Aims

Locus coeruleus pathology is present in many neurodegenerative disorders. The resulting adrenergic decline contributes to low attentiveness, memory, and mood. Restoration of adrenergic impact for therapeutic benefit, remains a viable option, but approaches using activation of excitatory adrenoceptors, such as beta-ARs, are untested. Critical to development of new CNS therapeutics is evidence of target engagement. This study suggests that measuring changes in cerebral blood flow (CBF) may be a useful biomarker

Methods

The MRI-derived Pseudo-continuous ASL; (3T Siemens Magnetom Skyra) was used to measure CBF response to the β₂-AR agonist salbutamol in healthy subjects. Images were taken prior to and following infusion of salbutamol, either alone or after administration of the beta-blocker nadolol.

Results

Salbutamol infusion (0.3, 0.9 and 1.8mg IV) produced dose related increases in heart rate which were eliminated completely by prior treatment with nadolol.

Significant increases in thalamic perfusion were observed using ASL only with the 1.8 mg dose, with CBF increases from 40.0±6 to 50.6±9.4 ml/100g/min, an increase of 27.4% (P=0.0081). Despite producing almost equivalent HR increases, the 0.9 mg dose failed to produce increases in thalamic CBF. Pre-treatment with nadolol only partially attenuated the CBF response.

Conclusions

β₂-AR activation with salbutamol increases thalamic perfusion in healthy participants. This effect seems unrelated to peripheral cardiovascular effects and is only moderately sensitive to the beta blocker nadolol. Given that ASL has revealed reductions in CBF in brains of patients with AD, the increases seen with salbutamol may represent clinically relevant signals of receptor engagement in the brain

Aims

The identification of clinically useful biomarkers for Alzheimer’s disease (AD) from blood is a long-standing goal. Here we report the use of a platform for untargeted plasma protein profiling, Proteograph, to identify candidate protein biomarkers from plasma for AD and Mild Cognitive Impairment (MCI).

Methods

Plasma samples from 200 subjects comprising 50 AD, 50 MCI, and 100 controls were profiled using a recently reported plasma protein profiling platform, Proteograph¹. Using a 5-nanoparticle panel and 85 µL of plasma per nanoparticle, proteins were quantified by data-independent acquisition (DIA) liquid-chromatography mass-spectrometry (LC-MS) in about 6 weeks. Normalized peptide intensities were used in ten rounds of 10-fold cross-validation to develop random forest models for class discrimination.

Results

Across the samples, 2,391 plasma proteins were detected, with 2,085 in at least 25%. 36 proteins with the highest AD OpenTargets² score were detected, including Amyloid Beta (A4) Precursor Protein. 25,593 protein-comprising peptides were detected, with 15,661 in at least 25% of the samples. Univariate analysis identified 441 and 526 proteins that were significantly different in AD or MCI versus control, respectively. Random-forest classification for AD and MCI produced ROC AUCs that were at least 0.90. Top features by importance included known and unknown candidate biomarkers.

Conclusions

These analyses have identified novel combinations of candidate plasma protein markers, many without prior known relevance to AD. More broadly, the Proteograph platform confirmed its ability to generate profiling data in a deep, broad, and rapid fashion, enabling large-scale studies to detect novel insights with clinically useful potential.

Aims

Identification of evolution of Aβ proteins from monomer with few nanometer size to fibrils upto hundreds micrometers in diameter and to finally regress to Alzheimer’s disease (AD) has not been addressed to date. Furthermore, pathophysiology associated with biophysical or structural conformation of Aβ proteins are not clearly understood until now. Here, we identified the Aβ aggregation states by dementia quotient (DQ) constant with terahertz (THz) spectroscopy without any label.

Methods

We clearly distinguished the Aβ fibrillization stages in vitro from near-field THz conductance measurements by controlling the solution thickness and the mole concentration of proteins in buffer solution. Three form of Aβ proteins; monomer, oligomer, and fibril, were embedded between two sapphire plates with 100μm thickness and were measured its transmittance signal by THz range of light under the THz spectroscope. After optical conductance analysis, by extracting the localization constant (De) from the modified Drude-Smith model, G(ω) = G(0)/ 1-iωt [1- De/(1-iωt)], where dementia quotient (- De) is exclusively identified from Aβ structural property.

Results

As a result, the DQ value is around 1 in fibril, around 0.64 in oligomer, and nearly zero in monomer, independent of Aβ concentrations [ref].

Conclusions

Our result suggests a paradigm shift in the AD diagnosis since the DQ index is clearly identified the progressive stage of different Aβ protein structural states, which from monomer evolves to oligomer and reaches to fibrils, by using the label-free optical conductance measurement.

[ref] C. Heo et al., THz Conductance Measurement for Fibrilization of Amyloid Beta Protein. ACS NANO (2020). Inside cover selected.

Aims

Cerebrospinal fluid (CSF) total tau (t-tau) is an established Alzheimer’s disease (AD) biomarker, while plasma t-tau only shows a marginal change. This may be due to a rapid metabolism and fragmentation of tau in plasma. We aimed to develop alternative immunoassays targeting different N-terminal and mid-region tau fragments and to investigate their performance in AD and other neurological conditions.

Methods

Three ultrasensitive immunoassays targeting mid-region and N-terminal tau fragments were developed using Single molecule array (Simoa) technology. The pilot cohort consisted of paired CSF (35μl/assay) and plasma (70μl/assay) samples defined as AD (N=22) or controls (N=22) based on core AD CSF biomarkers. Samples were additionally analysed with the commercially available Simoa t-tau kit (Human Total Tau 2.0, Quanterix).

Results

In CSF, all N-terminal and mid-region tau fragments were increased in AD patients compared with controls (p<0.001 for all assays, Figure 1). ROC analysis showed that the mid-region and N-terminal A fragments were able to separate the groups with an AUC of 88% (95% CI: 77-100% and 75-100%), performing slightly better than the commercial assay (AUC 83%; 95% CI: 70-96%, Figure 2). However, no difference between groups was seen in plasma (p=0.48-0.68; AUC 54-57% for all assays).

Figure 1.Figure 2.

Conclusions

All t-tau assays detected significantly increased CSF tau levels in AD; however, plasma t-tau had limited value as a biomarker for AD pathology. Future experiments aim to investigate the presence and temporal course of different CSF tau fragments in larger cohorts including AD, and other neurological disorders, such as Creutzfeldt-Jakob disease and stroke.

Aims

The identification of protein aggregates as biomarkers for neurodegeneration is an area of interest for diagnosis and treatment development. In this work we present novel super luminescent conjugated polyelectrolyte compounds, oligo(p-phenylene ethynylene) polyelectrolytes (OPEs), as in vitro and ex vivo sensors for tau paired helical filaments.

Methods

Tau helical filaments (PHFs) were isolated from brain tissue of transgenic mice (TgF344AD) and frontal temporal dementia (FTD) patients. The use of two OPEs, anionic OPE₁^2- and cationic OPE₂⁴⁺, as in vitro sensors of tissue-derived tau PHFs and immunohistochemical stains for fibrillar tau pathology in transgenic mice and human FTD brain sections.

Results

OPE₁^2- sensitively detected of tau PHFs isolated from barin tissue in fluorimetry assays and displayed strong sensing of neurofibrillary tangles in brain tissue sections. OPE₂⁴⁺detected neurofibrillary tangles as well and with higher sensitivity. Both OPEs stained brain tissue samples with limited background staining. Both sensors outperformed the gold-standard dye Thioflavin T in sensing capacities while co-stained with conventional antibodies AT180.

Conclusions

OPEs readily and selectively bound tau aggregates in vitro and ex vivo. They are potential rapid tools for identifying neuropathological tau inclusions in the brain. Such OPEs can be useful in understanding pathogenesis and in creating in vivo diagnostically relevant detection tools for protein-misfolding neurodegenerative diseases.

Aims

Blood-based biomarkers providing an objective diagnosis of Parkinson's disease (PD) and its differentiation from other neurodegenerative disorders are of a great importance and still highly requested. This work is aimed to study whether plasma metabolomic profiling could provide informative and specific signatures in the diagnosis of this disease.

Methods

Herein, an approach based on Fourier-transform mid-infrared (FTIR-MIR) spectroscopy combined with a two-step classification strategy based on a stepwise orthogonalization of predictors (SELECT) and Linear Discriminant Analysis (LDA) was studied to identify metabolomic markers in human plasma. Analysis were carried out on subjects with early stage of PD, those with PD related dementia, controls and patients with Alzheimer's disease (AD).

Results

2 classification models were performed. The first model permitted the differentiation between 3 holistic categories: PD patients (regardless of disease’s stage) from subjects affected by Alzheimer's disease (AD) as well as from healthy subjects. A total of 30 spectra markers were identified providing 100% in classification and 93% in prediction rates, respectively. The effectiveness of discrimination ability was confirmed performing prediction with an external set. The second model based on 15 markers enabled further differentiation between 2 Parkinson’s sub-groups (early-stage PD and PD-related dementia) achieving 100% in both classification and prediction rates.

Conclusions

This developed classification approach characterized by its simplicity and cost-effectiveness has revealed excellent efficacy in identifying spectroscopic signatures capable to discriminate between patients’ subgroups for the clinical diagnosis and classification of PD.

Aims

Our goal was to investigate if classical biomarkers of Alzheimer’s disease (AD) neuropathology and their association with cognitive phenotype and dementia are affected by the individual’s frailty status.

Methods

We analyzed cross-sectional analysis data extracted from the Alzheimer’s Disease Neuroimaging Initiative 2 (ADNI2) study, including subjects with normal cognition level, mild cognitive impairment (MCI), and AD dementia. Frailty was quantified by the Frailty Index (FI), based on a 40-items health deficit accumulation model. We analyzed classical AD biomarkers and cognitive status, following participants stratification according to frailty level: CSF Abeta_1-42, ¹⁸¹P-tau, and T-tau; MRI-based hippocampal volume; cortical glucose metabolism by FDG-PET; amyloid deposition by ¹⁸F-AV-45 PET. Logistic regression models, adjusted for age, sex, and education, allowed to explore the association of biomarkers with cognitive phenotype at two different FI levels. We assessed the diagnostic potential of deficits and biomarkers by Machine Learning.

Results

Subjects with higher FI scores had lower CSF Abeta_1-42, lower glucose metabolism by FDG-PET, smaller hippocampus, and a higher amyloid deposition by ¹⁸F-AV-45 PET. No significant differences were observed among the frailty groups for ApoE genotype, CSF T-tau, and P-Tau. Increasing frailty levels were associated with a weaker relationship between AD and ¹⁸F-AV-45 uptake and hippocampus volume and with a stronger relationship of AD with FDG-PET.

Conclusions

Frailty partially explains discrepancies between AD neuropathology and clinical phenotype and affects the association of AD pathological modifications with cognitive status.
AD and dementia should be conceived as ageing trajectories, determined by a network of interacting pathophysiological processes.

Aims

Amyloid-beta species, e.g. Abeta40 and Abeta42, can further undergo amyloidolytic processing by BACE1 in vitro and in vivo (Liebsch et al., 2019), resulting in the production of the metastable intermediate, Abeta34. Besides being classified as a non-amyloidogenic Abeta species, Abeta34 is an important new marker of amyloid clearance. However, little is known about how Abeta34 is produced and removed from the cell. Therefore, we aim to elucidate the molecular details of Abeta34 metabolism.

Methods

To locate Abeta34 in the cell and to elucidate Abeta-degrading enzymes involved in its further degradation, we performed (i) siRNA-mediated knockdown of candidate enzymes and (ii) transient overexpression of such proteases in SH-SY5Y neuroblastoma cells. Expression levels of proteins were verified by Western blotting and Abeta species were analyzed by ELISA and MALDI mass spectrometry.

Results

Endosomes and lysosomes are the sites where BACE1 is located and active. Therefore, these sites provide optimal conditions for Abeta34 production by BACE1, and so for its degradation by the candidate enzymes, namely Endothelin Converting Enzymes, Insulin Degrading Enzyme, Cathepsin B and Cathepsin D. We found that BACE1 generates Abeta34 in intracellular compartments mainly from longer Abeta species and identified the proteases that have a major role in Abeta34 degradation.

Conclusions

It is important to elucidate the cellular pathways that lead to Abeta34 production and degradation because there is a fundamental need to better understand how current inhibitors impact the balance between BACE1’s amyloidogenic (e.g. APP→Abeta40 and Abeta42) and amyloidolytic activities (e.g. Abeta40 or Abeta42→Abeta34).