Potential utility of autoantibodies as blood-based biomarkers for early detection and diagnosis of Parkinson's disease

Early Detection of Alzheimer's Disease-Related Pathology Using a Multi-Disease Diagnostic Platform Employing Autoantibodies as Blood-Based Biomarkers

BACKGROUND

Evidence for the universal presence of IgG autoantibodies in blood and their potential utility for the diagnosis of Alzheimer's disease (AD) and other neurodegenerative diseases has been extensively demonstrated by our laboratory. The fact that AD-related neuropathological changes in the brain can begin more than a decade before tell-tale symptoms emerge has made it difficult to develop diagnostic tests useful for detecting the earliest stages of AD pathogenesis.

OBJECTIVE

To determine the utility of a panel of autoantibodies for detecting the presence of AD-related pathology along the early AD continuum, including at pre-symptomatic [an average of 4 years before the transition to mild cognitive impairment (MCI)/AD)], prodromal AD (MCI), and mild-moderate AD stages.

METHODS

A total of 328 serum samples from multiple cohorts, including ADNI subjects with confirmed pre-symptomatic, prodromal, and mild-moderate AD, were screened using Luminex xMAP® technology to predict the probability of the presence of AD-related pathology. A panel of eight autoantibodies with age as a covariate was evaluated using randomForest and receiver operating characteristic (ROC) curves.

RESULTS

Autoantibody biomarkers alone predicted the probability of the presence of AD-related pathology with 81.0% accuracy and an area under the curve (AUC) of 0.84 (95% CI = 0.78-0.91). Inclusion of age as a parameter to the model improved the AUC (0.96; 95% CI = 0.93-0.99) and overall accuracy (93.0%).

CONCLUSION

Blood-based autoantibodies can be used as an accurate, non-invasive, inexpensive, and widely accessible diagnostic screener for detecting AD-related pathology at pre-symptomatic and prodromal AD stages that could aid clinicians in diagnosing AD.

Autoantibodies targeting neuronal proteins as biomarkers for neurodegenerative diseases

Neurodegenerative diseases (NDDs) are associated with the accumulation of a range of misfolded proteins across the central nervous system and related autoimmune responses, including the generation of antibodies and the activation of immune cells. Both innate and adaptive immunity become mobilized, leading to cellular and humoral effects. The role of humoral immunity in disease onset and progression remains to be elucidated with rising evidence suggestive of positive (protection, repair) and negative (injury, toxicity) outcomes. In this study, we review advances in research of neuron-targeting autoantibodies in the most prevalent NDDs. We discuss their biological origin, molecular diversity and changes in the course of diseases, consider their relevance to the initiation and progression of pathology as well as diagnostic and prognostic significance. It is suggested that the emerging autoimmune aspects of NDDs not only could facilitate the early detection but also might help to elucidate previously unknown facets of pathobiology with relevance to the development of precision medicine.

Gene-corrected p.A30P SNCA patient-derived isogenic neurons rescue neuronal branching and function

Parkinson's disease (PD) is characterised by the degeneration of A9 dopaminergic neurons and the pathological accumulation of alpha-synuclein. The p.A30P SNCA mutation generates the pathogenic form of the alpha-synuclein protein causing an autosomal-dominant form of PD. There are limited studies assessing pathogenic SNCA mutations in patient-derived isogenic cell models. Here we provide a functional assessment of dopaminergic neurons derived from a patient harbouring the p.A30P SNCA mutation. Using two clonal gene-corrected isogenic cell lines we identified image-based phenotypes showing impaired neuritic processes. The pathological neurons displayed impaired neuronal activity, reduced mitochondrial respiration, an energy deficit, vulnerability to rotenone, and transcriptional alterations in lipid metabolism. Our data describes for the first time the mutation-only effect of the p.A30P SNCA mutation on neuronal function, supporting the use of isogenic cell lines in identifying image-based pathological phenotypes that can serve as an entry point for future disease-modifying compound screenings and drug discovery strategies.

Autoimmunomic Signatures of Aging and Age-Related Neurodegenerative Diseases Are Associated With Brain Function and Ribosomal Proteins

Biological aging is a complex process featured by declined function of cells and tissues, including those of the immune system. As a consequence, aging affects the expression and development of autoantibodies and autoreactive T cells, which can be seen in their sum as the autoimmunome of an individual. In this study we analyzed whether sets of autoimmune features are associated with specific phenotypes which form autoimmunomic signatures related to age and neurodegenerative diseases. The autoantibody profile data of healthy subjects and patients from the GEO database was used to explore autoimmunomic signatures of aging and three neurodegenerative diseases including Parkinson's disease (PD), Alzheimer disease (AD) and Multiple Sclerosis (MS). Our results demonstrate that the autoimmunomic signature of aging is featured by an undulated increase of IgG autoantibodies associated with learning and behavior and a consistent increase of IgG autoantibodies related to ribosome and translation, and the autoimmunomic signature of aging are also associated with age-related neurodegenerative diseases. Intriguingly, Differential Expression-Sliding Window Analysis (DE-SWAN) identified three waves of changes of autoantibodies during aging at an age of 30, 50, and 62 years, respectively. Furthermore, IgG autoantibodies, in particular those against ribosomal proteins, could be used as prediction markers for aging and age-related neurodegenerative diseases. Therefore, this study for the first time uncovers comprehensive autoimmunomic signatures for aging and age-related neurodegenerative diseases.

Emerging targets for the diagnosis of Parkinson's disease: examination of systemic biomarkers

Parkinson's disease (PD) is a highly prevalent and irreversible neurodegenerative disorder that is typically diagnosed in an advanced stage. Currently, there are no approved biomarkers that reliably identify PD patients before they have undergone extensive neuronal damage, eliminating the opportunity for future disease-modifying therapies to intervene in disease progression. This unmet need for diagnostic and therapeutic biomarkers has fueled PD research for decades, but these efforts have not yet yielded actionable results. Recently, studies exploring mechanisms underlying PD progression have offered insights into multisystemic contributions to pathology, challenging the classic perspective of PD as a disease isolated to the brain. This shift in understanding has opened the door to potential new biomarkers from multiple sites in the body. This review focuses on emerging candidates for PD biomarkers in the context of current diagnostic approaches and multiple organ systems that contribute to disease.

Evidence that Brain-Reactive Autoantibodies Contribute to Chronic Neuronal Internalization of Exogenous Amyloid-β1-42 and Key Cell Surface Proteins During Alzheimer's Disease Pathogenesis

Blood-brain barrier (BBB) permeability is a recognized early feature of Alzheimer’s disease (AD). In the present study, we examined consequences of increased BBB permeability on the development of AD-related pathology by tracking selected leaked plasma components and their interactions with neurons in vivo and in vitro. Histological sections of cortical regions of postmortem AD brains were immunostained to determine the distribution of amyloid-β_1-42 (Aβ₄₂), cathepsin D, IgG, GluR2/3, and alpha7 nicotinic acetylcholine receptor (α7nAChR). Results revealed that chronic IgG binding to pyramidal neurons coincided with internalization of Aβ_42, IgG, GluR2/3, and α7nAChR as well as lysosomal compartment expansion in these cells in regions of AD pathology. To test possible mechanistic interrelationships of these phenomena, we exposed differentiated SH-SY5Y neuroblastoma cells to exogenous, soluble Aβ₄₂ peptide and serum from AD and control subjects. The rate and extent of Aβ₄₂ internalization in these cells was enhanced by serum containing neuron-binding IgG autoantibodies. This was confirmed by treating cells with individual antibodies specific for α7nAChR, purified IgG from AD or non-AD sera, and sera devoid of IgG, in the presence of 100 nM Aβ₄₂. Initial co-localization of IgG, α7nAChR, and Aβ₄₂ was temporally and spatially linked to early endosomes (Rab11) and later to lysosomes (LAMP-1). Aβ₄₂ internalization was attenuated by treatment with monovalent F(ab) antibody fragments generated from purified IgG from AD serum and then rescued by coupling F(ab) fragments with divalent human anti-Fab. Overall, results suggest that cross-linking of neuron-binding autoantibodies targeting cell surface proteins can accelerate intraneuronal Aβ₄₂ deposition in AD.

CuATSM PET to diagnose age-related diseases: a systematic literature review

Purpose

Cu(II)-diacetyl-bis(N4-methylthiosemicarbazone) positron emission tomography (CuATSM PET) is a non-invasive imaging technique that can be used to detect hypoxia and inform prognosis in cancer. Hypoxia and oxidative stress are also hallmarks of various age-related diseases. Whether CuATSM PET has a role in the evaluation of hypoxia and oxidative stress in age-related diseases has yet to be established. The aim of this systematic review is to evaluate the utility of CuATSM PET in the diagnosis and management of age-related diseases.

Methods

EMBASE, Medline, Scopus, Web of Science and Psychinfo were systematically searched for articles published between January 1st 1997 and February 13th 2020. We included articles published in English reporting the use of CuATSM PET in the diagnosis and management of age-related diseases in humans or animals.

Results

Nine articles were included describing CuATSM PET measures in neurological and cardiovascular disease. There was higher CuATSM uptake in diseased compared to control subjects in Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), myocardial ischemia (MI), cardiac dysautonomia and atherosclerosis. Higher CuATSM uptake was seen in diseased compared to control anatomical areas in PD, cerebrovascular disease (CVD), MI and atherosclerosis. CuATSM uptake was associated with disease severity in PD, ALS, CVD and atherosclerosis. An association between CuATSM uptake and disease duration was shown in atherosclerosis.

Conclusion

CuATSM uptake is higher in neurological and cardiovascular diseases and associated with disease severity and duration. Further investigations using CuATSM PET in other age-related diseases are needed.

Genome-wide identification of m6A-associated single-nucleotide polymorphisms in Parkinson's disease

N⁶-methyladenosine (m⁶A)-associated single nucleotide polymorphisms (SNPs) play a vital role in several neurological diseases. However, little is known about the relationship between m⁶A modification and Parkinson's disease (PD). We investigated potential functional variants of m⁶A-SNPs from large-scale genome-wide association studies (GWAS) in PD patients. The candidate m⁶A-SNPs were further assessed by expression quantitative trait loci (eQTL) analysis and differential gene expression analysis. We identified 12 m⁶A-SNPs that were significantly associated with PD risk. Further, eQTL and expression analyses identified five of these m⁶A-SNPs (rs75072999 of GAK, rs1378602, rs4924839 and rs8071834 of ALKBH5, and rs1033500 of C6orf10) that were associated with altered gene expression in PD. Our results suggest that m⁶A-SNPs could play a role in PD risk. Future studies are needed to confirm these PD-associated m⁶A-SNPs and elucidate their mechanisms.

The Functional Roles and Applications of Immunoglobulins in Neurodegenerative Disease

Natural autoantibodies, immunoglobulins (Igs) that target self-proteins, are common in the plasma of healthy individuals; some of the autoantibodies play pathogenic roles in systemic or tissue-specific autoimmune diseases, such as rheumatoid arthritis and systemic lupus erythematosus. Recently, the field of autoantibody-associated diseases has expanded to encompass neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD), with related studies examining the functions of Igs in the central nervous system (CNS). Recent evidence suggests that Igs have various effects in the CNS; these effects are associated with the prevention of neurodegeneration, as well as induction. Here, we summarize the functional roles of Igs with respect to neurodegenerative disease (AD and PD), focusing on the target antigens and effector cell types. In addition, we review the current knowledge about the roles of these antibodies as diagnostic markers and immunotherapies.

The origin and nature of the complex autoantibody profile in cerebrospinal fluid

The present study demonstrates, using human protein microarrays and plasma and cerebrospinal fluid samples obtained pre-surgically and simultaneously from 46 hip fracture repair patients, that CSF exhibits an extraordinarily complex IgG autoantibody profile composed of thousands of autoantibodies. We show that the pattern of expression levels of individual autoantibodies in CSF closely mimics that in the blood, regardless of age, gender or the presence or absence of disease, indicative of a blood-based origin for CSF autoantibodies. In addition, using five longitudinal serum samples obtained from one healthy individual over a span of nine years, we found that blood autoantibody profiles are remarkably stable over a long period of time, and that autoantibody profiles in both blood and CSF show features that are common among different individuals as well as individual-specific. Lastly, we demonstrate that an elevated CSF/plasma autoantibody ratio is more common in elderly hip fracture repair patients that experienced post-operative delirium than in non-delirium subjects, thus highlighting the crucial role that blood-brain and/or blood-CSF barrier compromise may play in the development of post-operative delirium.

Identification of distinct blood-based biomarkers in early stage of Parkinson's disease

Parkinson's disease (PD) is a slowly progressive geriatric disease, which can be one of the leading causes of serious socioeconomic burden in the aging society. Clinical trials suggest that prompt treatment of early-stage Parkinson's disease (EPD) may slow down the disease progress and have a better response. Therefore, conducting proteomics study to identify biomarkers for the diagnosis and disease-modifying therapies of EPD is vital. We aimed at identifying distinct protein autoantibody biomarkers of EPD by using the database of GSE62283 based on the platform GPL13669 downloaded from Gene Expression Omnibus database. Differentially expressed proteins (DEPs) between the EPD group (n = 103) and the normal control (NC) group (n = 111) were identified by protein-specific t test. Cluster analysis of DEPs was conducted by protein-protein interaction network to detect hub proteins. The hub proteins were then evaluated to determine the distinct biomarkers by principal component analysis, as well as functional and pathway enrichment analysis. Their biological functions were confirmed by gene ontology functional (GO) and Kyoto encyclopedia of genes and genomes pathway enrichment (KEGG). Two biomarkers, mitochondrial ribosome recycling factor (MRRF) and ribosomal protein S18 (RPS18), distinguished the EPD samples from the NC samples, and they were regarded as high-confidence distinct protein autoantibody biomarkers of EPD. The most significant GO function was protein serine/threonine kinase activity (GO: 0004674) and most of DEPs were enriched in ATP binding in molecular function category (GO: 0005524). These results may help in establishing the prompt and accurate diagnosis of EPD and may also contribute to develop mechanism-based treatments.

Detection of early-stage Alzheimer's pathology using blood-based autoantibody biomarkers in elderly hip fracture repair patients

Post-operative delirium (POD) is the most common complication following major surgery in non-demented older (>65 y/o) patients. Patients experiencing POD show increased risk for future cognitive decline, including mild cognitive impairment (MCI) and Alzheimer’s disease (AD) and, conversely, patients with cognitive decline at surgery show increased risk for POD. Here, we demonstrate that a previously established panel of AD-driven MCI (ADMCI) autoantibody (aAB) biomarkers can be used to detect prodromal AD pre-surgically in individuals admitted into the hospital for hip fracture repair (HFR) surgery. Plasma from 39 STRIDE (STRIDE: A Strategy to Reduce the Incidence of Postoperative Delirium in Elderly Patients) HFR patients and sera from 25 age- and sex-matched non-demented and non-surgical controls were screened using human protein microarrays to measure expression of a panel of 44 previously identified MCI aAB biomarkers. The predictive classification accuracy of the aAB biomarker panel was evaluated using Random Forest (RF). The ADMCI aAB biomarkers successfully distinguished 21 STRIDE HFR patients (CDR = 0.5) from 25 matched non-surgical controls with an overall accuracy of 91.3% (sensitivity = 95.2%; specificity = 88.0%). The ADMCI aAB panel also correctly identified six patients with preoperative CDR = 0 who later converted to CDR = 0.5 or >1 at one-year follow-up. Lastly, the majority of cognitively normal (CDR = 0) STRIDE HFR subjects that were positive for CSF AD biomarkers based on the A/T/N classification system were likewise classified as ADMCI aAB-positive using the biomarker panel. Results suggest that pre-surgical detection of ADMCI aAB biomarkers can readily identify HFR patients with likely early-stage AD pathology using pre-surgery blood samples, opening up the potential for early, blood-based AD detection and improvements in peri- and postoperative patient management.

High-throughput autoantibody analysis in malignant pleural effusion and tuberculosis pleural effusion

BACKGROUND

Malignant pleural effusion (MPE) and tuberculosis pleural effusion (TPE) are 2 kinds of common pleural diseases. Finding efficient and accurate biomarkers to distinguish the 2 is of benefit to basic and clinical research. In the present study, we carried out the first high-throughput autoantibody chip to screen the beneficial biomarker with samples of MPE and TPE and the corresponding serum.

METHODS

We collected pleural effusion and serum of patients with MPE (n = 10) and TPE (n = 10) who had been in Beijing Chao-Yang hospital from June 2013 to August 2014. Using RayBio Human Protein Array-G2 to measure the concentration of 487 defined autoantibodies.

RESULTS

Fold changes of Bcl-2-like protein 11 (BIM) autoantibody in MPE-serum/TPE-serum and MPE/TPE groups were 10 (P = .019) and 6 (P = .001); for decorin autoantibody, MPE-serum/TPE-serum ratio was 0.6 (P = .029), and MPE/TPE ratio was 0.3 (P < .001).

CONCLUSION

BIM autoantibody is a promising MPE biomarker by high-throughput autoantibody analysis in MPE and TPE.

AAgMarker 1.0: a resource of serological autoantigen biomarkers for clinical diagnosis and prognosis of various human diseases

Autoantibodies are produced to target an individual's own antigens (e.g. proteins). They can trigger autoimmune responses and inflammation, and thus, cause many types of diseases. Many high-throughput autoantibody profiling projects have been reported for unbiased identification of serological autoantigen-based biomarkers. However, a lack of centralized data portal for these published assays has been a major obstacle to further data mining and cross-evaluate the quality of these datasets generated from different diseases. Here, we introduce a user-friendly database, AAgMarker 1.0, which collects many published raw datasets obtained from serum profiling assays on the proteome microarrays, and provides a toolbox for mining these data. The current version of AAgMarker 1.0 contains 854 serum samples, involving 136 092 proteins. A total of 7803 (4470 non-redundant) candidate autoantigen biomarkers were identified and collected for 12 diseases, such as Alzheimer's disease, Bechet's disease and Parkinson's disease. Seven statistical parameters are introduced to quantitatively assess these biomarkers. Users can retrieve, analyse and compare the datasets through basic search, advanced search and browse. These biomarkers are also downloadable by disease terms. The AAgMarker 1.0 is now freely accessible at http://bioinfo.wilmer.jhu.edu/AAgMarker/. We believe this database will be a valuable resource for the community of both biomedical and clinical research.

An NMR-based lipidomic approach to identify Parkinson's disease-stage specific lipoprotein-lipid signatures in plasma

Disturbances in lipid composition and lipoproteins metabolism can play a crucial role in the pathogenesis of Parkinson's disease (PD) and other neurodegenerative diseases. The lipidomic strategy proposed here involves lipoprotein profiling using NMR spectroscopy and multivariate data pre-processing and analysis tools on 94 plasma samples (belonging to 38 early-stage PD patients, 10 PD-related dementia patients, 23 persons with Alzheimer's dementia, and 23 healthy control subjects) to firstly differentiate PD patients (irrespective of the stage of the disease) from persons with Alzheimer's disease (AD) as well as from controls, and then to discriminate among PD patients according to disease severity. The whole data set was subdivided into 86 training and 8 external test samples for validation purposes. A two-step classification scheme, based on linear discriminant analysis with variable selection accomplished by a stepwise orthogonalisation procedure, was proposed to optimise classification performance. Careful pre-processing of NMR signals was crucial to ensure data set quality. A total of 30 chemical shift buckets enabled differentiation between PD patients (regardless of disease severity), AD and control subjects, providing classification, cross-validation and external prediction rates of 100% in all cases. Only 15 variables were required to further discriminate between early-stage PD and PD-related dementia, again with 100% correct classifications, and internal/external predictions. The simplicity and effectiveness of the classification methodology proposed support the use of NMR spectroscopy, in combination with chemometrics, as a viable alternative diagnostic tool to conventional PD clinical diagnosis.

Naturally occurring antibodies isolated from PD patients inhibit synuclein seeding in vitro and recognize Lewy pathology

Deposition of α-synuclein into Lewy bodies and Lewy neurites is the hallmark of Parkinson’s disease (PD). It is hypothesized that α-synuclein pathology spreads by a “prion-like” mechanism (i.e., by seeded aggregation or templated misfolding). Therefore, various extracellular α-synuclein conformers and/or posttranslational modifications may serve as biomarkers of disease or potential targets for novel interventions. To explore whether the antibody repertoires of PD patients contain anti-α-synuclein antibodies that can potentially be used as markers or immunotherapy, we interrogated peripheral IgG⁺ memory B cells from PD patients for reactivity to α-synuclein. In total, ten somatically mutated antibodies were recovered, suggesting the presence of an ongoing antigen-driven immune response. The three antibodies that had the highest affinity to recombinant full-length α-synuclein, aSyn-323.1, aSyn-336.1 and aSyn-338.1, were characterized further and shown to recognize epitopes in the C terminus of α-synuclein with binding affinities between 0.3 and 2.8 μM. Furthermore, all three antibodies were able to neutralize the “seeding” of intracellular synuclein aggregates in an in vitro α-synuclein seeding assay. Finally, differential reactivities were observed for all three human anti-α-synuclein antibodies across tissue treatment conditions by immunohistochemistry. Our results suggest that the memory B-cell repertoire of PD patients might represent a potential source of biomarkers and therapies.

Autoantibody Biomarker Discovery in Primary Open Angle Glaucoma Using Serological Proteome Analysis (SERPA)

Glaucoma is an optic neurological disorder and the leading cause of irreversible blindness worldwide, with primary open angle glaucoma (POAG) as its most prevalent form. An early diagnosis of the disease is crucial to prevent loss of vision. Mechanisms behind glaucoma pathogenesis are not completely understood, but disease related alterations in the serological autoantibody profile indicate an immunologic component. These changes in immunoreactivity may serve as potential biomarkers for glaucoma diagnostics. We aimed to identify novel disease related autoantibodies targeting antigens in the trabecular meshwork as biomarkers to support early detection of POAG. We used serological proteome analysis (SERPA) for initial autoantibody profiling in a discovery sample set. The identified autoantibodies were validated by protein microarray analysis in a larger cohort with 60 POAG patients and 45 control subjects. In this study, we discovered CALD1, PGAM1, and VDAC2 as new biomarker candidates. With the use of artificial neural networks, the panel of these candidates and the already known markers HSPD1 and VIM was able to classify subjects into POAG patients and non-glaucomatous controls with a sensitivity of 81% and a specificity of 93%. These results suggest the benefit of these potential autoantibody biomarkers for utilization in glaucoma diagnostics.

Identification of potential blood biomarkers for Parkinson's disease by gene expression and DNA methylation data integration analysis

BACKGROUND

Blood-based gene expression or epigenetic biomarkers of Parkinson's disease (PD) are highly desirable. However, accuracy and specificity need to be improved, and methods for the integration of gene expression with epigenetic data need to be developed in order to make this feasible.

METHODS

Whole blood gene expression data and DNA methylation data were downloaded from Gene Expression Omnibus (GEO) database. A linear model was used to identify significantly differentially expressed genes (DEGs) and differentially methylated genes (DMGs) according to specific gene regions 5'-C-phosphate-G-3' (CpGs) or all gene regions CpGs in PD. Gene set enrichment analysis was then applied to DEGs and DMGs. Subsequently, data integration analysis was performed to identify robust PD-associated blood biomarkers. Finally, the random forest algorithm and a leave-one-out cross validation method were performed to construct classifiers based on gene expression data integrated with methylation data.

RESULTS

Eighty-five (85) significantly hypo-methylated and upregulated genes in PD patients compared to healthy controls were identified. The dominant hypo-methylated regions of these genes were significantly different. Some genes had a single dominant hypo-methylated region, while others had multiple dominant hypo-methylated regions. One gene expression classifier and two gene methylation classifiers based on all or dominant methylation-altered region CpGs were constructed. All have a good prediction power for PD.

CONCLUSIONS

Gene expression and methylation data integration analysis identified a blood-based 53-gene signature, which could be applied as a biomarker for PD.

Antibodies in the Diagnosis, Prognosis, and Prediction of Psychotic Disorders

Blood-based biomarker discovery for psychotic disorders has yet to impact upon routine clinical practice. In physical disorders antibodies have established roles as diagnostic, prognostic and predictive (theranostic) biomarkers, particularly in disorders thought to have a substantial autoimmune or infective aetiology. Two approaches to antibody biomarker identification are distinguished: a "top-down" approach, in which antibodies to specific antigens are sought based on the known function of the antigen and its putative role in the disorder, and emerging "bottom-up" or "omics" approaches that are agnostic as to the significance of any one antigen, using high-throughput arrays to identify distinctive components of the antibody repertoire. Here we review the evidence for antibodies (to self-antigens as well as infectious organism and dietary antigens) as biomarkers of diagnosis, prognosis, and treatment response in psychotic disorders. Neuronal autoantibodies have current, and increasing, clinical utility in the diagnosis of organic or atypical psychosis syndromes. Antibodies to selected infectious agents show some promise in predicting cognitive impairment and possibly other symptom domains (eg, suicidality) within psychotic disorders. Finally, infectious antibodies and neuronal and other autoantibodies have recently emerged as potential biomarkers of response to anti-infective therapies, immunotherapies, or other novel therapeutic strategies in psychotic disorders, and have a clear role in stratifying patients for future clinical trials. As in nonpsychiatric disorders, combining biomarkers and large-scale use of "bottom-up" approaches to biomarker identification are likely to maximize the eventual clinical utility of antibody biomarkers in psychotic disorders.

Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry

In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.

Autoantibodies as diagnostic biomarkers for the detection and subtyping of multiple sclerosis

The goal of this preliminary proof-of-concept study was to use human protein microarrays to identify blood-based autoantibody biomarkers capable of diagnosing multiple sclerosis (MS). Using sera from 112 subjects, including 51 MS subjects, autoantibody biomarkers effectively differentiated MS subjects from age- and gender-matched normal and breast cancer controls with 95.0% and 100% overall accuracy, but not from subjects with Parkinson's disease. Autoantibody biomarkers were also useful in distinguishing subjects with the relapsing-remitting form of MS from those with the secondary progressive subtype. These results demonstrate that autoantibodies can be used as noninvasive blood-based biomarkers for the detection and subtyping of MS.

Modeling the Attractor Landscape of Disease Progression: a Network-Based Approach

Genome-wide regulatory networks enable cells to function, develop, and survive. Perturbation of these networks can lead to appearance of a disease phenotype. Inspired by Conrad Waddington's epigenetic landscape of cell development, we use a Hopfield network formalism to construct an attractor landscape model of disease progression based on protein- or gene-correlation networks of Parkinson's disease, glioma, and colorectal cancer. Attractors in this landscape correspond to normal and disease states of the cell. We introduce approaches to estimate the size and robustness of these attractors, and take a network-based approach to study their biological features such as the key genes and their functions associated with the attractors. Our results show that the attractor of cancer cells is wider than the attractor of normal cells, suggesting a heterogeneous nature of cancer. Perturbation analysis shows that robustness depends on characteristics of the input data (number of samples per time-point, and the fraction which converge to an attractor). We identify unique gene interactions at each stage, which reflect the temporal rewiring of the gene regulatory network (GRN) with disease progression. Our model of the attractor landscape, constructed from large-scale gene expression profiles of individual patients, captures snapshots of disease progression and identifies gene interactions specific to different stages, opening the way for development of stage-specific therapeutic strategies.

Blood-based biomarkers in Alzheimer disease: Current state of the science and a novel collaborative paradigm for advancing from discovery to clinic

The last decade has seen a substantial increase in research focused on the identification of blood-based biomarkers that have utility in Alzheimer's disease (AD). Blood-based biomarkers have significant advantages of being time- and cost-efficient as well as reduced invasiveness and increased patient acceptance. Despite these advantages and increased research efforts, the field has been hampered by lack of reproducibility and an unclear path for moving basic discovery toward clinical utilization. Here we reviewed the recent literature on blood-based biomarkers in AD to provide a current state of the art. In addition, a collaborative model is proposed that leverages academic and industry strengths to facilitate the field in moving past discovery only work and toward clinical use. Key resources are provided. This new public-private partnership model is intended to circumvent the traditional handoff model and provide a clear and useful paradigm for the advancement of biomarker science in AD and other neurodegenerative diseases.

Recent developments in circulating biomarkers in Parkinson’s disease: the potential use of miRNAs in a clinical setting

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, affecting 5% of the elderly population. PD diagnosis is still based on the identification of neuromotor symptoms although nonmotor manifestations emerge years prior to diagnosis. The discovery of biomarkers at the earliest stages of PD is of extreme interest. miRNAs have been considered potential biomarkers for neurodegenerative diseases, but only a limited number have been found to be PD related. This review focuses on the current findings in the field of circulating miRNAs in PD and the challenges surrounding clinical utility and validation. We briefly describe the more established circulating biomarkers in PD and provide a more thorough review of miRNAs differentially expressed in PD. We highlight their potential for being considered as biomarkers for diagnosis while emphasizing the challenges for adequate validation of the findings and how miRNAs can be envisioned in a clinical setting satisfying regulatory bodies.

Blood biomarker for Parkinson disease: peptoids

Parkinson disease (PD) is the second most common neurodegenerative disease. Because dopaminergic neuronal loss begins years before motor symptoms appear, a biomarker for the early identification of the disease is critical for the study of putative neuroprotective therapies. Brain imaging of the nigrostriatal dopamine system has been used as a biomarker for early disease along with cerebrospinal fluid analysis of α-synuclein, but a less costly and relatively non-invasive biomarker would be optimal. We sought to identify an antibody biomarker in the blood of PD patients using a combinatorial peptoid library approach. We examined serum samples from 75 PD patients, 25 de novo PD patients, and 104 normal control subjects in the NINDS Parkinson’s Disease Biomarker Program. We identified a peptoid, PD2, which binds significantly higher levels of IgG3 antibody in PD versus control subjects (P<0.0001) and is 68% accurate in identifying PD. The PD2 peptoid is 84% accurate in identifying de novo PD. Also, IgG3 levels are significantly higher in PD versus control serum (P<0.001). Finally, PD2 levels are positively correlated with the United Parkinson’s Disease Rating Scale score (r=0.457, P<0001), a marker of disease severity. The PD2 peptoid may be useful for the early-stage identification of PD, and serve as an indicator of disease severity. Additional studies are needed to validate this PD biomarker.

The Immune System and Neuroinflammation as Potential Sources of Blood-Based Biomarkers for Alzheimer's Disease, Parkinson's Disease, and Huntington's Disease

Neurodegenerative diseases are characterized by a loss of neurons that leads to cognitive and behavioral dysfunction. Alzheimer's disease (AD) is the most common neurodegenerative disorder affecting millions of people in the United States and worldwide, followed by Parkinson's disease (PD). While some early onset forms of AD and PD are hereditary, the sporadic or late-onset cases are believed to result from lifestyle and environmental factors. On the contrary, Huntington's disease (HD) is a neurodegenerative disease solely caused by mutations in the gene for huntingtin protein. The disease mechanisms at play for all three disorders remain elusive, hampering efforts to develop effective therapeutic interventions. In light of this, the discovery of robust biomarkers is crucial in order to identify people at risk for AD and PD, preferably before symptoms arise. For all three diseases, the identification of biomarkers would not only allow development of treatments but also evaluation and adjustment of these with disease progression. It is now understood that neuroinflammation plays a crucial role in neurodegenerative diseases, along with subsequent immune activation. Therefore, research is actively ongoing to discover and evaluate inflammatory and immune-related biomarkers. Recent progress in this area for AD, PD, and HD is presented here.

Detection of Alzheimer's disease at mild cognitive impairment and disease progression using autoantibodies as blood-based biomarkers

Introduction

There is an urgent need to identify biomarkers that can accurately detect and diagnose Alzheimer's disease (AD). Autoantibodies are abundant and ubiquitous in human sera and have been previously demonstrated as disease-specific biomarkers capable of accurately diagnosing mild-moderate stages of AD and Parkinson's disease.

Methods

Sera from 236 subjects, including 50 mild cognitive impairment (MCI) subjects with confirmed low CSF Aβ42 levels, were screened with human protein microarrays to identify potential biomarkers for MCI. Autoantibody biomarker performance was evaluated using Random Forest and Receiver Operating Characteristic curves.

Results

Autoantibody biomarkers can differentiate MCI patients from age-matched and gender-matched controls with an overall accuracy, sensitivity, and specificity of 100.0%. They were also capable of differentiating MCI patients from those with mild-moderate AD and other neurologic and non-neurologic controls with high accuracy.

Discussion

Autoantibodies can be used as noninvasive and effective blood-based biomarkers for early diagnosis and staging of AD.