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A discrete cluster of urinary biomarkers discriminates between active systemic lupus erythematosus patients with and without glomerulonephritis

Overview of attention for article published in Arthritis Research & Therapy, October 2016
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  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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1 X user
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1 patent
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2 Facebook pages

Citations

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Title
A discrete cluster of urinary biomarkers discriminates between active systemic lupus erythematosus patients with and without glomerulonephritis
Published in
Arthritis Research & Therapy, October 2016
DOI 10.1186/s13075-016-1120-0
Pubmed ID
Authors

Carolina Landolt-Marticorena, Stephenie D. Prokopec, Stacey Morrison, Babak Noamani, Dennisse Bonilla, Heather Reich, James Scholey, Carmen Avila-Casado, Paul R. Fortin, Paul C. Boutros, Joan Wither

Abstract

Management of lupus nephritis (LN) would be greatly aided by the discovery of biomarkers that accurately reflect changes in disease activity. Here, we used a proteomics approach to identify potential urinary biomarkers associated with LN. Urine was obtained from 60 LN patients with paired renal biopsies, 25 active non-LN SLE patients, and 24 healthy controls. Using Luminex, 128 analytes were quantified and normalized to urinary creatinine levels. Data were analyzed by linear modeling and non-parametric statistics, with corrections for multiple comparisons. A second cohort of 33 active LN, 16 active non-LN, and 30 remission LN SLE patients was used to validate the results. Forty-four analytes were identified that were significantly increased in active LN as compared to active non-LN. This included a number of unique proteins (e.g., TIMP-1, PAI-1, PF4, vWF, and IL-15) as well as known candidate LN biomarkers (e.g., adiponectin, sVCAM-1, and IL-6), that differed markedly (>4-fold) between active LN and non-LN, all of which were confirmed in the validation cohort and normalized in remission LN patients. These proteins demonstrated an enhanced ability to discriminate between active LN and non-LN patients over several previously reported biomarkers. Ten proteins were found to significantly correlate with the activity score on renal biopsy, eight of which strongly discriminated between active proliferative and non-proliferative/chronic renal lesions. A number of promising urinary biomarkers that correlate with the presence of active renal disease and/or renal biopsy changes were identified and appear to outperform many of the existing proposed biomarkers.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 57 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 17%
Student > Doctoral Student 6 10%
Other 5 9%
Student > Ph. D. Student 5 9%
Student > Bachelor 4 7%
Other 10 17%
Unknown 18 31%
Readers by discipline Count As %
Medicine and Dentistry 27 47%
Agricultural and Biological Sciences 3 5%
Immunology and Microbiology 2 3%
Biochemistry, Genetics and Molecular Biology 2 3%
Environmental Science 1 2%
Other 2 3%
Unknown 21 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 21 March 2018.
All research outputs
#7,355,930
of 25,373,627 outputs
Outputs from Arthritis Research & Therapy
#1,510
of 3,381 outputs
Outputs of similar age
#104,389
of 327,571 outputs
Outputs of similar age from Arthritis Research & Therapy
#23
of 58 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 3,381 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has gotten more attention than average, scoring higher than 53% 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 327,571 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.