Dataset Information

Proteomics profiling reveals lipid metabolism abnormalities during oogenesis in unexplained recurrent pregnancy loss.

ABSTRACT:

Background

Unexplained recurrent pregnancy loss (URPL) is a clinical dilemma in reproductive fields. Its diagnosis is mainly exclusionary after extensive clinical examination, and some of the patients may still face the risk of miscarriage.

Methods

We analyzed follicular fluid (FF) from in vitro fertilization (IVF) in eight patients with URPL without endocrine abnormalities or verifiable causes of abortion and eight secondary infertility controls with no history of pregnancy loss who had experienced at least one normal pregnancy and delivery by direct data-independent acquisition (dDIA) quantitative proteomics to identify differentially expressed proteins (DEPs). In this study, bioinformatics analysis was performed using online software including g:profiler, String, and ToppGene. Cytoscape was used to construct the protein-protein interaction (PPI) network, and ELISA was used for validation.

Results

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the DEPs are involved in the biological processes (BP) of complement and coagulation cascades. Apolipoproteins (APOs) are key proteins in the PPI network. ELISA confirmed that APOB was low-expressed in both the FF and peripheral blood of URPL patients.

Conclusion

Dysregulation of the immune network intersecting coagulation and inflammatory response is an essential feature of URPL, and this disequilibrium exists as early as the oogenesis stage. Therefore, earlier intervention is necessary to prevent the development of URPL. Moreover, aberrant lipoprotein regulation appears to be a key factor contributing to URPL. The mechanism by which these factors are involved in the complement and coagulation cascade pathways remains to be further investigated, which also provides new candidate targets for URPL treatment.

SUBMITTER: Liu K

PROVIDER: S-EPMC11339622 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Publications

Proteomics profiling reveals lipid metabolism abnormalities during oogenesis in unexplained recurrent pregnancy loss.

Liu Kun K Xu Xiaojuan X Sun Liang L Li Hongxing H Jin Yi Y Ma Xiaoling X Shen Bairong B Martin Cesar C

Frontiers in immunology 20240808

<h4>Background</h4>Unexplained recurrent pregnancy loss (URPL) is a clinical dilemma in reproductive fields. Its diagnosis is mainly exclusionary after extensive clinical examination, and some of the patients may still face the risk of miscarriage.<h4>Methods</h4>We analyzed follicular fluid (FF) from <i>in vitro</i> fertilization (IVF) in eight patients with URPL without endocrine abnormalities or verifiable causes of abortion and eight secondary infertility controls with no history of pregnanc ...[more]

PMID: 39176081

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Project description:BackgroundUnexplained recurrent pregnancy loss (URPL) is a significant obstetric challenge affecting maternal health and well-being. Genetic factors, including mutations in the methylenetetrahydrofolate reductase (MTHFR) gene and elevated homocysteine levels, are increasingly recognized as contributors to URPL, though their precise roles remain complex. This study aimed to comprehensively explore these factors.ObjectivesThis study examines the links between MTHFR gene polymorphisms (C677T and A1298C), plasma homocysteine levels, and URPL. It also aims to create a predictive model for URPL based on these factors.DesignA case-control study with Vietnamese women who had at least one pregnancy between January 2017 and June 2020, recruited from Medlatec Hospital and Hanoi Medical University. Participants included URPL cases (n = 128) and controls (n = 126).MethodsParticipants were selected based on specific criteria. Main analyses identified the optimal multivariable logistic regression model for predicting URPL using Bayesian Model Averaging, with the optimal model chosen based on the highest Area Under the Curve (AUC) and posterior probability. A nomogram for clinical risk prediction was developed based on parameters from the optimal model.ResultsURPL cases exhibited significantly higher plasma homocysteine levels (11.73 ± 6.08 µmol/L) compared to controls (7.64 ± 1.78 µmol/L), correlating with increased URPL risk (OR: 1.64, 95% confidence interval (CI): 1.41-1.96; p < 0.001). The MTHFR C677T variant showed strong associations with URPL, particularly the CT genotype (OR: 6.07, 95% CI: 3.00-12.93; p < 0.001) and TT genotype (OR: 14.62, 95% CI: 2.85-114.77; p = 0.003). Similarly, the A1298C variant demonstrated elevated URPL risk with the AC genotype (OR: 2.73, 95% CI: 1.34-5.78; p = 0.007) and CC genotype (OR: 12.43, 95% CI: 3.17-64.22; p = 0.001).ConclusionThis study provides insights into the complex interplay of MTHFR gene mutations, elevated homocysteine levels, and URPL. Genetic testing and biomarker assessment may play a crucial role in customizing risk assessment and management strategies for women at risk of URPL.

Project description:Background and aimThe Th17/Treg balance in peripheral blood and reproductive tissues may have a role in the etiology of unexplained recurrent pregnancy loss (URPL). In this study, we evaluated the major cytokine of Treg cells transforming growth factor-beta (TGF-β), and their specific transcription factor Forkhead box P3 (FOXP3), as well as the most highlighted cytokine of Th17 cells (interleukin [IL]-17A) in both URPL patients and healthy women.MethodsSamples were extracted from the peripheral blood, endocervix, endometrium, and vagina of 14 patients with URPL and 12 normal non-pregnant women as a control (normal) group. Quantitative reverse transcription polymerase chain reaction was used to determine gene expression. Enzyme-linked immunosorbent assay was used to determine the levels of cytokines in the serum and cervicovaginal fluid.ResultsWe found that in the URPL group, FOXP3 gene expression was considerably higher in peripheral blood than in the normal group (P=0.043). TGF-β levels in the cervicovaginal fluid were different in the URPL and normal groups (P=0.015). In comparison to the control group, women with URPL had significantly greater IL-17 gene expression in the peripheral blood (P=0.01).ConclusionLower TGF-β levels in the cervicovaginal fluid of patients compared to controls may be related with increased IL-17 and FOXP3 mRNA levels in patients with URPL. Dysregulation of local immune responses in reproductive tissues may represent dysregulation of systemic regulatory immunological responses in the pathogenesis of URPL.Relevance for patientsDysregulation of immune responses may play a role in the pathogenesis of URPL at least in some patients with URPL. We conclude that the breakdown of tolerance in the local immune responses is more critical than the breakdown of tolerance in systemic tolerance in the pathogenesis of URPL. Therefore, modulating immune responses in the endometrium and decidua may be the focus of future therapeutic approaches in URPL. The impact of seminal plasma on the expansion of Tregs may provide a novel therapeutic intervention that has already been used in assisted reproductive technologies. Therefore, we suggest that transvaginal TGF-β in women with URPL may induce maternal tolerance which leads to the successful pregnancy.

Project description:BackgroundThe optimization of endometrial receptivity (ER) through individualized therapies has been shown to enhance the likelihood of successful gestation. However, current practice lacks comprehensive methods for evaluating the ER of patients with recurrent pregnancy loss (RPL). Radiomics, an emerging AI-based technique that enables the extraction of mineable information from medical images, holds potential to offer a more objective and quantitative approach to ER assessment. This innovative tool may facilitate a deeper understanding of the endometrial environment and enable clinicians to optimize ER evaluation in RPL patients.ObjectiveThis study aimed to identify ultrasound radiomics features associated with ER, with the purpose of predicting successful ongoing pregnancies in RPL patients, and to assess the predictive accuracy of these features against regular ER parameters.MethodsThis retrospective, controlled study involved 262 patients with unexplained RPL and 273 controls with a history of uncomplicated full-term pregnancies. Radiomics features were extracted from ultrasound endometrial segmentation images to derive a radiomics score (rad-score) for each participant. Associations between rad-scores, baseline clinical variables, and sonographic data were evaluated using univariate and multivariate logistic regression analyses to identify potential indicators of RPL. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive accuracy of the rad-score and other identified indicators in discriminating RPL cases. Furthermore, the relationships between age and these identified indicators were assessed via Pearson correlation analysis.ResultsFrom the 1312 extracted radiomics features, five non-zero coefficient radiomics signatures were identified as significantly associated with RPL, forming the basis of the rad-score. Following multivariate logistic regression analysis, age, spiral artery pulsatility index (SA-PI), vascularisation index (VI), and rad-score emerged as independent correlates of RPL (all P<0.05). ROC curve analyses revealed the superior discriminative capability of the rad-score (AUC=0.882) over age (AUC=0.778), SA-PI (AUC=0.771), and VI (AUC=0.595). There were notable correlations between age and rad-score (r=0.275), VI (r=-0.224), and SA-PI (r=0.211), indicating age-related variations in RPL predictors.ConclusionThis study revealed a significant association between unexplained RPL and elevated endometrial rad-scores during the WOI. Furthermore, it demonstrated the potential of rad-scores as a promising predictive tool for successful ongoing pregnancies in RPL patients.

Dataset Information

Proteomics profiling reveals lipid metabolism abnormalities during oogenesis in unexplained recurrent pregnancy loss.

Background

Methods

Results

Conclusion

Publications

Proteomics profiling reveals lipid metabolism abnormalities during oogenesis in unexplained recurrent pregnancy loss.

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