scholarly journals Synthesis aided structural determination of amyloid-β(1–15) glycopeptides, new biomarkers for Alzheimer's disease

2014 ◽  
Vol 50 (95) ◽  
pp. 15067-15070 ◽  
Author(s):  
Peng Wang ◽  
Jonas Nilsson ◽  
Gunnar Brinkmalm ◽  
Göran Larson ◽  
Xuefei Huang

The structure of an Aβ glycopeptide is determined, which is a potential biomarker for early diagnosis of Alzheimer's disease.

2021 ◽  
Vol 11 (2) ◽  
pp. 215
Author(s):  
Donovan A. McGrowder ◽  
Fabian Miller ◽  
Kurt Vaz ◽  
Chukwuemeka Nwokocha ◽  
Cameil Wilson-Clarke ◽  
...  

Alzheimer’s disease is a progressive, clinically heterogeneous, and particularly complex neurodegenerative disease characterized by a decline in cognition. Over the last two decades, there has been significant growth in the investigation of cerebrospinal fluid (CSF) biomarkers for Alzheimer’s disease. This review presents current evidence from many clinical neurochemical studies, with findings that attest to the efficacy of existing core CSF biomarkers such as total tau, phosphorylated tau, and amyloid-β (Aβ42), which diagnose Alzheimer’s disease in the early and dementia stages of the disorder. The heterogeneity of the pathophysiology of the late-onset disease warrants the growth of the Alzheimer’s disease CSF biomarker toolbox; more biomarkers showing other aspects of the disease mechanism are needed. This review focuses on new biomarkers that track Alzheimer’s disease pathology, such as those that assess neuronal injury (VILIP-1 and neurofilament light), neuroinflammation (sTREM2, YKL-40, osteopontin, GFAP, progranulin, and MCP-1), synaptic dysfunction (SNAP-25 and GAP-43), vascular dysregulation (hFABP), as well as CSF α-synuclein levels and TDP-43 pathology. Some of these biomarkers are promising candidates as they are specific and predict future rates of cognitive decline. Findings from the combinations of subclasses of new Alzheimer’s disease biomarkers that improve their diagnostic efficacy in detecting associated pathological changes are also presented.


2021 ◽  
pp. 1-12
Author(s):  
Heng Zhang ◽  
Diyang Lyu ◽  
Jianping Jia ◽  

Background: Synaptic degeneration has been suggested as an early pathological event that strongly correlates with severity of dementia in Alzheimer’s disease (AD). However, changes in longitudinal cerebrospinal fluid (CSF) growth-associated protein 43 (GAP-43) as a synaptic biomarker in the AD continuum remain unclear. Objective: To assess the trajectory of CSF GAP-43 with AD progression and its association with other AD hallmarks. Methods: CSF GAP-43 was analyzed in 788 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including 246 cognitively normal (CN) individuals, 415 individuals with mild cognitive impairment (MCI), and 127 with AD dementia based on cognitive assessments. The associations between a multimodal classification scheme with amyloid-β (Aβ), tau, and neurodegeneration, and changes in CSF GAP-43 over time were also analyzed. Results: CSF GAP-43 levels were increased at baseline in MCI and dementia patients, and increased significantly over time in the preclinical (Aβ-positive CN), prodromal (Aβ-positive MCI), and dementia (Aβ-positive dementia) stages of AD. Higher levels of CSF GAP-43 were also associated with higher CSF phosphorylated tau (p-tau) and total tau (t-tau), cerebral amyloid deposition and hypometabolism on positron emission tomography, the hippocampus and middle temporal atrophy, and cognitive performance deterioration at baseline and follow-up. Furthermore, CSF GAP-43 may assist in effectively predicting the probability of dementia onset at 2- or 4-year follow-up. Conclusion: CSF GAP-43 can be used as a potential biomarker associated with synaptic degeneration in subjects with AD; it may also be useful for tracking the disease progression and for monitoring the effects of clinical trials.


2020 ◽  
Vol 52 (4) ◽  
pp. 556-568 ◽  
Author(s):  
Sun Ah Park ◽  
Song Mi Han ◽  
Chae Eun Kim

Abstract Cerebrospinal fluid (CSF) biomarkers based on the core pathological proteins associated with Alzheimer’s disease (AD), i.e., amyloid-β (Aβ) and tau protein, are widely regarded as useful diagnostic biomarkers. However, a lack of biomarkers for monitoring the treatment response and indexing clinical severity has proven to be problematic in drug trials targeting Aβ. Therefore, new biomarkers are needed to track non-Aβ and non-tau pathology. Many proteins involved in the pathophysiological progression of AD have shown promise as new biomarkers. Neurodegeneration- and synapse-related biomarkers in CSF (e.g., neurofilament light polypeptide [NFL], neurogranin, and visinin-like protein 1) and blood (e.g., NFL) aid prediction of AD progress, as well as early diagnosis. Neuroinflammation, lipid dysmetabolism, and impaired protein clearance are considered important components of AD pathophysiology. Inflammation-related proteins in the CSF, such as progranulin, intercellular adhesion molecule 1, and chitinase-3-like protein 1 (YKL-40), are useful for the early detection of AD and can represent clinical severity. Several lipid metabolism-associated biomarkers and protein clearance-linked markers have also been suggested as candidate AD biomarkers. Combinations of subsets of new biomarkers enhance their utility in terms of broadly characterizing AD-associated pathological changes, thereby facilitating precise selection of susceptible patients and comprehensive monitoring of the treatment response. This approach could facilitate the development of effective treatments for AD.


2010 ◽  
Vol 223 (2) ◽  
pp. 366-370 ◽  
Author(s):  
P. Lewczuk ◽  
J. Kornhuber ◽  
E. Vanmechelen ◽  
O. Peters ◽  
I. Heuser ◽  
...  

2021 ◽  
Author(s):  
Letícia Freitas de Castro Silva ◽  
Elisa Pinheiro Weber ◽  
Gleice Silva Toledo ◽  
Josiane Fonseca Almeida

Introduction: Alzheimer’s disease (AD) is seen as the most important dementia, prevalent in the elderly over 60 years old. There is still no cure, and the pharmacological strategies are to delay the symptoms and development of the pathology. The pathophysiological mechanisms are: hyperphosphorylation of the tau protein and aggregation of amyloid-β. Update studies of the tested therapies target the main pathological mechanisms: accumulation of β amyloid (inhibitors and modulators of β-secretase and γ-secretase and active and passive anti-Aβ immunotherapies), tau protein (inhibition of abnormal hyperphosphorylation with GSK-3 inhibitors, passive and active immunotherapies and the use of intrathecal antisense oligonucleotides (ASOs) and correction of the ApoE protein (increase lipidation, correct structure, clearance of non-lipid ApoE and reduction of ApoE expression). Objectives and methodology: To develop a bibliographic review in order to address new drugs in the treatment of Alzheimer’s. Qualitative and descriptive study carried out by literary review with research on PubMed. Results: Several drugs have been tested in clinical trials, however, due to lack of effectiveness, none have been approved. Therefore, it’s important to understand the limitations of the tests developed as flaws in the methodology, insufficient understanding of the mechanisms involved and inclusion of patients in different stages of AD, so that future investigations can overcome these gaps. Conclusion: It’s important to investigate new pathophysiological mechanisms, as well as the factors that trigger AD. Diagnosis is essential, with further studies to identify new biomarkers of the disease that will also have an impact on the conduct of clinical trials.


2021 ◽  
Author(s):  
Maria Carolina Dalmasso ◽  
Martin Aran ◽  
Pablo Galeano ◽  
Silvia Perin ◽  
Patick Giavalisco ◽  
...  

Abstract Background: The metabolic routes altered in Alzheimer's disease (AD) brain are poorly understood. As the metabolic pathways are evolutionarily conserved, the metabolic profiles carried out in animal models of AD could be directly translated into human studiesMethods: We performed untargeted 1H-NMR metabolomics in hippocampus of McGill-R-Thy1-APP transgenic (Tg) rats, a model of AD-like cerebral amyloidosis. Three groups of 9 month-old rats were tested: hemizygous Tg+/-, displaying mild amyloid pathology characterized by intraneuronal amyloid β (iAβ) accumulation; homozygous Tg+/+, showing iAβ, senile plaques and neuroinflammation, and wild-type (WT). The translational potential of these findings was assessed in plasma of participants in the German longitudinal study on Aging, Cognition and Dementia (AgeCoDe), by targeted GC-EI/MS. Results: Eighteen metabolites were detected, three of them showed significant differences among genotypes, but only two were specifically assigned to a known molecule: nicotinamide adenine dinucleotide (NAD) and nicotinamide (Nam). Only Tg+/+ rats showed significantly decreased levels of total-NAD, NADH and NAD+ as compared to WT, and a significant increase in NAD+/NADH ratio, suggesting an alteration of the redox state, alongside the reduction of all forms of NAD. Transcript levels of NAD-consuming and NAD-synthesis enzymes were increased in both transgenic genotypes. Next, Nam and NAD were evaluated at the peripheral level in rat plasma, where NAD/H was undetectable, Nam levels were unchanged among genotypes, but Trigonelline (a metabolic product of Nam) was reduced in Tg+/+. While trigonelline was undetected, Nam was significantly reduced in AD demented patients respect to cognitively normal participants (controls). This finding in Nam was replicated in a second independent case-control sample drawn from the same AgeCoDe. Next, the predictive value of Nam on disease progression was analyzed. Herein, reduction of Nam levels was observed in AgeCoDe participants who progressed to AD dementia ~1 year after blood collection, whereas Nam level were not reduced in those who converted afterwards. Conclusions: This preclinical study suggests that dysregulation of NAD/Nam depends on cerebral amyloid burden, and support the hypothesis that changes observed in the hippocampus may be detected in plasma. Furthermore, the findings in AgeCoDe points toward the potential use of Nam as plasma biomarker for AD.


2016 ◽  
Vol 26 (4) ◽  
pp. 269-275 ◽  
Author(s):  
Sergey A. Kozin ◽  
Vladimir A. Mitkevich ◽  
Alexander A. Makarov

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