Biomarkers and Tools for Predicting Alzheimer's Disease in the Preclinical Stage

Alzheimer's disease (AD) is the only leading cause of death for which no disease-modifying therapy is currently available. Over the past decade, a string of disappointing clinical trial results has forced us to shift our focus to the preclinical stage of AD, which represents the most promising therapeutic window. However, the accurate diagnosis of preclinical AD requires the presence of brain β- amyloid deposition determined by cerebrospinal fluid or amyloid-positron emission tomography, significantly limiting routine screening and diagnosis in non-tertiary hospital settings. Thus, an easily accessible marker or tool with high sensitivity and specificity is highly needed. Recently, it has been discovered that individuals in the late stage of preclinical AD may not be truly "asymptomatic" in that they may have already developed subtle or subjective cognitive decline. In addition, advances in bloodderived biomarker studies have also allowed the detection of pathologic changes in preclinical AD. Exosomes, as cell-to-cell communication messengers, can reflect the functional changes of their source cell. Methodological advances have made it possible to extract brain-derived exosomes from peripheral blood, making exosomes an emerging biomarker carrier and liquid biopsy tool for preclinical AD. The eye and its associated structures have rich sensory-motor innervation. In this regard, studies have indicated that they may also provide reliable markers. Here, our report covers the current state of knowledge of neuropsychological and eye tests as screening tools for preclinical AD and assesses the value of blood and brain-derived exosomes as carriers of biomarkers in conjunction with the current diagnostic paradigm.

Increased Serum Beta-Secretase 1 Activity is an Early Marker of Alzheimer's Disease

BACKGROUND

Beta-site APP cleaving enzyme 1 (BACE1) is the rate-limiting enzyme in amyloid-β (Aβ) plaques formation. BACE1 activity is increased in brains of patients with AD and mild cognitive impairment (MCI) and plasma levels of BACE1 appears to reflect those in the brains.

OBJECTIVE

In this work, we investigated the role of serum BACE1 activity as biomarker for AD, estimating the diagnostic accuracy of the assay and assessing the correlation of BACE1 activity with levels of Aβ 1 - 40, Aβ 1 - 42, and Aβ 40/42 ratio in serum, known biomarkers of brain amyloidosis.

METHODS

Serum BACE1 activity and levels of Aβ 1 - 40, Aβ 1 - 42, were assessed in 31 AD, 28 MCI, diagnosed as AD at follow-up (MCI-AD), and 30 controls. The BACE1 analysis was performed with a luciferase assay, where interpolation of relative fluorescence units with a standard curve of concentration reveals BACE1 activity. Serum levels of Aβ 1 - 40, Aβ 1 - 42 were measured with the ultrasensitive Single Molecule Array technology.

RESULTS

BACE1 was increased (higher than 60%) in AD and MCI-AD: a cut-off of 11.04 kU/L discriminated patients with high sensitivity (98.31%) and specificity (100%). Diagnostic accuracy was higher for BACE1 than Aβ 40/42 ratio. High BACE1 levels were associated with worse cognitive performance and earlier disease onset, which was anticipated by 8 years in patients with BACE1 values above the median value (>  16.67 kU/L).

CONCLUSION

Our results provide new evidence supporting serum/plasma BACE1 activity as an early biomarker of AD.

Exploring brain glucose metabolic patterns in cognitively normal adults at risk of Alzheimer's disease: A cross-validation study with Chinese and ADNI cohorts

OBJECTIVE

Disease-related metabolic brain patterns have been verified for a variety of neurodegenerative diseases including Alzheimer's disease (AD). This study aimed to explore and validate the pattern derived from cognitively normal controls (NCs) in the Alzheimer's continuum.

METHODS

This study was based on two cohorts; one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the other from the Sino Longitudinal Study on Cognitive Decline (SILCODE). Each subject underwent [18F]fluoro-2-deoxyglucose positron emission tomography (PET) and [18F]florbetapir-PET imaging. Participants were binary-grouped based on β-amyloid (Aβ) status, and the positivity was defined as Aβ+. Voxel-based scaled subprofile model/principal component analysis (SSM/PCA) was used to generate the "at-risk AD-related metabolic pattern (ARADRP)" for NCs. The pattern expression score was obtained and compared between the groups, and receiver operating characteristic curves were drawn. Notably, we conducted cross-validation to verify the robustness and correlation analyses to explore the relationships between the score and AD-related pathological biomarkers.

RESULTS

Forty-eight Aβ+ NCs and 48 Aβ- NCs were included in the ADNI cohort, and 25 Aβ+ NCs and 30 Aβ- NCs were included in the SILCODE cohort. The ARADRPs were identified from the combined cohorts and the two separate cohorts, characterized by relatively lower regional loadings in the posterior parts of the precuneus, posterior cingulate, and regions of the temporal gyrus, as well as relatively higher values in the superior/middle frontal gyrus and other areas. Patterns identified from the two separate cohorts showed some regional differences, including the temporal gyrus, basal ganglia regions, anterior parts of the precuneus, and middle cingulate. Cross-validation suggested that the pattern expression score was significantly higher in the Aβ+ group of both cohorts (p < 0.01), and contributed to the diagnosis of Aβ+ NCs (with area under the curve values of 0.696-0.815). The correlation analysis revealed that the score was related to tau pathology measured in cerebrospinal fluid (p-tau: p < 0.02; t-tau: p < 0.03), but not Aβ pathology assessed with [18F]florbetapir-PET (p > 0.23).

CONCLUSIONS

ARADRP exists for NCs, and the acquired pattern expression score shows a certain ability to discriminate Aβ+ NCs from Aβ- NCs. The SSM/PCA method is expected to be helpful in the ultra-early diagnosis of AD in clinical practice.