ABSTRACT
Background: Published data suggest no increased rate of fare of autoimmune infammatory rheumatic diseases (AIIRD) after COVID-19 mRNA vaccination;however, the studies are limited by small sample size, short follow up or at risk of selection bias (voluntary physician reports or patient surveys). Objectives: To study fares of AIIRD within three months of the frst dose of an anti-SARS-COV2 mRNA vaccine. Methods: A retrospective cohort study of consecutive AIIRD patients ≥ 12 years old, across six public hospitals in Singapore who received at least one dose of an mRNA (Pfzer/BioNTech or Moderna) vaccine. Data were censored at the frst post-vaccine clinic visit when the patient had fared or if ≥ three months had elapsed since the frst dose of the vaccine, whichever came frst. Predictors of fare were determined by Cox proportional hazards analysis and time to fare was examined using a Nelson Aalen cumulative hazard estimate (Figure 1). Results: 2339 patients (74% Chinese, 72% female) of median (IQR) age 64 (53, 71) years were included in the interim analysis (Table 1). 2112 (90%) had the Pfzer/BioNTech vaccine and 195 (8%) had Moderna, with a median (IQR) interval of 21 (21, 23) days between the two doses. The most common AIIRD diagnoses were Rheumatoid arthritis (1063, 45%), Psoriatic arthritis (296, 12.6%) and Systemic lupus erythematosus (SLE) (288, 12.3%). 186 (8%) were treated with biologics/targeted disease modifying agents. 2125 (91%) patients were in low disease activity or remission. Treatment was interrupted for vaccination in only 18 (0.8%) patients. Seven (0.3%) patients had previous COVID-19 infection. 452 (19%) fares were recorded during 9798.8 patient-months [4.6/100 patient-months, median (IQR) follow up duration 4.2 (3.3, 5.3) months], of which 272 (11.6%) patients fared within the 3-month period of interest and 180 (7.7%) fared outside of the 3-month period (Table 1). Median (IQR) time-to-fare was 40.5 (18, 56.6) days. 60 (22.1%) were mild and self-limiting, 170 (62.5%) were mild-moderate and 42 (15.4%) were severe. 190 (69.8%) of those who fared required escalation of treatment and 15 (5.5%) required hospital admission. 239 (10.2%) had improved disease activity after the vaccine. On multivariate Cox regression analysis, patients in the oldest age tertile [median (IQR) 74 (71, 79) years] were less likely to fare [HR 0.80 (95% CI 0.63, 1.00), p = 0.05] Patients with infammatory arthritis (compared with connective tissue disease, vasculitis and others) and patients with baseline active disease were more likely to fare [HR 1.72 (95% CI 1.35, 2.20), p < 0.001 and 1.82 (95% CI 1.39, 2.39), p < 0.001 respectively] Conclusion: There was a moderately high rate of AIIRD fares after mRNA vaccination;however, there was no clustering of fares in the immediate post-vaccine period to suggest causality. Older patients were less likely to fare, while those with infammatory arthritis and active disease at baseline were more likely to fare.
ABSTRACT
We present METATRYP version 2 software that identifies shared peptides across the predicted proteomes of organisms within environmental metaproteomics studies to enable accurate taxonomic attribution of peptides during protein inference. Improvements include ingestion of complex sequence assembly data categories (metagenomic and metatranscriptomic assemblies, single cell amplified genomes, and metagenome assembled genomes), prediction of the least common ancestor (LCA) for a peptide shared across multiple organisms, increased performance through updates to the backend architecture, and development of a web portal (https://metatryp.whoi.edu). Major expansion of the marine METATRYP database with predicted proteomes from environmental sequencing confirms a low occurrence of shared tryptic peptides among disparate marine microorganisms, implying tractability for targeted metaproteomics. METATRYP was designed to facilitate ocean metaproteomics and has been integrated into the Ocean Protein Portal (https://oceanproteinportal.org); however, it can be readily applied to other domains. We describe the rapid deployment of a coronavirus-specific web portal (https://metatryp-coronavirus.whoi.edu/) to aid in use of proteomics on coronavirus research during the ongoing pandemic. A coronavirus-focused METATRYP database identified potential SARS-CoV-2 peptide biomarkers and indicated very few shared tryptic peptides between SARS-CoV-2 and other disparate taxa analyzed, sharing <1% peptides with taxa outside of the betacoronavirus group, establishing that taxonomic specificity is achievable using tryptic peptide-based proteomic diagnostic approaches.