coding variation in the distinct pathophysiological processes culminating in AD, which may lead to identification of novel therapeutic and diagnostic targets.
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| 6. |
- Shi, Liu, et al.
(författare)
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Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology.
- 2020
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Ingår i: Journal of Alzheimer's disease : JAD. - : IOS Press. - 1875-8908 .- 1387-2877. ; 77:3, s. 1353-1368
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Tidskriftsartikel (refereegranskat)abstract
- Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown.We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes.We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677).We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts.Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.
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| 7. |
- Shi, Liu, et al.
(författare)
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Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay.
- 2019
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Ingår i: Alzheimer's & dementia : the journal of the Alzheimer's Association. - : Wiley. - 1552-5279 .- 1552-5260. ; 15:11, s. 1478-1488
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Tidskriftsartikel (refereegranskat)abstract
- Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins.4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid.A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization.The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.
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| 8. |
- Shi, Liu, et al.
(författare)
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Replication study of plasma proteins relating to Alzheimer's pathology.
- 2021
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Ingår i: Alzheimer's & dementia : the journal of the Alzheimer's Association. - : Wiley. - 1552-5279 .- 1552-5260. ; 17:9, s. 1452-1464
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Tidskriftsartikel (refereegranskat)abstract
- This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis.Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively.Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis.Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.
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| 9. |
- Stamate, Daniel, et al.
(författare)
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A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood : Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort
- 2019
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Ingår i: Alzheimer’s & Dementia. - : John Wiley & Sons. - 2352-8737. ; 5:C, s. 933-938
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Tidskriftsartikel (refereegranskat)abstract
- IntroductionMachine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers.MethodsThis study analyzed samples from 242 cognitively normal (CN) people and 115 with AD‐type dementia utilizing plasma metabolites (n = 883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV).ResultsOn the test data, DL produced the AUC of 0.85 (0.80–0.89), XGBoost produced 0.88 (0.86–0.89) and RF produced 0.85 (0.83–0.87). By comparison, CSF measures of amyloid, p‐tau and t‐tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively.DiscussionThis study showed that plasma metabolites have the potential to match the AUC of well‐established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders.
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| 10. |
- van Maurik, Ingrid S., et al.
(författare)
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Biomarker-based prognosis for people with mild cognitive impairment (ABIDE) : a modelling study
- 2019
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Ingår i: Lancet Neurology. - : The Lancet Publishing Group. - 1474-4422 .- 1474-4465. ; 18:11, s. 1034-1044
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia.METHODS: In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models-a demographics model, a hippocampal volume model, and a CSF biomarkers model-by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework.FINDINGS: We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59-0·65), validated hippocampal volume model (0·67, 0·62-0·72), and updated CSF biomarkers model (0·72, 0·68-0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71-0·76).INTERPRETATION: We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour.
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