Epigenetic analysis of cell-free DNA by fragmentomic profiling

Autor: Qing Zhou, Guannan Kang, Peiyong Jiang, Rong Qiao, W. K. Jacky Lam, Stephanie C. Y. Yu, Mary-Jane L. Ma, Lu Ji, Suk Hang Cheng, Wanxia Gai, Wenlei Peng, Huimin Shang, Rebecca W. Y. Chan, Stephen L. Chan, Grace L. H. Wong, Linda T. Hiraki, Stefano Volpi, Vincent W. S. Wong, John Wong, Rossa W. K. Chiu, K. C. Allen Chan, Y. M. Dennis Lo
Rok vydání: 2022
Předmět:
Zdroj: Proceedings of the National Academy of Sciences. 119
ISSN: 1091-6490
0027-8424
DOI: 10.1073/pnas.2209852119
Popis: Cell-free DNA (cfDNA) fragmentation patterns contain important molecular information linked to tissues of origin. We explored the possibility of using fragmentation patterns to predict cytosine-phosphate-guanine (CpG) methylation of cfDNA, obviating the use of bisulfite treatment and associated risks of DNA degradation. This study investigated the cfDNA cleavage profile surrounding a CpG (i.e., within an 11-nucleotide [nt] window) to analyze cfDNA methylation. The cfDNA cleavage proportion across positions within the window appeared nonrandom and exhibited correlation with methylation status. The mean cleavage proportion was ∼twofold higher at the cytosine of methylated CpGs than unmethylated ones in healthy controls. In contrast, the mean cleavage proportion rapidly decreased at the 1-nt position immediately preceding methylated CpGs. Such differential cleavages resulted in a characteristic change in relative presentations of CGN and NCG motifs at 5′ ends, where N represented any nucleotide. CGN/NCG motif ratios were correlated with methylation levels at tissue-specific methylated CpGs (e.g., placenta or liver) (Pearson’s absolute r > 0.86). cfDNA cleavage profiles were thus informative for cfDNA methylation and tissue-of-origin analyses. Using CG-containing end motifs, we achieved an area under a receiver operating characteristic curve (AUC) of 0.98 in differentiating patients with and without hepatocellular carcinoma and enhanced the positive predictive value of nasopharyngeal carcinoma screening (from 19.6 to 26.8%). Furthermore, we elucidated the feasibility of using cfDNA cleavage patterns to deduce CpG methylation at single CpG resolution using a deep learning algorithm and achieved an AUC of 0.93. FRAGmentomics-based Methylation Analysis (FRAGMA) presents many possibilities for noninvasive prenatal, cancer, and organ transplantation assessment.
Databáze: OpenAIRE
Externí odkaz: