MétaCan
Menu
Back to cohort

S1100 Associations Between Body Mass Index and Serological Responses to SARS-CoV-2 Vaccination in Patients With Inflammatory Bowel Disease

2023· article· en· W4387733212 on OpenAlexaff
Kenneth Ernest-Suárez, Fiona Yeaman, Joshua Quan, Catherine Rowan, Christopher Ma, Remo Panaccione, Lindsay Hracs, Nastaran Sharifi, Michelle Herauf, Ante Markovinović, Stephanie Coward, Joseph W. Windsor, Léa Caplan, R Ingram, Cynthia H. Seow, Kerri L. Novak, Cathy Lu, Gilaad G. Kaplan

Bibliographic record

VenueThe American Journal of Gastroenterology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiabetes and associated disorders
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineBody mass indexVaccinationSerologyObesityOverweightInflammatory bowel diseaseInternal medicineCohortImmunologyAntibodyGastroenterologyDisease

Abstract

fetched live from OpenAlex

Introduction: Vaccines have been shown effective regardless of Body Mass Index (BMI), obesity may impact antibody levels compared to healthy weight subjects. The durability of vaccine response in people with obesity has not been definitively studied in those IBD. This study aims to determine the association between elevated BMI and serological responses (SR) to SARS-CoV-2 vaccination in individuals with IBD. Methods: SARS-CoV-2 vaccinated (≥ 2 doses) adults with IBD were recruited from the STOP COVID-19 IBD cohort. Patient height and weight recorded at recruitment were used to calculate BMI. Individuals were stratified into “obese” (BMI ≥30) and “normal to overweight” (BMI 18.5-30) groups according to the CDC Obesity classification. IgG antibodies to the spike protein of SARS-CoV-2 (anti-S) were assessed using the Abbott Architect SARS-CoV-2 IgG II Quant assay at 1–8 weeks after 1st dose vaccination, and 1–8 weeks and 8+ weeks after 2nd, 3rd, and 4th dose vaccination. Sex, age, IBD type, and medication status at 1st dose of vaccine were collected via chart review and compared between BMI groups using Chi-square tests for frequencies or Mann-Whitney U test for means. Positive SR (≥50 AU/mL) rates were compared between BMI groups using two-sample proportion tests. Anti-S concentrations, reported as geometric mean titres (GMT), were compared using Mann Whitney-U tests. For timepoints with significant GMT differences, multivariable linear regression was used to model the association between obesity and anti-S concentration, adjusted for age, sex, IBD type, medication class, and prior COVID-19 infection. Results: 105 individuals have with obesity and 362 non-obese were recruited. SR rates were similar between groups across all vaccine doses. Anti-S titres were significantly increased for individuals with BMI ≥30 following 1–8 weeks post-3rd dose vaccination (18721 vs. 11304 AU/mL). However, no significant GMT differences were observed for other timepoints (Table 1, Figure 1). This association between obesity and increased anti-S held after adjusting for confounders within a regression model (Geometric mean ratio: 1.61; 95% CI: 1.16, 2.22; P=0.004). Conclusion: Antibody levels in obese IBD patients were similar to non-obese with the exception of a higher initial response following 3rd vaccine dose. Future studies are necessary to explore clinical, pharmacodynamic, or immunological factors explaining a higher SR in obese individuals with IBD, and whether this confers greater protection. Table 1. - Overall patient characteristics, seroconversion, and GMT with associated 95% CIs stratified by BMI and vaccination timepoint and associated univariate analyses Characteristic Time point BMI ≥ 30 (n = 105) BMI 18.5-30 (n = 362) P-value Male sex, n (%) Overall 36 (34.3%) 187 (51.7%) 0.002 Mean age (SD) 51.2 (12.7) 48.7 (14.8) 0.117 Medication class, n (%) No immunosuppressives 11 (10.5%) 40 (11.0%) – Anti-TNF only 33 (31.4%) 128 (35.4%) 0.869 Immunomodulator only 2 (1.9%) 9 (2.5%) 0.802 Vedolizumab only 18 (17.1%) 34 (9.4%) 0.141 Ustekinumab only 20 (19.1%) 80 (22.1%) 0.821 Tofacitinib only 5 (4.8%) 1 (0.3%) 0.001 Combination therapy† 14 (13.3%) 62 (17.1%) 0.662 Corticosteroids‡ 2 (1.9%) 8 (2.2%) 0.912 IBD type, n (%) Crohn’s disease 76 (72.4%) 257 (71.0%) 0.632 Ulcerative colitis 28 (26.7%) 96 (26.5%) IBD-Unclassified 1 (0.9%) 9 (2.5%) Seroconversion, n/N (%) Post-1st 43/50 (86.0%) 147/182 (80.8%) 0.395 Post-2nd (1–8 weeks) 66/66 (100.0%) 233/237 (98.3%) 0.288 Post-2nd (8+ weeks) 52/55 (94.6%) 173/181 (95.6%) 0.750 Post-3rd (1–8 weeks) 59/59 (100.0%) 174/175 (99.4%) 0.561 Post-3rd (8+ weeks) 67/67 (100.0%) 237/239 (99.2%) 0.453 Post-4th (1–8 weeks) 21/21 (100.0%) 62/63 (98.4%) 0.561 Post-4th (8+ weeks) 20/20 (100.0%) 57/59 (96.6%) 0.404 Post-4th (Overall) 29/29 (100.0%) 82/84 (97.6%) 0.402 GMT (95% CI) Post-1st 243 (153, 387) 269 (208, 348) 0.851 Post-2nd (1–8 weeks) 5198 (3805, 7103) 3775 (3124, 4563) 0.151 Post-2nd (8+ weeks) 1223 (804, 1861) 1088 (842, 1405) 0.633 Post-3rd (1–8 weeks) 18721 (14065, 24918) 11304 (9456, 13512) 0.003 Post-3rd (8+ weeks) 5436 (3632, 8136) 4070 (3314, 4999) 0.119 Post-4th (1–8 weeks) 21202 (12236, 36739) 13626 (9982, 18600) 0.147 Post-4th (8+ weeks) 7496 (3799, 14790) 4558 (2971, 6993) 0.269 Post-4th (Overall) 15375 (9234, 25598) 9808 (7105, 13540) 0.184 *Indicates reference group.†Combination therapy refers to any combination of two or more of the following therapies: anti-TNF, immunomodulators, vedolizumab, ustekinumab, and tofacitinib.‡Oral prednisone at any dose or with any other drug class. Figure 1.: Anti-SARS-CoV-2 antibody concentration per vaccine category stratified by BMI between 18.5 and 30 (circles) and ≥30 (triangles). Black circles represent GMTs while narrow black bars represent bounds of 95% CI associated with each GMT. Solid blue line represents threshold for positive seroconversion (50 AU/mL).

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.246
Teacher spread0.240 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe American Journal of GastroenterologySame topicDiabetes and associated disordersFrench-language works237,207