Special Issue "Biomarkers of Alzheimer’s Disease: New Insights"

A special issue of Cells (ISSN 2073-4409). This special issue belongs to the section "Cellular Aging".

Deadline for manuscript submissions: 20 August 2022 | Viewed by 6319

Special Issue Editor

Prof. Dr. Ivana Delalle
E-Mail Website
Guest Editor
Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA 02118, USA
Interests: neuropathology; biomarkers of neurodegeneration
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Special Issue Information

Dear Colleagues,

Impaired cognitive function is a hallmark of Alzheimer’s disease (AD), and often one of the first symptoms. However, changes in cognitive function develop slowly over time and patients are diagnosed at an advanced stage of molecular pathology. The failure to diagnose AD, the most common form of dementia in the elderly, at an early stage of molecular pathology is considered to be the major reason why causative treatments have failed in clinical trials. Molecular biomarkers that could detect individuals at risk for developing AD and allow for timely intervention remain highly desirable. Cortical measurements of amyloid-beta and tau depositions via magnetic resonance imaging (MRI) and positron emission tomography (PET) are expensive and thus not accessible on the scale needed for a public health challenge such as AD. Large epidemiological studies provide a sufficient number of subjects to develop a robust classifier enabling the correlation of cognitive status in densely phenotyped individuals with molecular signatures obtained via systematic biobanking using reliable standard operating procedures. To that end, plasma P-tau217 levels in multiple international cohorts distinguished AD from other neurodegenerative diseases. Because the National Institute of Aging—Alzheimer’s Association research framework aims to define AD biologically, it also seeks to expand AD biomarkers according to the scientific progress in the field of AD pathogenesis.

Prof. Dr. Ivana Delalle
Guest Editor

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Keywords

  • plasma AD biomarkers
  • AD pathogenesis biomarkers
  • biomarkers of cognitive decline
  • biomarkers of neurodegeneration
  • epigenetic dysregulation
  • AD-risk genetic variants

Published Papers (6 papers)

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Research

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Article
NLRP1 Inflammasome Activation in the Hippocampal Formation in Alzheimer’s Disease: Correlation with Neuropathological Changes and Unbiasedly Estimated Neuronal Loss
Cells 2022, 11(14), 2223; https://doi.org/10.3390/cells11142223 - 17 Jul 2022
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Abstract
Neuroinflammation is one of the core pathological features of Alzheimer’s disease (AD) as both amyloid β (Aβ) and tau monomers and oligomers can trigger the long-term pro-inflammatory phenotype of microglial cells with consequent overactivation of the inflammasomes. To investigate the NLRP1 inflammasome activation [...] Read more.
Neuroinflammation is one of the core pathological features of Alzheimer’s disease (AD) as both amyloid β (Aβ) and tau monomers and oligomers can trigger the long-term pro-inflammatory phenotype of microglial cells with consequent overactivation of the inflammasomes. To investigate the NLRP1 inflammasome activation in AD, we analyzed the expression of NLRP1, ASC, cleaved gasdermin (cGSDMD), and active caspase-6 (CASP-6) proteins in each hippocampal subdivision (hilar part of CA3, CA2/3, CA1, subiculum) of postmortem tissue of 9 cognitively healthy controls (HC) and 11 AD patients whose disease duration varied from 3 to 7 years after the clinical diagnosis. The total number of neurons, along with the total number of neurofibrillary tangles (NFTs), were estimated in Nissl- and adjacent modified Bielschowsky-stained sections, respectively, using the optical disector method. The same 9 HC and 11 AD cases were additionally semiquantitatively analyzed for expression of IBA1, HLA-DR, and CD68 microglial markers. Our results show that the expression of NLRP1, ASC, and CASP-6 is present in a significantly greater number of hippocampal formation neurons in AD brains compared to controls, suggesting that the NLRP1 inflammasome is more active in the AD brain. None of the investigated inflammasome and microglial markers were found to correlate with the age of the subjects or the duration of AD. However, besides positive correlations with microglial IBA1 expression in the subiculum and with microglial CD68 expression in the CA1 field and subiculum in the AD group, the overall NLRP1 expression in the hippocampal formation was positively correlated with the number of NFTs, thus providing a causal link between neuroinflammation and neurofibrillary degeneration. The accumulation of AT8-immunoreactive phosphorylated tau proteins that we observed at nuclear pores of large pyramidal neurons of the Ammon’s horn further supports their role in the extent of neuronal dysfunction and degeneration in AD. This is important because unlike fibrillar amyloid-β deposits that are not related to dementia severity, total NFTs and neuron numbers in the hippocampal formation, especially in the CA1 field, are the best correlates of cognitive deterioration in both human brain aging and AD. Our findings also support the notion that the CA2 field vulnerability is strongly linked to specific susceptibilities to different tauopathies, including primary age-related tauopathy. Altogether, these findings contrast with reports of nonsignificant microglial activation in aged nonhuman primates and indicate that susceptibility to inflammasome activation may render the human brain comparatively more vulnerable to neurodegenerative changes and AD. In conclusion, our results confirm a key role of NLRP1 inflammasome in AD pathogenesis and suggest NLRP1 as a potential diagnostic marker and therapeutic target to slow or prevent AD progression. Full article
(This article belongs to the Special Issue Biomarkers of Alzheimer’s Disease: New Insights)
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Article
Identifying Blood Biomarkers for Dementia Using Machine Learning Methods in the Framingham Heart Study
Cells 2022, 11(9), 1506; https://doi.org/10.3390/cells11091506 - 30 Apr 2022
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Abstract
Blood biomarkers for dementia have the potential to identify preclinical disease and improve participant selection for clinical trials. Machine learning is an efficient analytical strategy to simultaneously identify multiple candidate biomarkers for dementia. We aimed to identify important candidate blood biomarkers for dementia [...] Read more.
Blood biomarkers for dementia have the potential to identify preclinical disease and improve participant selection for clinical trials. Machine learning is an efficient analytical strategy to simultaneously identify multiple candidate biomarkers for dementia. We aimed to identify important candidate blood biomarkers for dementia using three machine learning models. We included 1642 (mean 69 ± 6 yr, 53% women) dementia-free Framingham Offspring Cohort participants attending examination, 7 who had available blood biomarker data. We developed three machine learning models, support vector machine (SVM), eXtreme gradient boosting of decision trees (XGB), and artificial neural network (ANN), to identify candidate biomarkers for incident dementia. Over a mean 12 ± 5 yr follow-up, 243 (14.8%) participants developed dementia. In multivariable models including all 38 available biomarkers, the XGB model demonstrated the strongest predictive accuracy for incident dementia (AUC 0.74 ± 0.01), followed by ANN (AUC 0.72 ± 0.01), and SVM (AUC 0.69 ± 0.01). Stepwise feature elimination by random sampling identified a subset of the nine most highly informative biomarkers. Machine learning models confined to these nine biomarkers showed improved model predictive accuracy for dementia (XGB, AUC 0.76 ± 0.01; ANN, AUC 0.75 ± 0.004; SVM, AUC 0.73 ± 0.01). A parsimonious panel of nine candidate biomarkers were identified which showed moderately good predictive accuracy for incident dementia, although our results require external validation. Full article
(This article belongs to the Special Issue Biomarkers of Alzheimer’s Disease: New Insights)
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Article
Cerebrospinal Fluid EV Concentration and Size Are Altered in Alzheimer’s Disease and Dementia with Lewy Bodies
Cells 2022, 11(3), 462; https://doi.org/10.3390/cells11030462 - 28 Jan 2022
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Abstract
Alzheimer’s disease (AD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD) represent the three major neurodegenerative dementias characterized by abnormal brain protein accumulation. In this study, we investigated extracellular vesicles (EVs) and neurotrophic factors in the cerebrospinal fluid (CSF) of 120 subjects: [...] Read more.
Alzheimer’s disease (AD), dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD) represent the three major neurodegenerative dementias characterized by abnormal brain protein accumulation. In this study, we investigated extracellular vesicles (EVs) and neurotrophic factors in the cerebrospinal fluid (CSF) of 120 subjects: 36 with AD, 30 with DLB, 34 with FTD and 20 controls. Specifically, CSF EVs were analyzed by Nanoparticle Tracking Analysis and neurotrophic factors were measured with ELISA. We found higher EV concentration and lower EV size in AD and DLB groups compared to the controls. Classification tree analysis demonstrated EV size as the best parameter able to discriminate the patients from the controls (96.7% vs. 3.3%, respectively). The diagnostic performance of the EV concentration/size ratio resulted in a fair discrimination level with an area under the curve of 0.74. Moreover, the EV concentration/size ratio was associated with the p-Tau181/Aβ42 ratio in AD patients. In addition, we described altered levels of cystatin C and progranulin in the DLB and AD groups. We did not find any correlation between neurotrophic factors and EV parameters. In conclusion, the results of this study suggest a common involvement of the endosomal pathway in neurodegenerative dementias, giving important insight into the molecular mechanisms underlying these pathologies. Full article
(This article belongs to the Special Issue Biomarkers of Alzheimer’s Disease: New Insights)
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Article
NT1-Tau Is Increased in CSF and Plasma of CJD Patients, and Correlates with Disease Progression
Cells 2021, 10(12), 3514; https://doi.org/10.3390/cells10123514 - 13 Dec 2021
Cited by 2 | Viewed by 1081
Abstract
This study investigates the diagnostic and prognostic potential of different forms of tau in biofluids from patients with Creutzfeldt-Jakob disease (CJD). Extracellular tau, which is molecularly heterogeneous, was measured using ultra-sensitive custom-made Simoa assays for N-terminal (NT1), mid-region, and full-length tau. We assessed [...] Read more.
This study investigates the diagnostic and prognostic potential of different forms of tau in biofluids from patients with Creutzfeldt-Jakob disease (CJD). Extracellular tau, which is molecularly heterogeneous, was measured using ultra-sensitive custom-made Simoa assays for N-terminal (NT1), mid-region, and full-length tau. We assessed cross-sectional CSF and plasma from healthy controls, patients with Alzheimer’s disease (AD) and CJD patients. Then, we evaluated the correlation of the best-performing tau assay (NT1-tau) with clinical severity and functional decline (using the MRC Prion Disease Rating Scale) in a longitudinal CJD cohort (n = 145). In a cross-sectional study, tau measured in CSF with the NT1 and mid-region Simoa assays, separated CJD (n = 15) from AD (n = 18) and controls (n = 21) with a diagnostic accuracy (AUCs: 0.98–1.00) comparable to or better than neurofilament light chain (NfL; AUCs: 0.96–0.99). In plasma, NT1-measured tau was elevated in CJD (n = 5) versus AD (n = 15) and controls (n = 15). Moreover, in CJD plasma (n = 145) NT1-tau levels correlated with stage and rate of disease progression, and the effect on clinical progression was modified by the PRNP codon 129. Our findings suggest that plasma NT1-tau shows promise as a minimally invasive diagnostic and prognostic biomarker of CJD, and should be further investigated for its potential to monitor disease progression and response to therapies. Full article
(This article belongs to the Special Issue Biomarkers of Alzheimer’s Disease: New Insights)
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Review

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Review
Blood-Based Biomarkers for Alzheimer’s Disease Diagnosis and Progression: An Overview
Cells 2022, 11(8), 1367; https://doi.org/10.3390/cells11081367 - 17 Apr 2022
Cited by 1 | Viewed by 1483
Abstract
Alzheimer’s Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, [...] Read more.
Alzheimer’s Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ1–42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease. Full article
(This article belongs to the Special Issue Biomarkers of Alzheimer’s Disease: New Insights)
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Other

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Systematic Review
Central Auditory Functions of Alzheimer’s Disease and Its Preclinical Stages: A Systematic Review and Meta-Analysis
Cells 2022, 11(6), 1007; https://doi.org/10.3390/cells11061007 - 16 Mar 2022
Viewed by 816
Abstract
In 2020, 55 million people worldwide were living with dementia, and this number is projected to reach 139 million in 2050. However, approximately 75% of people living with dementia have not received a formal diagnosis. Hence, they do not have access to treatment [...] Read more.
In 2020, 55 million people worldwide were living with dementia, and this number is projected to reach 139 million in 2050. However, approximately 75% of people living with dementia have not received a formal diagnosis. Hence, they do not have access to treatment and care. Without effective treatment in the foreseeable future, it is essential to focus on modifiable risk factors and early intervention. Central auditory processing is impaired in people diagnosed with Alzheimer’s disease (AD) and its preclinical stages and may manifest many years before clinical diagnosis. This study systematically reviewed central auditory processing function in AD and its preclinical stages using behavioural central auditory processing tests. Eleven studies met the full inclusion criteria, and seven were included in the meta-analyses. The results revealed that those with mild cognitive impairment perform significantly worse than healthy controls within channel adaptive tests of temporal response (ATTR), time-compressed speech test (TCS), Dichotic Digits Test (DDT), Dichotic Sentence Identification (DSI), Speech in Noise (SPIN), and Synthetic Sentence Identification-Ipsilateral Competing Message (SSI-ICM) central auditory processing tests. In addition, this analysis indicates that participants with AD performed significantly worse than healthy controls in DDT, DSI, and SSI-ICM tasks. Clinical implications are discussed in detail. Full article
(This article belongs to the Special Issue Biomarkers of Alzheimer’s Disease: New Insights)
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