title: Framework for the Integration of Genomics, Epigenomics and Transcriptomics in Complex Diseases.
abstract: OBJECTIVE
  Different types of '-omics' data are becoming available in the post-genome era; still a single -omics assessment provides limited insights to understand the biological mechanism of complex diseases. Genomics, epigenomics and transcriptomics data provide insight into the molecular dysregulation of neoplastic diseases, among them urothelial bladder cancer (UBC). Here, we propose a detailed analytical framework necessary to achieve an adequate integration of the three sets of -omics data to ultimately identify previously hidden genetic mechanisms in UBC.
  
  
  METHODS
  We built a multi-staged framework to study possible pair-wise combinations and integrated the data in three-way relationships. SNP genotypes, CpG methylation levels and gene expression levels were determined for a total of 70 individuals with UBC and with fresh tumour tissue available.
  
  
  RESULTS
  We suggest two main hypothesis-based scenarios for gene regulation based on the -omics integration analysis, where DNA methylation affects gene expression and genetic variants co-regulate gene expression and DNA methylation. We identified several three-way trans-association 'hotspots' that are found at the molecular level and that deserve further studies.
  
  
  CONCLUSIONS
  The proposed integrative framework allowed us to identify relationships at the whole-genome level providing some new biological insights and highlighting the importance of integrating -omics data.
authors.affiliation: Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
authors.forename: Silvia
authors.initials: S
authors.lastname: Pineda
authors.forename: Paulina
authors.initials: P
authors.lastname: Gomez-Rubio
authors.forename: Antonio
authors.initials: A
authors.lastname: Picornell
authors.forename: Kyrylo
authors.initials: K
authors.lastname: Bessonov
authors.forename: Mirari
authors.initials: M
authors.lastname: Márquez
authors.forename: Manolis
authors.initials: M
authors.lastname: Kogevinas
authors.forename: Francisco X
authors.initials: FX
authors.lastname: Real
authors.forename: Kristel
authors.initials: K
authors.lastname: Van Steen
authors.forename: Nuria
authors.initials: N
authors.lastname: Malats
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D018899:CpG Islands / Q000235:genetics; D019175:DNA Methylation / Q000235:genetics; D004194:Disease / Q000235:genetics*; D057890:Epigenomics; D005260:Female; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D005787:Gene Frequency / Q000235:genetics; D055106:Genome-Wide Association Study; D060005:Genotyping Techniques; D006801:Humans; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D040641:Quantitative Trait Loci / Q000235:genetics; D013223:Statistics as Topic