Mammalian Meat Allergy and IgE to Alpha-Gal in Central Virginia: Findings From a COVID-19 Vaccine and Patient Cohort.

BACKGROUND: IgE to galactose-alpha-1,3-galactose (alpha-gal) is linked to tick bites and an important cause of anaphylaxis and urticarial reactions to mammalian meat. The alpha-gal syndrome (AGS) is recognized as being common in the southeastern United States. However, prevalence studies are lacking and open questions remain about risk factors and clinical presentation of alpha-gal sensitization. OBJECTIVE: Here we characterized the prevalence as well as the presentation and risk factors of AGS and alpha-gal IgE sensitization in adults in central Virginia recruited without regard to the history of allergic disease. METHODS: Adults in central Virginia, primarily University of Virginia Health employees, were recruited as part of a COVID-19 vaccine study. Subjects provided at least one blood sample and answered questionnaires about medical and dietary history. We used ImmunoCAP for IgE assays and assessed the ABO blood group by reverse typing using stored serum. We also investigated biobanked serum from COVID-19 patients. RESULTS: Median age of the 267 enrollees was 42 years, 76% were female, and 43 (16%) were sensitized to alpha-gal (cutoff of 0.1 IU/mL), of which mammalian meat allergy was reported by seven (2.6%). Sensitized subjects (1) were older, (2) had higher total IgE levels but a similar frequency of IgE to common respiratory allergens, and (3) were more likely to report tick bites than were nonsensitized subjects. Among those who were sensitized, alpha-gal IgE levels were higher among meat-allergic than nonallergic subjects (geometric mean, 9.0 vs 0.5 IU/mL; P < .001). Mammalian meat and dairy consumption was common in individuals with low-level sensitization. CONCLUSION: In central Virginia, AGS is a dominant cause of adult food allergy with a prevalence approaching or exceeding 2%.

Distinct Type 1 Immune Networks Underlie the Severity of Restrictive Lung Disease after COVID-19.

The variable etiology of persistent breathlessness after COVID-19 have confounded efforts to decipher the immunopathology of lung sequelae. Here, we analyzed hundreds of cellular and molecular features in the context of discrete pulmonary phenotypes to define the systemic immune landscape of post-COVID lung disease. Cluster analysis of lung physiology measures highlighted two phenotypes of restrictive lung disease that differed by their impaired diffusion and severity of fibrosis. Machine learning revealed marked CCR5+CD95+ CD8+ T-cell perturbations in mild-to-moderate lung disease, but attenuated T-cell responses hallmarked by elevated CXCL13 in more severe disease. Distinct sets of cells, mediators, and autoantibodies distinguished each restrictive phenotype, and differed from those of patients without significant lung involvement. These differences were reflected in divergent T-cell-based type 1 networks according to severity of lung disease. Our findings, which provide an immunological basis for active lung injury versus advanced disease after COVID-19, might offer new targets for treatment.