Using saliva epigenetic data to develop and validate a multivariable predictor of esophageal cancer status.

Background: Salivary epigenetic biomarkers may detect esophageal cancer. Methods: A total of 256 saliva samples from esophageal adenocarcinoma patients and matched volunteers were analyzed with Illumina EPIC methylation arrays. Three datasets were created, using 64% for discovery, 16% for testing and 20% for validation. Modules of gene-based methylation probes were created using weighted gene coexpression network analysis. Module significance to disease and gene importance to module were determined and a random forest classifier generated using best-scoring gene-related epigenetic probes. A cost-sensitive wrapper algorithm maximized cancer diagnosis. Results: Using age, sex and seven probes, esophageal adenocarcinoma was detected with area under the curve of 0.72 in discovery, 0.73 in testing and 0.75 in validation datasets. Cancer sensitivity was 88% with specificity of 31%. Conclusion: We have demonstrated a potentially clinically viable classifier of esophageal cancer based on saliva methylation.

Novel epigenetic network biomarkers for early detection of esophageal cancer.

BACKGROUND: Early detection of esophageal cancer is critical to improve survival. Whilst studies have identified biomarkers, their interpretation and validity is often confounded by cell-type heterogeneity. RESULTS: Here we applied systems-epigenomic and cell-type deconvolution algorithms to a discovery set encompassing RNA-Seq and DNA methylation data from esophageal adenocarcinoma (EAC) patients and matched normal-adjacent tissue, in order to identify robust biomarkers, free from the confounding effect posed by cell-type heterogeneity. We identify 12 gene-modules that are epigenetically deregulated in EAC, and are able to validate all 12 modules in 4 independent EAC cohorts. We demonstrate that the epigenetic deregulation is present in the epithelial compartment of EAC-tissue. Using single-cell RNA-Seq data we show that one of these modules, a proto-cadherin module centered around CTNND2, is inactivated in Barrett's Esophagus, a precursor lesion to EAC. By measuring DNA methylation in saliva from EAC cases and controls, we identify a chemokine module centered around CCL20, whose methylation patterns in saliva correlate with EAC status. CONCLUSIONS: Given our observations that a CCL20 chemokine network is overactivated in EAC tissue and saliva from EAC patients, and that in independent studies CCL20 has been found to be overactivated in EAC tissue infected with the bacterium F. nucleatum, a bacterium that normally inhabits the oral cavity, our results highlight the possibility of using DNAm measurements in saliva as a proxy for changes occurring in the esophageal epithelium. Both the CTNND2/CCL20 modules represent novel promising network biomarkers for EAC that merit further investigation.

Homocysteine, vitamin B12, and folic acid levels in Alzheimer's disease, mild cognitive impairment, and healthy elderly: baseline characteristics in subjects of the Australian Imaging Biomarker Lifestyle study.

There is some debate regarding the differing levels of plasma homocysteine, vitamin B12 and serum folate between healthy controls (HC), mild cognitive impairment (MCI), and Alzheimer's disease (AD). As part of the Australian Imaging Biomarker Lifestyle (AIBL) study of aging cohort, consisting of 1,112 participants (768 HC, 133 MCI patients, and 211 AD patients), plasma homocysteine, vitamin B12, and serum and red cell folate were measured at baseline to investigate their levels, their inter-associations, and their relationships with cognition. The results of this cross-sectional study showed that homocysteine levels were increased in female AD patients compared to female HC subjects (+16%, p-value < 0.001), but not in males. Red cell folate, but not serum folate, was decreased in AD patients compared to HC (-10%, p-value = 0.004). Composite z-scores of short- and long-term episodic memory, total episodic memory, and global cognition all showed significant negative correlations with homocysteine, in all clinical categories. Increasing red cell folate had a U-shaped association with homocysteine, so that high red cell folate levels were associated with worse long-term episodic memory, total episodic memory, and global cognition. These findings underscore the association of plasma homocysteine with cognitive deterioration, although not unique to AD, and identified an unexpected abnormality of red cell folate.

Plasma amyloid-beta as a biomarker in Alzheimer's disease: the AIBL study of aging.

Amyloid-beta (Abeta) plays a central role in the pathogenesis of Alzheimer's disease (AD) and has been postulated as a potential biomarker for AD. However, there is a lack of consensus as to its suitability as an AD biomarker. The objective of this study was to determine the significance of plasma Abeta as an AD biomarker and its relationship with Abeta load and to determine the effect of different assay methods on the interpretation of Abeta levels. Plasma Abeta1-40, Abeta1-42, and N-terminal cleaved fragments were measured using both a commercial multiplex assay and a well-documented ELISA in 1032 individuals drawn from the well-characterized Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging. Further, Abeta levels were compared to Abeta load derived from positron-emission tomography (PET) with the Pittsburgh compound B (PiB). Lower Abeta1-42 and Abeta1-42/1-40 ratio were observed in patients with AD and inversely correlated with PiB-PET derived Abeta load. However, assay methodology significantly impacted the interpretation of data. The cross-sectional analysis of plasma Abeta isoforms suggests that they may not be sufficient per se to diagnose AD. The value of their measurement in prognosis and monitoring of AD interventions needs further study, in addition to future longitudinal comparisons together with other predictors, which will determine whether plasma Abeta has diagnostic value in a panel of biomarkers.