Diagnosis of Alzheimer's Disease in Developed and Developing Countries: Systematic Review and Meta-Analysis of Diagnostic Test Accuracy

Tracking neuroinflammatory biomarkers in Alzheimer's disease: a strategy for individualized therapeutic approaches?

BACKGROUND

Recent trials of anti-amyloid-β (Aβ) monoclonal antibodies, including lecanemab and donanemab, in early Alzheimer disease (AD) showed that these drugs have limited clinical benefits and their use comes with a significant risk of serious adverse events. Thus, it seems crucial to explore complementary therapeutic approaches. Genome-wide association studies identified robust associations between AD and several AD risk genes related to immune response, including but not restricted to CD33 and TREM2. Here, we critically reviewed the current knowledge on candidate neuroinflammatory biomarkers and their role in characterizing the pathophysiology of AD.

MAIN BODY

Neuroinflammation is recognized to be a crucial and contributing component of AD pathogenesis. The fact that neuroinflammation is most likely present from earliest pre-stages of AD and co-occurs with the deposition of Aβ reinforces the need to precisely define the sequence and nature of neuroinflammatory events. Numerous clinical trials involving anti-inflammatory drugs previously yielded unfavorable outcomes in early and mild-to-moderate AD. Although the reasons behind these failures remain unclear, these may include the time and the target selected for intervention. Indeed, in our review, we observed a stage-dependent neuroinflammatory process in the AD brain. While the initial activation of glial cells counteracts early brain Aβ deposition, the downregulation in the functional state of microglia occurs at more advanced disease stages. To address this issue, personalized neuroinflammatory modulation therapy is required. The emergence of reliable blood-based neuroinflammatory biomarkers, particularly glial fibrillary acidic protein, a marker of reactive astrocytes, may facilitate the classification of AD patients based on the ATI(N) biomarker framework. This expands upon the traditional classification of Aβ ("A"), tau ("T"), and neurodegeneration ("N"), by incorporating a novel inflammatory component ("I").

CONCLUSIONS

The present review outlines the current knowledge on potential neuroinflammatory biomarkers and, importantly, emphasizes the role of longitudinal analyses, which are needed to accurately monitor the dynamics of cerebral inflammation. Such a precise information on time and place will be required before anti-inflammatory therapeutic interventions can be considered for clinical evaluation. We propose that an effective anti-neuroinflammatory therapy should specifically target microglia and astrocytes, while considering the individual ATI(N) status of patients.

Toolkit to Examine Lifelike Language (TELL): An app to capture speech and language markers of neurodegeneration

Automated speech and language analysis (ASLA) is a promising approach for capturing early markers of neurodegenerative diseases. However, its potential remains underexploited in research and translational settings, partly due to the lack of a unified tool for data collection, encryption, processing, download, and visualization. Here we introduce the Toolkit to Examine Lifelike Language (TELL) v.1.0.0, a web-based app designed to bridge such a gap. First, we outline general aspects of its development. Second, we list the steps to access and use the app. Third, we specify its data collection protocol, including a linguistic profile survey and 11 audio recording tasks. Fourth, we describe the outputs the app generates for researchers (downloadable files) and for clinicians (real-time metrics). Fifth, we survey published findings obtained through its tasks and metrics. Sixth, we refer to TELL's current limitations and prospects for expansion. Overall, with its current and planned features, TELL aims to facilitate ASLA for research and clinical aims in the neurodegeneration arena. A demo version can be accessed here:  https://demo.sci.tellapp.org/ .

Circulating Biomarkers for Alzheimer's Disease: Unlocking the Diagnostic Potential in Low- and Middle-Income Countries, Focusing on Africa

BACKGROUND

Alzheimer's disease (AD) is emerging as a significant public health challenge in Africa, with predictions indicating a tripling in incidence by 2050. The diagnosis of AD on the African continent is notably difficult, leading to late detection that severely limits treatment options and significantly impacts the quality of life for patients and their families.

SUMMARY

This review focuses on the potential of high-sensitivity specific blood biomarkers as promising tools for improving AD diagnosis and management globally, particularly in Africa. These advances are particularly pertinent in the continent, where access to medical and technical resources is often limited.

KEY MESSAGES

Identifying precise, sensitive, and specific blood biomarkers could contribute to the biological characterization and management of AD in Africa. Such advances promise to improve patient care and pave the way for new regional opportunities in pharmaceutical research and drug trials on the continent for AD.

Increasing the sensitivity of Simoa via bead count reduction facilitates the quantification of pTau-181 in dried plasma spots

Introduction

The exclusion of affected populations from Alzheimer's disease (AD) clinical research limits our understanding of disease heterogeneity and its impact on clinical care. While micro sampling with dried plasma spots (DPS) can promote inclusivity by enabling sample collection in remote areas, current techniques lack the sensitivity required for the quantification of phosphorylated tau at Thr181 (pTau-181) in DPS extracts.

Methods

We developed an assay for pTau-181 with reduced bead count and improved bead read efficiency (BRE) using a prototype Simoa instrument. This novel assay's performance was evaluated against standard pTau-181 assays on two Simoa platforms, and DPS extracts were tested for pTau-181 quantification feasibility.

Results

The novel assay quantifies pTau-181 at concentrations up to 16x lower than traditional pTau-181 assays on HD-X and SR-X platforms. DPS extracts tested with our low-bead assay were quantified considerably above the lower limit of quantification (LLOQ), indicating the suitability of this assay for future DPS extract measurements.

Discussion

Implementing DPS sampling and pTau-181 quantification could increase participation from underrepresented groups in AD research. However, additional assay optimization and an in-depth study of preanalytical sample stability are essential for the transition to clinical applicability.

Speech and language markers of neurodegeneration: a call for global equity

In the field of neurodegeneration, speech and language assessments are useful for diagnosing aphasic syndromes and for characterizing other disorders. As a complement to classic tests, scalable and low-cost digital tools can capture relevant anomalies automatically, potentially supporting the quest for globally equitable markers of brain health. However, this promise remains unfulfilled due to limited linguistic diversity in scientific works and clinical instruments. Here we argue for cross-linguistic research as a core strategy to counter this problem. First, we survey the contributions of linguistic assessments in the study of primary progressive aphasia and the three most prevalent neurodegenerative disorders worldwide-Alzheimer's disease, Parkinson's disease, and behavioural variant frontotemporal dementia. Second, we address two forms of linguistic unfairness in the literature: the neglect of most of the world's 7000 languages and the preponderance of English-speaking cohorts. Third, we review studies showing that linguistic dysfunctions in a given disorder may vary depending on the patient's language and that English speakers offer a suboptimal benchmark for other language groups. Finally, we highlight different approaches, tools and initiatives for cross-linguistic research, identifying core challenges for their deployment. Overall, we seek to inspire timely actions to counter a looming source of inequity in behavioural neurology.

A Systematic Review and Meta-Analysis Comparing the Diagnostic Accuracy Tests of COVID-19

In this paper, we present a systematic review and meta-analysis that aims to evaluate the reliability of coronavirus disease diagnostic tests in 2019 (COVID-19). This article seeks to describe the scientific discoveries made because of diagnostic tests conducted in recent years during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Between 2020 and 2021, searches for published papers on the COVID-19 diagnostic were made in the PubMed database. Ninety-nine scientific articles that satisfied the requirements were analyzed and included in the meta-analysis, and the specificity and sensitivity of the diagnostic accuracy were assessed. When compared to serological tests such as the enzyme-linked immunosorbent assay (ELISA), chemiluminescence immunoassay (CLIA), lateral flow immunoassay (LFIA), and chemiluminescent microparticle immunoassay (CMIA), molecular tests such as reverse transcription polymerase chain reaction (RT-PCR), reverse transcription loop-mediated isothermal amplification (RT-LAMP), and clustered regularly interspaced short palindromic repeats (CRISPR) performed better in terms of sensitivity and specificity. Additionally, the area under the curve restricted to the false-positive rates (AUC_FPR) of 0.984 obtained by the antiviral neutralization bioassay (ANB) diagnostic test revealed significant potential for the identification of COVID-19. It has been established that the various diagnostic tests have been effectively adapted for the detection of SARS-CoV-2; nevertheless, their performance still must be enhanced to contain potential COVID-19 outbreaks, which will also help contain potential infectious agent outbreaks in the future.

Co-occurring pathogenic variants in 6q27 associated with dementia spectrum disorders in a Peruvian family

Evidence suggests that there may be racial differences in risk factors associated with the development of Alzheimer's disease and related dementia (ADRD). We used whole-genome sequencing analysis and identified a novel combination of three pathogenic variants in the heterozygous state (UNC93A: rs7739897 and WDR27: rs61740334; rs3800544) in a Peruvian family with a strong clinical history of ADRD. Notably, the combination of these variants was present in two generations of affected individuals but absent in healthy members of the family. In silico and in vitro studies have provided insights into the pathogenicity of these variants. These studies predict that the loss of function of the mutant UNC93A and WDR27 proteins induced dramatic changes in the global transcriptomic signature of brain cells, including neurons, astrocytes, and especially pericytes and vascular smooth muscle cells, indicating that the combination of these three variants may affect the neurovascular unit. In addition, known key molecular pathways associated with dementia spectrum disorders were enriched in brain cells with low levels of UNC93A and WDR27. Our findings have thus identified a genetic risk factor for familial dementia in a Peruvian family with an Amerindian ancestral background.

Accuracy of Diagnostic Tests for the Detection of Chagas Disease: A Systematic Review and Meta-Analysis

The present systematic review and meta-analysis about the accuracy of diagnostic tests aim to describe the findings of literature over the last thirty years for the diagnosis of Chagas disease (CD). This work aimed to determine the accuracy of diagnostic techniques for CD in the disease's acute and chronic phases. The PubMed database was searched for studies published between 1990 and 2021 on CD diagnostics. Fifty-six published studies that met the criteria were analyzed and included in the meta-analysis, evaluating diagnostic accuracy through sensitivity and specificity. For Enzyme-Linked Immunosorbent Assay (ELISA), Fluorescent Antibody Technique (IFAT), Hemagglutination Test (HmT), Polymerase Chain Reaction (PCR), and Real-Time Polymerase Chain Reaction (qPCR) diagnosis methods, the sensitivity had a median of 99.0%, 78.0%, 75.0%, 76.0%, and 94.0%, respectively; while specificity presented a median of 99.0%, 99.0%, 99.0%, 98.0%, and 98.0%, respectively. This meta-analysis showed that ELISA and qPCR techniques had a higher performance compared to other methods of diagnosing CD in the chronic and acute phases, respectively. It was concluded utilizing the Area Under the Curve restricted to the false positive rates (AUCFPR), that the ELISA diagnostic test presents the highest performance in diagnosing acute and chronic CD, compared to serological and molecular tests. Future studies focusing on new CD diagnostics approaches should be targeted.

Prevalence of Dementia and Main Subtypes in Mexico: The Study on Aging and Dementia in Mexico (SADEM)

BACKGROUND

Dementia is a priority public health issue due to its high prevalence worldwide and its economic, social, and health impact. However, there are few reports in Mexico based on formal tests and with a clinical approach based on the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5).

OBJECTIVE

This study estimates the prevalence of the main types of dementia among elderly people living in the community in Mexico City.

METHODS

A population-based, two-step study was conducted, including 6,204 elderly individuals aged 60 or above with in-home assessment. All participants were screened for cognitive impairment; those who presented some cognitive problem underwent a standardized neurological examination. Each diagnosis was based on the criteria for dementia in the DSM-5, and the final consensus diagnosis of dementia was determined by an expert panel.

RESULTS

The global estimated prevalence of dementia in the Mexican population was 7.8% met the criteria for Alzheimer's disease, 4.3% for vascular dementia, and 2.1% for mixed dementia. The prevalence of dementia was higher in women than in men (15.3% versus 12.5%, respectively).

CONCLUSION

These results provide evidence to propose strategies for Latin American countries where dementia represents a challenge due to the heterogeneity of the populations and socioeconomic disparities, requiring early diagnosis and at the first levels of care.

Alzheimer's Disease: A Silent Pandemic - A Systematic Review on the Situation and Patent Landscape of the Diagnosis

BACKGROUND

Alzheimer's disease (AD) is characterized by cognitive impairment, tau protein deposits, and amyloid beta plaques. AD impacted 44 million people in 2016, and it is estimated to affect 100 million people by 2050. AD is disregarded as a pandemic compared with other diseases. To date, there is no effective treatment or diagnosis.

OBJECTIVE

We aimed to discuss the current tools used to diagnose COVID-19, to point out their potential to be adapted for AD diagnosis, and to review the landscape of existing patents in the AD field and future perspectives for AD diagnosis.

METHOD

We carried out a scientific screening following a research strategy in PubMed; Web of Science; the Derwent Innovation Index; the KCI-Korean Journal Database; SciELO; the Russian Science Citation index; and the CDerwent, EDerwent, and MDerwent index databases.

RESULTS

A total of 326 from 6,446 articles about AD and 376 from 4,595 articles about COVID-19 were analyzed. Of these, AD patents were focused on biomarkers and neuroimaging with no accurate, validated diagnostic methods, and only 7% of kit development patents were found. In comparison, COVID-19 patents were 60% about kit development for diagnosis; they are highly accurate and are now commercialized.

CONCLUSION

AD is still neglected and not recognized as a pandemic that affects the people and economies of all nations. There is a gap in the development of AD diagnostic tools that could be filled if the interest and effort that has been invested to tackle the COVID-19 emergency could also be applied for innovation.

A systematic analysis of diagnostic performance for Alzheimer's disease using structural MRI

Background

Alzheimer's disease (AD) is one of the most common neurodegenerative disorders in the elderly. Although numerous structural magnetic resonance imaging (sMRI) studies have reported diagnostic models that could distinguish AD from normal controls (NCs) with 80-95% accuracy, limited efforts have been made regarding the clinically practical computer-aided diagnosis (CAD) system for AD.

Objective

To explore the potential factors that hinder the clinical translation of the AD-related diagnostic models based on sMRI.

Methods

To systematically review the diagnostic models for AD based on sMRI, we identified relevant studies published in the past 15 years on PubMed, Web of Science, Scopus, and Ovid. To evaluate the heterogeneity and publication bias among those studies, we performed subgroup analysis, meta-regression, Begg's test, and Egger's test.

Results

According to our screening criterion, 101 studies were included. Our results demonstrated that high diagnostic accuracy for distinguishing AD from NC was obtained in recently published studies, accompanied by significant heterogeneity. Meta-analysis showed that many factors contributed to the heterogeneity of high diagnostic accuracy of AD using sMRI, which included but was not limited to the following aspects: (i) different datasets; (ii) different machine learning models, e.g. traditional machine learning or deep learning model; (iii) different cross-validation methods, e.g. k-fold cross-validation leads to higher accuracies than leave-one-out cross-validation, but both overestimate the accuracy when compared to validation in independent samples; (iv) different sample sizes; and (v) the publication times. We speculate that these complicated variables might be the adverse factor for developing a clinically applicable system for the early diagnosis of AD.

Conclusions

Our findings proved that previous studies reported promising results for classifying AD from NC with different models using sMRI. However, considering the many factors hindering clinical radiology practice, there would still be a long way to go to improve.

Tau Biomarkers in Dementia: Positron Emission Tomography Radiopharmaceuticals in Tauopathy Assessment and Future Perspective

Abnormal accumulation of Tau protein is closely associated with neurodegeneration and cognitive impairment and it is a biomarker of neurodegeneration in the dementia field, especially in Alzheimer’s disease (AD); therefore, it is crucial to be able to assess the Tau deposits in vivo. Beyond the fluid biomarkers of tauopathy described in this review in relationship with the brain glucose metabolic patterns, this review aims to focus on tauopathy assessment by using Tau PET imaging. In recent years, several first-generation Tau PET tracers have been developed and applied in the dementia field. Common limitations of first-generation tracers include off-target binding and subcortical white-matter uptake; therefore, several institutions are working on developing second-generation Tau tracers. The increasing knowledge about the distribution of first- and second-generation Tau PET tracers in the brain may support physicians with Tau PET data interpretation, both in the research and in the clinical field, but an updated description of differences in distribution patterns among different Tau tracers, and in different clinical conditions, has not been reported yet. We provide an overview of first- and second-generation tracers used in ongoing clinical trials, also describing the differences and the properties of novel tracers, with a special focus on the distribution patterns of different Tau tracers. We also describe the distribution patterns of Tau tracers in AD, in atypical AD, and further neurodegenerative diseases in the dementia field.

Genetic Counselling Improves the Molecular Characterisation of Dementing Disorders

Dementing disorders are a complex group of neurodegenerative diseases characterised by different, but often overlapping, pathological pathways. Genetics have been largely associated with the development or the risk to develop dementing diseases. Recent advances in molecular technologies permit analyzing of several genes in a small time, but the interpretation analysis is complicated by several factors: the clinical complexity of neurodegenerative disorders, the frequency of co-morbidities, and the high phenotypic heterogeneity of genetic diseases. Genetic counselling supports the diagnostic path, providing an accurate familial and phenotypic characterisation of patients. In this review, we summarise neurodegenerative dementing disorders and their genetic determinants. Genetic variants and associated phenotypes will be divided into high and low impact, in order to reflect the pathologic continuum between multifactorial and mendelian genetic factors. Moreover, we report a molecular characterisation of genes associated with neurodegenerative disorders with cognitive impairment. In particular, the high frequency of rare coding genetic variants in dementing genes strongly supports the role of geneticists in both, clinical phenotype characterisation and interpretation of genotypic data. The smart application of exome analysis to dementia patients, with a pre-analytical selection on familial, clinical, and instrumental features, improves the diagnostic yield of genetic test, reduces time for diagnosis, and allows a rapid and personalised management of disease.