title: Transcriptomic and proteomic analysis in the cardiovascular setting: unravelling the disease?
abstract: Whole gene expression analysis through microarray technologies revolutionized the manner of identifying changes in biological events and complex diseases, such as cardiovascular settings. These new methodologies may scan up to 35 000 transcripts at once rather than screening a small amount of genes one at a time. The ability of microarrays to provide a broad insight into the disease process directly within the tissues provides a unique insight into the intracellular perturbations of the cell organization and function and sheds an entirely unique new perspective on the heart failure process. Commonalities and differences at the molecular level will identify critical pathways of pathogenesis, and response to therapy, or both: indeed, gene expression profiling holds tremendous promise for classifying clinical phenotypes, developing prognostic predictors and, most importantly, providing novel unbiased insights into the mechanisms underlying heart disease and, eventually, novel causative genes. On the contrary, established proteomic technologies, together with the new alternative strategies currently under evaluation (i.e. metabolomics), are now making possible the translation of data obtained on the bench to the daily clinical routine with the discovery of new diagnostic/prognostic biomarkers (such as troponin for ACS and BNP for congestive heart failure) and the identification of new therapeutic approaches for combating heart diseases. Finally, genomic studies (including transcriptomics) together with proteomics should not represent a challenge for who is going to win the final battle, but rather they should provide a setting in which together and in a complementary fashion the final fight against heart disease can be won.
authors.affiliation: Centre for Inherited Cardiovascular Diseases, Foundation IRCCS Policlinico San Matteo, Italy.
authors.forename: Nicola
authors.initials: N
authors.lastname: Marziliano
authors.forename: Maurizia
authors.initials: M
authors.lastname: Grasso
authors.forename: Andrea
authors.initials: A
authors.lastname: Pilotto
authors.forename: Emanuele
authors.initials: E
authors.lastname: Porcu
authors.forename: Marilena
authors.initials: M
authors.lastname: Tagliani
authors.forename: Eliana
authors.initials: E
authors.lastname: Disabella
authors.forename: Marta
authors.initials: M
authors.lastname: Diegoli
authors.forename: Michele
authors.initials: M
authors.lastname: Pasotti
authors.forename: Valentina
authors.initials: V
authors.lastname: Favalli
authors.forename: Alessandra
authors.initials: A
authors.lastname: Serio
authors.forename: Fabiana
authors.initials: F
authors.lastname: Gambarin
authors.forename: Luigi
authors.initials: L
authors.lastname: Tavazzi
authors.forename: Catherine
authors.initials: C
authors.lastname: Klersy
authors.forename: Eloisa
authors.initials: E
authors.lastname: Arbustini
mesh_terms: D015415:Biomarkers / Q000378:metabolism; D002318:Cardiovascular Diseases / Q000235:genetics* / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D010641:Phenotype; D040081:Protein Array Analysis; D040901:Proteomics / Q000379:methods
chemical_list: D015415:Biomarkers; D005819:Genetic Markers