Table 1.

List of publications of using cfDNA epigenetics information to infer disease

Disease	Epigenetic profile used	Data type	Sample size	Prediction method	Publication
Lung cancer, HCC, pancreatic cancer, glioblastoma, gastric cancer, colorectal cancer, breast cancer patients	5hmC	hMe-Seal	49	RF, Mclust	Song et al. [10]
Colorectal cancer, gastric cancer, pancreatic cancer, liver cancer, thyroid cancer	5hmC	hMe-Seal	350	Logistic regression	Li et al. [11]
HCC	5mC	BS-seq	1933	Logistic regression	Xu et al. [9]
Pregnant/nonpregnant plasma	5mC	BS-seq	27	NA	Jensen et al. [22]
General cancer	5mC	Methylation 450k microarray/BS-seq	87	Probalistic model for tumor burden	Kang et al. [8]
Diabetes, multiple sclerosis, traumatic or ischemic brain damage, pancreatic cancer or pancreatitis	5mC	Methylation 450k microarray	218	NA	Lehmann-Werman et al. [23]
General disease	5mC	Methylation 450k microarray/BS-seq	NA	NA	Tanic et al. [24]
Colorectal, breast, lung, pancreatic and ovarian cancers	5mC	Methylation 450k microarray/BS-seq	NA	NA	Warton et al. [25]
General disease-related pathogenic mechanisms	5mC	Methylation 450k microarray	N=4 (17 tissues)	NA	Lokk et al. [26]
Colon, prostate, breast, lung cancer	Nucleosome positioning	DNA sequencing	179	Coverage depth	Ulz et al. [21]
Pregnancies/nonpregnancies	5mC	Methylation 450k microarray	22	NA	Hatt et al. [27]
Lung, colorectal cancer	5mC	BS-seq	59	NA	Guo et al. [28]
Tissue-specific methylation	5mC	MethylC-seq	N= 4 (18 tissues)	NA	Schultz et al. [15]
General cell types contribution	Nucleosome positioning	DNA sequencing	60	Coverage depth	Snyder et al. [29]
Prenatal, cancer and transplantation assessments	5mC	BS-seq	83	QP	Sun et al. [17]
Metastatic breast cancer	5mC	BS-seq	120	NA	Legendre et al. [30]

Note: The epigenetics information used is either DNA methylation (5mC), DNA hydroxymethylation (5hmC) or nucleosome position.