Comparative Effectiveness and Cost-Effectiveness of Colorectal Cancer Screening With Blood-Based Biomarkers (Liquid Biopsy) vs Fecal Tests or Colonoscopy.

BACKGROUND & AIMS: Colorectal cancer (CRC) screening is highly effective but underused. Blood-based biomarkers (liquid biopsy) could improve screening participation. METHODS: Using our established Markov model, screening every 3 years with a blood-based test that meets minimum Centers for Medicare & Medicaid Services' thresholds (CMSmin) (CRC sensitivity 74%, specificity 90%) was compared with established alternatives. Test attributes were varied in sensitivity analyses. RESULTS: CMSmin reduced CRC incidence by 40% and CRC mortality by 52% vs no screening. These reductions were less profound than the 68%-79% and 73%-81%, respectively, achieved with multi-target stool DNA (Cologuard; Exact Sciences) every 3 years, annual fecal immunochemical testing (FIT), or colonoscopy every 10 years. Assuming the same cost as multi-target stool DNA, CMSmin cost $28,500/quality-adjusted life-year gained vs no screening, but FIT, colonoscopy, and multi-target stool DNA were less costly and more effective. CMSmin would match FIT's clinical outcomes if it achieved 1.4- to 1.8-fold FIT's participation rate. Advanced precancerous lesion (APL) sensitivity was a key determinant of a test's effectiveness. A paradigm-changing blood-based test (sensitivity >90% for CRC and 80% for APL; 90% specificity; cost ≤$120-$140) would be cost-effective vs FIT at comparable participation. CONCLUSIONS: CMSmin could contribute to CRC control by achieving screening in those who will not use established methods. Substituting blood-based testing for established effective CRC screening methods will require higher CRC and APL sensitivities that deliver programmatic benefits matching those of FIT. High APL sensitivity, which can result in CRC prevention, should be a top priority for screening test developers. APL detection should not be penalized by a definition of test specificity that focuses on CRC only.

A conduit to metastasis: circulating tumor cell biology.

Advances in the enrichment and analysis of rare cells from the bloodstream have allowed for detection and characterization of circulating tumor cells (CTCs) from patients with cancer. The analysis of CTCs has provided significant insight into the metastatic process. Studies on the biology of CTCs have begun to elucidate the molecular mechanisms of CTC generation, intravasation, survival, interactions with components of the blood, extravasation, and colonization of distant organs. Additionally, the study of CTCs has exposed dramatic intrapatient and interpatient heterogeneity and their evolution over time. In this review, we focus on the current knowledge of CTC biology and the potential clinical implications.

Considerations for Use of Blood-Based Biomarkers in Epidemiologic Dementia Research.

Dementia represents a growing public health burden with large social, racial, and ethnic disparities. The etiology of dementia is poorly understood, and the lack of robust biomarkers in diverse, population-representative samples is a barrier to moving dementia research forward. Existing biomarkers and other measures of pathology-derived from neuropathology, neuroimaging, and cerebrospinal fluid samples-are commonly collected from predominantly White and highly educated samples drawn from academic medical centers in urban settings. Blood-based biomarkers are noninvasive and less expensive, offering promise to expand our understanding of the pathophysiology of dementia, including in participants from historically excluded groups. Although largely not yet approved by the Food and Drug Administration or used in clinical settings, blood-based biomarkers are increasingly included in epidemiologic studies on dementia. Blood-based biomarkers in epidemiologic research may allow the field to more accurately understand the multifactorial etiology and sequence of events that characterize dementia-related pathophysiological changes. As blood-based dementia biomarkers continue to be developed and incorporated into research and practice, we outline considerations for using them in dementia epidemiology, and illustrate key concepts with Alzheimer's Disease Neuroimaging Initiative (2003-present) data. We focus on measurement, including both validity and reliability, and on the use of dementia blood-based biomarkers to promote equity in dementia research and cognitive aging. This article is part of a Special Collection on Mental Health.

The prognostic value of the Merkel cell polyomavirus serum antibody test: A dual institutional observational study.

BACKGROUND: Merkel cell carcinoma (MCC) is an aggressive cancer with often poor outcomes. Limited biomarkers exist for predicting clinical outcomes. The Merkel cell polyomavirus (MCPyV) serum antibody test (AMERK) has shown potential for indicating better recurrence-free survival in a single-institution study. The study aimed to evaluate the link between initial AMERK serostatus and survival. Secondary objectives included examining the relationship between initial AMERK titer levels and tumor burden. METHODS: A retrospective cohort study across two institutions analyzed patients tested with AMERK within 90 days of MCC diagnosis. Regression models assessed the association of survival outcomes with serostatus, considering various factors. The relationship between AMERK titer and tumor burden indicators was evaluated using ANOVA. Significance testing was exploratory, without a fixed significance level. RESULTS: Of 261 MCC patients tested, 49.4% were initially seropositive (titer ≥75). Multivariable analysis showed that seropositivity improved recurrence, event-free, overall, and MCC-specific survival rates. Strong associations were found between initial AMERK titer and clinical, tumor, and nodal stages, tumor size, and disease extent. Notably, improved survival with seropositivity was observed only in patients with localized disease at initial presentation. CONCLUSION: Circulating antibodies to MCPyV oncoproteins, as indicated by the AMERK test, are linked with better survival in MCC patients with localized disease at presentation. This could enhance patient risk profiling and treatment personalization. The study's retrospective nature and exploratory analysis are key limitations. PLAIN LANGUAGE SUMMARY: Merkel cell carcinoma (MCC) is a potentially aggressive skin cancer, and tools to predict patient outcomes are limited. A blood test called anti-Merkel cell panel (AMERK), which checks for specific antibodies related to this cancer, might give us some clues. In this study, we looked at 261 MCC patients who took the AMERK test within 90 days of diagnosis. We found that patients with an initial positive AMERK result tended to have better outcomes, especially if their cancer was in the early stages. However, it is important to note that this study has limitations, including using retrospective data and exploratory analyses.

Development of a Diagnostic Model for Pancreatic Ductal Adenocarcinoma Using Machine Learning and Blood-Based miRNAs.

INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate among all major cancers due to a lack of symptoms in early stages, early detection tools, and optimal therapies for late-stage patients. Thus, effective and non-invasive diagnostic tests are greatly needed. Recently, circulating miRNAs have been reported to be altered in PDAC. They are promising biomarkers because of stability in the blood, ease of non-invasive detection, and convenient screening methods. This study aimed to use blood-based miRNA biomarkers and various analysis methods in the development of a machine-learning (ML) model for PDAC. METHODS: Blood-based miRNAs associated with PDAC were collected from open sources. miRNA sequences, targeted genes, and involved pathways were used to construct a set of descriptors for an ML model. RESULTS: Bioinformatics analysis revealed that most genes in pancreatic cancer and insulin signaling pathways were targeted by the PDAC-related miRNAs. The best-performing ML model with the Random Forest classifier was able to achieve an accuracy of 88.4%. Model evaluations of an independent PDAC-associated miRNAs test set had 100% accuracy while non-cancer miRNAs had 52.4% accuracy, indicating specificity to PDAC. CONCLUSIONS: Our results suggest an ML model developed using blood-based miRNA biomarkers' target gene, pathway, and sequence features could be potentially implicated in PDAC diagnostics.

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.

Identification of Potential Blood-Based Biomarkers for Frailty by Using an Integrative Approach.

INTRODUCTION: Although frailty is a geriatric syndrome that is associated with disability, hospitalization, and mortality, it can be reversible and preventable with the appropriate interventions. Additionally, as the current diagnostic criteria for frailty include only physical, psychological, cognitive, and social measurements, there is a need for promising blood-based molecular biomarkers to aid in the diagnosis of frailty. METHODS: To identify candidate blood-based biomarkers that can enhance current diagnosis of frailty, we conducted a comprehensive analysis of clinical data, messenger RNA-sequencing (RNA-seq), and aging-related factors using a total of 104 older adults aged 65-90 years (61 frail subjects and 43 robust subjects) in a cross-sectional case-control study. RESULTS: We identified two candidate biomarkers of frailty from the clinical data analysis, nine from the RNA-seq analysis, and six from the aging-related factors analysis. By using combinations of the candidate biomarkers and clinical information, we constructed risk prediction models. The best models used combinations that included skeletal muscle mass index measured by dual-energy X-ray absorptiometry (adjusted p = 0.026), GDF15 (adjusted p = 1.46E-03), adiponectin (adjusted p = 0.012), CXCL9 (adjusted p = 0.011), or apelin (adjusted p = 0.020) as the biomarker. These models achieved a high area under the curve of 0.95 in an independent validation cohort (95% confidence interval: 0.79-0.97). Our risk prediction models showed significantly higher areas under the curve than did models constructed using only basic clinical information (Welch's t test p < 0.001). CONCLUSION: All five biomarkers showed statistically significant correlations with components of the frailty diagnostic criteria. We discovered several potential biomarkers for the diagnosis of frailty. Further refinement may lead to their future clinical use.

Advances and current research status of early diagnosis for gallbladder cancer.

Gallbladder cancer (GBC) is the most common malignant tumor in the biliary system, characterized by high malignancy, aggressiveness, and poor prognosis. Early diagnosis holds paramount importance in ameliorating therapeutic outcomes. Presently, the clinical diagnosis of GBC primarily relies on clinical-radiological-pathological approach. However, there remains a potential for missed diagnosis and misdiagnose in the realm of clinical practice. We firstly analyzed the blood-based biomarkers, such as carcinoembryonic antigen and carbohydrate antigen 19-9. Subsequently, we evaluated the diagnostic performance of various imaging modalities, including ultrasound (US), endoscopic ultrasound (EUS), computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography/computed tomography (PET/CT) and pathological examination, emphasizing their strengths and limitations in detecting early-stage GBC. Furthermore, we explored the potential of emerging technologies, particularly artificial intelligence (AI) and liquid biopsy, to revolutionize GBC diagnosis. AI algorithms have demonstrated improved image analysis capabilities, while liquid biopsy offers the promise of non-invasive and real-time monitoring. However, the translation of these advancements into clinical practice necessitates further validation and standardization. The review highlighted the advantages and limitations of current diagnostic approaches and underscored the need for innovative strategies to enhance diagnostic accuracy of GBC. In addition, we emphasized the importance of multidisciplinary collaboration to improve early diagnosis of GBC and ultimately patient outcomes. This review endeavoured to impart fresh perspectives and insights into the early diagnosis of GBC.

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 Aß42/Aß40 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.

Plasma Aß42/Aß40 and phospho-tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease.

INTRODUCTION: Incorporating blood-based Alzheimer's disease biomarkers such as tau and amyloid beta (Aß) into screening algorithms may improve screening efficiency. METHODS: Plasma Aß, phosphorylated tau (p-tau)181, and p-tau217 concentration levels from AHEAD 3-45 study participants were measured using mass spectrometry. Tau concentration ratios for each proteoform were calculated to normalize for inter-individual differences. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by > 20 Centiloids. Mixture of experts analysis assessed the value of including tau concentration ratios into the existing predictive algorithm for amyloid positron emission tomography status. RESULTS: The area under the receiver operating curve (AUC) was 0.87 for Aß42/Aß40, 0.74 for phosphorylated variant p-tau181 ratio (p-tau181/np-tau181), and 0.92 for phosphorylated variant p-tau217 ratio (p-tau217/np-tau217). The Plasma Predicted Centiloid (PPC), a predictive model including p-tau217/np-tau217, Aß42/Aß40, age, and apolipoprotein E improved AUC to 0.95. DISCUSSION: Including plasma p-tau217/np-tau217 along with Aß42/Aß40 in predictive algorithms may streamline screening preclinical individuals into anti-amyloid clinical trials. CLINICALTRIALS: gov Identifier: NCT04468659 HIGHLIGHTS: The addition of plasma phosphorylated variant p-tau217 ratio (p-tau217/np-tau217) significantly improved plasma biomarker algorithms for identifying preclinical amyloid positron emission tomography positivity. Prediction performance at higher NAV Centiloid levels was improved with p-tau217/np-tau217. All models generated for this study are incorporated into the Plasma Predicted Centiloid (PPC) app for public use.

Scalable plasma and digital cognitive markers for diagnosis and prognosis of Alzheimer's disease and related dementias.

INTRODUCTION: With emergence of disease-modifying therapies, efficient diagnostic pathways are critically needed to identify treatment candidates, evaluate disease severity, and support prognosis. A combination of plasma biomarkers and brief digital cognitive assessments could provide a scalable alternative to current diagnostic work-up. METHODS: We examined the accuracy of plasma biomarkers and a 10-minute supervised tablet-based cognitive assessment (Tablet-based Cognitive Assessment Tool Brain Health Assessment [TabCAT-BHA]) in predicting amyloid ß positive (Aß+) status on positron emission tomography (PET), concurrent disease severity, and functional decline in 309 older adults with subjective cognitive impairment (n = 49), mild cognitive impairment (n = 159), and dementia (n = 101). RESULTS: Combination of plasma pTau181, Aß42/40, neurofilament light (NfL), and TabCAT-BHA was optimal for predicting Aß-PET positivity (AUC = 0.962). Whereas NfL and TabCAT-BHA optimally predicted concurrent disease severity, combining these with pTau181 and glial fibrillary acidic protein was most accurate in predicting functional decline. DISCUSSION: Combinations of plasma and digital cognitive markers show promise for scalable diagnosis and prognosis of ADRD. HIGHLIGHTS: The need for cost-efficient diagnostic and prognostic markers of AD is urgent. Plasma and digital cognitive markers provide complementary diagnostic contributions. Combination of these markers holds promise for scalable diagnosis and prognosis. Future validation in community cohorts is needed to inform clinical implementation.

REAL AD-Validation of a realistic screening approach for early Alzheimer's disease.

Early diagnosis is crucial to treatment success. This is especially relevant for Alzheimer's disease (AD), with its protracted preclinical phase. Most health care systems do not have the resources to conduct large-scale AD screenings in middle-aged individuals in need of novel AD treatment options and early, accurate diagnosis. Recent developments in blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods to detect cognitive and biomarker changes that may indicate early AD. In research cohorts, promising results have been reported, but these modalities have not been validated in population-based settings. The validation of a realistic screening approach for early Alzheimer's disease (REAL AD) study aims to validate the diagnostic and prognostic performance of the combined use of blood-based biomarkers and remote cognitive testing as a screening approach for early AD employing an existing health care infrastructure (the Swedish Västra Götaland Region Primary Healthcare). REAL AD aims to provide a concrete, individualized diagnostic framework, which could significantly improve AD prognosis. HIGHLIGHTS: In Sweden, most Alzheimer's disease (AD) diagnoses are made in primary care, where access to AD biomarkers is almost non-existent. Most health care systems have limited resources for the screening of middle-aged adults for early evidence of AD pathology. Blood-based biomarkers and remote cognitive testing offer novel, cost-effective, and scalable methods for detecting cognitive and biomarker changes that may indicate early AD. The REAL AD study aims to validate the diagnostic and prognostic performance of blood-based biomarkers and remote cognitive testing as a screening approach for early AD in an existing primary health care infrastructure in the Västra Götaland Region in Sweden. Studies such as REAL AD will play a vital role in helping to move the field toward concrete implementation of biomarkers in AD diagnostic workup at all care levels, eventually providing more comprehensive treatments options for the large and growing AD population, and for those at risk.

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. GOV IDENTIFIERS: NCT02956486 (MissionAD1), NCT03036280 (MissionAD2), NCT04468659 (AHEAD3-45), NCT03887455 (ClarityAD) 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.

Association of plasma biomarkers with cognition, cognitive decline, and daily function across and within neurodegenerative diseases: Results from the Ontario Neurodegenerative Disease Research Initiative.

INTRODUCTION: We investigated whether novel plasma biomarkers are associated with cognition, cognitive decline, and functional independence in activities of daily living across and within neurodegenerative diseases. METHODS: Glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), phosphorylated tau (p-tau)181 and amyloid beta (Aß)42/40 were measured using ultra-sensitive Simoa immunoassays in 44 healthy controls and 480 participants diagnosed with Alzheimer's disease/mild cognitive impairment (AD/MCI), Parkinson's disease (PD), frontotemporal dementia (FTD) spectrum disorders, or cerebrovascular disease (CVD). RESULTS: GFAP, NfL, and/or p-tau181 were elevated among all diseases compared to controls, and were broadly associated with worse baseline cognitive performance, greater cognitive decline, and/or lower functional independence. While GFAP, NfL, and p-tau181 were highly predictive across diseases, p-tau181 was more specific to the AD/MCI cohort. Sparse associations were found in the FTD and CVD cohorts and for Aß42/40 . DISCUSSION: GFAP, NfL, and p-tau181 are valuable predictors of cognition and function across common neurodegenerative diseases, and may be useful in specialized clinics and clinical trials.

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.

Considerations for widespread implementation of blood-based biomarkers of Alzheimer's disease.

Diagnosing Alzheimer's disease (AD) poses significant challenges to health care, often resulting in delayed or inadequate patient care. The clinical integration of blood-based biomarkers (BBMs) for AD holds promise in enabling early detection of pathology and timely intervention. However, several critical considerations, such as the lack of consistent guidelines for assessing cognition, limited understanding of BBM test characteristics, insufficient evidence on BBM performance across diverse populations, and the ethical management of test results, must be addressed for widespread clinical implementation of BBMs in the United States. The Global CEO Initiative on Alzheimer's Disease BBM Workgroup convened to address these challenges and provide recommendations that underscore the importance of evidence-based guidelines, improved training for health-care professionals, patient empowerment through informed decision making, and the necessity of community-based studies to understand BBM performance in real-world populations. Multi-stakeholder engagement is essential to implement these recommendations and ensure credible guidance and education are accessible to all stakeholders.

Recommendations for clinical implementation of blood-based biomarkers for Alzheimer's disease.

Blood-based biomarkers (BBM) for Alzheimer's disease (AD) are being increasingly used in clinical practice to support an AD diagnosis. In contrast to traditional diagnostic modalities, such as amyloid positron emission tomography and cerebrospinal fluid biomarkers, BBMs offer a more accessible and lower cost alternative for AD biomarker testing. Their unique scalability addresses the anticipated surge in demand for biomarker testing with the emergence of disease-modifying treatments (DMTs) that require confirmation of amyloid pathology. To facilitate the uptake of BBMs in clinical practice, The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to provide recommendations for two clinical implementational pathways for BBMs: one for current use for triaging and another for future use to confirm amyloid pathology. These pathways provide a standardized diagnostic approach with guidance on interpreting BBM test results. Integrating BBMs into clinical practice will simplify the diagnostic process and facilitate timely access to DMTs for eligible patients.

Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays.

INTRODUCTION: We aimed to evaluate clinical interpretation cutpoints for two plasma phosphorylated tau (p-tau)217 assays (ALZpath and Lumipulse) as predictors of amyloid status for implementation in clinical practice. METHODS: Clinical performance of plasma p-tau217 against amyloid positron emission tomography status was evaluated in participants with mild cognitive impairment or mild dementia (n = 427). RESULTS: Using a one-cutpoint approach (negative/positive), neither assay achieved ≥ 90% in both sensitivity and specificity. A two-cutpoint approach yielding 92% sensitivity and 96% specificity provided the desired balance of false positives and false negatives, while categorizing 20% and 39% of results as indeterminate for the Lumipulse and ALZpath assays, respectively. DISCUSSION: This study provides a systematic framework for selection of assay-specific cutpoints for clinical use of plasma p-tau217 for determination of amyloid status. Our findings suggest that a two-cutpoint approach may have advantages in optimizing diagnostic accuracy while minimizing potential harm from false positive results. HIGHLIGHTS: Phosphorylated tau (p-tau)217 cutpoints for detection of amyloid pathology were established. A two-cutpoint approach exhibited the best performance for clinical laboratory use. p-tau217 assays differed in the percentage of results categorized as intermediate.

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.

Blood-Based Biomarkers in Alzheimer's Disease: Advancing Non-Invasive Diagnostics and Prognostics.

Alzheimer's disease (AD), the most prevalent form of dementia, is expected to rise dramatically in incidence due to the global population aging. Traditional diagnostic approaches, such as cerebrospinal fluid analysis and positron emission tomography, are expensive and invasive, limiting their routine clinical use. Recent advances in blood-based biomarkers, including amyloid-beta, phosphorylated tau, and neurofilament light, offer promising non-invasive alternatives for early AD detection and disease monitoring. This review synthesizes current research on these blood-based biomarkers, highlighting their potential to track AD pathology and enhance diagnostic accuracy. Furthermore, this review uniquely integrates recent findings on protein-protein interaction networks and microRNA pathways, exploring novel combinations of proteomic, genomic, and epigenomic biomarkers that provide new insights into AD's molecular mechanisms. Additionally, we discuss the integration of these biomarkers with advanced neuroimaging techniques, emphasizing their potential to revolutionize AD diagnostics. Although large-scale validation is still needed, these biomarkers represent a critical advancement toward more accessible, cost-effective, and early diagnostic tools for AD.