Mendelian randomization analyses for PCOS: evidence, opportunities, and challenges

Osthole exhibits the remedial potential for polycystic ovary syndrome mice through Nrf2-Foxo1-GSH-NF-κB pathway

Polycystic ovary syndrome (PCOS) is the primary cause of female infertility with a lack of universal therapeutic regimen. Although osthole exhibits numerous pharmacological activities in treating various diseases, its therapeutic effect on PCOS is undiscovered. The present study found that application of osthole improved the symptoms of PCOS mice through preventing ovarian granulosa cells (GCs) production of more estrogen and alleviating the liberation of pro-inflammatory cytokine interleukin (IL)-1β, IL-6, and tumor necrosis factor alpha. Meanwhile, osthole enhanced ovarian antioxidant capacity and alleviated intracellular reactive oxygen species (ROS) accumulation with a concurrent attenuation for oxidative stress, while intervention of antioxidant enzymic activity and glutathione (GSH) synthesis neutralized the salvation of osthole on GCs secretory disorder and chronic inflammation. Further analysis revealed that osthole restored the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and forkhead box O 1 (Foxo1) whose repression antagonized the amelioration of osthole on the insufficiency of antioxidant capacity and accumulation of ROS. Moreover, Nrf2 served as an intermedium to mediate the regulation of osthole on Foxo1. Additionally, osthole restricted the phosphorylation of IκBα and nuclear factor kappa B (NF-κB) subunit p65 by DHEA and weakened the transcriptional activity of NF-κB, but this effectiveness was abrogated by the obstruction of Nrf2 and Foxo1, whereas adjunction of GSH renewed the redemptive effect of osthole on NF-κB whose activation caused an invalidation of osthole in rescuing the aberration of GCs secretory function and inflammation response. Collectively, osthole might relieve the symptoms of PCOS mice via Nrf2-Foxo1-GSH-NF-κB pathway.

Genetic insights of blood lipid metabolites on polycystic ovary syndrome risk: a bidirectional two-sample Mendelian randomization study

Background

Pathologically, metabolic disorder plays a crucial role in polycystic ovarian syndrome (PCOS). However, there is no conclusive evidence lipid metabolite levels to PCOS risk.

Methods

In this study, genome-wide association study (GWAS) genetic data for 122 lipid metabolites were used to assign instrumental variables (IVs). PCOS GWAS were derived from a large-scale meta-analysis of 10,074 PCOS cases and 103,164 controls. An inverse variance weighted (IVW) analysis was the primary methodology used for Mendelian randomization (MR). For sensitivity analyses, Cochran Q test, MR-Egger intercept, MR-PRESSO, leave-one-out analysis,and Steiger test were performed. Furthermore, we conducted replication analysis, meta-analysis, and metabolic pathway analysis. Lastly, reverse MR analysis was used to determine whether the onset of PCOS affected lipid metabolites.

Results

This study detected the blood lipid metabolites and potential metabolic pathways that have a genetic association with PCOS onset. After IVW, sensitivity analyses, replication and meta-analysis, two pathogenic lipid metabolites of PCOS were finally identified: Hexadecanedioate (OR=1.85,95%CI=1.27-2.70, P=0.001) and Dihomo-linolenate (OR=2.45,95%CI=1.30-4.59, P=0.005). Besides, It was found that PCOS may be mediated by unsaturated fatty acid biosynthesis and primary bile acid biosynthesis metabolic pathways. Reverse MR analysis showed the causal association between PCOS and 2-tetradecenoyl carnitine at the genetic level (OR=1.025, 95% CI=1.003-1.048, P=0.026).

Conclusion

Genetic evidence suggests a causal relationship between hexadecanedioate and dihomo-linolenate and the risk of PCOS. These compounds could potentially serve as metabolic biomarkers for screening PCOS and selecting drug targets. The identification of these metabolic pathways is valuable in guiding the exploration of the pathological mechanisms of PCOS, although further studies are necessary for confirmation.

Causal relationship of interferon-γ and interleukin-18 upstream of intervertebral disc degeneration pathogenesis: a two-sample Mendelian randomization study

Introduction

Intervertebral disc degeneration (IVDD) is a complex disease caused by genetic and environmental factors, but its pathogenesis is still unclear. Although studies of inflammatory cytokines have been used in recent years to unravel the biological mechanisms of a variety of diseases, such analyses have not yet been applied to IVDD. Therefore, we used a Mendelian Randomization approach to explore the potential mechanisms underlying the pathogenesis of IVDD.

Methods

We obtained GWAS data from publicly available databases for inflammatory cytokines and IVDD, respectively, and explored the causal relationship between individual inflammatory cytokines and IVDD using instrumental variable (IV) analysis. We primarily used IVW methods to assess causality, while sensitivity, heterogeneity and multidirectionality analyses were performed for positive results (p < 0.05). All analyses were performed using R software.

Results

In our study, we performed a two-sample MR analysis of 41 inflammatory cytokines to identify metabolites causally associated with IVDD. Ultimately, 2 serum metabolites associated with IVDD were identified (pval<0.05), IFN-γ and IL-18. sensitivity, heterogeneity, and Pleiotropy test analyses were performed for all results.

Conclusion

Our study identified a causal relationship between IFN-γ and IL-18 and IVDD. It is valuable for the monitoring and prevention of IVDD and the exploration of targeted drugs. However, more evidence is needed to validate our study.

Causal Association Between Type 2 Diabetes Mellitus and Alzheimer's Disease: A Two-Sample Mendelian Randomization Study

Background

There is now increasing evidence that type 2 diabetes mellitus (T2DM) is associated with Alzheimer's disease (AD). However, it is unclear whether the two are causally related.

Objective

To reveal the causal association between T2DM and AD, we performed a bidirectional Mendelian randomization (MR) analysis.

Methods

Genetic instrumental variables were systematically screened, and inverse-variance weighting, MR-Egger regression, weighted median, simple mode, and weighted mode were applied to assess the pathogenic associations between the two diseases, and sensitivity analyses were used to further validate the robustness of the results.

Results

The results of forward MR analysis with T2DM as the exposure were [OR = 0.998, 95% CI (0.975∼1.021), p = 0.857], and the results of reverse MR analysis with AD as the exposure were [OR = 0.966, 95% CI (0.934∼0.999), p = 0.043]. The results showed no significant association between T2DM and AD at the gene level (p < 0.025). Sensitivity analyses were consistent with the results of the main analysis, confirming the robustness of the study.

Conclusions

T2DM and AD may not be genetically causally associated.

Validation of mitochondrial biomarkers and immune dynamics in polycystic ovary syndrome

PROBLEM

Polycystic ovary syndrome (PCOS), a prevalent endocrine-metabolic disorder, presents considerable therapeutic challenges due to its complex and elusive pathophysiology.

METHOD OF STUDY

We employed three machine learning algorithms to identify potential biomarkers within a training dataset, comprising GSE138518, GSE155489, and GSE193123. The diagnostic accuracy of these biomarkers was rigorously evaluated using a validation dataset using area under the curve (AUC) metrics. Further validation in clinical samples was conducted using PCR and immunofluorescence techniques. Additionally, we investigate the complex interplay among immune cells in PCOS using CIBERSORT to uncover the relationships between the identified biomarkers and various immune cell types.

RESULTS

Our analysis identified ACSS2, LPIN1, and NR4A1 as key mitochondria-related biomarkers associated with PCOS. A notable difference was observed in the immune microenvironment between PCOS patients and healthy controls. In particular, LPIN1 exhibited a positive correlation with resting mast cells, whereas NR4A1 demonstrated a negative correlation with monocytes in PCOS patients.

CONCLUSION

ACSS2, LPIN1, and NR4A1 emerge as PCOS-related diagnostic biomarkers and potential intervention targets, opening new avenues for the diagnosis and management of PCOS.

Association between irritable bowel syndrome and Parkinson's disease by Cohort study and Mendelian randomization analysis

This study aimed to investigate the association between irritable bowel syndrome (IBS) and Parkinson's disease (PD) utilizing prospective cohort study and Mendelian randomization. The dataset contained a substantial cohort of 426,911 participants from the UK Biobank, discussing the association between IBS and PD with Cox proportional hazards models and case-control analysis while adjusting for covariates such as age, gender, ethnicity and education level. In univariate Cox regression model, the risk of PD was reduced in IBS patients (HR: 0.774, 95%CI: 0.625-0.956, P = 0.017), but the statistical significance diminished in the three models after adjusting for other variables. In a few subgroup analyses, IBS patients are less likely to develop into PD, and patients diagnosed with IBS after 2000 also had a lower risk (HR: 0.633, 95%CI: 0.403-0.994, P = 0.047) of subsequently developing PD. In addition, we matched five healthy control participants based on gender and age at the end of the study for each IBS patient diagnosed during the follow-up period, and logistic regression results (OR:1.239, 95%CI: 0.896-1.680, P = 0.181) showed that IBS was not associated with the risk of PD. Mendelian randomization did not find significant evidence of the causal relationship between IBS and Parkinson's disease (OR: 0.801, 95%CI: 0.570-1.278, P = 0.204). Overall, we suggest that IBS status is not associated with the risk of developing PD, and that these findings provide valuable insights into the clinical management and resource allocation of patients with IBS.

Effects of dietary intervention on human diseases: molecular mechanisms and therapeutic potential

Diet, serving as a vital source of nutrients, exerts a profound influence on human health and disease progression. Recently, dietary interventions have emerged as promising adjunctive treatment strategies not only for cancer but also for neurodegenerative diseases, autoimmune diseases, cardiovascular diseases, and metabolic disorders. These interventions have demonstrated substantial potential in modulating metabolism, disease trajectory, and therapeutic responses. Metabolic reprogramming is a hallmark of malignant progression, and a deeper understanding of this phenomenon in tumors and its effects on immune regulation is a significant challenge that impedes cancer eradication. Dietary intake, as a key environmental factor, can influence tumor metabolism. Emerging evidence indicates that dietary interventions might affect the nutrient availability in tumors, thereby increasing the efficacy of cancer treatments. However, the intricate interplay between dietary interventions and the pathogenesis of cancer and other diseases is complex. Despite encouraging results, the mechanisms underlying diet-based therapeutic strategies remain largely unexplored, often resulting in underutilization in disease management. In this review, we aim to illuminate the potential effects of various dietary interventions, including calorie restriction, fasting-mimicking diet, ketogenic diet, protein restriction diet, high-salt diet, high-fat diet, and high-fiber diet, on cancer and the aforementioned diseases. We explore the multifaceted impacts of these dietary interventions, encompassing their immunomodulatory effects, other biological impacts, and underlying molecular mechanisms. This review offers valuable insights into the potential application of these dietary interventions as adjunctive therapies in disease management.

Artificially sweetened beverages consumption and risk of obesity-related cancers: a wide-angled Mendelian randomization study

Background

The impact of artificially sweetened beverages (ASBs) consumption on obesity-related cancers (ORCs) risk remains controversial. To address this challenging issue, this study employed wide-angle mendelian randomization (MR) analyses to explore the genetic causality between ASB consumption and the risk of ORCs, thereby effectively minimizing the impact of external confounders.

Methods

We conducted a suite of analyses encompassing univariable, multivariable, and two-step MR to evaluate causal associations between ASB consumption (samples = 85,852) and risk of ORCs (total samples = 2,974,770) using summary statistics from genome-wide association studies (GWAS). Total, direct, and intermediary effects were derived by performing inverse-variance weighted (IVW), MR-Egger, weighted mode, weighted median, and lasso method. Additionally, we performed an extensive range of sensitivity analyses to counteract the potential effects of confounders, heterogeneity, and pleiotropy, enhancing the robustness and reliability of the findings.

Results

Genetically predicted ASB consumption was positively associated with the risk of colorectal cancer (CRC, p = 0.011; OR: 6.879; 95% CI: 1.551, 30.512 by IVW) and breast cancer (p = 0.022; OR: 3.881; 95% CI: 2.023, 9.776 by IVW). Multivariable analysis yielded similar results. The results of the two-step MR unveiled that body mass index (BMI) assumes a pivotal role in mediating the association between ASB consumption and CRC risk (intermediary effect = 0.068, p = 0.024).

Conclusion

No causal connection exists between ASB consumption and the majority of ORCs, in addition to CRC and breast cancer. Additionally, our findings suggest that BMI might be a potential mediator in the association between ASB consumption and CRC.

Peripheral immune cell traits and Parkinson's disease: A Mendelian randomization study

BACKGROUND

The peripheral immune system is altered in Parkinson's disease (PD), but the causal relationship between the two remains controversial. In this study, we aimed to estimate the causal relationship between peripheral immune features and PD using a two-sample Mendelian randomization (MR) approach.

METHODS

Genome-wide association study (GWAS) data of peripheral blood immune signatures from European populations were used for exposure and PD summary statistics were used as results. We conducted a two-sample MR study using the inverse-variance weighted (IVW), MR-Egger, and weighted median methods to evaluate the causal association between these factors. MR-Egger and MR-PRESSO were used for sensitivity analysis to test and correct horizontal pleiotropy.

RESULTS

A total of 731 immune traits were analyzed for association with PD using three MR methods. After adjustment for FDR, we observed four peripheral immunological features associated with PD using the IVW method, including expression of CX3CR1 on monocytes [OR: 0.85, 95% CI: (0.81, 0.91), P = 6.56E-07] and CX3CR1 on CD14+CD16+ monocytes [OR: 0.87, 95% CI: (0.82, 0.93), P = 9.95E-06].

CONCLUSIONS

Our study further revealed the important role of monocytes in PD and indicated that CX3CR1 expression on monocytes is associated with a reduced risk of PD.

Disturbed Follicular Microenvironment in Polycystic Ovary Syndrome: Relationship to Oocyte Quality and Infertility

Polycystic ovary syndrome (PCOS) is a common endocrine disorder associated with infertility and poor reproductive outcomes. The follicular fluid (FF) microenvironment plays a crucial role in oocyte development. This review summarizes evidence elucidating the alterations in FF composition in PCOS. Various studies demonstrated a pronounced proinflammatory milieu in PCOS FF, characterized by increased levels of cytokines, including but not limited to interleukin-6 (IL-6), tumor necrosis factor α, C-reactive protein, and IL-1β, concomitant with a reduction in anti-inflammatory IL-10. T lymphocytes and antigen-presenting cells are dysregulated in PCOS FF. PCOS FF exhibit heightened reactive oxygen species production and the accumulation of lipid peroxidation byproducts, and impaired antioxidant defenses. Multiple microRNAs are dysregulated in PCOS FF, disrupting signaling critical to granulosa cell function. Proteomic analysis reveals changes in pathways related to immune responses, metabolic perturbations, angiogenesis, and hormone regulation. Metabolomics identify disturbances in glucose metabolism, amino acids, lipid profiles, and steroid levels with PCOS FF. Collectively, these pathological alterations may adversely affect oocyte quality, embryo development, and fertility outcomes. Further research on larger cohorts is needed to validate these findings and to forge the development of prognostic biomarkers of oocyte developmental competence within FF. Characterizing the follicular environment in PCOS is key to elucidating the mechanisms underlying subfertility in this challenging disorder.

Investigating the causal relationship and potential shared diagnostic genes between primary biliary cholangitis and systemic lupus erythematosus using bidirectional Mendelian randomization and transcriptomic analyses

Background

The co-occurrence of primary biliary cholangitis (PBC) and systemic lupus erythematosus (SLE) has been consistently reported in observational studies. Nevertheless, the underlying causal correlation between these two conditions still needs to be established.

Methods

We performed a bidirectional two-sample Mendelian randomization (MR) study to assess their causal association. Five MR analysis methods were utilized for causal inference, with inverse-variance weighted (IVW) selected as the primary method. The Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) and the IVW Radial method were applied to exclude outlying SNPs. To assess the robustness of the MR results, five sensitivity analyses were carried out. Multivariable MR (MVMR) analysis was also employed to evaluate the effect of possible confounders. In addition, we integrated transcriptomic data from PBC and SLE, employing Weighted Gene Co-expression Network Analysis (WGCNA) to explore shared genes between the two diseases. Then, we used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment methods to perform on the shared genes. The Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was utilized to identify potential shared diagnostic genes. Finally, we verified the potential shared diagnostic genes in peripheral blood mononuclear cells (PBMCs)-specific cell populations of SLE patients by single-cell analysis.

Results

Our MR study provided evidence that PBC had a causal relationship with SLE (IVW, OR: 1.347, 95% CI: 1.276 - 1.422, P < 0.001) after removing outliers (MR-PRESSO, rs35464393, rs3771317; IVW Radial, rs11065987, rs12924729, rs3745516). Conversely, SLE also had a causal association with PBC (IVW, OR: 1.225, 95% CI: 1.141 - 1.315, P < 0.001) after outlier correction (MR-PRESSO, rs11065987, rs3763295, rs7774434; IVW Radial, rs2297067). Sensitivity analyses confirmed the robustness of the MR findings. MVMR analysis indicated that body mass index (BMI), smoking and drinking were not confounding factors. Moreover, bioinformatic analysis identified PARP9, ABCA1, CEACAM1, and DDX60L as promising diagnostic biomarkers for PBC and SLE. These four genes are highly expressed in CD14+ monocytes in PBMCs of SLE patients and potentially associated with innate immune responses and immune activation.

Conclusion

Our study confirmed the bidirectional causal relationship between PBC and SLE and identified PARP9, ABCA1, CEACAM1, and DDX60L genes as the most potentially shared diagnostic genes between the two diseases, providing insights for the exploration of the underlying mechanisms of these disorders.

Investigating the causal impact of polycystic ovary syndrome on gestational diabetes mellitus: a two-sample Mendelian randomization study

Introduction

Determining the causal relationship between polycystic ovary syndrome (PCOS) and gestational diabetes mellitus (GDM) holds significant implications for GDM prevention and treatment. Despite numerous observational studies suggesting an association between PCOS and GDM, it remains unclear whether a definitive causal relationship exists between these two conditions and which specific features of PCOS contribute to increased incidence of GDM.

Methods

The causal relationship between polycystic ovary syndrome (PCOS), its characteristic indices, and gestational diabetes mellitus (GDM) was investigated using a two-sample Mendelian randomization study based on publicly available statistics from genome-wide association studies (GWAS). The inverse-variance weighted method was employed as the primary analytical approach to examine the association between PCOS, its characteristic indices, and GDM. MR Egger intercept was used to assess pleiotropy, while Q values and their corresponding P values were utilized to evaluate heterogeneity. It is important to note that this study adopts a two-sample MR design where PCOS and its characteristic indices are considered as exposures, while GDM is treated as an outcome.

Results

The study results indicate that there is no causal relationship between PCOS and GDM (all methods P > 0.05, 95% CI of OR values passed 1). The IVW OR value was 1.007 with a 95% CI of 0.906 to 1.119 and a P value of 0.904. Moreover, the MR Egger Q value was 8.141 with a P value of 0.701, while the IVW Q value was also 8.141 with a P value of 0.774, indicating no significant heterogeneity. Additionally, the MR Egger intercept was 0.0004, which was close to zero with a P value of 0.988, suggesting no pleiotropy. However, the study did find a causal relationship between several other factors such as testosterone, high-density lipoprotein, sex hormone-binding globulin, body mass index, waist-hip ratio, apolipoprotein A-I, number of children, diabetes illnesses of mother, father and siblings, hemoglobin A1c, fasting insulin, fasting blood glucose, years of schooling, and GDM based on the IVW method.

Conclusion

We observed no association between genetically predicted PCOS and the risk of GDM, implying that PCOS itself does not confer an increased susceptibility to GDM. The presence of other PCOS-related factors such as testosterone, high-density lipoprotein, and sex hormone-binding globulin may elucidate the link between PCOS and GDM. Based on these findings, efforts aimed at preventing GDM in individuals with PCOS should prioritize those exhibiting high-risk features rather than encompassing all women with PCOS.

Pediatric Features of Genetic Predisposition to Polycystic Ovary Syndrome

CONTEXT

Polycystic ovary syndrome (PCOS) has historically been conceptualized as a disorder of the reproductive system in women. However, offspring of women with PCOS begin to show metabolic features of PCOS in childhood, suggestive of childhood manifestations.

OBJECTIVE

To identify childhood manifestations of genetic risk for PCOS.

METHODS

We calculated a PCOS polygenic risk score (PRS) for 12 350 girls and boys in 4 pediatric cohorts-ALSPAC (UK), COPSAC (Denmark), Project Viva (USA), and The HOLBÆK Study (Denmark). We tested for association of the PRS with PCOS-related phenotypes throughout childhood and with age at pubarche and age at peak height velocity and meta-analyzed effects across cohorts using fixed-effect models.

RESULTS

Higher PRS for PCOS was associated with higher body mass index in midchildhood (0.05 kg/m2 increase per 1 SD of PRS, 95% CI 0.03, 0.07, P = 3 × 10-5) and higher risk of obesity in early childhood (OR 1.34, 95% CI 1.13, 1.59, P = .0009); both persisted through late adolescence (P all ≤.03). Higher PCOS PRS was associated with earlier age at pubarche (0.85-month decrease per 1 SD of PRS, 95% CI -1.44, -0.26, P = .005) and younger age at peak height velocity (0.64-month decrease per 1 SD of PRS, 95% CI -0.94, -0.33, P = 4 × 10-5).

CONCLUSION

Genetic risk factors for PCOS are associated with alterations in metabolic, growth, and developmental traits in childhood. Thus, PCOS may not simply be a condition that affects women of reproductive age but, rather, a possible manifestation of an underlying condition that affects both sexes starting in early life.

Psoriasis and gut microbiota: A Mendelian randomization study

In recent years, an increasing number of observational studies have revealed an association between gut microbiota composition and psoriasis patients. However, whether this association reflects a causal relationship remains unclear. This study aimed to identify the causal relationship between gut microbiota and psoriasis through relevant research. In order to determine whether gut microbiota and psoriasis are causally related, we conducted a Mendelian randomization analysis using summary statistics from genome-wide association studies (GWAS). As the exposure factor, we used summary statistics data from a GWAS study conducted by the MiBioGen Consortium, including 18,340 individuals with whole-genome gut microbiota composition, and data from the FinnGen GWAS study on psoriasis, including 9267 patients and 364,071 controls as the disease outcome. Two-sample Mendelian randomization analysis was subsequently performed with inverse variance weighted, MR-Egger and weighted median, while sensitivity analyses were conducted to address heterogeneity and horizontal pleiotropy. The IVW results confirmed the causal relationship between certain gut microbiota groups and psoriasis. Specifically, family Veillonellaceae (OR = 1.162, 95% CI: 1.038-1.301, p = 0.009), genus Candidatus Soleaferrea (OR = 1.123, 95% CI: 1.011-1.247, p = 0.030) and genus Eubacterium fissicatena group (OR = 0.831, 95% CI: 0.755-0.915, p = 0.00016) showed significant associations. Sensitivity analysis did not reveal any abnormalities in SNPs. Currently, we have found some causal relationship between the gut microbiota and psoriasis. However, the study needs further RCTs for further validation.

Genetically predicted 486 blood metabolites concerning risk of systemic lupus erythematosus: a Mendelian randomization study

Metabolic abnormalities constitute a significant characteristic of systemic lupus erythematosus (SLE). We utilised a two-sample Mendelian randomisation (MR) study to evaluate the potential causal association between 486 blood metabolites and SLE. Exposure data at the metabolite level were extracted from 7824 European Genome-wide association studies (GWAS). Preliminary analysis utilised SLE GWAS data from FinnGen. The primary method for causal analysis relied on random inverse variance weighting (IVW). To ensure robustness, sensitivity analyses included the Cochran Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. Steiger testing and linkage disequilibrium score regression were employed to validate the identified metabolites. This study identified 12 metabolites, comprising six known chemical structures: 1,5-anhydroglucitol(1,5-AG) [odds ratio (OR) = 0.100, 95% confidence interval (CI): 0.015-0.773, P = 0.027), gamma-glutamylthreonine (OR = 0.077, 95% CI: 0.010-0.574, P = 0.012), 5-dodecenoate(12:1n7) (OR = 0.205, 95% CI: 0.061-0.685, P = 0.010), linoleoylglycerophosphoethanolamine * (OR = 0.159, 95% CI: 0.027-0.933, P = 0.044), erythrose (OR = 88.331,95% CI:1.098-63.214, P = 0.040) and 1-, adrenate (22:4n6) (OR = 9.876, 95% CI: 1.753-55.639, P = 0.001)]. Additionally, we found associations between SLE and six unknown chemical structures: X-06351 (OR = 0.071, 95% CI: 0.006-0.817, P = 0.034), X-10810 (OR = 4.268 95% CI: 1.260-14.459, P = 0.020), X-11412 (OR = 5.418 95% CI: 1.068-27.487, P = 0.041), X-11905 (OR = 0.551, 95%CI: 0.304-0.997, P = 0.049), X-12038 (OR = 0.178 95%CI: 0.032-0.988, P = 0.045), X-12217 (OR = 0.174 95%CI: 0.044-0.680, P = 0.014). This study offers evidence supporting a causal relationship between SLE and 12 circulating metabolites, six of which have known chemical structures and six that remain unidentified. These findings introduce a new perspective for further exploration of SLE mechanisms.

Genetic study of the causal effect of lipid profiles on insomnia risk: a Mendelian randomization trial

OBJECTIVES

In response to the controversy surrounding observational studies of the association between lipid profiles and the risk of insomnia, the aim of this study was to analyze lipid profiles, including triglycerides (TG), apolipoprotein A-1 (ApoA-1), apolipoprotein B (ApoB) and lipoprotein A (LPA), in a European population to further assess the causal relationship between these lipid types and insomnia.

MATERIALS AND METHODS

This study explores the causal effect of lipid profiles on insomnia based on a genome-wide association study (GWAS)-derived public dataset using two-sample and multivariate Mendelian randomization (MVMR) analysis. The main MR analyses used inverse variance weighting (IVW) odds ratio (OR), and the sensitivity analyses included weighted median (WM) and MR‒Egger.

RESULTS

Both MR and MVMR showed that lowering ApoA-1 and LPA levels had causal effects on the risk of insomnia [MR: per 10 units, ApoA-1: OR: 0.7546, 95% CI: 0.6075-0.9372, P = 0.011; LPA: OR: 0.8392, 95% CI: 0.7202-0.9778, P = 0.025; MVMR: per 10 units, ApoA-1: OR: 0.7600, 95% CI: 0.6362-0.9079, P = 0.002; LPA, OR: 0.903, 95% CI: 0.8283-0.9845, P = 0.021]. There were no causal effects of TG or ApoB on insomnia (all P > 0.05). The MR‒Egger intercept test, funnel plot, and IVW methods all suggested an absence of strong directional pleiotropy, and leave-one-out permutation analysis did not detect any single single-nucleotide polymorphism that had a strong influence on the results.

CONCLUSION

Elevated levels of ApoA-1 and LPA were independently and causally associated with the risk of insomnia, suggesting that elevated ApoA-1 and LPA levels may contribute to a reduced risk of insomnia.

Adiposity and lipid metabolism indicators mediate the adverse effect of glucose metabolism indicators on oogenesis and embryogenesis in PCOS women undergoing IVF/ICSI cycles

BACKGROUND

Polycystic ovary syndrome (PCOS) women have high incidences of dyslipidemia, obesity, impaired glucose tolerance (IGT), diabetes, and insulin resistance (IR) and are fragile to female infertility. Obesity and dyslipidemia may be the intermediate biological mechanism for the associations between glucose metabolism dysfunction and abnormal oogenesis and embryogenesis.

METHODS

This retrospective cohort study was performed at a university-affiliated reproductive center. A total of 917 PCOS women aged between 20 and 45 undergoing their first IVF/ICSI embryo transfer cycles from January 2018 to December 2020 were involved. Associations between glucose metabolism indicators, adiposity and lipid metabolism indicators, and IVF/ICSI outcomes were explored using multivariable generalized linear models. Mediation analyses were further performed to examine the potential mediation role of adiposity and lipid metabolism indicators.

RESULTS

Significant dose-dependent relationships were found between glucose metabolism indicators and IVF/ICSI early reproductive outcomes and between glucose metabolism indicators and adiposity and lipid metabolism indicators (all P < 0.05). Also, we found significant dose-dependent relationships between adiposity and lipid metabolism indicators and IVF/ICSI early reproductive outcomes (all P < 0.05). The mediation analysis indicated that elevated FPG, 2hPG, FPI, 2hPI, HbA1c, and HOMA2-IR were significantly associated with decreased retrieved oocyte count, MII oocyte count, normally fertilized zygote count, normally cleaved embryo count, high-quality embryo count, or blastocyst formation count after controlling for adiposity and lipid metabolism indicators. Serum TG mediated 6.0-31.0% of the associations; serum TC mediated 6.1-10.8% of the associations; serum HDL-C mediated 9.4-43.6% of the associations; serum LDL-C mediated 4.2-18.2% of the associations; and BMI mediated 26.7-97.7% of the associations.

CONCLUSIONS

Adiposity and lipid metabolism indicators (i.e., serum TG, serum TC, serum HDL-C, serum LDL-C, and BMI) are significant mediators of the effect of glucose metabolism indicators on IVF/ICSI early reproductive outcomes in PCOS women, indicating the importance of preconception glucose and lipid management and the dynamic equilibrium of glucose and lipid metabolism in PCOS women.

Maternal Preconception Glucose Homeostasis and Insulin Resistance Are Associated with Singleton and Twin Birthweight of Neonates Conceived by PCOS Women Undergoing IVF/ICSI Cycles

Polycystic ovary syndrome (PCOS) can induce fertility and metabolism disorders, which may increase the prevalence of glucose metabolism disorders and cause health hazards to women and their offspring. We aim to evaluate the effect of maternal preconception glucose metabolism on neonatal birthweight in PCOS women undergoing IVF/ICSI cycles. We retrospectively analyzed 269 PCOS women who delivered 190 singletons and 79 twins via IVF/ICSI at a reproductive center. The effects of maternal preconception glucose metabolism indicators on singleton and twin birthweight were evaluated using generalized linear models and generalized estimate equations, respectively. The potential nonlinear associations were evaluated using generalized additive models. The analyses were further stratified by maternal preconception BMI and delivery mode to evaluate the possible interaction effects. Among PCOS women, maternal preconception fasting plasma glucose (FPG) and glycohemoglobin (HbA1c) had significant negative associations with singleton birthweight (all p for trends = 0.04). We also found an overweight-specific association between elevated maternal preconception 2 h plasma insulin (2hPI) and twin birthweight (p for interactions = 0.05) and a caesarean-specific association between maternal preconception HbA1c and singleton birthweight (p for interactions = 0.02) in PCOS women. Maternal preconception glucose metabolism may affect neonatal birthweight, suggesting the importance of preconception glucose and insulin management for PCOS women. Further large prospective cohorts and animal studies are needed to confirm these findings and investigate the potential mechanisms.

Elevated serum uric acid level is associated with adverse reproductive outcomes in women with polycystic ovary syndrome undergoing in vitro fertilization or intracytoplasmic sperm injection embryo transfer cycles: a retrospective cohort study

BACKGROUND

Serum uric acid levels are elevated in polycystic ovary syndrome, however, the relationship between serum uric acid level and reproductive outcomes in women with polycystic ovary syndrome remains unclear.

OBJECTIVE

This study aimed to investigate the association between serum uric acid level and the reproductive outcomes in women with polycystic ovary syndrome undergoing in vitro fertilization or intracytoplasmic sperm injection embryo transfer cycles.

STUDY DESIGN

This was a retrospective cohort study performed at a university-affiliated reproductive medicine center. A total of 1903 women with polycystic ovary syndrome undergoing their first in vitro fertilization or intracytoplasmic sperm injection embryo transfer cycles between January 2010 and January 2021 were initially included. The trends for reproductive outcomes in polycystic ovary syndrome across quartiles of serum uric acid levels were assessed. A logistic regression analysis was performed to obtain the odds ratios for in vitro fertilization outcomes based on the quartiles of serum uric acid with or without adjusting for potential confounding variables. Using generalized additive models, serum uric acid was further treated as its original continuous property to visualize its nonlinear relationship with in vitro fertilization outcomes. The live birth rate was the main outcome.

RESULTS

After exclusions, a total of 883 women with polycystic ovary syndrome with their first fresh-embryo transfer cycles were included. In quartiles of serum uric acid levels, there was a significant decreasing trend in the live birth rate from the lowest quartile (Q1: 61.8%) to the highest (Q4: 45.9%) (P_trend=.002). The percentage of low birthweight increased from Q1 (22.3%) to Q4 (31.7%) (P_trend=.049). Compared with those in Q1, women in Q4 showed a significant lower probability of live birth and clinical pregnancy and a higher risk for low birthweight (all P<.05). Both the unadjusted and adjusted generalized additive models indicated that as the serum uric acid level increased, the probability of clinical pregnancy and the live birth rate exhibited an overall decreasing profile, and the risk for low birthweight showed an increasing profile.

CONCLUSION

An elevated serum uric acid level is associated with decreased probabilities of live birth and clinical pregnancy and an increased risk for low birthweight in women with polycystic ovary syndrome. However, these associations may be confounded by other factors and more well-designed studies are needed to confirm these findings in the future.

Recent advances in emerging PCOS therapies

Polycystic ovary syndrome is a prevalent endocrinopathy involving androgen excess, and anovulatory infertility. The disorder is also associated with many comorbidities such as obesity and hyperinsulinemia, and an increased risk of cardiovascular complications. Reproductive, endocrine, and metabolic symptoms are highly variable, with heterogenous phenotypes adding complexity to clinical management of symptoms. This review highlights recent findings regarding emerging therapies for treating polycystic ovary syndrome, including i) pharmacological agents to target androgen excess, ii) modulation of kisspeptin signalling to target central neuroendocrine dysregulation, and iii) novel insulin sensitisers to combat peripheral metabolic dysfunction.

Identification of the six-hormone secretion-related gene signature as a prognostic biomarker for colon adenocarcinoma

BACKGROUND

Colon adenocarcinoma (COAD) is a globally prevalent cancer, with hormone secretion playing a crucial role in its progression. Despite this, there is limited understanding of the impact of hormone secretion on COAD prognosis. This study aimed to establish a prognostic signature based on hormone secretion-related genes and to elucidate the potential functional mechanisms of these genes in COAD.

METHODS

Using data from The Cancer Genome Atlas COAD cohort (TCGA-COAD), six hormone secretion-related genes were identified (CYP19A1, FOXD1, GRP, INHBB, SPP1, and UCN). These genes were used to develop a Hormone secretion score (HSS), which was then evaluated using the Kaplan-Meier curve and multivariable Cox analysis. The HSS model was further validated with external GEO cohorts (GSE41258, GSE39582, and GSE87211). Functional enrichment analyses were performed, and the CIBERSORT and TIDE algorithms were used to assess tumor infiltration.

RESULTS

The study developed a prognostic signature, dividing patients into HSS-high and HSS-low groups. The HSS-high group showed a notably worse prognosis within the TCGA-COAD dataset and in three independent datasets: GSE41258, GSE39582, and GSE87211. Moreover, the HSS-high group predicted a shorter overall survival rate in patients maintaining microsatellite stability (MSS). The functional analysis associated HSS-high with the hypoxic, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathways and correlated with distant and lymph node metastases. The tumor immune microenvironment analysis revealed an elevated CIBERSORT score in the HSS-high group, suggesting an association with tumor metastasis. Further, the HSS-high group showed a higher TIDE score, indicating that patients with high HSS scores are less likely to benefit from Immune Checkpoint Inhibitor (ICI) therapy.

CONCLUSIONS

This study demonstrated the prognostic significance of a HSS signature based on six hormone secretion-related genes in COAD. The findings suggest that this gene signature may serve as a reliable biomarker for predicting survival outcomes in COAD patients.