Alzheimer's disease CSF biomarkers: clinical indications and rational use

Alzheimer Disease Cerebrospinal Fluid Biomarkers in a Tertiary Neurology Practice

OBJECTIVE

To evaluate the performance of Alzheimer disease (AD) cerebrospinal fluid (CSF) biomarkers in a tertiary neurology clinic setting with high frequency of non-AD cases, including normal pressure hydrocephalus (NPH).

METHODS

There were 534 patients who underwent AD CSF biomarkers (Roche Elecsys Aβ42, p-Tau181, total-Tau) from April 1, 2020, through April 23, 2021. A behavioral neurologist blinded to CSF results assigned a clinical diagnosis retrospectively on the basis of consensus criteria, and a neuroradiologist blinded to the diagnosis and CSF studies graded brain magnetic resonance images for indicators of CSF dynamics disorders. Associations between biomarkers, diagnoses, and imaging were assessed by χ2, analysis of covariance, and linear regression methods.

RESULTS

Median age at time of testing was 67 years (range, 19 to 96 years), median symptom duration was 2 years (range, 0.4 to 28 years), and median Short Test of Mental Status score was 30 (range, 0 to 38). Clinical diagnoses significantly correlated with different CSF biomarker values (χ2=208.3; P=10e-4). p-Tau181/Aβ42 ratios above 0.023 positively correlated with Alzheimer dementia (more than individual measures). This ratio also had the best performance for differentiating Alzheimer dementia from NPH (area under the curve, 0.869). Imaging markers supportive of CSF dynamics disorders correlated with low Aβ42, p-Tau181, and total-Tau.

CONCLUSION

In a heterogeneous clinical population, abnormal p-Tau181/Aβ42 ratios (>0.023) have the strongest association with Alzheimer dementia and probably represent a comorbid AD pathologic component in persons clearly matching non-AD neurodegenerative syndromes. Altered CSF dynamics were associated with lower concentrations of AD CSF biomarkers regardless of clinical diagnosis, but the ratio compensates for these changes. In the appropriate clinical setting, an isolated abnormal Aβ42 should prompt consideration of NPH.

Emergence of Extracellular Vesicles as "Liquid Biopsy" for Neurological Disorders: Boom or Bust

Extracellular vesicles (EVs) have emerged as an attractive liquid biopsy approach in the diagnosis and prognosis of multiple diseases and disorders. The feasibility of enriching specific subpopulations of EVs from biofluids based on their unique surface markers has opened novel opportunities to gain molecular insight from various tissues and organs, including the brain. Over the past decade, EVs in bodily fluids have been extensively studied for biomarkers associated with various neurological disorders, such as Alzheimer's disease, Parkinson's disease, schizophrenia, bipolar disorder, major depressive disorders, substance use disorders, human immunodeficiency virus-associated neurocognitive disorder, and cancer/treatment-induced neurodegeneration. These studies have focused on the isolation and cargo characterization of either total EVs or brain cells, such as neuron-, astrocyte-, microglia-, oligodendrocyte-, pericyte-, and endothelial-derived EVs from biofluids to achieve early diagnosis and molecular characterization and to predict the treatment and intervention outcomes. The findings of these studies have demonstrated that EVs could serve as a repetitive and less invasive source of valuable molecular information for these neurological disorders, supplementing existing costly neuroimaging techniques and relatively invasive measures, like lumbar puncture. However, the initial excitement surrounding blood-based biomarkers for brain-related diseases has been tempered by challenges, such as lack of central nervous system specificity in EV markers, lengthy protocols, and the absence of standardized procedures for biological sample collection, EV isolation, and characterization. Nevertheless, with rapid advancements in the EV field, supported by improved isolation methods and sensitive assays for cargo characterization, brain cell-derived EVs continue to offer unparallel opportunities with significant translational implications for various neurological disorders. SIGNIFICANCE STATEMENT: Extracellular vesicles present a less invasive liquid biopsy approach in the diagnosis and prognosis of various neurological disorders. Characterizing these vesicles in biofluids holds the potential to yield valuable molecular information, thereby significantly impacting the development of novel biomarkers for various neurological disorders. This paper has reviewed the methodology employed to isolate extracellular vesicles derived from various brain cells in biofluids, their utility in enhancing the molecular understanding of neurodegeneration, and the potential challenges in this research field.

Why to test for dementia: perspectives of patients, significant others and general practitioners

BACKGROUND

This study aims to provide greater insight into the current decision-making process on diagnostic testing for dementia by exploring the expectations, needs and experiences of patients with memory complaints, significant others and general practitioners (GPs).

METHODS

We performed semi-structured interviews with patients (>60 years) who consulted their GP on memory complaints, significant others and GPs. Participants were recruited until data saturation was reached in thematic analysis of interview transcripts.

RESULTS

We performed 51 interviews (patients n = 20, significant others n = 15, GPs n = 16). Thematic analysis revealed four themes: (i) 'drivers to (not) testing', i.e. need to act on symptoms, beliefs on the necessity and expected outcomes of diagnostic testing; (ii) 'patient preferences and context are critical in the actual decision', i.e. in the actual decision-making process interpretation of symptoms, GPs' desire to meet patient preferences, social context and healthcare system dynamics guided the decision; (iii) 'need for individualised communication in the decision-making process', i.e. for patients feeling heard was a prerequisite for decision-making and GPs tailored communication strategies to individual patients and (iv) 'GP practice and barriers to shared decision-making (SDM)', i.e. although GPs value SDM in the decision on diagnostic testing for dementia, patients express limited awareness of the decision and options at stake.

CONCLUSIONS

Decision-making on diagnostic testing for dementia is a multifactorial and preference-guided process for all involved stakeholders, but decisions are often not explicitly jointly made. Development of patient decision aids could facilitate better involvement and more informed choices by patients.

Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity. Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

Transcriptomic profiling of cerebrospinal fluid identifies ALS pathway enrichment and RNA biomarkers in MND individuals

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder and the most common form of motor neurone disease (MND) which is characterized by the damage and death of motor neurons in the brain and spinal cord of affected individuals. Due to the heterogeneity of the disease, a better understanding of the interaction between genetics and biochemistry with the identification of biomarkers is crucial for therapy development. In this study, we used cerebrospinal fluid (CSF) RNA-sequencing data from the New York Genome Center (NYGC) ALS Consortium and analyzed differential gene expression between 47 MND individuals and 29 healthy controls. Pathway analysis showed that the affected genes are enriched in many pathways associated with ALS, including nucleocytoplasmic transport, autophagy, and apoptosis. Moreover, we assessed differential expression on both gene- and transcript-based levels and demonstrate that the expression of previously identified potential biomarkers, including CAPG, CCL3, and MAP2, was significantly higher in MND individuals. Ultimately, this study highlights the transcriptomic composition of CSF which enables insights into changes in the brain in ALS and therefore increases the confidence in the use of CSF for biomarker development.

CSF biomarker analysis of ABCA7 mutation carriers suggests altered APP processing and reduced inflammatory response

BACKGROUND

The Alzheimer's disease (AD) risk gene ABCA7 has suggested functions in lipid metabolism and the immune system. Rare premature termination codon (PTC) mutations and an expansion of a variable number of tandem repeats (VNTR) polymorphism in the gene, both likely cause a lower ABCA7 expression and hereby increased risk for AD. However, the exact mechanism of action remains unclear. By studying CSF biomarkers reflecting different types of AD-related pathological processes, we aim to get a better insight in those processes and establish a biomarker profile of mutation carriers.

METHODS

The study population consisted of 229 AD patients for whom CSF was available and ABCA7 sequencing and VNTR genotyping had been performed. This included 28 PTC mutation and 16 pathogenic expansion carriers. CSF levels of Aβ1-42, Aβ1-40, P-tau181, T-tau, sAPPα, sAPPβ, YKL-40, and hFABP were determined using ELISA and Meso Scale Discovery assays. We compared differences in levels of these biomarkers and the Aβ ratio between AD patients with or without an ABCA7 PTC mutation or expansion using linear regression on INT-transformed data with APOE-status, age and sex as covariates.

RESULTS

Carriers of ABCA7 expansion mutations had significantly lower Aβ1-42 levels (P = 0.022) compared with non-carrier patients. The effect of the presence of ABCA7 mutations on CSF levels was especially pronounced in APOE ε4-negative carriers. In addition, VNTR expansion carriers had reduced Aβ1-40 (P = 0.023), sAPPα (P = 0.047), sAPPβ (P = 0.016), and YKL-40 (P = 0.0036) levels.

CONCLUSIONS

Our results are suggestive for an effect on APP processing by repeat expansions given the changes in the amyloid-related CSF biomarkers that were found in carriers. The decrease in YKL-40 levels in expansion carriers moreover suggests that these patients potentially have a reduced inflammatory response to AD damage. Moreover, our findings suggest the existence of a mechanism, independent of lowered expression, affecting neuropathology in expansion carriers.

Data Mining of Microarray Datasets in Translational Neuroscience

Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.

Multi-modal cross-attention network for Alzheimer's disease diagnosis with multi-modality data

Alzheimer's disease (AD) is a neurodegenerative disorder, the most common cause of dementia, so the accurate diagnosis of AD and its prodromal stage mild cognitive impairment (MCI) is significant. Recent studies have demonstrated that multiple neuroimaging and biological measures contain complementary information for diagnosis. Many existing multi-modal models based on deep learning simply concatenate each modality's features despite substantial differences in representation spaces. In this paper, we propose a novel multi-modal cross-attention AD diagnosis (MCAD) framework to learn the interaction between modalities for better playing their complementary roles for AD diagnosis with multi-modal data including structural magnetic resonance imaging (sMRI), fluorodeoxyglucose-positron emission tomography (FDG-PET) and cerebrospinal fluid (CSF) biomarkers. Specifically, the imaging and non-imaging representations are learned by the image encoder based on cascaded dilated convolutions and CSF encoder, respectively. Then, a multi-modal interaction module is introduced, which takes advantage of cross-modal attention to integrate imaging and non-imaging information and reinforce relationships between these modalities. Moreover, an extensive objective function is designed to reduce the discrepancy between modalities for effectively fusing the features of multi-modal data, which could further improve the diagnosis performance. We evaluate the effectiveness of our proposed method on the ADNI dataset, and the extensive experiments demonstrate that our MCAD achieves superior performance for multiple AD-related classification tasks, compared to several competing methods. Also, we investigate the importance of cross-attention and the contribution of each modality to the diagnostics performance. The experimental results demonstrate that combining multi-modality data via cross-attention is helpful for accurate AD diagnosis.

Harmonization of CSF and imaging biomarkers for Alzheimer's disease biomarkers: need and practical applications for genetics studies and preclinical classification

INTRODUCTION

In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers which leads to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values.

METHODS

We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS result using this method with currently accepted methods. We also used a generalized mixture modelling to calculate the threshold for biomarker-positivity.

RESULTS

Z-scores method performed as well as meta-analysis and did not lead to any spurious results. Cutoffs calculated with this approach were found to be very similar to those reported previously.

DISCUSSION

This approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.

Cerebrospinal Fluid-Basic Concepts Review

Cerebrospinal fluid plays a crucial role in protecting the central nervous system (CNS) by providing mechanical support, acting as a shock absorber, and transporting nutrients and waste products. It is produced in the ventricles of the brain and circulates through the brain and spinal cord in a continuous flow. In the current review, we presented basic concepts related to cerebrospinal fluid history, cerebrospinal fluid production, circulation, and its main components, the role of the blood-brain barrier and the blood-cerebrospinal fluid barrier in the maintenance of cerebrospinal fluid homeostasis, and the utility of Albumin Quotient (Q_Alb) evaluation in the diagnosis of CNS diseases. We also discussed the collection of cerebrospinal fluid (type, number of tubes, and volume), time of transport to the laboratory, and storage conditions. Finally, we briefly presented the role of cerebrospinal fluid examination in CNS disease diagnosis of various etiologies and highlighted that research on identifying cerebrospinal fluid biomarkers indicating disease presence or severity, evaluating treatment effectiveness, and enabling understanding of pathogenesis and disease mechanisms is of great importance. Thus, in our opinion, research on cerebrospinal fluid is still necessary for both the improvement of CNS disease management and the discovery of new treatment options.

Clinical usefulness of cerebrospinal fluid biomarkers in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a complex disease that shares clinical features with other dementias. It is important to establish a specific and reliable diagnosis. Nowadays, AD diagnosis is based on cerebrospinal fluid (CSF) biomarkers. However, the corresponding cut-offs differ amongst studies. This study aims to evaluate the CSF biomarkers in the AD differential diagnosis.

METHODS

Clinical relevant biomarkers (amyloid β42 (Aβ42), t-Tau, p-Tau, amyloid β40 (Aβ40), neurofilament light chain (NfL)) were determined in CSF samples from participants classified as AD (n = 124) and non-AD (n = 148) patients from the Neurology Unit. They were included and evaluated consecutively (August 2018-October 2020). The clinical utility of these biomarkers was evaluated by AUC-ROC curves and the corresponding cut-off points were defined.

RESULTS

The results showed satisfactory accuracy (AUC-ROC 0.91 for Aβ42, 0.890 for t-Tau and 0.933 for p-Tau); whilst Aβ40 and NfL did not show good discriminatory capacity (AUC-ROC 0.557 and 0.738, respectively). The ratios Aβ42/Aβ40 and t-Tau/Aβ42 improved the diagnosis indices of each individual biomarker, with AUC-ROC of 0.980 and 0.971, respectively. Also, elevated levels of NfL were found in the frontotemporal dementia group compared with the other participant groups.

CONCLUSIONS

The ratio Aβ42/Aβ40 showed the highest discriminating capacity between AD and non-AD patients and might be useful in clinical practice. Regarding NfL, it is not a specific biomarker for AD; however, it might be helpful for the differential diagnosis of frontotemporal dementia. Nevertheless, further analysis in an external cohort is required in order to validate these results.

Identification of hub proteins in cerebrospinal fluid as potential biomarkers of Alzheimer's disease by integrated bioinformatics

BACKGROUND

Alzheimer's disease (AD) is a heterogeneous neurodegenerative disease with complex pathophysiology. Therefore, the identification of novel effective fluid biomarkers is essential for Alzheimer's disease diagnosis and drug development. This study aimed to identify potential candidate hub proteins in cerebrospinal fluid for precise Alzheimer's disease diagnosis using bioinformatics methods.

METHODS

A total of 29 co-significant differentially expressed proteins were identified by differential protein expression analysis in four different cohorts. Functional enrichment analysis revealed that most of these proteins were enriched in pathways related to glycometabolism. Using the Least Absolute Shrinkage and Selection Operator (LASSO) and random forest feature selection methods, six hub proteins [14-3-3 protein zeta/delta (YWHAZ), SPARC-related modular calcium-binding protein 1 (SMOC1), aldolase A (ALDOA), pyruvate kinase isoenzyme type M2 (PKM), chitinase-3-like protein 1 (CHI3L1), and secreted phosphoprotein 1 (SPP1)] were identified.

RESULTS

These six hub proteins were upregulated in the cerebrospinal fluid of patients with Alzheimer's disease compared with cognitively unimpaired control individuals. Meanwhile, SMOC1, ALDOA, and PKM were specifically upregulated in the cerebrospinal fluid of patients with Alzheimer's disease but not in other neurodegenerative diseases. Build AD diagnostic models showed that a single hub protein or six hub proteins combination had an excellent ability to discriminate Alzheimer's disease.

CONCLUSIONS

In conclusion, our study suggests that these identified hub proteins, which are related to glycometabolism, may be potential biomarkers for further basic and clinical research in Alzheimer's disease.

AQP4 mitigates chronic neuropathic pain-induced cognitive impairment in mice

Neuropathic pain is a risk factor for cognitive defects. The ubiquitous expression of AQP4 in astrocytes throughout the central nervous system is altered in the neurodegenerative disease. However, the exact role of AQP4 in cognitive impairment induced by chronic neuropathic pain remains unclear. In this study, we discovered that AQP4 protein and mRNA expression decreased time-dependently in the model of chronic neuropathic pain-induced cognitive disorder. AQP4 overexpression recovered mice from cognitive impairment. Furthermore, the concentration of Aβ1-42 in the serum and hippocampus reduced in mice with AQP4 overexpression adeno-associated virus injection. In conclusion, AQP4 in astrocytes is important in mitigating cognitive impairment caused by chronic neuropathic pain.

Clinical utility of cerebrospinal fluid biomarkers in the evaluation of cognitive impairment: a systematic review and meta-analysis

BACKGROUND

The analytical and clinical validity of cerebrospinal (CSF) biomarkers has been extensively researched in dementia. Further work is needed to assess the ability of these biomarkers to improve diagnosis, management and health outcomes in the clinical setting OBJECTIVES: To assess the added value and clinical utility of CSF biomarkers in the diagnostic assessment of cognitively impaired patients under evaluation for Alzheimer's disease (AD).

METHODS

Systematic literature searches of Medline, EMBASE, PsycINFO and Web of Science research databases were conducted on 17 December 2022. Data from relevant studies were extracted and independently screened for quality using a tool for bias. Clinical utility was measured by clinicians' changes in diagnosis, diagnostic confidence and patient management (when available), after their examination of patients' CSF biomarkers. Cost-effectiveness was assessed by consideration of additional cost per patient and quality-adjusted life years.

RESULTS

Searches identified 17 studies comprising 2090 patient participants and 593 clinicians. The meta-analysis revealed that clinicians' use of CSF biomarkers resulted in a pooled percentage change in diagnosis of 25% (95% CI 14 to 37), an increase in diagnostic confidence of 14% (95% CI 9 to 18) and a pooled proportion of patients whose management changed of 31% (95% CI 12 to 50). CSF biomarkers were deemed cost-effective, particularly in memory services, where pre-test AD prevalence is higher compared with a primary care setting.

CONCLUSIONS

CSF biomarkers can be a helpful additional diagnostic tool for clinicians assessing patients with cognitive impairment. In particular, CSF biomarkers consistently improved clinicians' confidence in diagnosing AD and influenced on diagnostic change and patient management. Further research is needed to study the clinical utility of blood-based biomarkers in the clinical setting.

Anti-Inflammatory Effect of Traditional Chinese Medicine on the Concept of Mind-Body Interface

In this chapter, we conducted a systemic literature review for the anti-inflammatory effects of Traditional Chinese Medicine (TCM) applying molecular mechanisms focusing on the neuroinflammation and gut-brain axis in three neuropsychiatric disorders: major depressive disorder, Alzheimer's disease, and Parkinson's disease. We demonstrated the anti-inflammation or immunomodulation effects of TCM, including acupuncture, from basic and clinical research, including cellular and molecular approaches. In conclusion, inflammation plays a critical role in the neuropsychopathological process. At the same time, anti-inflammation seems to be the common biological pathway for the effects of TCM and acupuncture in depression, Alzheimer's disease, and Parkinson's disease.

Improved Alzheimer's Disease versus Frontotemporal Lobar Degeneration Differential Diagnosis Combining EEG and Neurochemical Biomarkers: A Pilot Study

BACKGROUND

Distinguishing between Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) results in poor diagnostic accuracy.

OBJECTIVE

To investigate the utility of electroencephalography (EEG)-based biomarkers in comparison and in addition to established cerebrospinal fluid (CSF) biomarkers in the AD versus FTLD differential diagnosis.

METHODS

The study cohort comprised 37 AD and 30 FTLD patients, of which 17 AD and 9 FTLD patients had definite diagnoses. All participants had CSF neurochemical (NCM) biomarker analyses (Aβ1-42, T-tau, P-tau181, and Nf-L) and underwent 19-channel resting-state EEG. From the EEG spectra, dominant frequency peaks were extracted in four regions resulting in four dominant frequencies. This produced eight features (4 NCM + 4 EEG).

RESULTS

When NCM and EEG markers were combined, the diagnostic accuracy increased significantly. In the whole group, the accuracy went up from 79% (NCM) to almost 82%, while in the definite group only, it went up from around 85% to almost 95%. Two differences in the occurrence of the dominant EEG frequency were discovered: people lacking a clear dominant peak almost all had definite AD, while people with two peaks more often had FTLD.

CONCLUSION

Combining EEG with NCM biomarkers resulted in differential diagnostic accuracies of 82% in clinically diagnosed AD and FTD patients and of 95% in patients having a definite diagnosis, which was significantly better than with EEG or NCM biomarkers alone. This suggests that NCM and EEG markers are complementary, revealing different aspects of the disease and therefore confirms again their relevance in developing additional diagnosis tools.

Current Diagnostic Methods and Non-Coding RNAs as Possible Biomarkers in Huntington’s Disease

Whether as a cause or a symptom, RNA transcription is recurrently altered in pathologic conditions. This is also true for non-coding RNAs, with regulatory functions in a variety of processes such as differentiation, cell identity and metabolism. In line with their increasingly recognized roles in cellular pathways, RNAs are also currently evaluated as possible disease biomarkers. They could be informative not only to follow disease progression and assess treatment efficacy in clinics, but also to aid in the development of new therapeutic approaches. This is especially important for neurological and genetic disorders, where the administration of appropriate treatment during the disease prodromal stage could significantly delay, if not halt, disease progression. In this review we focus on the current status of biomarkers in Huntington’s Disease (HD), a fatal hereditary and degenerative disease condition. First, we revise the sources and type of wet biomarkers currently in use. Then, we explore the feasibility of different RNA types (miRNA, ncRNA, circRNA) as possible biomarker candidates, discussing potential advantages, disadvantages, sources of origin and the ongoing investigations on this topic.

Biomarker and therapeutic potential of peripheral extracellular vesicles in Alzheimer's disease

Extracellular vesicles (EVs) are cell-derived nanoparticles with an important role in intercellular communication, even across brain barriers. The bidirectional brain-barrier crossing capacity of EVs is supported by research identifying neuronal markers in peripheral EVs, as well as the brain delivery of peripherally administered EVs. In addition, EVs are reflective of their cellular origin, underlining their biomarker and therapeutic potential when released by diseased and regenerative cells, respectively. Both characteristics are of interest in Alzheimer's disease (AD) where the current biomarker profile is solely based on brain-centered readouts and effective therapeutic options are lacking. In this review, we elaborate on the role of peripheral EVs in AD. We focus on bulk EVs and specific EV subpopulations including bacterial EVs (bEVs) and neuronal-derived EVs (nEVs), which have mainly been studied from a biomarker perspective. Furthermore, we highlight the therapeutic potential of peripherally administered EVs whereby research has centered around stem cell derived EVs.

Relevance of plasma biomarkers to pathologies in Alzheimer's disease, Parkinson's disease and frontotemporal dementia

Amyloid plaques and tau tangles are pathological hallmarks of Alzheimer's disease (AD). Parkinson's disease (PD) results from the accumulation of α-synuclein. TAR DNA-binding protein (TDP-43) and total tau protein (T-Tau) play roles in FTD pathology. All of the pathological evidence was found in the biopsy. However, it is impossible to perform stein examinations in clinical practice. Assays of biomarkers in plasma would be convenient. It would be better to investigate the combinations of various biomarkers in AD, PD and FTD. Ninety-one subjects without neurodegenerative diseases, 76 patients with amnesic mild cognitive impairment (aMCI) or AD dementia, combined as AD family, were enrolled. One hundred and nine PD patients with normal cognition (PD-NC) or dementia (PDD), combined as PD family, were enrolled. Twenty-five FTD patients were enrolled for assays of plasma amyloid β 1-40 (Aβ_1-40), Aβ_1-42, T-Tau, α-synuclein and TDP-43 using immunomagnetic reduction (IMR). The results show that Aβs and T-Tau are major domains in AD family. α-synuclein is highly dominant in PD family. FTD is closely associated with TDP-43 and T-Tau. The dominant plasma biomarkers in AD family, PD family and FTD are consistent with pathology. This implies that plasma biomarkers are promising for precise and differential assessments of AD, PD and FTD in clinical practice.

A Study on Voice Measures in Patients With Alzheimer's Disease

OBJECTIVE

As Alzheimer's disease (AD) might provoke certain nerve disorders, patients with AD can acquire sensorimotor adaptation problems, and thus the acoustic characteristics of the speech they produce may differ from those of healthy subjects. This study aimed to (1) extract acoustic characteristics (relating to articulatory gestures) potentially useful for detecting AD and (2) examine whether these characteristics could help identify AD patients.

METHODS

A total of 50 individuals participated in the study, including the AD group (17 cases), the Neurologically Healthy (NH) group (13 cases), the Mild Cognitive Impairment (MCI) group (11 cases), and the Vascular Cognitive Impairment (VCI) group (9 cases). Voice samples involving three vowels (/i/, /a/, and /u/) and six consonants (/p/, /pʰ/, /t/, /tʰ/, /k/, and /kʰ/) were collected using a digital recorder (TASCAM DR40X). Microphone-to-mouth distance was maintained at 30 cm. Acoustic measures included F0, jitter, shimmer, HNR, F1, F2, F3, and VOT.

RESULTS

One-way ANOVA tests were carried out to compare the acoustic measures among the four groups. F3 of vowel /u/, F2 bandwidth of vowel /a/, VOT of consonant /t/, and male participants' F0 of three vowels (/a/, /i/, and /u/) were found significantly different, while no significant differences were found in the other measures.

CONCLUSION

Some acoustic characteristics can indeed help detect AD patients.

A classification for complex imbalanced data in disease screening and early diagnosis

Imbalanced classification has drawn considerable attention in the statistics and machine learning literature. Typically, traditional classification methods often perform poorly when a severely skewed class distribution is observed, not to mention under a high-dimensional longitudinal data structure. Given the ubiquity of big data in modern health research, it is expected that imbalanced classification in disease diagnosis may encounter an additional level of difficulty that is imposed by such a complex data structure. In this article, we propose a nonparametric classification approach for imbalanced data in longitudinal and high-dimensional settings. Technically, the functional principal component analysis is first applied for feature extraction under the longitudinal structure. The univariate exponential loss function coupled with group LASSO penalty is then adopted into the classification procedure in high-dimensional settings. Along with a good improvement in imbalanced classification, our approach provides a meaningful feature selection for interpretation while enjoying a remarkably lower computational complexity. The proposed method is illustrated on the real data application of Alzheimer's disease early detection and its empirical performance in finite sample size is extensively evaluated by simulations.

Perspectives and challenges in patient stratification in Alzheimer’s disease

Background

Patient stratification is the division of a patient population into distinct subgroups based on the presence or absence of particular disease characteristics. As patient stratification can be used to account for the underlying pathology of a disease, it can help physicians to tailor therapeutic interventions to individuals and optimize their care management and treatment regime. Alzheimer’s disease, the most common form of dementia, is a heterogeneous disease and its management benefits from patient stratification in clinical trials, and the development of personalized care and treatment strategies for people living with the disease.

Main body

In this review, we discuss the importance of the stratification of people living with Alzheimer’s disease, the challenges associated with early diagnosis and patient stratification, and the evolution of patient stratification once disease-modifying therapies become widely available.

Conclusion

Patient stratification plays an important role in drug development in clinical trials and may play an even larger role in clinical practice. A timely diagnosis and stratification of people living with Alzheimer’s disease is paramount in determining people who are at risk of progressing from mild cognitive impairment to Alzheimer’s dementia. There are key issues associated with stratifying patients which include the heterogeneity and complex neurobiology behind Alzheimer’s disease, our inadequately prepared healthcare systems, and the cultural perceptions of Alzheimer’s disease. Stratifying people living with Alzheimer’s disease may be the key in establishing precision and personalized medicine in the field, optimizing disease prevention and pharmaceutical treatment to slow or stop cognitive decline, while minimizing adverse effects.

Transcranial Electromagnetic Treatment Stops Alzheimer’s Disease Cognitive Decline over a 2½-Year Period: A Pilot Study

Background: There is currently no therapeutic that can stop or reverse the progressive memory impairment of Alzheimer’s disease (AD). However, we recently published that 2 months of daily, in-home transcranial electromagnetic treatment (TEMT) reversed the cognitive impairment in eight mild/moderate AD subjects. These cognitive enhancements were accompanied by predicted changes in AD markers within both the blood and cerebrospinal fluid (CSF). Methods: In view of these encouraging findings, the initial clinical study was extended twice to encompass a period of 2½ years. The present study reports on the resulting long-term safety, cognitive assessments, and AD marker evaluations from the five subjects who received long-term treatment. Results: TEMT administration was completely safe over the 2½-year period, with no deleterious side effects. In six cognitive/functional tasks (including the ADAS-cog13, Rey AVLT, MMSE, and ADL), no decline in any measure occurred over this 2½-year period. Long-term TEMT induced reductions in the CSF levels of C-reactive protein, p-tau217, Aβ1-40, and Aβ1-42 while modulating CSF oligomeric Aβ levels. In the plasma, long-term TEMT modulated/rebalanced levels of both p-tau217 and total tau. Conclusions: Although only a limited number of AD patients were involved in this study, the results suggest that TEMT can stop the cognitive decline of AD over a period of at least 2½ years and can do so with no safety issues.

A novel approach to type 3 diabetes mechanism: The interplay between noncoding RNAs and insulin signaling pathway in Alzheimer's disease

Today, growing evidence indicates that patients with type 2 diabetes (T2D) are at a higher risk of developing Alzheimer's disease (AD). Indeed, AD as one of the main causes of dementia in people aged more than 65 years can be aggravated by insulin resistance (IR) and other metabolic risk factors related to T2D which are also linked to the function of the brain. Remarkably, a new term called "type 3 diabetes" has been suggested for those people who are diagnosed with AD while also showing the symptoms of IR and T2D. In this regard, the role of genetic and epigenetic changes associated with AD has been confirmed by many studies. On the other hand, it should be noted that the insulin signaling pathway is highly regulated by various mechanisms, including epigenetic factors. Among these, the role of noncoding RNAs (ncRNAs), including microRNAs and long noncoding RNAs has been comprehensively studied with respect to the pathology of AD and the most well-known underlying mechanisms. Nevertheless, the number of studies exploring the association between ncRNAs and the downstream targets of the insulin signaling pathway in the development of AD has notably increased in recent years. With this in view, the present study aimed to review the interplay between different ncRNAs and the insulin signaling pathway targets in the pathogenesis of AD to find a new approach in the field of combining biomarkers or therapeutic targets for this disease.

Investigation of Whole and Glandular Saliva as a Biomarker for Alzheimer's Disease Diagnosis

Salivary Aβ40, Aβ42, t-tau, and p-tau 181 are commonly employed in Alzheimer's disease (AD) investigations. However, the collection method of these biomarkers can affect their levels. To assess the impact of saliva collection methods on biomarkers in this study, 15 healthy people were employed in the morning with six saliva collection methods. The chosen methods were then applied in 30 AD patients and 30 non-AD controls. The levels of salivary biomarkers were calculated by a specific enzyme-linked immunosorbent assay. The receiver operating characteristic was utilized to assess salivary biomarkers in AD patients. The results demonstrated that the highest levels of salivary Aβ40, Aβ42, t-tau, and p-tau were in different saliva collection methods. The correlations between different saliva biomarkers in the same collection method were different. Salivary Aβ40, Aβ42, t-tau, and p-tau had no significant association. Salivary Aβ42 was higher in AD than in non-AD controls. However, p-tau/t-tau and Aβ42/Aβ40 had some relevance. The area under the curve for four biomarkers combined in AD diagnosis was 92.11%. An alternate saliva collection method (e.g., USS in Aβ40, UPS in Aβ42, t-tau, SSS in p-tau 181) was demonstrated in this study. Moreover, combining numerous biomarkers improves AD diagnosis.

Circulating extracellular vesicles: friends and foes in neurodegeneration

Extracellular vesicles have been identified as pivotal mediators of intercellular communication with critical roles in physiological and pathological conditions. Via this route, several molecules (e.g., nucleic acids, proteins, metabolites) can be transferred to proximal and distant targets to convey specific information. Extracellular vesicle-associated cargo molecules have been proposed as markers of several disease conditions for their potential of tracking down the generating cell. Indeed, circulating extracellular vesicles may represent biomarkers of dysfunctional cellular quality control systems especially in conditions characterized by the accrual of intracellular misfolded proteins. Furthermore, the identification of extracellular vesicles as tools for the delivery of nucleic acids or other cargo molecules to diseased tissues makes these circulating shuttles possible targets for therapeutic development. The increasing interest in the study of extracellular vesicles as biomarkers resides mainly in the fact that the identification of peripheral levels of extracellular vesicle-associated proteins might reflect molecular events occurring in hardly accessible tissues, such as the brain, thereby serving as a "brain liquid biopsy". The exploitation of extracellular vesicles for diagnostic and therapeutic purposed might offer unprecedented opportunities to develop personalized approaches. Here, we discuss the bright and dark sides of extracellular vesicles in the setting of two main neurodegenerative diseases (i.e., Parkinson's and Alzheimer's diseases). A special focus will be placed on the possibility of using extracellular vesicles as biomarkers for the two conditions to enable disease tracking and treatment monitoring.

Diagnostic Blood Biomarkers in Alzheimer’s Disease

Potential biomarkers for Alzheimer’s disease (AD) include amyloid β1–42 (Aβ1–42), t-Tau, p-Tau181, neurofilament light chain (NFL), and neuroimaging biomarkers. Their combined use is useful for diagnosing and monitoring the progress of AD. Therefore, further development of a combination of these biomarkers is essential. We investigated whether plasma NFL/Aβ1–42 can serve as a plasma-based primary screening biomarker reflecting brain neurodegeneration and amyloid pathology in AD for monitoring disease progression and early diagnosis. We measured the NFL and Aβ1–42 concentrations in the CSF and plasma samples and performed correlation analysis to evaluate the utility of these biomarkers in the early diagnosis and monitoring of AD spectrum disease progression. Pearson’s correlation analysis was used to analyse the associations between the fluid biomarkers and neuroimaging data. The study included 136 participants, classified into five groups: 28 cognitively normal individuals, 23 patients with preclinical AD, 22 amyloid-negative patients with amnestic mild cognitive impairment, 32 patients with prodromal AD, and 31 patients with AD dementia. With disease progression, the NFL concentrations increased and Aβ1–42 concentrations decreased. The plasma and CSF NFL/Aβ1–42 were strongly correlated (r = 0.558). Plasma NFL/Aβ1–42 was strongly correlated with hippocampal volume/intracranial volume (r = 0.409). In early AD, plasma NFL/Aβ1–42 was associated with higher diagnostic accuracy than the individual biomarkers. Moreover, in preclinical AD, plasma NFL/Aβ1–42 changed more rapidly than the CSF t-Tau or p-Tau181 concentrations. Our findings highlight the utility of plasma NFL/Aβ1–42 as a non-invasive plasma-based biomarker for early diagnosis and monitoring of AD spectrum disease progression.

Ultrasensitive Detection of Alzheimer's Amyloids on a Plasmonic-Gold Platform

More than 55 million people live with dementia worldwide in 2021, and there are nearly 10 million new cases every year. Alzheimer's disease (AD) is the most common cause of dementia. Despite urgent need, early detection of AD and long-term monitoring of AD progression have been challenging. This is due to the limited availability of brain imaging facilities and the highly invasive procedure with the cerebrospinal fluid assay to assess the level of AD biomarkers, such as beta-amyloid (Aβ). Reliable measurements of AD biomarkers in blood samples are still difficult because of their very low abundance. Here, we develop a rapid, specific, and ultrasensitive immunoassay using plasmonic-gold nanoisland (pGOLD) chips with near-infrared fluorescence-enhanced detection for Aβ_1-40 and Aβ_1-42. We show step-by-step processes and results during the platform establishment, including antibody specificity and sensitivity tests, antibody pair examination, condition optimization, and procedure refinement. Finally, we demonstrate the platform performance with detection sensitivity at the subpicogram per milliliter level. This platform, therefore, has a great application potential for early detection of AD using blood samples.

The prognostic utility of CSF neurogranin in predicting future cognitive decline in the Alzheimer's disease continuum: A systematic review and meta-analysis with narrative synthesis

Core cerebrospinal fluid (CSF) biomarkers (Aβ42, T-tau, P-tau) were included as supporting diagnostic criteria for Alzheimer's Disease (AD), but they lack the power to predict AD progression. On the other hand, a new biomarker CSF Neurogranin (Ng) has been shown to predict cognitive decline. This systematic review aims to synthesise the prognostic utility of CSF Ng in predicting cognitive decline in the AD continuum. Seven databases were searched systematically from inception to 30 September 2020. Participants were 55 years or older, who had baseline and at least one follow-up cognitive assessments. Risk of bias was assessed using the Quality in Prognosis Studies tool. Meta-analysis was conducted by pooling standardised beta coefficients and adjusted hazard ratios. Thirteen studies were included and high-quality evidence suggests that CSF Ng predicts Mini-Mental State Examination (MMSE) decline in Aβ⁺ mild cognitive impairment (MCI). Moderate quality evidence showed that CSF Ng could predict the decline of memory and executive function in MCI. Narrative synthesis found that CSF Ng/Aβ42 was also likely to predict cognitive decline. More studies are required to validate the use of CSF Ng as an AD prognostic marker and its application in future development of drug treatment and diagnosis.

Improvement of cognitive performance by a nutraceutical formulation: Underlying mechanisms revealed by laboratory studies

Cognitive decline, decrease in neuronal function and neuronal loss that accompany normal aging and dementia are the result of multiple mechanisms, many of which involve oxidative stress. Herein, we review these various mechanisms and identify pharmacological and non-pharmacological approaches, including modification of diet, that may reduce the risk and progression of cognitive decline. The optimal degree of neuronal protection is derived by combinations of, rather than individual, compounds. Compounds that provide antioxidant protection are particularly effective at delaying or improving cognitive performance in the early stages of Mild Cognitive Impairment and Alzheimer's disease. Laboratory studies confirm alleviation of oxidative damage in brain tissue. Lifestyle modifications show a degree of efficacy and may augment pharmacological approaches. Unfortunately, oxidative damage and resultant accumulation of biomarkers of neuronal damage can precede cognitive decline by years to decades. This underscores the importance of optimization of dietary enrichment, antioxidant supplementation and other lifestyle modifications during aging even for individuals who are cognitively intact.

Challenges in Alzheimer's Disease Diagnostic Work-Up: Amyloid Biomarker Incongruences

BACKGROUND

Discordance among amyloid biomarkers is a challenge to overcome in order to increase diagnostic accuracy in dementia.

OBJECTIVES

1) To verify that cerebrospinal fluid (CSF) Aβ42/Aβ40 ratio (AβR) better agrees with Amyloid PET (Amy-PET) results compared to CSF Aβ42; 2) to detect differences among concordant positive, concordant negative, and discordant cases, basing the concordance definition on the agreement between CSF AβR and Amy-PET results; 3) to define the suspected underlying pathology of discordant cases using in vivo biomarkers.

METHOD

We retrospectively enrolled 39 cognitively impaired participants in which neuropsychological tests, apolipoprotein E genotype determination, TC/MRI, FDG-PET, Amy-PET, and CSF analysis had been performed. In all cases, CSF analysis was repeated using the automated Lumipulse method. In discordant cases, FDG-PET scans were evaluated visually and using automated classifiers.

RESULTS

CSF AβR better agreed with Amy-PET compared to CSF Aβ42 (Cohen's K 0.431 versus 0.05). Comparisons among groups did not show any difference in clinical characteristics except for age at symptoms onset that was higher in the 6 discordant cases with abnormal CSF AβR values and negative Amy-PET (CSF AβR+/AmyPET-). FDG-PET and all CSF markers (Aβ42, AβR, p-Tau, t-Tau) were suggestive of Alzheimer's disease (AD) in 5 of these 6 cases.

CONCLUSION

1) CSF AβR is the CSF amyloid marker that shows the better level of agreement with Amy-PET results; 2) The use of FDG-PET and CSF-Tau markers in CSFAβR+/Amy-PET-discordant cases can support AD diagnosis; 3) Disagreement between positive CSF AβR and negative Amy-PET in symptomatic aged AD patients could be due to the variability in plaques conformation and a negative Amy-PET scan cannot be always sufficient to rule out AD.

Multiclass diagnosis of stages of Alzheimer's disease using linear discriminant analysis scoring for multimodal data

Alzheimer's disease (AD) is a progressive neurodegenerative disease, and mild cognitive impairment (MCI) is a transitional stage between normal control (NC) and AD. A multiclass classification of AD is a difficult task because there are multiple similarities between neighboring groups. The performance of classification can be improved by using multimodal data, but the improvement could be limited with inefficient fusion of multimodal data. This study aims to develop a framework for AD multiclass diagnosis with a linear discriminant analysis (LDA) scoring method to fuse multimodal data more efficiently. Magnetic resonance imaging, positron emission tomography, cerebrospinal fluid biomarkers, and genetic features were first preprocessed by performing age correction, feature selection, and feature reduction. Then, they were individually scored using LDA, and the scores that represent the AD pathological progress in different modalities were obtained. Finally, an extreme learning machine-based decision tree was established to perform multiclass diagnosis using these scores. The experiments were conducted on the AD Neuroimaging Initiative dataset, and accuracies of 66.7% and 57.3% and F1-scores of 64.9% and 55.7% were achieved in three- and four-way classifications, respectively. The results also showed that the proposed framework achieved a better performance than the method that did not score multimodal data and the methods in previous studies, thereby indicating that the LDA scoring strategy is an efficient way for multimodalities fusion in AD multiclass classification.

In Vitro Conversion Assays Diagnostic for Neurodegenerative Proteinopathies

BACKGROUND

In vitro conversion assays, including real-time quaking-induced conversion (RT-QuIC) and protein misfolding cyclic amplification (PMCA) techniques, were first developed to study the conversion process of the prion protein to its misfolded, disease-associated conformation. The intrinsic property of prion proteins to propagate their misfolded structure was later exploited to detect subfemtogram quantities of the misfolded protein present in tissues and fluids from humans and animals with transmissible spongiform encephalopathies. Currently, conversion assays are used clinically as sensitive and specific diagnostic tools for antemortem diagnosis of prion disease.

CONTENT

In vitro conversion assays are now being applied to the development of diagnostics for related neurodegenerative diseases, including detection of misfolded α-synuclein in Parkinson disease, misfolded amyloid-β in Alzheimer disease, and misfolded tau in Pick disease. Like the predicate prion protein in vitro conversion diagnostics, these assays exploit the ability of endogenously misfolded proteins to induce misfolding and aggregation of their natively folded counterpart in vitro. This property enables biomarker detection of the underlying protein pathology. Herein, we review RT-QuIC and PMCA for (a) prion-, (b) α-synuclein-, (c) amyloid-β-, and (d) tau-opathies.

SUMMARY

Although already in routine clinical use for the detection of transmissible spongiform encephalopathies, in vitro conversion assays for other neurodegenerative disorders require further development and evaluation of diagnostic performance before consideration for clinical implementation.

Genetic and Transcriptomic Biomarkers in Neurodegenerative Diseases: Current Situation and the Road Ahead

Neurodegenerative diseases are etiologically and clinically heterogeneous conditions, often reflecting a spectrum of disease rather than well-defined disorders. The underlying molecular complexity of these diseases has made the discovery and validation of useful biomarkers challenging. The search of characteristic genetic and transcriptomic indicators for preclinical disease diagnosis, prognosis, or subtyping is an area of ongoing effort and interest. The next generation of biomarker studies holds promise by implementing meaningful longitudinal and multi-modal approaches in large scale biobank and healthcare system scale datasets. This work will only be possible in an open science framework. This review summarizes the current state of genetic and transcriptomic biomarkers in Parkinson's disease, Alzheimer's disease, and amyotrophic lateral sclerosis, providing a comprehensive landscape of recent literature and future directions.

Anterior Cingulate Structure and Perfusion is Associated with Cerebrospinal Fluid Tau among Cognitively Normal Older Adult APOEɛ4 Carriers

Evidence suggests the ɛ4 allele of the apolipoprotein E (APOE) gene may accelerate an age-related process of cortical thickening and cerebral blood flow (CBF) reduction in the anterior cingulate cortex (ACC). Although the neural basis of this association remains unclear, evidence suggests it might reflect early neurodegenerative processes. However, to date, associations between cerebrospinal fluid (CSF) biomarkers of neurodegeneration, such as CSF tau, and APOE-related alterations in ACC cortical thickness (CTH) and CBF have yet to be explored. The current study explored the interaction of CSF tau and APOE genotype (ɛ4+, ɛ4-) on FreeSurfer-derived CTH and arterial spin labeling MRI-measured resting CBF in the ACC (caudal ACC [cACC] and rostral ACC [rACC]) among a sample of 45 cognitively normal older adults. Secondary analyses also examined associations between APOE, CTH/CBF, and cognitive performance. In the cACC, higher CSF tau was associated with higher CTH and lower CBF in ɛ4+, whereas these relationships were not evident in ɛ4-. In the rACC, higher CSF tau was associated with higher CTH for both ɛ4+ and ɛ4-, and with lower CBF only in ɛ4+. Significant interactions of CSF tau and APOE on CTH/CBF were not observed in two posterior reference regions implicated in Alzheimer's disease. Secondary analyses revealed a negative relationship between cACC CTH and executive functioning in ɛ4+ and a positive relationship in ɛ4-. Findings suggest the presence of an ɛ4-related pattern of increased CTH and reduced CBF in the ACC that is associated with biomarkers of neurodegeneration and subtle decrements in cognition.

Cerebral amyloid angiopathy: an underdiagnosed cause of recurrent neurological symptoms

Cerebral amyloid angiopathy (CAA) is a common, yet frequently underdiagnosed pathology characterised by accumulation of amyloid β proteins in the small blood vessels of the brain. As a result, cerebrovascular dysregulation follows, leading to cerebral microbleeds, lobar intracerebral haematomas and sulcal subarachnoid haemorrhages. Gradual motor and cognitive decline due to these brain injuries leads to significant functional limitation in patients. We describe the case of a 69-year-old man requiring multiple hospital admissions with a variety of neurological symptoms. Following imaging of the brain, he was eventually diagnosed with CAA. We present a brief up-to-date literature review on epidemiology, pathophysiology, clinical features, diagnosis and treatment options for CAA.

Diagnosis and Management of Cognitive Concerns in the Oldest-Old

Purpose of review

The fastest-growing group of elderly individuals is the "oldest-old," usually defined as those age 85 years and above. These individuals account for much of the rapid increase in cases of dementing illness throughout the world but remain underrepresented in the body of literature on this topic. The aim of this review is first to outline the unique contributing factors and complications that must be considered by clinicians in evaluating an oldest-old individual with cognitive complaints. Secondly, the evidence for management of these cognitive concerns is reviewed.

Recent findings

In addition to well-established associations between impaired cognition and physical disability, falls, and frailty, there is now evidence that exercise performed decades earlier confers a cognitive benefit in the oldest-old. Moreover, though aggressive blood pressure control is critical earlier in life for prevention of strokes, renal disease, and other comorbidities, hypertension started after age 80 is in fact associated with a decreased risk of clinical dementia, carrying significant implications for the medical management of oldest-old individuals. The oldest-old are more likely to reside in care facilities, where social isolation might be exacerbated by a consistently lower rate of internet-connected device use. The COVID-19 pandemic has not only highlighted the increased mortality rate among the oldest-old but has also brought the increased social isolation in this group to the forte.

Summary

Differing from the "younger-old" in a number of respects, the oldest-old is a unique population not just in their vulnerability to cognitive disorders but also in the diagnostic challenges they can pose. The oldest-old are more likely to be afflicted by sensory deficits, physical disability, poor nutrition, frailty, and depression, which must be accounted for in the assessment of cognitive complaints as they may confound or complicate the presentation. Social isolation and institutionalization are also associated with impaired cognition, perhaps as sequelae, precipitants, or both. Ante-mortem diagnostic tools remain particularly limited among the oldest-old, especially given the likelihood of these individuals to have multiple co-occurring types of neuropathology, and the presence of neuropathology in those who remain cognitively intact. In addition to the symptomatic treatments indicated for patients of all ages with dementia, management of cognitive impairment in the oldest-old may be further optimized by use of assistive devices, augmentation of dietary protein, and liberalization of medication regimens for risk factors such as hypertension.

Mitochondriopathies as a Clue to Systemic Disorders-Analytical Tools and Mitigating Measures in Context of Predictive, Preventive, and Personalized (3P) Medicine

The mitochondrial respiratory chain is the main site of reactive oxygen species (ROS) production in the cell. Although mitochondria possess a powerful antioxidant system, an excess of ROS cannot be completely neutralized and cumulative oxidative damage may lead to decreasing mitochondrial efficiency in energy production, as well as an increasing ROS excess, which is known to cause a critical imbalance in antioxidant/oxidant mechanisms and a "vicious circle" in mitochondrial injury. Due to insufficient energy production, chronic exposure to ROS overproduction consequently leads to the oxidative damage of life-important biomolecules, including nucleic acids, proteins, lipids, and amino acids, among others. Different forms of mitochondrial dysfunction (mitochondriopathies) may affect the brain, heart, peripheral nervous and endocrine systems, eyes, ears, gut, and kidney, among other organs. Consequently, mitochondriopathies have been proposed as an attractive diagnostic target to be investigated in any patient with unexplained progressive multisystem disorder. This review article highlights the pathomechanisms of mitochondriopathies, details advanced analytical tools, and suggests predictive approaches, targeted prevention and personalization of medical services as instrumental for the overall management of mitochondriopathy-related cascading pathologies.

Plasma and cerebrospinal fluid ABeta42 for the differential diagnosis of Alzheimer's disease dementia in participants diagnosed with any dementia subtype in a specialist care setting

BACKGROUND

Dementia is a syndrome that comprises many differing pathologies, including Alzheimer's disease dementia (ADD), vascular dementia (VaD) and frontotemporal dementia (FTD). People may benefit from knowing the type of dementia they live with, as this could inform prognosis and may allow for tailored treatment. Beta-amyloid (1-42) (ABeta42) is a protein which decreases in both the plasma and cerebrospinal fluid (CSF) of people living with ADD, when compared to people with no dementia. However, it is not clear if changes in ABeta42 are specific to ADD or if they are also seen in other types of dementia. It is possible that ABeta42 could help differentiate ADD from other dementia subtypes.

OBJECTIVES

To determine the accuracy of plasma and CSF ABeta42 for distinguishing ADD from other dementia subtypes in people who meet the criteria for a dementia syndrome.

SEARCH METHODS

We searched MEDLINE, and nine other databases up to 18 February 2020. We checked reference lists of any relevant systematic reviews to identify additional studies.

SELECTION CRITERIA

We considered cross-sectional studies that differentiated people with ADD from other dementia subtypes. Eligible studies required measurement of participant plasma or CSF ABeta42 levels and clinical assessment for dementia subtype.

DATA COLLECTION AND ANALYSIS

Seven review authors working independently screened the titles and abstracts generated by the searches. We collected data on study characteristics and test accuracy. We used the second version of the 'Quality Assessment of Diagnostic Accuracy Studies' (QUADAS-2) tool to assess internal and external validity of results. We extracted data into 2 x 2 tables, cross-tabulating index test results (ABeta42) with the reference standard (diagnostic criteria for each dementia subtype). We performed meta-analyses using bivariate, random-effects models. We calculated pooled estimates of sensitivity, specificity, positive predictive values, positive and negative likelihood ratios, and corresponding 95% confidence intervals (CIs). In the primary analysis, we assessed accuracy of plasma or CSF ABeta42 for distinguishing ADD from other mixed dementia types (non-ADD). We then assessed accuracy of ABeta42 for differentiating ADD from specific dementia types: VaD, FTD, dementia with Lewy bodies (DLB), alcohol-related cognitive disorder (ARCD), Creutzfeldt-Jakob disease (CJD) and normal pressure hydrocephalus (NPH). To determine test-positive cases, we used the ABeta42 thresholds employed in the respective primary studies. We then performed sensitivity analyses restricted to those studies that used common thresholds for ABeta42.

MAIN RESULTS

We identified 39 studies (5000 participants) that used CSF ABeta42 levels to differentiate ADD from other subtypes of dementia. No studies of plasma ABeta42 met the inclusion criteria. No studies were rated as low risk of bias across all QUADAS-2 domains. High risk of bias was found predominantly in the domains of patient selection (28 studies) and index test (25 studies). The pooled estimates for differentiating ADD from other dementia subtypes were as follows: ADD from non-ADD: sensitivity 79% (95% CI 0.73 to 0.85), specificity 60% (95% CI 0.52 to 0.67), 13 studies, 1704 participants, 880 participants with ADD; ADD from VaD: sensitivity 79% (95% CI 0.75 to 0.83), specificity 69% (95% CI 0.55 to 0.81), 11 studies, 1151 participants, 941 participants with ADD; ADD from FTD: sensitivity 85% (95% CI 0.79 to 0.89), specificity 72% (95% CI 0.55 to 0.84), 17 studies, 1948 participants, 1371 participants with ADD; ADD from DLB: sensitivity 76% (95% CI 0.69 to 0.82), specificity 67% (95% CI 0.52 to 0.79), nine studies, 1929 participants, 1521 participants with ADD. Across all dementia subtypes, sensitivity was greater than specificity, and the balance of sensitivity and specificity was dependent on the threshold used to define test positivity.

AUTHORS' CONCLUSIONS

Our review indicates that measuring ABeta42 levels in CSF may help differentiate ADD from other dementia subtypes, but the test is imperfect and tends to misdiagnose those with non-ADD as having ADD. We would caution against the use of CSF ABeta42 alone for dementia classification. However, ABeta42 may have value as an adjunct to a full clinical assessment, to aid dementia diagnosis.

Polyamine biomarkers as indicators of human disease

The significant increase of periodontitis, chronic kidney disease (CKD), Alzheimer's disease and cancer can be attributed to an ageing population. Each disease produces a range of biomarkers that can be indicative of disease onset and progression. Biomarkers are defined as cellular (intra/extracellular components and whole cells), biochemical (metabolites, ions and toxins) or molecular (nucleic acids, proteins and lipids) alterations which are measurable in biological media such as human tissues, cells or fluids. An interesting group of biomarkers that merit further investigation are the polyamines. Polyamines are a group of molecules consisting of cadaverine, putrescine, spermine and spermidine and have been implicated in the development of a range of systemic diseases, in part due to their production in periodontitis. Cadaverine and putrescine within the periodontal environment have demonstrated cell signalling interfering abilities, by way of leukocyte migration disruption. The polyamines spermine and spermidine in tumour cells have been shown to inhibit cellular apoptosis, effectively prolonging tumorigenesis and continuation of cancer within the host. Polyamine degradation products such as acrolein have been shown to exacerbate renal damage in CKD patients. Thus, the use of such molecules has merit to be utilized in the early indication of such diseases in patients.

Early-Onset Alzheimer's Disease: What Is Missing in Research?

PURPOSE OF REVIEW

Early-onset Alzheimer's disease (EOAD), defined as Alzheimer's disease (AD) occurring before age 65, is significantly less well studied than the late-onset form (LOAD) despite EOAD often presenting with a more aggressive disease progression. The aim of this review is to summarize the current understanding of the etiology of EOAD, their translation into clinical practice, and to suggest steps to be taken to move our understanding forward.

RECENT FINDINGS

EOAD cases make up 5-10% of AD cases but only 10-15% of these cases show known mutations in the APP, PSEN1, and PSEN2, which are linked to EOAD. New data suggests that these unexplained cases following a non-Mendelian pattern of inheritance is potentially caused by a mix of common and newly discovered rare variants. However, only a fraction of this genetic variation has been identified to date leaving the molecular mechanisms underlying this type of AD and their association with clinical, biomarker, and neuropathological changes unclear. While great advancements have been made in characterizing EOAD, much work is needed to disentangle the molecular mechanisms underlying this type of AD and to identify putative targets for more precise disease screening, diagnosis, prevention, and treatment.

Analysis of the Human Plasma Proteome Using Multi-Nanoparticle Protein Corona for Detection of Alzheimer's Disease

As the population affected by Alzheimer's disease (AD) grows, so does the need for a noninvasive and accurate diagnostic tool. Current research reveals that AD pathogenesis begins as early as decades before clinical symptoms. The unique properties of nanoparticles (NPs) may be exploited to develop noninvasive diagnostics for early detection of AD. After exposure of NPs to biological fluids, the NP surface is altered by an unbiased but selective and reproducible adsorption of biomolecules commonly referred to as the biomolecular corona or protein corona (PC). The discovery that the plasma proteome may be differentially altered during health and disease leads to the concept of disease-specific PCs. Herein, the disease-specific PCs formed around NPs in a multi-NPs platform are employed to successfully identify subtle changes in plasma protein patterns and detect AD (>92% specificity and ≈100% sensitivity). Similar discrimination power is achieved using banked plasma samples from a cohort of patients several years prior to their diagnosis with AD. With the nanoplatform's analytic ability to analyze pathological proteomic changes into a disease-specific identifier, this promising, noninvasive technology with implications for early detection and intervention could benefit not only patients with AD but other diseases as well.

Plasma GSH levels and Alzheimer's disease. A prospective approach.: Results from the HELIAD study

BACKGROUND

Potential links between oxidative stress and the pathophysiology of Alzheimer's disease (AD) have been reported in the existing literature. Biological markers of oxidative stress, such as the reduced form of glutathione (GSH), may have a potential role as predictive biomarkers for AD development. The aim of the present study was to explore the longitudinal associations between plasma GSH and the risk of developing AD or cognitive decline, in a sample of community-dwelling, non-demented older adults.

METHODS

Participants from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) were included in the present prospective study. The sample used in the analyses consisted of 391 non-demented individuals over the age of 64 (mean age = 73.85 years; SD = 5.06), with available baseline GSH measurements and longitudinal follow-up. Plasma GSH was treated both as a continuous variable and as tertiles in our analyses. Cox proportional hazards models were used to evaluate the hazard ratio (HR) for AD incidence as a function of baseline plasma GSH. Generalized estimating equations (GEE) models were deployed to explore the associations between baseline plasma GSH and the rate of change of performance scores on individual cognitive domains over time. Models were adjusted for age, years of education and sex. Supplementary exploratory models were also adjusted for mild cognitive impairment (MCI) at baseline, risk for malnutrition, physical activity and adherence to the Mediterranean dietary pattern.

RESULTS

A total of 24 incident AD cases occurred during a mean (SD) of 2.99 (0.92) years of follow-up. Individuals in the highest GSH tertile group (highest baseline plasma GSH values) had a 70.1% lower risk for development of AD, compared to those in the lowest one [HR = 0.299 (0.093-0.959); p = 0.042], and also demonstrated a slower rate of decline of their executive functioning over time (5.2% of a standard deviation less decline in the executive composite score for each additional year of follow-up; p = 0.028). The test for trend was also significant suggesting a potential dose-response relationship.

CONCLUSION

In the present study, higher baseline plasma GSH levels were associated with a decreased risk of developing AD and with a better preservation of executive functioning longitudinally.

Circadian changes in Alzheimer's disease: Neurobiology, clinical problems, and therapeutic opportunities

The understanding of Alzheimer's disease (AD) pathophysiology is an active area of research, and the traditional focus on hippocampus, amyloid and tau protein, and memory impairment has been expanded with components like neuroinflammation, insulin resistance, and circadian rhythm alterations. The bidirectional vicious cycle of neuroinflammation and neurodegeneration on a molecular level may cause functional deficits already long before the appearance of overt clinical symptoms. Located at the crossroads of metabolic, circadian, and hormonal signaling, the hypothalamus has been identified as another brain region affected by AD pathophysiology. Current findings on hypothalamic dysfunction open a broader horizon for studying AD pathogenesis and offer new opportunities for diagnosis and therapy. While treatments with cholinomimetics and memantine form a first line of pharmacological treatment, additional innovative research is pursued toward the development of antiinflammatory, growth factor, or antidiabetic types of medication. Following recent epidemiological data showing associations of AD incidence with modern societal and "life-style"-related risk factors, also nonpharmacological interventions, including sleep optimization, are being developed and some have been shown to be beneficial. Circadian aspects in AD are relevant from a pathophysiological standpoint, but they can also have an important role in pharmacologic and nonpharmacologic interventions, and appropriate timing of sleep, meals, and medication may boost therapeutic efficacy.

Views on Early Diagnosis of Alzheimer's Disease Among Dutch Physicians: A Qualitative Interview Study

BACKGROUND

Hope for future treatments to prevent or slow down dementia motivates researchers to strive for ever-earlier diagnoses of Alzheimer's disease (AD) based on biomarkers, even before symptoms occur. But is a biomarker-based early diagnosis desirable in clinical practice?

OBJECTIVE

This study explores the ethical considerations that shape current clinical practice regarding early AD diagnostics and the use of biomarkers.

METHODS

In this qualitative study, Dutch physicians were interviewed. Topics included physicians' views concerning early AD diagnosis in persons with no or mild cognitive impairment, physicians' considerations regarding current and expected future practices of early AD diagnosis, the use of biomarkers, and the use of the concepts preclinical and prodromal AD. We analyzed the transcripts using directed content analysis.

RESULTS

15 general practitioners, neurologists, and geriatricians in the Netherlands were interviewed. Most of them interpreted an early AD diagnosis with an early diagnosis of dementia. We identified six clusters of considerations sometimes in favor but most often against pursuing an early AD diagnosis in people with no or mild cognitive impairment that influence physicians' diagnostic decision-making: preferences and characteristics of persons, test characteristics, impact on care, type of setting, disease concepts, and issues on a societal level.

CONCLUSION

The discussion concerning an early AD diagnosis based on biomarkers which is widely held in the scientific field, has not entered clinical practice structurally. A biomarker-based early diagnosis does not fit within Dutch physicians' views on what good care for people with no, subjective, or mild cognitive impairment should entail.

Comparing fluid biomarkers of Alzheimer's disease between African American or Black African and white groups: A systematic review and meta-analysis

RATIONALE

Biomarker research for Alzheimer's disease (AD) has grown rapidly in recent years, ensuing the integration of the AD fluid biomarker profile: Aβ1-42, t-tau, and p-tau₁₈₁, into clinical and research criteria. However, current insights of AD arise almost exclusively from studies on white individuals. Some studies have revealed that epidemiology, clinical features, and genetics of AD show variations between individuals from black and white backgrounds, conveying the importance of ethnoracial differences, and the possibility of such differences also influencing AD biomarker levels. This systematic review explored whether AD fluid biomarker levels differ between African American (AA) or Black African and white groups.

AIM

To compare AD fluid biomarkers (Aβ1-42, p-tau₁₈₁, and t-tau) levels between AA or Black Africans and white individuals.

METHOD

PubMed, Scopus, and other sources were explored for studies that quantified AD biomarkers in biological fluid from whites and AA or Black African groups. Meta-analyses were performed to find the standardized mean difference for biomarkers that were quantified in ≥3 studies.

RESULTS

Five studies were included; studies on Black Africans were not found. The meta-analyses found CSF t-tau and p-tau₁₈₁ were consistently lower in AA than white individuals, in samples with normal cognition or with mild cognitive impairment/dementia.

CONCLUSIONS

The meta-analyses found significant differences for CSF tau between AA and white individuals with normal cognition and within the dementia spectrum, expressing the importance of taking into account ethnoracial factors when interpreting CSF AD biomarkers levels. However, the generalisability of these differences is restricted by small samples' size, lack of unified methodologies and recruitment's biases within studies; further large multicentre studies with harmonized protocols and sufficient power are imperative to investigate the extent of ethnoracial differences across the spectrum of cognitive decline, with vaster efforts necessary to diversify recruitment.

Extracellular Vesicles in Alzheimer's and Parkinson's Disease: Small Entities with Large Consequences

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are incurable, devastating neurodegenerative disorders characterized by the formation and spreading of protein aggregates throughout the brain. Although the exact spreading mechanism is not completely understood, extracellular vesicles (EVs) have been proposed as potential contributors. Indeed, EVs have emerged as potential carriers of disease-associated proteins and are therefore thought to play an important role in disease progression, although some beneficial functions have also been attributed to them. EVs can be isolated from a variety of sources, including biofluids, and the analysis of their content can provide a snapshot of ongoing pathological changes in the brain. This underlines their potential as biomarker candidates which is of specific relevance in AD and PD where symptoms only arise after considerable and irreversible neuronal damage has already occurred. In this review, we discuss the known beneficial and detrimental functions of EVs in AD and PD and we highlight their promising potential to be used as biomarkers in both diseases.

Developing Effective Alzheimer's Disease Therapies: Clinical Experience and Future Directions

Alzheimer's disease (AD) clinical trials, focused on disease modifying drugs and conducted in patients with mild to moderate AD, as well as prodromal (early) AD, have failed to reach efficacy endpoints in improving cognitive function in most cases to date or have been terminated due to adverse events. Drugs that have reached clinical stage were reviewed using web resources (such as clinicaltrials.gov, alzforum.org, company press releases, and peer reviewed literature) to identify late stage (Phase II and Phase III) efficacy clinical trials and summarize reasons for their failure. For each drug, only the latest clinical trials and ongoing trials that aimed at improving cognitive function were included in the analysis. Here we highlight the potential reasons that have hindered clinical success, including clinical trial design and choice of outcome measures, heterogeneity of patient populations, difficulties in diagnosing and staging the disease, drug design, mechanism of action, and toxicity related to the long-term use. We review and suggest approaches for AD clinical trial design aimed at improving our ability to identify novel therapies for this devastating disease.

Contributions of Molecular and Optical Techniques to the Clinical Diagnosis of Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide. The distinctive neuropathological feature of AD is the intracerebral accumulation of two abnormally folded proteins: β-amyloid (Aβ) in the form of extracellular plaques, and tau in the form of intracellular neurofibrillary tangles. These proteins are considered disease-specific biomarkers, and the definite diagnosis of AD relies on their post-mortem identification in the brain. The clinical diagnosis of AD is challenging, especially in the early stages. The disease is highly heterogeneous in terms of clinical presentation and neuropathological features. This phenotypic variability seems to be partially due to the presence of distinct Aβ conformers, referred to as strains. With the development of an innovative technique named Real-Time Quaking-Induced Conversion (RT-QuIC), traces of Aβ strains were found in the cerebrospinal fluid of AD patients. Emerging evidence suggests that different conformers may transmit their strain signature to the RT-QuIC reaction products. In this review, we describe the current challenges for the clinical diagnosis of AD and describe how the RT-QuIC products could be analyzed by a surface-enhanced Raman spectroscopy (SERS)-based systems to reveal the presence of strain signatures, eventually leading to early diagnosis of AD with the recognition of individual disease phenotype.