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Phenotype-Genotype Association Analysis of ACTH-Secreting Pituitary Adenoma and Its Molecular Link to Patient Osteoporosis.
- Source :
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International journal of molecular sciences [Int J Mol Sci] 2016 Sep 29; Vol. 17 (10). Date of Electronic Publication: 2016 Sep 29. - Publication Year :
- 2016
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Abstract
- Adrenocorticotrophin (ACTH)-secreting pituitary adenoma, also known as Cushing disease (CD), is rare and causes metabolic syndrome, cardiovascular disease and osteoporosis due to hypercortisolism. However, the molecular pathogenesis of CD is still unclear because of a lack of human cell lines and animal models. Here, we study 106 clinical characteristics and gene expression changes from 118 patients, the largest cohort of CD in a single-center. RNA deep sequencing is used to examine genotypic changes in nine paired female ACTH-secreting pituitary adenomas and adjacent nontumorous pituitary tissues (ANPT). We develop a novel analysis linking disease clinical characteristics and whole transcriptomic changes, using Pearson Correlation Coefficient to discover a molecular network mechanism. We report that osteoporosis is distinguished from the phenotype and genotype analysis. A cluster of genes involved in osteoporosis is identified using Pearson correlation coefficient analysis. Most of the genes are reported in the bone related literature, confirming the feasibility of phenotype-genotype association analysis, which could be used in the analysis of almost all diseases. Secreted phosphoprotein 1 ( SPP1 ), collagen type I α 1 chain ( COL1A1 ), 5'-nucleotidase ecto ( NT5E ), HtrA serine peptidase 1 ( HTRA1 ) and angiopoietin 1 ( ANGPT1 ) and their signalling pathways are shown to be involved in osteoporosis in CD patients. Our discoveries provide a molecular link for osteoporosis in CD patients, and may open new potential avenues for osteoporosis intervention and treatment.<br />Competing Interests: The authors declare no conflict of interest.
Details
- Language :
- English
- ISSN :
- 1422-0067
- Volume :
- 17
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- International journal of molecular sciences
- Publication Type :
- Academic Journal
- Accession number :
- 27690016
- Full Text :
- https://doi.org/10.3390/ijms17101654