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

Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches

Alzheimer's disease has an increasing prevalence in the population world-wide, yet current diagnostic methods based on recommended biomarkers are only available in specialized clinics. Due to these circumstances, Alzheimer's disease is usually diagnosed late, which contrasts with the currently available treatment options that are only effective for patients at an early stage. Blood-based biomarkers could fill in the gap of easily accessible and low-cost methods for early diagnosis of the disease. In particular, immune-based blood-biomarkers might be a promising option, given the recently discovered cross-talk of immune cells of the central nervous system with those in the peripheral immune system. Here, we give a background on recent advances in research on brain-immune system cross-talk in Alzheimer's disease and review machine learning approaches, which can combine multiple biomarkers with further information (e.g. age, sex, APOE genotype) into predictive models supporting an earlier diagnosis. In addition, mechanistic modeling approaches, such as agent-based modeling open the possibility to model and analyze cell dynamics over time. This review aims to provide an overview of the current state of immune-system related blood-based biomarkers and their potential for the early diagnosis of Alzheimer's disease.

Beyond the amyloid hypothesis: how current research implicates autoimmunity in Alzheimer's disease pathogenesis

The amyloid hypothesis has so far been at the forefront of explaining the pathogenesis of Alzheimer's Disease (AD), a progressive neurodegenerative disorder that leads to cognitive decline and eventual death. Recent evidence, however, points to additional factors that contribute to the pathogenesis of this disease. These include the neurovascular hypothesis, the mitochondrial cascade hypothesis, the inflammatory hypothesis, the prion hypothesis, the mutational accumulation hypothesis, and the autoimmunity hypothesis. The purpose of this review was to briefly discuss the factors that are associated with autoimmunity in humans, including sex, the gut and lung microbiomes, age, genetics, and environmental factors. Subsequently, it was to examine the rise of autoimmune phenomena in AD, which can be instigated by a blood-brain barrier breakdown, pathogen infections, and dysfunction of the glymphatic system. Lastly, it was to discuss the various ways by which immune system dysregulation leads to AD, immunomodulating therapies, and future directions in the field of autoimmunity and neurodegeneration. A comprehensive account of the recent research done in the field was extracted from PubMed on 31 January 2022, with the keywords "Alzheimer's disease" and "autoantibodies" for the first search input, and "Alzheimer's disease" with "IgG" for the second. From the first search, 19 papers were selected, because they contained recent research on the autoantibodies found in the biofluids of patients with AD. From the second search, four papers were selected. The analysis of the literature has led to support the autoimmune hypothesis in AD. Autoantibodies were found in biofluids (serum/plasma, cerebrospinal fluid) of patients with AD with multiple methods, including ELISA, Mass Spectrometry, and microarray analysis. Through continuous research, the understanding of the synergistic effects of the various components that lead to AD will pave the way for better therapeutic methods and a deeper understanding of the disease.

Decrease in naturally occurring antibodies against epitopes of Alzheimer's disease (AD) risk gene products is associated with cognitive decline in AD

BACKGROUND

Naturally occurring antibodies (NAbs) are germline-encoded immunoglobulins that can bind to and clear out self-neo-epitopes as well as apoptotic and necrotic cells. However, NAbs pathological relevance in Alzheimer's disease (AD) is not well-understood.

METHODS

Twenty-eight candidate proteins encoded by AD-associated genes were selected for this study based on a number of selection criteria, including preferential expression in the brain and B-lymphocyte cells. The levels of NAbs in plasma were analyzed according to their epitopes in age- and gender-matched cognitively normal subjects (CN, n = 56), subjects with mild cognitive impairment (MCI, n = 16) and subjects with AD (n = 56). We aimed to study the levels of their NAbs in plasma and their associations with cognitive decline in individuals with AD.

RESULTS

Of the 28 antigens tested, 17 showed decreased NAbs in individuals with AD; in particular, NAb-TREM2 had an area under the ROC curve of 0.806, with the highest sensitivity (0.370) at 95% specificity among all 28 tests. Further protein-protein interaction networks and functional enrichment analysis suggested that target genes were enriched in AD-related pathological processes classified under "Alzheimer's disease", "neurodegenerative disease" and "amyloidosis". The "Alzheimer's disease" and "neurodegenerative disease" clusters, which converged on the initial "recognition" step of microglial phagocytosis, showed the best diagnostic performance for AD.

CONCLUSIONS

This study suggests a decline in the function of the adaptive immune system in AD, and the levels of circulating NAbs are likely to serve as biomarkers for surveilling the progression of AD.

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.

Identification of Digital Health Priorities for Palliative Care Research: Modified Delphi Study

BACKGROUND

Developments in digital health have the potential to transform the delivery of health and social care to help citizens manage their health. Currently, there is a lack of consensus about digital health research priorities in palliative care and a lack of theories about how these technologies might improve care outcomes. Therefore, it is important for health care leaders to identify innovations to ensure that an increasingly frail population has appropriate access to palliative care services. Consequently, it is important to articulate research priorities as the first step in determining how finite resources should be allocated to a field saturated with rapidly developing innovation.

OBJECTIVE

The aim of this study is to identify research priority areas for digital health in palliative care.

METHODS

We selected digital health trends, most relevant to palliative care, from a list of emerging trends reported by a leading institute of quantitative futurists. We conducted 2 rounds of the Delphi questionnaire, followed by a consensus meeting and public engagement workshop to establish a final consensus on research priorities for digital technology in palliative care. We used the views of public representatives to gain their perspectives on the agreed priorities.

RESULTS

A total of 103 experts (representing 11 countries) participated in the first Delphi round. Of the 103 experts, 55 (53.3%) participated in the second round. The final consensus meetings were attended by 10.7% (11/103) of the experts. We identified 16 priority areas, which involved many applications of technologies, including care for patients and caregivers, self-management and reporting of diseases, education and training, communication, care coordination, and research methodology. We summarized the priority areas into eight topics: big data, mobile devices, telehealth and telemedicine, virtual reality, artificial intelligence, smart home, biotechnology, and digital legacy.

CONCLUSIONS

The priorities identified in this study represent a wide range of important emerging areas in the fields of digital health, personalized medicine, and data science. Human-centered design and robust governance systems should be considered in future research. It is important that the risks of using these technologies in palliative care are properly addressed to ensure that these tools are used meaningfully, wisely, and safely and do not cause unintentional harm.

Challenges and hopes for Alzheimer's disease

Recent drug development efforts targeting Alzheimer's disease (AD) have failed to produce effective disease-modifying agents for many reasons, including the substantial presymptomatic neuronal damage that is caused by the accumulation of the amyloid β (Aβ) peptide and tau protein abnormalities, deleterious adverse effects of drug candidates, and inadequate design of clinical trials. New molecular targets, biomarkers, and diagnostic techniques, as well as alternative nonpharmacological approaches, are sorely needed to detect and treat early pathological events. This article analyzes the successes and debacles of pharmaceutical endeavors to date, and highlights new technologies that may lead to the more effective diagnosis and treatment of the pathologies that underlie AD. The use of focused ultrasound, deep brain stimulation, stem cell therapy, and gene therapy, in parallel with pharmaceuticals and judicious lifestyle adjustments, holds promise for the deceleration, prevention, or cure of AD and other neurodegenerative disorders.

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.

Gain-Scanning for Protein Microarray Assays

Protein microarrays consist of known proteins spotted onto solid substrates and are used to perform highly multivariate assessments of protein-binding interactions. Human protein arrays are routinely applied to pathogen detection, immune response biomarker profiling, and antibody specificity profiling. Here, we describe and demonstrate a new data processing procedure, gain-scan, in which data were acquired under multiple photomultiplier tube (PMT) settings, followed by data fitting with a power function model to estimate the incident light signals of the array spots. Data acquisition under multiple PMT settings solves the difficulty of determining the single optimal PMT gain setting and allows us to maximize the detection of low-intensity signals while avoiding the saturation of high-intensity ones at the same time. The gain-scan data acquisition and fitting also significantly lower the variances over the detectable range of signals and improve the linear data normalization. The performance of the proposed procedure was verified by analyzing the profiling data of both the human polyclonal serum samples and the monoclonal antibody samples with both technical replicates and biological replicates. We showed that the multigain power function was an appropriate model for describing data acquired under multiple PMT settings. The gain-scan fitting alone or in combination with the linear normalization could effectively reduce the technical variability of the array data and lead to better sample separability and more sensitive differential analysis.

Neurovascular and immune mechanisms that regulate postoperative delirium superimposed on dementia

Objective

The present work evaluates the relationship between postoperative immune and neurovascular changes and the pathogenesis of surgery‐induced delirium superimposed on dementia.

Background and rationale

Postoperative delirium is a common complication in many older adults and in patients with dementia including Alzheimer's disease (AD). The course of delirium can be particularly debilitating, while its pathophysiology remains poorly defined.

Historical evolution

As of 2019, an estimated 5.8 million people of all ages have been diagnosed with AD, 97% of whom are >65 years of age. Each year, many of these patients require surgery. However, anesthesia and surgery can increase the risk for further cognitive decline. Surgery triggers neuroinflammation both in animal models and in humans, and a failure to resolve this inflammatory state may contribute to perioperative neurocognitive disorders as well as neurodegenerative pathology.

Updated hypothesis

We propose an immunovascular hypothesis whereby dysregulated innate immunity negatively affects the blood‐brain interface, which triggers delirium and thereby exacerbates AD neuropathology.

Early experimental data

We have developed a translational model to study delirium superimposed on dementia in APPSwDI/mNos2^−/− AD mice (CVN‐AD) after orthopedic surgery. At 12 months of age, CVN‐AD showed distinct neuroimmune and vascular impairments after surgery, including acute microgliosis and amyloid‐β deposition. These changes correlated with attention deficits, a core feature of delirium‐like behavior.

Future experiments and validation studies

Future research should determine the extent to which prevention of surgery‐induced microgliosis and/or neurovascular unit dysfunction can prevent or ameliorate postoperative memory and attention deficits in animal models. Translational human studies should evaluate perioperative indices of innate immunity and neurovascular integrity and assess their potential link to perioperative neurocognitive disorders.

Major challenges for the hypothesis

Understanding the complex relationships between delirium and dementia will require mechanistic studies aimed at evaluating the role of postoperative neuroinflammation and blood‐brain barrier changes in the setting of pre‐existing neurodegenerative and/or aging‐related pathology.

Linkage to other major theories

Non‐resolving inflammation with vascular disease that leads to cognitive impairments and dementia is increasingly important in risk stratification for AD in the aging population. The interdependence of these factors with surgery‐induced neuroinflammation and cognitive dysfunction is also becoming apparent, providing a strong platform for assessing the relationship between postoperative delirium and longer term cognitive dysfunction in older adults.