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Record W2556512023 · doi:10.1161/circresaha.116.309637

GlycA Is a Novel Biomarker of Inflammation and Subclinical Cardiovascular Disease in Psoriasis

2016· article· en· W2556512023 on OpenAlexaff
Aditya A. Joshi, Joseph B Lerman, Tsion Aberra, Mehdi Afshar, Heather Teague, Justin Rodante, Parasuram Krishnamoorthy, Qimin Ng, Taufiq Salahuddin, Balaji Natarajan, Benjamin Lockshin, Mark A. Ahlman, Marcus Y. Chen, Daniel J. Rader, Muredach P. Reilly, Alan T. Remaley, David A. Bluemke, Martin P. Playford, Joel M. Gelfand, Nehal N. Mehta

Bibliographic record

VenueCirculation Research · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsMcGill University
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institutes of Health
KeywordsPsoriasisMedicineCoronary artery diseaseInternal medicineCardiologySubclinical infectionBiomarkerDiseasePopulationFluorodeoxyglucosePositron emission tomographyGastroenterologyRadiologyImmunology

Abstract

fetched live from OpenAlex

RATIONALE: GlycA, an emerging inflammatory biomarker, predicted cardiovascular events in population-based studies. Psoriasis, an inflammatory disease associated with increased cardiovascular risk, provides a model to study inflammatory biomarkers in cardiovascular disease (CVD). Whether GlycA associates with psoriasis and how it predicts subclinical CVD beyond high-sensitivity C-reactive protein in psoriasis is unknown. OBJECTIVE: To investigate the relationships between GlycA and psoriasis and between GlycA and subclinical CVD. METHODS AND RESULTS: Patients with psoriasis and controls (n=412) participated in a 2-stage study. We measured GlycA by nuclear magnetic resonance spectroscopy. National Institutes of Health (NIH) participants underwent 18-F Fluorodeoxyglucose Positron Emission Tomography Computed Tomography (18-FDG PET/CT) scans to assess vascular inflammation (VI) and coronary computed tomographic angiography to quantify coronary artery disease burden. Psoriasis cohorts were young (mean age=47.9), with low cardiovascular risk and moderate skin disease. high-sensitivity C-reactive protein and GlycA were increased in psoriasis compared with controls (GlycA: [PENN: 408.8±75.4 versus 289.4±60.2, P<0.0001; NIH: 415.8±63.2 versus 346.2±46, P<0.0001]) and demonstrated a dose-response with psoriasis severity. In stage 2, VI (β=0.36, P<0.001) and coronary artery disease (β=0.29, P=0.004) associated with GlycA beyond CV risk factors in psoriasis. In receiver operating characteristic analysis, GlycA added value in predicting VI (P=0.01) and coronary artery disease (P<0.01). Finally, initiating anti-tumor necrosis factor therapy (n=16) reduced psoriasis severity (P<0.001), GlycA (463.7±92.5 versus 370.1±78.5, P<0.001) and VI (1.93±0.36 versus 1.76±0.19, P<0.001), whereas GlycA remained associated with VI (β=0.56, P<0.001) post treatment. CONCLUSIONS: GlycA associated with psoriasis severity and subclinical CVD beyond traditional CV risk and high-sensitivity C-reactive protein. Moreover, psoriasis treatment reduced GlycA and VI. These findings support the potential use of GlycA in subclinical CVD risk assessment in psoriasis and potentially other inflammatory diseases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.102
GPT teacher head0.341
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations127
Published2016
Admission routes1
Has abstractyes

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