The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD/MCI pathogenesis is unclear. This study compared the metabolomic and proteomic signature of plasma from cognitively normal (CN) and dementia patients diagnosed with MCI or AD, to identify specific cellular pathways and new biomarkers altered with the progression of the disease. We analysed 80 plasma samples from individuals with MCI or AD, as well as age- and gender-matched CN individuals, by utilising mass spectrometry methods and data analyses that included combined pathway analysis and model predictions. Several proteins clearly identified AD from the MCI and CN groups and included plasma actins, mannan-binding lectin serine protease 1, serum amyloid A2, fibronectin and extracellular matrix protein 1 and Keratin 9. The integrated pathway analysis showed various metabolic pathways were affected in AD, such as the arginine, alanine, aspartate, glutamate and pyruvate metabolism pathways. Therefore, our multi-omics approach identified novel plasma biomarkers for the MCI and AD groups, identified changes in metabolic processes, and may form the basis of a biomarker panel for stratifying dementia participants in future clinical trials.

Background: The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is poorly understood and the relationships between systemic abnormalities in metabolism and AD/AMCI pathogenesis are unclear. Objective: The aim of the study was to compare the metabolomic and proteomic signature of saliva from cognitively normal and patients diagnosed with MCI or AD, to identify specific cellular pathways altered with the progression of the disease. Methods: We analyzed 80 saliva samples from individuals with MCI or AD as well as age- and gender-matched healthy controls. Saliva proteomic and metabolomic analyses were conducted utilizing mass spectrometry methods and data combined using pathway analysis. Results: We found significant alterations in multiple cellular pathways, demonstrating that at the omics level, disease progression impacts numerous cellular processes. Multivariate statistics using SIMCA showed that partial least squares-data analysis could be used to provide separation of the three groups. Conclusion: This study found significant changes in metabolites and proteins from multiple cellular pathways in saliva. These changes were associated with AD, demonstrating that this approach might prove useful to identify new biomarkers based upon integration of multi-omics parameters.

Introduction: Aging is the primary risk factor for major human pathologies, including cancer, diabetes, cardiovascular diseases, and neurodegenerative diseases such as Alzheimer’s Disease (AD). AD is a progressive degenerative disorder of the brain and is the most common form of dementia.Methods: To-date no simple, inexpensive and minimally invasive procedure is available to confirm with certainty the early diagnosis of AD prior to the manifestations of symptoms characteristic of the disease. Therefore, if population screening of individuals is to be performed, easily accessible tissues would need to be used for a diagnostic test that would identify those who exhibit altered or aberrant aging profiles that may be indicative of AD risk, so that they can be prioritized for primary prevention. This need for minimally invasive tests could be achieved by targeting saliva, since it is now well recognized that many aging diseases including AD are associated with peripheral biomarkers that are not only restricted to pathology and biomarkers within the brain.Results: Therefore, the aim of this review is to summarize some of the main findings of salivary biomarkers of aging and AD; including various proteins, metabolites, and alterations to DNA and miRNA. The future of healthy aging resides in innovative platforms, biosensors and point-of-care devices that can extract real time information on the health status of an individual. Those platforms may be achieved through the development and validation of novel biomarkers of health using saliva which, although being the least explored for biomedical purposes, has the distinct advantage that it can be self-collected in a non-invasive manner.

Laser scanning cytometry (LSC) provides a novel approach for automated scoring of micronuclei (MN) in different types of mammalian cells, serving as a biomarker of genotoxicity and mutagenicity. In this review, we discuss the advances to date in measuring MN in cell lines, buccal cells and erythrocytes, describe the advantages and outline potential challenges of this distinctive approach of analysis of nuclear anomalies. The use of multiple laser wavelengths in LSC and the high dynamic range of fluorescence and absorption detection allow simultaneous measurement of multiple cellular and nuclear features such as cytoplasmic area, nuclear area, DNA content and density of nuclei and MN, protein content and density of cytoplasm as well as other features using molecular probes. This high-content analysis approach allows the cells of interest to be identified (e.g. binucleated cells in cytokinesis-blocked cultures) and MN scored specifically in them. MN assays in cell lines (e.g. the CHO cell MN assay) using LSC are increasingly used in routine toxicology screening. More high-content MN assays and the expansion of MN analysis by LSC to other models (i.e. exfoliated cells, dermal cell models, etc.) hold great promise for robust and exciting developments in MN assay automation as a high-content high-throughput analysis procedure.

Previous studies have shown that mild cognitive impairment (MCI) may be reflective of the early stages of more pronounced neurodegenerative disorders such as Alzheimer's disease (AD). There is a need for a minimally invasive and inexpensive diagnostic to identify those who exhibit cellular pathology indicative of MCI and AD risk so that they can be prioritized for primary preventative measures. The hypothesis was that a minimally invasive approach using cytological markers in isolated buccal mucosa cells can be used to identify individuals of both MCI and AD. An automated buccal cell assay was developed using laser scanning cytometry (LSC) to measure buccal cell type ratios, nuclear DNA content and shape, and neutral lipid content of buccal cells from clinically diagnosed AD (n = 13) and MCI (n = 13) patients prior to treatment compared to age‐ and gender‐matched controls (n = 26). DNA content was significantly higher in all cell types in both MCI (P < 0.01) and AD (P < 0.05) compared with controls mainly due to an increase in >2N nuclei. Abnormal nuclear shape (circularity) was significantly increased in transitional cells in MCI (P < 0.001) and AD (P < 0.01) when compared to controls. In contrast, neutral lipid content (as measured by Oil red O “ORO” staining) of buccal cells was significantly lower in the MCI group (P < 0.05) compared with the control group. The ratio of DNA content/ORO in buccal basal cells for both MCI and AD was significantly higher compared to the control group, with ratios for MCI being approximately 2.8‐fold greater (P < 0.01) and AD approximately 2.3‐fold greater (P < 0.05) than the control group. Furthermore, there was a strong negative correlation between buccal cell DNA content and ORO content in the AD group (r² = 0.75, P < 0.0001) but not in MCI or controls. The changes in the buccal cell cytome observed in this study could prove useful as potential biomarkers in identifying individuals with an increased risk of developing MCI and eventually AD. © 2014 International Society for Advancement of Cytometry