Blood-Based ATN Biomarkers of Alzheimer's Disease: A Meta-Analysis

Diagnostic and predictive power of plasma proteins in Alzheimer's disease: a cross-sectional and longitudinal study in China

Convenient and effective biomarkers are essential for the early diagnosis and treatment of Alzheimer's disease (AD). In the cross-sectional study, 103 patients with AD, 82 patients with aMCI and 508 normal controls (NC) were enrolled. The single-molecule array (Simoa) technique was used to assess the levels of plasma proteins, including NfL, T-tau, P-tau-181, Aβ40, Aβ42. Montreal Cognitive Assessment (MoCA) was used to assess the overall cognitive function of all subjects. Moreover, Amyloid PET and structural head MRI were also performed in a subset of the population. In the follow-up, the previous 508 normal older adults were followed up for two years, then COX regression analysis was used to investigate the association between baseline plasma proteins and future cognitive outcomes. NfL, T-tau, P-tau-181, Aβ40, Aβ42 and Aβ42/40 were altered in AD dementia, and NfL, Aβ42 and Aβ42/40 significantly outperformed all plasma proteins in differentiating AD dementia from NC, while NfL and Aβ42/40 could effectively distinguish between aMCI and NC. However, only plasma NfL was associated with future cognitive decline, and it was negatively correlated with MoCA (r = - 0.298, p < 0.001) and the volume of the left globus pallidus (r = - 0.278, p = 0.033). Plasma NfL can help distinguish between cognitively normal and cognitively impaired individuals (MCI/dementia) at the syndrome level. However, since we have not introduced other biomarkers for AD, such as PET CT or cerebrospinal fluid, and have not verified in other neurodegenerative diseases, whether plasma NFL can be used as a biomarker for AD needs to be further studied and explored.

Neurofilament Light Chain as a Biomarker of Global Cognition in Individuals With Possible Vascular Mild Cognitive Impairment

BACKGROUND

Neurofilament Light Chain (NfL) is a biomarker of axonal injury elevated in mild cognitive impairment (MCI) and Alzheimer's disease dementia. Blood NfL also inversely correlates with cognitive performance in those conditions. However, few studies have assessed NfL as a biomarker of global cognition in individuals demonstrating mild cognitive deficits who are at risk for vascular-related cognitive decline.

OBJECTIVE

To assess the relationship between blood NfL and global cognition in individuals with possible vascular MCI (vMCI) throughout cardiac rehabilitation (CR). Additionally, NfL levels were compared to age/sex-matched cognitively unimpaired (CU) controls.

METHOD

Participants with coronary artery disease (vMCI or CU) were recruited at entry to a 24-week CR program. Global cognition was measured using the Montreal Cognitive Assessment (MoCA) and plasma NfL level (pg/ml) was quantified using a highly sensitive enzyme-linked immunosorbent assay.

RESULTS

Higher plasma NfL was correlated with worse MoCA scores at baseline (β = -.352, P = .029) in 43 individuals with vMCI after adjusting for age, sex, and education. An increase in NfL was associated with worse global cognition (b[SE] = -4.81[2.06], P = .023) over time, however baseline NfL did not predict a decline in global cognition. NfL levels did not differ between the vMCI (n = 39) and CU (n = 39) groups (F(1, 76) = 1.37, P = .245).

CONCLUSION

Plasma NfL correlates with global cognition at baseline in individuals with vMCI, and is associated with decline in global cognition during CR. Our findings increase understanding of NfL and neurobiological mechanisms associated with cognitive decline in vMCI.

Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting

Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.

Unlocking Preclinical Alzheimer's: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics

Alzheimer's disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer's encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer's still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer's diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer's, which is particularly surprising because of Raman spectroscopy's high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer's disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods.

Feasibility and Preliminary Efficacy of American Elderberry Juice for Improving Cognition and Inflammation in Patients with Mild Cognitive Impairment

Despite data showing that nutritional interventions high in antioxidant/anti-inflammatory properties (anthocyanin-rich foods, such as blueberries/elderberries) may decrease risk of memory loss and cognitive decline, evidence for such effects in mild cognitive impairment (MCI) is limited. This study examined preliminary effects of American elderberry (Sambucus nigra subsp. canadensis) juice on cognition and inflammatory markers in patients with MCI. In a randomized, double-blind, placebo-controlled trial, patients with MCI (n = 24, Mage = 76.33 ± 6.95) received American elderberry (n = 11) or placebo (n = 13) juice (5 mL orally 3 times a day) for 6 months. At baseline, 3 months, and 6 months, patients completed tasks measuring global cognition, verbal memory, language, visuospatial cognitive flexibility/problem solving, and memory. A subsample (n = 12, 7 elderberry/5 placebo) provided blood samples to measure serum inflammatory markers. Multilevel models examined effects of the condition (elderberry/placebo), time (baseline/3 months/6 months), and condition by time interactions on cognition/inflammation outcomes. Attrition rates for elderberry (18%) and placebo (15%) conditions were fairly low. The dosage compliance (elderberry-97%; placebo-97%) and completion of cognitive (elderberry-88%; placebo-87%) and blood-based (elderberry-100%; placebo-100%) assessments was high. Elderberry (not placebo) trended (p = 0.09) towards faster visuospatial problem solving performance from baseline to 6 months. For the elderberry condition, there were significant or significantly trending decreases over time across several markers of low-grade peripheral inflammation, including vasorin, prenylcysteine oxidase 1, and complement Factor D. Only one inflammatory marker showed an increase over time (alpha-2-macroglobin). In contrast, for the placebo, several inflammatory marker levels increased across time (L-lactate dehydrogenase B chain, complement Factor D), with one showing deceased levels over time (L-lactate dehydrogenase A chain). Daily elderberry juice consumption in patients with MCI is feasible and well tolerated and may provide some benefit to visuospatial cognitive flexibility. Preliminary findings suggest elderberry juice may reduce low-grade inflammation compared to a placebo-control. These promising findings support the need for larger, more definitive prospective studies with longer follow-ups to better understand mechanisms of action and the clinical utility of elderberries for potentially mitigating cognitive decline.

The free plasma amyloid Aβ1-42/Aβ1-40 ratio predicts conversion to dementia for subjects with mild cognitive impairment with performance equivalent to that of the total plasma Aβ1-42/Aβ1-40 ratio. The BALTAZAR study

BACKGROUND AND PURPOSE

Blood-based biomarkers are a non-invasive solution to predict the risk of conversion of mild cognitive impairment (MCI) to dementia. The utility of free plasma amyloid peptides (not bound to plasma proteins and/or cells) as an early indicator of conversion to dementia is still debated, as the results of studies have been contradictory. In this context, we investigated whether plasma levels of the free amyloid peptides Aβ1-42 and Aβ1-40 and the free plasma Aβ1-42/Aβ1-40 ratio are associated with the conversion of MCI to dementia, in particular AD, over three years of follow-up in a subgroup of the BALTAZAR cohort. We also compared their predictive value to that of total plasma Aβ1-42 and Aβ1-40 levels and the total plasma Aβ1-42/Aβ1-40 ratio.

METHODS

The plasma Aβ1-42 and Aβ1-40 peptide assay was performed using the INNO-BIA kit (Fujirebio Europe). Free amyloid levels (defined by the amyloid fraction directly accessible to antibodies of the assay) were obtained with the undiluted plasma, whereas total amyloid levels were obtained after the dilution of plasma (1/3) with a denaturing buffer. Free and total Aβ1-42 and Aβ1-40 levels were measured at inclusion for a subgroup of participants (N = 106) with mild cognitive impairment (MCI) from the BALTAZAR study (a large-scale longitudinal multicenter cohort with a three-year follow-up). Associations between conversion and the free/total plasma Aβ1-42 and Aβ1-40 levels and Aβ1-42/Aβ1-40 ratio were analyzed using logistic and Cox Proportional Hazards models. Demographic, clinical, cognitive (MMSE, ADL and IADL), APOE, and MRI characteristics (relative hippocampal volume) were compared using non-parametric (Mann-Whitney) or parametric (Student) tests for quantitative variables and Chi-square or Fisher exact tests for qualitative variables.

RESULTS

The risk of conversion to dementia was lower for patients in the highest quartile of free plasma Aβ1-42/Aβ1-40 (≥ 25.8%) than those in the three lower quartiles: hazard ratio = 0.36 (95% confidence interval [0.15-0.87]), after adjustment for age, sex, education, and APOE ε4 (p-value = 0.022). This was comparable to the risk of conversion in the highest quartile of total plasma Aβ1-42/Aβ1-40: hazard ratio = 0.37 (95% confidence interval [0.16-0.89], p-value = 0.027). However, while patients in the highest quartile of total plasma Aβ1-42/Aβ1-40 showed higher MMSE scores and a higher hippocampal volume than patients in the three lowest quartiles of total plasma Aβ1-42/Aβ1-40, as well as normal CSF biomarker levels, the patients in the highest quartile of free plasma Aβ1-42/Aβ1-40 did not show any significant differences in MMSE scores, hippocampal volume, or CSF biomarker levels relative to the three lowest quartiles of free plasma Aβ1-42/Aβ1-40.

CONCLUSION

The free plasma Aβ1-42/Aβ1-40 ratio is associated with a risk of conversion from MCI to dementia within three years, with performance comparable to that of the total plasma Aβ1-42/Aβ1-40 ratio. Threshold levels of the free and total plasma Aβ1-42/Aβ1-40 ratio could be determined, with a 60% lower risk of conversion for patients above the threshold than those below.

From understanding to action: Exploring molecular connections of Down syndrome to Alzheimer's disease for targeted therapeutic approach

Down syndrome (DS) is caused by a third copy of chromosome 21. Alzheimer's disease (AD) is a neurodegenerative condition characterized by the deposition of amyloid-beta (Aβ) plaques and neurofibrillary tangles in the brain. Both disorders have elevated Aβ, tau, dysregulated immune response, and inflammation. In people with DS, Hsa21 genes like APP and DYRK1A are overexpressed, causing an accumulation of amyloid and neurofibrillary tangles, and potentially contributing to an increased risk of AD. As a result, people with DS are a key demographic for research into AD therapeutics and prevention. The molecular links between DS and AD shed insights into the underlying causes of both diseases and highlight potential therapeutic targets. Also, using biomarkers for early diagnosis and treatment monitoring is an active area of research, and genetic screening for high-risk individuals may enable earlier intervention. Finally, the fundamental mechanistic parallels between DS and AD emphasize the necessity for continued research into effective treatments and prevention measures for DS patients at risk for AD. Genetic screening with customized therapy approaches may help the DS population in current clinical studies and future biomarkers.

The Role of Tau Pathology in Alzheimer's Disease and Down Syndrome

Background: Individuals with Down syndrome (DS) exhibit an almost complete penetrance of Alzheimer's disease (AD) pathology but are underrepresented in clinical trials for AD. The Tau protein is associated with microtubule function in the neuron and is crucial for normal axonal transport. In several different neurodegenerative disorders, Tau misfolding leads to hyper-phosphorylation of Tau (p-Tau), which may seed pathology to bystander cells and spread. This review is focused on current findings regarding p-Tau and its potential to seed pathology as a "prion-like" spreader. It also considers the consequences of p-Tau pathology leading to AD, particularly in individuals with Down syndrome. Methods: Scopus (SC) and PubMed (PM) were searched in English using keywords "tau AND seeding AND brain AND down syndrome". A total of 558 SC or 529 PM potentially relevant articles were identified, of which only six SC or three PM articles mentioned Down syndrome. This review was built upon the literature and the recent findings of our group and others. Results: Misfolded p-Tau isoforms are seeding competent and may be responsible for spreading AD pathology. Conclusions: This review demonstrates recent work focused on understanding the role of neurofibrillary tangles and monomeric/oligomeric Tau in the prion-like spreading of Tau pathology in the human brain.

Retinal Alterations Predict Early Prodromal Signs of Neurodegenerative Disease

Neurodegenerative diseases are an increasingly common group of diseases that occur late in life with a significant impact on personal, family, and economic life. Among these, Alzheimer's disease (AD) and Parkinson's disease (PD) are the major disorders that lead to mild to severe cognitive and physical impairment and dementia. Interestingly, those diseases may show onset of prodromal symptoms early after middle age. Commonly, the evaluation of these neurodegenerative diseases is based on the detection of biomarkers, where functional and structural magnetic resonance imaging (MRI) have shown a central role in revealing early or prodromal phases, although it can be expensive, time-consuming, and not always available. The aforementioned diseases have a common impact on the visual system due to the pathophysiological mechanisms shared between the eye and the brain. In Parkinson's disease, α-synuclein deposition in the retinal cells, as well as in dopaminergic neurons of the substantia nigra, alters the visual cortex and retinal function, resulting in modifications to the visual field. Similarly, the visual cortex is modified by the neurofibrillary tangles and neuritic amyloid β plaques typically seen in the Alzheimer's disease brain, and this may reflect the accumulation of these biomarkers in the retina during the early stages of the disease, as seen in postmortem retinas of AD patients. In this light, the ophthalmic evaluation of retinal neurodegeneration could become a cost-effective method for the early diagnosis of those diseases, overcoming the limitations of functional and structural imaging of the deep brain. This analysis is commonly used in ophthalmic practice, and interest in it has risen in recent years. This review will discuss the relationship between Alzheimer's disease and Parkinson's disease with retinal degeneration, highlighting how retinal analysis may represent a noninvasive and straightforward method for the early diagnosis of these neurodegenerative diseases.

Exploring small non-coding RNAs as blood-based biomarkers to predict Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone.

METHODS

This nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed.

RESULTS

The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD.

CONCLUSIONS

The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.

The heritability of blood-based biomarkers related to risk of Alzheimer's disease in a population-based sample of early old-age men

INTRODUCTION

Despite their increased application, the heritability of Alzheimer's disease (AD)-related blood-based biomarkers remains unexplored.

METHODS

Plasma amyloid beta 40 (Aβ40), Aβ42, the Aβ42/40 ratio, total tau (t-tau), and neurofilament light (NfL) data came from 1035 men 60 to 73 years of age (μ = 67.0, SD = 2.6). Twin models were used to calculate heritability and the genetic and environmental correlations between them.

RESULTS

Additive genetics explained 44% to 52% of Aβ42, Aβ40, t-tau, and NfL. The Aβ42/40 ratio was not heritable. Aβ40 and Aβ42 were genetically near identical (rg  = 0.94). Both Aβ40 and Aβ42 were genetically correlated with NfL (rg  = 0.35 to 0.38), but genetically unrelated to t-tau.

DISCUSSION

Except for Aβ42/40, plasma biomarkers are heritable. Aβ40 and Aβ42 share mostly the same genetic influences, whereas genetic influences on plasma t-tau and NfL are largely unique in early old-age men. The absence of genetic associations between the Aβs and t-tau is not consistent with the amyloid cascade hypothesis.

Shedding light on neurofilament involvement in cognitive decline in obstructive sleep apnea and its possible role as a biomarker

Obstructive sleep apnea is one of the most common sleep disorders with a high estimated global prevalence and a large number of associated comorbidities in general as well as specific neuropsychiatric complications such as cognitive impairment. The complex pathogenesis and effects of the disorder including chronic intermittent hypoxia and sleep fragmentation may lead to enhanced neuronal damage, thereby contributing to neuropsychiatric pathologies. Obstructive sleep apnea has been described as an independent risk factor for several neurodegenerative diseases, including Alzheimer's disease and all-cause dementia. The influence of obstructive sleep apnea on cognitive deficits is still a topic of recent debate, and several mechanisms, including neurodegeneration and depression-related cognitive dysfunction, underlying this correlation are taken into consideration. The differentiation between both pathomechanisms of cognitive impairment in obstructive sleep apnea is a complex clinical issue, requiring the use of multiple and costly diagnostic methods. The studies conducted on neuroprotection biomarkers, such as brain-derived neurotrophic factors and neurofilaments, are recently gaining ground in the topic of cognition assessment in obstructive sleep apnea patients. Neurofilaments as neuron-specific cytoskeletal proteins could be useful non-invasive indicators of brain conditions and neurodegeneration, which already are observed in many neurological diseases leading to cognitive deficits. Additionally, neurofilaments play an important role as a biomarker in other sleep disorders such as insomnia. Thus, this review summarizes the current knowledge on the involvement of neurofilaments in cognitive decline and neurodegeneration in obstructive sleep apnea patients as well as discusses its possible role as a biomarker of these changes.

Novel fluid biomarkers for mild cognitive impairment: A systematic review and meta-analysis

Mild cognitive impairment (MCI) is a well-established prodromal stage of dementia (e.g., Alzheimer's disease) that is often accompanied by early signs of neurodegeneration. To facilitate a better characterization of the underlying pathophysiology, we assessed the available literature to evaluate potential fluid biomarkers in MCI. Peer-reviewed articles that measured cerebrospinal fluid (CSF) and/or peripheral biomarkers of neuronal injury (total-tau [T-tau], neurofilament light chain [NfL], heart-type fatty acid binding protein [HFABP], neuron-specific enolase, ubiquitin C-terminal hydrolase L1) and/or astroglial pathology (glial fibrillary acidic protein [GFAP], S100 calcium-binding protein B) in MCI and healthy controls were assessed. Group differences were summarized by standardized mean differences (SMDs) and 95% confidence intervals calculated using a random-effects model. Heterogeneity was quantified using I2. A total of 107 studies were included in the meta-analysis and 10 studies were qualitatively reviewed. In CSF, concentrations of NfL (SMD = 0.69 [0.56, 0.83]), GFAP (SMD = 0.41 [0.07, 0.75]), and HFABP (SMD = 0.57 [0.26, 0.89]) were elevated in MCI. In blood, increased concentrations of T-tau (SMD = 0.19 [0.09, 0.29]), NfL (SMD = 0.41 [0.32, 0.49]), and GFAP (SMD = 0.39 [0.23, 0.55]) were found in MCI. Heterogeneity that was identified in all comparisons was explored using meta-regression and subgroup analysis. Elevated NfL and GFAP can be detected in both CSF and peripheral blood. Monitoring these biomarkers in clinical settings may provide important insight into underlying neurodegenerative processes in MCI.

Identification of preclinical dementia according to ATN classification for stratified trial recruitment: A machine learning approach

INTRODUCTION

The Amyloid/Tau/Neurodegeneration (ATN) framework was proposed to identify the preclinical biological state of Alzheimer's disease (AD). We investigated whether ATN phenotype can be predicted using routinely collected research cohort data.

METHODS

927 EPAD LCS cohort participants free of dementia or Mild Cognitive Impairment were separated into 5 ATN categories. We used machine learning (ML) methods to identify a set of significant features separating each neurodegeneration-related group from controls (A-T-(N)-). Random Forest and linear-kernel SVM with stratified 5-fold cross validations were used to optimize model whose performance was then tested in the ADNI database.

RESULTS

Our optimal results outperformed ATN cross-validated logistic regression models by between 2.2% and 8.3%. The optimal feature sets were not consistent across the 4 models with the AD pathologic change vs controls set differing the most from the rest. Because of that we have identified a subset of 10 features that yield results very close or identical to the optimal.

DISCUSSION

Our study demonstrates the gains offered by ML in generating ATN risk prediction over logistic regression models among pre-dementia individuals.

Neurofilaments - Small proteins of physiological significance and predictive power for future neurodegeneration and cognitive decline across the life span

Neurofilaments (NFs) are not only important for axonal integrity and nerve conduction in large myelinated axons but they are also thought to be crucial for receptor and synaptic functioning. Therefore, NFs may play a critical role in cognitive functions, as cognitive processes are known to depend on synaptic integrity and are modulated by dopaminergic signaling. Here, we present a theory-driven interdisciplinary approach that NFs may link inflammation, neurodegeneration, and cognitive functions. We base our hypothesis on a wealth of evidence suggesting a causal link between inflammation and neurodegeneration and between these two and cognitive decline (see Fig. 1), also taking dopaminergic signaling into account. We conclude that NFs may not only serve as biomarkers for inflammatory, neurodegenerative, and cognitive processes but also represent a potential mechanical hinge between them, moreover, they may even have predictive power regarding future cognitive decline. In addition, we advocate the use of both NFs and MRI parameters, as their synthesis offers the opportunity to individualize medical treatment by providing a comprehensive view of underlying disease activity in neurological diseases. Since our society will become significantly older in the upcoming years and decades, maintaining cognitive functions and healthy aging will play an important role. Thanks to technological advances in recent decades, NFs could serve as a rapid, noninvasive, and relatively inexpensive early warning system to identify individuals at increased risk for cognitive decline and could facilitate the management of cognitive dysfunctions across the lifespan.

Plasma Concentrations of Neurofilament Light Chain Protein and Brain-Derived Neurotrophic Factor as Consistent Biomarkers of Cognitive Impairment in Alcohol Use Disorder

For a long time, Substance Use Disorders (SUDs) were not considered a component in the etiology of dementia. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders introduced substance-induced neurocognitive disorders, incorporating this notion to clinical practice. However, detection and monitoring of neurodegenerative processes in SUD patients remain a major clinical challenge, especially when early diagnosis is required. In the present study, we aimed to investigate new potential biomarkers of neurodegeneration that could predict cognitive impairment in SUD patients: the circulating concentrations of Neurofilament Light chain protein (NfL) and Brain-Derived Neurotrophic Factor (BDNF). Sixty SUD patients were compared with twenty-seven dementia patients and forty healthy controls. SUD patients were recruited and assessed using the Psychiatric Research Interview for Substance and Mental (PRISM) and a battery of neuropsychological tests, including the Montreal Cognitive Assessment test for evaluation of cognitive impairment. When compared to healthy control subjects, SUD patients showed increases in plasma NfL concentrations and NfL/BDNF ratio, as well as reduced plasma BDNF levels. These changes were remarkable in SUD patients with moderate-severe cognitive impairment, being comparable to those observed in dementia patients. NfL concentrations correlated with executive function and memory cognition in SUD patients. The parameters "age", "NfL/BDNF ratio", "first time alcohol use", "age of onset of alcohol use disorder", and "length of alcohol use disorder diagnosis" were able to stratify our SUD sample into patients with cognitive impairment from those without cognitive dysfunction with great specificity and sensibility. In conclusion, we propose the combined use of NfL and BDNF (NfL/BDNF ratio) to monitor substance-induced neurocognitive disorder.

The 2022 Lady Estelle Wolfson lectureship on neurofilaments

Neurofilament proteins (Nf) have been validated and established as a reliable body fluid biomarker for neurodegenerative pathology. This review covers seven Nf isoforms, Nf light (NfL), two splicing variants of Nf medium (NfM), two splicing variants of Nf heavy (NfH), α -internexin (INA) and peripherin (PRPH). The genetic and epigenetic aspects of Nf are discussed as relevant for neurodegenerative diseases and oncology. The comprehensive list of mutations for all Nf isoforms covers Amyotrophic Lateral Sclerosis, Charcot-Marie Tooth disease, Spinal muscular atrophy, Parkinson Disease and Lewy Body Dementia. Next, emphasis is given to the expanding field of post-translational modifications (PTM) of the Nf amino acid residues. Protein structural aspects are reviewed alongside PTMs causing neurodegenerative pathology and human autoimmunity. Molecular visualisations of NF PTMs, assembly and stoichiometry make use of Alphafold2 modelling. The implications for Nf function on the cellular level and axonal transport are discussed. Neurofilament aggregate formation and proteolytic breakdown are reviewed as relevant for biomarker tests and disease. Likewise, Nf stoichiometry is reviewed with regard to in vitro experiments and as a compensatory mechanism in neurodegeneration. The review of Nf across a spectrum of 87 diseases from all parts of medicine is followed by a critical appraisal of 33 meta-analyses on Nf body fluid levels. The review concludes with considerations for clinical trial design and an outlook for future research.

Plasma tau proteins for the diagnosis of mild cognitive impairment and Alzheimer's disease: A systematic review and meta-analysis

Objective

Detecting plasma tau biomarkers used to be impossible due to their low concentrations in blood samples. Currently, new high-sensitivity assays made it a reality. We performed a systematic review and meta-analysis in order to test the accuracy of plasma tau protein in diagnosing Alzheimer's disease (AD) or mild cognitive impairment (MCI).

Methods

We searched PubMed, Cochrane, Embase and Web of Science databases, and conducted correlation subgroup analysis, sensitivity analysis and publication bias analysis using R Programming Language.

Results

A total of 56 studies were included. Blood t-tau and p-tau levels increased from controls to MCI to AD patients, and showed significant changes in pairwise comparisons of AD, MCI and normal cognition. P-tau217 was more sensitive than p-tau181 and p-tau231 in different cognition periods. In addition, ultrasensitive analytical platforms, immunomagnetic reduction (IMR), increased the diagnostic value of tau proteins, especially the diagnostic value of t-tau.

Conclusion

Both t-tau and p-tau are suitable AD blood biomarkers, and p-tau217 is more sensitive than other tau biomarkers to differentiate MCI and AD. Detection techniques also have an impact on biomarkers' results. New ultrasensitive analytical platforms of IMR increase the diagnostic value of both t-tau and p-tau biomarkers.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, registration number: CRD42021264701.

[Blood Based Biomarker for Optimization of Early and Differential Diagnosis of Alzheimer's Dementia]

AIM

Dementia in Alzheimer´s disease is a global challenge. There is growing evidence that investigating blood biomarkers to diagnose Alzheimer´s disease is a promising fast, minimally invasive, and less costly method. The aim of this study was to review available studies on promising biomarkers for Alzheimer´s disease.

METHOD

The latest studies were collated for this review.

RESULTS

Immunoassays followed by mass spectrometry and immunomagnetic reduction were reported to be highly relevant methods for detecting amyloid-ß 42 (Aß42) and amyloid-ß 40 (Aß40) to calculate the Aß42/Aß40 ratio, thereby improving the early diagnosis of Alzheimer´s disease. Amyloid-ß (Aß) peptides in blood plasma were considered as potential markers, as they correlated with the brain's Aß pathology. Phosphorylated tau protein 181 (p-tau181), phosphorylated tau protein 217 (p-tau217) and phosphorylated tau protein 231 (p-tau231) in blood samples assessed via Simoa technology served as parameters for the early and differential diagnosis of AD, and were markers of tau pathology in the brain. Neurofilament light chain (Nfl) and glial fibrillary acid protein (GFAP) were additional markers possibly facilitating the assessment of axonal and astroglial brain damage in Alzheimer´s disease. GFAP in blood was useful as an additional marker to detect early and to predict the time course of Alzheimer´s disease.

CONCLUSIONS

Determining blood biomarkers represents less invasive and less costly diagnostics for Alzheimer´s disease. The investigation of blood biomarkers such as the Aß42/Aß40 ratio, p-tau217, p-tau231, Nfl and GFAP have been promising in establishing the AT(N) classification for Alzheimer´s disease. High-throughput methods should be evaluated in large patient cohort studies and via meta-analyses of studies. Consensus criteria with standard protocols for measuring these biomarkers while considering ethical issues and Alzheimer´s phenotype should unify normative values from different laboratories. The AT(N) classification of Alzheimer´s disease in blood would be a key element towards the implementation of minimally-invasive precision medicine.

Promising Blood Biomarkers for Clinical Use in Alzheimer's Disease: A Focused Update

Alzheimer’s disease (AD) is the most-common cause of neurodegenerative dementia, and it is characterized by abnormal amyloid and tau accumulation, which indicates neurodegeneration. AD has mostly been diagnosed clinically. However, ligand-specific positron emission tomography (PET) imaging, such as amyloid PET, and cerebrospinal fluid (CSF) biomarkers are needed to accurately diagnose AD, since they supplement the shortcomings of clinical diagnoses. Using biomarkers that represent the pathology of AD is essential (particularly when disease-modifying treatment is available) to identify the corresponding pathology of targeted therapy and for monitoring the treatment response. Although imaging and CSF biomarkers are useful, their widespread use is restricted by their high cost and the discomfort during the lumbar puncture, respectively. Recent advances in AD blood biomarkers shed light on their future use for clinical purposes. The amyloid β (Aβ)42/Aβ40 ratio and the concentrations of phosphorylated tau at threonine 181 and at threonine 217, and of neurofilament light in the blood were found to represent the pathology of Aβ, tau, and neurodegeneration in the brain when using automatic electrochemiluminescence technologies, single-molecule arrays, immunoprecipitation coupled with mass spectrometry, etc. These blood biomarkers are imminently expected to be incorporated into clinical practice to predict, diagnose, and determine the stage of AD. In this review we focus on advancements in the measurement technologies for blood biomarkers and the promising biomarkers that are approaching clinical application. We also discuss the current limitations, the needed further investigations, and the perspectives on their use.

A new generation of AD biomarkers: 2019 to 2021

Alzheimer's disease (AD) is the most common form of dementia and cases are rising worldwide. The effort to fight this disease is hampered by a lack of disease-modifying treatments and the absence of an early, accurate diagnostic tool. Neuropathology begins years or decades before symptoms occur and, upon onset of symptoms, diagnosis can take a year or more. Such delays postpone treatment and make research into the early stages of the disease difficult. Ideally, clinicians require a minimally invasive test that can detect AD in its early stages, before cognitive symptoms occur. Advances in proteomic technologies have facilitated the study of promising biomarkers of AD. Over the last two years (2019-2021) studies have identified and validated many species which can be measured in cerebrospinal fluid (CSF), plasma, or in both fluids, and which have a high predictive value for AD. We herein discuss proteins which have been highlighted as promising biomarkers of AD in the last two years, and consider implications for future research within the research framework of the amyloid (A), tau (T), neurodegeneration (N) scoring system. We review recently identified species of amyloid and tau which may improve diagnosis when used in combination with current measures such as amyloid-beta-42 (Aβ42), total tau (t-tau) and phosphorylated tau (p-tau). In addition, several proteins have been identified as likely proxies for neurodegeneration, including neurofilament light (NfL), synaptosomal-associated protein 25 (SNAP-25) and neurogranin (NRGN). Finally, proteins originating from diverse processes such as neuroinflammation, lipid transport and mitochondrial dysfunction could aid in both AD diagnosis and patient stratification.

Biofluid Biomarkers of Alzheimer’s Disease: Progress, Problems, and Perspectives

Since the establishment of the biomarker-based A-T-N (Amyloid/Tau/Neurodegeneration) framework in Alzheimer’s disease (AD), the diagnosis of AD has become more precise, and cerebrospinal fluid tests and positron emission tomography examinations based on this framework have become widely accepted. However, the A-T-N framework does not encompass the whole spectrum of AD pathologies, and problems with invasiveness and high cost limit the application of the above diagnostic methods aimed at the central nervous system. Therefore, we suggest the addition of an “X” to the A-T-N framework and a focus on peripheral biomarkers in the diagnosis of AD. In this review, we retrospectively describe the recent progress in biomarkers based on the A-T-N-X framework, analyze the problems, and present our perspectives on the diagnosis of AD.

Proteasome activity modulates amyloid toxicity

Alzheimer's disease (AD) is responsible for 60%-80% of identified cases of dementia. While the generation and accumulation of amyloid precursor protein (APP) fragments is accepted as a key step in AD pathogenesis, the precise role of these fragments remains poorly understood. To overcome this deficit, we induced the expression of the soluble C-terminal fragment of APP (C99), the rate-limiting peptide for the generation of amyloid fragments, in yeast that contain thermosensitive mutations in genes encoding proteasome subunits. Our previous work with this system demonstrated that these proteasome-deficient yeast cells, expressing C99 when proteasome activity was blunted, generated amyloid fragments similar to those observed in AD patients. We now report the phenotypic repercussions of inducing C99 expression in proteasome-deficient cells. We show increased levels of protein aggregates, cellular stress and chaperone expression, electron-dense accumulations in the nuclear envelope/ER, abnormal DNA condensation, and an induction of apoptosis. Taken together, these findings suggest that the generation of C99 and its associated fragments in yeast cells with compromised proteasomal activity results in phenotypes that may be relevant to the neuropathological processes observed in AD patients. These data also suggest that this yeast model should be useful for testing therapeutics that target AD-associated amyloid, since it allows for the assessment of the reversal of the perturbed cellular physiology observed when degradation pathways are dysfunctional.

Current research status of blood biomarkers in Alzheimer's disease: Diagnosis and prognosis

Alzheimer's disease (AD), which mainly occurs in the elderly, is a neurodegenerative disease with a hidden onset, which leads to progressive cognitive and behavioral changes. The annually increasing prevalence rate and number of patients with AD exert great pressure on the society. No effective disease-modifying drug treatments are available; thus, there is no cure yet. The disease progression can only be delayed through early detection and drug assistance. Therefore, the importance of exploring associated biomarkers for the early diagnosis and prediction of the disease progress is highlighted. The National Institute on Aging- Alzheimer's Association (NIA-AA) proposed A/T/N diagnostic criteria in 2018, including Aβ42, p-tau, t-tau in cerebrospinal fluid (CSF), and positron emission tomography (PET). However, the invasiveness of lumbar puncture for CSF assessment and non-popularity of PET have prompted researchers to look for minimally invasive, easy to collect, and cost-effective biomarkers. Therefore, studies have largely focused on some novel molecules in the peripheral blood. This is an emerging research field, facing many obstacles and challenges while achieving some promising results.

Secondary Prevention of Dementia: Combining Risk Factors and Scalable Screening Technology

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is the most common cause of dementia. Over a third of dementia cases are estimated to be due to potentially modifiable risk factors, thus offering opportunities for both identification of those most likely to be in early disease as well as secondary prevention. Diabetes, hypertension and chronic kidney failure have all been linked to increased risk for AD and dementia and through their high prevalence are particularly apt targets for initiatives to reduce burden of AD. This can take place through targeted interventions of cardiovascular risk factors (shown to improve cognitive outcomes) or novel disease modifying treatments in people with confirmed AD pathology. The success of this approach to secondary prevention depends on the availability of inexpensive and scalable methods for detecting preclinical and prodromal dementia states. Developments in blood-based biomarkers for Alzheimer's disease are rapidly becoming a viable such method for monitoring large at-risk groups. In addition, digital technologies for remote monitoring of cognitive and behavioral changes can add clinically relevant data to further improve personalisation of prevention strategies. This review sets the scene for this approach to secondary care of dementia through a review of the evidence for cardiovascular risk factors (diabetes, hypertension and chronic kidney disease) as major risk factors for AD. We then summarize the developments in blood-based and cognitive biomarkers that allow the detection of pathological states at the earliest possible stage. We propose that at-risk cohorts should be created based on the interaction between cardiovascular and constitutional risk factors. These cohorts can then be monitored effectively using a combination of blood-based biomarkers and digital technologies. We argue that this strategy allows for both risk factor reduction-based prevention programmes as well as for optimisation of any benefits offered by current and future disease modifying treatment through rapid identification of individuals most likely to benefit from them.

Associations between locus coeruleus integrity and nocturnal awakenings in the context of Alzheimer's disease plasma biomarkers: a 7T MRI study

Background

The brainstem locus coeruleus (LC) constitutes the intersection of the initial pathophysiological processes of Alzheimer’s disease (AD) and sleep-wake dysregulation in the preclinical stages of the disease. However, the interplay between in vivo assessment of LC degeneration and AD-related sleep alterations remains unknown. Here, we sought to investigate whether MRI-assessed LC structural integrity relates to subjective sleep-wake measures in the context of AD plasma biomarkers, in cognitively unimpaired older individuals.

Methods

Seventy-two cognitively unimpaired older individuals aged 50–85 years (mean age = 65.2 ± 8.2 years, 37 women, 21 APOE ε4 carriers) underwent high-resolution imaging of the LC at 7 Tesla, and LC structural integrity was quantified using a data-driven approach. Reports on habitual sleep quality and nocturnal awakenings were collected using sleep questionnaires. Plasma levels of total tau, p-tau₁₈₁, Aβ₄₀, and Aβ₄₂ were measured using single-molecule array technology.

Results

Intensity-based cluster analyses indicated two distinct LC segments, with one covering the middle-to-caudal LC and displaying lower intensity compared to the middle-to-rostral cluster (t₇₀ = −5.12, p < 0.0001). After correction for age, sex, depression, and APOE status, lower MRI signal intensity within the middle-to-caudal LC was associated with a higher number of self-reported nocturnal awakenings (F_1,63 = 6.73, p_FDR = 0.03). Furthermore, this association was mostly evident in individuals with elevated levels of total tau in the plasma (F_1,61 = 4.26, p = 0.04).

Conclusion

Our findings provide in vivo evidence that worse LC structural integrity is associated with more frequent nocturnal awakenings in the context of neurodegeneration, in cognitively unimpaired older individuals. These results support the critical role of the LC for sleep-wake regulation in the preclinical stages of AD and hold promises for the identification of at-risk populations for preventive interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-021-00902-8.

Blood Biomarkers for Alzheimer's Disease in Down Syndrome

Epidemiological evidence suggests that by the age of 40 years, all individuals with Down syndrome (DS) have Alzheimer's disease (AD) neuropathology. Clinical diagnosis of dementia by cognitive assessment is complex in these patients due to the pre-existing and varying intellectual disability, which may mask subtle declines in cognitive functioning. Cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers, although accurate, are expensive, invasive, and particularly challenging in such a vulnerable population. The advances in ultra-sensitive detection methods have highlighted blood biomarkers as a valuable and realistic tool for AD diagnosis. Studies with DS patients have proven the potential blood-based biomarkers for sporadic AD (amyloid-β, tau, phosphorylated tau, and neurofilament light chain) to be useful in this population. In addition, biomarkers related to other pathologies that could aggravate dementia progression-such as inflammatory dysregulation, energetic imbalance, or oxidative stress-have been explored. This review serves to provide a brief overview of the main findings from the limited neuroimaging and CSF studies, outline the current state of blood biomarkers to diagnose AD in patients with DS, discuss possible past limitations of the research, and suggest considerations for developing and validating blood-based biomarkers in the future.

Plasma Proteomic Biomarkers Relating to Alzheimer's Disease: A Meta-Analysis Based on Our Own Studies

Background and Objective: Plasma biomarkers for the diagnosis and stratification of Alzheimer's disease (AD) are intensively sought. However, no plasma markers are well established so far for AD diagnosis. Our group has identified and validated various blood-based proteomic biomarkers relating to AD pathology in multiple cohorts. The study aims to conduct a meta-analysis based on our own studies to systematically assess the diagnostic performance of our previously identified blood biomarkers. Methods: To do this, we included seven studies that our group has conducted during the last decade. These studies used either Luminex xMAP or ELISA to measure proteomic biomarkers. As proteins measured in these studies differed, we selected protein based on the criteria that it must be measured in at least four studies. We then examined biomarker performance using random-effect meta-analyses based on the mean difference between biomarker concentrations in AD and controls (CTL), AD and mild cognitive impairment (MCI), MCI, and CTL as well as MCI converted to dementia (MCIc) and non-converted (MCInc) individuals. Results: An overall of 2,879 subjects were retrieved for meta-analysis including 1,053 CTL, 895 MCI, 882 AD, and 49 frontotemporal dementia (FTD) patients. Six proteins were measured in at least four studies and were chosen for meta-analyses for AD diagnosis. Of them, three proteins had significant difference between AD and controls, among which alpha-2-macroglobulin (A2M) and ficolin-2 (FCN2) increased in AD while fibrinogen gamma chain (FGG) decreased in AD compared to CTL. Furthermore, FGG significantly increased in FTD compared to AD. None of the proteins passed the significance between AD and MCI, or MCI and CTL, or MCIc and MCInc, although complement component 4 (CC4) tended to increase in MCIc individuals compared to MCInc. Conclusions: The results suggest that A2M, FCN2, and FGG are promising biomarkers to discriminate AD patients from controls, which are worthy of further validation.

State-of-the-Art Methods and Emerging Fluid Biomarkers in the Diagnostics of Dementia-A Short Review and Diagnostic Algorithm

The most common neurodegenerative dementias include Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). The correct etiology-based diagnosis is pivotal for clinical management of these diseases as well as for the suitable timing and choosing the accurate disease-modifying therapies when these become available. Enzyme-linked immunosorbent assay (ELISA)-based methods, detecting altered levels of cerebrospinal fluid (CSF) Tau, phosphorylated Tau, and Aβ-42 in AD, allowed the wide use of this set of biomarkers in clinical practice. These analyses demonstrate a high diagnostic accuracy in AD but suffer from a relatively restricted usefulness due to invasiveness and lack of prognostic value. In recent years, the development of novel advanced techniques has offered new state-of-the-art opportunities in biomarker discovery. These include single molecule array technology (SIMOA), a tool for non-invasive analysis of ultra-low levels of central nervous system-derived molecules from biofluids, such as CSF or blood, and real-time quaking (RT-QuIC), developed to analyze misfolded proteins. In the present review, we describe the history of methods used in the fluid biomarker analyses of dementia, discuss specific emerging biomarkers with translational potential for clinical use, and suggest an algorithm for the use of new non-invasive blood biomarkers in clinical practice.

The Diagnostic Value of Exosome-Derived Biomarkers in Alzheimer's Disease and Mild Cognitive Impairment: A Meta-Analysis

Background: Alzheimer's disease (AD) diagnoses once depended on neuropathologic examination. Now, many widely used, validated biomarkers benefits for monitoring of AD neuropathologic changes. Exosome-derived biomarker studies have reported them to be significantly related to AD's early occurrence and development, although the findings are inconclusive. The aim of this meta-analysis was to identify exosome-derived biomarkers for the diagnosis of AD and mild cognitive impairment (MCI).

Methods: PubMed, PubMed Central, Web of Science, Embase, Google Scholar, Cochrane Library, the Chinese National Knowledge Infrastructure (CNKI), and the Chinese Biomedical Literature Database (CBM) were searched for studies assessing the diagnostic value of biomarkers, including data describing the pooled sensitivity (SEN), specificity (SPE), positive diagnostic likelihood ratio (DLR+), negative diagnostic likelihood ratio (DLR–), diagnostic odds ratio (DOR), and area under the curve (AUC). The quality of the included studies was assessed using RevMan 5.3 software. Publication bias was analyzed.

Results: In total, 19 eligible studies, including 3,742 patients, were selected for this meta-analysis. The SEN, SPE, DLR+, DLR–, DOR, and AUC (95% confidence intervals) of exosome-derived biomarkers in the diagnosis of AD or MCI were 0.83 (0.76–0.87), 0.82 (0.77–0.86), 4.53 (3.46–5.93), 0.21 (0.15–0.29), 17.27 (11.41–26.14), and 0.89 (0.86–0.92), respectively. Sub-group analyses revealed that studies based on serum or microRNA (miRNA) analysis, and those of Caucasian populations, AD patients, patient sample size >50, neuron-derived exosomes (NDE) from plasma and p-tau had higher sensitivity, specificity, and AUC values.

Conclusion: Exosome-derived biomarkers have shown potential diagnostic value in AD and MCI, although further research is required for confirmation.