Machine Learning-Driven Discovery of TRIM Genes as Diagnostic Biomarkers for Idiopathic Pulmonary Fibrosis

20 June 2025 : Clinical Research

Xiangfei Huang^{CEFG 1}, Wen Yu^{BCE 1}, Fuzhou Hua^{E 2}, Aiping Wei^{E 1}, Xifeng Wang^{AE 1*}, Shibiao Chen^{AEG 1}

DOI: 10.12659/MSM.948510

Med Sci Monit 2025; 31:e948510

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Table 2 The correlation between the disease-characteristic genes and the clinical features.

Gene	Clinical features	Cor	p-value
TNIK	Age	−0.244	0.067
	DLco% predicted^*	0.278	0.038
	FVC% predicted^**	0.399	0.002
	Survival^*	0.306	0.021
NCL	Age	−0.240	0.073
	DLco% predicted	0.109	0.426
	FVC% predicted	0.244	0.067
	Survival	0.161	0.232
ROPN1L	Age	0.196	0.144
	DLco% predicted	−0.141	0.301
	FVC% predicted	−0.182	0.174
	Survival	−0.247	0.064
MTR	Age	−0.213	0.112
	DLco% predicted	0.138	0.309
	FVC% predicted	0.222	0.096
	Survival	0.140	0.301
HNRNPH1	Age	−0.183	0.174
	DLco% predicted	0.126	0.356
	FVC% predicted^*	0.294	0.026
	Survival	0.157
Correlations were analyzed using Pearson correlation coefficients. ^* ≤0.05; ^** ≤0.01.

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