Blood-based biomarkers for Alzheimer's disease

Modeling the Simultaneous Dynamics of Proteins in Blood Plasma and the Cerebrospinal Fluid in Human In Vivo

The analysis of protein dynamics or turnover in patients has the potential to reveal altered protein recycling, such as in Alzheimer's disease, and to provide informative data regarding drug efficacy or certain biological processes. The observed protein dynamics in a solid tissue or a fluid is the net result of not only protein synthesis and degradation but also transport across biological compartments. We report an accurate 3-biological compartment model able to simultaneously account for the protein dynamics observed in blood plasma and the cerebrospinal fluid (CSF) including a hidden central nervous system (CNS) compartment. We successfully applied this model to 69 proteins of a single individual displaying similar or very different dynamics in plasma and CSF. This study puts a strong emphasis on the methods and tools needed to develop this type of model. We believe that it will be useful to any researcher dealing with protein dynamics data modeling.

Choroid plexus volume as a novel candidate neuroimaging marker of the Alzheimer's continuum

BACKGROUND

Enlarged choroid plexus (ChP) volume has been reported in patients with Alzheimer's disease (AD) and inversely correlated with cognitive performance. However, its clinical diagnostic and predictive value, and mechanisms by which ChP impacts the AD continuum remain unclear.

METHODS

This prospective cohort study enrolled 607 participants [healthy control (HC): 110, mild cognitive impairment (MCI): 269, AD dementia: 228] from the Chinese Imaging, Biomarkers, and Lifestyle study between January 1, 2021, and December 31, 2022. Of the 497 patients on the AD continuum, 138 underwent lumbar puncture for cerebrospinal fluid (CSF) hallmark testing. The relationships between ChP volume and CSF pathological hallmarks (Aβ42, Aβ40, Aβ42/40, tTau, and pTau181), neuropsychological tests [Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Neuropsychiatric Inventory (NPI), and Activities of Daily Living (ADL) scores], and multimodal neuroimaging measures [gray matter volume, cortical thickness, and corrected cerebral blood flow (cCBF)] were analyzed using partial Spearman's correlation. The mediating effects of four neuroimaging measures [ChP volume, hippocampal volume, lateral ventricular volume (LVV), and entorhinal cortical thickness (ECT)] on the relationship between CSF hallmarks and neuropsychological tests were examined. The ability of the four neuroimaging measures to identify cerebral Aβ42 changes or differentiate among patients with AD dementia, MCI and HCs was determined using receiver operating characteristic analysis, and their associations with neuropsychological test scores at baseline were evaluated by linear regression. Longitudinal associations between the rate of change in the four neuroimaging measures and neuropsychological tests scores were evaluated on the AD continuum using generalized linear mixed-effects models.

RESULTS

The participants' mean age was 65.99 ± 8.79 years. Patients with AD dementia exhibited the largest baseline ChP volume than the other groups (P < 0.05). ChP volume enlargement correlated with decreased Aβ42 and Aβ40 levels; lower MMSE and MoCA and higher NPI and ADL scores; and lower volume, cortical thickness, and cCBF in other cognition-related regions (all P < 0.05). ChP volume mediated the association of Aβ42 and Aβ40 levels with MMSE scores (19.08% and 36.57%), and Aβ42 levels mediated the association of ChP volume and MMSE or MoCA scores (39.49% and 34.36%). ChP volume alone better identified cerebral Aβ42 changes than LVV alone (AUC = 0.81 vs. 0.67, P = 0.04) and EC thickness alone (AUC = 0.81 vs.0.63, P = 0.01) and better differentiated patients with MCI from HCs than hippocampal volume alone (AUC = 0.85 vs. 0.81, P = 0.01), and LVV alone (AUC = 0.85 vs.0.82, P = 0.03). Combined ChP and hippocampal volumes significantly increased the ability to differentiate cerebral Aβ42 changes and patients among AD dementia, MCI, and HCs groups compared with hippocampal volume alone (all P < 0.05). After correcting for age, sex, years of education, APOE ε4 status, eTIV, and hippocampal volume, ChP volume was associated with MMSE, MoCA, NPI, and ADL score at baseline, and rapid ChP volume enlargement was associated with faster deterioration in NPI scores with an average follow-up of 10.03 ± 4.45 months (all P < 0.05).

CONCLUSIONS

ChP volume may be a novel neuroimaging marker associated with neurodegenerative changes and clinical AD manifestations. It could better detect the early stages of the AD and predict prognosis, and significantly enhance the differential diagnostic ability of hippocampus on the AD continuum.

Neuropsychiatric symptoms as a prodromal factor in Alzheimer's type neurodegenerative disease: A scoping review

Objective: Identifying neuropsychiatric symptoms (NPS) can aid in the early detection of Alzheimer's disease (AD); however, there is still a need for a greater consensus. This review aims to delineate the predominant NPS, compile a comprehensive list of the most commonly employed NPS assessment tools, and corroborate the principal findings regarding the link between NPS and neuropsychological assessment and neurobiological substrates. Methods: To conduct this scoping review, we followed the Preferred Reporting Items for Systematic Reviews guidelines and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). We searched for relevant articles published between 2017 and 2023 in MEDLINE, PsycINFO, PubMed, Web of Science, and Cochrane Library. Results: Of the 61 eligible articles, depression, anxiety, and apathy were the main NPSs. The Neuropsychiatric Inventory Questionnaire and Neuropsychiatric Inventory were the primary assessment tools used to evaluate NPS. Correlations between NPS severity and neurobiological markers were considered clinically significant. Furthermore, clinical procedures prioritized the use of global cognitive screening tools, assessments of executive functions, and functionality evaluations. Conclusion: Standardization of procedures is necessary because of the diversity of methods. The data show that NPS can predict the etiology, severity, form, and type of disease progression, serving as a precursor sign of AD. The results of the most common cognitive screening tools and NPS instruments provided an interesting overview of future clinical approaches.

The associations between nutritional status and physical frailty and Alzheimer's disease plasma biomarkers in older cognitively unimpaired adults with positive of amyloid-β PET

BACKGROUND & AIMS

It has been revealed good nutritional status and no physical frailty, which are modifiable lifestyle factors, are linked to less cognitive decline and a lower risk of Alzheimer's disease (AD). We aimed to investigate the associations between nutritional status and physical frailty and plasma AD biomarkers, especially the Tau-associated biomarkers in older cognitively unimpaired (CU) adults with higher β-amyloid (Aβ) burden.

METHODS

The nutritional status and physical frailty were assessed via Mini-Nutritional Assessment Short-Form (MNA-SF) and Fried frailty index. The participants underwent the examination of plasma AD biomarkers and 18F-florbetapir PET scan as well as 18F-MK6240 PET in the validation cohort. Correlation and multiple linear regression analyses were used to investigate the associations between nutritional status and frailty and AD biomarkers.

RESULTS

Two cohorts were included in our study. A total of 129 participants with Aβ-PET positive were enrolled in the development cohort. Multiple linear regression analysis showed MNA-SF scores, normal nutritional status, Fried frailty index scores, frailty and some domains of frailty including weight loss, maximal grip strength and exhaustion were associated with plasma p-Tau-181. Furthermore, weight loss, Fried frailty index scores and frailty were associated with higher Aβ-PET standard uptake value ratio. We further performed subgroup analyses stratified by age, sex and apolipoprotein E ε4 genotype to investigate the beneficial characteristics of nutrition and frailty in the special subgroups. Validation cohort contained 38 Aβ-PET positive participants. MNA-SF scores, normal nutritional status, Fried frailty index scores and frailty were associated with Tau burden evaluated by 18F-MK6240 PET Braak-like stages.

CONCLUSIONS

Our data indicates that normal nutritional status and no physical frailty may be associated with expected trend of plasma AD biomarkers, especially less Tau pathology in older CU adults with Aβ deposition. Adjusting to these characteristics of nutrition and physical frailty may help reduce the risk of AD development.

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.

Androgen deprivation therapy exacerbates Alzheimer's-associated cognitive decline via increased brain immune cell infiltration

Androgen deprivation therapy (ADT) for prostate cancer is associated with an increased risk of dementia, including Alzheimer's disease (AD). The mechanistic connection between ADT and AD-related cognitive impairment in patients with prostate cancer remains elusive. We established a clinically relevant prostate cancer-bearing AD mouse model to explore this. Both tumor-bearing and ADT induce complex changes in immune and inflammatory responses in peripheral blood and in the brain. ADT disrupts the integrity of the blood-brain barrier (BBB) and promotes immune cell infiltration into the brain, enhancing neuroinflammation and gliosis without affecting the amyloid plaque load. Moreover, treatment with natalizumab, an FDA-approved drug targeting peripheral immune cell infiltration, reduces neuroinflammation and improves cognitive function in this model. Our study uncovers an inflammatory mechanism, extending beyond amyloid pathology, that underlies ADT-exacerbated cognitive deficits, and suggests natalizumab as a potentially effective treatment in alleviating the detrimental effects of ADT on cognition.

The appropriate sample-handling procedure for measuring the plasma β-amyloid level using a fully automated immunoassay

Plasma β-amyloid (Aβ) assays are a promising tool for Alzheimer's disease diagnosis in clinical practice. To obtain reliable results, establishing an appropriate sample-handling procedure for each analytical platform is warranted. This study proposes an appropriate sample-handling procedure using HISCL analyzer by elucidating the individual/combined effects of pre-analytical parameters on plasma Aβ42/Aβ40 levels. We investigated the effects of various pre-analytical parameters, including storage times for whole blood, plasma, and freezing conditions, on plasma Aβ42/Aβ40 levels, and confirmed if these values met the acceptable criteria. Plasma Aβ42/Aβ40 levels were acceptable in all conditions. We determined our protocol by confirming that plasma Aβ42/Aβ40 levels remained acceptable when combining pre-analytical parameters. We established an appropriate sample-handling protocol that ensures reliable measurement of plasma Aβ42/Aβ40 levels using HISCL analyzer. We believe the Aβ assay, with our protocol, shows promise for aiding AD diagnosis in clinical settings.

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.

Automatic offline-capable smartphone paper-based microfluidic device for efficient biomarker detection of Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is a prevalent neurodegenerative disease with no effective treatment. Efficient and rapid detection plays a crucial role in mitigating and managing AD progression. Deep learning-assisted smartphone-based microfluidic paper analysis devices (μPADs) offer the advantages of low cost, good sensitivity, and rapid detection, providing a strategic pathway to address large-scale disease screening in resource-limited areas. However, existing smartphone-based detection platforms usually rely on large devices or cloud servers for data transfer and processing. Additionally, the implementation of automated colorimetric enzyme-linked immunoassay (c-ELISA) on μPADs can further facilitate the realization of smartphone μPADs platforms for efficient disease detection.

RESULTS

This paper introduces a new deep learning-assisted offline smartphone platform for early AD screening, offering rapid disease detection in low-resource areas. The proposed platform features a simple mechanical rotating structure controlled by a smartphone, enabling fully automated c-ELISA on μPADs. Our platform successfully applied sandwich c-ELISA for detecting the β-amyloid peptide 1-42 (Aβ 1-42, a crucial AD biomarker) and demonstrated its efficacy in 38 artificial plasma samples (healthy: 19, unhealthy: 19, N = 6). Moreover, we employed the YOLOv5 deep learning model and achieved an impressive 97 % accuracy on a dataset of 1824 images, which is 10.16 % higher than the traditional method of curve-fitting results. The trained YOLOv5 model was seamlessly integrated into the smartphone using the NCNN (Tencent's Neural Network Inference Framework), enabling deep learning-assisted offline detection. A user-friendly smartphone application was developed to control the entire process, realizing a streamlined "samples in, answers out" approach.

SIGNIFICANCE

This deep learning-assisted, low-cost, user-friendly, highly stable, and rapid-response automated offline smartphone-based detection platform represents a good advancement in point-of-care testing (POCT). Moreover, our platform provides a feasible approach for efficient AD detection by examining the level of Aβ 1-42, particularly in areas with low resources and limited communication infrastructure.

Associations of Plasma Tau with Amyloid and Tau PET: Results from the Community-Based Framingham Heart Study

Background

Associations of plasma total tau levels with future risk of AD have been described.

Objective

To examine the extent to which plasma tau reflects underlying AD brain pathology in cognitively healthy individuals.

Methods

We examined cross-sectional associations of plasma total tau with 11C-Pittsburgh Compound-B (PiB)-PET and 18F-Flortaucipir (FTP)-PET in middle-aged participants at the community-based Framingham Heart Study.

Results

Our final sample included 425 participants (mean age 57.6± 9.9, 50% F). Plasma total tau levels were positively associated with amyloid-β deposition in the precuneus region (β±SE, 0.11±0.05; p = 0.025). A positive association between plasma total tau and tau PET in the rhinal cortex was suggested in participants with higher amyloid-PET burden and in APOEɛ4 carriers.

Conclusions

Our study highlights that plasma total tau is a marker of amyloid deposition as early as in middle-age.

SIMOA Diagnostics on Alzheimer's Disease and Frontotemporal Dementia

BACKGROUND

Accurate diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD) represents a health issue due to the absence of disease traits. We assessed the performance of a SIMOA panel in cerebrospinal fluid (CSF) from 43 AD and 33 FTD patients with 60 matching Control subjects in combination with demographic-clinical characteristics.

METHODS

136 subjects (AD: n = 43, FTD: n = 33, Controls: n = 60) participated. Single-molecule array (SIMOA), glial fibrillary acidic protein (GFAP), neurofilament light (NfL), TAU, and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) in CSF were analyzed with a multiplex neuro 4plex kit. Receiver operating characteristic (ROC) curve analysis compared area under the curve (AUC), while the principal of the sparse partial least squares discriminant analysis (sPLS-DA) was used with the intent to strengthen the identification of confident disease clusters.

RESULTS

CSF exhibited increased levels of all SIMOA biomarkers in AD compared to Controls (AUCs: 0.71, 0.86, 0.92, and 0.94, respectively). Similar patterns were observed in FTD with NfL, TAU, and UCH-L1 (AUCs: 0.85, 0.72, and 0.91). sPLS-DA revealed two components explaining 19% and 9% of dataset variation.

CONCLUSIONS

CSF data provide high diagnostic accuracy among AD, FTD, and Control discrimination. Subgroups of demographic-clinical characteristics and biomarker concentration highlighted the potential of combining different kinds of data for successful and more efficient cohort clustering.

Joint effect of testosterone and neurofilament light chain on cognitive decline in men: The Shanghai Aging Study

INTRODUCTION

The association of testosterone and cognitive decline is inconclusive, and its joint effect with neurofilaments light chain (NfL) remains largely unknown.

METHODS

A total of 581 non-demented older men in the Shanghai Aging Study were included. Blood total testosterone (TT), free testosterone (FT), and NfL were measured at baseline. The relationships between TT, FT, TT/FT-NfL, and cognitive decline were explored by Cox regression models.

RESULTS

During a median follow-up of 6.7 years, there was an inverse association between TT/FT and cognitive decline (TT, trend p = .004, Q1 vs Q4, hazard ratio [HR] = 4.39, 95% confidence interval [CI] = 1.60 to 12.04; FT, trend p = .002, Q1 vs Q4, HR = 5.29, 95% CI = 1.50 to 16.89). Compared to participants with high TT/FT-low NfL, those with low TT/FT-high NfL had significantly higher risks of cognitive decline (TT, HR = 5.10, 95% CI = 1.11 to 23.40; FT, HR = 6.14, 95% CI = 1.34 to 28.06).

DISCUSSION

Our findings suggest that the combination of testosterone and neurodegenerative markers may provide reliable predictive insights into future cognitive decline.

HIGHLIGHTS

Testosterone is inversely associated with cognitive decline in older men. There is a joint effect of testosterone and NfL on cognitive decline. Sex hormone and neurodegeneration may synergistically contribute to cognitive deterioration.

Distinctive contribution of two additional residues in protein aggregation of Aβ42 and Aβ40 isoforms

Amyloid-β (Aβ) is one of the amyloidogenic intrinsically disordered proteins (IDPs) that self-assemble to protein aggregates, incurring cell malfunction and cytotoxicity. While Aβ has been known to regulate multiple physiological functions, such as enhancing synaptic functions, aiding in the recovery of the blood-brain barrier/brain injury, and exhibiting tumor suppression/antimicrobial activities, the hydrophobicity of the primary structure promotes pathological aggregations that are closely associated with the onset of Alzheimer's disease (AD). Aβ proteins consist of multiple isoforms with 37-43 amino acid residues that are produced by the cleavage of amyloid-β precursor protein (APP). The hydrolytic products of APP are secreted to the extracellular regions of neuronal cells. Aβ 1-42 (Aβ42) and Aβ 1-40 (Aβ40) are dominant isoforms whose significance in AD pathogenesis has been highlighted in numerous studies to understand the molecular mechanism and develop AD diagnosis and therapeutic strategies. In this review, we focus on the differences between Aβ42 and Aβ40 in the molecular mechanism of amyloid aggregations mediated by the two additional residues (Ile41 and Ala42) of Aβ42. The current comprehension of Aβ42 and Aβ40 in AD progression is outlined, together with the structural features of Aβ42/Aβ40 amyloid fibrils, and the aggregation mechanisms of Aβ42/Aβ40. Furthermore, the impact of the heterogeneous distribution of Aβ isoforms during amyloid aggregations is discussed in the system mimicking the coexistence of Aβ42 and Aβ40 in human cerebrospinal fluid (CSF) and plasma. [BMB Reports 2024; 57(6): 263-272].

miR-519a-3p, found to regulate cellular prion protein during Alzheimer's disease pathogenesis, as a biomarker of asymptomatic stages

Clinical relevance of miRNAs as biomarkers is growing due to their stability and detection in biofluids. In this, diagnosis at asymptomatic stages of Alzheimer's disease (AD) remains a challenge since it can only be made at autopsy according to Braak NFT staging. Achieving the objective of detecting AD at early stages would allow possible therapies to be addressed before the onset of cognitive impairment. Many studies have determined that the expression pattern of some miRNAs is dysregulated in AD patients, but to date, none has been correlated with downregulated expression of cellular prion protein (PrPC) during disease progression. That is why, by means of cross studies of miRNAs up-regulated in AD with in silico identification of potential miRNAs-binding to 3'UTR of human PRNP gene, we selected miR-519a-3p for our study. Then, in vitro experiments were carried out in two ways. First, we validated miR-519a-3p target on 3'UTR-PRNP, and second, we analyzed the levels of PrPC expression after using of mimic technology on cell culture. In addition, RT-qPCR was performed to analyzed miR-519a-3p expression in human cerebral samples of AD at different stages of disease evolution. Additionally, samples of other neurodegenerative diseases such as other non-AD tauopathies and several synucleinopathies were included in the study. Our results showed that miR-519a-3p overlaps with PRNP 3'UTR in vitro and promotes downregulation of PrPC. Moreover, miR-519a-3p was found to be up-regulated exclusively in AD samples from stage I to VI, suggesting its potential use as a novel label of preclinical stages of the disease.

Is blood pTau a reliable indicator of the CSF status? A narrative review

BACKGROUND

The identification of biomarkers for the early diagnosis of Alzheimer's disease (AD) is a crucial goal of the current research. Blood biomarkers are less invasive, easier to obtain and achievable by a cheaper means than those on cerebrospinal fluid (CSF) and significantly more economic than functional neuroimaging investigations; thus, a great interest is focused on blood isoforms of the phosphorylated Tau protein (pTau), indicators of ongoing tau pathology (i.e. neurofibrillary tangles, NFTs, an AD neuropathological hallmark) in the central nervous system (CNS). However, current data often highlight discordant results about the ability of blood pTau to predict CSF status.

OBJECTIVE

We aim to synthesise the studies that compared pTau levels on CSF and blood to assess their correlation in AD continuum.

METHODS

We performed a narrative literature review using, first, MEDLINE (via PubMed) by means of MeSH terms, and then, we expanded the reults by means of Scopus and Web of Sciences to be as inclusive as possible. Finally, we added work following an expert opinion. Only papers presenting original data on pTau values on both blood and CSF were included.

RESULTS

The 33 included studies show an extreme heterogeneity in terms of pTau isoform (pTau181, 217 and 231), laboratory methods, diagnostic criteria and choice of comparison groups. Most studies evaluated plasma pTau181, while data on other isoforms and serum are scarcer.

DISCUSSION

Most papers identify a correlation between CSF and blood measurements. Furthermore, even when not specified, it is often possible to show an increase in blood pTau values as AD-related damage progresses in the AD continuum and higher values in AD than in other neurodegenerative diseases. Notably, plasma pTau231 seems the first biomarker to look for in the earliest and pre-clinical stages, quickly followed by pTau217 and, finally, by pTau181.

CONCLUSIONS

Our results encourage the use of blood pTau for the early identification of patients with AD continuum.

Choriocapillaris reduction accurately discriminates against early-onset Alzheimer's disease

INTRODUCTION

This study addresses the urgent need for non-invasive early-onset Alzheimer's disease (EOAD) prediction. Using optical coherence tomography angiography (OCTA), we present a choriocapillaris model sensitive to EOAD, correlating with serum biomarkers.

METHODS

Eighty-four EOAD patients and 73 controls were assigned to swept-source OCTA (SS-OCTA) or the spectral domain OCTA (SD-OCTA) cohorts. Our hypothesis on choriocapillaris predictive potential in EOAD was tested and validated in these two cohorts.

RESULTS

Both cohorts revealed diminished choriocapillaris signals, demonstrating the highest discriminatory capability (area under the receiver operating characteristic curve: SS-OCTA 0.913, SD-OCTA 0.991; P < 0.001). A sparser SS-OCTA choriocapillaris correlated with increased serum amyloid beta (Aβ)42, Aβ42/40, and phosphorylated tau (p-tau)181 levels (all P < 0.05). Apolipoprotein E status did not affect choriocapillaris measurement.

DISCUSSION

The choriocapillaris, observed in both cohorts, proves sensitive to EOAD diagnosis, and correlates with serum Aβ and p-tau181 levels, suggesting its potential as a diagnostic tool for identifying and tracking microvascular changes in EOAD.

HIGHLIGHTS

Optical coherence tomography angiography may be applied for non-invasive screening of Alzheimer's disease (AD). Choriocapillaris demonstrates high sensitivity and specificity for early-onset AD diagnosis. Microvascular dynamics abnormalities are associated with AD.

Combining plasma Aβ and p-tau217 improves detection of brain amyloid in non-demented elderly

BACKGROUND

Maximizing the efficiency to screen amyloid-positive individuals in asymptomatic and non-demented aged population using blood-based biomarkers is essential for future success of clinical trials in the early stage of Alzheimer's disease (AD). In this study, we elucidate the utility of combination of plasma amyloid-β (Aβ)-related biomarkers and tau phosphorylated at threonine 217 (p-tau217) to predict abnormal Aβ-positron emission tomography (PET) in the preclinical and prodromal AD.

METHODS

We designed the cross-sectional study including two ethnically distinct cohorts, the Japanese trial-ready cohort for preclinica and prodromal AD (J-TRC) and the Swedish BioFINDER study. J-TRC included 474 non-demented individuals (CDR 0: 331, CDR 0.5: 143). Participants underwent plasma Aβ and p-tau217 assessments, and Aβ-PET imaging. Findings in J-TRC were replicated in the BioFINDER cohort including 177 participants (cognitively unimpaired: 114, mild cognitive impairment: 63). In both cohorts, plasma Aβ(1-42) (Aβ42) and Aβ(1-40) (Aβ40) were measured using immunoprecipitation-MALDI TOF mass spectrometry (Shimadzu), and p-tau217 was measured with an immunoassay on the Meso Scale Discovery platform (Eli Lilly).

RESULTS

Aβ-PET was abnormal in 81 participants from J-TRC and 71 participants from BioFINDER. Plasma Aβ42/Aβ40 ratio and p-tau217 individually showed moderate to high accuracies when detecting abnormal Aβ-PET scans, which were improved by combining plasma biomarkers and by including age, sex and APOE genotype in the models. In J-TRC, the highest AUCs were observed for the models combining p-tau217/Aβ42 ratio, APOE, age, sex in the whole cohort (AUC = 0.936), combining p-tau217, Aβ42/Aβ40 ratio, APOE, age, sex in the CDR 0 group (AUC = 0.948), and combining p-tau217/Aβ42 ratio, APOE, age, sex in the CDR 0.5 group (AUC = 0.955), respectively. Each subgroup results were replicated in BioFINDER, where the highest AUCs were seen for models combining p-tau217, Aβ42/40 ratio, APOE, age, sex in cognitively unimpaired (AUC = 0.938), and p-tau217/Aβ42 ratio, APOE, age, sex in mild cognitive impairment (AUC = 0.914).

CONCLUSIONS

Combination of plasma Aβ-related biomarkers and p-tau217 exhibits high performance when predicting Aβ-PET positivity. Adding basic clinical information (i.e., age, sex, APOE ε genotype) improved the prediction in preclinical AD, but not in prodromal AD. Combination of Aβ-related biomarkers and p-tau217 could be highly useful for pre-screening of participants in clinical trials of preclinical and prodromal AD.

Potential Application of MicroRNAs and Some Other Molecular Biomarkers in Alzheimer's Disease

Alzheimer's disease (AD) is the world's most common neurodegenerative disease, expected to affect up to one-third of the elderly population in the near future. Among the major challenges in combating AD are the inability to reverse the damage caused by the disease, expensive diagnostic tools, and the lack of specific markers for the early detection of AD. This paper highlights promising research directions for molecular markers in AD diagnosis, including the diagnostic potential of microRNAs. The latest molecular methods for diagnosing AD are discussed, with particular emphasis on diagnostic techniques prior to the appearance of full AD symptoms and markers detectable in human body fluids. A collection of recent studies demonstrates the promising potential of molecular methods in AD diagnosis, using miRNAs as biomarkers. Up- or downregulation in neurodegenerative diseases may not only provide a new diagnostic tool but also serve as a marker for differentiating neurodegenerative diseases. However, further research in this direction is needed.

Photobiomodulation in experimental models of Alzheimer's disease: state-of-the-art and translational perspectives

Alzheimer's disease (AD) poses a significant public health problem, affecting millions of people across the world. Despite decades of research into therapeutic strategies for AD, effective prevention or treatment for this devastating disorder remains elusive. In this review, we discuss the potential of photobiomodulation (PBM) for preventing and alleviating AD-associated pathologies, with a focus on the biological mechanisms underlying this therapy. Future research directions and guidance for clinical practice for this non-invasive and non-pharmacological therapy are also highlighted. The available evidence indicates that different treatment paradigms, including transcranial and systemic PBM, along with the recently proposed remote PBM, all could be promising for AD. PBM exerts diverse biological effects, such as enhancing mitochondrial function, mitigating the neuroinflammation caused by activated glial cells, increasing cerebral perfusion, improving glymphatic drainage, regulating the gut microbiome, boosting myokine production, and modulating the immune system. We suggest that PBM may serve as a powerful therapeutic intervention for AD.

The Enigma of Tau Protein Aggregation: Mechanistic Insights and Future Challenges

Tau protein misfolding and aggregation are pathological hallmarks of Alzheimer's disease and over twenty neurodegenerative disorders. However, the molecular mechanisms of tau aggregation in vivo remain incompletely understood. There are two types of tau aggregates in the brain: soluble aggregates (oligomers and protofibrils) and insoluble filaments (fibrils). Compared to filamentous aggregates, soluble aggregates are more toxic and exhibit prion-like transmission, providing seeds for templated misfolding. Curiously, in its native state, tau is a highly soluble, heat-stable protein that does not form fibrils by itself, not even when hyperphosphorylated. In vitro studies have found that negatively charged molecules such as heparin, RNA, or arachidonic acid are generally required to induce tau aggregation. Two recent breakthroughs have provided new insights into tau aggregation mechanisms. First, as an intrinsically disordered protein, tau is found to undergo liquid-liquid phase separation (LLPS) both in vitro and inside cells. Second, cryo-electron microscopy has revealed diverse fibrillar tau conformations associated with different neurodegenerative disorders. Nonetheless, only the fibrillar core is structurally resolved, and the remainder of the protein appears as a "fuzzy coat". From this review, it appears that further studies are required (1) to clarify the role of LLPS in tau aggregation; (2) to unveil the structural features of soluble tau aggregates; (3) to understand the involvement of fuzzy coat regions in oligomer and fibril formation.

Real-word application of the AT(N) classification and disease-modifying treatment eligibility in a hospital-based cohort

BACKGROUND AND OBJECTIVES

The AT(N) classification system stratifies patients based on biomarker profiles, including amyloid-beta deposition (A), tau pathology (T), and neurodegeneration (N). This study aims to apply the AT(N) classification to a hospital-based cohort of patients with cognitive decline and/or dementia, within and outside the Alzheimer's disease (AD) continuum, to enhance our understanding of the multidimensional aspects of AD and related disorders. Furthermore, we wish to investigate how many cases from our cohort would be eligible for the available disease modifying treatments, such as aducanemab and lecanemab.

METHODS

We conducted a retrospective evaluation of 429 patients referred to the Memory Center of IRCCS San Raffaele Hospital in Milan. Patients underwent clinical/neuropsychological assessments, lumbar puncture, structural brain imaging, and positron emission tomography (FDG-PET). Patients were stratified according to AT(N) classification, group comparisons were performed and the number of eligible cases for anti-β amyloid monoclonal antibodies was calculated.

RESULTS

Sociodemographic and clinical features were similar across groups. The most represented group was A + T + N + accounting for 38% of cases, followed by A + T - N + (21%) and A - T - N + (20%). Although the clinical presentation was similar, the A + T + N + group showed more severe cognitive impairment in memory, language, attention, executive, and visuospatial functions compared to other AT(N) groups. Notably, T + patients demonstrated greater memory complaints compared to T -  cases. FDG-PET outperformed MRI and CT in distinguishing A + from A -  patients. Although 61% of the observed cases were A + , only 17% of them were eligible for amyloid-targeting treatments.

DISCUSSION

The AT(N) classification is applicable in a real-world clinical setting. The classification system provided insights into clinical management and treatment strategies. Low cognitive performance and specific regional FDG-PET hypometabolism at diagnosis are highly suggestive for A + T + or A - T + profiles. This work provides also a realistic picture of the proportion of AD patients eligible for disease modifying treatments emphasizing the need for early detection.

Surface-functionalized SERS platform for deep learning-assisted diagnosis of Alzheimer's disease

Early diagnosis of Alzheimer's disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Raman spectroscopy (SERS) analysis of blood-based biomarkers is a convenient alternative to rapidly obtain spectral information from biofluids. However, despite the rapid acquisition of spectral information from biofluids, it is challenging to distinguish spectral features of biomarkers due to interference from biofluidic components. Here, we introduce a deep learning-assisted, SERS-based platform for separate analysis of blood-based amyloid β (1-42) and metabolites, enabling the diagnosis of Alzheimer's disease. SERS substrates consisting of Au nanowire arrays are fabricated and functionalized in two characteristic ways to compare the validity of different Alzheimer's disease biomarkers measured on our SERS system. The 6E10 antibody is immobilized for the capture of amyloid β (1-42) and analysis of its oligomerization process, while various self-assembled monolayers are attached for different dipole interactions with blood-based metabolites. Ultimately, SERS spectra of blood plasma of Alzheimer's disease patients and human controls are measured on the substrates and classified via advanced deep learning techniques that automatically extract informative features to learn generalizable representations. Accuracies up to 99.5% are achieved for metabolite-based analyses, which are verified with an explainable artificial intelligence technique that identifies key spectral features used for classification and for deducing significant biomarkers.

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.

Present and Future of Blood-Based Biomarkers of Alzheimer's Disease: Beyond the Classics

The field of blood-based biomarkers for Alzheimer's disease (AD) has advanced at an incredible pace, especially after the development of sensitive analytic platforms that can facilitate large-scale screening. Such screening will be important when more sophisticated diagnostic methods are scarce and expensive. Thus, blood-based biomarkers can potentially reduce diagnosis inequities among populations from different socioeconomic contexts. This large-scale screening can be performed so that older adults at risk of cognitive decline assessed using these methods can then undergo more complete assessments with classic biomarkers, increasing diagnosis efficiency and reducing costs to the health systems. Blood-based biomarkers can also aid in assessing the effect of new disease-modifying treatments. This paper reviews recent advances in the area, focusing on the following leading candidates for blood-based biomarkers: amyloid-beta (Aβ), phosphorylated tau isoforms (p-tau), neurofilament light (NfL), and glial fibrillary acidic (GFAP) proteins, as well as on new candidates, Neuron-Derived Exosomes contents (NDEs) and Transactive response DNA-binding protein-43 (TDP-43), based on data from longitudinal observational cohort studies. The underlying challenges of validating and incorporating these biomarkers into routine clinical practice and primary care settings are also discussed. Importantly, challenges related to the underrepresentation of ethnic minorities and socioeconomically disadvantaged persons must be considered. If these challenges are overcome, a new time of cost-effective blood-based biomarkers for AD could represent the future of clinical procedures in the field and, together with continued prevention strategies, the beginning of an era with a lower incidence of dementia worldwide.

DNA tetrahedron-based dual-signal fluorescence detection of apoE4 gene sites on a microplate reader

As a neurodegenerative disorder, Alzheimer's disease (AD) is characterized by cognitive dysfunction and behavioral impairment. Among the various genetic risk factors for AD, apoE4 gene plays a pivotal role in the onset and progression of AD, and detection of apoE4 gene holds significance for prevention and early diagnosis of AD. Herein, dual-signal fluorescence detection of fragments associated with apoE ε4 allele near codon 112 (Tc1) and codon 158 (Tc2) was achieved using DNA tetrahedron nanostructure (DTN). The Förster resonance energy transfer (FRET) process in the DTN was initiated in which the nucleic acid intercalating dye thiazole orange (TO) served as the donor and the cyanine dyes of cyanine3 (Cy3) and cyanine5 (Cy5) at the two vertices of DTN served as the acceptors. In the presence of Tc1 and Tc2, the FRET process between TO and the cyanine dyes was hindered by the enzymatic cleavage reaction, which ensures the dual-signal fluorescence assay of apoE4 gene sites. The limit of detection for Tc1 and Tc2 was estimated to be 0.82 nM and 0.77 nM, respectively, and the whole assay was accomplished within 1 h on a microplate reader. The proposed method thus possesses the advantages of easy operation, short detection time, and high-throughput capability.

Expected wait times for access to a disease-modifying Alzheimer's treatment in England: A modelling study

OBJECTIVES

We previously analysed the preparedness to deliver a disease-modifying Alzheimer's treatment in the United Kingdom and predicted substantial wait times. This study updates the prediction for the National Health Service (NHS) in England, using an improved model and newer data.

METHODS

We reviewed published data on capacity for diagnosis of cognitive impairment combined with expert input and constructed a model for wait times to access from 2023 to 2043. The model tracks patients from initial evaluation in primary care, cognitive testing by a dementia specialist, confirmatory biomarker testing with positron emission tomography (PET) scans or examination of cerebrospinal fluid and infusion delivery. Capacity for specialist visits and PET scans are assumed to be capacity constrained, and cerebrospinal fluid testing and infusion delivery to be scalable.

RESULTS

Capacity constraints were projected to result in substantial wait times: patients referred to specialists based on a brief cognitive test, which is the current standard of care, would expect an overall initial wait times of 56 months in 2023, increasing to 129 months in 2029 and then falling slowly to around 100 months. Use of a blood test for the confirmation of Alzheimer's pathology as an additional triage step, would reduce wait times to around 17 to 25 months.

DISCUSSION

The NHS England lacks capacity to provide timely access to a disease-modifying treatment, which is estimated to result in significant wait times and potentially avoidable disease progression. Better diagnostic tools at initial evaluation may reduce delays.

The free plasma amyloid Aβ1-42/Aβ1-40 ratio predicts conversion to dementia for subjects with mild cognitive impairment with performance equivalent to that of the total plasma Aβ1-42/Aβ1-40 ratio. The BALTAZAR study

BACKGROUND AND PURPOSE

Blood-based biomarkers are a non-invasive solution to predict the risk of conversion of mild cognitive impairment (MCI) to dementia. The utility of free plasma amyloid peptides (not bound to plasma proteins and/or cells) as an early indicator of conversion to dementia is still debated, as the results of studies have been contradictory. In this context, we investigated whether plasma levels of the free amyloid peptides Aβ1-42 and Aβ1-40 and the free plasma Aβ1-42/Aβ1-40 ratio are associated with the conversion of MCI to dementia, in particular AD, over three years of follow-up in a subgroup of the BALTAZAR cohort. We also compared their predictive value to that of total plasma Aβ1-42 and Aβ1-40 levels and the total plasma Aβ1-42/Aβ1-40 ratio.

METHODS

The plasma Aβ1-42 and Aβ1-40 peptide assay was performed using the INNO-BIA kit (Fujirebio Europe). Free amyloid levels (defined by the amyloid fraction directly accessible to antibodies of the assay) were obtained with the undiluted plasma, whereas total amyloid levels were obtained after the dilution of plasma (1/3) with a denaturing buffer. Free and total Aβ1-42 and Aβ1-40 levels were measured at inclusion for a subgroup of participants (N = 106) with mild cognitive impairment (MCI) from the BALTAZAR study (a large-scale longitudinal multicenter cohort with a three-year follow-up). Associations between conversion and the free/total plasma Aβ1-42 and Aβ1-40 levels and Aβ1-42/Aβ1-40 ratio were analyzed using logistic and Cox Proportional Hazards models. Demographic, clinical, cognitive (MMSE, ADL and IADL), APOE, and MRI characteristics (relative hippocampal volume) were compared using non-parametric (Mann-Whitney) or parametric (Student) tests for quantitative variables and Chi-square or Fisher exact tests for qualitative variables.

RESULTS

The risk of conversion to dementia was lower for patients in the highest quartile of free plasma Aβ1-42/Aβ1-40 (≥ 25.8%) than those in the three lower quartiles: hazard ratio = 0.36 (95% confidence interval [0.15-0.87]), after adjustment for age, sex, education, and APOE ε4 (p-value = 0.022). This was comparable to the risk of conversion in the highest quartile of total plasma Aβ1-42/Aβ1-40: hazard ratio = 0.37 (95% confidence interval [0.16-0.89], p-value = 0.027). However, while patients in the highest quartile of total plasma Aβ1-42/Aβ1-40 showed higher MMSE scores and a higher hippocampal volume than patients in the three lowest quartiles of total plasma Aβ1-42/Aβ1-40, as well as normal CSF biomarker levels, the patients in the highest quartile of free plasma Aβ1-42/Aβ1-40 did not show any significant differences in MMSE scores, hippocampal volume, or CSF biomarker levels relative to the three lowest quartiles of free plasma Aβ1-42/Aβ1-40.

CONCLUSION

The free plasma Aβ1-42/Aβ1-40 ratio is associated with a risk of conversion from MCI to dementia within three years, with performance comparable to that of the total plasma Aβ1-42/Aβ1-40 ratio. Threshold levels of the free and total plasma Aβ1-42/Aβ1-40 ratio could be determined, with a 60% lower risk of conversion for patients above the threshold than those below.

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.

Subsequent correlated changes in complement component 3 and amyloid beta oligomers in the blood of patients with Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) involves the complement cascade, with complement component 3 (C3) playing a key role. However, the relationship between C3 and amyloid beta (Aβ) in blood is limited.

METHODS

Plasma C3 and Aβ oligomerization tendency (AβOt) were measured in 35 AD patients and 62 healthy controls. Correlations with cerebrospinal fluid (CSF) biomarkers, cognitive impairment, and amyloid positron emission tomography (PET) were analyzed. Differences between biomarkers were compared in groups classified by concordances of biomarkers.

RESULTS

Plasma C3 and AβOt were elevated in AD patients and in CSF or amyloid PET-positive groups. Weak positive correlation was found between C3 and AβOt, while both had strong negative correlations with CSF Aβ42 and cognitive performance. Abnormalities were observed for AβOt and CSF Aβ42 followed by C3 changes.

DISCUSSION

Increased plasma C3 in AD are associated with amyloid pathology, possibly reflecting a defense response for Aβ clearance. Further studies on Aβ-binding proteins will enhance understanding of Aβ mechanisms in blood.

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

INTRODUCTION

Alzheimer's disease (AD) trial participants are often screened for eligibility by brain amyloid positron emission tomography/cerebrospinal fluid (PET/CSF), which is inefficient as many are not amyloid positive. Use of blood-based biomarkers may reduce screen failures.

METHODS

We recruited 755 non-Hispanic White, 115 Hispanic, 112 non-Hispanic Black, and 19 other minority participants across groups of cognitively normal (n = 417), mild cognitive impairment (n = 312), or mild AD (n = 272) participants. Plasma amyloid beta (Aβ)40, Aβ42, Aβ42/Aβ40, total tau, phosphorylated tau (p-tau)181, and p-tau217 were measured; amyloid PET/CSF (n = 956) determined amyloid positivity. Clinical, blood biomarker, and ethnicity/race differences associated with amyloid status were evaluated.

RESULTS

Greater impairment, older age, and carrying an apolipoprotein E (apoE) ε4 allele were associated with greater amyloid burden. Areas under the receiver operating characteristic curve for amyloid status of plasma Aβ42/Aβ40, p-tau181, and p-tau217 with amyloid positivity were ≥ 0.7117 for all ethnoracial groups (p-tau217, ≥0.8128). Age and apoE ε4 adjustments and imputation of biomarker values outside limit of quantitation provided small improvement in predictive power.

DISCUSSION

Blood-based biomarkers are highly associated with amyloid PET/CSF results in diverse populations enrolled at clinical trial sites.

HIGHLIGHTS

Amyloid beta (Aβ)42/Aβ40, phosphorylated tau (p-tau)181, and p-tau 217 blood-based biomarkers predicted brain amyloid positivity. P-tau 217 was the strongest predictor of brain amyloid positivity. Biomarkers from diverse ethnic, racial, and clinical cohorts predicted brain amyloid positivity. Community-based populations have similar Alzheimer's disease (AD) biomarker levels as other populations. A prescreen process with blood-based assays may reduce the number of AD trial screen failures.

Neuropathology, Neuroimaging, and Fluid Biomarkers in Alzheimer's Disease

An improved understanding of the pathobiology of Alzheimer's disease (AD) should lead ultimately to an earlier and more accurate diagnosis of AD, providing the opportunity to intervene earlier in the disease process and to improve outcomes. The known hallmarks of Alzheimer's disease include amyloid-β plaques and neurofibrillary tau tangles. It is now clear that an imbalance between production and clearance of the amyloid beta protein and related Aβ peptides, especially Aβ42, is a very early, initiating factor in Alzheimer's disease (AD) pathogenesis, leading to aggregates of hyperphosphorylation and misfolded tau protein, inflammation, and neurodegeneration. In this article, we review how the AD diagnostic process has been transformed in recent decades by our ability to measure these various elements of the pathological cascade through the use of imaging and fluid biomarkers. The more recently developed plasma biomarkers, especially phosphorylated-tau217 (p-tau217), have utility for screening and diagnosis of the earliest stages of AD. These biomarkers can also be used to measure target engagement by disease-modifying therapies and the response to treatment.

Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease

Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aβ40lumi and Aβ42/Aβ40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aβ40lumi and t-tau/Aβ40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aβ40lumi, p-tau181/Aβ40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.

New approach for early and specific Alzheimer disease diagnosis from different plasma biomarkers

BACKGROUND

Alzheimer Disease (AD) is a complex pathology, in which several biochemical pathways could be involved. Therefore, the development of clinical studies combining different nature biomarkers in an AD diagnosis approach is required. Specifically, the present study evaluated blood biomarkers from different molecular pathways (epigenomics, lipid metabolism, lipid peroxidation), to obtain an early and specific AD diagnosis approach.

METHODS

The participants were classified into early AD (n = 53), and non-AD (healthy controls, other dementias) (n = 83). Blood samples were collected and biochemical determinations (microRNAs, lipids, lipid peroxidation compounds) were carried out by quantitative PCR and liquid chromatography coupled to mass spectrometry, respectively. Then, a logistic regression model with a Bayesian variable selection procedure was developed.

RESULTS

The Bayesian variable selection procedure for microRNAs did not show any relevant variable. Therefore, microRNA biomarkers were excluded. So, the developed model considered only lipids and lipid peroxidation compounds. The corresponding selected variables were age, 18:0 LPC, PGE2, isoprostanes and, isofurans. The validated model (by leave-one-out cross-validation) provided satisfactory diagnosis indexes (AUC 0.83, Sensitivity 87 %, Specificity 79 %).

CONCLUSION

The developed model included biomarkers from different pathways (lipid metabolism, oxidative stress), achieving a promising approach to early, specific and, minimally invasive AD diagnosis. Nevertheless, further work to validate clinically these preliminary results with an external cohort is required. Also, the integration of different compounds coming from several biochemical pathways could constitute a relevant research field for the development of AD therapeutic targets.

A blood-based biomarker workflow for optimal tau-PET referral in memory clinic settings

Blood-based biomarkers for screening may guide tau positrion emissition tomography (PET) scan referrals to optimize prognostic evaluation in Alzheimer's disease. Plasma Aβ42/Aβ40, pTau181, pTau217, pTau231, NfL, and GFAP were measured along with tau-PET in memory clinic patients with subjective cognitive decline, mild cognitive impairment or dementia, in the Swedish BioFINDER-2 study (n = 548) and in the TRIAD study (n = 179). For each plasma biomarker, cutoffs were determined for 90%, 95%, or 97.5% sensitivity to detect tau-PET-positivity. We calculated the percentage of patients below the cutoffs (who would not undergo tau-PET; "saved scans") and the tau-PET-positivity rate among participants above the cutoffs (who would undergo tau-PET; "positive predictive value"). Generally, plasma pTau217 performed best. At the 95% sensitivity cutoff in both cohorts, pTau217 resulted in avoiding nearly half tau-PET scans, with a tau-PET-positivity rate among those who would be referred for a scan around 70%. And although tau-PET was strongly associated with subsequent cognitive decline, in BioFINDER-2 it predicted cognitive decline only among individuals above the referral cutoff on plasma pTau217, supporting that this workflow could reduce prognostically uninformative tau-PET scans. In conclusion, plasma pTau217 may guide selection of patients for tau-PET, when accurate prognostic information is of clinical value.

Exploring the potential of fully automated LUMIPULSE G plasma assays for detecting Alzheimer's disease pathology

BACKGROUND

LUMIPULSE G-automated immunoassays represent a widely used method for the quantification of Alzheimer's disease (AD) biomarkers in the cerebrospinal fluid (CSF). Less invasive blood-based markers confer a promising tool for AD diagnosis at prodromal stages (mild cognitive impairment (MCI)). Highly sensitive assays for the quantification of amyloid-beta (Aβ) and phosphorylated Tau-181 (p-Tau181) in the blood are showing promising results. In this study, we evaluated the clinical performance of the recently available fully automated LUMIPULSE plasma marker assays for detecting brain AD pathology and for predicting progression from MCI to AD dementia stage.

METHODS

A retrospective exploratory cohort of 138 individuals (22 neurological controls [NC], 72 MCI, and 44 AD dementia patients) was included. Data regarding baseline CSF concentrations of Aβ42, Aβ40, t-Tau, and p-Tau181 was available and used to establish the presence of AD brain pathology. Baseline Aβ42, Aβ40, and p-Tau181 concentrations were determined in stored plasma samples using high-throughput fully automated LUMIPULSE assays. Progression from MCI to AD dementia was evaluated during follow-up (mean 6.4 ± 2.5 years). Moreover, a prospective validation cohort of 72 individuals with memory complaints underwent AD biomarker quantification, closely mirroring typical clinical practice. This cohort aimed to confirm the study's main findings.

RESULTS

In the exploratory cohort, correlations between CSF and plasma were moderate for p-Tau181 (ρ = 0.61, p < 0.001) and weak for Aβ42/Aβ40 ratio (ρ = 0.39, p < 0.001). Plasma p-Tau181 and p-Tau181/Aβ42 concentrations were significantly increased while Aβ42/Aβ40 was significantly decreased (p < 0.001) in patients with AD dementia and prodromal AD, as well as in individuals with CSF abnormal amyloid concentrations (A +). Plasma p-Tau181 showed a robust performance in differentiating patients clinically diagnosed as AD (AUC = 0.89; 95% CI 0.83-0.94); A + vs. A - (AUC = 0.84, 95% CI 0.77-0.91) and also in predicting conversion to AD dementia in MCI patients (AUC = 0.89, 95% CI 0.81-0.96). When tested in the validation cohort, plasma p-Tau181 displayed 83.3% of the overall percentage of agreement according to amyloid status.

CONCLUSIONS

Our results show that the measurement of p-Tau181 in plasma has great potential as a non-invasive prognostic screening tool for implementation in a clinical setting.

Implementation of an ultra-sensitive microwell-based electrochemical sensor for the detection of Alzheimer's disease

Alzheimer's Disease (AD) is one of the most common neurodegenerative disorders in elderly people. It is diagnosed by detecting amyloid beta (Aβ) protein in cerebrospinal fluid (CSF) obtained by lumbar puncture or through expensive positron emission tomography (PET) imaging. Although blood-based diagnosis of AD offers a less invasive and cost-effective alternative, the quantification of Aβ is technically challenging due to its low abundance in peripheral blood. To address this, we developed a compact yet highly sensitive microwell-based electrochemical sensor with a densely packed microelectrode array (20 by 20) for enhancing sensitivity. Employing microwells on the working and counter electrodes minimized the leakage current from the metallic conductors into the assay medium, refining the signal fidelity. We achieved a detection limit <10 fg/mL for Aβ by elevating the signal-to-noise ratio, thus capable of AD biomarker quantification. Moreover, the microwell structure maintained the performance irrespective of variations in bead number, indicative of the sensor's robustness. The sensor's efficacy was validated through the analysis of Aβ concentrations in plasma samples from 96 subjects, revealing a significant distinction between AD patients and healthy controls with an area under the receiver operating characteristic curve (AUC) of 0.85. Consequently, our novel microwell-based electrochemical biosensor represents a highly sensitive platform for detecting scant blood-based biomarkers, including Aβ, offering substantial potential for advancing AD diagnostics.

Predicting clinical progression trajectories of early Alzheimer's disease patients

BACKGROUND

Models for forecasting individual clinical progression trajectories in early Alzheimer's disease (AD) are needed for optimizing clinical studies and patient monitoring.

METHODS

Prediction models were constructed using a clinical trial training cohort (TC; n = 934) via a gradient boosting algorithm and then evaluated in two validation cohorts (VC 1, n = 235; VC 2, n = 421). Model inputs included baseline clinical features (cognitive function assessments, APOE ε4 status, and demographics) and brain magnetic resonance imaging (MRI) measures.

RESULTS

The model using clinical features achieved R2 of 0.21 and 0.31 for predicting 2-year cognitive decline in VC 1 and VC 2, respectively. Adding MRI features improved the R2 to 0.29 in VC 1, which employed the same preprocessing pipeline as the TC. Utilizing these model-based predictions for clinical trial enrichment reduced the required sample size by 20% to 49%.

DISCUSSION

Our validated prediction models enable baseline prediction of clinical progression trajectories in early AD, benefiting clinical trial enrichment and various applications.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Targeting blood brain barrier-Remote ischemic conditioning alleviates cognitive impairment in female APP/PS1 rats

AIMS

Alzheimer's disease (AD) is a significant global health concern, and it is crucial that we find effective methods to prevent or slow down AD progression. Recent studies have highlighted the essential role of blood vessels in clearing Aβ, a protein that contributes to AD. Scientists are exploring blood biomarkers as a potential tool for future AD diagnosis. One promising method that may help prevent AD is remote ischemic conditioning (RIC). RIC involves using sub-lethal ischemic-reperfusion cycles on limbs. However, a comprehensive understanding of how RIC can prevent AD and its long-term effectiveness is still lacking. Further research is essential to fully comprehend the potential benefits of RIC in preventing AD.

METHODS

Female wild-type (WT) and APP/PS1 transgenic rats, aged 12 months, underwent ovariectomy and were subsequently assigned to WT, APP/PS1, and APP/PS1 + RIC groups. RIC was conducted five times a week for 4 weeks. The rats' depressive and cognitive behaviors were evaluated using force swimming, open-field tests, novel objective recognition, elevated plus maze, and Barnes maze tests. Evaluation of the neurovascular unit (NVU), synapses, vasculature, astrocytes, and microglia was conducted using immunofluorescence staining (IF), Western blot (WB), and transmission electron microscopy (TEM). Additionally, the cerebro-vasculature was examined using micro-CT, and cerebral blood flow (CBF) was measured using Speckle Doppler. Blood-brain barrier (BBB) permeability was determined by measuring the Evans blue leakage. Finally, Aβ levels in the rat frontal cortex were measured using WB, ELISA, or IF staining.

RESULTS

RIC enhanced memory-related protein expression and rescued depressive-like behavior and cognitive decline in APP/PS1 transgenic rats. Additionally, the intervention protected NVU in the rat frontal cortex, as evidenced by (1) increased expression of TJ (tight junction) proteins, pericyte marker PDGFRβ, and glucose transporter 1 (GLUT1), as well as decreased VCAM1; (2) mitigation of ultrastructure impairment in neuron, cerebral vascular, and astrocyte; (3) upregulation of A2 astrocyte phenotype markers and downregulation of A1 phenotype markers, indicating a shift toward a healthier phenotype. Correspondingly, RIC intervention alleviated neuroinflammation, as evidenced by the decreased Iba1 level, a microglia marker. Meanwhile, RIC intervention elevated CBF in frontal cortex of the rats. Notably, RIC intervention effectively suppressed Aβ toxicity, as demonstrated by the enhancement of α-secretase and attenuation of β-secretase (BACE1) and γ- secretase and Aβ1-42 and Aβ1-40 levels as well.

CONCLUSION

Chronic RIC intervention exerts vascular and neuroprotective roles, suggesting that RIC could be a promising therapeutic strategy targeting the BBB and NVU during AD development.

Evaluation of serum neurofilament light chain and glial fibrillary acidic protein in the diagnosis of Alzheimer's disease

Purpose

This study aimed to evaluate the use of serum neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) in the diagnosis of Alzheimer's disease (AD) and the differential diagnosis between AD and mild cognitive impairment (MCI).

Methods

From September 2021 to October 2022, we collected venous blood from patients and healthy individuals who visited our hospital's Neurology Department, and we isolated serum to detect NfL and GFAP using direct chemiluminescence. The results were analyzed using one-way analysis of variance (ANOVA) analysis and receiver operating characteristic (ROC) curves.

Results

Pairwise comparisons among the three groups showed that compared with the health checkup (HC) group, serum NfL and GFAP were increased in both AD and MCI (PNfL < 0.05, PGFAP < 0.01). There were significant differences in GFAP between MCI and AD groups, and the level in AD group was higher (p < 0.01), while there was no difference in NfL. Both serum NfL and serum GFAP levels can independently diagnose AD (p < 0.01). The ROC curve showed that GFAP had a higher diagnostic efficacy, with an area under the ROC curve (AUC) of 0.928. The cut-off values of the two serum markers for the diagnosis of AD were NfL > 40.09 pg./mL and GFAP >31.40 pg./mL. Sensitivity and specificity for NfL in the diagnosis of AD were 59.6 and 76.2%, respectively, and for GFAP, they were 90.4 and 82.1%, respectively. The combined diagnosis of GFAP and NfL improved the diagnostic efficiency (AUC = 0.931, sensitivity = 78.8%, specificity = 92.3%). The cut-off value of GFAP for the differential diagnosis of MCI and AD was 46.05 pg./mL.

Conclusion

Both serum NfL and serum GFAP can be used as biomarkers for the diagnosis of AD. Serum GFAP has better diagnostic efficacy and can distinguish AD from MCI. A combined diagnosis can improve diagnostic specificity.

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

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

A DNA octahedral amplifier for endogenous circRNA detection and bioimaging in living cells and its biomarker study

The discovery of reliable biomarkers is essential for early diagnosis, treatment, and prognosis assessment of diseases. Many research studies have shown that circRNA is a potential biomarker for diagnosis and prognosis of diseases. However, in situ monitoring circRNA in live cells is still a challenge at present, which brings a major limitation to the development and verification of circRNA as a disease biomarker. In this study, a catalytic hairpin assembly (CHA) reaction-based DNA octahedral amplifier (DOA) was developed for fluorescence resonance energy transfer (FRET) detection and bioimaging of circRNA in living cells. The DOA was first produced by self-assembling a DNA octahedron with six customized single-stranded DNAs, and two hairpins H1 (Cy3) and H2 (Cy5) were then hybridized to four vertices of the DNA octahedron. Idiopathic pulmonary fibrosis (IPF)-related circHIPK3 was used as the target. Once the CHA reaction from H1 and H2 on DOA was activated by a sequence-specific back-splice junction (BSJ) of circHIPK3, a significant FRET signal can be obtained from Cy3 to Cy5. The circHIPK3 was subsequently released to cause the next CHA reaction. Because the DOA has the advantages of the spatial-confinement effect, resistance to nuclease degradation and easy penetration into cells, rapid and excellent signal amplification FRET detection and bioimaging of endogenous circHIPK3 can be achieved in various cells. This study provides a high-precision assay platform to explore the possibility of using circRNA as a biomarker, and it is valuable for circRNA-related early diagnosis and treatment of diseases.

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

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

Early ultrasonic vocalization deficits and related thyroarytenoid muscle pathology in the transgenic TgF344-AD rat model of Alzheimer's disease

Background

Alzheimer's disease (AD) is a progressive neurologic disease and the most common cause of dementia. Classic pathology in AD is characterized by inflammation, abnormal presence of tau protein, and aggregation of β-amyloid that disrupt normal neuronal function and lead to cell death. Deficits in communication also occur during disease progression and significantly reduce health, well-being, and quality of life. Because clinical diagnosis occurs in the mid-stage of the disease, characterizing the prodrome and early stages in humans is currently challenging. To overcome these challenges, we use the validated TgF344-AD (F344-Tg(Prp-APP, Prp-PS1)19/Rrrc) transgenic rat model that manifests cognitive, behavioral, and neuropathological dysfunction akin to AD in humans.

Objectives

The overarching goal of our work is to test the central hypothesis that pathology and related behavioral deficits such as communication dysfunction in part manifest in the peripheral nervous system and corresponding target tissues already in the early stages. The primary aims of this study are to test the hypotheses that: (1) changes in ultrasonic vocalizations (USV) occur in the prodromal stage at 6 months of age and worsen at 9 months of age, (2) inflammation as well as AD-related pathology can be found in the thyroarytenoid muscle (TA) at 12 months of age (experimental endpoint tissue harvest), and to (3) demonstrate that the TgF344-AD rat model is an appropriate model for preclinical investigations of early AD-related vocal deficits.

Methods

USVs were collected from male TgF344-AD (N = 19) and wildtype (WT) Fischer-344 rats (N = 19) at 6 months (N = 38; WT: n = 19; TgF344-AD: n = 19) and 9 months of age (N = 18; WT: n = 10; TgF344-AD: n = 8) and acoustically analyzed for duration, mean power, principal frequency, low frequency, high frequency, peak frequency, and call type. RT-qPCR was used to assay peripheral inflammation and AD-related pathology via gene expressions in the TA muscle of male TgF344-AD rats (n = 6) and WT rats (n = 6) at 12 months of age.

Results

This study revealed a significant reduction in mean power of ultrasonic calls from 6 to 9 months of age and increased peak frequency levels over time in TgF344-AD rats compared to WT controls. Additionally, significant downregulation of AD-related genes Uqcrc2, Bace2, Serpina3n, and Igf2, as well as downregulation of pro-inflammatory gene Myd88 was found in the TA muscle of TgF344-AD rats at 12 months of age.

Discussion

Our findings demonstrate early and progressive vocal deficits in the TgF344-AD rat model. We further provide evidence of dysregulation of AD-pathology-related genes as well as inflammatory genes in the TA muscles of TgF344-AD rats in the early stage of the disease, confirming this rat model for early-stage investigations of voice deficits and related pathology.

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

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

Exploring small non-coding RNAs as blood-based biomarkers to predict Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone.

METHODS

This nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed.

RESULTS

The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD.

CONCLUSIONS

The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.

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.

Novel Panel of Long Noncoding RNAs as Diagnostic Biomarkers for Amnestic Mild Cognitive Impairment in Peripheral Blood

Background

Long noncoding RNAs (lncRNAs) regulate the pathogenesis of Alzheimer's disease (AD).

Objective

To identify lncRNAs in the peripheral blood as potential diagnostic biomarkers for amnestic mild cognitive impairment.

Methods

In the discovery group, a microarray was used to screen for significant differences in lncRNA expression between patients with mild cognitive impairment (MCI) caused by AD and normal controls (NCs) (n = 10; MCI, 5; NC, 5). Furthermore, two analytic groups were assessed (analytic group 1: n = 10; amnestic MCI (aMCI), 5; NC, 5; analytic group 2: n = 30; AD, 10; aMCI, 10; NC, 10) and finalized in the validation group (n = 150; AD, 50; aMCI, 50; NC, 50). In the analytic and validation groups, real-time quantitative reverse-transcription polymerase chain reaction was used to identify differentially expressed lncRNAs between the aMCI and NC groups.

Results

We identified 67 upregulated and 220 downregulated lncRNAs among the expression profiles. The panel with lncRNAs T324988, NR_024049, ENST00000567919, and ENST00000549762 displayed the highest discrimination ability between patients with aMCI and NCs. The area under the receiver operating characteristic curve of this combined model was 0.941, with a sensitivity of 92.00% and specificity of 84.00%.

Conclusions

This study reports on a panel of four lncRNAs as promising biomarkers to diagnose aMCIs.

Blood-Based Biomarkers for Early Alzheimer's Disease Diagnosis in Real-World Settings

As our knowledge about the biology of Alzheimer's disease (AD) expands and we recognize the significance of early intervention for effective treatment, there is a shift in focus toward detecting the disease at an early stage. AD is characterized by the accumulation of misfolded amyloid-β (Aβ) and phosphorylated tau proteins in the brain, leading to the formation of senile plaques and neurofibrillary tangles. While a definitive diagnosis of AD can only be confirmed through autopsy by examining these pathological features, there are now reliable methods available for diagnosing the disease in living individuals. These methods involve analyzing cerebrospinal fluid and using positron emission tomography to accurately assess the presence of Aβ and tau proteins. While these diagnostic markers have shown high accuracy in memory-clinic populations, they do have limitations such as the requirement for invasive lumbar puncture or exposure to ionizing radiation. Additionally, they are not easily accessible outside of specialized healthcare settings. Blood-based biomarkers of the core pathological features of AD are being developed, showing promise for less invasive, scalable identification of AD cases in the community. The advantages for the healthcare systems of this development are obvious, but the diagnostic performance of blood-based biomarkers in broader, non-selected populations outside of retrospective analyses and research cohorts still requires further investigation, including the combination with more effective neuropsychological assessments such as digital cognitive test solutions.

The Return of Biomarker Results in Research: Balancing Complexity, Precision, and Ethical Responsibility

Recent research aimed at the discovery, integration, and communication of health outcome measures (or "biomarkers") in Alzheimer's disease has raised challenging questions related to whether, how and when results from these investigations should be disclosed to research participants. Reflecting the apparent heterogeneity of many neurodegenerative diseases, biomarker or other risk factor results are often probabilistic, interactive, multi-modal, and selective. Such characteristics make it very complex to summarize and communicate to clinicians, researchers, and research participants. Whereas the format and content of academic literature is well-managed by the peer-review process, reporting individualized results to participants involves complex, sensitive, and ethical considerations. This paper describes three key factors to consider in decisions about the return of results to research participants: complexity, precision, and responsibility. The paper also presents six practical recommendations for implementing meaningful and ethical communication with research participants.