@article {1179, title = {Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas.}, journal = {BMC medical genomics}, volume = {8}, year = {2015}, month = {2015}, pages = {83}, abstract = {BACKGROUND: The molecular mechanisms leading to sporadic medullary thyroid carcinoma (sMTC) and juvenile papillary thyroid carcinoma (PTC), two rare tumours of the thyroid gland, remain poorly understood. Genetic studies on thyroid carcinomas have been conducted, although just a few loci have been systematically associated. Given the difficulties to obtain single-loci associations, this work expands its scope to the study of epistatic interactions that could help to understand the genetic architecture of complex diseases and explain new heritable components of genetic risk. METHODS: We carried out the first screening for epistasis by Multifactor-Dimensionality Reduction (MDR) in genome-wide association study (GWAS) on sMTC and juvenile PTC, to identify the potential simultaneous involvement of pairs of variants in the disease. RESULTS: We have identified two significant epistatic gene interactions in sMTC (CHFR-AC016582.2 and C8orf37-RNU1-55P) and three in juvenile PTC (RP11-648k4.2-DIO1, RP11-648k4.2-DMGDH and RP11-648k4.2-LOXL1). Interestingly, each interacting gene pair included a non-coding RNA, providing thus support to the relevance that these elements are increasingly gaining to explain carcinoma development and progression. CONCLUSIONS: Overall, this study contributes to the understanding of the genetic basis of thyroid carcinoma susceptibility in two different case scenarios such as sMTC and juvenile PTC.}, keywords = {epistasis, GWAS, Thyroid cancer}, issn = {1755-8794}, doi = {10.1186/s12920-015-0160-7}, url = {http://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-015-0160-7}, author = {Luz{\'o}n-Toro, Berta and Bleda, Marta and Navarro, Elena and Garc{\'\i}a-Alonso, Luz and Ruiz-Ferrer, Macarena and Medina, Ignacio and Mart{\'\i}n-S{\'a}nchez, Marta and Gonzalez, Cristina Y and Fern{\'a}ndez, Raquel M and Torroglosa, Ana and Anti{\v n}olo, Guillermo and Dopazo, Joaquin and Borrego, Salud} } @article {20478823, title = {Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling.}, journal = {Nucleic Acids Research}, volume = {38}, year = {2010}, month = {2010 May 16}, pages = {W210-W213. Featured in NAR}, chapter = {Featured in NAR}, abstract = {

Babelomics is a response to the growing necessity of integrating and analyzing different types of genomic data in an environment that allows an easy functional interpretation of the results. Babelomics includes a complete suite of methods for the analysis of gene expression data that include normalization (covering most commercial platforms), pre-processing, differential gene expression (case-controls, multiclass, survival or continuous values), predictors, clustering; large-scale genotyping assays (case controls and TDTs, and allows population stratification analysis and correction). All these genomic data analysis facilities are integrated and connected to multiple options for the functional interpretation of the experiments. Different methods of functional enrichment or gene set enrichment can be used to understand the functional basis of the experiment analyzed. Many sources of biological information, which include functional (GO, KEGG, Biocarta, Reactome, etc.), regulatory (Transfac, Jaspar, ORegAnno, miRNAs, etc.), text-mining or protein-protein interaction modules can be used for this purpose. Finally a tool for the de novo functional annotation of sequences has been included in the system. This provides support for the functional analysis of non-model species. Mirrors of Babelomics or command line execution of their individual components are now possible. Babelomics is available at http://www.babelomics.org.

}, keywords = {babelomics, gene expression, genotyping, gepas, GSA, GWAS}, url = {http://nar.oxfordjournals.org/content/38/suppl_2/W210.full}, author = {Medina, Ignacio and Carbonell, Jos{\'e} and Pulido, Luis and Madeira, Sara C and Goetz, Stefan and Ana Conesa and T{\'a}rraga, Joaqu{\'\i}n and Pascual-Montano, Alberto and Nogales-Cadenas, Ruben and Santoyo, Javier and Garc{\'\i}a, Francisco and Marb{\`a}, Martina and Montaner, David and Joaqu{\'\i}n Dopazo} } @article {19094230, title = {Biological processes, properties and molecular wiring diagrams of candidate low-penetrance breast cancer susceptibility genes}, journal = {BMC Med Genomics}, volume = {1}, year = {2008}, note = {

Bonifaci, Nuria Berenguer, Antoni Diez, Javier Reina, Oscar Medina, Ignacio Dopazo, Joaquin Moreno, Victor Pujana, Miguel Angel England BMC medical genomics BMC Med Genomics. 2008 Dec 18;1:62.

}, pages = {62}, abstract = {

ABSTRACT: BACKGROUND: Recent advances in whole-genome association studies (WGASs) for human cancer risk are beginning to provide the part lists of low-penetrance susceptibility genes. However, statistical analysis in these studies is complicated by the vast number of genetic variants examined and the weak effects observed, as a result of which constraints must be incorporated into the study design and analytical approach. In this scenario, biological attributes beyond the adjusted statistics generally receive little attention and, more importantly, the fundamental biological characteristics of low-penetrance susceptibility genes have yet to be determined. METHODS: We applied an integrative approach for identifying candidate low-penetrance breast cancer susceptibility genes, their characteristics and molecular networks through the analysis of diverse sources of biological evidence. RESULTS: First, examination of the distribution of Gene Ontology terms in ordered WGAS results identified asymmetrical distribution of Cell Communication and Cell Death processes linked to risk. Second, analysis of 11 different types of molecular or functional relationships in genomic and proteomic data sets defined the \"omic\" properties of candidate genes: i/ differential expression in tumors relative to normal tissue; ii/ somatic genomic copy number changes correlating with gene expression levels; iii/ differentially expressed across age at diagnosis; and iv/ expression changes after BRCA1 perturbation. Finally, network modeling of the effects of variants on germline gene expression showed higher connectivity than expected by chance between novel candidates and with known susceptibility genes, which supports functional relationships and provides mechanistic hypotheses of risk. CONCLUSION: This study proposes that cell communication and cell death are major biological processes perturbed in risk of breast cancer conferred by low-penetrance variants, and defines the common omic properties, molecular interactions and possible functional effects of candidate genes and proteins.

}, keywords = {gene set, GWAS, SNP}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=19094230}, author = {Bonifaci, N. and Berenguer, A. and Diez, J. and Reina, O. and Medina, Ignacio and Dopazo, J. and Moreno, V. and Pujana, M. A.} }