Support vector machines (SVM) are a powerful tool to analyze data with a number of predictors approximately equal or larger than the number of observations. However, originally, application of SVM to analyze biomedical data was limited because SVM was not designed to evaluate importance of predictor variables. Creating predictor models based on only the most relevant variables is essential in biomedical research. Currently, substantial work has been done to allow assessment of variable importance in SVM models but this work has focused on SVM implemented with linear kernels. The power of SVM as a prediction model is associated with the flexibility generated by use of non-linear kernels. Moreover, SVM has been extended to model survival outcomes. This paper extends the Recursive Feature Elimination (RFE) algorithm by proposing three approaches to rank variables based on non-linear SVM and SVM for survival analysis. The proposed algorithms allows visualization of each one the RFE iterations, and hence, identification of the most relevant predictors of the response variable. Using simulation studies based on time-to-event outcomes and three real datasets, we evaluate the three methods, based on pseudo-samples and kernel principal component analysis, and compare them with the original SVM-RFE algorithm for non-linear kernels. The three algorithms we proposed performed generally better than the gold standard RFE for non-linear kernels, when comparing the truly most relevant variables with the variable ranks produced by each algorithm in simulation studies. Generally, the RFE-pseudo-samples outperformed the other three methods, even when variables were assumed to be correlated in all tested scenarios. The proposed approaches can be implemented with accuracy to select variables and assess direction and strength of associations in analysis of biomedical data using SVM for categorical or time-to-event responses. Conducting variable selection and interpreting direction and strength of associations between predictors and outcomes with the proposed approaches, particularly with the RFE-pseudo-samples approach can be implemented with accuracy when analyzing biomedical data. These approaches, perform better than the classical RFE of Guyon for realistic scenarios about the structure of biomedical data.

Several recent findings suggest that targeting the endogenous cannabinoid system can be considered as a potential therapeutic approach to treat Alzheimer's disease (AD). The present study supports this hypothesis demonstrating that delta-9-tetrahydro

The MaPLE study was a randomized, controlled, crossover trial involving adults ≥60 y.o. (n = 51) living in a residential care facility during an 8-week polyphenol-rich (PR)-diet. Results from the MaPLE trial showed that the PR-diet reduced the intestinal permeability (IP) in older adults by inducing changes to gut microbiota (GM). The present work aimed at studying the changes in serum metabolome in the MaPLE trial, as a further necessary step to depict the complex crosstalk between dietary polyphenols, GM, and intestinal barrier. Serum metabolome was monitored using a semi-targeted UHPLC-MS/MS analysis. Metataxonomic analysis (16S rRNA gene profiling) of GM was performed on faecal samples. Clinical characteristics and serum levels of the IP marker zonulin were linked to GM and metabolomics data in a multi-omics network. Compared to the control diet, the PR-diet increased serum metabolites related to polyphenols and methylxanthine intake. Theobromine and methylxanthines, derived from cocoa and/or green tea, were positively correlated with butyrate-producing bacteria (the order Clostridiales and the genera Roseburia, Butyricicoccus and Faecalibacterium) and inversely with zonulin. A direct correlation between polyphenol metabolites hydroxyphenylpropionic acid-sulfate, 2-methylpyrogallol-sulfate and catechol-sulfate with Butyricicoccus was also observed, while hydroxyphenylpropionic acid-sulfate and 2-methylpyrogallol-sulfate negatively correlated with Methanobrevibacter. The multi-omics network indicated that participant's age, baseline zonulin levels, and changes in Porphyromonadaceae abundance were the main factors driving the effects of a PR-diet on zonulin. Overall, these results reveal the complex relationships among polyphenols consumption, intestinal permeability, and GM composition in older adults, and they may be important when setting personalized dietary interventions for older adults. ISRCTN10214981.

Myxovirus A (MxA), a protein encoded by the MX1 gene with antiviral activity, has proven to be a sensitive measure of IFNβ bioactivity in multiple sclerosis (MS). However, the use of MxA as a biomarker of IFNβ bioactivity has been criticized for the lack of evidence of its role on disease pathogenesis and the clinical response to IFNβ. Here, we aimed to identify specific biomarkers of IFNβ bioactivity in order to compare their gene expression induction by type I IFNs with the MxA, and to investigate their potential role in MS pathogenesis. Gene expression microarrays were performed in PBMC from MS patients who developed neutralizing antibodies (NAB) to IFNβ at 12 and/or 24 months of treatment and patients who remained NAB negative. Nine genes followed patterns in gene expression over time similar to the MX1, which was considered the gold standard gene, and were selected for further experiments: IFI6, IFI27, IFI44L, IFIT1, HERC5, LY6E, RSAD2, SIGLEC1, and USP18. In vitro experiments in PBMC from healthy controls revealed specific induction of selected biomarkers by IFNβ but not IFNγ, and several markers, in particular USP18 and HERC5, were shown to be significantly induced at lower IFNβ concentrations and more selective than the MX1 as biomarkers of IFNβ bioactivity. In addition, USP18 expression was deficient in MS patients compared with healthy controls (p = 0.0004). We propose specific biomarkers that may be considered in addition to the MxA to evaluate IFNβ bioactivity, and to further explore their implication in MS pathogenesis.

Neuroprotection of erythropoietin (EPO) following long-term administration is hampered by the associated undesirable effects on hematopoiesis and body weight. For this reason, we tested carbamylated-EPO (CEPO), which has no effect on erythropoiesis, and compared it with EPO in the AβPP/PS1 mouse model of familial Alzheimer's disease. Groups of 5-month-old wild type (WT) and transgenic mice received chronic treatment consisting of CEPO (2,500 or 5,000 UI/kg) or EPO (2,500 UI/kg) 3 days/week for 4 weeks. Memory at the end of treatment was assessed with the object recognition test. Microarray analysis and quantitative-PCR were used for gene expression studies. No alterations in erythropoiesis were observed in CEPO-treated WT and AβPP/PS1 transgenic mice. EPO and CEPO improved memory in AβPP/PS1 animals. However, only EPO decreased amyloid-β (Aβ) plaque burden and soluble Aβ40. Microarray analysis of gene expression revealed a limited number of common genes modulated by EPO and CEPO. CEPO but not EPO significantly increased gene expression of dopamine receptors 1 and 2, and adenosine receptor 2a, and significantly down-regulated adrenergic receptor α1D and gastrin releasing peptide. CEPO treatment resulted in higher protein levels of dopamine receptors 1 and 2 in WT and AβPP/PS1 animals, whereas the adenosine receptor 2a was reduced in WT animals. The present results suggest that the improved behavior observed in AβPP/PS1 transgenic mice after CEPO treatment may be mediated, at least in part, by the observed modulation of the expression of molecules involved in neurotransmission

Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task.