Evidence map›Paper›PMID 27067270›Full record

ArticleArthritis research & therapy2016

A novel inflammatory biomarker, GlycA, associates with disease activity in rheumatoid arthritis and cardio-metabolic risk in BMI-matched controls.

David B Bartlett, Margery A Connelly, Hiba AbouAssi, Lori A Bateman, K Noelle Tune, Janet L Huebner, Virginia B Kraus, Deborah A Winegar, James D Otvos, William E Kraus and 1 more

Abstract read
In one paragraph

Article in Arthritis research & therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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  17. Title: Human Serum/Plasma Glycoprotein Analysis byJournal of clinical medicine · 2020
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

David B BartlettDepartment of Medicine and Duke Molecular Physiology Institute, Duke School of Medicine, Durham, NC, USA.
Margery A ConnellyLipoScience, Laboratory Corporation of America® Holdings, Raleigh, NC, USA.
Hiba AbouAssiDepartment of Medicine and Duke Molecular Physiology Institute, Duke School of Medicine, Durham, NC, USA.
Lori A BatemanCenter for Health Promotion and Disease Prevention, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
K Noelle TuneCenter for Health Promotion and Disease Prevention, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Janet L HuebnerDepartment of Medicine and Duke Molecular Physiology Institute, Duke School of Medicine, Durham, NC, USA.
Virginia B KrausDepartment of Medicine and Duke Molecular Physiology Institute, Duke School of Medicine, Durham, NC, USA.
Deborah A WinegarLipoScience, Laboratory Corporation of America® Holdings, Raleigh, NC, USA.
James D OtvosLipoScience, Laboratory Corporation of America® Holdings, Raleigh, NC, USA.
William E KrausDepartment of Medicine and Duke Molecular Physiology Institute, Duke School of Medicine, Durham, NC, USA.
Kim M HuffmanDepartment of Medicine and Duke Molecular Physiology Institute, Duke School of Medicine, Durham, NC, USA. Huffm007@mc.duke.edu.

Funding

Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI Virginia B Kraus · 2006 to 2026
$24.6M
Mechanisms of Insulin Resistance in Rheumatoid ArthritisK23AR054904 · NIAMS · DUKE UNIVERSITY · PI HUFFMAN, KIM M. · 2008 to 2012
$354k
NIAMS NIH HHS K23 AR054904NIAMS NIH HHS K23AR054904NIA NIH HHS P30 AG028716NIA NIH HHS P30AG028716
6 · The paper itself

Abstract

backgroundRA and CVD both have inflammation as part of the underlying biology. Our objective was to explore the relationships of GlycA, a measure of glycosylated acute phase proteins, with inflammation and cardiometabolic risk in RA, and explore whether these relationships were similar to those for persons without RA.

methodsPlasma GlycA was determined for 50 individuals with mild-moderate RA disease activity and 39 controls matched for age, gender, and body mass index (BMI). Regression analyses were performed to assess relationships between GlycA and important markers of traditional inflammation and cardio-metabolic health: inflammatory cytokines, disease activity, measures of adiposity and insulin resistance.

resultsOn average, RA activity was low (DAS-28 = 3.0 ± 1.4). Traditional inflammatory markers, ESR, hsCRP, IL-1β, IL-6, IL-18 and TNF-α were greater in RA versus controls (P < 0.05 for all). GlycA concentrations were significantly elevated in RA versus controls (P = 0.036). In RA, greater GlycA associated with disease activity (DAS-28; RDAS-28 = 0.5) and inflammation (RESR = 0.7, RhsCRP = 0.7, RIL-6 = 0.3: P < 0.05 for all); in BMI-matched controls, these inflammatory associations were absent or weaker (hsCRP), but GlycA was related to IL-18 (RhsCRP = 0.3, RIL-18 = 0.4: P < 0.05). In RA, greater GlycA associated with more total abdominal adiposity and less muscle density (Rabdominal-adiposity = 0.3, Rmuscle-density = -0.3, P < 0.05 for both). In BMI-matched controls, GlycA associated with more cardio-metabolic markers: BMI, waist circumference, adiposity measures and insulin resistance (R = 0.3-0.6, P < 0.05 for all).

conclusionsGlycA provides an integrated measure of inflammation with contributions from traditional inflammatory markers and cardio-metabolic sources, dominated by inflammatory markers in persons with RA and cardio-metabolic factors in those without.

Indexed as

Acute-Phase ProteinsAdiposityAdultAgedArthritis, RheumatoidBiomarkersBody Mass IndexCardiovascular DiseasesCross-Sectional StudiesFemaleGlycosylationHumansInflammationInsulin ResistanceMagnetic Resonance SpectroscopyMaleAcute-Phase ProteinsBiomarkersBiomarkerGlycosylationInflammationMetabolic syndromeRheumatoid arthritis

Identifiers

PMID27067270
PMCPMC4828830

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.