Integrating global burden of disease analysis and single-cell omics identifies ANTXR2 as a potential diagnostic biomarker for AML in China.

BACKGROUND

The epidemiological characteristics of acute myeloid leukemia (AML) in China, including long-term trends and reliable diagnostic biomarkers, remain insufficiently explored. This study aims to bridge these gaps by combining global burden of disease (GBD) data with single-cell multi-omics technology.

METHODS

Utilizing GBD 2021 data, we assessed the disease burden of AML in China (1990-2021) and projected trends to 2040 using an ARIMA model. Single-cell high-dimensional weighted gene co-expression network analysis was employed to identify granulomonocyte precursor-specific modules linked to AML pathogenesis. Machine learning and differential expression analysis of GEO/TCGA/GTEx RNA sequencing data were applied to screen disease-associated genes, followed by immune infiltration analysis. The diagnostic potential of ANTXR2 was validated in AML models and clinical samples.

RESULTS

GBD analysis revealed an elderly-onset pattern of AML globally and in China, with disease burden positively correlating with the Socio-demographic Index. Over the past three decades, China has experienced significant declines in AML incidence, prevalence, mortality, and disability-adjusted life years, with males consistently exhibiting a higher burden than females. These downward trends are expected to persist until 2040. Among the 22 identified disease-associated genes, ANTXR2 emerged as a potential diagnostic biomarker. In AML models and clinical samples, ANTXR2 mRNA levels were significantly reduced, suggesting this gene may play a role in apoptosis during disease progression.

CONCLUSION

This study presents the most comprehensive evaluation of AML's disease burden in China by integrating GBD analysis with single-cell multi-omics. The identification of ANTXR2 as a diagnostic biomarker provides new avenues for AML detection and management.