Cerebrospinal fluid levels of synaptic and neuronal integrity correlate with gray matter volume and amyloid load in the precuneus of cognitively intact older adults

The potential of blood neurofilament light as a marker of neurodegeneration for Alzheimer's disease

Over the past several years, there has been a surge in blood biomarker studies examining the value of plasma or serum neurofilament light (NfL) as a biomarker of neurodegeneration for Alzheimer's disease. However, there have been limited efforts to combine existing findings to assess the utility of blood NfL as a biomarker of neurodegeneration for Alzheimer's disease. In addition, we still need better insight into the specific aspects of neurodegeneration that are reflected by the elevated plasma or serum concentration of NfL. In this review, we survey the literature on the cross-sectional and longitudinal relationships between blood-based NfL levels and other, neuroimaging-based, indices of neurodegeneration in individuals on the Alzheimer's continuum. Then, based on the biomarker classification established by the FDA-NIH Biomarker Working group, we determine the utility of blood-based NfL as a marker for monitoring the disease status (i.e. monitoring biomarker) and predicting the severity of neurodegeneration in older adults with and without cognitive decline (i.e. a prognostic or a risk/susceptibility biomarker). The current findings suggest that blood NfL exhibits great promise as a monitoring biomarker because an increased NfL level in plasma or serum appears to reflect the current severity of atrophy, hypometabolism and the decline of white matter integrity, particularly in the brain regions typically affected by Alzheimer's disease. Longitudinal evidence indicates that blood NfL can be useful not only as a prognostic biomarker for predicting the progression of neurodegeneration in patients with Alzheimer's disease but also as a susceptibility/risk biomarker predicting the likelihood of abnormal alterations in brain structure and function in cognitively unimpaired individuals with a higher risk of developing Alzheimer's disease (e.g. those with a higher amyloid-β). There are still limitations to current research, as discussed in this review. Nevertheless, the extant literature strongly suggests that blood NfL can serve as a valuable prognostic and susceptibility biomarker for Alzheimer's disease-related neurodegeneration in clinical settings, as well as in research settings.

Amyloid-β42/Neurogranin Ratio as a Potential Index for Cognitive Impairment in Parkinson's Disease

BACKGROUND

Synaptopathy is critical in pathophysiology of Parkinson's disease (PD). Cerebrospinal fluid (CSF) levels of neurogranin (NG) and amyloid-β42 (Aβ42) are considered markers of synaptic dysfunction in neurodegenerative diseases.

OBJECTIVE

To evaluate the CSF synaptopathy-related biomarkers, especially the novel Aβ42/NG ratio, in PD, establishing possible associations with cognitive level and other clinical parameters.

METHODS

Levels of NG, Aβ42, amyloid-β40, total and phosphorylated tau, and Aβ42/NG ratio were measured in 30 PD patients and 30 controls and correlated with cognitive and motor parameters. The accuracy in distinguishing the cognitive status was determined.

RESULTS

NG and Aβ42 were significantly reduced in PD, with higher NG levels in patients with worse cognition. The Aβ42/NG ratio showed a direct correlation with Mini-Mental State Examination, independently from age and sex, and differentiated cognitively impaired patients with 92% sensitivity and 71.4% specificity, accuracy higher than NG alone. No correlations resulted with motor disturbances or therapy.

CONCLUSIONS

The novel Aβ42/NG ratio couples either presynaptic or postsynaptic markers of synaptic dysfunction, representing a potential global index of synaptopathy, useful to track cognitive functions in PD.

Baseline cognition is the best predictor of 4-year cognitive change in cognitively intact older adults

BACKGROUND

We examined in cognitively intact older adults the relative weight of cognitive, genetic, structural and amyloid brain imaging variables for predicting cognitive change over a 4-year time course.

METHODS

One hundred-eighty community-recruited cognitively intact older adults (mean age 68 years, range 52-80 years, 81 women) belonging to the Flemish Prevent Alzheimer's Disease Cohort KU Leuven (F-PACK) longitudinal observational cohort underwent a baseline evaluation consisting of detailed cognitive assessment, structural MRI and 18F-flutemetamol PET. At inclusion, subjects were stratified based on Apolipoprotein E (APOE) ε4 and Brain-Derived Neurotrophic Factor (BDNF) val66met polymorphism according to a factorial design. At inclusion, 15% were amyloid-PET positive (Centiloid >23.4). All subjects underwent 2-yearly follow-up of cognitive performance for a 4-year time period. Baseline cognitive scores were analysed using factor analysis. The slope of cognitive change over time was modelled using latent growth curve analysis. Using correlation analysis, hierarchical regression and mediation analysis, we examined the effect of demographic (age, sex, education) and genetic variables, baseline cognition, MRI volumetric (both voxelwise and region-based) as well as amyloid imaging measures on the longitudinal slope of cognitive change.

RESULTS

A base model of age and sex explained 18.5% of variance in episodic memory decline. This increased to 41.6% by adding baseline episodic memory scores. Adding amyloid load or volumetric measures explained only a negligible additional amount of variance (increase to 42.2%). A mediation analysis indicated that the effect of age on episodic memory scores was partly direct and partly mediated via hippocampal volume. Amyloid load did not play a significant role as mediator between age, hippocampal volume and episodic memory decline.

CONCLUSION

In cognitively intact older adults, the strongest baseline predictor of subsequent episodic memory decline was the baseline episodic memory score. When this score was included, only very limited explanatory power was added by brain volume or amyloid load measures. The data warn against classifications that are purely biomarker-based and highlight the value of baseline cognitive performance levels in predictive models.

System-Level Analysis of Alzheimer's Disease Prioritizes Candidate Genes for Neurodegeneration

Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder. Since the advent of the genome-wide association study (GWAS) we have come to understand much about the genes involved in AD heritability and pathophysiology. Large case-control meta-GWAS studies have increased our ability to prioritize weaker effect alleles, while the recent development of network-based functional prediction has provided a mechanism by which we can use machine learning to reprioritize GWAS hits in the functional context of relevant brain tissues like the hippocampus and amygdala. In parallel with these developments, groups like the Alzheimer’s Disease Neuroimaging Initiative (ADNI) have compiled rich compendia of AD patient data including genotype and biomarker information, including derived volume measures for relevant structures like the hippocampus and the amygdala. In this study we wanted to identify genes involved in AD-related atrophy of these two structures, which are often critically impaired over the course of the disease. To do this we developed a combined score prioritization method which uses the cumulative distribution function of a gene’s functional and positional score, to prioritize top genes that not only segregate with disease status, but also with hippocampal and amygdalar atrophy. Our method identified a mix of genes that had previously been identified in AD GWAS including APOE, TOMM40, and NECTIN2(PVRL2) and several others that have not been identified in AD genetic studies, but play integral roles in AD-effected functional pathways including IQSEC1, PFN1, and PAK2. Our findings support the viability of our novel combined score as a method for prioritizing region- and even cell-specific AD risk genes.

Clinical Utility of the Pathogenesis-Related Proteins in Alzheimer's Disease

Research on the Aβ cascade and alternations of biomarkers in neuro-inflammation, synaptic dysfunction, and neuronal injury followed by Aβ have progressed. But the question is how to use the biomarkers. Here, we examine the evidence and pathogenic implications of protein interactions and the time order of alternation. After the deposition of Aβ, the change of tau, neurofilament light chain (NFL), and neurogranin (Ng) is the main alternation and connection to others. Neuro-inflammation, synaptic dysfunction, and neuronal injury function is exhibited prior to the structural and metabolic changes in the brain following Aβ deposition. The time order of such biomarkers compared to the tau protein is not clear. Despite the close relationship between biomarkers and plaque Aβ deposition, several factors favor one or the other. There is an interaction between some proteins that can predict the brain amyloid burden. The Aβ cascade hypothesis could be the pathway, but not all subjects suffer from Alzheimer's disease (AD) within a long follow-up, even with very elevated Aβ. The interaction of biomarkers and the time order of change require further research to identify the right subjects and right molecular target for precision medicine therapies.

β-Secretase1 biological markers for Alzheimer's disease: state-of-art of validation and qualification

β-Secretase1 (BACE1) protein concentrations and rates of enzyme activity, analyzed in human bodily fluids, are promising candidate biological markers for guidance in clinical trials investigating BACE1 inhibitors to halt or delay the dysregulation of the amyloid-β pathway in Alzheimer's disease (AD). A robust body of evidence demonstrates an association between cerebrospinal fluid/blood BACE1 biomarkers and core pathophysiological mechanisms of AD, such as brain protein misfolding and aggregration, neurodegeneration, and synaptic dysfunction.In pharmacological trials, BACE1 candidate biomarkers may be applied to a wide set of contexts of use (CoU), including proof of mechanism, dose-finding, response and toxicity dose estimation. For clinical CoU, BACE1 biomarkers show good performance for prognosis and disease prediction.The roadmap toward validation and qualification of BACE1 biomarkers requires standardized pre-analytical and analytical protocols to reduce inter-site variance that may have contributed to inconsistent results.BACE1 biomarker-drug co-development programs, including biomarker-guided outcomes and endpoints, may support the identification of sub-populations with a higher probability to benefit from BACE1 inhibitors with a reduced risk of adverse effects, in line with the evolving precision medicine paradigm.

Synaptic biomarkers in CSF aid in diagnosis, correlate with cognition and predict progression in MCI and Alzheimer's disease

INTRODUCTION

Amyloid, Tau, and neurodegeneration biomarkers can stage Alzheimer's Disease (AD). Synaptic biomarkers may help track cognition.

METHODS

In cognitively normal controls, Mild Cognitive Impairment (MCI) and AD, we investigated CSF biomarkers in relation to cognitive measures and as predictors of cognitive and global decline.

RESULTS

There were 90 normal controls (mean age 73.0, 58% women), 57 MCI (mean age 74.3, 35% women), and 46 AD (mean age 70.7, 41% women). CSF Aβ1-42 and Neuronal Pentraxin 2 (NPTX2) were decreased, and CSF Tau, neurogranin, and SNAP25 increased in AD versus controls. Aβ1-42/Tau or NPTX2/Tau discriminated AD and controls best. NPTX2/Tau correlated strongly with cognition in AD and MCI and predicted a 2-3-year decline. We replicated findings in the ADNI cohort.

DISCUSSION

CSF synaptic biomarkers, particularly NPTX2, which regulates synaptic homeostasis, relate to cognition and predict progression in AD beyond Aβ1-42 and Tau. This is relevant for prognosis and clinical trials.

Serum neurofilament heavy chains as early marker of motor neuron degeneration

Objective

To determine whether serum phosphorylated neurofilament heavy chain (pNfH) levels are elevated before patients were diagnosed with sporadic or familial ALS, and what the prognostic value of these prediagnostic pNfH levels is.

Methods

pNfH was measured via ELISA in leftovers of serum drawn for routine purposes before the time of diagnosis. These prediagnostic samples were retrieved from the biobank of the University Hospitals Leuven for 95 patients who in follow‐up received a diagnosis of ALS. Additionally, 35 patients with mild cognitive impairment (MCI) and 85 healthy controls (HC) were included in this retrospective study.

Results

The median disease duration (range) from onset to prediagnostic sampling and from onset to diagnosis was 6.5 (−71.9–36.1) and 9.9 (2.0–40.7) months, respectively. Fifty‐eight percent of the prediagnostic samples had serum pNfH levels above the 95th percentile of pNfH levels measured in HC. Serum pNfH levels (median (range)) were elevated up to 18 months before the diagnosis of ALS (91 pg/mL (6–342 pg/mL)) in comparison with HC (30 pg/mL (6–146 pg/mL); P = 0.05), and increased during the prediagnostic stage, which was not observed in patients with MCI. Furthermore, prediagnostic pNfH levels were a univariate predictor of survival in ALS (hazard ratio (95% CI): 2.16 (1.20–3.87); P = 0.01).

Interpretation

Our findings demonstrate that serum pNfH is elevated well before the time of diagnosis in mainly sporadic ALS patients. These results encourage to prospectively explore if pNfH has an added value to shorten the diagnostic delay in ALS.