AbstractAlzheimer’s Disease Patients Research Articles

Shared and differing functional connectivity abnormalities of the default mode network in mild cognitive impairment and Alzheimer’s disease

Abstract Alzheimer’s disease (AD) and mild cognitive impairment (MCI) both show abnormal resting-state functional connectivity (rsFC) of default mode network (DMN), but it is unclear to what extent these abnormalities are shared. Therefore, we performed a comprehensive meta-analysis, including 31 MCI studies and 20 AD studies. MCI patients, compared to controls, showed decreased within-DMN rsFC in bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), precuneus/posterior cingulate cortex (PCC), right temporal lobes, and left angular gyrus and increased rsFC between DMN and left inferior temporal gyrus. AD patients, compared to controls, showed decreased rsFC within DMN in bilateral mPFC/ACC and precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC between DMN and right dorsolateral prefrontal cortex. Conjunction analysis showed shared decreased rsFC in mPFC/ACC and precuneus/PCC. Compared to MCI, AD had decreased rsFC in left precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC in right temporal lobes. MCI and AD share a decreased within-DMN rsFC likely underpinning episodic memory deficits and neuropsychiatric symptoms, but differ in DMN rsFC alterations likely related to impairments in other cognitive domains such as language, vision, and execution. This may throw light on neuropathological mechanisms in these two stages of dementia.

Markov model combined with MR diffusion tensor imaging for predicting the onset of Alzheimer's disease.

Alzheimer's disease (AD) affects cognition, behavior, and memory of brain. It causes 60-80% of dementia cases. Cross-sectional imaging investigations of AD show that magnetic resonance (MR) with diffusion tensor image (DTI)-detected lesion locations in AD patients are heterogeneous and distributed across the imaging area. This study suggested that Markov model (MM) combined with MR-DTI (MM + MR-DTI) was offered as a method for predicting the onset of AD. In 120 subjects (normal controls [NCs], amnestic mild cognitive impairment [aMCI] patients, and AD patients) from a discovery dataset and 122 subjects (NCs, aMCI, and AD) from a replicated dataset, we used them to evaluate the white matter (WM) integrity and abnormalities. We did this by using automated fiber quantification, which allowed us to identify 20 central WM tracts. Point-wise alterations in WM tracts were shown using discovery and replication datasets. The statistical analysis revealed a substantial correlation between microstructural WM alterations and output in the patient groups and cognitive performance, suggesting that this may be a potential biomarker for AD. The MR-based classifier demonstrated the following performance levels for the basis classifiers, with DTI achieving the lowest performance. The following outcomes were seen in MM + MR-DTI using multimodal techniques when combining two modalities. Finally, a combination of every imaging method produced results with an accuracy of 98%, a specificity of 97%, and a sensitivity of 99%. In summary, DTI performs better when paired with structural MR, despite its relatively weak performance when used alone. These findings support the idea that WM modifications play a significant role in AD.

Characterization of the transcriptome and TCR of brain and cerebrospinal fluid infiltrated CD8 +T cells in an Alzheimer’s disease mouse model

Abstract Alzheimer’s disease (AD) is a common form of dementia characterized by the accumulation of protein aggregates in the brain of older adults. It has been observed that CD8 +T cells, particularly CD8 +TEMRA cells, infiltrate the brain and cerebrospinal fluid (CSF) of AD patients. However, the precise role of these cells in the development and progression of AD is not well understood. In this study, we used single-cell RNA sequencing (scRNAseq) and single-cell T cell receptor sequencing (scTCRseq) to examine the CD8 +T cells in the brain and CSF of a mouse model of AD (5xFAD) and its wild-type (WT) littermate controls. The AD mice (age 40–70 weeks) used in our experiments have developed memory deficits. Our analysis revealed a significant increase in the number of CD8 +T cells in the brain and CSF of AD mice compared to WT controls (n=4, p<0.05). Furthermore, these cells displayed a distinct transcriptome profile characterized by increased expression of inflammatory pathways, compared to WT mice. Through TCR sequence analysis, we also observed significant clonal expansion of CD8 +T cells in AD mice compared to WT mice. These findings provide a starting point for further investigation into the role of infiltrating CD8 +T cells in the pathogenesis of AD in this mouse model.

Label-free hyperspectral imaging and deep-learning prediction of retinal amyloid β-protein and phosphorylated tau.

Alzheimer’s disease (AD) is a major risk for the aging population. The pathological hallmarks of AD—an abnormal deposition of amyloid β-protein (Aβ) and phosphorylated tau (pTau)—have been demonstrated in the retinas of AD patients, including in prodromal patients with mild cognitive impairment (MCI). Aβ pathology, especially the accumulation of the amyloidogenic 42-residue long alloform (Aβ42), is considered an early and specific sign of AD, and together with tauopathy, confirms AD diagnosis. To visualize retinal Aβ and pTau, state-of-the-art methods use fluorescence. However, administering contrast agents complicates the imaging procedure. To address this problem from fundamentals, ex-vivo studies were performed to develop a label-free hyperspectral imaging method to detect the spectral signatures of Aβ42 and pS396-Tau, and predicted their abundance in retinal cross-sections. For the first time, we reported the spectral signature of pTau and demonstrated an accurate prediction of Aβ and pTau distribution powered by deep learning. We expect our finding will lay the groundwork for label-free detection of AD.

Modelling the Effects of Medium-Chain Triglycerides on Cerebral Ketone Body Metabolism

Alzheimer’s Disease (AD) is a neurodegenerative disorder that causes drastic structural brain atrophy and affects multiple brain functions. Cerebral glucose hypometabolism, associated with senile plaque density formation, is a pre-symptomatic feature of AD and significantly contributes to AD’s future development and progression. As cerebral glucose metabolism gradually slows down due to advanced aging, a healthy adult brain experiences an 8% decrease in cerebral glucose metabolic rate (CGMR) compared to a decline of 20%–40% CGMR in AD patients. To bridge the increasing brain energy gap caused by glucose hypometabolism, ketone bodies (KBs) are used as a supplementary source of energy as cerebral KB metabolism remains unaffected in AD patients. Ketogenic interventions such as Medium-Chain Triglyceride (MCT)-induced treatment can help augment the brain’s energy source availability and might delay further cognitive decline. With this, we constructed a mathematical model on cerebral glucose and KB metabolism to illustrate the drastic effects of glucose hypometabolism on healthy aging individuals, Mild Cognitive Impairment (MCI) subjects, and AD patients. Through the generated simulations, we have shown that KB concentration levels rise during prolonged starvation, and in consideration of glucose hypometabolism, MCT-induced intervention increases the concentration levels of acetyl-CoA (AC) in MCI/AD patients. Furthermore, MCT-induced supplement helps increase the AC concentration levels in healthy adults under normal conditions.

Why Women Are Predisposed to Alzheimer’s Disease

Alzheimer’s disease (AD) exhibits progressive dementia, profound disability, and impaired quality of life. Globally, there are more than 50 million AD patients, over two-thirds of which are women. The cause behind this gender difference had remained unclear for decades until FSH (follicle stimulating hormone), a hormone that dramatically increases in women after menopause, was recently found to trigger this phenomenon.

Transcriptional Profiling of Hippocampus Identifies Network Alterations in Alzheimer’s Disease

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by rapid brain cell degeneration affecting different areas of the brain. Hippocampus is one of the earliest involved brain regions in the disease. Modern technologies based on high-throughput data have identified transcriptional profiling of several neurological diseases, including AD, for a better comprehension of genetic mechanisms of the disease. In this study, we investigated differentially expressed genes (DEGs) from six Gene Expression Omnibus (GEO) datasets of hippocampus of AD patients. The identified DEGs were submitted to Weighted correlation network analysis (WGCNA) and ClueGo to explore genes with a higher degree centrality and to comprehend their biological role. Subsequently, MCODE was used to identify subnetworks of interconnected DEGs. Our study found 40 down-regulated genes and 36 up-regulated genes as consensus DEGs. Analysis of the co-expression network revealed ACOT7, ATP8A2, CDC42, GAD1, GOT1, INA, NCALD, and WWTR1 to be genes with a higher degree centrality. ClueGO revealed the pathways that were mainly enriched, such as clathrin coat assembly, synaptic vesicle endocytosis, and DNA damage response signal transduction by p53 class mediator. In addition, we found a subnetwork of 12 interconnected genes (AMPH, CA10, CALY, NEFL, SNAP25, SNAP91, SNCB, STMN2, SV2B, SYN2, SYT1, and SYT13). Only CA10 and CALY are targets of known drugs while the others could be potential novel drug targets.

Autophagy Regulation Influences β-Amyloid Toxicity in Transgenic Caenorhabditis elegans.

Alzheimer’s disease (AD) is a progressive, neurodegenerative disease characterized by the accumulation of amyloid-beta (Aβ) proteins in the form of plaques that cause a proteostasis imbalance in the brain. Several studies have identified autophagy deficits in both AD patients and AD animal models. Here, we used transgenic Caenorhabditis elegans to study the relationship between autophagy flux and Aβ. We labeled autophagosomes with an advanced fluorescence reporter system, and used this to observe that human Aβ expression caused autophagosome accumulation in C. elegans muscle. The autophagy-related drugs chloroquine and 3-MA were employed to investigate the relationship between changes in autophagic flux and the toxicity of Aβ expression. We found that reducing autophagosome accumulation delayed Aβ-induced paralysis in the CL4176 strain of C. elegans, and alleviated Aβ-induced toxicity, thus having a neuroprotective effect. Finally, we used RNA-sequencing and proteomics to identify genes whose expression was affected by Aβ aggregation in C. elegans. We identified a series of enriched autophagy-related signal pathways, suggesting that autophagosome accumulation impairs Aβ protein homeostasis in nematodes. Thus, maintaining normal autophagy levels appears to be important in repairing the protein homeostasis imbalance caused by Aβ expression.

A pathological role of the Hsp40 protein Ydj1/DnaJA1 in models of Alzheimer's disease.

Alzheimer's disease (AD) is the most common form of dementia with millions of people affected worldwide. Pathophysiological manifestations of AD include the extracellular accumulation of amyloid beta (Abeta) pep-tides, products of the proteolytic cleavage of the amy-loid precursor protein APP. Increasing evidence sug-gests that Abeta peptides also accumulate intracellular-ly, triggering neurotoxic events such as mitochondrial dysfunction. However, the molecular factors driving formation and toxicity of intracellular Abeta are poorly understood. In our recent study [EMBO Mol Med 2022 - e13952], we used different eukaryotic model systems to identify such factors. Based on a genetic screen in yeast and subsequent molecular analyses, we found that both the yeast chaperone Ydj1 and its human ortholog DnaJA1 physically interact with Abeta, facili-tate the aggregation of Abeta peptides into small oli-gomers and promote their translocation to mitochon-dria. Deletion or downregulation of this chaperone pro-tected from Abeta-mediated toxicity in yeast and Dro-sophila AD models, respectively. Most importantly, the identified chaperone is found to be dysregulated in post-mortem human samples of AD patients. Here, we aim to outline our key findings, highlighting pathological functions of a heat shock protein (Hsp) family member, which are generally considered protective rather than toxic during neurodegeneration. Our results thus chal-lenge the concept of developing generalized chaperone activation-based therapies and call for carefully consid-ering also maladaptive functions of specific heat shock proteins.

Artificial Intelligence Predictor for Alzheimer's Disease Trained on Blood Transcriptome: The Role of Oxidative Stress.

Alzheimer’s disease (AD) is an incurable neurodegenerative disease diagnosed by clinicians through healthcare records and neuroimaging techniques. These methods lack sensitivity and specificity, so new antemortem non-invasive strategies to diagnose AD are needed. Herein, we designed a machine learning predictor based on transcriptomic data obtained from the blood of AD patients and individuals without dementia (non-AD) through an 8 × 60 K microarray. The dataset was used to train different models with different hyperparameters. The support vector machines method allowed us to reach a Receiver Operating Characteristic score of 93% and an accuracy of 89%. High score levels were also achieved by the neural network and logistic regression methods. Furthermore, the Gene Ontology enrichment analysis of the features selected to train the model along with the genes differentially expressed between the non-AD and AD transcriptomic profiles shows the “mitochondrial translation” biological process to be the most interesting. In addition, inspection of the KEGG pathways suggests that the accumulation of β-amyloid triggers electron transport chain impairment, enhancement of reactive oxygen species and endoplasmic reticulum stress. Taken together, all these elements suggest that the oxidative stress induced by β-amyloid is a key feature trained by the model for the prediction of AD with high accuracy.

Impact of Chronic Conditions and Dementia in Rural West Texas: A Healthy Aging Study

Alzheimer’s disease (AD) is a devastating illness in elderly individuals, that currently has no known cure. Causal genetic factors only account for 1-2% of AD patients. However, other causal factors are still unknown for a majority of AD patients. Currently, multiple factors are implicated in late-onset AD, including unhealthy diet, physical inactivity, traumatic brain injury, chronic conditions, epigenetic factors, and environmental exposures. Although clinical symptoms of dementia are common to all races and ethnic groups, conditions that lead to dementia are different in terms of lifestyle, genetic profile, and socio-economic conditions. Increasing evidence also suggests that some elderly individuals age without cognitive impairments in their 60–90s as seen in rural West Texas, while some individuals progress with chronic conditions and cognitive impairments into their 60s. To understand these discriminations, we assessed current literature on demographic features of health in rural West Texas. This paper also outlines our initiated clinical study with a purpose of understanding the factors that allow some individuals to live without cognitive impairments at the age of 60–90 years, whereas others develop deficits in cognitive function around or above 60 years. Our ongoing study hopes to determine the factors that delay aging in some individuals by investigating various aspects including genetics, epigenetics, ethnicity, biology, culture, and lifestyle. This will be achieved by gathering information about participants’ ethnographic profiles, cognitive assessments, blood-profiles, brain scans, and blood-based genomic analyses in relation to lifestyle. The outcomes of our study will provide insights into healthy aging in rural West Texas.

Trained Immunity in Neurodegenerative Diseases

Abstract Alzheimer’s disease (AD) and Parkinson’s disease (PD) are complex and progressive neurodegenerative disturbances leading to cognitive or motor dysfunctions and lacking effective therapy. A deregulation of innate immune response and inflammation appears to be deeply involved in both illnesses, though with still unclear mechanisms. Evidence in animals attributes a neurodegeneration-modulating role to mechanisms of innate memory, but human data on this topic are still scarce. In this study, we investigated whether -possibly due to concomitant factors including enhanced infectious burden, microbial dysbiosis and genetic risk factors linked to immunity-the innate immune cells of AD and PD patients show long-term functional reprogramming characterized by either potentiated or tolerant responses, which could ultimately contribute to disease development. Thus, following repeated in vitro stimulation with either heat-inactivated Candida albicans or LPS, we measured the cytokine response of CD14+ cells from AD and PD patients, both in comparison with those of age- and gender-matched healthy control subjects and in association with symptom severity. We observed different cytokine patterns associated with tolerant or potentiated responses among the three groups of subjects, pointing to different and disease-dependent trained immune status in patients. Our results would provide insights about how previous triggering of innate immunity can influence neuroinflammation and disease progression, offering new knowledge on trained immunity impact in neurodegenerative diseases.

Alterations of the Sympathoadrenal Axis Related to the Development of Alzheimer's Disease in the 3xTg Mouse Model.

Simple SummaryAlzheimer’s disease (AD), the most common form of dementia, is becoming a global health problem and public health priority. In the advanced stages of AD, besides the initial cognitive symptoms, behavioral problems, particularly agitation and aggressiveness, become prevalent in AD patients. These non-cognitive symptoms could be related to alterations in the regulatory mechanism of the sympathetic nervous system. In this study, we used chromaffin cells (CCs) isolated from the adrenal gland of 3xTg (an AD mouse model) mice to characterize potential alterations in the regulation of the responses to stress mediated by the secretion of catecholamines. We compared these regulatory mechanisms in mice at two different ages: in 2-month-old mice, where no AD symptoms were observed, and in mice over 12 months of age, when AD-related cognitive impairment related was fully established. We found that the modulation of neurotransmitter release was stronger in CCs isolated from the adrenal medulla of 3xTg mice older than 12 months of age, an effect likely related to disease progression as it was not observed in CCs from age-matched wild-type (WT) mice. This enhanced modulation leads to an increased catecholamine release in response to stressful situations, which may explain the non-cognitive behavioral problems found in AD patients.Alzheimer’s disease (AD), the most common form of dementia, is becoming a global health problem and public health priority. In the advanced stages of AD, besides the initial cognitive symptoms, behavioral problems, particularly agitation and aggressiveness, become prevalent in AD patients. These non-cognitive symptoms could be related to a noradrenergic overactivation. In this study, we used chromaffin cells (CCs) isolated from the adrenal gland of 3xTg AD model mice to characterize potential alterations in the autocrine-paracrine modulation of voltage-dependent calcium channels (VDCCs), which in turn serve to regulate the release of catecholamines. We used mice at the presymptomatic stage (2 months) and mice over 12 months of age, when AD-related cognitive impairment was fully established. We found that the modulation of inward currents through VDCCs induced by extracellular ATP was stronger in CCs isolated from the adrenal medulla of 3xTg mice older than 12 months of age, an effect likely related to disease progression as it was not observed in CCs from age-matched WT mice. This enhanced modulation leads to increased catecholamine release in response to stressful situations, which may explain the non-cognitive behavioral problems found in AD patients.

The Therapeutic Potential of Synthetic and Natural Cannabinoids in Treating Alzheimer’s Disease

Alzheimer’s disease (AD) is one of the most prevalent and debilitating neurodegenerative diseases in the world, highlighting the need for research on novel treatments and therapies. Previous studies have found that the body’s endocannabinoid system (ECS) interacts closely with its neural system, making it a potential avenue for the treatment of neurological disorders. One hallmark of AD is the accumulation of amyloid-beta (Aβ) in the brain and its potentially detrimental effects on cognitive function. Cannabis-based drugs have been observed to regulate Aβ modifications and inhibit AD progression. Furthermore, cannabinoids have been noted to reduce inflammation and neurotoxicity. Synthetic cannabinoids were able to rescue memory deficits and neurodegeneration, and reduce immunoreactivity. Similarly, natural cannabinoids like Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) demonstrate therapeutic potential by interacting with the cholinergic system, and reversing the symptoms of AD. Although further research and testing are needed, it is evident that the use of cannabinoids shows promise for future treatment in AD patients.

Mechanism of the Fibroblast Growth Factor 23/α-Klotho Axis in Peripheral Blood Mononuclear Cell Inflammation in Alzheimer’s Disease

ABSTRACT Alzheimer’s disease (AD) is a prevalent type of dementia and threatens the health of most elderly people and poses a huge burden to families and society. The fibroblast growth factor 23 (FGF23)/α-Klotho axis is associated with multiple aging-related diseases. Hence, this study explored the mechanism of the FGF23/α-Klotho axis in AD. FGF23/α-Klotho protein contents and levels of inflammatory cytokines in AD patients were measured, and the correlation between FGF23/α-Klotho protein contents and inflammatory cytokines was analyzed. FGF23 and α-Klotho expressions were blocked in peripheral blood mononuclear cells (PBMCs) in AD patients (AD-PBMCs) to assess the effects on cell inflammation and the Wnt/β-catenin pathway activation. The Wnt/β-catenin pathway was inhibited to evaluate cell inflammation. Combined treatments of the cells were conducted to verify the role of the FGF23/α-Klotho axis and the Wnt/β-catenin pathway in inflammation in AD-PBMCs. Increased FGF23 protein concentration and reduced α-Klotho protein concentration were observed in AD patients and correlated with inflammatory cytokine levels. FGF23 inhibition or α-Klotho overexpression reduced the production of inflammatory cytokines and activated the Wnt/β-catenin pathway in AD-PBMCs. Blocking the Wnt/β-catenin pathway increased inflammatory cytokine production in AD-PBMCs and annulled the effects of the FGF23/α-Klotho axis on AD-induced cell inflammation. We concluded that the FGF23/α-Klotho axis can regulate the AD-induced cell inflammation through the Wnt/β-catenin pathway.

Screening for Core Genes Related to Pathogenesis of Alzheimer's Disease.

Alzheimer’s disease (AD), a nervous system disease, lacks effective therapies at present. RNA expression is the basic way to regulate life activities, and identifying related characteristics in AD patients may aid the exploration of AD pathogenesis and treatment. This study developed a classifier that could accurately classify AD patients and healthy people, and then obtained 3 core genes that may be related to the pathogenesis of AD. To this end, RNA expression data of the middle temporal gyrus of AD patients were firstly downloaded from GEO database, and the data were then normalized using limma package following a supplementation of missing data by k-Nearest Neighbor (KNN) algorithm. Afterwards, the top 500 genes of the most feature importance were obtained through Max-Relevance and Min-Redundancy (mRMR) analysis, and based on these genes, a series of AD classifiers were constructed through Support Vector Machine (SVM), Random Forest (RF), and KNN algorithms. Then, the KNN classifier with the highest Matthews correlation coefficient (MCC) value composed of 14 genes in incremental feature selection (IFS) analysis was identified as the best AD classifier. As analyzed, the 14 genes played a pivotal role in determination of AD and may be core genes associated with the pathogenesis of AD. Finally, protein-protein interaction (PPI) network and Random Walk with Restart (RWR) analysis were applied to obtain core gene-associated genes, and key pathways related to AD were further analyzed. Overall, this study contributed to a deeper understanding of AD pathogenesis and provided theoretical guidance for related research and experiments.

Uncal apex movement and positioning in Alzheimer's Disease

Alzheimer’s Disease (AD) patients have consistently shown declines in declarative memory, consolidation, and in many other cognitive areas. These changes are associated with atrophy and volumetric declines in medial temporal lobe structures, such as the hippocampus. Hippocampal atrophy has been associated with AD. However, the influence of AD atrophy on the position of the uncal apex—an anatomical landmark for the hippocampus—has not been longitudinally examined. The current study’s objective is to investigate changes in the position of the uncal apex of AD patients over the course of two years. The current study draws upon the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data set (adni.loni.usc.edu). For each participant, I obtained demographic data, anatomical MRI images in native space, hippocampal segmentations from the subcortical stream of FreeSurfer (v.5.3.0), and linear transforms to MNI space. Using uncal apex y-positions transformed in MNI space, I found that the uncal apex fell in a more posterior position in AD patients relative to control and that over time, the uncal apex migrates toward a more anterior position in both groups. These results suggest that part of the neuroimaging examinations that are done on AD patients should examine uncal apex positions as a biomarker of early AD progression. Future directions and limitations are discussed

PIP2 Improves Cerebral Blood Flow in a Mouse Model of Alzheimer's Disease.

Alzheimer’s disease (AD) is a leading cause of dementia and a substantial healthcare burden. Despite this, few treatment options are available for controlling AD symptoms. Notably, neuronal activity-dependent increases in cortical cerebral blood flow (CBF; functional hyperemia) are attenuated in AD patients, but the associated pathological mechanisms are not fully understood at the molecular level. A fundamental mechanism underlying functional hyperemia is activation of capillary endothelial inward-rectifying K+ (Kir2.1) channels by neuronally derived potassium (K+), which evokes a retrograde capillary-to-arteriole electrical signal that dilates upstream arterioles, increasing blood delivery to downstream active regions. Here, using a mouse model of familial AD (5xFAD), we tested whether this impairment in functional hyperemia is attributable to reduced activity of capillary Kir2.1 channels. In vivo CBF measurements revealed significant reductions in whisker stimulation (WS)-induced and K+-induced hyperemic responses in 5xFAD mice compared with age-matched controls. Notably, measurements of whole-cell currents in freshly isolated 5xFAD capillary endothelial cells showed that Kir2.1 current density was profoundly reduced, suggesting a defect in Kir2.1 function. Because Kir2.1 activity absolutely depends on binding of phosphatidylinositol 4,5-bisphosphate (PIP2) to the channel, we hypothesized that capillary Kir2.1 channel impairment could be corrected by exogenously supplying PIP2. As predicted, a PIP2 analog restored Kir2.1 current density to control levels. More importantly, systemic administration of PIP2 restored K+-induced CBF increases and WS-induced functional hyperemic responses in 5xFAD mice. Collectively, these data provide evidence that PIP2-mediated restoration of capillary endothelial Kir2.1 function improves neurovascular coupling and CBF in the setting of AD.

How Your Blood Knows Your Brain Is Sick

Alzheimer’s disease (AD) is a complex disease that attacks the brain that mostly affects people 65 years and older. AD affects more and more people each year. A major problem with AD is that it is diagnosed too late. A big goal is to find ways to help doctors identify the disease early, so they can better help AD patients. Biomarkers are something that can tell you if a part of the body is feeling healthy or is being attacked by a disease. This article will describe one exciting new category of biomarkers that carry information from the brain into the blood. These biomarkers can be used to see how healthy the brain is feeling or if it is getting hurt by a disease like AD.

Contributions of Molecular and Optical Techniques to the Clinical Diagnosis of Alzheimer's Disease.

Alzheimer’s disease (AD) is the most common neurodegenerative disorder worldwide. The distinctive neuropathological feature of AD is the intracerebral accumulation of two abnormally folded proteins: β-amyloid (Aβ) in the form of extracellular plaques, and tau in the form of intracellular neurofibrillary tangles. These proteins are considered disease-specific biomarkers, and the definite diagnosis of AD relies on their post-mortem identification in the brain. The clinical diagnosis of AD is challenging, especially in the early stages. The disease is highly heterogeneous in terms of clinical presentation and neuropathological features. This phenotypic variability seems to be partially due to the presence of distinct Aβ conformers, referred to as strains. With the development of an innovative technique named Real-Time Quaking-Induced Conversion (RT-QuIC), traces of Aβ strains were found in the cerebrospinal fluid of AD patients. Emerging evidence suggests that different conformers may transmit their strain signature to the RT-QuIC reaction products. In this review, we describe the current challenges for the clinical diagnosis of AD and describe how the RT-QuIC products could be analyzed by a surface-enhanced Raman spectroscopy (SERS)-based systems to reveal the presence of strain signatures, eventually leading to early diagnosis of AD with the recognition of individual disease phenotype.