Fluid biomarkers in Alzheimer's disease

Advancements and challenges in mouse models of Alzheimer's disease

Alzheimer's disease (AD) poses a significant health challenge worldwide, and the development of effective treatments necessitates a comprehensive understanding of its pathophysiology. Mouse models have been instrumental in offering insights into the crucial pathogenesis of AD. However, current models rarely recapitulate all aspects of AD pathology in patients; thus, translating the findings from mouse to human clinical trials has proved to be complex. In this review, we outline the development of some prevalently used AD mice, with a particular emphasis on the latest advances in newly generated models. In addition, we discuss the advantages and limitations in mouse models of AD and their applications in blood-based biomarkers. Finally, we speculate on potential future research directions.

Examination of plasma biomarkers of amyloid, tau, neurodegeneration, and neuroinflammation in former elite American football players

INTRODUCTION

Blood-based biomarkers offer a promising approach for the detection of neuropathologies from repetitive head impacts (RHI). We evaluated plasma biomarkers of amyloid, tau, neurodegeneration, and inflammation in former football players.

METHODS

The sample included 180 former football players and 60 asymptomatic, unexposed male participants (aged 45-74). Plasma assays were conducted for beta-amyloid (Aβ) 40, Aβ42, hyper-phosphorylated tau (p-tau) 181+231, total tau (t-tau), neurofilament light (NfL), glial fibrillary acidic protein (GFAP), interleukin-6 (IL-6), Aβ42/p-tau181 and Aβ42/Aβ40 ratios. We evaluated their ability to differentiate the groups and associations with RHI proxies and traumatic encephalopathy syndrome (TES).

RESULTS

P-tau181 and p-tau231(padj = 0.016) were higher and Aβ42/p-tau181 was lower(padj = 0.004) in football players compared to controls. Discrimination accuracy for p-tau was modest (area under the curve [AUC] = 0.742). Effects were not attributable to AD-related pathology. Younger age of first exposure (AFE) correlated with higher NfL (padj = 0.03) and GFAP (padj = 0.033). Plasma GFAP was higher in TES-chronic traumatic encephalopathy (TES-CTE) Possible/Probable (padj = 0.008).

DISCUSSION

Plasma p-tau181 and p-tau231, GFAP, and NfL may offer some usefulness for the characterization of RHI-related neuropathologies.

HIGHLIGHTS

Former football players had higher plasma p-tau181 and p-tau231 and lower Aβ42/ptau-181 compared to asymptomatic, unexposed men. Younger age of first exposure was associated with increased plasma NfL and GFAP in older but not younger participants. Plasma GFAP was higher in participants with TES-CTE possible/probable compared to TES-CTE no/suggestive.

Novel plasma protein biomarkers: A time-dependent predictive model for Alzheimer's disease

BACKGROUND

The accurate prediction of Alzheimer's disease (AD) is crucial for the efficient management of its progression. The objective of this research was to construct a new risk predictive model utilizing novel plasma protein biomarkers for predicting AD incidence in the future and analyze their potential biological correlation with AD incidence.

METHODS

A cohort of 440 participants aged 60 years and older from the Alzheimer's Disease Neuroimaging Initiative (ADNI) longitudinal cohort was utilized. The baseline plasma proteomics data was employed to conduct Cox regression, LASSO regression, and cross-validation to identify plasma protein signatures predictive of AD risk. Subsequently, a multivariable Cox proportional hazards model based on these signatures was constructed. The performance of the risk prediction model was evaluated using time-dependent receiver operating characteristic (t-ROC) curves and Kaplan-Meier curves. Additionally, we analyzed the correlations between protein signature expression in plasma and predicted AD risk, the time of AD onset, the expression of protein signatures in cerebrospinal fluid (CSF), the expression of CSF and plasma biomarkers, and APOE ε4 genotypes. Colocalization and Mendelian randomization analyses was conducted to investigate the association between protein features and AD risk. GEO database was utilized to analyze the differential expression of protein features in the blood and brain of AD patients.

RESULTS

We identified seven protein signatures (APOE, CGA, CRP, CCL26, CCL20, NRCAM, and PYY) that independently predicted AD incidence in the future. The risk prediction model demonstrated area under the ROC curve (AUC) values of 0.77, 0.76, and 0.77 for predicting AD incidence at 4, 6, and 8 years, respectively. Furthermore, the model remained stable in the range of the 3rd to the 12th year (ROC ≥ 0.74). The low-risk group, as defined by the model, exhibited a significantly later AD onset compared to the high-risk group (P < 0.0001). Moreover, all protein signatures exhibited significant correlations with AD risk (P < 0.001) and the time of AD onset (P < 0.01). There was no strong correlation between the protein expression levels in plasma and CSF, as well as AD CSF biomarkers. APOE, CGA, and CRP exhibited significantly lower expression levels in APOE ε4 positive individuals (P < 0.05). Additionally, colocalization analysis reveals a significant association between AD and SNP loci in APOE. Mendelian randomization analysis shows a negative correlation between NRCAM and AD risk. Transcriptomic analysis indicates a significant downregulation of NRCAM and PYY in the peripheral blood of AD patients (P < 0.01), while APOE, CGA, and NRCAM are significantly downregulated in the brains of AD patients (P < 0.0001).

CONCLUSION

Our research has successfully identified protein signatures in plasma as potential risk biomarkers that can independently predict AD onset in the future. Notably, this risk prediction model has demonstrated commendable predictive performance and stability over time. These findings underscore the promising utility of plasma protein signatures in dynamically predicting the risk of AD, thereby facilitating early screening and intervention strategies.

Standard versus High Cardiopulmonary Bypass Flow Rate: A Randomized Controlled Subtrial Comparing Brain Injury Biomarker Release

OBJECTIVES

To compare brain injury biomarker release levels between two different cardiopulmonary bypass (CPB) flow rates in elective cardiac surgery and to explore differences in postoperative delirium between groups and associations between age, sex, CPB time, oxygen levels, and near-infrared spectroscopy, and biomarker levels.

DESIGN

A randomized controlled substudy trial SETTING: Sahlgrenska University Hospital, Sweden PARTICIPANTS: Forty patients undergoing elective cardiac surgery with CPB INTERVENTION: Patients were assigned at random to either a standard (2.4 L/min/m2) or a high (2.9 L/min/m2) CPB flow rate.

MEASUREMENTS AND MAIN RESULTS

Glial fibrillary acidic protein, neurofilament light chain, total-tau, and phosphorylated-tau217 were sampled in plasma before anesthesia induction, after 60 minutes on CPB, and at 30 minutes, 24 hours, and 72 hours post-CPB. Mixed models for repeated measures were used to analyze differences in biomarker levels between groups and to assess relationships, which showed no differences between the 2 flow rate groups. There also was no difference in the occurrence of delirium between the 2 groups. Associations were found between age and increased neurofilament light chain levels. Female sex, oxygen delivery >330 mL/min/m2, and near-infrared spectroscopy level >60% were associated with lower biomarker levels.

CONCLUSIONS

An increased flow rate did not have any significant effects on biomarker levels compared to a standard flow rate. Several associations were identified between treatment characteristics and biomarker levels. No difference in delirium was seen.

The causal relationship between CSF metabolites and GBM: a two-sample mendelian randomization analysis

BACKGROUND

Glioblastoma multiforme (GBM) is a highly aggressive primary malignant brain tumor characterized by rapid progression, poor prognosis, and high mortality rates. Understanding the relationship between cerebrospinal fluid (CSF) metabolites and GBM is crucial for identifying potential biomarkers and pathways involved in the pathogenesis of this devastating disease.

METHODS

In this study, Mendelian randomization (MR) analysis was employed to investigate the causal relationship between 338 CSF metabolites and GBM. The data for metabolites were obtained from a genome-wide association study summary dataset based on 291 individuals, and the GBM data was derived from FinnGen included 91 cases and 174,006 controls of European descent. The Inverse Variance Weighted method was utilized to estimate the causal effects. Supplementary comprehensive assessments of causal effects between CSF metabolites and GBM were conducted using MR-Egger regression, Weighted Median, Simple Mode, and Weighted Mode methods. Additionally, tests for heterogeneity and pleiotropy were performed.

RESULTS

Through MR analysis, a total of 12 identified metabolites and 2 with unknown chemical properties were found to have a causal relationship with GBM. 1-palmitoyl-2-stearoyl-gpc (16:0/18:0), 7-alpha-hydroxy-3-oxo-4-cholestenoate, Alpha-tocopherol, Behenoyl sphingomyelin (d18:1/22:0), Cysteinylglycine, Maleate, Uracil, Valine, X-12,101, X-12,104 and Butyrate (4:0) are associated with an increased risk of GBM. N1-methylinosine, Stachydrine and Succinylcarnitine (c4-dc) are associated with decreased GBM risk.

CONCLUSION

In conclusion, this study sheds light on the intricate interplay between CSF metabolites and GBM, offering novel perspectives on disease mechanisms and potential treatment avenues. By elucidating the role of CSF metabolites in GBM pathogenesis, this research contributes to the advancement of diagnostic capabilities and targeted therapeutic interventions for this aggressive brain tumor. Further exploration of these findings may lead to improved management strategies and better outcomes for patients with GBM.

A genetic and proteomic comparison of key AD biomarkers across tissues

INTRODUCTION

Plasma has been proposed as an alternative to cerebrospinal fluid (CSF) for measuring Alzheimer's disease (AD) biomarkers, but no studies have analyzed in detail which biofluid is more informative for genetics studies of AD.

METHOD

Eleven proteins associated with AD (α-synuclein, apolipoprotein E [apoE], CLU, GFAP, GRN, NfL, NRGN, SNAP-25, TREM2, VILIP-1, YKL-40) were assessed in plasma (n = 2317) and CSF (n = 3107). Both plasma and CSF genome-wide association study (GWAS) analyses were performed for each protein, followed by functional annotation. Additional characterization for each biomarker included calculation of correlations and predictive power.

RESULTS

Eighteen plasma protein quantitative train loci (pQTLs) associated with 10 proteins and 16 CSF pQTLs associated with 9 proteins were identified. Plasma and CSF shared some genetic loci, but protein levels between tissues correlated weakly. CSF protein levels better associated with AD compared to plasma.

DISCUSSION

The present results indicate that CSF is more informative than plasma for genetic studies in AD.

HIGHLIGHTS

The identification of novel protein quantitative trait loci (pQTLs) in both plasma and cerebrospinal fluid (CSF). Plasma and CSF levels of neurodegeneration-related proteins correlated weakly. CSF is more informative than plasma for genetic studies of Alzheimer's disease (AD). Neurofilament light (NfL), triggering receptor expressed on myeloid cells 2 (TREM2), and chitinase-3-like protein 1 (YKL-40) tend to show relatively strong inter-tissue associations. A novel signal in the apolipoprotein E (APOE) region was identified, which is an eQTL for APOC1.

Aging, sex, metabolic and life experience factors: Contributions to neuro-inflammaging in Alzheimer's disease research

Alzheimer's disease (AD) is prevalent around the world, yet our understanding of the disease is still very limited. Recent work suggests that the cornerstone of AD may include the inflammation that accompanies it. Failure of a normal pro-inflammatory immune response to resolve may lead to persistent central inflammation that contributes to unsuccessful clearance of amyloid-beta plaques as they form, neuronal death, and ultimately cognitive decline. Individual metabolic, and dietary (lipid) profiles can differentially regulate this inflammatory process with aging, obesity, poor diet, early life stress and other inflammatory factors contributing to a greater risk of developing AD. Here, we integrate evidence for the interface between these factors, and how they contribute to a pro-inflammatory brain milieu. In particular, we discuss the importance of appropriate polyunsaturated fatty acids (PUFA) in the diet for the metabolism of specialised pro-resolving mediators (SPMs); raising the possibility for dietary strategies to improve AD outlook.

Early- and Late-Onset Alzheimer's Disease: Two Sides of the Same Coin?

Early-onset Alzheimer's disease (EOAD), defined as Alzheimer's disease onset before 65 years of age, has been significantly less studied than the "classic" late-onset form (LOAD), although EOAD often presents with a more aggressive disease course, caused by variants in the APP, PSEN1, and PSEN2 genes. EOAD has significant differences from LOAD, including encompassing diverse phenotypic manifestations, increased genetic predisposition, and variations in neuropathological burden and distribution. Phenotypically, EOAD can be manifested with non-amnestic variants, sparing the hippocampi with increased tau burden. The aim of this article is to review the different genetic bases, risk factors, pathological mechanisms, and diagnostic approaches between EOAD and LOAD and to suggest steps to further our understanding. The comprehension of the monogenic form of the disease can provide valuable insights that may serve as a roadmap for understanding the common form of the disease.

Biofluid biomarkers for Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial neurodegenerative disease, with a complex pathogenesis and an irreversible course. Therefore, the early diagnosis of AD is particularly important for the intervention, prevention, and treatment of the disease. Based on the different pathophysiological mechanisms of AD, the research progress of biofluid biomarkers are classified and reviewed. In the end, the challenges and perspectives of future research are proposed.

Biomarker Changes during 20 Years Preceding Alzheimer's Disease

BACKGROUND

Biomarker changes that occur in the period between normal cognition and the diagnosis of sporadic Alzheimer's disease have not been extensively investigated in longitudinal studies.

METHODS

We conducted a multicenter, nested case-control study of Alzheimer's disease biomarkers in cognitively normal participants who were enrolled in the China Cognition and Aging Study from January 2000 through December 2020. A subgroup of these participants underwent testing of cerebrospinal fluid (CSF), cognitive assessments, and brain imaging at 2-year-to-3-year intervals. A total of 648 participants in whom Alzheimer's disease developed were matched with 648 participants who had normal cognition, and the temporal trajectories of CSF biochemical marker concentrations, cognitive testing, and imaging were analyzed in the two groups.

RESULTS

The median follow-up was 19.9 years (interquartile range, 19.5 to 20.2). CSF and imaging biomarkers in the Alzheimer's disease group diverged from those in the cognitively normal group at the following estimated number of years before diagnosis: amyloid-beta (Aβ)42, 18 years; the ratio of Aβ42 to Aβ40, 14 years; phosphorylated tau 181, 11 years; total tau, 10 years; neurofilament light chain, 9 years; hippocampal volume, 8 years; and cognitive decline, 6 years. As cognitive impairment progressed, the changes in CSF biomarker levels in the Alzheimer's disease group initially accelerated and then slowed.

CONCLUSIONS

In this study involving Chinese participants during the 20 years preceding clinical diagnosis of sporadic Alzheimer's disease, we observed the time courses of CSF biomarkers, the times before diagnosis at which they diverged from the biomarkers from a matched group of participants who remained cognitively normal, and the temporal order in which the biomarkers became abnormal. (Funded by the Key Project of the National Natural Science Foundation of China and others; ClinicalTrials.gov number, NCT03653156.).

Novel aspects of the phosphorylation and structure of pathological tau: implications for tauopathy biomarkers

The deposition of highly phosphorylated and aggregated tau is a characteristic of tauopathies, including Alzheimer's disease. It has long been known that different isoforms of tau are aggregated in different cell types and brain regions in each tauopathy. Recent advances in analytical techniques revealed the details of the biochemical and structural biological differences of tau specific to each tauopathy. In this review, we explain recent advances in the analysis of post-translational modifications of tau, particularly phosphorylation, brought about by the development of mass-spectrometry and Phos-tag technology. We then discuss the structure of tau filaments in each tauopathy revealed by the advent of cryo-EM. Finally, we describe the progress in biofluid and imaging biomarkers for tauopathy. This review summarizes current efforts to elucidate the characteristics of pathological tau and the landscape of the use of tau as a biomarker to diagnose and determine the pathological stage of tauopathy.

Type 2 Diabetes Moderates the Association Between Amyloid and 1-Year Change in Everyday Functioning in Older Veterans

BACKGROUND

Type 2 diabetes mellitus (T2DM) affects ∼25% of Veterans, a prevalence rate double that of the general population. T2DM is associated with greater dementia risk and has been shown to exacerbate the impact of Alzheimer's disease (AD) risk factors on declines in daily functioning; however, there are few studies that investigate these patterns in older Veterans.

OBJECTIVE

This study sought to determine whether T2DM moderates the association between amyloid-β (Aβ) positron emission tomography (PET) and 1-year change in everyday functioning in older Veterans.

METHODS

One-hundred-ninety-eight predominately male Vietnam-Era Veterans without dementia from the Department of Defense-Alzheimer's Disease Neuroimaging Initiative (DoD-ADNI) with (n = 74) and without (n = 124) T2DM completed Aβ PET imaging and everyday functioning measures, including the Clinical Dementia Rating-Sum of Boxes (CDR-SB) and Everyday Cognition (ECog). Linear mixed effects models tested the moderating role of T2DM on the association between Aβ PET and 1-year change in everyday functioning.

RESULTS

The 3-way T2DM×Aβ PET×time interaction was significant for CDR-SB (p < 0.001) as well as the Memory (p = 0.007) and Language (p = 0.011) subscales from the ECog. Greater amyloid burden was associated with greater increases in functional difficulties, but only in Veterans with T2DM.

CONCLUSIONS

Higher Aβ was only associated with declines in everyday functioning over 1 year in Veterans with T2DM. Given that people with T2DM are more likely to have co-occurring cerebrovascular disease, the combination of multiple neuropathologies may result in faster declines. Future studies should examine how diabetes duration, severity, and medications impact these associations.

Correlative Imaging to Detect Rare HIV Reservoirs and Associated Damage in Tissues

Correlative light-electron microscopy (CLEM) has evolved in the last decades, especially after significant developments in sample preparation, imaging acquisition, software, spatial resolution, and equipment, including confocal, live-cell, super-resolution, and electron microscopy (scanning, transmission, focused ion beam, and cryo-electron microscopy). However, the recent evolution of different laser-related techniques, such as mass spectrometry imaging (MSI) and laser capture microdissection, could further expand spatial imaging capabilities into high-resolution OMIC approaches such as proteomic, lipidomics, small molecule, and drug discovery. Here, we will describe a protocol to integrate the detection of rare viral reservoirs with imaging mass spectrometry.

GAP-43 closely interacts with BDNF in hippocampal neurons and is associated with Alzheimer's disease progression

Introduction

Growth-associated protein 43 (GAP-43) is known as a neuronal plasticity protein because it is widely expressed at high levels in neuronal growth cones during axonal regeneration. GAP-43 expressed in mature adult neurons is functionally important for the neuronal communication of synapses in learning and memory. Brain-derived neurotrophic factor (BDNF) is closely related to neurodegeneration and synaptic plasticity during the aging process. However, the molecular mechanisms regulating neurodegeneration and synaptic plasticity underlying the pathogenesis and progression of Alzheimer's disease (AD) still remain incompletely understood.

Methods

Remarkably, the expressions of GAP-43 and BDNF perfectly match in various neurons in the Human Brain Atlas database. Moreover, GAP-43 and BDNF are highly expressed in a healthy adults' hippocampus brain region and are inversely correlated with the amyloid beta (Aβ), which is the pathological peptide of amyloid plaques found in the brains of patients with AD.

Results

These data led us to investigate the impact of the direct molecular interaction between GAP-43 and BDNF in hippocampal neuron fate. In this study, we show that GAP-43 and BDNF are inversely associated with pathological molecules for AD (Tau and Aβ). In addition, we define the three-dimensional protein structure for GAP-43 and BDNF, including the predictive direct binding sites via analysis using ClusPro 2.0, and demonstrate that the deprivation of GAP-43 and BDNF triggers hippocampal neuronal death and memory dysfunction, employing the GAP-43 or BDNF knock-down cellular models and 5XFAD mice.

Conclusion

These results show that GAP-43 and BDNF are direct binding partners in hippocampal neurons and that their molecular signaling might be potential therapeutic targets for AD.