Multiomics Profiling of Alzheimer's Disease Serum for the Identification of Autoantibody Biomarkers

The early diagnosis of Alzheimer's disease: Blood-based panel biomarker discovery by proteomics and metabolomics

Diagnosis and prediction of Alzheimer's disease (AD) are increasingly pressing in the early stage of the disease because the biomarker-targeted therapies may be most effective. Diagnosis of AD largely depends on the clinical symptoms of AD. Currently, cerebrospinal fluid biomarkers and neuroimaging techniques are considered for clinical detection and diagnosis. However, these clinical diagnosis results could provide indications of the middle and/or late stages of AD rather than the early stage, and another limitation is the complexity attached to limited access, cost, and perceived invasiveness. Therefore, the prediction of AD still poses immense challenges, and the development of novel biomarkers is needed for early diagnosis and urgent intervention before the onset of obvious phenotypes of AD. Blood-based biomarkers may enable earlier diagnose and aid detection and prognosis for AD because various substances in the blood are vulnerable to AD pathophysiology. The application of a systematic biological paradigm based on high-throughput techniques has demonstrated accurate alterations of molecular levels during AD onset processes, such as protein levels and metabolite levels, which may facilitate the identification of AD at an early stage. Notably, proteomics and metabolomics have been used to identify candidate biomarkers in blood for AD diagnosis. This review summarizes data on potential blood-based biomarkers identified by proteomics and metabolomics that are closest to clinical implementation and discusses the current challenges and the future work of blood-based candidates to achieve the aim of early screening for AD. We also provide an overview of early diagnosis, drug target discovery and even promising therapeutic approaches for AD.

Autoantibodies to BACE1 promote Aβ accumulation and neurodegeneration in Alzheimer's disease

The profile of autoantibodies is dysregulated in patients with Alzheimer's disease (AD). Autoantibodies to beta-site amyloid precursor protein (APP)-cleaving enzyme 1 (BACE1) are present in human blood. This study aims to investigate the clinical relevance and pathophysiological roles of autoantibodies to BACE1 in AD. Clinical investigations were conducted in two independent cohorts, the Chongqing cohort, and the Australian Imaging, Biomarkers, and Lifestyle (AIBL) cohort. The Chongqing cohort included 55 AD patients, 28 patients with non-AD dementia, and 70 cognitively normal subjects (CN). The AIBL cohort included 162 Aβ-PET- CN, 169 Aβ-PET+ cognitively normal subjects (preclinical AD), and 31 Aβ-PET+ cognitively impaired subjects (Clinical AD). Plasma autoantibodies to BACE1 were determined by one-site Elisa. The associations of plasma autoantibodies to BACE1 with brain Aβ load and cognitive trajectory were investigated. The effects of autoantibodies to BACE1 on AD-type pathologies and underlying mechanisms were investigated in APP/PS1 mice and SH/APPswe/PS1wt cell lines. In the Chongqing cohort, plasma autoantibodies to BACE1 were higher in AD patients, in comparison with CN and non-AD dementia patients. In the AIBL cohort, plasma autoantibodies to BACE1 were highest in clinical AD patients, followed by preclinical AD and CN subjects. Higher autoantibodies to BACE1 were associated with an increased incidence of brain amyloid positivity conversion during follow-up. Autoantibodies to BACE1 exacerbated brain amyloid deposition and subsequent AD-type pathologies, including Tau hyperphosphorylation, neuroinflammation, and neurodegeneration in APP/PS1 mice. Autoantibodies to BACE1 increased Aβ production by promoting BACE1 expression through inhibiting PPARγ signaling. These findings suggest that autoantibodies to BACE1 are pathogenic in AD and the upregulation of these autoantibodies may promote the development of the disease. This study offers new insights into the mechanism of AD from an autoimmune perspective.

Autoantibodies in cancer: a systematic review of their clinical role in the most prevalent cancers

Although blood autoantibodies were initially associated with autoimmune diseases, multiple evidence have been accumulated showing their presence in many types of cancer. This has opened their use in clinics, since cancer autoantibodies might be useful for early detection, prognosis, and monitoring of cancer patients. In this review, we discuss the different techniques available for their discovery and validation. Additionally, we discuss here in detail those autoantibody panels verified in at least two different reports that should be more likely to be specific of each of the four most incident cancers. We also report the recent developed kits for breast and lung cancer detection mostly based on autoantibodies and the identification of novel therapeutic targets because of the screening of the cancer humoral immune response. Finally, we discuss unsolved issues that still need to be addressed for the implementation of cancer autoantibodies in clinical routine for cancer diagnosis, prognosis, and/or monitoring.

Micromotor-based electrochemical immunoassays for reliable determination of amyloid-β (1-42) in Alzheimer's diagnosed clinical samples

Alzheimer's disease (AD), in addition to being the most common cause of dementia, is very difficult to diagnose, with the 42-amino acid form of Aβ (Aβ-42) being one of the main biomarkers used for this purpose. Despite the enormous efforts made in recent years, the technologies available to determine Aβ-42 in human samples require sophisticated instrumentation, present high complexity, are sample and time-consuming, and are costly, highlighting the urgent need not only to develop new tools to overcome these limitations but to provide an early detection and treatment window for AD, which is a top-challenge. In recent years, micromotor (MM) technology has proven to add a new dimension to clinical biosensing, enabling ultrasensitive detections in short times and microscale environments. To this end, here an electrochemical immunoassay based on polypyrrole (PPy)/nickel (Ni)/platinum nanoparticles (PtNPs) MM is proposed in a pioneering manner for the determination of Aβ-42 in left prefrontal cortex brain tissue, cerebrospinal fluid, and plasma samples from patients with AD. MM combines the high binding capacity of their immunorecognition external layer with self-propulsion through the catalytic generation of oxygen bubbles in the internal layer due to decomposition of hydrogen peroxide as fuel, allowing rapid bio-detection (15 min) of Aβ-42 with excellent selectivity and sensitivity (LOD = 0.06 ng/mL). The application of this disruptive technology to the analysis of just 25 μL of the three types of clinical samples provides values concordant with the clinical values reported, thus confirming the potential of the MM approach to assist in the reliable, simple, fast, and affordable diagnosis of AD by determining Aβ-42.

HDAC1/2 inhibitor therapy improves multiple organ systems in aged mice

Aging increases the risk of age-related diseases, imposing substantial healthcare and personal costs. Targeting fundamental aging mechanisms pharmacologically can promote healthy aging and reduce this disease susceptibility. In this work, we employed transcriptome-based drug screening to identify compounds emulating transcriptional signatures of long-lived genetic interventions. We discovered compound 60 (Cmpd60), a selective histone deacetylase 1 and 2 (HDAC1/2) inhibitor, mimicking diverse longevity interventions. In extensive molecular, phenotypic, and bioinformatic assessments using various cell and aged mouse models, we found Cmpd60 treatment to improve age-related phenotypes in multiple organs. Cmpd60 reduces renal epithelial-mesenchymal transition and fibrosis in kidney, diminishes dementia-related gene expression in brain, and enhances cardiac contractility and relaxation for the heart. In sum, our two-week HDAC1/2 inhibitor treatment in aged mice establishes a multi-tissue, healthy aging intervention in mammals, holding promise for therapeutic translation to promote healthy aging in humans.

Specific serum autoantibodies predict the development and progression of Alzheimer's disease with high accuracy

Autoimmunity plays a key role in the pathogenesis of Alzheimer's disease (AD). However, whether autoantibodies in peripheral blood can be used as biomarkers for AD has been elusive. Serum samples were obtained from 1,686 participants, including 767 with AD, 146 with mild cognitive impairment (MCI), 255 with other neurodegenerative diseases, and 518 healthy controls. Specific autoantibodies were measured using a custom-made immunoassay. Multivariate support vector machine models were employed to investigate the correlation between serum autoantibody levels and disease states. As a result, seven candidate AD-specific autoantibodies were identified, including MAPT, DNAJC8, KDM4D, SERF1A, CDKN1A, AGER, and ASXL1. A classification model with high accuracy (area under the curve (AUC) = 0.94) was established. Importantly, these autoantibodies could distinguish AD from other neurodegenerative diseases and out-performed amyloid and tau protein concentrations in cerebrospinal fluid in predicting cognitive decline (P < 0.001). This study indicated that AD onset and progression are possibly accompanied by an unappreciated serum autoantibody response. Therefore, future studies could optimize its application as a convenient biomarker for the early detection of AD.

Climate Stressors and Physiological Dysregulations: Mechanistic Connections to Pathologies

This review delves into the complex relationship between environmental factors, their mechanistic cellular and molecular effects, and their significant impact on human health. Climate change is fueled by industrialization and the emission of greenhouse gases and leads to a range of effects, such as the redistribution of disease vectors, higher risks of disease transmission, and shifts in disease patterns. Rising temperatures pose risks to both food supplies and respiratory health. The hypothesis addressed is that environmental stressors including a spectrum of chemical and pathogen exposures as well as physical and psychological influences collectively impact genetics, metabolism, and cellular functions affecting physical and mental health. The objective is to report the mechanistic associations linking environment and health. As environmental stressors intensify, a surge in health conditions, spanning from allergies to neurodegenerative diseases, becomes evident; however, linkage to genetic-altered proteomics is more hidden. Investigations positing that environmental stressors cause mitochondrial dysfunction, metabolic syndrome, and oxidative stress, which affect missense variants and neuro- and immuno-disorders, are reported. These disruptions to homeostasis with dyslipidemia and misfolded and aggregated proteins increase susceptibility to cancers, infections, and autoimmune diseases. Proposed interventions, such as vitamin B supplements and antioxidants, target oxidative stress and may aid mitochondrial respiration and immune balance. The mechanistic interconnections of environmental stressors and disruptions in health need to be unraveled to develop strategies to protect public health.

Applications of multi-omics analysis in human diseases

Multi-omics usually refers to the crossover application of multiple high-throughput screening technologies represented by genomics, transcriptomics, single-cell transcriptomics, proteomics and metabolomics, spatial transcriptomics, and so on, which play a great role in promoting the study of human diseases. Most of the current reviews focus on describing the development of multi-omics technologies, data integration, and application to a particular disease; however, few of them provide a comprehensive and systematic introduction of multi-omics. This review outlines the existing technical categories of multi-omics, cautions for experimental design, focuses on the integrated analysis methods of multi-omics, especially the approach of machine learning and deep learning in multi-omics data integration and the corresponding tools, and the application of multi-omics in medical researches (e.g., cancer, neurodegenerative diseases, aging, and drug target discovery) as well as the corresponding open-source analysis tools and databases, and finally, discusses the challenges and future directions of multi-omics integration and application in precision medicine. With the development of high-throughput technologies and data integration algorithms, as important directions of multi-omics for future disease research, single-cell multi-omics and spatial multi-omics also provided a detailed introduction. This review will provide important guidance for researchers, especially who are just entering into multi-omics medical research.

Fiber-Type Shifting in Sarcopenia of Old Age: Proteomic Profiling of the Contractile Apparatus of Skeletal Muscles

The progressive loss of skeletal muscle mass and concomitant reduction in contractile strength plays a central role in frailty syndrome. Age-related neuronal impairments are closely associated with sarcopenia in the elderly, which is characterized by severe muscular atrophy that can considerably lessen the overall quality of life at old age. Mass-spectrometry-based proteomic surveys of senescent human skeletal muscles, as well as animal models of sarcopenia, have decisively improved our understanding of the molecular and cellular consequences of muscular atrophy and associated fiber-type shifting during aging. This review outlines the mass spectrometric identification of proteome-wide changes in atrophying skeletal muscles, with a focus on contractile proteins as potential markers of changes in fiber-type distribution patterns. The observed trend of fast-to-slow transitions in individual human skeletal muscles during the aging process is most likely linked to a preferential susceptibility of fast-twitching muscle fibers to muscular atrophy. Studies with senescent animal models, including mostly aged rodent skeletal muscles, have confirmed fiber-type shifting. The proteomic analysis of fast versus slow isoforms of key contractile proteins, such as myosin heavy chains, myosin light chains, actins, troponins and tropomyosins, suggests them as suitable bioanalytical tools of fiber-type transitions during aging.

Dual ankyrinG and subpial autoantibodies in a man with well-controlled HIV infection with steroid-responsive meningoencephalitis: A case report

Neuroinvasive infection is the most common cause of meningoencephalitis in people living with human immunodeficiency virus (HIV), but autoimmune etiologies have been reported. We present the case of a 51-year-old man living with HIV infection with steroid-responsive meningoencephalitis whose comprehensive pathogen testing was non-diagnostic. Subsequent tissue-based immunofluorescence with acute-phase cerebrospinal fluid revealed anti-neural antibodies localizing to the axon initial segment (AIS), the node of Ranvier (NoR), and the subpial space. Phage display immunoprecipitation sequencing identified ankyrinG (AnkG) as the leading candidate autoantigen. A synthetic blocking peptide encoding the PhIP-Seq-identified AnkG epitope neutralized CSF IgG binding to the AIS and NoR, thereby confirming a monoepitopic AnkG antibody response. However, subpial immunostaining persisted, indicating the presence of additional autoantibodies. Review of archival tissue-based staining identified candidate AnkG autoantibodies in a 60-year-old woman with metastatic ovarian cancer and seizures that were subsequently validated by cell-based assay. AnkG antibodies were not detected by tissue-based assay and/or PhIP-Seq in control CSF (N = 39), HIV CSF (N = 79), or other suspected and confirmed neuroinflammatory CSF cases (N = 1,236). Therefore, AnkG autoantibodies in CSF are rare but extend the catalog of AIS and NoR autoantibodies associated with neurological autoimmunity.

Associations of Naturally Occurring Antibodies to Presenilin-1 with Brain Amyloid-β Load and Cognitive Impairment in Alzheimer's Disease

BACKGROUND

Imbalance between the production and clearance of amyloid-β (Aβ) promotes the development of Alzheimer's disease (AD). Presenilin-1 (PS1) is the catalytic subunit of γ-secretase, which is involved in the process of Aβ production. The profiles of autoantibodies are dysregulated in AD patients.

OBJECTIVE

This study aims to investigate the relative levels and clinical relevance of naturally occurring antibodies to PS1 (NAbs-PS1) in AD.

METHODS

A total of 55 subjects with AD (including both dementia and mild cognitive impairment due to AD), 28 subjects with cognitive impairment (including both dementia and mild cognitive impairment) not due to AD (non-AD CI), and 70 cognitively normal (CN) subjects were recruited. One-site ELISA was utilized to determine the relative levels of NAbs-PS1 in plasma.

RESULTS

AD subjects had lower plasma levels of NAbs-PS1 than CN and non-AD CI subjects. Plasma NAbs-PS1 were negatively associated with the brain Aβ load, as reflected by PET-PiB SUVR, and were positively associated with cognitive functions of participants. Plasma NAbs-PS1 discriminated AD patients from CN with an area under the curve (AUC) of 0.730, a sensitivity of 69.09%, and a specificity of 67.14%, and they discriminated AD patients from non-AD CI subjects with an AUC of 0.750, a specificity of 70.91%, and a sensitivity of 71.43%.

CONCLUSION

This study found an aberrant immunological phenotype in AD patients. Further investigations are needed to determine the pathophysiological functions of NAbs-PS1 in AD.

Omics-based biomarkers discovery for Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorders presenting with the pathological hallmarks of amyloid plaques and tau tangles. Over the past few years, great efforts have been made to explore reliable biomarkers of AD. High-throughput omics are a technology driven by multiple levels of unbiased data to detect the complex etiology of AD, and it provides us with new opportunities to better understand the pathophysiology of AD and thereby identify potential biomarkers. Through revealing the interaction networks between different molecular levels, the ultimate goal of multi-omics is to improve the diagnosis and treatment of AD. In this review, based on the current AD pathology and the current status of AD diagnostic biomarkers, we summarize how genomics, transcriptomics, proteomics and metabolomics are all conducing to the discovery of reliable AD biomarkers that could be developed and used in clinical AD management.

Development of a protein microarray for profiling circulating autoantibodies in human diseases

PURPOSE

To develop a robust microarray platform to detect thousands of serological autoantibodies (AAbs) simultaneously in different diseases.

EXPERIMENTAL DESIGN

An AAbMap microarray was prepared by printing a total of 4032 purified His-tagged human proteins and peptide probes on a chemically-modified slide. The sensitivity, dynamic range, and the inter- and intra-array reproducibility of the AAb microarray were then systematically tested and optimized. Finally, the large-scale profiling of AAbs in the serum of patients with different human diseases using the AAbMap microarray was demonstrated.

RESULTS

The dynamic range of antibody (Ab) detection was 2 to 3 orders of magnitude with the lowest limit of detection (LOD) of 68 pg/mL. The intra-array (r) correlation of duplicate spots was 1.00, whereas the inter-array correlations between different arrays and batches were 0.99 and 0.97 to 0.98, respectively. Notably, 132, 266, 171, and 84 AAbs were detected in pooled serum from healthy controls (HCs) or patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), or lung cancer (LC), respectively. These AAbs included antibodies that target well-known disease biomarkers, such as anti-cyclic citrullinated peptide, anti-ribonucleoprotein, and anti-nucleosome.

CONCLUSIONS AND CLINICAL RELEVANCE

We developed a microarray platform to measure thousands of serological AAbs simultaneously with high sensitivity and reproducibility. The array can help study autoimmunity and complement genomics, proteomics, and metabolomics data for systematic investigations of human diseases.