Background: Thalassemia is one of the most prevalent and severe monogenic disorders worldwide. In China, a three-tiered prevention and control strategy has been established for this disease, comprising preconception carrier screening, prenatal diagnosis, and neonatal screening. However, the implementation of neonatal thalassemia screening remains far behind the first two tiers, and the effectiveness of current screening strategies warrants systematic evaluation.
Methods: To address this gap, we conducted a prospective neonatal screening for 800 newborns from the Yulin region by directly using third-generation sequencing (TGS), with the results rigorously compared to those obtained through conventional strategies.
Results: The overall thalassemia carrier rate was 23.38%, with 14.75% for α-thalassemia, 6.50%for β-thalassemia, and 2.13% for combined α-/β-thalassemia, respectively. A total of 25 distinct variants were identified across the globin gene clusters, including 13 previously reported common variants in the Chinese population and 12 rare variants, underscoring substantial genetic heterogeneity and a considerable disease burden in this region. Comparative analysis revealed that hematological testing failed to detect 46 carriers, and 14 cases showed discordant genotypes between conventional genetic assays and TGS with all discordant variants validated by Sanger sequencing or multiple ligation probe amplification technology. Collectively, TGS increased the detection rate by 10.27%.
Conclusion: These results demonstrate the comprehensive genomic landscape of thalassemia in the Yulin region. Furthermore, these findings provide evidence for the advantages of TGS over conventional strategies in neonatal thalassemia screening, thereby offering insights for the paradigm toward precision prevention and control of thalassemia, especially in high-prevalence regions.
Keywords: neonatal screening; precision prevention and control; rare variant; thalassemia; third-generation sequencing.
Copyright © 2026 Ning, He, Wei, Liang, Xie, Zhou, Liang, Liu, Mao and Qin.