Early diagnostics and therapeutics for Alzheimer's disease--how early can we get there?

Development of SERS Active Nanoprobe for Selective Adsorption and Detection of Alzheimer's Disease Biomarkers Based on Molecular Docking

Purpose

Development of SERS-based Raman nanoprobes can detect the misfolding of Amyloid beta (Aβ) 42 peptides, making them a viable diagnostic technique for Alzheimer's disease (AD). The detection and imaging of amyloid peptides and fibrils are expected to help in the early identification of AD.

Methods

Here, we propose a fast, easy-to-use, and simple scheme based on the selective adsorption of Aβ42 molecules on SERS active gold nanoprobe (RB-AuNPs) of diameter 29 ± 3 nm for Detection of Alzheimer's Disease Biomarkers. Binding with the peptides results in a spectrum shift, which correlates with the target peptide. We also demonstrated the possibility of using silver nanoparticles (AgNPs) as precursors for the preparation of a SERS active nanoprobe with carbocyanine (CC) dye and AgNPs known as silver nanoprobe (CC-AgNPs) of diameter 25 ± 4 nm.

Results

RB-AuNPs probe binding with the peptides results in a spectrum shift, which correlates with the target peptide. Arginine peak appears after the conjugation confirms the binding of Aβ 42 with the nanoprobe. Tyrosine peaks appear after conjugated Aβ42 with CC-AgNPs providing binding of the peptide with the probe. The nanoprobe produced a strong, stable SERS signal. Further molecular docking was utilized to analyse the interaction and propose a structural hypothesis for the process of binding the nanoprobe to Aβ42 and Tau protein.

Conclusion

This peptide-probe interaction provides a general enhancement factor and the molecular structure of the misfolded peptides. Secondary structural information may be obtained at the molecular level for specific residues owing to isotope shifts in the Raman spectra. Conjugation of the nanoprobe with Aβ42 selectively detected AD in bodily fluids. The proposed nanoprobes can be easily applied to the detection of Aβ plaques in blood, saliva, and sweat samples.

Role of phosphatidylserine in amyloid-beta oligomerization at asymmetric phospholipid bilayers

Amyloid-beta (Aβ_1-42) aggregation triggers neurotoxicity and is linked to Alzheimer's disease. Aβ_1-42 oligomers, rather than extended fibrils, adhere to the cell membrane, causing cell death. Phosphatidylserine (PS), an anionic phospholipid, is prevalent in neuronal membranes (< 20 molar percentage) and, while isolated to the cytoplasmic leaflet of the membrane in healthy cells, its exposure in apoptotic cells and migration to exoplasmic leaflet is triggered by oxidative damage to the membrane. It is widely believed that PS plays a crucial role in the Aβ peptide interaction in the membranes of neuronal cells. However, due to the complexity of the cell membrane, it can be challenging to address molecular level understanding of the PS-Aβ binding and oligomerization processes. Herein, we use microcavity supported lipid bilayers (MSLBs) to analyse PS and Aβ_1-42 binding, oligomer formation, and membrane damage. MSLBs are a useful model to evaluate protein-membrane interactions because of their cell-like dual aspect fluidity, their addressability and compositional versatility. We used electrochemical impedance spectroscopy (EIS) and confocal fluorescence microscopy to compare the impact of Aβ_1-42 on simple zwitterioinic membrane, dioleoylphosphatidylcholine (DOPC), with MSLBs comprised of transversally asymmetric binary DOPC and dioleoylphosphatidylserine (DOPS). Monomeric Aβ_1-42 adsorbs weakly to the pristine zwitterionic DOPC membrane without aggregation. Using a membrane integrity test, with pyranine trapped within the cavities beneath the membrane, Aβ_1-42 exposure did not result in pyranine leakage, indicating that DOPC membranes were intact. When 10 mol% DOPS was doped asymmetrically into the membrane's outer leaflet, oligomerization of Aβ_1-42 monomer was evident in EIS and atomic force microscopy (AFM), and confocal imaging revealed that membrane damage, resulted in extensive pyranine leakage from the pores. The effects were time, and DOPS and Aβ_1-42 concentration-dependent. Membrane pore formation was visible within 30 minutes, and oligomerization, membrane-oligomer multilayer, and Aβ_1-42 fibril formation evident over 3 to 18 hours. In asymmetric membranes with DOPS localized to the lower leaflet, optothermally (laser induced) damage increased local DOPS concentrations at the distal leaflet, promoting Aβ_1-42 aggregation.

Alzheimer's Disease Classification Based on Multi-feature Fusion

BACKGROUND

In this study, we investigated the fusion of texture and morphometric features as a possible diagnostic biomarker for Alzheimer's Disease (AD).

METHODS

In particular, we classified subjects with Alzheimer's disease, Mild Cognitive Impairment (MCI) and Normal Control (NC) based on texture and morphometric features. Currently, neuropsychiatric categorization provides the ground truth for AD and MCI diagnosis. This can then be supported by biological data such as the results of imaging studies. Cerebral atrophy has been shown to correlate strongly with cognitive symptoms. Hence, Magnetic Resonance (MR) images of the brain are important resources for AD diagnosis. In the proposed method, we used three different types of features identified from structural MR images: Gabor, hippocampus morphometric, and Two Dimensional (2D) and Three Dimensional (3D) Gray Level Co-occurrence Matrix (GLCM). The experimental results, obtained using a 5-fold cross-validated Support Vector Machine (SVM) with 2DGLCM and 3DGLCM multi-feature fusion approaches, indicate that we achieved 81.05% ±1.34, 86.61% ±1.25 correct classification rate with 95% Confidence Interval (CI) falls between (80.75-81.35) and (86.33-86.89) respectively, 83.33%±2.15, 84.21%±1.42 sensitivity and 80.95%±1.52, 85.00%±1.24 specificity in our classification of AD against NC subjects, thus outperforming recent works found in the literature. For the classification of MCI against AD, the SVM achieved a 76.31% ± 2.18, 78.95% ±2.26 correct classification rate, 75.00% ±1.34, 76.19%±1.84 sensitivity and 77.78% ±1.14, 82.35% ±1.34 specificity.

RESULTS AND CONCLUSION

The results of the third experiment, with MCI against NC, also showed that the multiclass SVM provided highly accurate classification results. These findings suggest that this approach is efficient and may be a promising strategy for obtaining better AD, MCI and NC classification performance.

Multivariate Statistical Analysis of Surface Enhanced Raman Spectra of Human Serum for Alzheimer’s Disease Diagnosis

Alzheimer’s disease (AD) is the most common form of dementia worldwide and is characterized by progressive cognitive decline. Along with being incurable and lethal, AD is difficult to diagnose with high levels of accuracy. Blood serum from Alzheimer’s disease (AD) patients was analyzed by surface-enhanced Raman spectroscopy (SERS) coupled with multivariate statistical analysis. The obtained spectra were compared with spectra from healthy controls (HC) to develop a simple test for AD detection. Serum spectra from AD patients were further compared to spectra from patients with other neurodegenerative dementias (OD). Colloidal silver nanoparticles (AgNPs) were used as the SERS-active substrates. Classification experiments involving serum SERS spectra using artificial neural networks (ANNs) achieved a diagnostic sensitivity around 96% for differentiating AD samples from HC samples in a binary model and 98% for differentiating AD, HC, and OD samples in a tertiary model. The results from this proof-of-concept study demonstrate the great potential of SERS blood serum analysis to be developed further into a novel clinical assay for the effective and accurate diagnosis of AD.

Selective and Sensitive Pull Down of Amyloid Fibrils Produced in Vitro and in Vivo by the Use of Pentameric-Thiophene-Coupled Resins

Protein aggregation is a hallmark of several degenerative diseases, including Alzheimer's disease, Parkinson's disease and familial amyloidosis (Finnish type) (FAF). A method to isolate and detect amyloids is desired for the diagnosis of amyloid diseases. Here, we report the synthesis of pentameric thiophene amyloid ligand (p-FTAA) linked to agarose resin for selective purification of amyloid aggregates produced in vitro and in vivo. Using amyloid fibrils produced in vitro from α-synuclein, gelsolin, and Aβ_1-40 and gelsolin amyloid aggregates extracted from tissue homogenates of a mouse model of FAF, we observed that p-FTAA resin was able to pull down amyloid aggregates. The functionalized resin was also able to pull down oligomers produced in vitro from the A30P variant of α-synuclein. The methodology described here can be useful for the diagnosis of amyloidogenic disease and also can be used to purify amyloid fibrils from biological samples, rendering the fibrils available for more accurate structural and biochemical characterization.

Raman spectroscopy of blood serum for Alzheimer's disease diagnostics: specificity relative to other types of dementia

The key moment for efficiently and accurately diagnosing dementia occurs during the early stages. This is particularly true for Alzheimer's disease (AD). In this proof-of-concept study, we applied near infrared (NIR) Raman microspectroscopy of blood serum together with advanced multivariate statistics for the selective identification of AD. We analyzed data from 20 AD patients, 18 patients with other neurodegenerative dementias (OD) and 10 healthy control (HC) subjects. NIR Raman microspectroscopy differentiated patients with more than 95% sensitivity and specificity. We demonstrated the high discriminative power of artificial neural network (ANN) classification models, thus revealing the high potential of this developed methodology for the differential diagnosis of AD. Raman spectroscopic, blood-based tests may aid clinical assessments for the effective and accurate differential diagnosis of AD, decrease the labor, time and cost of diagnosis, and be useful for screening patient populations for AD development and progression. Multivariate data analysis of blood serum Raman spectra allows for the differentiation between patients with Alzheimer's disease, other types of dementia and healthy individuals.

Selection of aptamers for amyloid beta-protein, the causative agent of Alzheimer's disease

Alzheimer's disease (AD) is a progressive, age-dependent, neurodegenerative disorder with an insidious course that renders its presymptomatic diagnosis difficult(1). Definite AD diagnosis is achieved only postmortem, thus establishing presymptomatic, early diagnosis of AD is crucial for developing and administering effective therapies(2,3). Amyloid beta-protein (Abeta) is central to AD pathogenesis. Soluble, oligomeric Abeta assemblies are believed to affect neurotoxicity underlying synaptic dysfunction and neuron loss in AD(4,5). Various forms of soluble Abeta assemblies have been described, however, their interrelationships and relevance to AD etiology and pathogenesis are complex and not well understood(6). Specific molecular recognition tools may unravel the relationships amongst Abeta assemblies and facilitate detection and characterization of these assemblies early in the disease course before symptoms emerge. Molecular recognition commonly relies on antibodies. However, an alternative class of molecular recognition tools, aptamers, offers important advantages relative to antibodies(7,8). Aptamers are oligonucleotides generated by in-vitro selection: systematic evolution of ligands by exponential enrichment (SELEX)(9,10). SELEX is an iterative process that, similar to Darwinian evolution, allows selection, amplification, enrichment, and perpetuation of a property, e.g., avid, specific, ligand binding (aptamers) or catalytic activity (ribozymes and DNAzymes). Despite emergence of aptamers as tools in modern biotechnology and medicine(11), they have been underutilized in the amyloid field. Few RNA or ssDNA aptamers have been selected against various forms of prion proteins (PrP)(12-16). An RNA aptamer generated against recombinant bovine PrP was shown to recognize bovine PrP-beta(17), a soluble, oligomeric, beta-sheet-rich conformational variant of full-length PrP that forms amyloid fibrils(18). Aptamers generated using monomeric and several forms of fibrillar beta(2;)-microglobulin (beta(2;)m) were found to bind fibrils of certain other amyloidogenic proteins besides beta(2;)m fibrils(19). Ylera et al. described RNA aptamers selected against immobilized monomeric Abeta40(20). Unexpectedly, these aptamers bound fibrillar Abeta40. Altogether, these data raise several important questions. Why did aptamers selected against monomeric proteins recognize their polymeric forms? Could aptamers against monomeric and/or oligomeric forms of amyloidogenic proteins be obtained? To address these questions, we attempted to select aptamers for covalently-stabilized oligomeric Abeta40(21) generated using photo-induced cross-linking of unmodified proteins (PICUP)(22,23). Similar to previous findings(17,19,20), these aptamers reacted with fibrils of Abeta and several other amyloidogenic proteins likely recognizing a potentially common amyloid structural aptatope(21). Here, we present the SELEX methodology used in production of these aptamers(21).

Surface feature-guided mapping of cerebral metabolic changes in cognitively normal and mildly impaired elderly

PURPOSE

The aim of this study was to investigate the longitudinal positron emission tomography (PET) metabolic changes in the elderly.

PROCEDURES

Nineteen nondemented subjects (mean Mini-Mental Status Examination 29.4 +/- 0.7 SD) underwent two detailed neuropsychological evaluations and resting 2-deoxy-2-[F-18]fluoro-D: -glucose (FDG)-PET scan (interval 21.7 +/- 3.7 months), baseline structural 3T magnetic resonance (MR) imaging, and apolipoprotein E4 genotyping. Cortical PET metabolic changes were analyzed in 3-D using the cortical pattern matching technique.

RESULTS

Baseline vs. follow-up whole-group comparison revealed significant metabolic decline bilaterally in the posterior temporal, parietal, and occipital lobes and the left lateral frontal cortex. The declining group demonstrated 10-15% decline in bilateral posterior cingulate/precuneus, posterior temporal, parietal, and occipital cortices. The cognitively stable group showed 2.5-5% similarly distributed decline. ApoE4-positive individuals underwent 5-15% metabolic decline in the posterior association cortices.

CONCLUSIONS

Using 3-D surface-based MR-guided FDG-PET mapping, significant metabolic changes were seen in five posterior and the left lateral frontal regions. The changes were more pronounced for the declining relative to the cognitively stable group.

RNA aptamers generated against oligomeric Abeta40 recognize common amyloid aptatopes with low specificity but high sensitivity

Aptamers are useful molecular recognition tools in research, diagnostics, and therapy. Despite promising results in other fields, aptamer use has remained scarce in amyloid research, including Alzheimer's disease (AD). AD is a progressive neurodegenerative disease believed to be caused by neurotoxic amyloid β-protein (Aβ) oligomers. Aβ oligomers therefore are an attractive target for development of diagnostic and therapeutic reagents. We used covalently-stabilized oligomers of the 40-residue form of Aβ (Aβ40) for aptamer selection. Despite gradually increasing the stringency of selection conditions, the selected aptamers did not recognize Aβ40 oligomers but reacted with fibrils of Aβ40, Aβ42, and several other amyloidogenic proteins. Aptamer reactivity with amyloid fibrils showed some degree of protein-sequence dependency. Significant fibril binding also was found for the naïve library and could not be eliminated by counter-selection using Aβ40 fibrils, suggesting that aptamer binding to amyloid fibrils was RNA-sequence-independent. Aptamer binding depended on fibrillogenesis and showed a lag phase. Interestingly, aptamers detected fibril formation with ≥15-fold higher sensitivity than thioflavin T (ThT), revealing substantial β-sheet and fibril formation undetected by ThT. The data suggest that under physiologic conditions, aptamers for oligomeric forms of amyloidogenic proteins cannot be selected due to high, non-specific affinity of oligonucleotides for amyloid fibrils. Nevertheless, the high sensitivity, whereby aptamers detect β-sheet formation, suggests that they can serve as superior amyloid recognition tools.

Synthesis and Purification of Highly Hydrophobic Peptides Derived from the C-Terminus of Amyloid β-Protein

Some biotechnological inventions involve expensive, sophisticated machines. Others are relatively simple innovations that nevertheless address, and solve difficult problems. Synthesis and purification of highly hydrophobic peptides can be a difficult and challenging task, particularly when these peptides have low solubility in both aqueous and organic solvents. Here we describe the synthesis and purification of a series of peptides derived from the hydrophobic C-terminus of the 42-residue form of amyloid β-protein (Aβ42), a peptide believed to be the primary cause for Alzheimer's disease (AD). The series of C-terminal fragments (CTFs) had the general formula Aβ(x-42), x=28-39, which potentially can be used as inhibitors of Aβ42 assembly and neurotoxicity. Synthesis and purification of peptides containing 8-residues or less were straightforward. However, HPLC purification of longer peptides was problematic and provided <1% yield in particularly difficult cases due to very poor solubility in the solvent systems used both in reverse- and in normal phase chromatography. Modification of the purification protocol using water precipitation followed by removal of scavengers by washing with diethyl ether circumvented the need for HPLC purification and provided these peptides with purity as high as HPLC-purified peptides and substantially increased yield.

Brain mapping as a tool to study neurodegeneration

Alzheimer's disease (AD) is the most common neurodegenerative disorder for those 65 years or older; it currently affects 4.5 million in the United States and is predicted to rise to 13.2 million by the year 2050. Neuroimaging and brain mapping techniques offer extraordinary power to understand AD, providing spatially detailed information on the extent and trajectory of the disease as it spreads in the living brain. Computational anatomy techniques, applied to large databases of brain MRI scans, reveal the dynamic sequence of cortical and hippocampal changes with disease progression and how these relate to cognitive decline and future clinical outcomes. People who are mildly cognitively impaired, in particular, are at a fivefold increased risk of imminent conversion to dementia, and they show specific structural brain changes that are predictive of imminent disease onset. We review the principles and key findings of several new methods for assessing brain degeneration, including voxel-based morphometry, tensor-based morphometry, cortical thickness mapping, hippocampal atrophy mapping, and automated methods for mapping ventricular anatomy. Applications to AD and other dementias are discussed, with a brief review of related findings in other neurological and neuropsychiatric illnesses, including epilepsy, HIV/AIDS, schizophrenia, and disorders of brain development.