基于子宫内膜异位症患者异位子宫内膜组织代谢特征的非靶向代谢组学分析

doi:10.13481/j.1671-587X.20260318

Abstract

Abstract:

Objective To explore the characteristic metabolites in ectopic endometrium tissue of the patients with endometriosis （EMs） based on non-targeted metabolomics technology， and to clarify the key metabolic regulatory networks in the occurrence and development of the disease. Methods Paired ectopic and eutopic endometrium tissues from 91 EMs patients who（EMs group） underwent surgical treatment from January 2024 to January 2025， and normal endometrium tissue from 63 non-EMs patients（non-EMs group） were collected. Ultra-high performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） was used for non-targeted metabolomics detection and analysis. R （v4.3.0） software was used for statistical analysis of the data； principal component analysis （PCA） and orthogonal partial least squares discriminant analysis （OPLS-DA） were used to screen the characteristic metabolites of the disease； and Kyoto Encyclopedia of Genes and Genomes （KEGG） database was used for metabolic pathway enrichment analysis. Results A total of 245 endometrium tissue samples were collected， including 91 paired ectopic and eutopic endometrium tissue samples from the EMs patients and 63 normal endometrium tissue samples. The average age of patients in EMs group was （37.10±3.26） years old， and that of non-EMs group was （38.85±4.67） years old. A total of 2 116 metabolites were identified in all samples. Among the EMs patients， compared with eutopic endometrium tissue， 247 metabolites were up-regulated and 161 metabolites were down-regulated in ectopic endometrium tissue； compared with normal endometrium tissue of non-EMs patients， 412 metabolites were up-regulated and 97 metabolites were down-regulated in ectopic endometrium tissue of EMs patients； compared with normal endometrium tissue of non-EMs patients， 94 metabolites were up-regulated and 65 metabolites were down-regulated in eutopic endometrium tissue of EMs patients. Compared with both eutopic endometrium tissue of EMs patients and normal endometrium tissue of non-EMs patients， 163 metabolites represented by 6-acetamido-3-oxohexanoate were up-regulated， and 39 metabolites represented by alloxamine were down-regulated in ectopic endometrium tissue of EMs patients. KEGG metabolic pathway analysis showed that the up-regulated metabolites such as histamine， tyramine， dopamine and palmitoylethanolamide were significantly enriched in the neuroactive ligand-receptor interaction pathway （P<0.05）. Conclusion There is significant metabolic reprogramming in the ectopic endometrium tissue of EMs patients. Among them， metabolites represented by 6-acetamido-3-oxohexanoate are significantly increased in ectopic endometrium tissue， and the up-regulated metabolites are significantly enriched in the neuroactive ligand-receptor interaction pathway.

Key words: Endometriosis, Non-targeted metabolomics, Metabolite, Metabolic pathway, Kyoto Encyclopedia of Genes and Genomes, Enrichment analysis

CLC Number:

R711.71

Qingyun WANG,Qingyuan WANG,Qing LI,Ye HE,Wenyan WANG,Bing WEI. Non-targeted metabolomics analysis based on metabolic characteristics of ectopic endometrium tissue of patients with endometriosis[J].Journal of Jilin University(Medicine Edition), 2026, 52(3): 755-763.

Figures/Tables 8

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References 26

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Clinical characteristic	n	Age（years）	BMI（kg·m^-2）	ASRM^astage
Clinical characteristic	n	Age（years）	BMI（kg·m^-2）	Ⅰ	Ⅱ-Ⅲ	Ⅳ
EMs	91	37.10±3.26	21.80±1.82	2	39	50
Non-EMs	63	38.85±4.67	22.05±1.70	—	—	—
P		0.094	0.795

Group	Number of differential metabolites
Group	Up-regulated	Down-regulated	Total
Ectopic vs eutopic	247	161	408
Ectopic vs normal	412	97	509
Eutopic vs normal	94	65	159

Metabolite	Category	Molecular formula	Log₂FC	P	VIP
Malonic semialdehyde	Carbohydrate	C₃H₄O₄	2.51	0.001	1.992
Glyoxylic acid	Carboxylic acid	C₂H₂O₃	2.40	<0.001	2.166
2-Methylbutyrylglycine	Amino acids, peptides and their analogues	C₇H₁₃NO₃	2.16	<0.001	2.161
Imidazole 4-formaldehyde	Iminazole	C₅H₆N₂O	1.05	<0.001	2.158
6-acetamino-3-oxohexanoate	-	C₈H₁₃NO₄	3.45	<0.001	2.172
4-hydroxy-5-phenyltetrahydro-1,3-oxazine-2-one	-	C₁₀H₁₁NO₃	2.43	<0.001	2.168
N-acetyl-L-phenylalanine	Amino acids, peptides and their analogues	C₁₁H1₃NO₃	1.20	0.003	2.082
L-2-aminethylserine phosphate	Amino acids, peptides and their analogues	C₅H1₃N₂O₆P	2.89	<0.001	2.186
Alosetron	Carbohydrate	C₂₅H₄₂N₄O₁₄	-2.77	<0.001	2.043
3-Oxo-octanoic CoA	Fatty alkyloxy esters	C₂₉H₄₈N7O₁₈P₃S	-4.15	0.001	1.980

KEGG number	Name	P	Impact	Name of differential metabolite
Hsa05030	Cocaine addiction	0.033	0.250	L-tyrosine, Dopamine
Hsa00630	Acetaldehyde and dicarboxylic acid metabolism	0.091	0.208	Acetaldehyde, dihydroxyacetone phosphate, D-glycerate-3- phosphate, glycerate phosphate, malonate semialdehyde
Hsa05031	Amphetamine addiction	0.051	0.200	L-tyrosine, Dopamine
Hsa05034	Alcohol dependence	0.051	0.200	L-tyrosine, Dopamine
Hsa04917	Prolactin signaling pathway	0.061	0.181	L-tyrosine, Dopamine
Hsa04721	Synaptic vesicle circulation	0.072	0.166	Histamine, Dopamine
Hsa04728	Dopaminergic synapses	0.072	0.166	L-tyrosine, Dopamine
Hsa04080	Neuroactive ligand-receptor interactions	0.003	0.132	Histamine, Tyramine, Cortisol, sphingomyelin-1-phosphate, Thyroxine, Dopamine, Palmitoyl ethanolamine
Hsa04974	Protein digestion and absorption	0.098	0.105	L-tyrosine, Histamine, L-isoleucine, Tyramine
Hsa00071	Fatty acid degradation	0.117	0.129	3-Oxoheptanoacyl-CoA, Tetradecanoacyl-CoA, Dodecano-2,6- dienoyl-CoA, 3,6-dodecanoyl-CoA

Non-targeted metabolomics analysis based on metabolic characteristics of ectopic endometrium tissue of patients with endometriosis

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