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Abstract Background A molecular characterization of Alzheimer's Disease (AD) is the key to the identification of altered gene sets that lead to AD progression. We rely on the assumption that candidate marker genes for a given disease belong to specific pathogenic pathways, and we aim at unveiling those pathways stable across tissues, treatments and measurement systems. In this context, we analyzed three heterogeneous datasets, two microarray gene expression sets and one protein abundance set, applying a recently proposed feature selection method based on regularization. Results For each dataset we identified a signature that was successively evaluated both from the computational and functional characterization viewpoints, estimating the classification error and retrieving the most relevant biological knowledge from different repositories. Each signature includes genes already known to be related to AD and genes that are likely to be involved in the pathogenesis or in the disease progression. The integrated analysis revealed a meaningful overlap at the functional level. Conclusions The identification of three gene signatures showing a relevant overlap of pathways and ontologies, increases the likelihood of finding potential marker genes for AD.

Genome-wide association studies (GWAS) have revealed a plethora of putative susceptibility genes for Alzheimer's disease (AD), with the sole exception of APOE gene unequivocally validated in independent study. Considering that the etiology of complex diseases like AD could depend on functional multiple genes interaction network, here we proposed an alternative GWAS analysis strategy based on (i) multivariate methods and on a (ii) telescope approach, in order to guarantee the identification of correlated variables, and reveal their connections at three biological connected levels. Specifically as multivariate methods, we employed two machine learning algorithms and a genetic association test and we considered SNPs, Genes and Pathways features in the analysis of two public GWAS dataset (ADNI-1 and ADNI-2). For each dataset and for each feature we addressed two binary classifications tasks: cases vs. controls and the low vs. high risk of developing AD considering the allelic status of APOEe4. This complex strategy allowed the identification of SNPs, genes and pathways lists statistically robust and meaningful from the biological viewpoint. Among the results, we confirm the involvement of TOMM40 gene in AD and we propose GRM7 as a novel gene significantly associated with AD.

Some years ago, we reported the generation of a Fanconi anemia (FA) microRNA signature. This study aims to develop an analytical strategy to select a smaller and more reliable set of molecules that could be tested for potential benefits for the FA phenotype, elucidate its biochemical and molecular mechanisms, address experimental activity, and evaluate its possible impact on FA therapy. In silico analyses of the data obtained in the original study were thoroughly processed and anenrichment analysis was employed to identify the classes of genes that are over-represented in the FA-miRNA population under study. Primary bone marrow mononuclear cells (MNCs) from sixFA patients and sixhealthy donors as control samples were employed in the study. RNAs containing the small RNA fractions were reverse-transcribed and real-time PCR was performed in triplicate using the specific primers. Experiments were performed in triplicate.The in-silico analysis reported six miRNAs as likely contributors to the complex pathological spectrum of FA. Among these, three miRNAs were validated by real-time PCR. Primary bone marrow mononuclear cells (MNCs) reported a significant reduction in the expression level of miRNA-1246 and miRNA-206 in the FA samples in comparison to controls.This study highlights several biochemical pathways as culprits in the phenotypic manifestations and the pathophysiological mechanisms acting in FA. A relatively low number of miRNAs appear involved in all these different phenotypes, demonstrating the extreme plasticity of the gene expression modulation. This study further highlights miR-206 as a pivotal player in regulatory functions and signaling in the bone marrow mesenchymal stem cell (BMSC) process in FA. Due to this evidence, the activity of miR-206 in FA deserves specific experimental scrutiny. The results, here presented, might be relevant in the management of FA. [ABSTRACT FROM AUTHOR]

Motivation: The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for the discovery of biomarkers using microarray data often provide results with limited overlap. These differences are imputable to 1) dataset size (few subjects with respect to the number of features); 2) heterogeneity of the disease; 3) heterogeneity of experimental protocols and computational pipelines employed in the analysis. In this paper, we focus on the first two issues and assess, both on simulated (through an in silico regulation network model) and real clinical datasets, the consistency of candidate biomarkers provided by a number of different methods. Methods: We extensively simulated the effect of heterogeneity characteristic of complex diseases on different sets of microarray data. Heterogeneity was reproduced by simulating both intrinsic variability of the population and the alteration of regulatory mechanisms. Population variability was simulated by modeling evolution of a pool of subjects; then, a subset of them underwent alterations in regulatory mechanisms so as to mimic the disease state. Results: The simulated data allowed us to outline advantages and drawbacks of different methods across multiple studies and varying number of samples and to evaluate precision of feature selection on a benchmark with known biomarkers. Although comparable classification accuracy was reached by different methods, the use of external cross-validation loops is helpful in finding features with a higher degree of precision and stability. Application to real data confirmed these results. [ABSTRACT FROM AUTHOR]

Gut microbiota plays a role in human health and autoimmunity. Among environmental factor linked to type 1 diabetes (T1DM) pathogenesis, gut microbiota impairment seems to be involved. We evaluated gut microbial fingerprinting in 31 pediatric patients with new-onset T1DM and 25 healthy children using multiple polymorphic region of the 16S rRNA. We performed machine learning and metagenome functional analyses to identify significant taxa and metabolic pathways and correlate with clinical and metabolic parameters. Inclusion criteria were living in Northern Italy, born from Caucasian parents, singleton birth, personal history negative for acute/chronic gastrointestinal diseases and/or antibiotic or probiotics administration. Different Bacteroidetes species i.e., B.stercoris (q=1,473E-4), B.intestinalis (q=0.010), B.fragilis (q=0.0452) were significantly more frequent in patients as well as B.bifidum, Gammaproteobacteria, Holdemania, Synergistetes and their descendants. Abundance of the Synergistetes (q=0.001), Synergistia (q=4.798E-5), Synergistales (q=2.64E-4) and Synergistaceae (q=0.0017) was reported. Among Deltaproteobacteria descendants, the Desulfovibrionales (q=0.0016), Desulfovibrionaceae (q=0.016) and the Bilophila genus (q=0.036) were significantly lower in patients as well as B.vulgatus, Deltaproteobacteria, Parasutterella and Lactobacillus, Turicibacter genera. BMI-SDS, insulin autoantibodies, glycemia, HbA1c, Tanner and age were the most significant positively or negatively parameters related to specific clusters of taxa. The supervised analyses confirmed the importance of B. stercoris in T1DM patients and a relevant role of Synergistetes and its descendants. The robustness and coherence of our results underline the relevance of studying microbioma using multiple polymorphic regions, different types of analysis and approaches within each analysis. Disclosure: G. d'Annunzio: Consultant; Self; Sandoz. R. Biassoni: None. M. Squillario: None. E. Ugolotti: None. A. Barla: None. G. Piccolo: None. N. Minuto: None. M. Maghnie: None. [ABSTRACT FROM AUTHOR]

Background/aim: The aim of the present study was to evaluate the safety and the clinical outcome of platelet-rich plasma for the treatment of teno-desmic injures in competition horses., Patients and Methods: From January 2009 to December 2011, 150 sport horses suffering from teno-desmic injuries were treated with no-gelled platelet-concentrate., Results: No horse showed any major adverse reaction as a result of the procedure. Full healing was obtained for 81% of the horses. Twelve percent had clinical improvement and only 7% a failure. Eight percent of cases of relapse were observed. No statistically significant correlation existed between clinical outcome and the area of the lesion. A statistically significant correlation existed between the clinical outcome and the age of the horse., Conclusion: Treatment with platelet-derived growth factors leads to the formation of a tendon with normal morphology and functionality, which translate in the resumption of the agonistic activity for the horses we treated., (Copyright © 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.)