| 1. |
- 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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| 2. |
- Ashton, Nicholas J., et al.
(författare)
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Plasma levels of soluble TREM2 and neurofilament light chain in TREM2 rare variant carriers.
- 2019
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Ingår i: Alzheimer's research & therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Results from recent clinical studies suggest that cerebrospinal fluid (CSF) biomarkers that are indicative of Alzheimer's disease (AD) can be replicated in blood, e.g. amyloid-beta peptides (Aβ42 and Aβ40) and neurofilament light chain (NFL). Such data proposes that blood is a rich source of potential biomarkers reflecting central nervous system pathophysiology and should be fully explored for biomarkers that show promise in CSF. Recently, soluble fragments of the triggering receptor expressed on myeloid cells 2 (sTREM2) protein in CSF have been reported to be increased in prodromal AD and also in individuals with TREM2 rare genetic variants that increase the likelihood of developing dementia.In this study, we measured the levels of plasma sTREM2 and plasma NFL using the MesoScale Discovery and single molecule array platforms, respectively, in 48 confirmed TREM2 rare variant carriers and 49 non-carriers.Our results indicate that there are no changes in plasma sTREM2 and NFL concentrations between TREM2 rare variant carriers and non-carriers. Furthermore, plasma sTREM2 is not different between healthy controls, mild cognitive impairment (MCI) or AD.Concentrations of plasma sTREM2 do not mimic the recent changes found in CSF sTREM2.
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| 3. |
- 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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| 4. |
- Lleó, Alberto, et al.
(författare)
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Longitudinal cerebrospinal fluid biomarker trajectories along the Alzheimer's disease continuum in the BIOMARKAPD study
- 2019
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Ingår i: Alzheimer's & Dementia. - : Elsevier. - 1552-5260 .- 1552-5279. ; 15:6, s. 742-753
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Tidskriftsartikel (refereegranskat)abstract
- INTRODUCTION: Within-person trajectories of cerebrospinal fluid (CSF) biomarkers in Alzheimer's disease (AD) are not well defined.METHODS: We included 467 subjects from the BIOMARKAPD study with at least two serial CSF samples. Diagnoses were subjective cognitive decline (n = 75), mild cognitive impairment (n = 128), and AD dementia (n = 110), and a group of cognitively unimpaired subjects (n = 154) were also included. We measured baseline and follow-up CSF levels of total tau (t-tau), phosphorylated tau (p-tau), YKL-40, and neurofilament light (NfL). Median CSF sampling interval was 2.1 years.RESULTS: CSF levels of t-tau, p-tau, NfL, and YKL-40 were 2% higher per each year of baseline age in controls (P <.001). In AD, t-tau levels were 1% lower (P <.001) and p-tau levels did not change per each year of baseline age. Longitudinally, only NfL (P <.001) and YKL-40 (P <.02) increased during the study period.DISCUSSION: All four CSF biomarkers increase with age, but this effect deviates in AD for t-tau and p-tau.
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| 5. |
- 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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