Blood phosphorylated tau 181 as a biomarker for Alzheimer's disease: a diagnostic performance and prediction modelling study using data from four prospective cohorts

A detection model of cognitive impairment via the integrated gait and eye movement analysis from a large Chinese community cohort

INTRODUCTION

Whether the integration of eye-tracking, gait, and corresponding dual-task analysis can distinguish cognitive impairment (CI) patients from controls remains unclear.

METHODS

One thousand four hundred eighty-one participants, including 724 CI and 757 controls, were enrolled in this study. Eye movement and gait, combined with dual-task patterns, were measured. The LightGBM machine learning models were constructed.

RESULTS

A total of 105 gait and eye-tracking features were extracted. Forty-six parameters, including 32 gait and 14 eye-tracking features, showed significant differences between two groups (P < 0.05). Of these, the Gait_3Back-TurnTime and Dual-task cost-TurnTime patterns were significantly correlated with plasma phosphorylated tau 181 (p-tau181) level. A model based on dual-task gait, dual-task smooth pursuit, prosaccade, and anti-saccade achieved the best area under the receiver operating characteristics curve (AUC) of 0.987 for CI detection, while combined with p-tau181, the model discriminated mild cognitive impairment from controls with an AUC of 0.824.

DISCUSSION

Combining dual-task gait and dual-task eye-tracking analysis is feasible for the detection of CI.

HIGHLIGHTS

This is the first study to report the efficiency of integrated parameters of dual-task gait and eye-tracking for cognitive impairment (CI) detection in a large cohort. We identified 46 gait and eye-tracking features associated with CI, and two were correlated to plasma phosphorylated tau 181. We constructed the model based on dual-task gait, smooth pursuit, prosaccade, and anti-saccade, achieving the best area under the curve of 0.987 for CI detection.

Tau in dementia with Lewy bodies

OBJECTIVE

Neurofibrillary tangles are present in a proportion of people with dementia with Lewy bodies and may be associated with worse cognition. Recent advances in biomarkers for Alzheimer's disease include second-generation tau positron emission tomography as well as the detection of phosphorylated tau at threonine 181 (p-tau181) in plasma. This study aimed to investigate tau in people with dementia with Lewy bodies using a second-generation tau positron emission tomography tracer as well as plasma p-tau181.

METHODS

Twenty-seven participants (mean age 74.7 ± 5.5) with clinically diagnosed probable dementia with Lewy bodies underwent comprehensive clinical assessment and positron emission tomography imaging (18F-MK6240 and 18F-NAV4694). Plasma p-tau181 levels were measured using Simoa technology.

RESULTS

Five dementia with Lewy bodies participants (18.5%) had an abnormal tau positron emission tomography (increased tau uptake in the temporal meta-region-of-interest). Higher plasma p-tau181 concentrations correlated with higher tau deposition in the temporal region (ρ = 0.46, 95% confidence interval = [0.10, 0.72]) and classified abnormal tau positron emission tomography in dementia with Lewy bodies with an area under the curve of 0.95 (95% confidence interval = [0.86, 0.99]). Plasma p-tau181 also correlated positively with cortical amyloid-beta binding (ρ = 0.68, 95% confidence interval = [0.40, 0.84]) and classified abnormal amyloid-beta positron emission tomography in dementia with Lewy bodies with an area under the curve of 0.91 (95% confidence interval = [0.79, 0.99]). There was no association found between tau deposition and any of the clinical variables.

CONCLUSIONS

Tau is a common co-pathology in dementia with Lewy bodies. Plasma p-tau181 correlated with abnormal tau and amyloid-beta positron emission tomography and may potentially be used as a marker to identify co-morbid Alzheimer's disease-related pathology in dementia with Lewy bodies. The clinical implications of tau in dementia with Lewy bodies need to be further evaluated in larger longitudinal studies.

Plasma proteomic profiles predict future dementia in healthy adults

The advent of proteomics offers an unprecedented opportunity to predict dementia onset. We examined this in data from 52,645 adults without dementia in the UK Biobank, with 1,417 incident cases and a follow-up time of 14.1 years. Of 1,463 plasma proteins, GFAP, NEFL, GDF15 and LTBP2 consistently associated most with incident all-cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VaD), and ranked high in protein importance ordering. Combining GFAP (or GDF15) with demographics produced desirable predictions for ACD (area under the curve (AUC) = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)). This was also true when predicting over 10-year ACD, AD and VaD. Individuals with higher GFAP levels were 2.32 times more likely to develop dementia. Notably, GFAP and LTBP2 were highly specific for dementia prediction. GFAP and NEFL began to change at least 10 years before dementia diagnosis. Our findings strongly highlight GFAP as an optimal biomarker for dementia prediction, even more than 10 years before the diagnosis, with implications for screening people at high risk for dementia and for early intervention.

Consensus on rapid screening for prodromal Alzheimer's disease in China

Alzheimer's disease (AD) is a common cause of dementia, characterised by cerebral amyloid-β deposition, pathological tau and neurodegeneration. The prodromal stage of AD (pAD) refers to patients with mild cognitive impairment (MCI) and evidence of AD's pathology. At this stage, disease-modifying interventions should be used to prevent the progression to dementia. Given the inherent heterogeneity of MCI, more specific biomarkers are needed to elucidate the underlying AD's pathology. Although the uses of cerebrospinal fluid and positron emission tomography are widely accepted methods for detecting AD's pathology, their clinical applications are limited by their high costs and invasiveness, particularly in low-income areas in China. Therefore, to improve the early detection of Alzheimer's disease (AD) pathology through cost-effective screening methods, a panel of 45 neurologists, psychiatrists and gerontologists was invited to establish a formal consensus on the screening of pAD in China. The supportive evidence and grades of recommendations are based on a systematic literature review and focus group discussion. National meetings were held to allow participants to review, vote and provide their expert opinions to reach a consensus. A majority (two-thirds) decision was used for questions for which consensus could not be reached. Recommended screening methods are presented in this publication, including neuropsychological assessment, peripheral biomarkers and brain imaging. In addition, a general workflow for screening pAD in China is established, which will help clinicians identify individuals at high risk and determine therapeutic targets.

Plasma pTau-217 and N-terminal tau (NTA) enhance sensitivity to identify tau PET positivity in amyloid-β positive individuals

INTRODUCTION

We set out to identify tau PET-positive (A+T+) individuals among amyloid-beta (Aβ) positive participants using plasma biomarkers.

METHODS

In this cross-sectional study we assessed 234 participants across the AD continuum who were evaluated by amyloid PET with [18 F]AZD4694 and tau-PET with [18 F]MK6240 and measured plasma levels of total tau, pTau-181, pTau-217, pTau-231, and N-terminal tau (NTA-tau). We evaluated the performances of plasma biomarkers to predict tau positivity in Aβ+ individuals.

RESULTS

Highest associations with tau positivity in Aβ+ individuals were found for plasma pTau-217 (AUC [CI95% ] = 0.89 [0.82, 0.96]) and NTA-tau (AUC [CI95% ] = 0.88 [0.91, 0.95]). Combining pTau-217 and NTA-tau resulted in the strongest agreement (Cohen's Kappa = 0.74, CI95%  = 0.57/0.90, sensitivity = 92%, specificity = 81%) with PET for classifying tau positivity.

DISCUSSION

The potential for identifying tau accumulation in later Braak stages will be useful for patient stratification and prognostication in treatment trials and in clinical practice.

HIGHLIGHTS

We found that in a cohort without pre-selection pTau-181, pTau-217, and NTA-tau showed the highest association with tau PET positivity. We found that in Aβ+ individuals pTau-217 and NTA-tau showed the highest association with tau PET positivity. Combining pTau-217 and NTA-tau resulted in the strongest agreement with the tau PET-based classification.

Neuropathological and sociodemographic factors associated with the cortical amyloid load in aging and Alzheimer's disease

Alzheimer's disease (AD) is the leading cause of dementia and is characterized by a progressive decline in cognitive abilities. A pathological hallmark of AD is a region-specific accumulation of the amyloid-beta protein (Aβ). Here, we explored the association between regional Aβ deposition, sociodemographic, and local biochemical factors. We quantified the Aβ burden in postmortem cortical samples from parietal (PCx) and temporal (TCx) regions of 27 cognitively unimpaired (CU) and 15 AD donors, aged 78-100 + years. Histological images of Aβ immunohistochemistry and local concentrations of pathological and inflammatory proteins were obtained at the "Aging, Dementia and TBI Study" open database. We used the area fraction fractionator stereological methodology to quantify the Aβ burden in the gray and white matter within each cortical region. We found higher Aβ burdens in the TCx of AD octogenarians compared to CU ones. We also found higher Aβ loads in the PCx of AD nonagenarians than in AD octogenarians. Moreover, AD women exhibited increased Aβ deposition compared to CU women. Interestingly, we observed a negative correlation between education years and Aβ burden in the white matter of both cortices in CU samples. In AD brains, the Aβ40, Aβ42, and pTau181 isoforms of Aβ and Tau proteins were positively correlated with the Aβ burden. Additionally, in the TCx of AD donors, the proinflammatory cytokine TNFα showed a positive correlation with the Aβ load. These novel findings contribute to understanding the interplay between sociodemographic characteristics, local inflammatory signaling, and the development of AD-related pathology in the cerebral cortex.

A multiclass extreme gradient boosting model for evaluation of transcriptomic biomarkers in Alzheimer's disease prediction

BACKGROUND

Patients with young-onset Alzheimer's disease (AD) (before the age of 50 years old) often lack obvious imaging changes and amyloid protein deposition, which can lead to misdiagnosis with other cognitive impairments. Considering the association between immunological dysfunction and progression of neurodegenerative disease, recent research has focused on identifying blood transcriptomic signatures for precise prediction of AD.

METHODS

In this study, we extracted blood biomarkers from large-scale transcriptomics to construct multiclass eXtreme Gradient Boosting models (XGBoost), and evaluated their performance in distinguishing AD from cognitive normal (CN) and mild cognitive impairment (MCI).

RESULTS

Independent testing with external dataset revealed that the combination of blood transcriptomic signatures achieved an area under the receiver operating characteristic curve (AUC of ROC) of 0.81 for multiclass classification (sensitivity = 0.81; specificity = 0.63), 0.83 for classification of AD vs. CN (sensitivity = 0.72; specificity = 0.73), and 0.85 for classification of AD vs. MCI (sensitivity = 0.77; specificity = 0.73). These candidate signatures were significantly enriched in 62 chromosome regions, such as Chr.19p12-19p13.3, Chr.1p22.1-1p31.1, and Chr.1q21.2-1p23.1 (adjusted p < 0.05), and significantly overrepresented by 26 transcription factors, including E2F2, FOXO3, and GATA1 (adjusted p < 0.05). Biological analysis of these signatures pointed to systemic dysregulation of immune responses, hematopoiesis, exocytosis, and neuronal support in neurodegenerative disease (adjusted p < 0.05).

CONCLUSIONS

Blood transcriptomic biomarkers hold great promise in clinical use for the accurate assessment and prediction of AD.

Application of blood-based biomarkers of Alzheimer's disease in clinical practice: Recommendations from Taiwan Dementia Society

Blood-based biomarkers (BBM) are potentially powerful tools that assist in the biological diagnosis of Alzheimer's disease (AD) in vivo with minimal invasiveness, relatively low cost, and good accessibility. This review summarizes current evidence for using BBMs in AD, focusing on amyloid, tau, and biomarkers for neurodegeneration. Blood-based phosphorylated tau and the Aβ42/Aβ40 ratio showed consistent concordance with brain pathology measured by CSF or PET in the research setting. In addition, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are neurodegenerative biomarkers that show the potential to assist in the differential diagnosis of AD. Other pathology-specific biomarkers, such as α-synuclein and TAR DNA-binding protein 43 (TDP-43), can potentially detect AD concurrent pathology. Based on current evidence, the working group from the Taiwan Dementia Society (TDS) achieved consensus recommendations on the appropriate use of BBMs for AD in clinical practice. BBMs may assist clinical diagnosis and prognosis in AD subjects with cognitive symptoms; however, the results should be interpreted by dementia specialists and combining biochemical, neuropsychological, and neuroimaging information. Further studies are needed to evaluate BBMs' real-world performance and potential impact on clinical decision-making.

A nonhuman primate model with Alzheimer's disease-like pathology induced by hippocampal overexpression of human tau

BACKGROUND

Alzheimer's disease (AD) is one of the most burdening diseases of the century with no disease-modifying treatment at this time. Nonhuman primates (NHPs) share genetic, anatomical, and physiological similarities with humans, making them ideal model animals for investigating the pathogenesis of AD and potential therapies. However, the use of NHPs in AD research has been hindered by the paucity of AD monkey models due to their long generation time, ethical considerations, and technical challenges in genetically modifying monkeys.

METHODS

Here, we developed an AD-like NHP model by overexpressing human tau in the bilateral hippocampi of adult rhesus macaque monkeys. We evaluated the pathological features of these monkeys with immunostaining, Nissl staining, cerebrospinal fluid (CSF) analysis, magnetic resonance imaging (MRI), positron emission tomography (PET), and behavioural tests.

RESULTS

We demonstrated that after hippocampal overexpression of tau protein, these monkeys displayed multiple pathological features of AD, including 3-repeat (3R)/4-repeat (4R) tau accumulation, tau hyperphosphorylation, tau propagation, neuronal loss, hippocampal atrophy, neuroinflammation, Aβ clearance deficits, blood vessel damage, and cognitive decline. More interestingly, the accumulation of both 3R and 4R tau is specific to NHPs but not found in adult rodents.

CONCLUSIONS

This work establishes a tau-induced AD-like NHP model with many key pathological and behavioural features of AD. In addition, our model may potentially become one of the AD NHP models adopted by researchers worldwide since it can be generated within 2 ~ 3 months through a single injection of AAVs into the monkey brains. Hence, our model NHPs may facilitate mechanistic studies and therapeutic treatments for AD.

Longitudinal progression of blood biomarkers reveals a key role of astrocyte reactivity in preclinical Alzheimer's disease

Defining the progression of blood biomarkers of Alzheimer's disease (AD) is essential for targeting treatments in patients most likely to benefit from early intervention. We delineated the temporal ordering of blood biomarkers a decade prior to the onset of AD symptoms in participants in the Baltimore Longitudinal Study of Aging. We show that increased astrocyte reactivity, assessed by elevated glial fibrillary acidic protein (GFAP) levels is an early event in the progression of blood biomarker changes in preclinical AD. In AD-converters who are initially cognitively unimpaired (N=158, 377 serial plasma samples), higher plasma GFAP levels are observed as early as 10-years prior to the onset of cognitive impairment due to incident AD compared to individuals who remain cognitively unimpaired (CU, N=160, 379 serial plasma samples). Plasma GFAP levels in AD-converters remain elevated 5-years prior to and coincident with the onset of cognitive impairment due to AD. In participants with neuropathologically confirmed AD, plasma GFAP levels are elevated relative to cognitively normal individuals and intermediate in those who remain cognitively unimpaired despite significant AD pathology (asymptomatic AD). Higher plasma GFAP levels at death are associated with greater severity of both neuritic plaques and neurofibrillary tangles. In the 5XFAD transgenic model of AD, we observed greater GFAP levels in the cortex and hippocampus of transgenic mice relative to wild-type prior to the development of cognitive impairment. Reactive astrocytosis, an established biological response to neuronal injury, may be an early initiator of AD pathogenesis and a promising therapeutic target.

Multi-Omic Blood Biomarkers as Dynamic Risk Predictors in Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease is the leading cause of dementia worldwide, accounting for a growing burden of morbidity and mortality. Diagnosing Alzheimer's disease before symptoms are established is clinically challenging, but would provide therapeutic windows for disease-modifying interventions. Blood biomarkers, including genetics, proteins and metabolites, are emerging as powerful predictors of Alzheimer's disease at various timepoints within the disease course, including at the preclinical stage. In this review, we discuss recent advances in such blood biomarkers for determining disease risk. We highlight how leveraging polygenic risk scores, based on genome-wide association studies, can help stratify individuals along their risk profile. We summarize studies analyzing protein biomarkers, as well as report on recent proteomic- and metabolomic-based prediction models. Finally, we discuss how a combination of multi-omic blood biomarkers can potentially be used in memory clinics for diagnosis and to assess the dynamic risk an individual has for developing Alzheimer's disease dementia.

Definition of a Threshold for the Plasma Aβ42/Aβ40 Ratio Measured by Single-Molecule Array to Predict the Amyloid Status of Individuals without Dementia

Alzheimer's disease (AD) is characterized by amyloid beta (Aβ) plaques and hyperphosphorylated tau in the brain. Aβ plaques precede cognitive impairments and can be detected through amyloid-positron emission tomography (PET) or in cerebrospinal fluid (CSF). Assessing the plasma Aβ42/Aβ40 ratio seems promising for non-invasive and cost-effective detection of brain Aβ accumulation. This approach involves some challenges, including the accuracy of blood-based biomarker measurements and the establishment of clear, standardized thresholds to categorize the risk of developing brain amyloid pathology. Plasma Aβ42/Aβ40 ratio was measured in 277 volunteers without dementia, 70 AD patients and 18 non-AD patients using single-molecule array. Patients (n = 88) and some volunteers (n = 66) were subject to evaluation of amyloid status by CSF Aβ quantification or PET analysis. Thresholds of plasma Aβ42/Aβ40 ratio were determined based on a Gaussian mixture model, a decision tree, and the Youden's index. The 0.0472 threshold, the one with the highest sensitivity, was retained for general population without dementia screening, and the 0.0450 threshold was retained for research and clinical trials recruitment, aiming to minimize the need for CSF or PET analyses to identify amyloid-positive individuals. These findings offer a promising step towards a cost-effective method for identifying individuals at risk of developing AD.

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.

Metabotropic glutamate receptor 5 (mGluR5) is associated with neurodegeneration and amyloid deposition in Alzheimer's disease: A [18F]PSS232 PET/MRI study

BACKGROUND

Metabotropic glutamate receptor 5 (mGluR5) is involved in regulating integrative brain function and synaptic transmission. Aberrant mGluR5 signaling and relevant synaptic failure play a key role in the initial pathophysiological mechanism of Alzheimer's disease (AD). The study aims to investigate the association between mGluR5 availability and AD's biomarkers and cognitive function.

METHODS

We examined 35 individuals with mGluR5 tracer [18F]PSS232 to assess mGluR5 availability, and with [18F]Florbetapir PET to assess global amyloid deposition, and [18F]FDG PET to assess glucose metabolism. The plasma neurofilament light (NfL) and p-tau181 levels in a subset of individuals were measured (n = 27). The difference in mGluR5 availability between the AD and normal control (NC) groups was explored. The associations of mGluR5 availability with amyloid deposition, glucose metabolism, gray matter volume (GMV), neuropsychological assessment scores, and plasma biomarkers were analyzed.

RESULTS

The mGluR5 availability was significantly reduced in AD patients' hippocampus and parahippocampal gyrus compared to NCs. Global amyloid deposition was positively associated with mGluR5 availability in the AD group and reversely associated in the NC group. The mGluR5 availability was positively correlated with regional glucose metabolism in the overall and stratified analyses. The availability of mGluR5 in the hippocampus and parahippocampal gyrus demonstrated a strong relationship with the GMV of the medial temporal lobe, plasma p-tau181 or NfL levels, and global cognitive performance.

CONCLUSIONS

[18F]PSS232 PET can quantify the changes of mGluR5 availability in the progression of AD. mGluR5 availability correlated not only with neuropathological biomarkers of AD but also with neurodegenerative biomarkers and cognitive performance. mGluR5 may be a novel neurodegenerative biomarker, and whether mGluR5 could be a potential therapeutic target for AD needs to be further studied.

Blood Biomarkers of Alzheimer's Disease and Cognition: A Literature Review

Recent advances in blood-based biomarkers of Alzheimer's Disease (AD) show great promise for clinical applications, offering a less invasive alternative to current cerebrospinal fluid (CSF) measures. However, the relationships between these biomarkers and specific cognitive functions, as well as their utility in predicting longitudinal cognitive decline, are not yet fully understood. This descriptive review surveys the literature from 2018 to 2023, focusing on the associations of amyloid-β (Aβ), Total Tau (t-Tau), Phosphorylated Tau (p-Tau), Neurofilament Light (NfL), and Glial Fibrillary Acidic Protein (GFAP) with cognitive measures. The reviewed studies are heterogeneous, varying in design and population (cognitively unimpaired, cognitively impaired, or mixed populations), and show results that are sometimes conflicting. Generally, cognition positively correlates with Aβ levels, especially when evaluated through the Aβ42/Aβ40 ratio. In contrast, t-Tau, p-Tau, Nfl, and GFAP levels typically show a negative correlation with cognitive performance. While p-Tau measures generally exhibit stronger associations with cognitive functions compared to other biomarkers, no single blood marker has emerged as being predominantly linked to a specific cognitive domain. These findings contribute to our understanding of the complex relationship between blood biomarkers and cognitive performance and underscore their potential utility in clinical assessments of cognition.

Post-translational modification and mitochondrial function in Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease with currently no cure. Most PD cases are sporadic, and about 5-10% of PD cases present a monogenic inheritance pattern. Mutations in more than 20 genes are associated with genetic forms of PD. Mitochondrial dysfunction is considered a prominent player in PD pathogenesis. Post-translational modifications (PTMs) allow rapid switching of protein functions and therefore impact various cellular functions including those related to mitochondria. Among the PD-associated genes, Parkin, PINK1, and LRRK2 encode enzymes that directly involved in catalyzing PTM modifications of target proteins, while others like α-synuclein, FBXO7, HTRA2, VPS35, CHCHD2, and DJ-1, undergo substantial PTM modification, subsequently altering mitochondrial functions. Here, we summarize recent findings on major PTMs associated with PD-related proteins, as enzymes or substrates, that are shown to regulate important mitochondrial functions and discuss their involvement in PD pathogenesis. We will further highlight the significance of PTM-regulated mitochondrial functions in understanding PD etiology. Furthermore, we emphasize the potential for developing important biomarkers for PD through extensive research into PTMs.

Differential diagnosis of mild cognitive impairment of Alzheimer's disease by Simoa p-tau181 measurements with matching plasma and CSF

Alzheimer's disease (AD) is characterized by a long preclinical phase. Although late-stage AD/dementia may be robustly differentiated from cognitively normal individuals by means of a clinical evaluation, PET imaging, and established biofluid biomarkers, disease differentiation between cognitively normal and various subtypes of mild cognitive impairment (MCI) remains a challenging task. Differential biomarkers for early-stage AD diagnosis with accessible biofluid samples are urgently needed. Misfolded phosphorylated tau aggregates (p-tau) are present in multiple neurodegenerative diseases known as "tauopathies", with the most common being AD. P-tau181 is a well-established p-tau biomarker to differentiate AD dementia from non-AD pathology. However, it is unclear if p-tau181 is capable of diagnosing MCI, an early AD stage, from cognitively normal subjects, or if it can discriminate MCI subtypes amnestic MCI (aMCI) from non-amnestic MCI (naMCI). Here we evaluated the capability of p-tau181 in diagnosing MCI from cognitively normal subjects and discriminating aMCI from naMCI subtypes. We collected matching plasma and CSF samples of a clinically diagnosed cohort of 35 cognitively normal, 34 aMCI, 17 naMCI, and 31 AD dementia cases (total 117 participants) with supplemental CSF Aβ42 and total tau AD biomarker levels and performed Simoa p-tau181 assays. The diagnostic capabilities of Simoa p-tau181 assays to differentiate these cohorts were evaluated. We found (i) p-tau181 can robustly differentiate MCI or aMCI from cognitively normal cohorts with matching plasma and CSF samples, but such differentiation is weaker in diagnosing naMCI from cognitively normal groups, (ii) p-tau181 is not capable of differentiating aMCI from naMCI cohorts, and (iii) either factor of Aβ or total tau burden markedly improved differentiation power to diagnose aMCI from cognitively normal group. Plasma and CSF p-tau181 levels may serve as a promising biomarker for diagnosing aMCI from normal controls in the preclinical phase. But more robust new biomarkers are needed to differentiate naMCI from cognitively normal cases or to discriminate between MCI subtypes, aMCI from naMCI.

African Ancestry Individuals with Higher Educational Attainment Are Resilient to Alzheimer's Disease Measured by pTau181

Background

Cognitive and functional abilities in individuals with Alzheimer's disease (AD) pathology (ADP) are highly variable. Factors contributing to this variability are not well understood. Previous research indicates that higher educational attainment (EA) correlates with reduced cognitive impairments among those with ADP. While cognitive and functional impairments are correlated, they are distinguishable in their manifestations.

Objective

To investigate whether levels of education are associated with functional impairments among those with ADP.

Methods

This research involved 410 African American (AA) individuals (Institutional Review Boards 20070307, 01/27/2023) to ascertain whether EA correlates with functional resilience and if this effect varies between APOE ɛ4 carriers and non-carriers. Utilizing EA as a cognitive reserve proxy, CDR-FUNC as a functional difficulties measure, and blood pTau181 as an ADP proxy, the non-parametric Mann-Whitney U test assessed the relationship between EA and CDR-FUNC in individuals with advanced pTau181 levels.

Results

The results showed that EA correlated with functional difficulties in AA individuals with high levels of pTau181, such that individuals with high EA are more likely to have better functional ability compared to those with lower EA (W = 730.5, p = 0.0007). Additionally, we found that the effect of high EA on functional resilience was stronger in ɛ4 non-carriers compared to ɛ4 carriers (W = 555.5, p = 0.022).

Conclusion

This study extends the role of cognitive reserve and EA to functional performance showing that cognitive reserve influences the association between ADP burden and functional difficulties. Interestingly, this protective effect seems less pronounced in carriers of the strong genetic risk allele ɛ4.

The Clinical Aspects of COVID and Alzheimer's Disease: A Round-Up of Where Things Stand and Are Headed

 The link between long COVID-19 and brain/cognitive impairments is concerning and may foster a worrisome worldwide emergence of novel cases of neurodegenerative diseases with aging. This review aims to update the knowledge, crosstalk, and possible intersections between the Post-COVID Syndrome (PCS) and Alzheimer's disease (AD). References included in this review were obtained from PubMed searches conducted between October 2023 and November 2023. PCS is a very heterogenous and poorly understood disease with recent evidence of a possible association with chronic diseases such as AD. However, more scientific data is required to establish the link between PCS and AD.

Plasma Phosphorylated Tau 231 Increases at One-Year Intervals in Cognitively Unimpaired Subjects

Background

Plasma biomarkers of Alzheimer's disease (AD) constitute a non-invasive tool for diagnosing and classifying subjects. They change even in preclinical stages, but it is necessary to understand their properties so they can be helpful in a clinical context.

Objective

With this work we want to study the evolution of p-tau231 plasma levels in the preclinical stages of AD and its relationship with both cognitive and imaging parameters.

Methods

We evaluated plasma phosphorylated (p)-tau231 levels in 146 cognitively unimpaired subjects in sequential visits. We performed a Linear Mixed-effects Model to analyze their rate of change. We also correlated their baseline levels with cognitive tests and structural and functional image values. ATN status was defined based on cerebrospinal fluid biomarkers.

Results

Plasma p-tau231 showed a significant rate of change over time. It correlated negatively with memory tests only in amyloid-positive subjects. No significant correlations were found with any imaging measures.

Conclusions

Increases in plasma p-tau231 can be detected at one-year intervals in cognitively healthy subjects. It could constitute a sensitive marker for detecting early signs of neuronal network impairment by amyloid.

Plasma pTau181 Predicts Clinical Progression in a Phase 2 Randomized Controlled Trial of the 11β-HSD1 Inhibitor Xanamem® for Mild Alzheimer's Disease

Background

Blood biomarkers are proposed as a diagnostic alternative to amyloid PET or cerebrospinal fluid (CSF) analyses for the diagnosis of Alzheimer's disease (AD). Relatively little is known of the natural history of patients identified by different blood biomarkers.

Objective

To identify patients with elevated plasma phosphorylated tau (pTau)181 from a prior Phase 2a trial, and explore the natural histories of their clinical progression, and potential efficacy of Xanamem, a selective inhibitor of 11beta-hydroxysteroid dehydrogenase type 1 (11β-HSD1) in these patients.

Methods

A prespecified, double-blind analysis was conducted in 72 participants with clinically diagnosed AD and available plasma samples from baseline and Week 12 of the "XanADu" Phase 2a trial of Xanamem versus placebo. The analysis prespecified plasma pTau181 > median to identify patients more likely to have AD ("H", > 6.74 pg/mL, n = 34). Cohen's d (d) of≥0.2 defined potential clinical significance.

Results

In the placebo group, H patients showed greater clinical progression compared to L patients (pTau181≤median) on ADCOMS (d = 0.55, p < 0.001), CDR-SB (d = 0.63, p < 0.001), MMSE (d = 0.52, p = 0.12), and ADAS-Cog14 (d = 0.53, p = 0.19). In H patients, a potentially clinically meaningful Xanamem treatment effect compared to placebo was seen in the CDR-SB (LS mean difference 0.6 units, d = 0.41, p = 0.09) and Neuropsychological Test Battery (NTB; LS mean difference 1.8 units, d = 0.26, p = 0.48) but not ADCOMS or ADAS-Cog14.

Conclusions

This trial demonstrates that elevated plasma pTau181 identifies participants more likely to have progressive AD and is a suitable method for enrichment in AD clinical trials. Xanamem treatment showed evidence of potential clinically meaningful benefits.

Aqueous and Plasma Levels of Phosphorylated Tau 181 in Individuals with Normal Cognition

Background

Plasma and cerebrospinal fluid (CSF) levels of p-tau181 have been associated with Alzheimer's disease (AD). The retina and vitreous have shown measurable quantities of phosphorylated tau 181 (p-tau181). The aqueous humor, which can be collected during cataract surgery, may have measurable concentrations of p-tau181.

Objective

To determine whether p-tau181 is detectable in the aqueous humor and if so, whether it is associated with other measures that might be consistent with AD such as higher plasma p-tau181 concentration and lower Montreal Cognitive Assessment (MoCA-BLIND version 7.1) score.

Methods

Aqueous humor samples, blood samples, and MoCA-BLIND scores were collected from patients who did not carry a clinical diagnosis of cognitive impairment at the time of cataract surgery. Aqueous p-tau181 concentrations and plasma p-tau181 concentrations were then measured using ultra-sensitive single-molecule assay ELISA technology. A rank-transformed mixed-effects multivariate regression model was used to determine associations between aqueous concentrations, plasma concentrations, and MoCA-BLIND scores.

Results

16 eyes of 16 participants were enrolled with an average age of 71.6. Average MoCA-BLIND score was 20.6/22, average aqueous p-tau181 concentration was 6.4 pg/mL, and average plasma p-tau181 concentration was 3.1 pg/mL. Higher plasma p-tau181 was significantly associated with higher aqueous p-tau181 (p = 0.02). Aqueous p-tau181 and plasma p-tau181 were negatively associated with MoCA-BLIND scores (p = 0.005 and p = 0.001 respectively) in these patients.

Conclusions

Aqueous p-tau181 is positively correlated with plasma p-tau181 and is negatively correlated with MoCA-BLIND scores. Further study in individuals with mild cognitive impairment or AD characterized by cerebrospinal fluid and volumetric MRI metrics may yield further insights.

Plasma Insulin Predicts Early Amyloid-β Pathology Changes in Alzheimer's Disease

Background

Evidence suggests that type 2 diabetes (T2D) is an independent risk factor for Alzheimer's disease (AD), sharing similar pathophysiological traits like impaired insulin signaling.

Objective

To test the association between plasma insulin and cerebrospinal fluid (CSF) AD pathology.

Methods

A total of 304 participants were included in the Alzheimer's Disease Neuroimaging Initiative, assessing plasma insulin and CSF AD pathology. We explored the cross-sectional and longitudinal associations between plasma insulin and AD pathology and compared their associations across different AD clinical and pathological stages.

Results

In the non-demented group, amyloid-β (Aβ)+ participants (e.g., as reflected by CSF Aβ42) exhibited significantly lower plasma insulin levels compared to non-demented Aβ-participants (p < 0.001). This reduction in plasma insulin was more evident in the A+T+ group (as shown by CSF Aβ42 and pTau181 levels) when compared to the A-T- group within the non-dementia group (p = 0.002). Additionally, higher plasma insulin levels were consistently associated with more normal CSF Aβ42 levels (p < 0.001) across all participants. This association was particularly significant in the Aβ-group (p = 0.002) and among non-demented individuals (p < 0.001). Notably, baseline plasma insulin was significantly correlated with longitudinal changes in CSF Aβ42 (p = 0.006), whereas baseline CSF Aβ42 did not show a similar correlation with changes in plasma insulin over time.

Conclusions

These findings suggest an association between plasma insulin and early Aβ pathology in the early stages of AD, indicating that plasma insulin may be a potential predictor of changes in early Aβ pathology.

Plasma Alzheimer's biomarkers and brain amyloid in Hispanic and non-Hispanic older adults

INTRODUCTION

Alzheimer's disease studies often lack ethnic diversity.

METHODS

We evaluated associations between plasma biomarkers commonly studied in Alzheimer's (p-tau181, GFAP, and NfL), clinical diagnosis (clinically normal, amnestic MCI, amnestic dementia, or non-amnestic MCI/dementia), and Aβ-PET in Hispanic and non-Hispanic older adults. Hispanics were predominantly of Cuban or South American ancestry.

RESULTS

Three-hundred seventy nine participants underwent blood draw (71.9 ± 7.8 years old, 60.2% female, 57% Hispanic of which 88% were Cuban or South American) and 240 completed Aβ-PET. P-tau181 was higher in amnestic MCI (p = 0.004, d = 0.53) and dementia (p < 0.001, d = 0.97) than in clinically normal participants and discriminated Aβ-PET[+] and Aβ-PET[-] (AUC = 0.86). P-tau181 outperformed GFAP and NfL. There were no significant interactions with ethnicity. Among amnestic MCI, Hispanics had lower odds of elevated p-tau181 than non-Hispanic (OR = 0.41, p = 0.006).

DISCUSSION

Plasma p-tau181 informs etiological diagnosis of cognitively impaired Hispanic and non-Hispanic older adults. Hispanic ethnicity may relate to greater likelihood of non-Alzheimer's contributions to memory loss.

HIGHLIGHTS

Alzheimer's biomarkers were measured in Hispanic and non-Hispanic older adults. Plasma p-tau181 related to amnestic cognitive decline and brain amyloid burden. AD biomarker associations did not differ between Hispanic and non-Hispanic ethnicity. Hispanic individuals may be more likely to have non-Alzheimer causes of memory loss.

Day-to-day sleep variability with Alzheimer's biomarkers in at-risk elderly

INTRODUCTION

Measuring day-to-day sleep variability might reveal unstable sleep-wake cycles reflecting neurodegenerative processes. We evaluated the association between Alzheimer's disease (AD) fluid biomarkers with day-to-day sleep variability.

METHODS

In the PREVENT-AD cohort, 203 dementia-free participants (age: 68.3 ± 5.4; 78 males) with a parental history of sporadic AD were tested with actigraphy and fluid biomarkers. Day-to-day variability (standard deviations over a week) was assessed for sleep midpoint, duration, efficiency, and nighttime activity count.

RESULTS

Lower cerebrospinal fluid (CSF) ApoE, higher CSF p-tau181/amyloid-β (Aβ)42, and higher plasma p-tau231/Aβ42 were associated with higher variability of sleep midpoint, sleep duration, and/or activity count. The associations between fluid biomarkers with greater sleep duration variability were especially observed in those that carried the APOE4 allele, mild cognitive impairment converters, or those with gray matter atrophy.

DISCUSSION

Day-to-day sleep variability were associated with biomarkers of AD in at-risk individuals, suggesting that unstable sleep promotes neurodegeneration or, conversely, that AD neuropathology disrupts sleep-wake cycles.

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration

INTRODUCTION

Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification.

MATERIALS AND METHODS

We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition.

RESULTS

CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration.

DISCUSSION

These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation.

HIGHLIGHTS

Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.

Plasma Biomarkers as Predictors of Progression to Dementia in Individuals with Mild Cognitive Impairment

Background

Blood-based biomarkers (BBMs) are of growing interest in the field of Alzheimer's disease (AD) and related dementias.

Objective

This study aimed to assess the ability of plasma biomarkers to 1) predict disease progression from mild cognitive impairment (MCI) to dementia and 2) improve the predictive ability of magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) measures when combined.

Methods

We used data from the Alzheimer's Disease Neuroimaging Initiative. Machine learning models were trained using the data from participants who remained cognitively stable (CN-s) and with Dementia diagnosis at 2-year follow-up visit. The models were used to predict progression to dementia in MCI individuals. We assessed the performance of models with plasma biomarkers against those with CSF and MRI measures, and also in combination with them.

Results

Our models with plasma biomarkers classified CN-s individuals from AD with an AUC of 0.75±0.03 and could predict conversion to dementia in MCI individuals with an AUC of 0.64±0.03 (17.1% BP, base prevalence). Models with plasma biomarkers performed better when combined with CSF and MRI measures (CN versus AD: AUC of 0.89±0.02; MCI-to-AD: AUC of 0.76±0.03, 21.5% BP).

Conclusions

Our results highlight the potential of plasma biomarkers in predicting conversion to dementia in MCI individuals. While plasma biomarkers could improve the predictive ability of CSF and MRI measures when combined, they also show the potential to predict non-progression to AD when considered alone. The predictive ability of plasma biomarkers is crucially linked to reducing the costly and effortful collection of CSF and MRI measures.

Machine Learning-Derived MRI-Based Neurodegeneration Biomarker for Alzheimer's Disease: A Multi-Database Validation Study

BACKGROUND

Pilot study showed that Alzheimer's disease resemblance atrophy index (AD-RAI), a machine learning-derived MRI-based neurodegeneration biomarker of AD, achieved excellent diagnostic performance in diagnosing AD with moderate to severe dementia.

OBJECTIVE

The primary objective was to validate and compare the performance of AD-RAI with conventional volumetric hippocampal measures in diagnosing AD with mild dementia. The secondary objectives were 1) to investigate the association between imaging biomarkers with age and gender among cognitively unimpaired (CU) participants; 2) to analyze whether the performance of differentiating AD with mild dementia from CU will improve after adjustment for age/gender.

METHODS

AD with mild dementia (n = 218) and CU (n = 1,060) participants from 4 databases were included. We investigated the area under curve (AUC), sensitivity, specificity, and balanced accuracy of AD-RAI, hippocampal volume (HV), and hippocampal fraction (HF) in differentiating between AD and CU participants. Among amyloid-negative CU participants, we further analyzed correlation between the biomarkers with age/gender. We also investigated whether adjustment for age/gender will affect performance.

RESULTS

The AUC of AD-RAI (0.93) was significantly higher than that of HV (0.89) and HF (0.89). Subgroup analysis among A + AD and A- CU showed that AUC of AD-RAI (0.97) was also higher than HV (0.94) and HF (0.93). Diagnostic performance of AD-RAI and HF was not affected by age/gender while that of HV improved after age adjustment.

CONCLUSIONS

AD-RAI achieves excellent clinical validity and outperforms conventional volumetric hippocampal measures in aiding the diagnosis of AD mild dementia without the need for age adjustment.

Predicting neurodegeneration from sleep related biofluid changes

Sleep-wake disturbances are common in neurodegenerative diseases and may occur years before the clinical diagnosis, potentially either representing an early stage of the disease itself or acting as a pathophysiological driver. Therefore, discovering biomarkers that identify individuals with sleep-wake disturbances who are at risk of developing neurodegenerative diseases will allow early diagnosis and intervention. Given the association between sleep and neurodegeneration, the most frequently analyzed fluid biomarkers in people with sleep-wake disturbances to date include those directly associated with neurodegeneration itself, such as neurofilament light chain, phosphorylated tau, amyloid-beta and alpha-synuclein. Abnormalities in these biomarkers in patients with sleep-wake disturbances are considered as evidence of an underlying neurodegenerative process. Levels of hormonal sleep-related biomarkers such as melatonin, cortisol and orexin are often abnormal in patients with clinical neurodegenerative diseases, but their relationships with the more standard neurodegenerative biomarkers remain unclear. Similarly, it is unclear whether other chronobiological/circadian biomarkers, such as disrupted clock gene expression, are causal factors or a consequence of neurodegeneration. Current data would suggest that a combination of fluid biomarkers may identify sleep-wake disturbances that are most predictive for the risk of developing neurodegenerative disease with more optimal sensitivity and specificity.

The Associations of Phosphorylated Tau 181 and Tau 231 Levels in Plasma and Cerebrospinal Fluid with Cognitive Function in Alzheimer's Disease: A Systematic Review and Meta-Analysis

Background

Cerebrospinal fluid (CSF) or blood biomarkers like phosphorylated tau proteins (p-tau) are used to detect Alzheimer's disease (AD) early. Increasing studies on cognitive function and blood or CSF p-tau levels are controversial.

Objective

Our study examined the potential of p-tau as a biomarker of cognitive status in normal control (NC), mild cognitive impairment (MCI), and AD patients.

Methods

We searched PubMed, Cochrane, Embase, and Web of Science for relevant material through 12 January 2023. 5,017 participants from 20 studies-1,033 AD, 2,077 MCI, and 1,907 NC-were evaluated. Quantitative analysis provided continuous outcomes as SMDs with 95% CIs. Begg tested publication bias.

Results

MCI patients had lower CSF p-tau181 levels than AD patients (SMD =-0.60, 95% CI (-0.85, -0.36)) but higher than healthy controls (SMD = 0.67). AD/MCI patients had greater plasma p-tau181 levels than healthy people (SMD =-0.73, 95% CI (-1.04, -0.43)). MCI patients had significantly lower p-tau231 levels than AD patients in plasma and CSF (SMD =-0.90, 95% CI (-0.82, -0.45)). MCI patients showed greater CSF and plasma p-tau231 than healthy controls (SMD = 1.34, 95% CI (0.89, 1.79) and 0.43, (0.23, 0.64)). Plasma p-tau181/231 levels also distinguished the three categories. MCI patients had higher levels than healthy people, while AD patients had higher levels than MCI patients.

Conclusions

CSF p-tau181 and p-tau231 biomarkers distinguished AD, MCI, and healthy populations. Plasma-based p-tau181 and p-tau231 biomarkers for AD and MCI need further study.

Optimized Pre-analytical Handling Protocol for Blood-Based Biomarkers of Alzheimer's Disease

The therapeutic management of patients with Alzheimer's disease (AD) has been hindered by poor diagnostic accuracy. As such, there is an unmet clinical need for tools that can detect and diagnose the disease in its early stages. Compared with cerebrospinal fluid (CSF)-based biomarkers or positron emission tomography (PET), the use of reliable blood-based biomarkers could offer an accessible and minimally invasive method of streamlining diagnosis in the clinical setting. However, the influence of pre-analytical processing and sample handling parameters on the accurate measurement of protein biomarkers is well established, especially for AD CSF-based biomarkers. In this chapter, we provide recommendations for an optimal sample handling protocol for the analysis of blood-based biomarkers specifically for amyloid pathology in AD.

Plasma Biomarker Strategy for Selecting Patients With Alzheimer Disease for Antiamyloid Immunotherapies

Importance

Antiamyloid immunotherapies against Alzheimer disease (AD) are emerging. Scalable, cost-effective tools will be needed to identify amyloid β (Aβ)-positive patients without an advanced stage of tau pathology who are most likely to benefit from these therapies. Blood-based biomarkers might reduce the need to use cerebrospinal fluid (CSF) or positron emission tomography (PET) for this.

Objective

To evaluate plasma biomarkers for identifying Aβ positivity and stage of tau accumulation.

Design, Setting, and Participants

The cohort study (BioFINDER-2) was a prospective memory-clinic and population-based study. Participants with cognitive concerns were recruited from 2017 to 2022 and divided into a training set (80% of the data) and test set (20%).

Exposure

Baseline values for plasma phosphorylated tau 181 (p-tau181), p-tau217, p-tau231, N-terminal tau, glial fibrillary acidic protein, and neurofilament light chain.

Main Outcomes and Measures

Performance to classify participants by Aβ status (defined by Aβ-PET or CSF Aβ42/40) and tau status (tau PET). Number of hypothetically saved PET scans in a plasma biomarker-guided workflow.

Results

Of a total 912 participants, there were 499 males (54.7%) and 413 females (45.3%), and the mean (SD) age was 71.1 (8.49) years. Among the biomarkers, plasma p-tau217 was most strongly associated with Aβ positivity (test-set area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI, 0.90-0.97). A 2-cut-point procedure was evaluated, where only participants with ambiguous plasma p-tau217 values (17.1% of the participants in the test set) underwent CSF or PET to assign definitive Aβ status. This procedure had an overall sensitivity of 0.94 (95% CI, 0.90-0.98) and a specificity of 0.86 (95% CI, 0.77-0.95). Next, plasma biomarkers were used to differentiate low-intermediate vs high tau-PET load among Aβ-positive participants. Plasma p-tau217 again performed best, with the test AUC = 0.92 (95% CI, 0.86-0.97), without significant improvement when adding any of the other plasma biomarkers. At a false-negative rate less than 10%, the use of plasma p-tau217 could avoid 56.9% of tau-PET scans needed to identify high tau PET among Aβ-positive participants. The results were validated in an independent cohort (n = 118).

Conclusions and Relevance

This study found that algorithms using plasma p-tau217 can accurately identify most Aβ-positive individuals, including those likely to have a high tau load who would require confirmatory tau-PET imaging. Plasma p-tau217 measurements may substantially reduce the number of invasive and costly confirmatory tests required to identify individuals who would likely benefit from antiamyloid therapies.

Cell-free RNA signatures predict Alzheimer's disease

There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases.

Diagnostic performance of plasma pTau 217, pTau 181, Aβ 1-42 and Aβ 1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease

BACKGROUND

Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown.

METHODS

We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A+) or negative (A-) according to CSF Aβ1-42/Aβ1-40 ratio. Plasma pTau217, pTau181, Aβ1-42 and Aβ1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aβ1-42/Aβ1-40 ratio. We analyzed the potential of pTau217 to predict amyloidosis in CSF.

RESULTS

Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aβ1-42/Aβ1-40 ratio was lower in A + compared to A-. pTau181 and the Aβ1-42/Aβ1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aβ1-42/Aβ1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (x4.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%.

CONCLUSION

The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

Mechanisms behind changes of neurodegeneration biomarkers in plasma induced by sleep deprivation

Acute sleep deprivation has been shown to affect cerebrospinal fluid and plasma concentrations of biomarkers associated with neurodegeneration, though the mechanistic underpinnings remain unknown. This study compared individuals who, for one night, were either subject to total sleep deprivation or free sleep, (i) examining plasma concentrations of neurodegeneration biomarkers the morning after sleep deprivation or free sleep and (ii) determining how overnight changes in biomarkers plasma concentrations correlate with indices of meningeal lymphatic and glymphatic clearance functions. Plasma concentrations of amyloid-β 40 and 42, phosphorylated tau peptide 181, glial fibrillary acid protein and neurofilament light were measured longitudinally in subjects who from Day 1 to Day 2 either underwent total sleep deprivation (n = 7) or were allowed free sleep (n = 21). The magnetic resonance imaging contrast agent gadobutrol was injected intrathecally, serving as a cerebrospinal fluid tracer. Population pharmacokinetic model parameters of gadobutrol cerebrospinal fluid-to-blood clearance were utilized as a proxy of meningeal lymphatic clearance capacity and intrathecal contrast-enhanced magnetic resonance imaging as a proxy of glymphatic function. After one night of acute sleep deprivation, the plasma concentrations of amyloid-β 40 and 42 were reduced, but not the ratio, and concentrations of the other biomarkers were unchanged. The overnight change in amyloid-β 40 and 42 plasma concentrations in the sleep group correlated significantly with indices of meningeal lymphatic clearance capacity, while this was not seen for the other neurodegeneration biomarkers. However, overnight change in plasma concentrations of amyloid-β 40 and 42 did not correlate with the glymphatic marker. On the other hand, the overnight change in plasma concentration of phosphorylated tau peptide 181 correlated significantly with the marker of glymphatic function in the sleep deprivation group but not in the sleep group. The present data add to the evidence of the role of sleep and sleep deprivation on plasma neurodegeneration concentrations; however, the various neurodegeneration biomarkers respond differently with different mechanisms behind sleep-induced alterations in amyloid-β and tau plasma concentrations. Clearance capacity of meningeal lymphatics seems more important for sleep-induced changes in amyloid-β 40 and 42 plasma concentrations, while glymphatic function seems most important for change in plasma concentration of phosphorylated tau peptide 181 during sleep deprivation. Altogether, the present data highlight diverse mechanisms behind sleep-induced effects on concentrations of plasma neurodegeneration biomarkers.

Effects of Neighboring Phosphorylation Events on the Affinities of pT181-Tau Antibodies

A tau variant phosphorylated on threonine 181 (pT181-tau) has been widely investigated as a potential Alzheimer's disease (AD) biomarker in cerebrospinal fluid (CSF) and blood. pT181-tau is present in neurofibrillary tangles (NFTs) of AD brains, and CSF levels of pT181-tau correlate with the overall NFT burden. Various immunobased analytical methods, including Western blotting and ELISA, have been used to quantify pT181-tau in human biofluids. The reliability of these methods is dependent on the affinity and binding specificity of the antibodies used to measure pT181-tau levels. Although both of these properties could, in principle, be affected by phosphorylation within or near the antibody's cognate antigen, such effects have not been extensively studied. Here, we developed a biolayer interferometry assay to determine the degree to which the affinity of pT181-tau antibodies is altered by the phosphorylation of serine or threonine residues near the target epitope. Our results revealed that phosphorylation near T181 negatively affected the binding of pT181-tau antibodies to their cognate antigen to varying degrees. In particular, two of three antibodies tested showed a complete loss of affinity for the pT181 target when S184 or S185 was phosphorylated. These findings highlight the importance of selecting antibodies that have been thoroughly characterized in terms of affinity and binding specificity, addressing the potential disruptive effects of post-translational modifications in the epitope region to ensure accurate biomarker quantitation.

Plasma p-tau212: antemortem diagnostic performance and prediction of autopsy verification of Alzheimer's disease neuropathology

Blood phosphorylated tau (p-tau) biomarkers, including p-tau217, show high associations with Alzheimer's disease (AD) neuropathologic change and clinical stage. Certain plasma p-tau217 assays recognize tau forms phosphorylated additionally at threonine-212, but the contribution of p-tau212 alone to AD is unknown. We developed a blood-based immunoassay that is specific to p-tau212 without cross-reactivity to p-tau217. Thereafter, we examined the diagnostic utility of plasma p-tau212. In five cohorts (n=388 participants), plasma p-tau212 showed high performances for AD diagnosis and for the detection of both amyloid and tau pathology, including at autopsy as well as in memory clinic populations. The diagnostic accuracy and fold changes of plasma p-tau212 were similar to those for p-tau217 but higher than p-tau181 and p-tau231. Immunofluorescent staining of brain tissue slices showed prominent p-tau212 reactivity in neurofibrillary tangles that co-localized with p-tau217 and p-tau202/205. These findings support plasma p-tau212 as a novel peripherally accessible biomarker of AD pathophysiology.

Prediction of Parkinson's Disease Using Machine Learning Methods

The detection of Parkinson's disease (PD) in its early stages is of great importance for its treatment and management, but consensus is lacking on what information is necessary and what models should be used to best predict PD risk. In our study, we first grouped PD-associated factors based on their cost and accessibility, and then gradually incorporated them into risk predictions, which were built using eight commonly used machine learning models to allow for comprehensive assessment. Finally, the Shapley Additive Explanations (SHAP) method was used to investigate the contributions of each factor. We found that models built with demographic variables, hospital admission examinations, clinical assessment, and polygenic risk score achieved the best prediction performance, and the inclusion of invasive biomarkers could not further enhance its accuracy. Among the eight machine learning models considered, penalized logistic regression and XGBoost were the most accurate algorithms for assessing PD risk, with penalized logistic regression achieving an area under the curve of 0.94 and a Brier score of 0.08. Olfactory function and polygenic risk scores were the most important predictors for PD risk. Our research has offered a practical framework for PD risk assessment, where necessary information and efficient machine learning tools were highlighted.

Detection of APP gene recombinant in human blood plasma

The pathogenesis of Alzheimer's disease (AD) is believed to involve the accumulation of amyloid-β in the brain, which is produced by the sequential cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase. Recently, analysis of genomic DNA and mRNA from postmortem brain neurons has revealed intra-exonic recombinants of APP (gencDNA), which have been implicated in the accumulation of amyloid-β. In this study, we computationally analyzed publicly available sequence data (SRA) using probe sequences we constructed to screen APP gencDNAs. APP gencDNAs were detected in SRAs constructed from both genomic DNA and RNA obtained from the postmortem brain and in the SRA constructed from plasma cell-free mRNA (cf-mRNA). The SRA constructed from plasma cf-mRNA showed a significant difference in the number of APP gencDNA reads between SAD and NCI: the p-value from the Mann-Whitney U test was 5.14 × 10-6. The transcripts were also found in circulating nucleic acids (CNA) from our plasma samples with NGS analysis. These data indicate that transcripts of APP gencDNA can be detected in blood plasma and suggest the possibility of using them as blood biomarkers for Alzheimer's disease.

Association of Blood-Based DNA Methylation Markers With Late-Onset Alzheimer Disease: A Potential Diagnostic Approach

BACKGROUND AND OBJECTIVES

There is an urgent need to identify novel noninvasive biomarkers for Alzheimer disease (AD) diagnosis. Recent advances in blood-based measurements of phosphorylated tau (pTau) species are promising but still insufficient to address clinical needs. Epigenetics has been shown to be helpful to better understand AD pathogenesis. Epigenetic biomarkers have been successfully implemented in other medical disciplines, such as oncology. The objective of this study was to explore the diagnostic accuracy of a blood-based DNA methylation marker panel as a noninvasive tool to identify patients with late-onset Alzheimer compared with age-matched controls.

METHODS

A case-control study was performed. Blood DNA methylation levels at 46 cytosine-guanine sites (21 genes selected after a comprehensive literature search) were measured by bisulfite pyrosequencing in patients with "probable AD dementia" following National Institute on Aging and the Alzheimer's Association guidelines (2011) and age-matched and sex-matched controls recruited at Neurology Department-University Hospital of Navarre, Spain, selected by convenience sampling. Plasma pTau181 levels were determined by Simoa technology. Multivariable logistic regression analysis was performed to explore the optimal model to discriminate patients with AD from controls. Furthermore, we performed a stratified analysis by sex.

RESULTS

The final study cohort consisted of 80 patients with AD (age: median [interquartile range] 79 [11] years; 58.8% female) and 100 cognitively healthy controls (age 77 [10] years; 58% female). A panel including DNA methylation levels at NXN, ABCA7, and HOXA3 genes and plasma pTau181 significantly improved (area under the receiver operating characteristic curve 0.93, 95% CI 0.89-0.97) the diagnostic performance of a single pTau181-based model, adjusted for age, sex, and APOE ɛ4 genotype. The sensitivity and specificity of this panel were 83.30% and 90.00%, respectively. After sex-stratified analysis, HOXA3 DNA methylation levels showed consistent association with AD.

DISCUSSION

These results highlight the potential translational value of blood-based DNA methylation biomarkers for noninvasive diagnosis of AD.

REGISTRATION INFORMATION

Research Ethics Committee of the University Hospital of Navarre (PI17/02218).

Evolution and Predictive Role of Plasma Alzheimer's Disease-related Pathological Biomarkers in Parkinson's Disease

Plasma Alzheimer's disease-related pathological biomarkers' role in Parkinson's disease (PD) remains unknown. We aimed to determine whether plasma Alzheimer's disease-related biomarkers can predict PD progression. A total of 184 PD patients and 86 healthy controls were included and followed up for 5 years. Plasma phosphorylated tau181 (p-tau181), Aβ40, and Aβ42 were measured at baseline and the 1- and 2-year follow-ups using the Quanterix-single-molecule array. Global cognitive function and motor symptoms were assessed using the Montreal Cognitive Assessment and Unified Parkinson's Disease Rating Scale part III. Genetic analyses were conducted to identify APOE and MAPT genotypes. Plasma p-tau181 levels were higher in PD than healthy controls. APOE-ε4 carriers had lower plasma Aβ42 levels and Aβ42/Aβ40 ratio. The linear mixed-effects models showed that Montreal Cognitive Assessment scores were associated with plasma p-tau181/Aβ42 ratio (β -1.719 [-3.398 to -0.040], p = .045). Higher baseline plasma p-tau181 correlated with faster cognitive decline and motor symptoms deterioration in total patients (β -0.170 [-0.322 to -0.018], p = .029; β 0.329 [0.032 to 0.626], p = .030) and APOE-ε4 carriers (β -0.318 [-0.602 to -0.034], p = .030; β 0.632 [0.017 to 1.246], p = .046), but not in the noncarriers. Higher baseline plasma Aβ40 correlated with faster cognitive decline in total patients (β -0.007 [-0.015 to -0.0001], p = .047) and faster motor symptoms deterioration in total patients (β 0.026 [0.010 to 0.041], p = .001) and APOE-ε4 carriers (β 0.044 [-0.026 to 0.049], p = .020), but not in the noncarriers. The plasma p-tau181/Aβ2 ratio monitors the cognitive status of PD. Higher baseline plasma p-tau181 and Aβ40 predict faster cognitive decline and motor symptoms deterioration in PD, especially in APOE-ε4 carriers.

Cerebrospinal and Blood Biomarkers in Alzheimer's Disease: Did Mild Cognitive Impairment Definition Affect Their Clinical Usefulness?

Despite Alzheimer's Disease (AD) being known from the times of Alois Alzheimer, who lived more than one century ago, many aspects of the disease are still obscure, including the pathogenesis, the clinical spectrum definition, and the therapeutic approach. Well-established biomarkers for AD come from the histopathological hallmarks of the disease, which are Aβ and phosphorylated Tau protein aggregates. Consistently, cerebrospinal fluid (CSF) Amyloid β (Aβ) and phosphorylated Tau level measurements are currently used to detect AD presence. However, two central biases affect these biomarkers. Firstly, incomplete knowledge of the pathogenesis of diseases legitimates the search for novel molecules that, reasonably, could be expressed by neurons and microglia and could be detected in blood simpler and earlier than the classical markers and in a higher amount. Further, studies have been performed to evaluate whether CSF biomarkers can predict AD onset in Mild Cognitive Impairment (MCI) patients. However, the MCI definition has changed over time. Hence, the studies on MCI patients seem to be biased at the beginning due to the imprecise enrollment and heterogeneous composition of the miscellaneous MCI subgroup. Plasma biomarkers and novel candidate molecules, such as microglia biomarkers, have been tentatively investigated and could represent valuable targets for diagnosing and monitoring AD. Also, novel AD markers are urgently needed to identify molecular targets for treatment strategies. This review article summarizes the main CSF and blood AD biomarkers, underpins their advantages and flaws, and mentions novel molecules that can be used as potential biomarkers for AD.

Few-shot prediction of amyloid β accumulation from mainly unpaired data on biomarker candidates

The pair-wise observation of the input and target values obtained from the same sample is mandatory in any prediction problem. In the biomarker discovery of Alzheimer's disease (AD), however, obtaining such paired data is laborious and often avoided. Accumulation of amyloid-beta (Aβ) in the brain precedes neurodegeneration in AD, and the quantitative accumulation level may reflect disease progression in the very early phase. Nevertheless, the direct observation of Aβ is rarely paired with the observation of other biomarker candidates. To this end, we established a method that quantitatively predicts Aβ accumulation from biomarker candidates by integrating the mostly unpaired observations via a few-shot learning approach. When applied to 5xFAD mouse behavioral data, the proposed method predicted the accumulation level that conformed to the observed amount of Aβ in the samples with paired data. The results suggest that the proposed model can contribute to discovering Aβ predictability-based biomarkers.

CSF 14-3-3β is associated with progressive cognitive decline in Alzheimer's disease

Alzheimer's disease is a neurodegenerative disorder characterized pathologically by amyloid-beta plaques, tau tangles and neuronal loss. In clinical practice, the 14-3-3 isoform beta (β) is a biomarker that aids in the diagnosis of sporadic Creutzfeldt-Jakob disease. Recently, a proteomics study found increased CSF 14-3-3β levels in Alzheimer's disease patients, suggesting a potential link between CSF 14-3-3β and Alzheimer's disease. Our present study aimed to further investigate the role of CSF 14-3-3β in Alzheimer's disease by analysing the data of 719 participants with available CSF 14-3-3β measurements from the Alzheimer's Disease Neuroimaging Initiative. Higher CSF 14-3-3β levels were observed in the mild cognitive impairment group compared to the cognitively normal group, with the highest CSF 14-3-3β levels in the Alzheimer's disease dementia group. This study also found significant associations between CSF 14-3-3β levels and CSF biomarkers of p-tau, t-tau, pTau/Aβ42 ratios and GAP-43, as well as other Alzheimer's disease biomarkers such as Aβ-PET. An early increase in CSF 14-3-3β levels was observed prior to Aβ-PET-positive status, and CSF 14-3-3β levels continued to rise after crossing the Aβ-PET positivity threshold before reaching a plateau. The diagnostic accuracy of CSF 14-3-3β (area under the receiver operating characteristic curve = 0.819) was moderate compared to other established Alzheimer's disease biomarkers in distinguishing cognitively normal Aβ pathology-negative individuals from Alzheimer's disease Aβ pathology-positive individuals. Higher baseline CSF 14-3-3β levels were associated with accelerated cognitive decline, reduced hippocampus volumes and declining fluorodeoxyglucose-PET values over a 4-year follow-up period. Patients with mild cognitive impairment and high CSF 14-3-3β levels at baseline had a significantly increased risk [hazard ratio = 2.894 (1.599-5.238), P < 0.001] of progression to Alzheimer's disease dementia during follow-up. These findings indicate that CSF 14-3-3β may be a potential biomarker for Alzheimer's disease and could provide a more comprehensive understanding of the underlying pathological changes of Alzheimer's disease, as well as aid in the diagnosis and monitoring of disease progression.

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

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

A limbic-predominant amnestic neurodegenerative syndrome associated with TDP-43 pathology

Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a neuropathologically-defined disease that affects 40% of persons in advanced age, but its associated neurological syndrome is not defined. LATE neuropathological changes (LATE-NC) are frequently comorbid with Alzheimer's disease neuropathologic changes (ADNC). When seen in isolation, LATE-NC have been associated with a predominantly amnestic profile and slow clinical progression. We propose a set of clinical criteria for a limbic-predominant amnestic neurodegenerative syndrome (LANS) that is highly associated with LATE-NC but also other pathologic entities. The LANS criteria incorporate core, standard and advanced features that are measurable in vivo, including older age at evaluation, mild clinical syndrome, disproportionate hippocampal atrophy, impaired semantic memory, limbic hypometabolism, absence of neocortical degenerative patterns and low likelihood of neocortical tau, with degrees of certainty (highest, high, moderate, low). We operationalized this set of criteria using clinical, imaging and biomarker data to validate its associations with clinical and pathologic outcomes. We screened autopsied patients from Mayo Clinic (n = 922) and ADNI (n = 93) cohorts and applied the LANS criteria to those with an antemortem predominant amnestic syndrome (Mayo, n = 165; ADNI, n = 53). ADNC, ADNC/LATE-NC and LATE-NC accounted for 35%, 37% and 4% of cases in the Mayo cohort, respectively, and 30%, 22%, and 9% of cases in the ADNI cohort, respectively. The LANS criteria effectively categorized these cases, with ADNC having the lowest LANS likelihoods, LATE-NC patients having the highest likelihoods, and ADNC/LATE-NC patients having intermediate likelihoods. A logistic regression model using the LANS features as predictors of LATE-NC achieved a balanced accuracy of 74.6% in the Mayo cohort, and out-of-sample predictions in the ADNI cohort achieved a balanced accuracy of 73.3%. Patients with high LANS likelihoods had a milder and slower clinical course and more severe temporo-limbic degeneration compared to those with low likelihoods. Stratifying ADNC/LATE-NC patients from the Mayo cohort according to their LANS likelihood revealed that those with higher likelihoods had more temporo-limbic degeneration and a slower rate of cognitive decline, and those with lower likelihoods had more lateral temporo-parietal degeneration and a faster rate of cognitive decline. The implementation of LANS criteria has implications to disambiguate the different driving etiologies of progressive amnestic presentations in older age and guide prognosis, treatment, and clinical trials. The development of in vivo biomarkers specific to TDP-43 pathology are needed to refine molecular associations between LANS and LATE-NC and precise antemortem diagnoses of LATE.

Ketone bodies mediate alterations in brain energy metabolism and biomarkers of Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia. AD is a progressive neurodegenerative disorder characterized by cognitive dysfunction, including learning and memory deficits, and behavioral changes. Neuropathology hallmarks of AD such as amyloid beta (Aβ) plaques and neurofibrillary tangles containing the neuron-specific protein tau is associated with changes in fluid biomarkers including Aβ, phosphorylated tau (p-tau)-181, p-tau 231, p-tau 217, glial fibrillary acidic protein (GFAP), and neurofilament light (NFL). Another pathological feature of AD is neural damage and hyperactivation of astrocytes, that can cause increased pro-inflammatory mediators and oxidative stress. In addition, reduced brain glucose metabolism and mitochondrial dysfunction appears up to 15 years before the onset of clinical AD symptoms. As glucose utilization is compromised in the brain of patients with AD, ketone bodies (KBs) may serve as an alternative source of energy. KBs are generated from the β-oxidation of fatty acids, which are enhanced following consumption of ketogenic diets with high fat, moderate protein, and low carbohydrate. KBs have been shown to cross the blood brain barrier to improve brain energy metabolism. This review comprehensively summarizes the current literature on how increasing KBs support brain energy metabolism. In addition, for the first time, this review discusses the effects of ketogenic diet on the putative AD biomarkers such as Aβ, tau (mainly p-tau 181), GFAP, and NFL, and discusses the role of KBs on neuroinflammation, oxidative stress, and mitochondrial metabolism.

A prospective feasibility trial exploring novel biomarkers for neurotoxicity after isolated limb perfusion

BACKGROUND

Isolated limb perfusion (ILP) is a regional cancer treatment in which high-dose chemotherapy is administered in an isolated extremity. The main side effect is regional toxicity, which occasionally leads to nerve damage. Measuring neuroaxonal biomarkers, might be a method predicting such complications. Therefore, the primary aim of the study is to investigate if neuronal biomarkers are measurable and alters in an isolated extremity during ILP. Secondly, if postoperative regional toxicity, alterations in sensitivity, and/or muscle strength are correlated to the biomarker levels.

METHODS

Eighteen scheduled ILP-patients were included in the study. Glial fibrillary acidic protein (GFAP), neurofilament light (NfL), and tau concentrations were measured in plasma sampled preoperatively, at the start and end of the ILP, on days 3 and 30, using ultrasensitive Single molecule array (Simoa) technology. The patients were assessed by a physiotherapist pre- and postoperatively.

RESULTS

At ILP end, significantly higher NfL and tau levels were measured in the extremity than in the corresponding systemic circulation (NfL; 17 vs 6 ng/L, p < .01, tau; 1.8 vs 0.6 ng/L, p < .01), and the extremity levels were significantly increased at ILP end (NfL; 66 ± 37%, p < .001, tau; 75 ± 45%, p = .001). On days 3 and 30, significantly increased NfL and GFAP levels were measured systemically (NfL day 3: 69 ± 30%, p < .001; day 30: 76 ± 26%, p < .001; GFAP day 3: 33 ± 22%, p < .002; day 30: 33 ± 23%, p ≤ .004). Finally, no significant correlations were found between regional toxicity or between postoperative muscle or sensitivity decrease and biomarker release.

CONCLUSION

During ILP, NfL and tau levels increased significantly. No obvious correlations were observed between biomarker release and regional toxicity or decreased muscle strength or sensitivity, although large-scale studies are warranted.

TWINGEN - protocol for an observational clinical biobank recall and biomarker study to identify individuals with high risk of Alzheimer's disease

Introduction

A better understanding of the earliest stages of Alzheimer's disease (AD) could expedite the development or administration of treatments. Large population biobanks hold the promise to identify individuals at an elevated risk of AD and related dementias based on health registry information. Here, we establish the protocol for an observational clinical recall and biomarker study called TWINGEN with the aim to identify individuals at high risk of AD by assessing cognition, health and AD-related biomarkers. Suitable candidates were identified and invited to participate in the new study among Finnish biobank donors according to TWINGEN study criteria.

Methods and analysis

A multi-center study (n=800) to obtain blood-based biomarkers, telephone-administered and web-based memory and cognitive parameters, questionnaire information on lifestyle, health and psychological factors, and accelerometer data for measures of physical activity, sedentary behavior and sleep. A sub-cohort are being asked to participate in an in-person neuropsychological assessment (n=200) and wear an Oura ring (n=50). All participants in the TWINGEN study have genome-wide genotyping data and up to 48 years of follow-up data from the population-based older Finnish Twin Cohort (FTC) study of the University of Helsinki. TWINGEN data will be transferred to Finnish Institute of Health and Welfare (THL) biobank and we aim to further to transfer it to the FinnGen study where it will be combined with health registry data for prediction of AD.

Ethics and dissemination

This recall study consists of FTC/THL/FinnGen participants whose data were acquired in accordance with the Finnish Biobank Act. The recruitment protocols followed the biobank protocols approved by Finnish Medicines Agency. The TWINGEN study plan was approved by the Ethics Committee of Hospital District of Helsinki and Uusimaa (number 16831/2022). THL Biobank approved the research plan with the permission no: THLBB2022_83.

Clinical and demographic factors modify the association between plasma phosphorylated tau-181 and cognition

INTRODUCTION

Plasma phosphorylated tau181 (p-tau181) associations with global cognition and memory are clear, but the link between p-tau181 with other cognitive domains and subjective cognitive decline (SCD) across the clinical spectrum of Alzheimer's disease (AD) and how this association changes based on genetic and demographic factors is poorly understood.

METHODS

Participants were drawn from the Alzheimer's Disease Neuroimaging Initiative and included 1185 adults aged >55 years with plasma p-tau181 and neuropsychological test data. Linear regression models related plasma p-tau181 to neuropsychological composite and SCD scores with follow-up models examining plasma p-tau181 interactions with cognitive diagnosis, APOE ε4 carrier status, age, and sex on cognitive outcomes.

RESULTS

Higher plasma p-tau181 was associated with worse memory, executive functioning, and language abilities, and greater informant-reported SCD. Visuospatial abilities and self-report SCD were not associated with plasma p-tau181. Associations were generally stronger in MCI or dementia, APOE ε4 carriers, women, and younger participants.

DISCUSSION

Higher levels of plasma p-tau181 are associated with worse neuropsychological test performance across multiple cognitive domains; however, these associations vary based on disease stage, genetic risk status, age, and sex.