Combining blood-based biomarkers to predict risk for Alzheimer’s disease dementia

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.

The impact of exercise on blood-based biomarkers of Alzheimer's disease in cognitively unimpaired older adults

Physical activity is a promising preventative strategy for Alzheimer's disease: it is associated with lower dementia risk, better cognition, greater brain volume and lower brain beta-amyloid. Blood-based biomarkers have emerged as a low-cost, non-invasive strategy for detecting preclinical Alzheimer's disease, however, there is limited literature examining the effect of exercise (a structured form of physical activity) on blood-based biomarkers. The current study investigated the influence of a 6-month exercise intervention on levels of plasma beta-amyloid (Aβ42, Aβ40, Aβ42/40), phosphorylated tau (p-tau181), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) chain in cognitively unimpaired older adults, and as a secondary aim, whether blood-based biomarkers related to cognition. Ninety-nine community-dwelling older adults (69.1 ± 5.2) were allocated to an inactive control, or to moderate or high intensity exercise groups where they cycled twice weekly for six months. At baseline and six months (post-intervention), fasted blood was collected and analysed using single molecule array (SIMOA) assays, and cognition was assessed. Results demonstrated no change in levels of any plasma biomarker from pre- to post-intervention. At baseline, higher NfL was associated with poorer cognition (β = -0.33, SE = 0.13, adjusted p = .042). Exploratory analyses indicated higher cardiorespiratory fitness was associated with higher NfL and GFAP levels in apolipoprotein E (APOE) ε4 non-carriers compared to ε4 carriers (NfL, β = -0.43, SE = 0.19, p = .029; GFAP, β = -0.41, SE = 0.20, p = .044), though this association was mediated by body mass index (BMI). These results highlight the importance of considering BMI in analysis of blood-based biomarkers, especially when investigating differences between APOE ε4 carriers and non-carriers. Our results also indicate that longer follow-up periods may be required to observe exercise-induced change in blood-based biomarkers.

Silver nanoparticle-based SERS sensors for sensitive detection of amyloid-β aggregates in biological fluids

One of the hallmarks of Alzheimer's disease (AD) pathogenesis is the production, aggregation, and deposition of amyloid-β (Aβ) peptide. Surface-enhanced Raman spectroscopy (SERS) is a promising analytical technique capable of providing valuable information on chemical composition and molecule conformations in biological samples. However, one of the main challenges for introducing the SERS technique into the practice is preparation of scalable and at the same time stable nanostructured sensors with uniform spatial distribution of nanoparticles. Herein, we propose SERS platforms for reproducible, sensitive, label-free quantification of amyloid-β aggregates for short-wavelength - 532 and 633 nm - lasers. A SERS sensor - based on silver nanoparticles immobilized into a chitosan film (AgNP/CS) - provided a uniform distribution of AgNPs from a colloidal suspension across the SERS sensor, resulting in nanomolar limits of detection (LODs) for Aβ42 aggregates with a portable 532 nm laser. The laser-induced deposition was used to obtain denser periodic plasmonic sensors (AgNP/LID) with a uniform nanoparticle distribution. The AgNP/LID SERS sensor allowed for 15 pM LOD for Aβ42 aggregates with 633 nm laser. Notably, both nanostructured substrates allowed to distinguish amyloid aggregates from monomers. Therefore, our approach demonstrated applicability of SERS for detection of macromolecular volumetric objects as amyloid-β aggregates for fundamental biological studies as well as for "point-of-care" diagnostics and screening for early stages of neurodegenerative diseases.

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.

Plasma Aβ42/40 ratio, p-tau181, GFAP, and NfL across the Alzheimer's disease continuum: A cross-sectional and longitudinal study in the AIBL cohort

INTRODUCTION

Plasma amyloid beta (Aβ)1-42/Aβ1-40 ratio, phosphorylated-tau181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) are putative blood biomarkers for Alzheimer's disease (AD). However, head-to-head cross-sectional and longitudinal comparisons of the aforementioned biomarkers across the AD continuum are lacking.

METHODS

Plasma Aβ1-42, Aβ1-40, p-tau181, GFAP, and NfL were measured utilizing the Single Molecule Array (Simoa) platform and compared cross-sectionally across the AD continuum, wherein Aβ-PET (positron emission tomography)-negative cognitively unimpaired (CU Aβ-, n = 81) and mild cognitive impairment (MCI Aβ-, n = 26) participants were compared with Aβ-PET-positive participants across the AD continuum (CU Aβ+, n = 39; MCI Aβ+, n = 33; AD Aβ+, n = 46) from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) cohort. Longitudinal plasma biomarker changes were also assessed in MCI (n = 27) and AD (n = 29) participants compared with CU (n = 120) participants. In addition, associations between baseline plasma biomarker levels and prospective cognitive decline and Aβ-PET load were assessed over a 7 to 10-year duration.

RESULTS

Lower plasma Aβ1-42/Aβ1-40 ratio and elevated p-tau181 and GFAP were observed in CU Aβ+, MCI Aβ+, and AD Aβ+, whereas elevated plasma NfL was observed in MCI Aβ+ and AD Aβ+, compared with CU Aβ- and MCI Aβ-. Among the aforementioned plasma biomarkers, for models with and without AD risk factors (age, sex, and apolipoprotein E (APOE) ε4 carrier status), p-tau181 performed equivalent to or better than other biomarkers in predicting a brain Aβ-/+ status across the AD continuum. However, for models with and without the AD risk factors, a biomarker panel of Aβ1-42/Aβ1-40, p-tau181, and GFAP performed equivalent to or better than any of the biomarkers alone in predicting brain Aβ-/+ status across the AD continuum. Longitudinally, plasma Aβ1-42/Aβ1-40, p-tau181, and GFAP were altered in MCI compared with CU, and plasma GFAP and NfL were altered in AD compared with CU. In addition, lower plasma Aβ1-42/Aβ1-40 and higher p-tau181, GFAP, and NfL were associated with prospective cognitive decline and lower plasma Aβ1-42/Aβ1-40, and higher p-tau181 and GFAP were associated with increased Aβ-PET load prospectively.

DISCUSSION

These findings suggest that plasma biomarkers are altered cross-sectionally and longitudinally, along the AD continuum, and are prospectively associated with cognitive decline and brain Aβ-PET load. In addition, although p-tau181 performed equivalent to or better than other biomarkers in predicting an Aβ-/+ status across the AD continuum, a panel of biomarkers may have superior Aβ-/+ status predictive capability across the AD continuum.

HIGHLIGHTS

Area under the curve (AUC) of p-tau181 ≥ AUC of Aβ42/40, GFAP, NfL in predicting PET Aβ-/+ status (Aβ-/+).  AUC of Aβ42/40+p-tau181+GFAP panel ≥ AUC of Aβ42/40/p-tau181/GFAP/NfL for Aβ-/+.  Longitudinally, Aβ42/40, p-tau181, and GFAP were altered in MCI versus CU.  Longitudinally, GFAP and NfL were altered in AD versus CU.  Aβ42/40, p-tau181, GFAP, and NfL are associated with prospective cognitive decline.  Aβ42/40, p-tau181, and GFAP are associated with increased PET Aβ load prospectively.

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.

Blood and Cerebrospinal Fluid Biomarkers in Vascular Dementia and Alzheimer's Disease: A Brief Review

The Maintenance of brain health is a lifelong process whereby potentially deleterious exposures such as cardiovascular risks, amyloid beta, and phosphorylated tau may adversely affect the brain decades before there are clinical manifestations. Thus, the early structural and neuropathological foundation for the development of cognitive impairment and its allied features later in life may provide precursor targets such that interventions may be applied to prevent or slow cognitively impairing processes if the underlying mechanism(s) can be addressed in time.

Future Directions for the HRS Harmonized Cognitive Assessment Protocol

In the absence of effective pharmacological treatment to halt or reverse the course of Alzheimer's disease and related dementias (ADRDs), population-level research on the modifiable determinants of dementia risk and outcomes for those living with ADRD is critical. The Harmonized Cognitive Assessment Protocol (HCAP), fielded in 2016 as part of the U.S. Health and Retirement Study (HRS) and multiple international counterparts, has the potential to play an important role in such efforts. The stated goals of the HCAP are to improve our ability to understand the determinants, prevalence, costs, and consequences of cognitive impairment and dementia in the U.S. and to support cross-national comparisons. The first wave of the HCAP demonstrated the feasibility and value of the more detailed cognitive assessments in the HCAP compared to the brief cognitive assessments in the core HRS interviews. To achieve its full potential, we provide eight recommendations for improving future iterations of the HCAP. Our highest priority recommendation is to increase the representation of historically marginalized racial/ethnic groups disproportionately affected by ADRDs. Additional recommendations relate to the timing of the HCAP assessments; clinical and biomarker validation data, including to improve cross-national comparisons; dropping lower performing items; enhanced documentation; and the addition of measures related to caregiver impact. We believe that the capacity of the HCAP to achieve its stated goals will be greatly enhanced by considering these changes and additions.

Toward the optimized assessment of clinical outcomes in studies of novel treatments for Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is characterized by a progressive decline in cognition and daily function, leading to a greater need for caregiver support. Clinical disease is segmented into a preclinical stage, mild cognitive impairment, and mild, moderate, and severe stages of Alzheimer's dementia. Although AD trials enroll participants at various stages of illness, treatment efficacy is often assessed using endpoints based on measures of outcomes that are held fixed across disease stages. We hypothesize that matching the primary outcomes measured in the endpoint hierarchy to the stage of disease targeted by the trial will increase the likelihood of detecting true treatment benefits.

AREAS COVERED

We discuss current approaches to assessing clinical outcomes in AD trials, followed by a consideration of how effect detection can be improved by linking the stage of AD to the endpoints that most likely reflect stage-specific disease progression.

EXPERT OPINION

Failing to account for stage-specific relevance and sensitivity of clinical outcomes may be one factor that contributes to trial failures in AD. Given the history of failure, experts have begun to scrutinize the relevance and sensitivity of outcomes as a potentially modifiable barrier to successful trials. To this end, we present a framework for refining trial endpoint selection and evaluation.

Contextual Exceptionalism After Death: An Information Ethics Approach to Post-Mortem Privacy in Health Data Research

In this article, we use the theory of Information Ethics to argue that deceased people have a prima facie moral right to privacy in the context of health data research, and that this should be reflected in regulation and guidelines. After death, people are no longer biological subjects but continue to exist as informational entities which can still be harmed/damaged. We find that while the instrumental value of recognising post-mortem privacy lies in the preservation of the social contract for health research, its intrinsic value is grounded in respect for the dignity of the post-mortem informational entity. However, existing guidance on post-mortem data protection is available only in the context of genetic studies. In comparing the characteristics of genetic data and other health-related data, we identify two features of DNA often given as arguments for this genetic exceptionalism: relationality and embodiment. We use these concepts to show that at the appropriate Level of Abstraction, there is no morally relevant distinction between posthumous genetic and other health data. Thus, genetic data should not automatically receive special moral status after death. Instead we make a plea for 'contextual exceptionalism'. Our analysis concludes by reflecting on a real-world case and providing suggestions for contextual factors that researchers and oversight bodies should take into account when designing and evaluating research projects with health data from deceased subjects.

Alzheimer's disease: a scoping review of biomarker research and development for effective disease diagnosis

INTRODUCTION

Alzheimer's disease (AD) is regarded as the foremost reason for neurodegeneration that prominently affects the geriatric population. Characterized by extracellular accumulation of amyloid-beta (Aβ), intracellular aggregation of hyperphosphorylated tau (p-tau), and neuronal degeneration that causes impairment of memory and cognition. Amyloid/tau/neurodegeneration (ATN) classification is utilized for research purposes and involves amyloid, tau, and neuronal injury staging through MRI, PET scanning, and CSF protein concentration estimations. CSF sampling is invasive, and MRI and PET scanning requires sophisticated radiological facilities which limit its widespread diagnostic use. ATN classification lacks effectiveness in preclinical AD.

AREAS COVERED

This publication intends to collate and review the existing biomarker profile and the current research and development of a new arsenal of biomarkers for AD pathology from different biological samples, microRNA (miRNA), proteomics, metabolomics, artificial intelligence, and machine learning for AD screening, diagnosis, prognosis, and monitoring of AD treatments.

EXPERT OPINION

It is an accepted observation that AD-related pathological changes occur over a long period of time before the first symptoms are observed providing ample opportunity for detection of biological alterations in various biological samples that can aid in early diagnosis and modify treatment outcomes.

Detection, Diagnosis and Treatment of Acute Ischemic Stroke: Current and Future Perspectives

Stroke is one of the leading causes of disability worldwide. Early diagnosis and treatment of stroke are important for better clinical outcome. Rapid and accurate diagnosis of stroke subtypes is critical. This review discusses the advantages and disadvantages of the current diagnostic and assessment techniques used in clinical practice, particularly for diagnosing acute ischemic stroke. Alternative techniques for rapid detection of stroke utilizing blood based biomarkers and novel portable devices employing imaging methods such as volumetric impedance phase-shift spectroscopy, microwave tomography and Doppler ultrasound are also discussed. Current therapeutic approaches for treating acute ischemic stroke using thrombolytic drugs and endovascular thrombectomy are discussed, with a focus on devices and approaches recently developed to treat large cranial vessel occlusions.

miRNA sensing hydrogels capable of self-signal amplification for early diagnosis of Alzheimer's disease

Alzheimer's disease (AD), one of the leading senile disorders in the world, causes severe memory loss and cognitive impairment. To date, there is no clear cure for AD. However, early diagnosis and monitoring can help mitigate the effects of this disease. In this study, we reported a platform for diagnosing early-stage AD using microRNAs (miRNAs) in the blood as biomarkers. First, we selected an appropriate target miRNA (miR-574-5p) using AD model mice (4-month-old 5XFAD mice) and developed a hydrogel-based sensor that enabled high-sensitivity detection of the target miRNA. This hydrogel contained catalytic hairpin assembly (CHA) reaction-based probes, leading to fluorescence signal amplification without enzymes and temperature changes, at room temperature. This sensor exhibited high sensitivity and selectivity, as evidenced by its picomolar-level detection limit (limit of detection: 1.29 pM). Additionally, this sensor was evaluated using the plasma of AD patients and non-AD control to validate its clinical applicability. Finally, to use this sensor as a point-of-care-testing (POCT) diagnostic system, a portable fluorometer was developed and verified for feasibility of application.

Plasma p217+tau versus NAV4694 amyloid and MK6240 tau PET across the Alzheimer's continuum

Introduction

We evaluated a new Simoa plasma assay for phosphorylated tau (P‐tau) at aa217 enhanced by additional p‐tau sites (p217+tau).

Methods

Plasma p217+tau levels were compared to ¹⁸F‐NAV4694 amyloid beta (Aβ) positron emission tomography (PET) and ¹⁸F‐MK6240 tau PET in 174 cognitively impaired (CI) and 223 cognitively unimpaired (CU) participants.

Results

Compared to Aβ− CU, the plasma levels of p217+tau increased 2‐fold in Aβ+ CU and 3.5‐fold in Aβ+ CI. In Aβ− the p217+tau levels did not differ significantly between CU and CI. P217+tau correlated with Aβ centiloids P = .67 (CI, P = .64; CU, P = .45) and tau SUVR_MTP = .63 (CI, P = .69; CU, P = .34). Area under curve (AUC) for Alzheimer's disease (AD) dementia versus Aβ− CU was 0.94, for AD dementia versus other dementia was 0.93, for Aβ+ versus Aβ− PET was 0.89, and for tau+ versus tau− PET was 0.89.

Discussion

Plasma p217+tau levels elevate early in the AD continuum and correlate well with Aβ and tau PET.

A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer's Disease Spectrum

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative condition driven by multifactorial etiology. Mild cognitive impairment (MCI) is a transitional condition between healthy aging and dementia. No reliable biomarkers are available to predict the conversion from MCI to AD.

OBJECTIVE

To evaluate the use of machine learning (ML) on a wealth of data offered by the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Alzheimer's Disease Metabolomics Consortium (ADMC) database in the prediction of the MCI to AD conversion.

METHODS

We implemented an ML-based Random Forest (RF) algorithm to predict conversion from MCI to AD. Data related to the study population (587 MCI subjects) were analyzed by RF as separate or combined features and assessed for classification power. Four classes of variables were considered: neuropsychological test scores, AD-related cerebrospinal fluid (CSF) biomarkers, peripheral biomarkers, and structural magnetic resonance imaging (MRI) variables.

RESULTS

The ML-based algorithm exhibited 86% accuracy in predicting the AD conversion of MCI subjects. When assessing the features that helped the most, neuropsychological test scores, MRI data, and CSF biomarkers were the most relevant in the MCI to AD prediction. Peripheral parameters were effective when employed in association with neuropsychological test scores. Age and sex differences modulated the prediction accuracy. AD conversion was more effectively predicted in females and younger subjects.

CONCLUSION

Our findings support the notion that AD-related neurodegenerative processes result from the concerted activity of multiple pathological mechanisms and factors that act inside and outside the brain and are dynamically affected by age and sex.

Family members' perspectives on learning cognitively unimpaired older adults' amyloid-β PET scan results

BACKGROUND/OBJECTIVES

Disclosure of Alzheimer's disease (AD) risk information to cognitively unimpaired older adults may become more common if preclinical AD is shown to be identifiable and amenable to treatment. Little, however, is known about how families will react to this information.

DESIGN AND SETTING

Semi-structured telephonic interviews.

PARTICIPANTS

Seventy study partners (mean age = 68 [±11]; 50% female; 70% spouses/significant others; 18% children, siblings; 12% friends) of cognitively unimpaired adults who learned a personalized AD dementia risk estimate and an amyloid-β PET scan result through their participation in preclinical AD research.

MEASUREMENT

Interviewees were asked about their desire for information regarding their family member's AD dementia risk, baseline expectations of risk, understanding of amyloid-β PET scan results, and the impact of AD dementia risk information on emotions, health behaviors, and future plans, as well as on perceptions of their family member's or friend's memory.

RESULTS

Interviewees generally understood the AD dementia risk information (83%) and considered it valuable (75%). Risk information perceived as favorable elicited feelings of happiness and relief; unfavorable information elicited disappointment, as well as increased awareness of the participants' memory and monitoring for incipient changes in cognition. While noting that AD dementia risk information was not medically actionable at this time due to the lack of disease-modifying therapies, some interviewees described changes to their family members' and their own health behaviors and future plans.

CONCLUSION

Guidelines for the disclosure of AD dementia risk estimates and biomarker results to cognitively unimpaired adults should account for the needs and interests of individuals and their family members, who may step into a pre-caregiver role.