Skip to content

Author

You-Zhen Liao

1 paper indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Jul 2026

Hidden asymptomatic breakthrough infection in a proof-of-concept longitudinal study on SARS-CoV-2 vaccine recipients

Individuals with asymptomatic SARS-CoV-2 infection can unknowingly transmit the virus, yet identifying such subclinical infections in post-vaccinated populations remains challenging. We conducted a longitudinal study of 129 infection-naïve vaccine recipients immunized with various combinations of SARS-CoV-2 spike (S) protein vaccine platforms. Sera were collected before the first dose (v1), at 2 weeks (v7) and 6 months (v8) after the third dose. Taiwan’s first major COVID-19 outbreak occurred between v7 and v8. We measured anti-nucleocapsid (anti-N) and anti-S IgG antibody titers by ELISA and assessed virus-neutralizing activity using live virus and pseudovirus assays. By developing an iterative serial screening method, we identified asymptomatic breakthrough (post-vaccination) infections among unconfirmed cases. Our v7-v8 paired cohort resolved into three distinct groups: confirmed cases (21%), asymptomatic breakthrough infections (17%), and uninfected subjects (62%). In normalized v8 sera, confirmed cases exhibited an anti-S+++ (high) /anti-N+++ (high) phenotype, while uninfected subjects showed an anti-S+ (low)/anti-N+(baseline) phenotype. Statistical analysis validated a distinct asymptomatic group characterized by an antibody profile anti-S++ (intermediate) /anti-N+ (baseline). This approach may enable more accurate estimates of vaccine efficacy and infection prevalence. In a spike-vaccinated population, anti-N antibody is more a potential specific marker for COVID-19 symptomatic disease than an ideal marker for SARS-CoV-2 infection. To our knowledge, this is the first preliminary report of identification of asymptomatic breakthrough infection from a well-vaccinated population using self-matched longitudinal pairs of serum samples.

C. Shih, You-Zhen Liao, Che-Yu Hsu et al. · 0 citations