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EXPOSURE TO PER- AND POLYFLUOROALKYL SUBSTANCES (PFAS) AND SYSTEMIC LUPUS ERYTHEMATOSUS: A PILOT STUDY IN THE MICHIGAN LUPUS EPIDEMIOLOGY & SURVEILLANCE (MILES) PROGRAM

2025· article· en· W4410513081 on OpenAlexvenueno aff
Jaclyn M. Goodrich, Faith M. Strickland, Kexin Li, Lu Wang, Sioḃán D. Harlow, Sung Kyun Park, Katherine E. Manz, Wendy Marder, W. Joseph McCune, Afton L. Hassett, Suzanna M. Zick, Emily C. Somers

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Disorders and Syndromes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEpidemiologySystemic lupus erythematosusSystemic lupusLupus erythematosusEnvironmental healthImmunologyInternal medicineDiseaseAntibody

Abstract

fetched live from OpenAlex

PV077 / #669 Poster Topic: AS10 - Environment and SLE Background/Purpose Per- and polyfluoroalkyl substances (PFAS), often called “forever chemicals,” are a large class of chemicals found in consumer products and as contaminants in food and drinking water. PFAS are known to be immunotoxic. Evidence supports a link between PFAS and some autoimmune conditions, but their relationship with systemic lupus erythematosus (SLE) risk and disease severity has not been well characterized. This pilot study in women with SLE explored the relationship between serum PFAS levels and disease activity. We hypothesized that higher PFAS levels would be linked to increased disease activity in Black and White women. Methods In serum specimens from 70 female participants with SLE (self-reported race: Black n=35, White n=35) in the Michigan Lupus Epidemiology and Surveillance (MILES) Cohort, we quantified 48 PFAS analytes using isotope dilution and solid-phase extraction followed by liquid chromatography-mass-spectrometry. Disease activity was measured by the Systemic Lupus Activity Questionnaire (SLAQ), a validated patient-reported outcome measure. For PFAS analytes that were detected in ≥40% of participants, we first modeled the relationship between each PFAS concentration and SLAQ score, adjusting for age, race, and BMI. Combining Least Absolute Shrinkage and Selection Operator (LASSO) and expertise knowledge, we selected the most important PFAS features for a multivariable regression, adjusted for covariates, to model PFAS mixtures in all women and stratified by race. Results Among the 48 PFAS measured, 28 were detected in at least 1 serum specimen, and 16 were “commonly detected” in ≥40% of samples. Five PFAS had significantly higher rates of detection (%) or median levels in Black compared to White women. Adjusting for other confounders, 2 of the 16 commonly detected PFAS exhibited statistically significant associations with SLAQ score (p-value <0.05). Perfluorodecanoic acid (PFDA) was positively associated [1.69 unit increase SLAQ per 1-unit increase in standardized PFDA (95% CI 0, 3.37)], and perfluorohexanesulfonic acid (PFHxS) was inversely associated [-1.62 (95% CI -3.23, -0.01)] with SLAQ. We applied LASSO to identify the most important PFAS features relevant to SLAQ and prevent overfitting. Five PFAS, selected by LASSO, were modeled simultaneously with SLAQ. PFDA and perfluoro-n-hexadecanoic acid (PFHxDA) had consistent positive associations in all women and when stratified by race, whereas no significant inverse associations were detected in the mixture analysis (Figure). Figure. Conclusions This pilot study is the first to examine relationships between environmental exposures to immunotoxic PFAS and SLE activity. We observed associations between higher serum concentrations of 2 PFAS – PFDA and PFHxDA – with increased disease activity, measured by SLAQ score. Data suggest that immunotoxicity of PFAS may extend to SLE, a prototypic autoimmune disease.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.226
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.027
GPT teacher head0.311
Teacher spread0.284 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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