Lasting immunity will be critical for overcoming COVID-19. However, the factors associated with the development of high titers of anti-SARS-CoV-2 Abs and how long those Abs persist remain incompletely defined. In particular, an understanding of the relationship between COVID-19 symptoms and anti-SARS-CoV-2 Abs is limited. To address these unknowns, we quantified serum anti-SARS-CoV-2 Abs in clinically diverse COVID-19 convalescent human subjects 5 wk (n 5 113) and 3 mo (n 5 79) after symptom resolution with three methods: a novel multiplex assay to quantify IgG against four SARS-CoV-2 Ags, a new SARS-CoV-2 receptor binding domain-angiotensin converting enzyme 2 inhibition assay, and a SARS-CoV-2 neutralizing assay. We then identified clinical and demographic factors, including never-before-assessed COVID-19 symptoms, that consistently correlate with high anti-SARS-CoV-2 Ab levels. We detected anti-SARS-CoV-2 Abs in 98% of COVID-19 convalescent subjects 5 wk after symptom resolution, and Ab levels did not decline at 3 mo. Greater disease severity, older age, male sex, higher body mass index, and higher Charlson Comorbidity Index score correlated with increased anti-SARS-CoV-2 Ab levels. Moreover, we report for the first time (to our knowledge) that COVID-19 symptoms, most consistently fever, body aches, and low appetite, correlate with higher anti-SARS-CoV-2 Ab levels. Our results provide robust and new insights into the development and persistence of anti-SARS-CoV-2 Abs. ImmunoHorizons, 2021, 5: 466-476.

Objective. Anti-citrullinated protein antibodies (ACPAs) and rheumatoid factor (RF) are commonly present in rheumatoid arthritis (RA) without a clear rationale for their coexistence. Moreover, autoantibodies develop against proteins with different posttranslational modifications and native proteins without obvious unifying characteristics of the antigens. We undertook this study to broadly evaluate autoantibody binding in seronegative and seropositive RA to identify novel features of reactivity.Methods. An array was created using a total of 172,828 native peptides, citrulline-containing peptides, and homocitrulline-containing peptides derived primarily from proteins citrullinated in the rheumatoid joint. IgG and IgM binding to peptides were compared between cyclic citrullinated peptide (CCP)-positive RF+, CCP+RF−, CCP−RF+, and CCP−RF− serum from RA patients (n = 48) and controls (n = 12). IgG-bound and endogenously citrullinated peptides were analyzed for amino acid patterns and predictors of intrinsic disorder, i.e., unstable 3-dimensional structure. Binding to IgG-derived peptides was specifically evaluated. Enzyme-linked immunosorbent assay confirmed key results.Results. Broadly, CCP+RF+ patients had high citrulline-specific IgG binding to array peptides and CCP+RF− and CCP−RF+ patients had modest citrulline-specific IgG binding (median Z scores 3.02, 1.42, and 0.75, respectively; P < 0.0001). All RA groups had low homocitrulline-specific binding. CCP+RF+ patients had moderate IgG binding to native peptides (median Z score 2.38; P < 0.0001). The highest IgG binding was to citrulline-containing peptides, irrespective of protein identity, especially if citrulline was adjacent to glycine or serine, motifs also seen in endogenous citrullination in the rheumatoid joint. Highly bound peptides had multiple features predictive of disorder. IgG from CCP+RF+ patients targeted citrulline-containing IgG-derived peptides.Conclusion. Disordered antigens, which are frequently citrullinated, and common epitopes for ACPAs and RF are potentially unifying features for RA autoantibodies.

The consequences of past COVID-19 infection for personal and population health are emerging, but accurately identifying distant infection is a challenge. Anti-spike antibodies rise after both vaccination and infection and anti-nucleocapsid antibodies rapidly decline. We evaluated anti-membrane antibodies in COVID-19 naïve, vaccinated, and convalescent subjects to determine if they persist and accurately detect distant infection. We found that anti-membrane antibodies persist for at least a year and are a sensitive and specific marker of past COVID-19 infection. Thus, anti-membrane and anti-spike antibodies together can differentiate between COVID-19 convalescent, vaccinated, and naïve states to advance public health and research.

Autoantibodies against citrullinated proteins are a hallmark of rheumatoid arthritis, a destructive inflammatory arthritis. Peptidylarginine deiminase 4 (PAD4) has been hypothesized to contribute to rheumatoid arthritis by citrullinating histones to induce neutrophil extracellular traps (NETs), which display citrullinated proteins that are targeted by autoantibodies to drive inflammation and arthritis. Consistent with this theory, PAD4-deficient mice have reduced NETs, autoantibodies, and arthritis. However, PAD4′s role in human rheumatoid arthritis is less clear. Here, we determine if single nucleotide polymorphism rs2240335 in PADI4, whose G allele is associated with reduced PAD4 in neutrophils, correlates with NETs, anti-histone antibodies, and rheumatoid arthritis susceptibility in North Americans. Control and rheumatoid arthritis subjects, divided into anti-cyclic citrullinated peptide (CCP) antibody positive and negative groups, were genotyped at rs2240335. In homozygotes, in vitro NETosis was quantified in immunofluorescent images and circulating NET and anti-histone antibody levels by enzyme linked immunosorbent assay (ELISA). Results were compared by t-test and correlation of rheumatoid arthritis diagnosis with rs2240335 by Armitage trend test. NET levels did not significantly correlate with genotype. G allele homozygotes in the CCP− rheumatoid arthritis group had reduced anti-native and anti-citrullinated histone antibodies. However, the G allele conferred increased risk for rheumatoid arthritis diagnosis, suggesting a complex role for PAD4 in human rheumatoid arthritis.

Peptide microarrays have emerged as a powerful technology in immunoproteomics as they provide a tool to measure the abundance of different antibodies in patient serum samples. The high dimensionality and small sample size of many experiments challenge conventional statistical approaches, including those aiming to control the false discovery rate (FDR). Motivated by limitations in reproducibility and power of current methods, we advance an empirical Bayesian tool that computes local false discovery rate statistics and local false sign rate statistics when provided with data on estimated effects and estimated standard errors from all the measured peptides. As the name suggests, the MixTwice tool involves the estimation of two mixing distributions, one on underlying effects and one on underlying variance parameters. Constrained optimization techniques provide for model fitting of mixing distributions under weak shape constraints (unimodality of the effect distribution). Numerical experiments show that MixTwice can accurately estimate generative parameters and powerfully identify non-null peptides. In a peptide array study of rheumatoid arthritis (RA), MixTwice recovers meaningful peptide markers in one case where the signal is weak, and has strong reproducibility properties in one case where the signal is strong. Availability MixTwice is available as an R software package https://cran.rproject. org/web/packages/MixTwice/ Supplementary information Supplementary data are available at Bioinformatics online.