{"title":"卵巢反应差的不孕症患者卵泡液的非靶向代谢组学分析","authors":"Liang Guo, Jiaming Song, Xiyang Xia, Jianya Jiang, Yingying Yang, Wei Chen, Li Chen, Pingping Xue","doi":"10.3389/fendo.2025.1547550","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Poor ovarian response (POR) is a pathological condition characterized by inadequate ovarian response to gonadotropin stimulation in patients undergoing <i>in vitro</i> fertilization and embryo transfer. It represents a primary cause of failure in many assisted reproductive technology treatments. Utilizing non-targeted metabolomics technology applied to follicular fluid, this research aims to elucidate the metabolic characteristics associated with POR, explore the underlying molecular mechanisms, and identify potential biomarkers. By analyzing metabolic factors that influence oocyte quality, we aspire to provide insights for the early detection and intervention of patients with POR.</p><p><strong>Methods: </strong>In this research, 60 follicular fluid samples were collected for a non-targeted metabolomic study, including 30 samples from POR patients and 30 from women with normal ovarian reserve. The orthogonal partial least squares discriminant analysis model was employed to discern separation trends between the two groups. Pathway enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Additionally, random forest and logistic regression models were utilized to identify biomarkers indicative of POR within the follicular fluid.</p><p><strong>Results: </strong>Based on data from the Human Metabolome Database, our metabolomic analysis identified 40 differential metabolites associated with POR, including 18 up-regulated and 22 down-regulated metabolites. KEGG pathway analysis revealed that these metabolites predominantly participate in glycerophospholipid metabolism, choline metabolism in cancer, autophagy processes. Notably, perillyl aldehyde emerged as a potential biomarker for POR.</p><p><strong>Conclusions: </strong>This study represents the first comprehensive examination of metabolic alterations in follicular fluid among patients with POR using non-targeted metabolomics technology. We have identified significant metabolic changes within the follicular fluid of individuals affected by POR which may offer valuable insights into therapeutic strategies for managing this condition as well as improving outcomes in assisted reproductive technologies.</p>","PeriodicalId":12447,"journal":{"name":"Frontiers in Endocrinology","volume":"16 ","pages":"1547550"},"PeriodicalIF":3.9000,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12104088/pdf/","citationCount":"0","resultStr":"{\"title\":\"Non-targeted metabolomic analysis of follicular fluid in infertile individuals with poor ovarian response.\",\"authors\":\"Liang Guo, Jiaming Song, Xiyang Xia, Jianya Jiang, Yingying Yang, Wei Chen, Li Chen, Pingping Xue\",\"doi\":\"10.3389/fendo.2025.1547550\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Poor ovarian response (POR) is a pathological condition characterized by inadequate ovarian response to gonadotropin stimulation in patients undergoing <i>in vitro</i> fertilization and embryo transfer. It represents a primary cause of failure in many assisted reproductive technology treatments. Utilizing non-targeted metabolomics technology applied to follicular fluid, this research aims to elucidate the metabolic characteristics associated with POR, explore the underlying molecular mechanisms, and identify potential biomarkers. By analyzing metabolic factors that influence oocyte quality, we aspire to provide insights for the early detection and intervention of patients with POR.</p><p><strong>Methods: </strong>In this research, 60 follicular fluid samples were collected for a non-targeted metabolomic study, including 30 samples from POR patients and 30 from women with normal ovarian reserve. The orthogonal partial least squares discriminant analysis model was employed to discern separation trends between the two groups. Pathway enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Additionally, random forest and logistic regression models were utilized to identify biomarkers indicative of POR within the follicular fluid.</p><p><strong>Results: </strong>Based on data from the Human Metabolome Database, our metabolomic analysis identified 40 differential metabolites associated with POR, including 18 up-regulated and 22 down-regulated metabolites. KEGG pathway analysis revealed that these metabolites predominantly participate in glycerophospholipid metabolism, choline metabolism in cancer, autophagy processes. Notably, perillyl aldehyde emerged as a potential biomarker for POR.</p><p><strong>Conclusions: </strong>This study represents the first comprehensive examination of metabolic alterations in follicular fluid among patients with POR using non-targeted metabolomics technology. We have identified significant metabolic changes within the follicular fluid of individuals affected by POR which may offer valuable insights into therapeutic strategies for managing this condition as well as improving outcomes in assisted reproductive technologies.</p>\",\"PeriodicalId\":12447,\"journal\":{\"name\":\"Frontiers in Endocrinology\",\"volume\":\"16 \",\"pages\":\"1547550\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12104088/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Endocrinology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fendo.2025.1547550\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Endocrinology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fendo.2025.1547550","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Non-targeted metabolomic analysis of follicular fluid in infertile individuals with poor ovarian response.
Background: Poor ovarian response (POR) is a pathological condition characterized by inadequate ovarian response to gonadotropin stimulation in patients undergoing in vitro fertilization and embryo transfer. It represents a primary cause of failure in many assisted reproductive technology treatments. Utilizing non-targeted metabolomics technology applied to follicular fluid, this research aims to elucidate the metabolic characteristics associated with POR, explore the underlying molecular mechanisms, and identify potential biomarkers. By analyzing metabolic factors that influence oocyte quality, we aspire to provide insights for the early detection and intervention of patients with POR.
Methods: In this research, 60 follicular fluid samples were collected for a non-targeted metabolomic study, including 30 samples from POR patients and 30 from women with normal ovarian reserve. The orthogonal partial least squares discriminant analysis model was employed to discern separation trends between the two groups. Pathway enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Additionally, random forest and logistic regression models were utilized to identify biomarkers indicative of POR within the follicular fluid.
Results: Based on data from the Human Metabolome Database, our metabolomic analysis identified 40 differential metabolites associated with POR, including 18 up-regulated and 22 down-regulated metabolites. KEGG pathway analysis revealed that these metabolites predominantly participate in glycerophospholipid metabolism, choline metabolism in cancer, autophagy processes. Notably, perillyl aldehyde emerged as a potential biomarker for POR.
Conclusions: This study represents the first comprehensive examination of metabolic alterations in follicular fluid among patients with POR using non-targeted metabolomics technology. We have identified significant metabolic changes within the follicular fluid of individuals affected by POR which may offer valuable insights into therapeutic strategies for managing this condition as well as improving outcomes in assisted reproductive technologies.
期刊介绍:
Frontiers in Endocrinology is a field journal of the "Frontiers in" journal series.
In today’s world, endocrinology is becoming increasingly important as it underlies many of the challenges societies face - from obesity and diabetes to reproduction, population control and aging. Endocrinology covers a broad field from basic molecular and cellular communication through to clinical care and some of the most crucial public health issues. The journal, thus, welcomes outstanding contributions in any domain of endocrinology.
Frontiers in Endocrinology publishes articles on the most outstanding discoveries across a wide research spectrum of Endocrinology. The mission of Frontiers in Endocrinology is to bring all relevant Endocrinology areas together on a single platform.