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Polycystic ovarian syndrome is accompanied by repression of gene signatures associated with biosynthesis and metabolism of steroids, cholesterol and lipids

Overview of attention for article published in Journal of Ovarian Research, April 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#49 of 651)
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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1 news outlet
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1 X user

Citations

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47 Dimensions

Readers on

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69 Mendeley
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Title
Polycystic ovarian syndrome is accompanied by repression of gene signatures associated with biosynthesis and metabolism of steroids, cholesterol and lipids
Published in
Journal of Ovarian Research, April 2015
DOI 10.1186/s13048-015-0151-5
Pubmed ID
Authors

Dessie Salilew-Wondim, Qi Wang, Dawit Tesfaye, Karl Schellander, Michael Hoelker, Md Munir Hossain, Benjamin K Tsang

Abstract

Polycystic ovarian syndrome (PCOS) is a spectrum of heterogeneous disorders of reproduction and metabolism in women with potential systemic sequel such as diabetes and obesity. Although, PCOS is believed to be caused by genetic abnormalities, the genetic background that can be associated with PCOS phenotypes remains unclear due to the complexity of the trait. In this study, we used a rat model which exhibits reproductive and metabolic abnormalities similar to the human PCOS to unravel the molecular mechanisms underlining this complex syndrome. Female Sprague-Dawley rats were randomly assigned to DHT and control (CTL) groups. Rats in the DHT group were implanted with a silicone capsule continuous-releasing 83 μg 5α-dihydrotestosterone (DHT) per day for 12 weeks to mimic the hyperandrogenic state in women with PCOS. The animals were euthanized at 15 weeks of age and the pairs of ovaries were excised and the ovarian cortex tissues were used for gene expression analysis. Total RNA was from the ovarian cortex was amplified, labeled and hybridized to the Affymetrix GeneChip® Rat Genome 230 2.0 Array. A linear model system for microarray data analysis was used to identify genes affected in DHT treated rat ovaries and the molecular pathway of those genes were analyzed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis tool. A total of 573 gene transcripts, including CPA1, CDH1, INSL3, AMH, ALDH1B1, INHBA, CYP17A1, RBP4, GAS6, GAS7 and GATA4, were activated while 430 others including HSD17B7, HSD3B6, STAR, HMGCS1, HMGCR, CYP51, CYP11A1 and CYP19A1 were repressed in DHT-treated ovaries. Functional annotation of the dysregulated genes revealed that biosynthesis and metabolism of steroids, cholesterol and lipids to be the most top functions enriched by the repressed genes. However, cell differentiation/proliferation, transcriptional regulation, neurogenesis, cell adhesion and blood vessel development processes were enriched by activated genes. The dysregulation of genes associated with biosynthesis and metabolism of steroids, cholesterol and lipids, cell differentiation/proliferation in DHT- treated ovaries could be a molecular clue for abnormal steroidogenesis, estrous cycle irregularity, abnormal folliculogenesis, anovulation and lipid metabolism in PCOS patients.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 16%
Student > Master 10 14%
Student > Bachelor 9 13%
Researcher 7 10%
Professor > Associate Professor 3 4%
Other 8 12%
Unknown 21 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 22%
Medicine and Dentistry 13 19%
Agricultural and Biological Sciences 9 13%
Immunology and Microbiology 3 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Other 6 9%
Unknown 22 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 April 2015.
All research outputs
#3,466,617
of 23,940,793 outputs
Outputs from Journal of Ovarian Research
#49
of 651 outputs
Outputs of similar age
#44,600
of 267,651 outputs
Outputs of similar age from Journal of Ovarian Research
#2
of 11 outputs
Altmetric has tracked 23,940,793 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 651 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 267,651 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.