| 41. |
- Shi, L., et al.
(författare)
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Plasma Proteomic Biomarkers Relating to Alzheimer's Disease: A Meta-Analysis Based on Our Own Studies
- 2021
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Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media SA. - 1663-4365. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Background and Objective: Plasma biomarkers for the diagnosis and stratification of Alzheimer's disease (AD) are intensively sought. However, no plasma markers are well established so far for AD diagnosis. Our group has identified and validated various blood-based proteomic biomarkers relating to AD pathology in multiple cohorts. The study aims to conduct a meta-analysis based on our own studies to systematically assess the diagnostic performance of our previously identified blood biomarkers. Methods: To do this, we included seven studies that our group has conducted during the last decade. These studies used either Luminex xMAP or ELISA to measure proteomic biomarkers. As proteins measured in these studies differed, we selected protein based on the criteria that it must be measured in at least four studies. We then examined biomarker performance using random-effect meta-analyses based on the mean difference between biomarker concentrations in AD and controls (CTL), AD and mild cognitive impairment (MCI), MCI, and CTL as well as MCI converted to dementia (MCIc) and non-converted (MCInc) individuals. Results: An overall of 2,879 subjects were retrieved for meta-analysis including 1,053 CTL, 895 MCI, 882 AD, and 49 frontotemporal dementia (FTD) patients. Six proteins were measured in at least four studies and were chosen for meta-analyses for AD diagnosis. Of them, three proteins had significant difference between AD and controls, among which alpha-2-macroglobulin (A2M) and ficolin-2 (FCN2) increased in AD while fibrinogen gamma chain (FGG) decreased in AD compared to CTL. Furthermore, FGG significantly increased in FTD compared to AD. None of the proteins passed the significance between AD and MCI, or MCI and CTL, or MCIc and MCInc, although complement component 4 (CC4) tended to increase in MCIc individuals compared to MCInc. Conclusions: The results suggest that A2M, FCN2, and FGG are promising biomarkers to discriminate AD patients from controls, which are worthy of further validation.
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| 42. |
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| 44. |
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| 45. |
- Wallin, Anders, 1950, et al.
(författare)
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Biochemical markers in vascular cognitive impairment associated with subcortical small vessel disease - A consensus report.
- 2017
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Ingår i: BMC neurology. - : Springer Science and Business Media LLC. - 1471-2377. ; 17:1
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Forskningsöversikt (refereegranskat)abstract
- Vascular cognitive impairment (VCI) is a heterogeneous entity with multiple aetiologies, all linked to underlying vascular disease. Among these, VCI related to subcortical small vessel disease (SSVD) is emerging as a major homogeneous subtype. Its progressive course raises the need for biomarker identification and/or development for adequate therapeutic interventions to be tested. In order to shed light in the current status on biochemical markers for VCI-SSVD, experts in field reviewed the recent evidence and literature data.The group conducted a comprehensive search on Medline, PubMed and Embase databases for studies published until 15.01.2017. The proposal on current status of biochemical markers in VCI-SSVD was reviewed by all co-authors and the draft was repeatedly circulated and discussed before it was finalized.This review identifies a large number of biochemical markers derived from CSF and blood. There is a considerable overlap of VCI-SSVD clinical symptoms with those of Alzheimer's disease (AD). Although most of the published studies are small and their findings remain to be replicated in larger cohorts, several biomarkers have shown promise in separating VCI-SSVD from AD. These promising biomarkers are closely linked to underlying SSVD pathophysiology, namely disruption of blood-CSF and blood-brain barriers (BCB-BBB) and breakdown of white matter myelinated fibres and extracellular matrix, as well as blood and brain inflammation. The leading biomarker candidates are: elevated CSF/blood albumin ratio, which reflects BCB/BBB disruption; altered CSF matrix metalloproteinases, reflecting extracellular matrix breakdown; CSF neurofilment as a marker of axonal damage, and possibly blood inflammatory cytokines and adhesion molecules. The suggested SSVD biomarker deviations contrasts the characteristic CSF profile in AD, i.e. depletion of amyloid beta peptide and increased phosphorylated and total tau.Combining SSVD and AD biomarkers may provide a powerful tool to identify with greater precision appropriate patients for clinical trials of more homogeneous dementia populations. Thereby, biomarkers might promote therapeutic progress not only in VCI-SSVD, but also in AD.
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| 46. |
- Willemse, E. A. J., et al.
(författare)
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Pre-analytical stability of novel cerebrospinal fluid biomarkers
- 2019
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Ingår i: Clinica Chimica Acta. - : Elsevier BV. - 0009-8981. ; 497, s. 204-211
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Tidskriftsartikel (refereegranskat)abstract
- Stability of the cerebrospinal fluid (CSF) composition under different pre-analytical conditions is relevant for the diagnostic potential of biomarkers. Our aim was to examine the pre-analytical stability of promising CSF biomarkers that are currently evaluated for their discriminative use in various neurological diseases. Pooled CSF was aliquoted and experimentally exposed to delayed storage: 0, 1, 2, 4, 24, 72, or 168 h at 4 °C or room temperature (RT), or 1–4 months at −20 °C; or up to 7 freeze/thaw (f/t) cycles, before final storage at −80 °C. Eleven CSF biomarkers were screened using immunoassays, liquid chromatography, or enzymatic methods. Levels of neurogranin (truncP75), chitinase-3-like protein (YKL-40), beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), acetylcholinesterase (AChE) enzymatic activity, theobromine, secreted protein acidic and rich in cysteine-like 1 (SPARCL-1) and homovanillic acid (HVA) levels were not affected by the applied storage conditions. 3-Methoxy-4-hydroxyphenylglycol (MHPG) levels linearly and strongly decreased after 4 h at RT (−10%) or 24 h at 4 °C (−27%), and with 6% after every f/t cycle. 5-Methyltetrahydrofolate (5-MTHF) (−29% after 1 week at RT) and 5-hydroxyindoleacetic acid levels (5-HIAA) (−16% after 1 week at RT) were reduced and 3,4-dihydroxyphenylacetic acid (DOPAC) levels (+22% after 1 week at RT) increased, but only after >24 h at RT. Ten out of eleven potential CSF novel biomarkers showed very limited change under common storage and f/t conditions, suggesting that these CSF biomarkers can be trustfully tested under the pre-analytical conditions present across different cohorts. © 2019 Elsevier B.V.
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| 47. |
- Zhang, Y. T., et al.
(författare)
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Predicting AT(N) pathologies in Alzheimer's disease from blood-based proteomic data using neural networks
- 2022
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Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media SA. - 1663-4365. ; 14
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Tidskriftsartikel (refereegranskat)abstract
- Background and objective: Blood-based biomarkers represent a promising approach to help identify early Alzheimer's disease (AD). Previous research has applied traditional machine learning (ML) to analyze plasma omics data and search for potential biomarkers, but the most modern ML methods based on deep learning has however been scarcely explored. In the current study, we aim to harness the power of state-of-the-art deep learning neural networks (NNs) to identify plasma proteins that predict amyloid, tau, and neurodegeneration (AT[N]) pathologies in AD.Methods: We measured 3,635 proteins using SOMAscan in 881 participants from the European Medical Information Framework for AD Multimodal Biomarker Discovery study (EMIF-AD MBD). Participants underwent measurements of brain amyloid 13 (A13) burden, phosphorylated tau (p-tau) burden, and total tau (t-tau) burden to determine their AT(N) statuses. We ranked proteins by their association with A13, p-tau, t-tau, and AT(N), and fed the top 100 proteins along with age and apolipoprotein E (APOE) status into NN classifiers as input features to predict these four outcomes relevant to AD. We compared NN performance of using proteins, age, and APOE genotype with performance of using age and APOE status alone to identify protein panels that optimally improved the prediction over these main risk factors. Proteins that improved the prediction for each outcome were aggregated and nominated for pathway enrichment and protein-protein interaction enrichment analysis.Results: Age and APOE alone predicted A13, p-tau, t-tau, and AT(N) burden with area under the curve (AUC) scores of 0.748, 0.662, 0.710, and 0.795. The addition of proteins significantly improved AUCs to 0.782, 0.674, 0.734, and 0.831, respectively. The identified proteins were enriched in five clusters of AD-associated pathways including human immunodeficiency virus 1 infection, p53 signaling pathway, and phosphoinositide-3-kinase-protein kinase B/Akt signaling pathway.Conclusion: Combined with age and APOE genotype, the proteins identified have the potential to serve as blood-based biomarkers for AD and await validation in future studies. While the NNs did not achieve better scores than the support vector machine model used in our previous study, their performances were likely limited by small sample size.
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| 48. |
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| 49. |
- Gallagher, Michael D., et al.
(författare)
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TMEM106B is a genetic modifier of frontotemporal lobar degeneration with C9orf72 hexanucleotide repeat expansions
- 2014
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Ingår i: Acta Neuropathologica. - : Springer Science and Business Media LLC. - 0001-6322 .- 1432-0533. ; 127:3, s. 407-418
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Tidskriftsartikel (refereegranskat)abstract
- Hexanucleotide repeat expansions in chromosome 9 open reading frame 72 (C9orf72) have recently been linked to frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis, and may be the most common genetic cause of both neurodegenerative diseases. Genetic variants at TMEM106B influence risk for the most common neuropathological subtype of FTLD, characterized by inclusions of TAR DNA-binding protein of 43 kDa (FTLD-TDP). Previous reports have shown that TMEM106B is a genetic modifier of FTLD-TDP caused by progranulin (GRN) mutations, with the major (risk) allele of rs1990622 associating with earlier age at onset of disease. Here, we report that rs1990622 genotype affects age at death in a single-site discovery cohort of FTLD patients with C9orf72 expansions (n = 14), with the major allele correlated with later age at death (p = 0.024). We replicate this modifier effect in a 30-site international neuropathological cohort of FTLD-TDP patients with C9orf72 expansions (n = 75), again finding that the major allele associates with later age at death (p = 0.016), as well as later age at onset (p = 0.019). In contrast, TMEM106B genotype does not affect age at onset or death in 241 FTLD-TDP cases negative for GRN mutations or C9orf72 expansions. Thus, TMEM106B is a genetic modifier of FTLD with C9orf72 expansions. Intriguingly, the genotype that confers increased risk for developing FTLD-TDP (major, or T, allele of rs1990622) is associated with later age at onset and death in C9orf72 expansion carriers, providing an example of sign epistasis in human neurodegenerative disease.
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| 50. |
- Jansen, Willemijn J, et al.
(författare)
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Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.
- 2022
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Ingår i: JAMA neurology. - : American Medical Association (AMA). - 2168-6157 .- 2168-6149. ; 79:3, s. 228-243
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Tidskriftsartikel (refereegranskat)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 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (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.
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