02491nas a2200373   4500008004100000022001400041245014600055210006900201260001600270300000800286490000600294520125600300653001101556653003801567653003401605653001301639653002501652653001101677653000901688100002701697700001701724700002701741700002001768700002301788700002401811700002001835700002001855700002801875700002001903700002501923700002001948700001901968856013001987       2012                        eng d  a1750-117200aFour new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung's disease.0 aFour new loci associations discovered by pathwaybased and networ  c2012 Dec 28  a1030 v73 a<p>Finding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a pathway-based analysis (PBA) has been initially conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung's disease. Candidate genes have been further validated in an independent population of 106 trios. The study revealed a strong association of 11 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes. Among the preselected candidates, a total of 4 loci, RASGEF1A, IQGAP2, DLC1 and CHRNA7, related to signal transduction and migration processes, were found to be significantly associated to HSCR. Network analysis also confirms their involvement in the network of already known disease genes. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.</p>10aFemale10aGenetic Predisposition to Disease10aGenome-Wide Association Study10aGenotype10aHirschsprung Disease10aHumans10aMale1 aFernández, Raquel, Ma1 aBleda, Marta1 aNúñez-Torres, Rocío1 aMedina, Ignacio1 aLuzón-Toro, Berta1 aGarcía-Alonso, Luz1 aTorroglosa, Ana1 aMarbà, Martina1 aEnguix-Riego, Ma, Valle1 aMontaner, David1 aAntiňolo, Guillermo1 aDopazo, Joaquin1 aBorrego, Salud  uhttps://www.clinbioinfosspa.es/content/four-new-loci-associations-discovered-pathway-based-and-network-analyses-genome-wide-002193nas a2200289   4500008004100000022001400041245014800055210006900203260001600272300000800288490000600296520126100302100002701563700001701590700002701607700002001634700002301654700002401677700002001701700002001721700002801741700002001769700002501789700002101814700001901835856004901854       2012                        eng d  a1750-117200aFour new loci associations discovered by pathway-based and network analyses of the genome-wide variability profile of Hirschsprung’s disease.0 aFour new loci associations discovered by pathwaybased and networ  c2012 Dec 28  a1030 v73 aABSTRACT: Finding gene associations in rare diseases is frequently hampered by the reduced numbers of patients accessible. Conventional gene-based association tests rely on the availability of large cohorts, which constitutes a serious limitation for its application in this scenario. To overcome this problem we have used here a combined strategy in which a pathway-based analysis (PBA) has been initially conducted to prioritize candidate genes in a Spanish cohort of 53 trios of short-segment Hirschsprung’s disease. Candidate genes have been further validated in an independent population of 106 trios. The study revealed a strong association of 11 gene ontology (GO) modules related to signal transduction and its regulation, enteric nervous system (ENS) formation and other HSCR-related processes. Among the preselected candidates, a total of 4 loci, RASGEF1A, IQGAP2, DLC1 and CHRNA7, related to signal transduction and migration processes, were found to be significantly associated to HSCR. Network analysis also confirms their involvement in the network of already known disease genes. This approach, based on the study of functionally-related gene sets, requires of lower sample sizes and opens new opportunities for the study of rare diseases.1 aFernández, Raquel, Ma1 aBleda, Marta1 aNúñez-Torres, Rocío1 aMedina, Ignacio1 aLuzón-Toro, Berta1 aGarcía-Alonso, Luz1 aTorroglosa, Ana1 aMarbà, Martina1 aEnguix-Riego, Ma, Valle1 aMontaner, David1 aAntiňolo, Guillermo1 aDopazo, Joaquín1 aBorrego, Salud  uhttp://www.ojrd.com/content/7/1/103/abstract