Assessment of a Plasma Amyloid Probability Score to Estimate Amyloid Positron Emission Tomography Findings Among Adults With Cognitive Impairment

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 (Aβ) 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.

Blood Biomarkers to Detect Alzheimer Disease in Primary Care and Secondary Care

Importance

An accurate blood test for Alzheimer disease (AD) could streamline the diagnostic workup and treatment of AD.

Objective

To prospectively evaluate a clinically available AD blood test in primary care and secondary care using predefined biomarker cutoff values.

Design, Setting, and Participants

There were 1213 patients undergoing clinical evaluation due to cognitive symptoms who were examined between February 2020 and January 2024 in Sweden. The biomarker cutoff values had been established in an independent cohort and were applied to a primary care cohort (n = 307) and a secondary care cohort (n = 300); 1 plasma sample per patient was analyzed as part of a single batch for each cohort. The blood test was then evaluated prospectively in the primary care cohort (n = 208) and in the secondary care cohort (n = 398); 1 plasma sample per patient was sent for analysis within 2 weeks of collection.

Exposure

Blood tests based on plasma analyses by mass spectrometry to determine the ratio of plasma phosphorylated tau 217 (p-tau217) to non-p-tau217 (expressed as percentage of p-tau217) alone and when combined with the amyloid-β 42 and amyloid-β 40 (Aβ42:Aβ40) plasma ratio (the amyloid probability score 2 [APS2]).

Main Outcomes and Measures

The primary outcome was AD pathology (determined by abnormal cerebrospinal fluid Aβ42:Aβ40 ratio and p-tau217). The secondary outcome was clinical AD. The positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy, and area under the curve (AUC) values were calculated.

Results

The mean age was 74.2 years (SD, 8.3 years), 48% were women, 23% had subjective cognitive decline, 44% had mild cognitive impairment, and 33% had dementia. In both the primary care and secondary care assessments, 50% of patients had AD pathology. When the plasma samples were analyzed in a single batch in the primary care cohort, the AUC was 0.97 (95% CI, 0.95-0.99) when the APS2 was used, the PPV was 91% (95% CI, 87%-96%), and the NPV was 92% (95% CI, 87%-96%); in the secondary care cohort, the AUC was 0.96 (95% CI, 0.94-0.98) when the APS2 was used, the PPV was 88% (95% CI, 83%-93%), and the NPV was 87% (95% CI, 82%-93%). When the plasma samples were analyzed prospectively (biweekly) in the primary care cohort, the AUC was 0.96 (95% CI, 0.94-0.98) when the APS2 was used, the PPV was 88% (95% CI, 81%-94%), and the NPV was 90% (95% CI, 84%-96%); in the secondary care cohort, the AUC was 0.97 (95% CI, 0.95-0.98) when the APS2 was used, the PPV was 91% (95% CI, 87%-95%), and the NPV was 91% (95% CI, 87%-95%). The diagnostic accuracy was high in the 4 cohorts (range, 88%-92%). Primary care physicians had a diagnostic accuracy of 61% (95% CI, 53%-69%) for identifying clinical AD after clinical examination, cognitive testing, and a computed tomographic scan vs 91% (95% CI, 86%-96%) using the APS2. Dementia specialists had a diagnostic accuracy of 73% (95% CI, 68%-79%) vs 91% (95% CI, 88%-95%) using the APS2. In the overall population, the diagnostic accuracy using the APS2 (90% [95% CI, 88%-92%]) was not different from the diagnostic accuracy using the percentage of p-tau217 alone (90% [95% CI, 88%-91%]).

Conclusions and Relevance

The APS2 and percentage of p-tau217 alone had high diagnostic accuracy for identifying AD among individuals with cognitive symptoms in primary and secondary care using predefined cutoff values. Future studies should evaluate how the use of blood tests for these biomarkers influences clinical care.

Baseline levels and longitudinal changes in plasma Aβ42/40 among Black and white individuals

Blood-based biomarkers of Alzheimer disease (AD) may facilitate testing of historically under-represented groups. The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to compare AD biomarkers in participants who identify their race as either Black or white. Plasma samples from 324 Black and 1,547 white participants underwent analysis with C2N Diagnostics' PrecivityAD test for Aβ42 and Aβ40. Compared to white individuals, Black individuals had higher average plasma Aβ42/40 levels at baseline, consistent with a lower average level of amyloid pathology. Interestingly, this difference resulted from lower average levels of plasma Aβ40 in Black participants. Despite the differences, Black and white individuals had similar longitudinal rates of change in Aβ42/40, consistent with a similar rate of amyloid accumulation. Our results agree with multiple recent studies demonstrating a lower prevalence of amyloid pathology in Black individuals, and additionally suggest that amyloid accumulates consistently across both groups.

NODDI in gray matter is a sensitive marker of aging and early AD changes

INTRODUCTION

Age-related and Alzheimer's disease (AD) dementia-related neurodegeneration impact brain health. While morphometric measures from T1-weighted scans are established biomarkers, they may be less sensitive to earlier changes. Neurite orientation dispersion and density imaging (NODDI), offering biologically meaningful interpretation of tissue microstructure, may be an advanced brain health biomarker.

METHODS

We contrasted regional gray matter NODDI and morphometric evaluations concerning their correlation with (1) age, (2) clinical diagnosis stage, and (3) tau pathology as assessed by AV1451 positron emission tomography.

RESULTS

Our study hypothesizes that NODDI measures are more sensitive to aging and early AD changes than morphometric measures. One NODDI output, free water fraction (FWF), showed higher sensitivity to age-related changes, generally better effect sizes in separating mild cognitively impaired from cognitively unimpaired participants, and stronger associations with regional tau deposition than morphometric measures.

DISCUSSION

These findings underscore NODDI's utility in capturing early neurodegenerative changes and enhancing our understanding of aging and AD.

Highlights

Neurite orientation dispersion and density imaging can serve as an effective brain health biomarker for aging and early Alzheimer's disease (AD).Free water fraction has higher sensitivity to normal brain aging.Free water fraction has stronger associations with early AD and regional tau deposition.

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 (Aβ) 42/Aβ40 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 Aβ42/Aβ40 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 Aβ42/Aβ40 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 Aβ42/Aβ40's range. Combining it with plasma Aβ42/Aβ40 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 Aβ42/Aβ40 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.

Linking Dementia Pathology and Alteration in Brain Activation to Complex Daily Functional Decline During the Preclinical Dementia Stages: Protocol for a Prospective Observational Cohort Study

BACKGROUND

Progressive difficulty in performing everyday functional activities is a key diagnostic feature of dementia syndromes. However, not much is known about the neural signature of functional decline, particularly during the very early stages of dementia. Early intervention before overt impairment is observed offers the best hope of reducing the burdens of Alzheimer disease (AD) and other dementias. However, to justify early intervention, those at risk need to be detected earlier and more accurately. The decline in complex daily function (CdF) such as managing medications has been reported to precede impairment in basic activities of daily living (eg, eating and dressing).

OBJECTIVE

Our goal is to establish the neural signature of decline in CdF during the preclinical dementia period.

METHODS

Gait is central to many CdF and community-based activities. Hence, to elucidate the neural signature of CdF, we validated a novel electroencephalographic approach to measuring gait-related brain activation while participants perform complex gait-based functional tasks. We hypothesize that dementia-related pathology during the preclinical period activates a unique gait-related electroencephalographic (grEEG) pattern that predicts a subsequent decline in CdF.

RESULTS

We provide preliminary findings showing that older adults reporting CdF limitations can be characterized by a unique gait-related neural signature: weaker sensorimotor and stronger motor control activation. This subsample also had smaller brain volume and white matter hyperintensities in regions affected early by dementia and engaged in less physical exercise. We propose a prospective observational cohort study in cognitively unimpaired older adults with and without subclinical AD (plasma amyloid-β) and vascular (white matter hyperintensities) pathologies. We aim to (1) establish the unique grEEG activation as the neural signature and predictor of decline in CdF during the preclinical dementia period; (2) determine associations between dementia-related pathologies and incidence of the neural signature of CdF; and (3) establish associations between a dementia risk factor, physical inactivity, and the neural signature of CdF.

CONCLUSIONS

By establishing the clinical relevance and biological basis of the neural signature of CdF decline, we aim to improve prediction during the preclinical stages of ADs and other dementias. Our approach has important research and translational implications because grEEG protocols are relatively inexpensive and portable, and predicting CdF decline may have real-world benefits.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/56726.

Use of a Blood Biomarker Test Improves Economic Utility in the Evaluation of Older Patients Presenting with Cognitive Impairment

More than 16 million Americans living with cognitive impairment warrant a diagnostic evaluation to determine the cause of this disorder. The recent availability of disease-modifying therapies for Alzheimer's disease (AD) is expected to significantly drive demand for such diagnostic testing. Accurate, accessible, and affordable methods are needed. Blood biomarkers (BBMs) offer advantages over usual care amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in these regards. This study used a budget impact model to assess the economic utility of the PrecivityAD® blood test, a clinically validated BBM test for the evaluation of brain amyloid, a pathological hallmark of AD. The model compared 2 scenarios: (1) baseline testing involving usual care practice, and (2) early use of a BBM test before usual care CSF and PET biomarker use. At a modest 40% adoption rate, the BBM test scenario had comparable sensitivity and specificity to the usual care scenario and showed net savings in the diagnostic work-up of $3.57 million or $0.30 per member per month in a 1 million member population, translating to over $1B when extrapolated to the US population as a whole and representing a 11.4% cost reduction. Savings were driven by reductions in the frequency and need for CSF and PET testing. Additionally, BBM testing was associated with a cost savings of $643 per AD case identified. Use of the PrecivityAD blood test in the clinical care pathway may prevent unnecessary testing, provide cost savings, and reduce the burden on both patients and health plans.

New plasma LC-MS/MS assays for the quantitation of beta-amyloid peptides and identification of apolipoprotein E proteoforms for Alzheimer's disease risk assessment

Early detection of Alzheimer's disease (AD) represents an unmet clinical need. Beta-amyloid (Aβ) plays an important role in AD pathology, and the Aβ42/40 peptide ratio is a good indicator for amyloid deposition. In addition, variants of the apolipoprotein E (APOE) gene are associated with variable AD risk. Here, we describe the development and validation of high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) assays for plasma Aβ40 and Aβ42 quantitation, as well as apolipoprotein E (ApoE) proteotype determination as a surrogate for APOE genotype. Aβ40 and Aβ42 were simultaneously immunoprecipitated from plasma, proteolytically digested, and quantitated by LC-MS/MS. ApoE proteotype status was qualitatively assessed by targeting tryptic peptides from the ApoE2, ApoE3, and ApoE4 proteoforms. Both assays were validated according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. Within-run precision was 1.8%-4.2% (Aβ40), 1.9%-7.2% (Aβ42), and 2.6%-8.3% (Aβ42/40 ratio). Between-run precision was 3.5%-5.9% (Aβ40), 3.8%-8.0% (Aβ42), and 3.3%-8.7% (Aβ42/40 ratio). Both Aβ40 and Aβ42 were linear from 10 to 2500 pg/mL. Identified ApoE proteotypes had 100% concordance with APOE genotypes. We have developed a precise, accurate, and sensitive high-throughput LC-MS/MS assay for plasma Aβ40, Aβ42, and proteoforms of ApoE.

Clinical validation of the PrecivityAD2 blood test: A mass spectrometry-based test with algorithm combining %p-tau217 and Aβ42/40 ratio to identify presence of brain amyloid

BACKGROUND

With the availability of disease-modifying therapies for Alzheimer's disease (AD), it is important for clinicians to have tests to aid in AD diagnosis, especially when the presence of amyloid pathology is a criterion for receiving treatment.

METHODS

High-throughput, mass spectrometry-based assays were used to measure %p-tau217 and amyloid beta (Aβ)42/40 ratio in blood samples from 583 individuals with suspected AD (53% positron emission tomography [PET] positive by Centiloid > 25). An algorithm (PrecivityAD2 test) was developed using these plasma biomarkers to identify brain amyloidosis by PET.

RESULTS

The area under the receiver operating characteristic curve (AUC-ROC) for %p-tau217 (0.94) was statistically significantly higher than that for p-tau217 concentration (0.91). The AUC-ROC for the PrecivityAD2 test output, the Amyloid Probability Score 2, was 0.94, yielding 88% agreement with amyloid PET. Diagnostic performance of the APS2 was similar by ethnicity, sex, age, and apoE4 status.

DISCUSSION

The PrecivityAD2 blood test showed strong clinical validity, with excellent agreement with brain amyloidosis by PET.

Utilization of fluid-based biomarkers as endpoints in disease-modifying clinical trials for Alzheimer's disease: a systematic review

BACKGROUND

Clinical trials in Alzheimer's disease (AD) had high failure rates for several reasons, including the lack of biological endpoints. Fluid-based biomarkers may present a solution to measure biologically relevant endpoints. It is currently unclear to what extent fluid-based biomarkers are applied to support drug development.

METHODS

We systematically reviewed 272 trials (clinicaltrials.gov) with disease-modifying therapies starting between 01-01-2017 and 01-01-2024 and identified which CSF and/or blood-based biomarker endpoints were used per purpose and trial type.

RESULTS

We found that 44% (N = 121) of the trials employed fluid-based biomarker endpoints among which the CSF ATN biomarkers (Aβ (42/40), p/tTau) were used most frequently. In blood, inflammatory cytokines, NFL, and pTau were most frequently employed. Blood- and CSF-based biomarkers were used approximately equally. Target engagement biomarkers were used in 26% (N = 72) of the trials, mainly in drugs targeting inflammation and amyloid. Lack of target engagement markers is most prominent in synaptic plasticity/neuroprotection, neurotransmitter receptor, vasculature, epigenetic regulators, proteostasis and, gut-brain axis targeting drugs. Positive biomarker results did not always translate to cognitive effects, most commonly the small significant reductions in CSF tau isoforms that were seen following anti-Tau treatments. On the other hand, the positive anti-amyloid trials results on cognitive function were supported by clear effect in most fluid markers.

CONCLUSIONS

As the field moves towards primary prevention, we expect an increase in the use of fluid-based biomarkers to determine disease modification. Use of blood-based biomarkers will rapidly increase, but CSF markers remain important to determine brain-specific treatment effects. With improving techniques, new biomarkers can be found to diversify the possibilities in measuring treatment effects and target engagement. It remains important to interpret biomarker results in the context of the trial and be aware of the performance of the biomarker. Diversifying biomarkers could aid in the development of surrogacy biomarkers for different drug targets.

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.

Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches

Alzheimer's disease has an increasing prevalence in the population world-wide, yet current diagnostic methods based on recommended biomarkers are only available in specialized clinics. Due to these circumstances, Alzheimer's disease is usually diagnosed late, which contrasts with the currently available treatment options that are only effective for patients at an early stage. Blood-based biomarkers could fill in the gap of easily accessible and low-cost methods for early diagnosis of the disease. In particular, immune-based blood-biomarkers might be a promising option, given the recently discovered cross-talk of immune cells of the central nervous system with those in the peripheral immune system. Here, we give a background on recent advances in research on brain-immune system cross-talk in Alzheimer's disease and review machine learning approaches, which can combine multiple biomarkers with further information (e.g. age, sex, APOE genotype) into predictive models supporting an earlier diagnosis. In addition, mechanistic modeling approaches, such as agent-based modeling open the possibility to model and analyze cell dynamics over time. This review aims to provide an overview of the current state of immune-system related blood-based biomarkers and their potential for the early diagnosis of Alzheimer's disease.

Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Executive Summary of 2023 International Conference of the Korean Dementia Association (IC-KDA 2023): A Report From the Academic Committee of the Korean Dementia Association

The Korean Dementia Association (KDA) has been organizing biennial international academic conferences since 2019, with the International Conference of the KDA (IC-KDA) 2023 held in Busan under the theme 'Beyond Boundaries: Advancing Global Dementia Solutions.' The conference comprised 6 scientific sessions, 3 plenary lectures, and 4 luncheon symposiums, drawing 804 participants from 35 countries. Notably, a Korea-Taiwan Joint Symposium addressed insights into Alzheimer's disease (AD). Plenary lectures by renowned scholars explored topics such as microbiome-related AD pathogenesis, social cognition in neurodegenerative diseases, and genetic frontotemporal dementia (FTD). On the first day, specific presentations covered subjects like the gut-brain axis and neuroinflammation in dementia, blood-based biomarkers in AD, and updates in AD therapeutics. The second day's presentations addressed recent issues in clinical neuropsychology, FTD cohort studies, and the pathogenesis of non-AD dementia. The Academic Committee of the KDA compiles lecture summaries to provide comprehensive understanding of the advanced dementia knowledge presented at IC-KDA 2023.

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-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 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 Aβ1-42/Aβ1-40 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.

Sensitivity of the African neuropsychology battery memory subtests and learning slopes in discriminating APOE 4 and amyloid pathology in adult individuals in the Democratic Republic of Congo

Background

The current study examined the sensitivity of two memory subtests and their corresponding learning slope metrics derived from the African Neuropsychology Battery (ANB) to detect amyloid pathology and APOEε4 status in adults from Kinshasa, the Democratic Republic of the Congo.

Methods

85 participants were classified for the presence of β-amyloid pathology and based on allelic presence of APOEε4 using Simoa. All participants were screened using CSID and AQ, underwent verbal and visuospatial memory testing from ANB, and provided blood samples for plasma Aβ42, Aβ40, and APOE proteotype. Pearson correlation, linear and logistic regression were conducted to compare amyloid pathology and APOEε4 status with derived learning scores, including initial learning, raw learning score, learning over trials, and learning ratio.

Results

Our sample included 35 amyloid positive and 44 amyloid negative individuals as well as 42 without and 39 with APOEε4. All ROC AUC ranges for the prediction of amyloid pathology based on learning scores were low, ranging between 0.56-0.70 (95% CI ranging from 0.44-0.82). The sensitivity of all the scores ranged between 54.3-88.6, with some learning metrics demonstrating good sensitivity. Regarding APOEε4 prediction, all AUC values ranged between 0.60-0.69, with all sensitivity measures ranging between 53.8-89.7. There were minimal differences in the AUC values across learning slope metrics, largely due to the lack of ceiling effects in this sample.

Discussion

This study demonstrates that some ANB memory subtests and learning slope metrics can discriminate those that are normal from those with amyloid pathology and those with and without APOEε4, consistent with findings reported in Western populations.

Clinical utility of plasma Aβ42/40 ratio by LC-MS/MS in Alzheimer's disease assessment

Introduction

Plasma Aβ42/40 ratio can help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear.

Methods

Aβ42/40 ratio was measured by LC-MS/MS for 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and for 6,192 consecutive clinical specimens submitted for Aβ42/40 testing.

Results

High diagnostic sensitivity and negative predictive value (NPV) for Aβ-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aβ42/40 values for individuals with positive vs. negative Aβ-PET results. Assuming a moderate prevalence of Aβ-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%.

Conclusion

High-throughput plasma Aβ42/40 LC-MS/MS assays can help identify patients with low likelihood of AD pathology, which can reduce PET evaluations, allowing for cost savings.

Plasma Aβ42/Aβ40 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 (Aβ) into screening algorithms may improve screening efficiency.

METHODS

Plasma Aβ, 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 Aβ42/Aβ40, 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, Aβ42/Aβ40, age, and apolipoprotein E improved AUC to 0.95.

DISCUSSION

Including plasma p-tau217/np-tau217 along with Aβ42/Aβ40 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.

Comparative methods for quantifying plasma biomarkers in Alzheimer's disease: Implications for the next frontier in cerebral amyloid angiopathy diagnostics

Plasma amyloid beta (Aβ) and tau are emerging as accessible biomarkers for Alzheimer's disease (AD). However, many assays exist with variable test performances, highlighting the need for a comparative assessment to identify the most valid assays for future use in AD and to apply to other settings in which the same biomarkers may be useful, namely, cerebral amyloid angiopathy (CAA). CAA is a progressive cerebrovascular disease characterized by deposition of Aβ40 and Aβ42 in cortical and leptomeningeal vessels. Novel immunotherapies for AD can induce amyloid-related imaging abnormalities resembling CAA-related inflammation. Few studies have evaluated plasma biomarkers in CAA. Identifying a CAA signature could facilitate diagnosis, prognosis, and a safer selection of patients with AD for emerging immunotherapies. This review evaluates studies that compare the diagnostic test performance of plasma biomarker techniques in AD and cerebrovascular and plasma biomarker profiles of CAA; it also discusses novel hypotheses and future avenues for plasma biomarker research in CAA.

Associations of sleep duration and daytime sleepiness with plasma amyloid beta and cognitive performance in cognitively unimpaired, middle-aged and older African Americans

STUDY OBJECTIVES

Given the established racial disparities in both sleep health and dementia risk for African American populations, we assess cross-sectional and longitudinal associations of self-report sleep duration (SRSD) and daytime sleepiness with plasma amyloid beta (Aβ) and cognition in an African American (AA) cohort.

METHODS

In a cognitively unimpaired sample drawn from the African Americans Fighting Alzheimer's in Midlife (AA-FAiM) study, data on SRSD, Epworth Sleepiness Scale, demographics, and cognitive performance were analyzed. Aβ40, Aβ42, and the Aβ42/40 ratio were quantified from plasma samples. Cross-sectional analyses explored associations between baseline predictors and outcome measures. Linear mixed-effect regression models estimated associations of SRSD and daytime sleepiness with plasma Aβ and cognitive performance levels and change over time.

RESULTS

One hundred and forty-seven participants comprised the cross-sectional sample. Baseline age was 63.2 ± 8.51 years. 69.6% self-identified as female. SRSD was 6.4 ± 1.1 hours and 22.4% reported excessive daytime sleepiness. The longitudinal dataset included 57 participants. In fully adjusted models, neither SRSD nor daytime sleepiness is associated with cross-sectional or longitudinal Aβ. Associations with level and trajectory of cognitive test performance varied by measure of sleep health.

CONCLUSIONS

SRSD was below National Sleep Foundation recommendations and daytime sleepiness was prevalent in this cohort. In the absence of observed associations with plasma Aβ, poorer self-reported sleep health broadly predicted poorer cognitive function but not accelerated decline. Future research is necessary to understand and address modifiable sleep mechanisms as they relate to cognitive aging in AA at disproportionate risk for dementia.

CLINICAL TRIAL INFORMATION

Not applicable.

Baseline levels and longitudinal rates of change in plasma Aβ42/40 among self-identified Black/African American and White individuals

Objective

The use of blood-based biomarkers of Alzheimer disease (AD) may facilitate access to biomarker testing of groups that have been historically under-represented in research. We evaluated whether plasma Aβ42/40 has similar or different baseline levels and longitudinal rates of change in participants racialized as Black or White.

Methods

The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to evaluate for potential differences in AD biomarkers between individuals racialized as Black or White. Plasma samples collected at three AD Research Centers (Washington University, University of Pennsylvania, and University of Alabama-Birmingham) underwent analysis with C2N Diagnostics' PrecivityAD™ blood test for Aβ42 and Aβ40. General linear mixed effects models were used to estimate the baseline levels and rates of longitudinal change for plasma Aβ measures in both racial groups. Analyses also examined whether dementia status, age, sex, education, APOE ε4 carrier status, medical comorbidities, or fasting status modified potential racial differences.

Results

Of the 324 Black and 1,547 White participants, there were 158 Black and 759 White participants with plasma Aβ measures from at least two longitudinal samples over a mean interval of 6.62 years. At baseline, the group of Black participants had lower levels of plasma Aβ40 but similar levels of plasma Aβ42 as compared to the group of White participants. As a result, baseline plasma Aβ42/40 levels were higher in the Black group than the White group, consistent with the Black group having lower levels of amyloid pathology. Racial differences in plasma Aβ42/40 were not modified by age, sex, education, APOE ε4 carrier status, medical conditions (hypertension and diabetes), or fasting status. Despite differences in baseline levels, the Black and White groups had a similar longitudinal rate of change in plasma Aβ42/40.

Interpretation

Black individuals participating in AD research studies had a higher mean level of plasma Aβ42/40, consistent with a lower level of amyloid pathology, which, if confirmed, may imply a lower proportion of Black individuals being eligible for AD clinical trials in which the presence of amyloid is a prerequisite. However, there was no significant racial difference in the rate of change in plasma Aβ42/40, suggesting that amyloid pathology accumulates similarly across racialized groups.

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-β42/40 (Aβ42/40). 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 Aβ42/40 biomarkers. Relationships between the biomarkers and cognitive performance were analyzed using multiple linear regression models.

RESULTS

Lower plasma Aβ42/40 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.

Clinical utility of plasma Aβ42/40 ratio by LC-MS/MS in Alzheimer's disease assessment

INTRODUCTION

Plasma Aβ42/40 ratio can be used to help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear.

METHODS

Aβ42/40 ratio was measured by LC-MS/MS in 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and 6,192 consecutive clinical specimens submitted for Aβ42/40 testing.

RESULTS

High diagnostic sensitivity and negative predictive value (NPV) for Aβ-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aβ42/40 values for individuals with positive vs negative Aβ-PET results. Assuming a moderate prevalence of Aβ-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%.

DISCUSSION

Using high-throughput plasma Aβ42/40 LC-MS/MS assays can help reduce PET evaluations in patients with low likelihood of AD pathology, allowing for cost savings.

Design and feasibility of an Alzheimer's disease blood test study in a diverse community-based population

INTRODUCTION

Alzheimer's disease (AD) blood tests are likely to become increasingly important in clinical practice, but they need to be evaluated in diverse groups before use in the general population.

METHODS

This study enrolled a community-based sample of older adults in the St. Louis, Missouri, USA area. Participants completed a blood draw, Eight-Item Informant Interview to Differentiate Aging and Dementia (AD8® ), Montreal Cognitive Assessment (MoCA), and survey about their perceptions of the blood test. A subset of participants completed additional blood collection, amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), and Clinical Dementia Rating (CDR® ).

RESULTS

Of the 859 participants enrolled in this ongoing study, 20.6% self-identified as Black or African American. The AD8 and MoCA correlated moderately with the CDR. The blood test was well accepted by the cohort, but it was perceived more positively by White and highly educated individuals.

DISCUSSION

Studying an AD blood test in a diverse population is feasible and may accelerate accurate diagnosis and implementation of effective treatments.

HIGHLIGHTS

A diverse group of older adults was recruited to evaluate a blood amyloid test. The enrollment rate was high and the blood test was well accepted by participants. Cognitive impairment screens have moderate performance in a diverse population. Alzheimer's disease blood tests are likely to be feasible for use in real-world settings.

Genetic risk scores enhance the diagnostic value of plasma biomarkers of brain amyloidosis

Blood-based biomarkers offer strong potential to revolutionize diagnosis, trial enrolment and treatment monitoring in Alzheimer's disease (AD). However, further advances are needed before these biomarkers can achieve wider deployment beyond selective research studies and specialty memory clinics, including the development of frameworks for optimal interpretation of biomarker profiles. We hypothesized that integrating Alzheimer's disease genetic risk score (AD-GRS) data would enhance the diagnostic value of plasma AD biomarkers by better capturing extant disease heterogeneity. Analysing 962 individuals from a population-based sample, we observed that an AD-GRS was independently associated with amyloid PET levels (an early marker of AD pathophysiology) over and above APOE ε4 or plasma p-tau181, amyloid-β42/40, glial fibrillary acidic protein or neurofilament light chain. Among individuals with a high or moderately high plasma p-tau181, integrating AD-GRS data significantly improved classification accuracy of amyloid PET positivity, including the finding that the combination of a high AD-GRS and high plasma p-tau181 outperformed p-tau181 alone in classifying amyloid PET positivity (88% versus 68%; P = 0.001). A machine learning approach incorporating plasma biomarkers, demographics and the AD-GRS was highly accurate in predicting amyloid PET levels (90% training set; 89% test set) and Shapley value analyses (an explainer method based in cooperative game theory) indicated that the AD-GRS and plasma biomarkers had differential importance in explaining amyloid deposition across individuals. Polygenic risk for AD dementia appears to account for a unique portion of disease heterogeneity, which could non-invasively enhance the interpretation of blood-based AD biomarker profiles in the population.

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-β42/40 (Aβ42/40). 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 Aβ42/40 biomarkers. Relationships between the biomarkers and cognitive performance were analyzed using multiple linear regression models.

Results

Lower plasma Aβ42/40 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 APOE e4 allele, did not alter these relationships.

Conclusion

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.

Plasma ATN(I) classification and precision pharmacology in Alzheimer's disease

Evaluating potential therapies for Alzheimer's disease (AD) depends on use of biomarkers for appropriate subject selection and monitoring disease progression. Biomarkers that predict onset of clinical symptoms are particularly important for AD because they enable intervention before irreversible neurodegeneration occurs. The amyloid-β-tau-neurodegeneration (ATN) classification system is currently used as a biological staging model for AD and is based on three classes of biomarkers evaluating amyloid-β (Aβ), tau pathology and neurodegeneration or neuronal injury. Promising blood-based biomarkers for each of these categories have been identified (Aβ42/Aβ40 ratio, phosphorylated tau, neurofilament light chain), and this matrix is now being expanded toward an ATN(I) system, where "I" represents a neuroinflammatory biomarker. The plasma ATN(I) system, together with APOE genotyping, offers a basis for individualized evaluation and a move away from the classic "one size fits all" approach toward a biomarker-driven individualisation of therapy for patients with AD.

Plasma biomarkers identify older adults at risk of Alzheimer's disease and related dementias in a real-world population-based cohort

INTRODUCTION

Plasma biomarkers-cost effective, non-invasive indicators of Alzheimer's disease (AD) and related disorders (ADRD)-have largely been studied in clinical research settings. Here, we examined plasma biomarker profiles and their associated factors in a population-based cohort to determine whether they could identify an at-risk group, independently of brain and cerebrospinal fluid biomarkers.

METHODS

We measured plasma phosphorylated tau181 (p-tau181), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and amyloid beta (Aβ)42/40 ratio in 847 participants from a population-based cohort in southwestern Pennsylvania.

RESULTS

K-medoids clustering identified two distinct plasma Aβ42/40 modes, further categorizable into three biomarker profile groups: normal, uncertain, and abnormal. In different groups, plasma p-tau181, NfL, and GFAP were inversely correlated with Aβ42/40, Clinical Dementia Rating, and memory composite score, with the strongest associations in the abnormal group.

DISCUSSION

Abnormal plasma Aβ42/40 ratio identified older adult groups with lower memory scores, higher dementia risks, and higher ADRD biomarker levels, with potential implications for population screening.

HIGHLIGHTS

Population-based plasma biomarker studies are lacking, particularly in cohorts without cerebrospinal fluid or neuroimaging data. In the Monongahela-Youghiogheny Healthy Aging Team study (n = 847), plasma biomarkers associated with worse memory and Clinical Dementia Rating (CDR), apolipoprotein E ε4, and greater age. Plasma amyloid beta (Aβ)42/40 ratio levels allowed clustering participants into abnormal, uncertain, and normal groups. Plasma Aβ42/40 correlated differently with neurofilament light chain, glial fibrillary acidic protein, phosphorylated tau181, memory composite, and CDR in each group. Plasma biomarkers can enable relatively affordable and non-invasive community screening for evidence of Alzheimer's disease and related disorders pathophysiology.

Association of plasma biomarkers with cognitive function in persons with dementia and cognitively healthy in the Democratic Republic of Congo

Introduction

This study investigates whether plasma biomarkers (Aβ42/40 and p-tau 181), APS, as well as apolipoprotein E (APOE) proteotype predict cognitive deficits in elderly adults from the Democratic Republic of Congo.

Methods

Forty-four with possible AD (pAD) and 41 healthy control (HC) subjects were screened using CSID and AQ, underwent cognitive assessment with the African Neuropsychology Battery (ANB), and provided blood samples for plasma Aβ42, Aβ40, Aβ42/40, and APOE proteotype. Linear and logistic regression were used to evaluate the associations of plasma biomarkers with ANB tests and the ability of biomarkers to predict cognitive status.

Results

Patients with pAD had significantly lower plasma Aβ42/40 levels, higher APS, and higher prevalence of APOE E4 allele compared to HC. Groups did not differ in levels of Aβ40, Aβ42, or P-tau 181. Results showed that Aβ42/40 ratio and APS were significantly associated with African Naming Test (ANT), African List Memory Test (ALMT), and African Visuospatial Memory Test (AVMT) scores, while the presence of APOE E4 allele was associated with ANT, ALMT, AVMT, and APT scores. P-tau 181 did not show any significant associations while adjusting for age, education, and gender. APS showed the highest area under the curve (AUC) value (AUC = 0.78, 95% confidence interval [CI]: 0.68-0.88) followed by Aβ42/40 (AUC = 0.75, 95% CI: 0.66-0.86) and APOE E4 (AUC = 0.69 (CI 0.57-0.81) in discriminating pAD from HC.

Discussion

These results demonstrate associations between select plasma biomarker of AD pathology (Aβ42/40), APS, and APOE E4 allele) and ANB test scores and the ability of these biomarkers to differentiate pAD from cognitively normal SSA individuals, consistent with findings reported in other settings.

A blood biomarker test for brain amyloid impacts the clinical evaluation of cognitive impairment

OBJECTIVE

The objective of this study was to examine clinicians' patient selection and result interpretation of a clinically validated mass spectrometry test measuring amyloid beta and ApoE blood biomarkers combined with patient age (PrecivityAD® blood test) in symptomatic patients evaluated for Alzheimer's disease (AD) or other causes of cognitive decline.

METHODS

The Quality Improvement and Clinical Utility PrecivityAD Clinician Survey (QUIP I, ClinicalTrials.gov Identifier: NCT05477056) was a prospective, single-arm cohort study among 366 patients evaluated by neurologists and other cognitive specialists. Participants underwent blood biomarker testing and received an amyloid probability score (APS), indicating the likelihood of a positive result on an amyloid positron emission tomography (PET) scan. The primary study outcomes were appropriateness of patient selection as well as result interpretation associated with PrecivityAD blood testing.

RESULTS

A 95% (347/366) concordance rate was noted between clinicians' patient selection and the test's intended use criteria. In the final analysis including these 347 patients (median age 75 years, 56% women), prespecified test result categories incorporated 133 (38%) low APS, 162 (47%) high APS, and 52 (15%) intermediate APS patients. Clinicians' pretest and posttest AD diagnosis probability changed from 58% to 23% in low APS patients and 71% to 89% in high APS patients (p < 0.0001). Anti-AD drug therapy decreased by 46% in low APS patients (p < 0.0001) and increased by 57% in high APS patients (p < 0.0001).

INTERPRETATION

These findings demonstrate the clinical utility of the PrecivityAD blood test in clinical care and may have added relevance as new AD therapies are introduced.

Comparative assessment of Alzheimer's disease-related biomarkers in plasma and neuron-derived extracellular vesicles: a nested case-control study

Introduction: Alzheimer's disease (AD) is currently defined according to biomarkers reflecting the core underlying neuropathological processes: Aβ deposition, Tau, and neurodegeneration (ATN). The soluble phase of plasma and plasma neuron-derived extracellular vesicles (NDEVs) are increasingly being investigated as sources of biomarkers. The aim of this study was to examine the comparative biomarker potential of these two biofluids, as well as the association between respective biomarkers. Methods: We retrospectively identified three distinct diagnostic groups of 44 individuals who provided samples at baseline and at a mean of 3.1 years later; 14 were cognitively unimpaired at baseline and remained so (NRM-NRM), 13 had amnestic MCI that progressed to AD dementia (MCI-DEM) and 17 had AD dementia at both timepoints (DEM-DEM). Plasma NDEVs were isolated by immunoaffinity capture targeting the neuronal markers L1CAM, GAP43, and NLGN3. In both plasma and NDEVs, we assessed ATN biomarkers (Aβ42, Aβ40, total Tau, P181-Tau) alongside several other exploratory markers. Results: The Aβ42/Aβ40 ratio in plasma and NDEVs was lower in MCI-DEM than NRM-NRM at baseline and its levels in NDEVs decreased over time in all three groups. Similarly, plasma and NDEV-associated Aβ42 was lower in MCI-DEM compared to NRM-NRM at baseline and its levels in plasma decreased over time in DEM-DEM. For NDEV-associated proBDNF, compared to NRM-NRM, its levels were lower in MCI-DEM and DEM-DEM at baseline, and they decreased over time in the latter group. No group differences were found for other exploratory markers. NDEV-associated Aβ42/Aβ40 ratio and proBDNF achieved the highest areas under the curve (AUCs) for discriminating between diagnostic groups, while proBDNF was positively associated with Mini-Mental State Examination (MMSE) score. No associations were found between the two biofluids for any assessed marker. Discussion: The soluble phase of plasma and plasma NDEVs demonstrate distinct biomarker profiles both at a single time point and longitudinally. The lack of association between plasma and NDEV measures indicates that the two types of biofluids demonstrate distinct biomarker signatures that may be attributable to being derived through different biological processes. NDEV-associated proBDNF may be a useful biomarker for AD diagnosis and monitoring.

Blood-based biomarkers for Alzheimer's disease: Current state and future use in a transformed global healthcare landscape

Timely detection of the pathophysiological changes and cognitive impairment caused by Alzheimer's disease (AD) is increasingly pressing because of the advent of biomarker-guided targeted therapies that may be most effective when provided early in the disease. Currently, diagnosis and management of early AD are largely guided by clinical symptoms. FDA-approved neuroimaging and cerebrospinal fluid biomarkers can aid detection and diagnosis, but the clinical implementation of these testing modalities is limited because of availability, cost, and perceived invasiveness. Blood-based biomarkers (BBBMs) may enable earlier and faster diagnoses as well as aid in risk assessment, early detection, prognosis, and management. Herein, we review data on BBBMs that are closest to clinical implementation, particularly those based on measures of amyloid-β peptides and phosphorylated tau species. We discuss key parameters and considerations for the development and potential deployment of these BBBMs under different contexts of use and highlight challenges at the methodological, clinical, and regulatory levels.

A two-step workflow based on plasma p-tau217 to screen for amyloid β positivity with further confirmatory testing only in uncertain cases

Cost-effective strategies for identifying amyloid-β (Aβ) positivity in patients with cognitive impairment are urgently needed with recent approvals of anti-Aβ immunotherapies for Alzheimer's disease (AD). Blood biomarkers can accurately detect AD pathology, but it is unclear whether their incorporation into a full diagnostic workflow can reduce the number of confirmatory cerebrospinal fluid (CSF) or positron emission tomography (PET) tests needed while accurately classifying patients. We evaluated a two-step workflow for determining Aβ-PET status in patients with mild cognitive impairment (MCI) from two independent memory clinic-based cohorts (n = 348). A blood-based model including plasma tau protein 217 (p-tau217), age and APOE ε4 status was developed in BioFINDER-1 (area under the curve (AUC) = 89.3%) and validated in BioFINDER-2 (AUC = 94.3%). In step 1, the blood-based model was used to stratify the patients into low, intermediate or high risk of Aβ-PET positivity. In step 2, we assumed referral only of intermediate-risk patients to CSF Aβ42/Aβ40 testing, whereas step 1 alone determined Aβ-status for low- and high-risk groups. Depending on whether lenient, moderate or stringent thresholds were used in step 1, the two-step workflow overall accuracy for detecting Aβ-PET status was 88.2%, 90.5% and 92.0%, respectively, while reducing the number of necessary CSF tests by 85.9%, 72.7% and 61.2%, respectively. In secondary analyses, an adapted version of the BioFINDER-1 model led to successful validation of the two-step workflow with a different plasma p-tau217 immunoassay in patients with cognitive impairment from the TRIAD cohort (n = 84). In conclusion, using a plasma p-tau217-based model for risk stratification of patients with MCI can substantially reduce the need for confirmatory testing while accurately classifying patients, offering a cost-effective strategy to detect AD in memory clinic settings.

Translating blood biomarkers into clinical practice for Alzheimer's disease: Challenges and perspectives

Early and accurate diagnosis of Alzheimer's disease (AD) in clinical practice is urgent with advances in AD treatment. Blood biomarker assays are preferential diagnostic tools for widespread clinical use with the advantages of being less invasive, cost effective, and easily accessible, and they have shown good performance in research cohorts. However, in community-based populations with maximum heterogeneity, great challenges are still faced in diagnosing AD based on blood biomarkers in terms of accuracy and robustness. Here, we analyze these challenges, including the confounding impact of systemic and biological factors, small changes in blood biomarkers, and difficulty in detecting early changes. Furthermore, we provide perspectives on several potential strategies to overcome these challenges for blood biomarkers to bridge the gap from research to clinical practice.

FDG-PET versus Amyloid-PET Imaging for Diagnosis and Response Evaluation in Alzheimer's Disease: Benefits and Pitfalls

In June 2021, the US Federal Drug and Food Administration (FDA) granted accelerated approval for the antibody aducanumab and, in January 2023, also for the antibody lecanemab, based on a perceived drug-induced removal of cerebral amyloid-beta as assessed by amyloid-PET and, in the case of lecanemab, also a presumption of limited clinical efficacy. Approval of the antibody donanemab is awaiting further data. However, published trial data indicate few, small and uncertain clinical benefits, below what is considered "clinically meaningful" and similar to the effect of conventional medication. Furthermore, a therapy-related decrease in the amyloid-PET signal may also reflect increased cell damage rather than simply "amyloid removal". This interpretation is more consistent with increased rates of amyloid-related imaging abnormalities and brain volume loss in treated patients, relative to placebo. We also challenge the current diagnostic criteria for AD based on amyloid-PET imaging biomarkers and recommend that future anti-AD therapy trials apply: (1) diagnosis of AD based on the co-occurrence of cognitive decline and decreased cerebral metabolism assessed by FDA-approved FDG-PET, (2) therapy efficacy determined by favorable effect on cognitive ability, cerebral metabolism by FDG-PET, and brain volumes by MRI, and (3) neuropathologic examination of all deaths occurring in these trials.

Plasma Aβ42/40 and cognitive variability are associated with cognitive function in Black Americans: Findings from the AA-FAIM cohort

Introduction

It is critical to develop more inclusive Alzheimer's disease (AD) research protocols to ensure that historically excluded groups are included in preclinical research and have access to timely diagnosis and treatment. If validated in racialized groups, plasma AD biomarkers and measures of subtle cognitive dysfunction could provide avenues to expand diversity in preclinical AD research. We sought to evaluate the utility of two easily obtained, low-burden disease markers, plasma amyloid beta (Aβ)42/40, and intra-individual cognitive variability (IICV), to predict concurrent and longitudinal cognitive performance in a sample of Black adults.

Methods

Two hundred fifty-seven Black participants enrolled in the African Americans Fighting Alzheimer's in Midlife (AA-FAIM) study underwent at least one cognitive assessment visit; a subset of n = 235 had plasma samples. Baseline IICV was calculated as the standard deviation across participants' z scores on five cognitive measures: Rey Auditory Verbal Learning Test Delayed Recall, Trail Making Test Parts A and B (Trails A and B), and Boston Naming Test. Using mixed effects regression models, we compared concurrent and longitudinal models to baseline plasma Aβ42/40 or IICV by age interactions. PrecivityAD assays quantified baseline plasma Aβ42/40.

Results

IICV was associated with concurrent/baseline performance on several outcomes but did not modify associations between age and cognitive decline. In contrast, plasma Aβ42/40 was unrelated to baseline cognitive performance, but a pattern emerged in interactions with age in longitudinal models of Trails A and B and Rey Auditory Verbal Learning Test total learning trials. Although not significant after correcting for multiple comparisons, low Aβ42/40 was associated with faster cognitive declines over time.

Discussion

Our results are promising as they extend existing findings to an Black American sample using low-cost, low-burden methods that can be implemented outside of a research center, thus supporting efforts for inclusive AD biomarker research.

Plasma Aβ42/Aβ40 Ratios in Older People With Human Immunodeficiency Virus

BACKGROUND

As people with human immunodeficiency virus (HIV) (PWH) age, it remains unclear whether they are at higher risk for age-related neurodegenerative disorders-for example, Alzheimer disease (AD)-and, if so, how to differentiate HIV-associated neurocognitive impairment from AD. We examined a clinically available blood biomarker test for AD (plasma amyloid-β [Aβ] 42/Aβ40 ratio) in PWH who were cognitively normal (PWH_CN) or cognitively impaired (PWH_CI) and people without HIV (PWoH) who were cognitively normal (PWoH_CN) or had symptomatic AD (PWoH_AD).

METHODS

A total of 66 PWH (age >40 years) (HIV RNA <50 copies/mL) and 195 PWoH provided blood samples, underwent magnetic resonance imaging, and completed a neuropsychological battery or clinical dementia rating scale. Participants were categorized by impairment (PWH_CN, n = 43; PWH_CI, n = 23; PWoH_CN, n = 138; PWoH_AD, n = 57). Plasma Aβ42 and Aβ40 concentrations were obtained using a liquid chromatography-tandem mass spectrometry method to calculate the PrecivityAD amyloid probability score (APS). The APS incorporates age and apolipoprotein E proteotype into a risk score for brain amyloidosis. Plasma Aβ42/Aβ40 ratios and APSs were compared between groups and assessed for relationships with hippocampal volumes or cognition and HIV clinical characteristics (PWH only).

RESULTS

The plasma Aβ42/Aβ40 ratio was significantly lower, and the APS higher, in PWoH_AD than in other groups. A lower Aβ42/Aβ40 ratio and higher APS was associated with smaller hippocampal volumes for PWoH_AD. The Aβ42/Aβ40 ratio and APS were not associated with cognition or HIV clinical measures for PWH.

CONCLUSIONS

The plasma Aβ42/Aβ40 ratio can serve as a screening tool for AD and may help differentiate effects of HIV from AD within PWH, but larger studies with older PWH are needed.

Plasma Biomarkers of Alzheimer's Disease: A Review of Available Assays, Recent Developments, and Implications for Clinical Practice

Recently, low-sensitive plasma assays have been replaced by new ultra-sensitive assays such as single molecule enzyme-linked immunosorbent assay (Simoa), the Mesoscale Discovery (MSD) platform, and immunoprecipitation-mass spectrometry (IP-MS) with higher accuracy in the determination of plasma biomarkers of Alzheimer's disease (AD). Despite the significant variability, many studies have established in-house cut-off values for the most promising available biomarkers. We first reviewed the most used laboratory methods and assays to measure plasma AD biomarkers. Next, we review studies focused on the diagnostic performance of these biomarkers to identify AD cases, predict cognitive decline in pre-clinical AD cases, and differentiate AD cases from other dementia. We summarized data from studies published until January 2023. A combination of plasma Aβ_42/40 ratio, age, and APOE status showed the best accuracy in diagnosing brain amyloidosis with a liquid chromatography-mass spectrometry (LC-MS) assay. Plasma p-tau217 has shown the best accuracy in distinguishing Aβ-PET+ from Aβ-PET-even in cognitively unimpaired individuals. We also summarized the different cut-off values for each biomarker when available. Recently developed assays for plasma biomarkers have undeniable importance in AD research, with improved analytical and diagnostic performance. Some biomarkers have been extensively used in clinical trials and are now clinically available. Nonetheless, several challenges remain to their widespread use in clinical practice.

Blood biomarkers for Alzheimer's disease in clinical practice and trials

Blood-based biomarkers hold great promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD) in clinical practice. This is very timely, considering the recent development of anti-amyloid-β (Aβ) immunotherapies. Several assays for measuring phosphorylated tau (p-tau) in plasma exhibit high diagnostic accuracy in distinguishing AD from all other neurodegenerative diseases in patients with cognitive impairment. Prognostic models based on plasma p-tau levels can also predict future development of AD dementia in patients with mild cognitive complaints. The use of such high-performing plasma p-tau assays in the clinical practice of specialist memory clinics would reduce the need for more costly investigations involving cerebrospinal fluid samples or positron emission tomography. Indeed, blood-based biomarkers already facilitate identification of individuals with pre-symptomatic AD in the context of clinical trials. Longitudinal measurements of such biomarkers will also improve the detection of relevant disease-modifying effects of new drugs or lifestyle interventions.

Clinical utility of an antibody-free LC-MS method to detect brain amyloid deposition in cognitively unimpaired individuals from the screening visit of the A4 Study

INTRODUCTION

This study explored the ability of plasma amyloid beta (Aβ)42/Aβ40 to identify brain amyloid deposition in cognitively unimpaired (CU) individuals.

METHODS

Plasma Aβ was quantified with an antibody-free high-performance liquid chromatography tandem mass spectrometry method from Araclon Biotech (ABtest-MS) in a subset of 731 CU individuals from the screening visit of the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study, to assess associations of Aβ42/Aβ40 with Aβ positron emission tomography (PET).

RESULTS

A model including Aβ42/Aβ40, age, apolipoprotein E ε4, and recruitment site identified Aβ PET status with an area under the curve of 0.88 and an overall accuracy of 81%. A plasma-based pre-screening step could save up to 42% of the total number of Aβ PET scans.

DISCUSSION

ABtest-MS accurately identified brain amyloid deposition in a population of CU individuals, supporting its implementation in AD secondary prevention trials to reduce recruitment time and costs. Although a certain degree of heterogeneity is inherent to large and multicentric trials, ABtest-MS could be more robust to pre-analytical bias compared to other immunoprecipitation mass spectrometry methods.

HIGHLIGHTS

Plasma amyloid beta (Aβ)42/Aβ40 accurately identified brain Aβ deposition in cognitively unimpaired individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study.The inclusion of the recruitment site in the predictive models has a non-negligible effect.A plasma biomarker-based model could reduce recruitment costs in Alzheimer's disease secondary prevention trials.Antibody-free liquid chromatography mass spectrometry methods may be more robust to pre-analytical variability than other platforms.

Early Detection of Alzheimer's Disease-Related Pathology Using a Multi-Disease Diagnostic Platform Employing Autoantibodies as Blood-Based Biomarkers

BACKGROUND

Evidence for the universal presence of IgG autoantibodies in blood and their potential utility for the diagnosis of Alzheimer's disease (AD) and other neurodegenerative diseases has been extensively demonstrated by our laboratory. The fact that AD-related neuropathological changes in the brain can begin more than a decade before tell-tale symptoms emerge has made it difficult to develop diagnostic tests useful for detecting the earliest stages of AD pathogenesis.

OBJECTIVE

To determine the utility of a panel of autoantibodies for detecting the presence of AD-related pathology along the early AD continuum, including at pre-symptomatic [an average of 4 years before the transition to mild cognitive impairment (MCI)/AD)], prodromal AD (MCI), and mild-moderate AD stages.

METHODS

A total of 328 serum samples from multiple cohorts, including ADNI subjects with confirmed pre-symptomatic, prodromal, and mild-moderate AD, were screened using Luminex xMAP ® technology to predict the probability of the presence of AD-related pathology. A panel of eight autoantibodies with age as a covariate was evaluated using randomForest and receiver operating characteristic (ROC) curves.

RESULTS

Autoantibody biomarkers alone predicted the probability of the presence of AD-related pathology with 81.0% accuracy and an area under the curve (AUC) of 0.84 (95% CI = 0.78-0.91). Inclusion of age as a parameter to the model improved the AUC (0.96; 95% CI = 0.93-0.99) and overall accuracy (93.0%).

CONCLUSION

Blood-based autoantibodies can be used as an accurate, non-invasive, inexpensive, and widely accessible diagnostic screener for detecting AD-related pathology at pre-symptomatic and prodromal AD stages that could aid clinicians in diagnosing AD.

Comparison of ultrasensitive and mass spectrometry quantification of blood-based amyloid biomarkers for Alzheimer's disease diagnosis in a memory clinic cohort

BACKGROUND

Alzheimer's disease (AD) is a complex neurodegenerative disorder with β-amyloid pathology as a key underlying process. The relevance of cerebrospinal fluid (CSF) and brain imaging biomarkers is validated in clinical practice for early diagnosis. Yet, their cost and perceived invasiveness are a limitation for large-scale implementation. Based on positive amyloid profiles, blood-based biomarkers should allow to detect people at risk for AD and to monitor patients under therapeutics strategies. Thanks to the recent development of innovative proteomic tools, the sensibility and specificity of blood biomarkers have been considerably improved. However, their diagnosis and prognosis relevance for daily clinical practice is still incomplete.

METHODS

The Plasmaboost study included 184 participants from the Montpellier's hospital NeuroCognition Biobank with AD (n = 73), mild cognitive impairments (MCI) (n = 32), subjective cognitive impairments (SCI) (n = 12), other neurodegenerative diseases (NDD) (n = 31), and other neurological disorders (OND) (n = 36). Dosage of β-amyloid biomarkers was performed on plasma samples using immunoprecipitation-mass spectrometry (IPMS) developed by Shimadzu (IPMS-Shim Aβ₄₂, Aβ₄₀, APP_669-711) and Simoa Human Neurology 3-PLEX A assay (Aβ₄₂, Aβ₄₀, t-tau). Links between those biomarkers and demographical and clinical data and CSF AD biomarkers were investigated. Performances of the two technologies to discriminate clinically or biologically based (using the AT(N) framework) diagnosis of AD were compared using receiver operating characteristic (ROC) analyses.

RESULTS

The amyloid IPMS-Shim composite biomarker (combining APP_669-711/Aβ₄₂ and Aβ₄₀/Aβ₄₂ ratios) discriminated AD from SCI (AUC: 0.91), OND (0.89), and NDD (0.81). The IPMS-Shim Aβ_42/40 ratio also discriminated AD from MCI (0.78). IPMS-Shim biomarkers have similar relevance to discriminate between amyloid-positive and amyloid-negative individuals (0.73 and 0.76 respectively) and A-T-N-/A+T+N+ profiles (0.83 and 0.85). Performances of the Simoa 3-PLEX Aβ_42/40 ratio were more modest. Pilot longitudinal analysis on the progression of plasma biomarkers indicates that IPMS-Shim can detect the decrease in plasma Aβ₄₂ that is specific to AD patients.

CONCLUSIONS

Our study confirms the potential usefulness of amyloid plasma biomarkers, especially the IPMS-Shim technology, as a screening tool for early AD patients.

Everyday Driving and Plasma Biomarkers in Alzheimer's Disease: Leveraging Artificial Intelligence to Expand Our Diagnostic Toolkit

BACKGROUND

Driving behavior as a digital marker and recent developments in blood-based biomarkers show promise as a widespread solution for the early identification of Alzheimer's disease (AD).

OBJECTIVE

This study used artificial intelligence methods to evaluate the association between naturalistic driving behavior and blood-based biomarkers of AD.

METHODS

We employed an artificial neural network (ANN) to examine the relationship between everyday driving behavior and plasma biomarker of AD. The primary outcome was plasma Aβ42/Aβ40, where Aβ42/Aβ40 < 0.1013 was used to define amyloid positivity. Two ANN models were trained and tested for predicting the outcome. The first model architecture only includes driving variables as input, whereas the second architecture includes the combination of age, APOE ɛ4 status, and driving variables.

RESULTS

All 142 participants (mean [SD] age 73.9 [5.2] years; 76 [53.5%] men; 80 participants [56.3% ] with amyloid positivity based on plasma Aβ42/Aβ40) were cognitively normal. The six driving features, included in the ANN models, were the number of trips during rush hour, the median and standard deviation of jerk, the number of hard braking incidents and night trips, and the standard deviation of speed. The F1 score of the model with driving variables alone was 0.75 [0.023] for predicting plasma Aβ42/Aβ40. Incorporating age and APOE ɛ4 carrier status improved the diagnostic performance of the model to 0.80 [>0.051].

CONCLUSION

Blood-based AD biomarkers offer a novel opportunity to establish the efficacy of naturalistic driving as an accessible digital marker for AD pathology in driving research.

Evaluation of Blood-Based Plasma Biomarkers as Potential Markers of Amyloid Burden in Preclinical Alzheimer's Disease

BACKGROUND

Participant eligibility for the A4 Study was determined by amyloid PET imaging. Given the disadvantages of amyloid PET imaging in accessibility and cost, blood-based biomarkers may serve as a sufficient biomarker and more cost-effective screening tool for patient enrollment into preclinical AD trials.

OBJECTIVE

To determine if a blood-based screening test can adequately identify amyloid burden in participants screened into a preclinical AD trial.

METHODS

In this cross-sectional study, 224 participants from the A4 Study received an amyloid PET scan (18Florbetapir) within 90 days of blood sample collection. Blood samples from all study participants were processed within 2 h after phlebotomy. Plasma amyloid measures were quantified by Shimazdu and C2 N Diagnostics using mass spectrometry-based platforms. A corresponding subset of blood samples (n = 100) was processed within 24 h after phlebotomy and analyzed by C2 N.

RESULTS

Plasma Aβ42/Aβ40 demonstrated the highest association for Aβ accumulation in the brain with an AUC 0.76 (95%CI = 0.69, 0.82) at C2 N and 0.80 (95%CI = 0.75, 0.86) at Shimadzu. Blood samples processed to plasma within 2 h after phlebotomy provided a better prediction of amyloid PET status than blood samples processed within 24 h (AUC 0.80 versus 0.64; p < 0.001). Age, sex, and APOE ɛ4 carrier status did not the diagnostic performance of plasma Aβ42/Aβ40 to predict amyloid PET positivity in A4 Study participants.

CONCLUSION

Plasma Aβ42/Aβ40 may serve as a potential biomarker for predicting elevated amyloid in the brain. Utilizing blood testing over PET imaging may improve screening efficiency into clinical trials.

Predicting continuous amyloid PET values with CSF and plasma Aβ42/Aβ40

Introduction

Continuous measures of amyloid burden as measured by positron emission tomography (PET) are being used increasingly to stage Alzheimer's disease (AD). This study examined whether cerebrospinal fluid (CSF) and plasma amyloid beta (Aβ)42/Aβ40 could predict continuous values for amyloid PET.

Methods

CSF Aβ42 and Aβ40 were measured with automated immunoassays. Plasma Aβ42 and Aβ40 were measured with an immunoprecipitation-mass spectrometry assay. Amyloid PET was performed with Pittsburgh compound B (PiB). The continuous relationships of CSF and plasma Aβ42/Aβ40 with amyloid PET burden were modeled.

Results

Most participants were cognitively normal (427 of 491 [87%]) and the mean age was 69.0 ± 8.8 years. CSF Aβ42/Aβ40 predicted amyloid PET burden until a relatively high level of amyloid accumulation (69.8 Centiloids), whereas plasma Aβ42/Aβ40 predicted amyloid PET burden until a lower level (33.4 Centiloids).

Discussion

CSF Aβ42/Aβ40 predicts the continuous level of amyloid plaque burden over a wider range than plasma Aβ42/Aβ40 and may be useful in AD staging.

Highlights

Cerebrospinal fluid (CSF) amyloid beta (Aβ)42/Aβ40 predicts continuous amyloid positron emission tomography (PET) values up to a relatively high burden.Plasma Aβ42/Aβ40 is a comparatively dichotomous measure of brain amyloidosis.Models can predict regional amyloid PET burden based on CSF Aβ42/Aβ40.CSF Aβ42/Aβ40 may be useful in staging AD.

The performance of plasma amyloid beta measurements in identifying amyloid plaques in Alzheimer's disease: a literature review

The extracellular buildup of amyloid beta (Aβ) plaques in the brain is a hallmark of Alzheimer's disease (AD). Detection of Aβ pathology is essential for AD diagnosis and for identifying and recruiting research participants for clinical trials evaluating disease-modifying therapies. Currently, AD diagnoses are usually made by clinical assessments, although detection of AD pathology with positron emission tomography (PET) scans or cerebrospinal fluid (CSF) analysis can be used by specialty clinics. These measures of Aβ aggregation, e.g. plaques, protofibrils, and oligomers, are medically invasive and often only available at specialized medical centers or not covered by medical insurance, and PET scans are costly. Therefore, a major goal in recent years has been to identify blood-based biomarkers that can accurately detect AD pathology with cost-effective, minimally invasive procedures.To assess the performance of plasma Aβ assays in predicting amyloid burden in the central nervous system (CNS), this review compares twenty-one different manuscripts that used measurements of 42 and 40 amino acid-long Aβ (Aβ42 and Aβ40) in plasma to predict CNS amyloid status. Methodologies that quantitate Aβ42 and 40 peptides in blood via immunoassay or immunoprecipitation-mass spectrometry (IP-MS) were considered, and their ability to distinguish participants with amyloidosis compared to amyloid PET and CSF Aβ measures as reference standards was evaluated. Recent studies indicate that some IP-MS assays perform well in accurately and precisely measuring Aβ and detecting brain amyloid aggregates.

A Review of Application of Aβ42/40 Ratio in Diagnosis and Prognosis of Alzheimer’s Disease

The number of patients with Alzheimer’s disease (AD) and non-Alzheimer’s disease (non-AD) has drastically increased over recent decades. The amyloid cascade hypothesis attributes a vital role to amyloid-β protein (Aβ) in the pathogenesis of AD. As the main pathological hallmark of AD, amyloid plaques consist of merely the 42 and 40 amino acid variants of Aβ (Aβ 42 and Aβ 40). The cerebrospinal fluid (CSF) biomarker Aβ 42/40 has been extensively investigated and eventually integrated into important diagnostic tools to support the clinical diagnosis of AD. With the development of highly sensitive assays and technologies, blood-based Aβ 42/40, which was obtained using a minimally invasive and cost-effective method, has been proven to be abnormal in synchrony with CSF biomarker values. This paper presents the recent progress of the CSF Aβ 42/40 ratio and plasma Aβ 42/40 for AD as well as their potential clinical application as diagnostic markers or screening tools for dementia.

Plasma Amyloid-β dynamics in late-life major depression: a longitudinal study

Depressed individuals are twice as likely to develop Alzheimer's disease (AD) as compared to controls. Brain amyloid-β (Aβ) deposition is believed to have a major role in AD pathogenesis but studies also suggest associations of Aβ dynamics and depression. The aim of this study was to test if plasma Aβ levels are longitudinally associated to late-life depression. We measured plasma levels of amyloid-β_1-40 (Aβ40) and amyloid-β_1-42 (Aβ42) peptides longitudinally for three consecutive years in 48 cognitively intact elderly subjects with late-life major depressive disorder (LLMD) and 45 age-matched cognitively healthy controls. We found that the Aβ42/Aβ40 plasma ratio was significantly and steadily lower in depressed subjects compared to controls (p < 0.001). At screening, Aβ42/Aβ40 plasma did not correlate with depression severity (as measured with Hamilton Depression Scale) or cognitive performance (as measured with Mini-Mental State Examination) but was associated to depression severity at 3 years after adjustment for age, education, cognitive performance, and antidepressants use. This study showed that reduced plasma Aβ42/Aβ40 ratio is consistently associated with LLMD diagnosis and that increased severity of depression at baseline predicted low Aβ42/Aβ40 ratio at 3 years. Future studies are needed to confirm these findings and examine if the consistently lower plasma Aβ42/Aβ40 ratio in LLMD reflects increased brain amyloid deposition, as observed in AD subjects, and an increased risk for progressive cognitive decline and AD.

Biomarkers for Alzheimer's Disease: Context of Use, Qualification, and Roadmap for Clinical Implementation

Background and Objectives: The US Food and Drug Administration (FDA) defines a biomarker as a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention. Biomarkers may be used in clinical care or as drug development tools (DDTs) in clinical trials. The goal of this review and perspective is to provide insight into the regulatory guidance for the use of biomarkers in clinical trials and clinical care. Materials and Methods: We reviewed FDA guidances relevant to biomarker use in clinical trials and their transition to use in clinical care. We identified instructive examples of these biomarkers in Alzheimer's disease (AD) drug development and their application in clinical practice. Results: For use in clinical trials, biomarkers must have a defined context of use (COU) as a risk/susceptibility, diagnostic, monitoring, predictive, prognostic, pharmacodynamic, or safety biomarker. A four-stage process defines the pathway to establish the regulatory acceptance of the COU for a biomarker including submission of a letter of intent, description of the qualification plan, submission of a full qualification package, and acceptance through a qualification recommendation. Biomarkers used in clinical care may be companion biomarkers, in vitro diagnostic devices (IVDs), or laboratory developed tests (LDTs). A five-phase biomarker development process has been proposed to structure the biomarker development process. Conclusions: Biomarkers are increasingly important in drug development and clinical care. Adherence to regulatory guidance for biomarkers used in clinical trials and patient care is required to advance these important drug development and clinical tools.

Blood Biomarkers from Research Use to Clinical Practice: What Must Be Done? A Report from the EU/US CTAD Task Force

Timely and accurate diagnosis of Alzheimer's disease (AD) in clinical practice remains challenging. PET and CSF biomarkers are the most widely used biomarkers to aid diagnosis in clinical research but present limitations for clinical practice (i.e., cost, accessibility). Emerging blood-based markers have the potential to be accurate, cost-effective, and easily accessible for widespread clinical use, and could facilitate timely diagnosis. The EU/US CTAD Task Force met in May 2022 in a virtual meeting to discuss pathways to implementation of blood-based markers in clinical practice. Specifically, the CTAD Task Force assessed: the state-of-art for blood-based markers, the current use of blood-based markers in clinical trials, the potential use of blood-based markers in clinical practice, the current challenges with blood-based markers, and the next steps needed for broader adoption in clinical practice.