Serological response and breakthrough infection after COVID-19 vaccination in patients with cirrhosis and post-liver transplant

Abstract

Background: Vaccine hesitancy and lack of access remain major issues in disseminating COVID-19 vaccination to liver patients globally. Factors predicting poor response to vaccination and risk of breakthrough infection are important data to target booster vaccine programs. The primary aim of the current study was to measure humoral responses to 2 doses of COVID-19 vaccine. Secondary aims included the determination of factors predicting breakthrough infection.

Methods: COVID-19 vaccination and Biomarkers in cirrhosis And post-Liver Transplantation is a prospective, multicenter, observational case-control study. Participants were recruited at 4-10 weeks following first and second vaccine doses in cirrhosis [n = 325; 94% messenger RNA (mRNA) and 6% viral vaccine], autoimmune liver disease (AILD) (n = 120; 77% mRNA and 23% viral vaccine), post-liver transplant (LT) (n = 146; 96% mRNA and 3% viral vaccine), and healthy controls (n = 51; 72% mRNA, 24% viral and 4% heterologous combination). Serological end points were measured, and data regarding breakthrough SARS-CoV-2 infection were collected.

Results: After adjusting by age, sex, and time of sample collection, anti-Spike IgG levels were the lowest in post-LT patients compared to cirrhosis (p < 0.0001), AILD (p < 0.0001), and control (p = 0.002). Factors predicting reduced responses included older age, Child-Turcotte-Pugh B/C, and elevated IL-6 in cirrhosis; non-mRNA vaccine in AILD; and coronary artery disease, use of mycophenolate and dysregulated B-call activating factor, and lymphotoxin-α levels in LT. Incident infection occurred in 6.6%, 10.6%, 7.4%, and 15.6% of cirrhosis, AILD, post-LT, and control, respectively. The only independent factor predicting infection in cirrhosis was low albumin level.

Conclusions: LT patients present the lowest response to the SARS-CoV-2 vaccine. In cirrhosis, the reduced response is associated with older age, stage of liver disease and systemic inflammation, and breakthrough infection with low albumin level.

FIGURE 1

Study design and CONSORT diagram of recruitment and end points analyzed. COBALT is a prospective, multicenter, observational case-control study assessing immunogenicity of SARS-CoV-2 vaccine response in patients with cirrhosis, AILD, post-LT, and control. Participants were sampled within a 6-week window, between 4 and 10 weeks after the second SARS-CoV-2 vaccine dose (*or only vaccine dose if 1-dose regimen). Participants were followed up for breakthrough infection until booster vaccination or 8-month follow-up. Abbreviations: AILD, autoimmune liver disease; LT, liver transplant; COBALT, COVID-19 vaccination and Biomarkers in cirrhosis And post-Liver Transplantation.

FIGURE 2

Serological measurements of anti-SARS-CoV-2 antibodies postvaccination. (A and B), Serum concentrations of anti-Spike and anti-RBD IgG antibodies (respectively) in healthy controls, patients with cirrhosis (CIRRH), autoimmune liver disease (AILD), and liver transplant (LT). All measurements were obtained using electrochemoluminescence-based meso scale discovery multiplex assays. Samples were diluted at 1:5,000 for quantification, as recommended by the manufacturer. All data are represented on log10 scale scatterplot graphs; lines and error bars represent geometric mean and 95% CI. All comparisons were assessed by ANCOVA, adjusted for age, sex, and time of sample collection postvaccination, followed by Bonferroni-corrected pairwise comparisons between covariate-adjusted estimated group means. Abbreviations: AILD, autoimmune liver disease; CIRRH, cirrhosis; LT, liver transplant; RBD, receptor binding domain.

FIGURE 3

Anti-SARS-CoV-2 antibody neutralization potential measured by surrogate viral neutralization assay (sVNT). (A and B) Percentage neutralization achieved (PNA) against the reference strain Spike and RBD (respectively) by serum from healthy controls, patients with cirrhosis (CIRRH), autoimmune liver disease (AILD), and liver transplant (LT). (C–G) PNA against Alpha, Beta, Gamma, Delta, and Omicron Spike, respectively, by serum from the same 4 groups. (H) sensitivity analysis for Omicron PNA in the 4 subject groups after removing all subjects with Omicron PNA below the detection limit. All measurements were obtained using electrochemoluminescence-based meso scale discovery multiplex competitive binding assays. Samples were diluted at 1:12.5 for quantification, as recommended by the manufacturer. All data are represented on probability/percentage Logit scale scatterplot graphs; lines and error bars represent geometric mean and 95% CI. All comparisons were assessed by ANCOVA, adjusted for age, sex, and time of sample collection postvaccination, followed by Bonferroni-corrected pairwise comparisons between covariate-adjusted estimated group means. Abbreviations: AILD, autoimmune liver disease; CIRRH, cirrhosis; LT, liver transplant; PNA, percentage neutralization achieved; sVNT, surrogate viral neutralization assay; RBD, receptor binding domain.

FIGURE 4

Breakthrough infections by country. The top graph illustrates breakthrough infections recorded in the Italian cohort (black line) longitudinally represented on the background of the main viral variants sequenced over time in Italy. The bottom graph is similar in relation to the Spanish cohort and main viral variants sequenced in Spain. Longitudinal country-specific viral variant data were downloaded from the ECDC website (European Centre for Disease Prevention and Control). No specific clusters of breakthrough infections were observed based on the subject group, but subjects from all 4 groups (healthy controls, cirrhosis, autoimmune liver disease, and liver transplant) were comparably spread along the infection timeline. The Spanish breakthrough infection cohort did not contain any healthy controls. Available data on the volume of COVID-19 sequencing, the number and percentage distribution of VOC for each country, week, and variant submitted since 2020-W40 to the GISAID EpiCoV database (https://www.gisaid.org/) and TESSy (as either case-based or aggregate data). Abbreviation: ECDC, European Centre for Disease Prevention and Control.

FIGURE 5

Cox regression analysis to identify demographic, clinical, serological, or immunological factors associated with high risk of breakthrough infection. The forest plot represents the HRs for factors associated with breakthrough infection, compared to no infection, in patients with cirrhosis (CIRRH) (A), autoimmune liver disease (AILD) (B), and liver transplant (LT) (C). Only factors with Cox regression coefficients significant at alpha = 0.05 in the multivariable analysis are represented in decreasing order of significance. Error bars represent the 95% CI for the respective HRs. The dotted black line marks HR=1, that is, no association. Abbreviations: AILD, autoimmune liver disease; CIRRH, cirrhosis; LT, liver transplant.