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Autoantibody profiling to follow evolution of lupus syndromes

Overview of attention for article published in Arthritis Research & Therapy, July 2012
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Title
Autoantibody profiling to follow evolution of lupus syndromes
Published in
Arthritis Research & Therapy, July 2012
DOI 10.1186/ar3927
Pubmed ID
Authors

Nancy J Olsen, Quan-Zhen Li, Jiexia Quan, Ling Wang, Azza Mutwally, David R Karp

Abstract

ABSTRACT: INTRODUCTION: Identification of patients who are in early stages of lupus is currently done through clinical evaluation and is not greatly facilitated by available diagnostic tests. Profiling for patient characteristics and antibody specificities that predict disease would enhance the ability of physicians to identify and treat early cases prior to onset of organ damaging illness. METHODS: A group of 22 patients with 4 or fewer diagnostic criteria for lupus were studied for changes in clinical and autoantibody profiles after a mean follow up period of 2.4 years. An array with more than 80 autoantigens was used to profile immunoglobulin G (IgG) and immunoglobulin M (IgM) autoantibodies. Correlations with clinical disease progression were examined. RESULTS: 3 of the 22 patients (14%) added sufficient criteria during follow up to satisfy a diagnosis of systemic lupus erythematosus (SLE) or to acquire a diagnosis of SLE renal disease. Patients who progressed were all females and were younger than those who did not progress (P=0.00054). IgG but not IgM autoreactivity showed greater increases in the progressor group than in the non-progressor group (P=0.047). IgG specificities that were higher at baseline in progressors included proliferating cell nuclear antigen (PCNA), beta 2 microglobulin, C1q and hemocyanin (P<0.019). Progressors had significant increases in La/SSB and liver cytosol type 1 (LC1) IgG autoantibodies over the period of evaluation (P≤0.0072). A quantitative risk profile generated from baseline demographic and autoantibody variables yielded highly different scores for the progressor and non-progressor groups (P=1.38 × 10-7) CONCLUSIONS: In addition to demographic features, autoantibody profiles using an expanded array of specificities were correlated with the risk of progressive disease in patients with lupus. These findings suggest the feasibility of developing a simple diagnostic that could be applied by nonspecialists to screen for lupus and permit effective triage for specialty care.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Sweden 1 2%
Unknown 41 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 19%
Professor > Associate Professor 5 12%
Student > Ph. D. Student 5 12%
Researcher 4 9%
Student > Bachelor 3 7%
Other 11 26%
Unknown 7 16%
Readers by discipline Count As %
Medicine and Dentistry 22 51%
Agricultural and Biological Sciences 7 16%
Immunology and Microbiology 5 12%
Biochemistry, Genetics and Molecular Biology 2 5%
Business, Management and Accounting 1 2%
Other 1 2%
Unknown 5 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 04 August 2014.
All research outputs
#16,046,765
of 25,371,288 outputs
Outputs from Arthritis Research & Therapy
#2,337
of 3,381 outputs
Outputs of similar age
#109,189
of 179,047 outputs
Outputs of similar age from Arthritis Research & Therapy
#39
of 52 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
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 is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 179,047 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.