Blood biomarkers in Alzheimer's disease

Systematic review of amyloid-beta clearance proteins from the brain to the periphery: implications for Alzheimer's disease diagnosis and therapeutic targets

Amyloid-beta clearance plays a key role in the pathogenesis of Alzheimer's disease. However, the variation in functional proteins involved in amyloid-beta clearance and their correlation with amyloid-beta levels remain unclear. In this study, we conducted meta-analyses and a systematic review using studies from the PubMed, Embase, Web of Science, and Cochrane Library databases, including journal articles published from inception to June 30, 2023. The inclusion criteria included studies comparing the levels of functional proteins associated with amyloid-beta clearance in the blood, cerebrospinal fluid, and brain of healthy controls, patients with mild cognitive impairment, and patients with Alzheimer's disease. Additionally, we analyzed the correlation between these functional proteins and amyloid-beta levels in patients with Alzheimer's disease. The methodological quality of the studies was assessed via the Newcastle‒Ottawa Scale. Owing to heterogeneity, we utilized either a fixed-effect or random-effect model to assess the 95% confidence interval (CI) of the standard mean difference (SMD) among healthy controls, patients with mild cognitive impairment, and patients with Alzheimer's disease. The findings revealed significant alterations in the levels of insulin-degrading enzymes, neprilysin, matrix metalloproteinase-9, cathepsin D, receptor for advanced glycation end products, and P-glycoprotein in the brains of patients with Alzheimer's disease, patients with mild cognitive impairment, and healthy controls. In cerebrospinal fluid, the levels of triggering receptor expressed on myeloid cells 2 and ubiquitin C-terminal hydrolase L1 are altered, whereas the levels of TREM2, CD40, CD40L, CD14, CD22, cathepsin D, cystatin C, and α2 M in peripheral blood differ. Notably, TREM2 and cathepsin D showed changes in both brain (SMD = 0.31, 95% CI: 0.16-0.47, P < 0.001, I2 = 78.4%; SMD = 1.24, 95% CI: 0.01-2.48, P = 0.048, I2 = 90.1%) and peripheral blood (SMD = 1.01, 95% CI: 0.35-1.66, P = 0.003, I2 = 96.5%; SMD = 7.55, 95% CI: 3.92-11.18, P < 0.001, I2 = 98.2%) samples. Furthermore, correlations were observed between amyloid-beta levels and the levels of TREM2 ( r = 0.16, 95% CI: 0.04-0.28, P = 0.009, I2 = 74.7%), neprilysin ( r = -0.47, 95% CI: -0.80-0.14, P = 0.005, I2 = 76.1%), and P-glycoprotein ( r = -0.31, 95% CI: -0.51-0.11, P = 0.002, I2 = 0.0%) in patients with Alzheimer's disease. These findings suggest that triggering receptor expressed on myeloid cells 2 and cathepsin D could serve as potential diagnostic biomarkers for Alzheimer's disease, whereas triggering receptor expressed on myeloid cells 2, neprilysin, and P-glycoprotein may represent potential therapeutic targets.

Identification of blood plasma protein ratios for distinguishing Alzheimer's disease from healthy controls using machine learning

Early detection of Alzheimer's disease is essential for effective treatment and the development of therapies that modify disease progression. Developing sensitive and specific noninvasive diagnostic tools is crucial for improving clinical outcomes and advancing our understanding of this condition. Liquid biopsy techniques, especially those involving plasma biomarkers, provide a promising noninvasive method for early diagnosis and disease monitoring. In this study, we analyzed the plasma proteomic profiles of 38 healthy individuals, with an average age of 66.5 years, and 22 patients with Alzheimer's disease, with an average age of 79.7 years. Proteins in the plasma were quantified using specialized panels designed for proteomic extension assays. Through computational analysis using a linear support vector machine algorithm, we identified 82 differentially expressed proteins between the two groups. From these, we calculated 6642 possible protein ratios and identified specific combinations of these ratios as significant features for distinguishing between individuals with Alzheimer's disease and healthy individuals. Notably, the protein ratios kynureninase to macrophage scavenger receptor type 1, Neurocan to protogenin, and interleukin-5 receptor alpha to glial cell line-derived neurotrophic factor receptor alpha 1 achieving accuracy up to 98 % in differentiating between the two groups. This study underscores the potential of leveraging protein relationships, expressed as ratios, in advancing Alzheimer's disease diagnostics. Furthermore, our findings highlight the promise of liquid biopsy techniques as a noninvasive and accurate approach for early detection and monitoring of Alzheimer's disease using blood plasma.

Understanding the Molecular Impact of Physical Exercise on Alzheimer's Disease

Alzheimer's disease is one of the most common neurodegenerative diseases, characterized by a wide range of neurological symptoms that begin with personality changes and psychiatric symptoms, progress to mild cognitive impairment, and eventually lead to dementia. Physical exercise is part of the non-pharmacological treatments used in Alzheimer's disease, as it has been shown to delay the neurodegenerative process by improving the redox state in brain tissue, providing anti-inflammatory effects or stimulating the release of the brain-derived neurotrophic factor that enhances the brain structure and cognitive performance. Here, we reviewed the results obtained from studies conducted in both animal models and human subjects to comprehend how physical exercise interventions can exert changes in the molecular mechanisms underlying the pathophysiological processes in Alzheimer's disease: amyloid β-peptide pathology, tau pathology, neuroglial changes, mitochondrial dysfunction, and oxidative stress. Physical exercise seems to have a protective effect against Alzheimer's disease, since it has been shown to induce positive changes in some of the biomarkers related to the pathophysiological processes of the disease. However, additional studies in humans are necessary to address the current lack of conclusive evidence.

Advancing personalized medicine: Integrating statistical algorithms with omics and nano-omics for enhanced diagnostic accuracy and treatment efficacy

Medical laboratory services enable precise measurement of thousands of biomolecules and have become an inseparable part of high-quality healthcare services, exerting a profound influence on global health outcomes. The integration of omics technologies into laboratory medicine has transformed healthcare, enabling personalized treatments and interventions based on individuals' distinct genetic and metabolic profiles. Interpreting laboratory data relies on reliable reference values. Presently, population-derived references are used for individuals, risking misinterpretation due to population heterogeneity, and leading to medical errors. Thus, personalized references are crucial for precise interpretation of individual laboratory results, and the interpretation of omics data should be based on individualized reference values. We reviewed recent advancements in personalized laboratory medicine, focusing on personalized omics, and discussed strategies for implementing personalized statistical approaches in omics technologies to improve global health and concluded that personalized statistical algorithms for interpretation of omics data have great potential to enhance global health. Finally, we demonstrated that the convergence of nanotechnology and omics sciences is transforming personalized laboratory medicine by providing unparalleled diagnostic precision and innovative therapeutic strategies.

A Two-Year Observational Study to Evaluate Conversion Rates from High- and Low-Risk Patients with Amnestic Mild Cognitive Impairment to Probable Alzheimer's Disease in a Real-World Setting

Background

Predicting conversion to probable Alzheimer&s disease (AD) from amnestic mild cognitive impairment (aMCI) is difficult but important. A nomogram was developed previously for determining the risk of 3-year probable AD conversion in aMCI.

Objective

To compare the probable AD conversion rates with cognitive and neurodegenerative changes for 2 years from high- and low risk aMCI groups classified using the nomogram.

Methods

This prospective, multicenter, observational study was conducted in Korea. A total of patients were classified as high- or low-risk aMCI according to the nomogram and followed-up for 2 years to compare the annual conversion rate to probable AD and brain structure changes between the two groups.

Results

In total, 176 (high-risk, 85; low-risk, 91) and 160 (high-risk, 77; low-risk, 83) patients completed the 1-year and 2-year follow-up, respectively. The probable AD conversion rate was significantly higher in the high-risk (Year 1, 28.9%; Year 2, 46.1%) versus low-risk group (Year 1, 0.0%; Year 2, 4.9%, both p < 0.0001). Mean changes from baseline in Seoul Neuropsychological Screening Battery-Dementia Version, Clinical Dementia Rating-Sum of Box, and Korean version of the Instrumental Activities of Daily Living scores and cortical atrophy index at Years 1 and 2 were significantly greater in the high-risk group (p < 0.0001).

Conclusions

The high-risk aMCI group, as determined by the nomogram, had a higher conversion rate to probable AD and faster cognitive decline and neurodegeneration change than the low-risk group. These real-world results have clinical implications that help clinicians in accurately predicting patient outcomes and facilitating early decision-making.Trial Registration: ClinicalTrials.gov (NCT03448445).

SIRT1 and miR-34a-5p Expression in PBMCs as Potential Biomarkers for Patients With Type 2 Diabetes With Cognitive Impairments

CONTEXT

Patients with type 2 diabetes mellitus (T2DM) are at significantly increased risk of Alzheimer disease (AD). However, no biomarkers are available for early identification of patients with T2DM with cognitive impairment (T2DM-CI). Mitochondrial dysfunction is linked to AD. Silent Information Regulator 1 (SIRT1), which is responsible for regulating mitochondrial biogenesis, and its related miRNAs were also altered in AD.

OBJECTIVE

This study aimed to determine whether mitochondrial function in peripheral blood mononuclear cells (PBMCs) of patients with T2DM-CI was altered and if these alterations could be used as biomarkers.

METHODS

A total of 374 subjects were enrolled, including AD, T2DM-CI, T2DM-nCI (T2DM without cognitive impairment), and healthy controls. The mitochondrial function was determined using a commercial assay kit. The mitochondrial DNA (mtDNA) content, the expression of SIRT1, and selected miRNAs in PBMCs were measured by quantitative polymerase chain reaction. The correlations and diagnostic accuracy were assessed using the Spearman correlation coefficient or receiver operating characteristics analysis, respectively.

RESULTS

We found significant changes in mitochondrial function in PBMCs of patients with AD compared with controls (all P < .05), which were not found in T2DM-CI. However, mtDNA content and SIRT1 mRNA expression were lower in PBMCs of patients with T2DM-CI, while miR-34a-5p expression was higher than in patients with T2DM-nCI (all P < .05). A combination of SIRT1 and miR-34a-5p demonstrated excellent discrimination between T2DM-CI and T2DM-nCI (area under the curve = 0.793; sensitivity: 80.01%; specificity: 78.46%). Furthermore, correlation analysis revealed a link between miR-34a-5p expression and hyperglycemia in T2DM-CI.

CONCLUSION

Our findings revealed that there was an alteration of mitochondria at the peripheral level in patients with T2DM-CI. SIRT1 combined with miR-34a-5p in PBMCs performed well in identifying patients with T2DM-CI and may be a promising biomarker.

Evaluation of serum neurofilament light chain and glial fibrillary acidic protein in the diagnosis of Alzheimer's disease

Purpose

This study aimed to evaluate the use of serum neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in the diagnosis of Alzheimer's disease (AD) and the differential diagnosis between AD and mild cognitive impairment (MCI).

Methods

From September 2021 to October 2022, we collected venous blood from patients and healthy individuals who visited our hospital's Neurology Department, and we isolated serum to detect NfL and GFAP using direct chemiluminescence. The results were analyzed using one-way analysis of variance (ANOVA) analysis and receiver operating characteristic (ROC) curves.

Results

Pairwise comparisons among the three groups showed that compared with the health checkup (HC) group, serum NfL and GFAP were increased in both AD and MCI (PNfL < 0.05, PGFAP < 0.01). There were significant differences in GFAP between MCI and AD groups, and the level in AD group was higher (p < 0.01), while there was no difference in NfL. Both serum NfL and serum GFAP levels can independently diagnose AD (p < 0.01). The ROC curve showed that GFAP had a higher diagnostic efficacy, with an area under the ROC curve (AUC) of 0.928. The cut-off values of the two serum markers for the diagnosis of AD were NfL > 40.09 pg./mL and GFAP >31.40 pg./mL. Sensitivity and specificity for NfL in the diagnosis of AD were 59.6 and 76.2%, respectively, and for GFAP, they were 90.4 and 82.1%, respectively. The combined diagnosis of GFAP and NfL improved the diagnostic efficiency (AUC = 0.931, sensitivity = 78.8%, specificity = 92.3%). The cut-off value of GFAP for the differential diagnosis of MCI and AD was 46.05 pg./mL.

Conclusion

Both serum NfL and serum GFAP can be used as biomarkers for the diagnosis of AD. Serum GFAP has better diagnostic efficacy and can distinguish AD from MCI. A combined diagnosis can improve diagnostic specificity.

The Major Hypotheses of Alzheimer's Disease: Related Nanotechnology-Based Approaches for Its Diagnosis and Treatment

Alzheimer's disease (AD) is a well-known chronic neurodegenerative disorder that leads to the progressive death of brain cells, resulting in memory loss and the loss of other critical body functions. In March 2019, one of the major pharmaceutical companies and its partners announced that currently, there is no drug to cure AD, and all clinical trials of the new ones have been cancelled, leaving many people without hope. However, despite the clear message and startling reality, the research continued. Finally, in the last two years, the Food and Drug Administration (FDA) approved the first-ever medications to treat Alzheimer's, aducanumab and lecanemab. Despite researchers' support of this decision, there are serious concerns about their effectiveness and safety. The validation of aducanumab by the Centers for Medicare and Medicaid Services is still pending, and lecanemab was authorized without considering data from the phase III trials. Furthermore, numerous reports suggest that patients have died when undergoing extended treatment. While there is evidence that aducanumab and lecanemab may provide some relief to those suffering from AD, their impact remains a topic of ongoing research and debate within the medical community. The fact is that even though there are considerable efforts regarding pharmacological treatment, no definitive cure for AD has been found yet. Nevertheless, it is strongly believed that modern nanotechnology holds promising solutions and effective clinical strategies for the development of diagnostic tools and treatments for AD. This review summarizes the major hallmarks of AD, its etiological mechanisms, and challenges. It explores existing diagnostic and therapeutic methods and the potential of nanotechnology-based approaches for recognizing and monitoring patients at risk of irreversible neuronal degeneration. Overall, it provides a broad overview for those interested in the evolving areas of clinical neuroscience, AD, and related nanotechnology. With further research and development, nanotechnology-based approaches may offer new solutions and hope for millions of people affected by this devastating disease.

Biomarkers and Risk Assessment of Alzheimer's Disease in Low- and Middle-Income Countries

Dementia is a chronic syndrome which is common among the elderly and is associated with significant morbidity and mortality for patients and their caregivers. Alzheimer's disease (AD), the most common form of clinical dementia, is biologically characterized by the deposition of amyloid-β plaques and neurofibrillary tangles in the brain. The onset of AD begins decades before manifestation of symptoms and clinical diagnosis, underlining the need to shift from clinical diagnosis of AD to a more objective diagnosis using biomarkers. Having performed a literature search of original articles and reviews on PubMed and Google Scholar, we present this review detailing the existing biomarkers and risk assessment tools for AD. The prevalence of dementia in low- and middle-income countries (LMICs) is predicted to increase over the next couple of years. Thus, we aimed to identify potential biomarkers that may be appropriate for use in LMICs, considering the following factors: sensitivity, specificity, invasiveness, and affordability of the biomarkers. We also explored risk assessment tools and the potential use of artificial intelligence/machine learning solutions for diagnosing, assessing risks, and monitoring the progression of AD in low-resource settings. Routine use of AD biomarkers has yet to gain sufficient ground in clinical settings. Therefore, clinical diagnosis of AD will remain the mainstay in LMICs for the foreseeable future. Efforts should be made towards the development of low-cost, easily administered risk assessment tools to identify individuals who are at risk of AD in the population. We recommend that stakeholders invest in education, research and development targeted towards effective risk assessment and management.

Non-Invasive Nasal Discharge Fluid and Other Body Fluid Biomarkers in Alzheimer’s Disease

The key to current Alzheimer’s disease (AD) therapy is the early diagnosis for prompt intervention, since available treatments only slow the disease progression. Therefore, this lack of promising therapies has called for diagnostic screening tests to identify those likely to develop full-blown AD. Recent AD diagnosis guidelines incorporated core biomarker analyses into criteria, including amyloid-β (Aβ), total-tau (T-tau), and phosphorylated tau (P-tau). Though effective, the accessibility of screening tests involving conventional cerebrospinal fluid (CSF)- and blood-based analyses is often hindered by the invasiveness and high cost. In an attempt to overcome these shortcomings, biomarker profiling research using non-invasive body fluid has shown the potential to capture the pathological changes in the patients’ bodies. These novel non-invasive body fluid biomarkers for AD have emerged as diagnostic and pathological targets. Here, we review the potential peripheral biomarkers, including non-invasive peripheral body fluids of nasal discharge, tear, saliva, and urine for AD.

Blood levels of circulating methionine components in Alzheimer’s disease and mild cognitive impairment: A systematic review and meta-analysis

Background

Circulating methionine components have been reported to be associated with Alzheimer’s disease (AD) and mild cognitive impairment (MCI), although outcomes are not always consistent.

Materials and methods

Database searching was conducted using PubMed, Embase, Cochrane Library, and Web of Science from inception to 26 December 2021. In this study, two reviewers independently identified eligible articles and extracted the data. We used Joanna Briggs Institute (JBI) Critical Appraisal tools to assess the overall quality of the included studies. STATA software was employed to perform meta-analysis evaluating the standardized mean difference (SMD) with its 95% confidence intervals (CIs) using random-effects models. Evidence quality was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria.

Results

Totally, 30 observational studies were eligible for inclusion. Compared with cognitively normal controls, patients with AD had increased homocysteine (Hcy) levels in the blood [standardized mean difference (SMD) = 0.59, 95% confidence interval [CI]: 0.36–0.82, P = 0.000], plasma (SMD = 0.39, 95% CI: 0.23–0.55, P = 0.000), and serum (SMD = 1.56, 95% CI: 0.59–2.95, P = 0.002). Patients with MCI were not significantly different from controls (SMD = 0.26, 95% CI: –0.07–0.58, P = 0.127). Patients with AD or MCI did not significantly differ from controls of blood vitamin B12 levels, AD (SMD = –0.05, 95% CI: –0.19–0.08, P = 0.440), or MCI (SMD = 0.01, 95% CI: –0.16–0.17, P = 0.94). Some cohort studies have suggested that higher Hcy, methionine, and S-adenosylmethionine levels may accelerate cognitive decline in patients with MCI or AD, and vitamin B12 deficiency is a risk factor for the disease; however, the results of other studies were inconsistent. According to the GRADE system, all these outcomes scored very low to low quality, and no high-quality evidence was found.

Conclusion

Only Hcy levels in the plasma and serum were found to be inversely related to the risk of AD. However, due to the low quality of supporting these results, high-quality studies are needed to verify these findings.

Systematic Review Registration

http://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022308961.

Biomarkers of Neurodegenerative Diseases: Biology, Taxonomy, Clinical Relevance, and Current Research Status

The understanding of neurodegenerative diseases, traditionally considered to be well-defined entities with distinguishable clinical phenotypes, has undergone a major shift over the last 20 years. The diagnosis of neurodegenerative diseases primarily requires functional brain imaging techniques or invasive tests such as lumbar puncture to assess cerebrospinal fluid. A new biological approach and research efforts, especially in vivo, have focused on biomarkers indicating underlying proteinopathy in cerebrospinal fluid and blood serum. However, due to the complexity and heterogeneity of neurodegenerative processes within the central nervous system and the large number of overlapping clinical diagnoses, identifying individual proteinopathies is relatively difficult and often not entirely accurate. For this reason, there is an urgent need to develop laboratory methods for identifying specific biomarkers, understand the molecular basis of neurodegenerative disorders and classify the quantifiable and readily available tools that can accelerate efforts to translate the knowledge into disease-modifying therapies that can improve and simplify the areas of differential diagnosis, as well as monitor the disease course with the aim of estimating the prognosis or evaluating the effects of treatment. The aim of this review is to summarize the current knowledge about clinically relevant biomarkers in different neurodegenerative diseases.

BIOFACE: A Prospective Study of Risk Factors, Cognition, and Biomarkers in a Cohort of Individuals with Early-Onset Mild Cognitive Impairment. Study Rationale and Research Protocols

Background:

Mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) diagnosis is based on cerebrospinal fluid (CSF) or neuroimaging biomarkers. Currently, non-invasive and inexpensive blood-based biomarkers are being investigated, such as neuronal-derived plasma exosomes (NPEs). Neuroinflammation and early vascular changes have been described in AD pathogenesis and can be traced in plasma and NPEs. However, they have not been studied in early onset MCI (EOMCI).

Objective:

To describe the rationale, design, and baseline characteristics of the participants from the BIOFACE cohort, a two-year observational study on EOMCI conducted at Fundació ACE. The study goal is to characterize the different phenotypes from a clinical, neuropsychological, and biomarker point of view and to investigate the CSF and plasma proteomics as well as the role of NPEs as early biomarkers of AD.

Methods:

Participants underwent extended neurological and neuropsychological batteries, multimodal biomarkers including brain MRI, blood, saliva, CSF, anthropometric, and neuro-ophthalmological examinations.

Results:

Ninety-seven patients with EOMCI were recruited. 59.8%were women. Mean age at symptom onset was 57 years; mean MMSE was 28. First degree and presenile family history of dementia was present in 60.8%and 15.5%, respectively. Depressive and anxiety disorders along with vascular risk factors were the most frequent comorbidities. 29%of participants were APOE ɛ4 carriers, and 67%showed a CSF normal ATN profile.

Conclusion:

BIOFACE is a two-year study of clinical, cognition, and biomarkers that will shed light on the physiopathology and the potential utility of plasma and NPEs as non-invasive early diagnostic and prognostic biomarkers in people younger than 65 years.

Serum BDNF as a Potential Biomarker of Alzheimer's Disease: Verification Through Assessment of Serum, Cerebrospinal Fluid, and Medial Temporal Lobe Atrophy

There is an urgent need to establish blood biomarkers for Alzheimer's disease (AD). Although it has been speculated that brain-derived neurotrophic factor (BDNF) is associated with AD, whether it can be used as a blood biomarker has yet to be determined. We used serum, cerebrospinal fluid (CSF), and medial temporal lobe atrophy from patients with AD to evaluate the association of BDNF with AD and assess its severity. For the blood analysis, 66 participants [21 normal controls (NCs) with normal cognitive function, 22 patients with mild cognitive impairment (MCI) due to AD, and 23 patients with AD] were included. For the CSF analysis, 30 participants were included. Magnetic resonance imaging, including a voxel-based specific regional analysis system for AD, and a Mini Mental State Examination were performed. Serum levels of BDNF and CSF levels of amyloid-β42, total tau, and phosphorylated tau were measured using ELISA. Serum BDNF levels were significantly lower in the MCI due to AD group than in the NC group (p = 0.037). Although there was no significant difference in the AD group, there was a downward trend compared to the NC group. Serum BDNF levels were positively correlated with CSF Aβ42 levels (r = 0.49, p = 0.005). There was a significant correlation between serum BDNF levels and medial temporal lobe atrophy. Decreased serum BDNF can potentially be used as a biomarker for early AD detection. Early detection of AD with a less invasive blood test is very beneficial, as it allows for intervention before dementia progresses.