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Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD

Overview of attention for article published in Human Genomics, November 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

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8 X users
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2 patents
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1 Facebook page

Citations

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29 Dimensions

Readers on

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68 Mendeley
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1 CiteULike
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Title
Transcriptome analysis reveals manifold mechanisms of cyst development in ADPKD
Published in
Human Genomics, November 2016
DOI 10.1186/s40246-016-0095-x
Pubmed ID
Authors

Rita M. C. de Almeida, Sherry G. Clendenon, William G. Richards, Michael Boedigheimer, Michael Damore, Sandro Rossetti, Peter C. Harris, Britney-Shea Herbert, Wei Min Xu, Angela Wandinger-Ness, Heather H. Ward, James A. Glazier, Robert L. Bacallao

Abstract

Autosomal dominant polycystic kidney disease (ADPKD) causes progressive loss of renal function in adults as a consequence of the accumulation of cysts. ADPKD is the most common genetic cause of end-stage renal disease. Mutations in polycystin-1 occur in 87% of cases of ADPKD and mutations in polycystin-2 are found in 12% of ADPKD patients. The complexity of ADPKD has hampered efforts to identify the mechanisms underlying its pathogenesis. No current FDA (Federal Drug Administration)-approved therapies ameliorate ADPKD progression. We used the de Almeida laboratory's sensitive new transcriptogram method for whole-genome gene expression data analysis to analyze microarray data from cell lines developed from cell isolates of normal kidney and of both non-cystic nephrons and cysts from the kidney of a patient with ADPKD. We compared results obtained using standard Ingenuity Volcano plot analysis, Gene Set Enrichment Analysis (GSEA) and transcriptogram analysis. Transcriptogram analysis confirmed the findings of Ingenuity, GSEA, and published analysis of ADPKD kidney data and also identified multiple new expression changes in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways related to cell growth, cell death, genetic information processing, nucleotide metabolism, signal transduction, immune response, response to stimulus, cellular processes, ion homeostasis and transport and cofactors, vitamins, amino acids, energy, carbohydrates, drugs, lipids, and glycans. Transcriptogram analysis also provides significance metrics which allow us to prioritize further study of these pathways. Transcriptogram analysis identifies novel pathways altered in ADPKD, providing new avenues to identify both ADPKD's mechanisms of pathogenesis and pharmaceutical targets to ameliorate the progression of the disease.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users 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 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 19%
Researcher 11 16%
Student > Bachelor 9 13%
Other 6 9%
Student > Doctoral Student 5 7%
Other 9 13%
Unknown 15 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 21%
Medicine and Dentistry 13 19%
Pharmacology, Toxicology and Pharmaceutical Science 5 7%
Engineering 5 7%
Agricultural and Biological Sciences 5 7%
Other 11 16%
Unknown 15 22%
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 12 July 2023.
All research outputs
#3,625,813
of 25,394,764 outputs
Outputs from Human Genomics
#93
of 564 outputs
Outputs of similar age
#66,372
of 415,364 outputs
Outputs of similar age from Human Genomics
#2
of 5 outputs
Altmetric has tracked 25,394,764 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 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 83% 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 415,364 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 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.