Study of Alzheimer's disease- and frontotemporal dementia-associated genes in the Cretan Aging Cohort.

Using exome sequencing, we analyzed 196 participants of the Cretan Aging Cohort (CAC; 95 with Alzheimer's disease [AD], 20 with mild cognitive impairment [MCI], and 81 cognitively normal controls). The APOE ε4 allele was more common in AD patients (23.2%) than in controls (7.4%; p < 0.01) and the PSEN2 p.Arg29His and p.Cys391Arg variants were found in 3 AD and 1 MCI patient, respectively. Also, we found the frontotemporal dementia (FTD)-associated TARDBP gene p.Ile383Val variant in 2 elderly patients diagnosed with AD and in 2 patients, non CAC members, with the amyotrophic lateral sclerosis/FTD phenotype. Furthermore, the p.Ser498Ala variant in the positively selected GLUD2 gene was less frequent in AD patients (2.11%) than in controls (16%; p < 0.01), suggesting a possible protective effect. While the same trend was found in another local replication cohort (n = 406) and in section of the ADNI cohort (n = 808), this finding did not reach statistical significance and therefore it should be considered preliminary. Our results attest to the value of genetic testing to study aged adults with AD phenotype.

Postprandial Responses of Serum Cholesterol, Glucose and Plasma Antioxidant Activity, after Intake of an Innovative High Fat Mayonnaise-Based Appetizer, Enhanced with Olive Paste, in Healthy Volunteers.

Several Mediterranean functional foods and their process by-products may exert a beneficial role on hyperlipidemia, hyperglycemia, and oxidative stress modulation, providing bioactive compounds with functional properties, contributing to possible chronic disease prevention (cardiovascular disease, metabolic syndrome, obesity, diabetes mellitus, etc.). The purpose of the present interventional study was to investigate the postprandial responses of metabolic biomarkers, after the intake of an innovative mayonnaise-based appetizer, enhanced with olive paste, in healthy volunteers. In this cross-over design, randomized and single-blind, interventional−clinical trial, 10 healthy volunteers, aged 20−30 years old, after splitting into the control group and the Mediterranean group, consumed a pasta meal rich in fat and carbohydrates (150 g), containing a mayonnaise-based appetizer or the same appetizer, enhanced with 9% olive paste. After a 1-week washout period, the subjects consumed the meals in reverse. Differences between groups on postprandial responses of total plasma antioxidant capacity according to the FRAP method, serum total cholesterol, glucose, and uric acid levels, were determined before, 30 min, 1.5 h, and 3 h after consumption. The results showed that, in comparison to the control group, consumption of the enhanced appetizer resulted in a significantly decreased total serum cholesterol and glucose levels, and also led to a significant increase in plasma total antioxidant activity, 3 h after consumption (p < 0.05). Further investigation with large prospective studies is needed to validate the current results.

Postprandial Bioactivity of a Spread Cheese Enriched with Mountain Tea and Orange Peel Extract in Plasma Oxidative Stress Status, Serum Lipids and Glucose Levels: An Interventional Study in Healthy Adults.

Postprandial lipemia, glycemia and oxidative stress may affect the occurrence of cardiovascular disease. The purpose of the present intervention study was to investigate the effect of a spread cheese enriched with mountain tea (Sideritis sp.) and orange peel (Citrus sinensis) extract on postprandial metabolic biomarkers in healthy volunteers. In a cross-over design, 14 healthy subjects 20-30 years old were consumed either a meal rich in fat and carbohydrates (80 g white bread, 40 g butter and 30 g full fat spread cheese) or a meal with the spread cheese enriched with 6% mountain tea-orange peel extract. Differences in postprandial total plasma antioxidant capacity, resistance of plasma to oxidation, serum lipids, glucose and uric acid levels were evaluated at 0, 1.5 and 3 h after consumption. Plasma total antioxidant capacity was significantly increased 3 h after the consumption of the meal in the presence of the extract-enriched cheese, compared to the conventional cheese (p = 0.05). Plasma resistance to oxidation was increased at 30 min in the Functional meal compared with the Control meal. A tendency to decrease the postprandial rise in glucose and triglyceride levels, 1.5 h and 3 h, respectively, after the intake of the meal with the extract-enriched cheese was observed (p = 0.062). No significant changes in the concentrations of the remaining biomarkers studied were observed (p > 0.05). Further studies with a larger sample are needed in both healthy adults and patients with cardiovascular disease to draw safer conclusions about the postprandial effect of the extracts on metabolic biomarkers that predict cardiovascular risk.

A network-based approach to enrich gene signatures for the prediction of breast cancer metastases.

Despite the multiplicity of the gene expression analysis studies for the identification of genomics based origins of cancerous diseases, the presented gene signatures have generally little overlap. The genes do not function in isolation and therefore a more holistic approach that takes into account the interactions among them is needed. In this study we present a stepwise refinement methodology where starting from some initial set of biomarkers we expand and enrich this set taking into account existing biological information. In particular, we start with a 27 gene signature previously identified as indicative of the presence of circulating tumor cells (CTCs) in peripheral blood of breast cancer patients. We use the manually curated HINT database of protein-protein interactions as the background biological network to locate the network-based similarity of the input genes and how they connect to each other. The result is an enriched connected set of genes that is subsequently expanded to form an even bigger network based on the ability of the surrounding genes to strongly correlate with the phenotypes of a training set of breast cancer patient cases. The induced network is then used as a new gene signature for the classification of breast brain metastases in an independent dataset. The results are encouraging for the validity of this method.

On the identification of circulating tumor cells in breast cancer.

Breast cancer is a highly heterogeneous disease and very common among western women. The main cause of death is not the primary tumor but its metastases at distant sites, such as lymph nodes and other organs (preferentially lung, liver, and bones). The study of circulating tumor cells (CTCs) in peripheral blood resulting from tumor cell invasion and intravascular filtration highlights their crucial role concerning tumor aggressiveness and metastasis. Genomic research regarding CTCs monitoring for breast cancer is limited due to the lack of indicative genes for their detection and isolation. Instead of direct CTC detection, in our study, we focus on the identification of factors in peripheral blood that can indirectly reveal the presence of such cells. Using selected publicly available breast cancer and peripheral blood microarray datasets, we follow a two-step elimination procedure for the identification of several discriminant factors. Our procedure facilitates the identification of major genes involved in breast cancer pathology, which are also indicative of CTCs presence.

Integration of gene signatures using biological knowledge.

OBJECTIVE: Gene expression patterns that distinguish clinically significant disease subclasses may not only play a prominent role in diagnosis, but also lead to the therapeutic strategies tailoring the treatment to the particular biology of each disease. Nevertheless, gene expression signatures derived through statistical feature-extraction procedures on population datasets have received rightful criticism, since they share few genes in common, even when derived from the same dataset. We focus on knowledge complementarities conveyed by two or more gene-expression signatures by means of embedded biological processes and pathways, which alternatively form a meta-knowledge platform of analysis towards a more global, robust and powerful solution. METHODS: The main contribution of this work is the introduction and study of an approach for integrating different gene signatures based on the underlying biological knowledge, in an attempt to derive a unified global solution. It is further recognized that one group's signature does not perform well on another group's data, due to incompatibilities of microarray technologies and the experimental design. We assess this cross-platform aspect, showing that a unified solution derived on the basis of both statistical and biological validation may also help in overcoming such inconsistencies. RESULTS: Based on the proposed approach we derived a unified 69-gene signature, which outperforms significantly the performance of the initial signatures succeeding a 0.73 accuracy metric on 234 new patients with 81% sensitivity and 64% specificity. The same signature manages to reveal the two prognostic groups on an additional dataset of 286 new patients obtained through a different experimental protocol and microarray platform. Furthermore, it manages to derive two clusters in a dataset from a different platform, showing remarkable difference on both gene-expression and survival-prediction levels.