Dataset Information

Gene expression profile in pelvic organ prolapse

ABSTRACT: Introduction and Hypothesis: Identify processes contributing to pelvic organ prolapse (POP) by transcriptional profiling of pelvic connective tissue in conjunction with light microscopy. Methods: We performed a frequency matched case-control study of women undergoing hysterectomy. Total RNA, extracted from uterosacral and round ligament samples used to generate labeled cRNA, was hybridized to microarrays and analyzed for the expression of 32,878 genes. Significance Analysis of Microarrays, (Stanford University, CA), identified differentially expressed genes used for ontoanalysis, and quantitative PCR (qPCR) confirmed results. Light microscopy confirmed tissue type and assessed inflammatory infiltration. Results: The analysis of thirty-four arrays revealed 249 differentially expressed genes with fold changes larger than 1.5 fold and false discovery rates ≤5.2%. Immunity and Defense was the most significant biological process differentially expressed in POP. Selected qPCR confirmed 4 genes. Light microscopy showed no inflammatory infiltrates. Conclusions: Genes enriched for Immunity and Defense contribute to POP independent of inflammatory infiltrates. Keywords: whole tissue (endopelvic fascia) type comparison

ORGANISM(S): Homo sapiens

PROVIDER: GSE12852 | GEO | 2008/09/20

SECONDARY ACCESSION(S): PRJNA111083

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:The overall purpose of this University of Utah Pelvic Organ Prolapse Disorder Study was to identify and localize predisposition genes contributing to pelvic organ prolapse (POP). POP cases recruited for this study were identified by one of three methods: high-risk POP pedigree cases, POP sister pairs, and surgically-treated POP cases reporting a family history of POP. High-risk POP pedigree cases were identified using the Utah Population Database (UPDB), a genealogy database of residents in Utah that has been linked to diagnostic ICD9 and CPT codes in medical records at the University of Utah and Intermountain Healthcare. We identified families with a significant excess number of POP cases compared to matched population rates and targeted these individuals for recruitment as well as any other POP cases in the family. POP sister pair cases were identified at the University of Utah Urogyncology clinic for women who had undergone POP surgery and also self-reported one or more sisters who were also surgically treated for POP. POP affection status of all sisters was confirmed either by physical examination or by chart review. Surgically treated-POP cases reporting a family history of POP were identified at the University of Utah Urogyncology clinic by self-report of a family history of POP. Efforts were made to recruit other affected family members and confirm affection status. To obtain DNA, subjects provided either a blood specimen or saliva. Medical records were reviewed by a urogynecologist and diagnostic information for pelvic organ prolapse and stress and overactive bladder were obtained. Collected DNA was genotyped and analyzed. To maintain confidentiality of the familial data, genetic data from only one subject per family has been submitted to dbGaP. Use of the University of Utah Pelvic Organ Prolapse Disorder Study data is limited to investigators studying pelvic floor disorders. These pelvic floor disorders include pelvic organ prolapse, urinary and anal incontinence, and other conditions related to weakening or injury to the muscles and connective tissue in the pelvis as a result of pelvic surgery, pregnancy, or vaginal delivery of a child. These data will be used only for research purposes related to pelvic floor disorders. They will not be used to determine the individual identity of any person or their relationship to another person or for research on non-disease traits.

Dataset Information

Gene expression profile in pelvic organ prolapse

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets