Table 2.

TEs outputted by machine learning analysis. These eight TEs were able to discriminate pre and normal condition patients with an AUC accuracy of 69%

Chr	Start	End	TE	Gene
22	23,900,208	23,900,715	MER9a2	NA
16	67,141,398	67,142,927	MER52A	C16orf70
2	26,305,911	26,306,395	LTR15	AC10896.1
19	11,853,714	11,854,477	HERVK3-int	ZNF439
17	67,398,160	67,399,008	HSMAR1	PITPNC1
2	97,505,313	97,505,837	MER1A	ANKRD36B
20	44,217,986	44,218,725	L1ME4b	OSER1-DT
19	54,668,341	54,669,123	L1M5	LILRB4