CNS cell-derived exosome signatures as blood-based biomarkers of neurodegenerative diseases.

Molecular biomarkers require the reproducible capture of disease-associated changes and are ideally sensitive, specific and accessible with minimal invasiveness to patients. Exosomes are a subtype of extracellular vesicles that have gained attention as potential biomarkers. They are released by all cell types and carry molecular cargo that reflects the functional state of the cells of origin. These characteristics make them an attractive means of measuring disease-related processes within the central nervous system (CNS), as they cross the blood-brain barrier (BBB) and can be captured in peripheral blood. In this review, we discuss recent progress made toward identifying blood-based protein and RNA biomarkers of several neurodegenerative diseases from circulating, CNS cell-derived exosomes. Given the lack of standardized methodology for exosome isolation and characterization, we discuss the challenges of capturing and quantifying the molecular content of exosome populations from blood for translation to clinical use.

Remote and unsupervised digital memory assessments can reliably detect cognitive impairment in Alzheimer's disease.

INTRODUCTION: Remote unsupervised cognitive assessments have the potential to complement and facilitate cognitive assessment in clinical and research settings. METHODS: Here, we evaluate the usability, validity, and reliability of unsupervised remote memory assessments via mobile devices in individuals without dementia from the Swedish BioFINDER-2 study and explore their prognostic utility regarding future cognitive decline. RESULTS: Usability was rated positively; remote memory assessments showed good construct validity with traditional neuropsychological assessments and were significantly associated with tau-positron emission tomography and downstream magnetic resonance imaging measures. Memory performance at baseline was associated with future cognitive decline and prediction of future cognitive decline was further improved by combining remote digital memory assessments with plasma p-tau217. Finally, retest reliability was moderate for a single assessment and good for an aggregate of two sessions. DISCUSSION: Our results demonstrate that unsupervised digital memory assessments might be used for diagnosis and prognosis in Alzheimer's disease, potentially in combination with plasma biomarkers. HIGHLIGHTS: Remote and unsupervised digital memory assessments are feasible in older adults and individuals in early stages of Alzheimer's disease. Digital memory assessments are associated with neuropsychological in-clinic assessments, tau-positron emission tomography and magnetic resonance imaging measures. Combination of digital memory assessments with plasma p-tau217 holds promise for prognosis of future cognitive decline. Future validation in further independent, larger, and more diverse cohorts is needed to inform clinical implementation.

Serum detection of blood brain barrier injury in subjects with a history of stroke and transient ischemic attack.

Objective: Stroke and transient ischemic attack may have long-term negative effects on the blood-brain barrier (BBB) and promote endothelial inflammation, both of which could increase neurodegeneration and dementia risk beyond the cell death associated with the index event. Methods: Serum from 88 postmortem subjects in the Arizona Study of Aging and Neurodegenerative Disorders were analyzed by sandwich ELISA for specific biomarkers to investigate the effects of cerebrovascular accidents (CVAs) on BBB integrity and endothelial activation. Statistical analyses were performed using the Mann-Whitney U Test, Spearman rank correlation, and linear/logistic regressions adjusted for potential confounders; a P-value < .05 was considered significant for all analyses. Results: Serum PDGFRẞ, a putative biomarker of BBB injury, was significantly increased in subjects with vs without a history of CVA who had similar cardiovascular risk factors (P < .01). This difference was stable after adjusting for age, hypertension, and other potential confounders in regression analysis (odds ratio, 27.02; 95% confidence interval, 2.61-411.7; P < .01). In addition, PDGFRẞ was positively associated with VCAM-1, a biomarker of endothelial inflammation (ρ = 0.42; P < .01). Conclusions: Our data suggest that patients with stroke or transient ischemic attack have lasting changes in the BBB. Still more, this demonstrates the utility of PDGFRẞ as a serum-based biomarker of BBB physiology, a potentially powerful tool in studying the role of the BBB in various neurodegenerative diseases and COVID infection sequelae. Clinical Relevance: Our data demonstrate the utility of serum PDGFRẞ, a putative biomarker of BBB integrity in the setting of stroke and TIA (CVA). A serum biomarker of BBB integrity could be a useful tool to detect early BBB damage and allow prospective work to study how such damage affects long-term neurodegenerative risk. Since BBB disruption occurs early in ADRD development, it could be monitored to help better understand disease progression and involvement of vascular pathways in ADRD.

Plasma pTau217 predicts continuous brain amyloid levels in preclinical and early Alzheimer's disease.

BACKGROUND: This study investigated the potential of phosphorylated plasma Tau217 ratio (pTau217R) and plasma amyloid beta (Aß) 42/Aß40 in predicting brain amyloid levels measured by positron emission tomography (PET) Centiloid (CL) for Alzheimer's disease (AD) staging and screening. METHODS: Quantification of plasma pTau217R and Aß42/Aß40 employed immunoprecipitation-mass spectrometry. CL prediction models were developed on a cohort of 904 cognitively unimpaired, preclinical and early AD subjects and validated on two independent cohorts. RESULTS: Models integrating pTau217R outperformed Aß42/Aß40 alone, predicting amyloid levels up to 89.1 CL. High area under the receiver operating characteristic curve (AUROC) values (89.3% to 94.7%) were observed across a broad CL range (15 to 90). Utilizing pTau217R-based models for low amyloid levels reduced PET scans by 70.5% to 78.6%. DISCUSSION: pTau217R effectively predicts brain amyloid levels, surpassing cerebrospinal fluid Aß42/Aß40's range. Combining it with plasma Aß42/Aß40 enhances sensitivity for low amyloid detection, reducing unnecessary PET scans and expanding clinical utility. HIGHLIGHTS: Phosphorylated plasma Tau217 ratio (pTau217R) effectively predicts amyloid-PET Centiloid (CL) across a broad spectrum. Integrating pTau217R with Aß42/Aß40 extends the CL prediction upper limit to 89.1 CL. Combined model predicts amyloid status with high accuracy, especially in cognitively unimpaired individuals. This model identifies subjects above or below various CL thresholds with high accuracy. pTau217R-based models significantly reduce PET scans by up to 78.6% for screening out individuals with no/low amyloid.

Advances in blood biomarkers for Alzheimer disease (AD): A review.

Alzheimer disease (AD) and Alzheimer Disease and Related Dementias (AD/ADRD) are growing public health challenges globally affecting millions of older adults, necessitating concerted efforts to advance our understanding and management of these conditions. AD is a progressive neurodegenerative disorder characterized pathologically by amyloid plaques and tau neurofibrillary tangles that are the primary cause of dementia in older individuals. Early and accurate diagnosis of AD dementia is crucial for effective intervention and treatment but has proven challenging to accomplish. Although testing for AD brain pathology with cerebrospinal fluid (CSF) or positron emission tomography (PET) has been available for over 2 decades, most patients never underwent this testing because of inaccessibility, high out-of-pocket costs, perceived risks, and the lack of AD-specific treatments. However, in recent years, rapid progress has been made in developing blood biomarkers for AD/ADRD. Consequently, blood biomarkers have emerged as promising tools for non-invasive and cost-effective diagnosis, prognosis, and monitoring of AD progression. This review presents the evolving landscape of blood biomarkers in AD/ADRD and explores their potential applications in clinical practice for early detection, prognosis, and therapeutic interventions. It covers recent advances in blood biomarkers, including amyloid beta (Aß) peptides, tau protein, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP). It also discusses their diagnostic and prognostic utility while addressing associated challenges and limitations. Future research directions in this rapidly evolving field are also proposed.

Single molecule array measures of LRRK2 kinase activity in serum link Parkinson's disease severity to peripheral inflammation.

BACKGROUND: LRRK2-targeting therapeutics that inhibit LRRK2 kinase activity have advanced to clinical trials in idiopathic Parkinson's disease (iPD). LRRK2 phosphorylates Rab10 on endolysosomes in phagocytic cells to promote some types of immunological responses. The identification of factors that regulate LRRK2-mediated Rab10 phosphorylation in iPD, and whether phosphorylated-Rab10 levels change in different disease states, or with disease progression, may provide insights into the role of Rab10 phosphorylation in iPD and help guide therapeutic strategies targeting this pathway. METHODS: Capitalizing on past work demonstrating LRRK2 and phosphorylated-Rab10 interact on vesicles that can shed into biofluids, we developed and validated a high-throughput single-molecule array assay to measure extracellular pT73-Rab10. Ratios of pT73-Rab10 to total Rab10 measured in biobanked serum samples were compared between informative groups of transgenic mice, rats, and a deeply phenotyped cohort of iPD cases and controls. Multivariable and weighted correlation network analyses were used to identify genetic, transcriptomic, clinical, and demographic variables that predict the extracellular pT73-Rab10 to total Rab10 ratio. RESULTS: pT73-Rab10 is absent in serum from Lrrk2 knockout mice but elevated by LRRK2 and VPS35 mutations, as well as SNCA expression. Bone-marrow transplantation experiments in mice show that serum pT73-Rab10 levels derive primarily from circulating immune cells. The extracellular ratio of pT73-Rab10 to total Rab10 is dynamic, increasing with inflammation and rapidly decreasing with LRRK2 kinase inhibition. The ratio of pT73-Rab10 to total Rab10 is elevated in iPD patients with greater motor dysfunction, irrespective of disease duration, age, sex, or the usage of PD-related or anti-inflammatory medications. pT73-Rab10 to total Rab10 ratios are associated with neutrophil degranulation, antigenic responses, and suppressed platelet activation. CONCLUSIONS: The extracellular serum ratio of pT73-Rab10 to total Rab10 is a novel pharmacodynamic biomarker for LRRK2-linked innate immune activation associated with disease severity in iPD. We propose that those iPD patients with higher serum pT73-Rab10 levels may benefit from LRRK2-targeting therapeutics that mitigate associated deleterious immunological responses.

Moderate intensity aerobic exercise alleviates motor deficits in 6-OHDA lesioned rats and reduces serum levels of biomarkers of Parkinson's disease severity without recovery of striatal dopamine or tyrosine hydroxylase.

Alleviation of motor impairment by aerobic exercise (AE) in Parkinson's disease (PD) patients points to activation of neurobiological mechanisms that may be targetable by therapeutic approaches. However, evidence for AE-related recovery of striatal dopamine (DA) signaling or tyrosine hydroxylase (TH) loss has been inconsistent in rodent studies. This ambiguity may be related to the timing of AE intervention in relation to the status of nigrostriatal neuron loss. Here, we replicated human PD at diagnosis by establishing motor impairment with >80% striatal DA and TH loss prior to initiating AE, and assessed its potential to alleviate motor decline and restore DA and TH loss. We also evaluated if serum levels of neurofilament light (NfL) and glial fibrillary acidic protein (GFAP), biomarkers of human PD severity, changed in response to AE. 6-hydroxydopamine (6-OHDA) was infused unilaterally into rat medial forebrain bundle to induce progressive nigrostriatal neuron loss over 28 days. Moderate intensity AE (3× per week, 40 min/session), began 8-10 days post-lesion following establishment of impaired forelimb use. Striatal tissue DA, TH protein and mRNA, and serum levels of NfL/GFAP were determined 3-wks after AE began. Despite severe striatal DA depletion at AE initiation, forelimb use deficits and hypokinesia onset were alleviated by AE, without recovery of striatal DA or TH protein loss, but reduced NfL and GFAP serum levels. This proof-of-concept study shows AE alleviates motor impairment when initiated with >80% striatal DA loss without obligate recovery of striatal DA or TH protein. Moreover, the AE-related reduction of NfL and GFAP serum levels may serve as objective blood-based biomarkers of AE efficacy.

Multiomics Blood-Based Biomarkers Predict Alzheimer's Predementia with High Specificity in a Multicentric Cohort Study.

BACKGROUND: The primary criteria for diagnosing mild cognitive impairment (MCI) due to Alzheimer's Disease (AD) or probable mild AD dementia rely partly on cognitive assessments and the presence of amyloid plaques. Although these criteria exhibit high sensitivity in predicting AD among cognitively impaired patients, their specificity remains limited. Notably, up to 25% of non-demented patients with amyloid plaques may be misdiagnosed with MCI due to AD, when in fact they suffer from a different brain disorder. The introduction of anti-amyloid antibodies complicates this scenario. Physicians must prioritize which amyloid-positive MCI patients receive these treatments, as not all are suitable candidates. Specifically, those with non-AD amyloid pathologies are not primary targets for amyloid-modifying therapies. Consequently, there is an escalating medical necessity for highly specific blood biomarkers that can accurately detect pre-dementia AD, thus optimizing amyloid antibody prescription. OBJECTIVES: The objective of this study was to evaluate a predictive model based on peripheral biomarkers to identify MCI and mild dementia patients who will develop AD dementia symptoms in cognitively impaired population with high specificity. DESIGN: Peripheral biomarkers were identified in a gene transfer-based animal model of AD and then validated during a retrospective multi-center clinical study. SETTING: Participants from 7 retrospective cohorts (US, EU and Australia). PARTICIPANTS: This study followed 345 cognitively impaired individuals over up to 13 years, including 193 with MCI and 152 with mild dementia, starting from their initial visits. The final diagnoses, established during their last assessments, classified 249 participants as AD patients and 96 as having non-AD brain disorders, based on the specific diagnostic criteria for each disorder subtype. Amyloid status, assessed at baseline, was available for 82.9% of the participants, with 61.9% testing positive for amyloid. Both amyloid-positive and negative individuals were represented in each clinical group. Some of the AD patients had co-morbidities such as metabolic disorders, chronic diseases, or cardiovascular pathologies. MEASUREMENTS: We developed targeted mass spectrometry assays for 81 blood-based biomarkers, encompassing 45 proteins and 36 metabolites previously identified in AAV-AD rats. METHODS: We analyzed blood samples from study participants for the 81 biomarkers. The B-HEALED test, a machine learning-based diagnostic tool, was developed to differentiate AD patients, including 123 with Prodromal AD and 126 with mild AD dementia, from 96 individuals with non-AD brain disorders. The model was trained using 70% of the data, selecting relevant biomarkers, calibrating the algorithm, and establishing cutoff values. The remaining 30% served as an external test dataset for blind validation of the predictive accuracy. RESULTS: Integrating a combination of 19 blood biomarkers and participant age, the B-HEALED model successfully distinguished participants that will develop AD dementia symptoms (82 with Prodromal AD and 83 with AD dementia) from non-AD subjects (71 individuals) with a specificity of 93.0% and sensitivity of 65.4% (AUROC=81.9%, p<0.001) during internal validation. When the amyloid status (derived from CSF or PET scans) and the B-HEALED model were applied in association, with individuals being categorized as AD if they tested positive in both tests, we achieved 100% specificity and 52.8% sensitivity. This performance was consistent in blind external validation, underscoring the model's reliability on independent datasets. CONCLUSIONS: The B-HEALED test, utilizing multiomics blood-based biomarkers, demonstrates high predictive specificity in identifying AD patients within the cognitively impaired population, minimizing false positives. When used alongside amyloid screening, it effectively identifies a nearly pure prodromal AD cohort. These results bear significant implications for refining clinical trial inclusion criteria, facilitating drug development and validation, and accurately identifying patients who will benefit the most from disease-modifying AD treatments.

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 (Aß) plaques and neurofibrillary tangles in the brain. Both disorders have elevated Aß, 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.

Confounding factors of the expression of mTBI biomarkers, S100B, GFAP and UCH-L1 in an aging population.

OBJECTIVES: To evaluate some confounding factors that influence the concentrations of S100 calcium binding protein B (S100B), glial fibrillary acidic protein (GFAP), and ubiquitin carboxyl-terminal hydrolase L-1 (UCH-L1) in older individuals. Indeed, recent guidelines have proposed the combined use of S100B and the "GFAP-UCH-L1" mTBI test to rule out mild traumatic brain injuries (mTBI). As older adults are the most at risk of mTBI, it is particularly important to understand the confounding factors of those mTBI rule-out biomarkers in aging population. METHODS: The protein S100B and the "GFAP and UCH-L1" mTBI test were measured using Liaison XL (Diasorin) and Alinity I (Abbott), respectively, in 330 and 341 individuals with non-suspected mTBI from the SarcoPhAge cohort. RESULTS: S100B, GFAP and UCH-L1 were all significantly correlated with renal function whereas alcohol consumption, Geriatric Depression Score (GDS), smoking habits and anticoagulant intake were not associated with any of these three biomarkers. Body mass index (BMI) and age were associated with GFAP and UCH-L1 expression while sex and mini-mental state examination (MMSE) were only associated with GFAP. According to the manufacturer's cut-offs for mTBI rule-out, only 5.5 % of participants were positive for S100B whereas 66.9 % were positive for the "GFAP-UCH-L1" mTBI test. All positive "GFAP-UCH-L1" mTBI tests were GFAP+/UCH-L1-. Among individuals with cystatin C>1.55 mg/L, 25 % were positive for S100B while 90 % were positive for the mTBI test. CONCLUSIONS: Our data show that confounding factors have different impacts on the positivity rate of the "GFAP-UCH-L1" mTBI test compared to S100B.

A critical appraisal of blood-based biomarkers for Alzheimer's disease.

Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-ß (Aß) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aß1-42, the Aß1-42/Aß1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aß1-42/Aß1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.

Associations of plasma neurofilament light chain with cognition and neuroimaging measures in community-dwelling early old age men.

BACKGROUND: Plasma neurofilament light chain (NfL) is a promising biomarker of neurodegeneration with potential clinical utility in monitoring the progression of neurodegenerative diseases. However, the cross-sectional associations of plasma NfL with measures of cognition and brain have been inconsistent in community-dwelling populations. METHODS: We examined these associations in a large community-dwelling sample of early old age men (N = 969, mean age = 67.57 years, range = 61-73 years), who are either cognitively unimpaired (CU) or with mild cognitive impairment (MCI). Specifically, we investigated five cognitive domains (executive function, episodic memory, verbal fluency, processing speed, visual-spatial ability), as well as neuroimaging measures of gray and white matter. RESULTS: After adjusting for age, health status, and young adult general cognitive ability, plasma NfL level was only significantly associated with processing speed and white matter hyperintensity (WMH) volume, but not with other cognitive or neuroimaging measures. The association with processing speed was driven by individuals with MCI, as it was not detected in CU individuals. CONCLUSIONS: These results suggest that in early old age men without dementia, plasma NfL does not appear to be sensitive to cross-sectional individual differences in most domains of cognition or neuroimaging measures of gray and white matter. The revealed plasma NfL associations were limited to WMH for all participants and processing speed only within the MCI cohort. Importantly, considering cognitive status in community-based samples will better inform the interpretation of the relationships of plasma NfL with cognition and brain and may help resolve mixed findings in the literature.

Combining Blood-Based Biomarkers and Structural MRI Measurements to Distinguish Persons with and without Significant Amyloid Plaques.

Background: Amyloid-ß (Aß) plaques play a pivotal role in Alzheimer's disease. The current positron emission tomography (PET) is expensive and limited in availability. In contrast, blood-based biomarkers (BBBMs) show potential for characterizing Aß plaques more affordably. We have previously proposed an MRI-based hippocampal morphometry measure to be an indicator of Aß plaques. Objective: To develop and validate an integrated model to predict brain amyloid PET positivity combining MRI feature and plasma Aß42/40 ratio. Methods: We extracted hippocampal multivariate morphometry statistics from MR images and together with plasma Aß42/40 trained a random forest classifier to perform a binary classification of participant brain amyloid PET positivity. We evaluated the model performance using two distinct cohorts, one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the other from the Banner Alzheimer's Institute (BAI), including prediction accuracy, precision, recall rate, F1 score, and AUC score. Results: Results from ADNI (mean age 72.6, Aß+ rate 49.5%) and BAI (mean age 66.2, Aß+ rate 36.9%) datasets revealed the integrated multimodal (IMM) model's superior performance over unimodal models. The IMM model achieved prediction accuracies of 0.86 in ADNI and 0.92 in BAI, surpassing unimodal models based solely on structural MRI (0.81 and 0.87) or plasma Aß42/40 (0.73 and 0.81) predictors. CONCLUSIONS: Our IMM model, combining MRI and BBBM data, offers a highly accurate approach to predict brain amyloid PET positivity. This innovative multiplex biomarker strategy presents an accessible and cost-effective avenue for advancing Alzheimer's disease diagnostics, leveraging diverse pathologic features related to Aß plaques and structural MRI.

Plasma neurofilament light, glial fibrillary acid protein, and phosphorylated tau 181 as biomarkers for neuropsychiatric symptoms and related clinical disease progression.

BACKGROUND: Neuropsychiatric symptoms (NPS) are common in older people, may occur early in the development of dementia disorders, and have been associated with faster cognitive decline. Here, our objectives were to investigate whether plasma levels of neurofilament light chain (NfL), glial fibrillary acid protein (GFAP), and tau phosphorylated at threonine 181 (pTau181) are associated with current NPS and predict future NPS in non-demented older people. Furthermore, we tested whether the presence of NPS combined with plasma biomarkers are useful to predict Alzheimer's disease (AD) pathology and cognitive decline. METHODS: One hundred and fifty-one participants with normal cognition (n=76) or mild cognitive impairment (n=75) were examined in a longitudinal brain aging study at the Memory Centers, University Hospital of Lausanne, Switzerland. Plasma levels of NfL, GFAP, and pTau181 along with CSF biomarkers of AD pathology were measured at baseline. NPS were assessed through the Neuropsychiatric Inventory Questionnaire (NPI-Q), along with the cognitive and functional performance at baseline and follow-up (mean: 20 months). Linear regression and ROC analyses were used to address the associations of interest. RESULTS: Higher GFAP levels were associated with NPS at baseline (ß=0.23, p=.008). Higher NfL and GFAP levels were associated with the presence of NPS at follow-up (ß=0.29, p=.007 and ß=0.28, p=.007, respectively) and with an increase in the NPI-Q severity score over time (ß=0.23, p=.035 and ß=0.27, p=.011, respectively). Adding NPS and the plasma biomarkers to a reference model improved the prediction of future NPS (AUC 0.73 to 0.84, p=.007) and AD pathology (AUC 0.79 to 0.86, p=.006), but not of cognitive decline (AUC 0.79 to 0.84, p=.068). CONCLUSION: Plasma GFAP is associated with NPS while NfL and GFAP are both associated with future NPS and NPS severity. Considering the presence of NPS along with blood-based AD-biomarkers may improve diagnosis and prediction of clinical progression of NPS and inform clinical decision-making in non-demented older people.

Epigenetic scores of blood-based proteins as biomarkers of general cognitive function and brain health.

BACKGROUND: Epigenetic Scores (EpiScores) for blood protein levels have been associated with disease outcomes and measures of brain health, highlighting their potential usefulness as clinical biomarkers. They are typically derived via penalised regression, whereby a linear weighted sum of DNA methylation (DNAm) levels at CpG sites are predictive of protein levels. Here, we examine 84 previously published protein EpiScores as possible biomarkers of cross-sectional and longitudinal measures of general cognitive function and brain health, and incident dementia across three independent cohorts. RESULTS: Using 84 protein EpiScores as candidate biomarkers, associations with general cognitive function (both cross-sectionally and longitudinally) were tested in three independent cohorts: Generation Scotland (GS), and the Lothian Birth Cohorts of 1921 and 1936 (LBC1921 and LBC1936, respectively). A meta-analysis of general cognitive functioning results in all three cohorts identified 18 EpiScore associations (absolute meta-analytic standardised estimates ranged from 0.03 to 0.14, median of 0.04, PFDR < 0.05). Several associations were also observed between EpiScores and global brain volumetric measures in the LBC1936. An EpiScore for the S100A9 protein (a known Alzheimer disease biomarker) was associated with general cognitive functioning (meta-analytic standardised beta: - 0.06, P = 1.3 × 10-9), and with time-to-dementia in GS (Hazard ratio 1.24, 95% confidence interval 1.08-1.44, P = 0.003), but not in LBC1936 (Hazard ratio 1.11, P = 0.32). CONCLUSIONS: EpiScores might make a contribution to the risk profile of poor general cognitive function and global brain health, and risk of dementia, however these scores require replication in further studies.

Plasma biomarkers for Alzheimer's and related dementias: A review and outlook for clinical neuropsychology.

Recent technological advances have improved the sensitivity and specificity of blood-based biomarkers for Alzheimer's disease and related dementias. Accurate quantification of amyloid-ß peptide, phosphorylated tau (pTau) isoforms, as well as markers of neurodegeneration (neurofilament light chain [NfL]) and neuro-immune activation (glial fibrillary acidic protein [GFAP] and chitinase-3-like protein 1 [YKL-40]) in blood has allowed researchers to characterize neurobiological processes at scale in a cost-effective and minimally invasive manner. Although currently used primarily for research purposes, these blood-based biomarkers have the potential to be highly impactful in the clinical setting - aiding in diagnosis, predicting disease risk, and monitoring disease progression. Whereas plasma NfL has shown promise as a non-specific marker of neuronal injury, plasma pTau181, pTau217, pTau231, and GFAP have demonstrated desirable levels of sensitivity and specificity for identification of individuals with Alzheimer's disease pathology and Alzheimer's dementia. In this forward looking review, we (i) provide an overview of the most commonly used blood-based biomarkers for Alzheimer's disease and related dementias, (ii) discuss how comorbid medical conditions, demographic, and genetic factors can inform the interpretation of these biomarkers, (iii) describe ongoing efforts to move blood-based biomarkers into the clinic, and (iv) highlight the central role that clinical neuropsychologists may play in contextualizing and communicating blood-based biomarker results for patients.

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.

The Association of Alzheimer's Disease-Related Blood-Based Biomarkers with Cognitive Screening Test Performance in the Congolese Population in Kinshasa.

BACKGROUND: Alzheimer's disease (AD), the most common cause of dementia, poses a significant global burden. Diagnosis typically involves invasive and costly methods like neuroimaging or cerebrospinal fluid (CSF) biomarker testing of phosphorylated tau (p-tau) and amyloid-ß42/40 (Aß42/40). Such procedures are especially impractical in resource-constrained regions, such as the Democratic Republic of Congo (DRC). Blood-based biomarker testing may provide a more accessible screening opportunity. OBJECTIVE: This study aims to examine if AD-related blood-based biomarkers are associated with cognitive test performance in the Congolese population, where limited research has been conducted. METHODS: In this cross-sectional study of 81 Congolese individuals, cognitive assessments (Alzheimer's Questionnaire (AQ) and Community Screening Interview for Dementia (CSID)) distinguished dementia cases from controls. Blood draws were taken to assess p-tau 181 and Aß42/40 biomarkers. Relationships between the biomarkers and cognitive performance were analyzed using multiple linear regression models. RESULTS: Lower plasma Aß42/40 was significantly associated with lower CSID scores and higher AQ scores, indicative of AD (p < 0.001). These relationships were observed in healthy controls (CSID p = 0.01, AQ p = 0.03), but not in dementia cases. However, p-tau 181 did not exhibit significant associations with either measure. Factors such as age, sex, education, presence of APOEɛ4 allele, did not alter these relationships. CONCLUSIONS: Understanding relationships between AD-related screening tests and blood biomarkers is a step towards utilization of blood-based biomarker tests as a screening tool for AD, especially in resource-limited regions. Further research should be conducted to evaluate blood biomarker test efficacy in larger samples and other populations.

Development of Continuous Assessment of Muscle Quality and Frailty in Older Patients Using Multiparametric Combinations of Ultrasound and Blood Biomarkers: Protocol for the ECOFRAIL Study.

BACKGROUND: Frailty resulting from the loss of muscle quality can potentially be delayed through early detection and physical exercise interventions. There is a demand for cost-effective tools for the objective evaluation of muscle quality, in both cross-sectional and longitudinal assessments. Literature suggests that quantitative analysis of ultrasound data captures morphometric, compositional, and microstructural muscle properties, while biological assays derived from blood samples are associated with functional information. OBJECTIVE: This study aims to assess multiparametric combinations of ultrasound and blood-based biomarkers to offer a cross-sectional evaluation of the patient frailty phenotype and to track changes in muscle quality associated with supervised exercise programs. METHODS: This prospective observational multicenter study will include patients aged 70 years and older who are capable of providing informed consent. We aim to recruit 100 patients from hospital environments and 100 from primary care facilities. Each patient will undergo at least two examinations (baseline and follow-up), totaling a minimum of 400 examinations. In hospital environments, 50 patients will be measured before/after a 16-week individualized and supervised exercise program, while another 50 patients will be followed up after the same period without intervention. Primary care patients will undergo a 1-year follow-up evaluation. The primary objective is to compare cross-sectional evaluations of physical performance, functional capacity, body composition, and derived scales of sarcopenia and frailty with biomarker combinations obtained from muscle ultrasound and blood-based assays. We will analyze ultrasound raw data obtained with a point-of-care device, along with a set of biomarkers previously associated with frailty, using quantitative real-time polymerase chain reaction and enzyme-linked immunosorbent assay. Additionally, we will examine the sensitivity of these biomarkers to detect short-term muscle quality changes and functional improvement after a supervised exercise intervention compared with usual care. RESULTS: At the time of manuscript submission, the enrollment of volunteers is ongoing. Recruitment started on March 1, 2022, and ends on June 30, 2024. CONCLUSIONS: The outlined study protocol will integrate portable technologies, using quantitative muscle ultrasound and blood biomarkers, to facilitate an objective cross-sectional assessment of muscle quality in both hospital and primary care settings. The primary objective is to generate data that can be used to explore associations between biomarker combinations and the cross-sectional clinical assessment of frailty and sarcopenia. Additionally, the study aims to investigate musculoskeletal changes following multicomponent physical exercise programs. TRIAL REGISTRATION: ClinicalTrials.gov NCT05294757; https://clinicaltrials.gov/ct2/show/NCT05294757. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50325.

The Bio-Hermes Study: Biomarker database developed to investigate blood-based and digital biomarkers in community-based, diverse populations clinically screened for Alzheimer's disease.

INTRODUCTION: Alzheimer's disease (AD) trial participants are often screened for eligibility by brain amyloid positron emission tomography/cerebrospinal fluid (PET/CSF), which is inefficient as many are not amyloid positive. Use of blood-based biomarkers may reduce screen failures. METHODS: We recruited 755 non-Hispanic White, 115 Hispanic, 112 non-Hispanic Black, and 19 other minority participants across groups of cognitively normal (n = 417), mild cognitive impairment (n = 312), or mild AD (n = 272) participants. Plasma amyloid beta (Aß)40, Aß42, Aß42/Aß40, total tau, phosphorylated tau (p-tau)181, and p-tau217 were measured; amyloid PET/CSF (n = 956) determined amyloid positivity. Clinical, blood biomarker, and ethnicity/race differences associated with amyloid status were evaluated. RESULTS: Greater impairment, older age, and carrying an apolipoprotein E (apoE) ε4 allele were associated with greater amyloid burden. Areas under the receiver operating characteristic curve for amyloid status of plasma Aß42/Aß40, p-tau181, and p-tau217 with amyloid positivity were ≥ 0.7117 for all ethnoracial groups (p-tau217, ≥0.8128). Age and apoE ε4 adjustments and imputation of biomarker values outside limit of quantitation provided small improvement in predictive power. DISCUSSION: Blood-based biomarkers are highly associated with amyloid PET/CSF results in diverse populations enrolled at clinical trial sites. HIGHLIGHTS: Amyloid beta (Aß)42/Aß40, phosphorylated tau (p-tau)181, and p-tau 217 blood-based biomarkers predicted brain amyloid positivity. P-tau 217 was the strongest predictor of brain amyloid positivity. Biomarkers from diverse ethnic, racial, and clinical cohorts predicted brain amyloid positivity. Community-based populations have similar Alzheimer's disease (AD) biomarker levels as other populations. A prescreen process with blood-based assays may reduce the number of AD trial screen failures.