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Record W2102274887 · doi:10.1186/1559-0275-12-1

Quantitative tandem mass-spectrometry of skin tissue reveals putative psoriatic arthritis biomarkers

2015· article· en· W2102274887 on OpenAlexafffund
Daniela Creţu, Kun Liang, Punit Saraon, Ihor Batruch, Eleftherios P. Diamandis, Vinod Chandran

Bibliographic record

VenueClinical Proteomics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsToronto Western HospitalUniversity Health NetworkUniversity of WaterlooUniversity of TorontoMount Sinai Hospital
FundersCanadian Institutes of Health ResearchAbbVie CanadaKrembil FoundationUniversity of Toronto
KeywordsPsoriatic arthritisProteomicsMass spectrometryPsoriasisTandem mass spectrometryComputational biologyMedicineChemistryChromatographyDermatologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Psoriatic arthritis (PsA) is a distinct inflammatory arthritis occurring in 30% of psoriasis patients. There is a high prevalence of undiagnosed PsA in psoriasis patients; therefore, identifying soluble biomarkers for PsA could help in screening psoriasis patients for appropriate referral to a rheumatologist. Potential PsA biomarkers likely originate in sites of inflammation, such as the skin, and subsequently enter systemic circulation. Our goal was to identify candidate PsA biomarkers by comparing the proteome of skin biopsies obtained from patients with PsA to that from patients with psoriasis without PsA. METHODS: Skin biopsies were obtained from involved and uninvolved skin of 10 PsA and 10 age/gender-matched psoriasis patients without PsA (PsC). Using strong cation exchange chromatography, followed by label-free quantitative tandem mass spectrometry, we characterized the proteomes of pooled skin samples. Extracted ion current intensities were used to calculate protein abundance ratios, and these were utilized to identify differentially regulated proteins. RESULTS: Forty-seven proteins were elevated in PsA-derived skin compared to PsC-derived skin. Selected reaction monitoring assays were developed to quantify these potential PsA markers in individual skin samples, and 8 markers were confirmed in an independent sample set. ITGB5 and POSTN were measured in serum samples from 33 PsA and 15 PsC patients, using enzyme-linked immunosorbent assays. ITGB5 was significantly elevated in PsA serum (P < 0.01), and POSTN showed a trend. ITGB5 and POSTN correlated significantly in both patient groups (r = 0.472, P < 0.001). CONCLUSION: Proteomic analysis of PsA and PsC skin identified eight new candidate biomarkers. These markers need to be validated with a larger and independent cohort, in order to delineate their clinical utility in PsA patients. These proteins may also uncover unknown aspects of PsA pathobiology.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.365
Teacher spread0.312 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations87
Published2015
Admission routes2
Has abstractyes

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