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

Causal Associations of 33 Health Examination Indicators and Colorectal Cancer in European and East Asian Populations: A Mendelian Randomization Analysis

Background: Colorectal cancer (CRC) is a significant cause of cancer-related mortality worldwide. While many health examination indicators might be associated with CRC, their causal relationships remain unclear. The authors analyzed their causal relationship in European and East Asian populations. Methods: The authors collected the genome-wide association data for 33 clinical indicators and CRC in European and East Asian populations from the IEU OpenGWAS project and Riken's Japanese Genetic Association Database. These indicators include 13 hematological indicators, 7 liver function indicators, 2 kidney function indicators, 5 lipid metabolism indicators, 2 glucose metabolism indicators, 1 electrolyte indicator, and 3 comorbidity indicators. The authors performed univariate (UV) and multivariate (MV) Mendelian randomization (MR) analyses on the European and East Asian populations and followed a meta-analysis. Results: UVMR analysis identified 11 indicators (white blood cell count [WBC], mean corpuscular hemoglobin [MCH], mean corpuscular hemoglobin concentration, mean corpuscular volume [MCV], platelet count [Plt], C-reactive protein [CRP], total protein [TP], aspartate aminotransferase [AST], total cholesterol [TC], low-density lipoprotein cholesterol, and apolipoprotein B) with significant causal relationships (p < 0.05). Notably, AST, TC, glycated hemoglobin, and serum creatinine showed inverted causal relationships in different populations. After MV adjustment for TC and TP, MCH (odds ratio [OR]EU = 1.0012, 1.0000 to 1.0024; ORmeta = 1.0012, 1.0001 to 1.0024), Plt (OREU = 0.9986, 0.9974 to 0.9998; ORmeta = 0.9986, 0.9974 to 0.9998), and CRP (OREU = 0.9981, 0.9965 to 0.9998; ORmeta = 0.9981, 0.9965 to 0.9998) were independent influencing indicators in European and Eurasian populations, whereas WBC (OREAS = 0.8316, 0.7005 to 0.9871), MCH (OREAS = 1.2430, 1.1132 to 1.3879), and MCV (OREAS = 1.0012, 1.0001 to 1.0024) were independent influencing indicators in the East Asian population. Conclusion: The causal relationship between MCH, TP, and Plt and CRC has been discovered for the first time. Furthermore, TC and CRP were also independent influencing indicators. These findings offer beneficial referential value for the enhancement of preliminary screening protocols for CRC.

Metabolic Profiles of Pregnancy With Polycystic Ovary Syndrome: Insights into Maternal-Fetal Metabolic Communication

CONTEXT

Polycystic ovary syndrome (PCOS) pregnancies are linked to metabolic disorders affecting maternal and fetal outcomes, with maternal metabolites differing from those in normal pregnancies.

OBJECTIVE

To investigate the metabolic communication at the maternal-fetal interface in PCOS pregnancies.

DESIGN

Placenta and umbilical cord serum were analyzed using gas chromatography-mass spectrometry. In-depth analysis was performed with clinical characteristics.

SETTING

Placenta and umbilical cord serum were analyzed using gas chromatography-mass spectrometry, alongside clinical characteristics.

PARTICIPANTS

Forty-five uncomplicated PCOS pregnancies and 50 normal pregnancies.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

The metabolic characteristics at the maternal-fetal interface in PCOS pregnancies and the underlying mechanisms.

RESULTS

A total of 79 metabolites in the placenta and 25 in umbilical cord serum showed significant differences between PCOS and normal pregnancies. The 10 most significant placental metabolites were identified through receiver operating characteristic analysis, 9 of which correlated significantly with maternal serum testosterone levels. Lasso regression analysis identified 4 key placental metabolite combinations: gamma-aminobutyric acid, proline, glycine, and isoleucine, achieving an area under the curve of 93.24%. In umbilical cord serum, 6 metabolites differed significantly between PCOS and normal pregnancies, with the highest area under the curve reaching 76.07%; 5 of these metabolites showed significant correlations with maternal serum testosterone levels. Nine differential metabolites were shared between the placenta and umbilical cord serum, which also shared metabolic pathways, including ABC transporters and aminoacyl-tRNA biosynthesis, potentially influencing maternal-fetal interactions.

CONCLUSION

This study identifies the metabolomic profile and key pathways in maternal-fetal communication during PCOS pregnancies.

Insights into modifiable risk factors of retinal vascular occlusion: A Mendelian randomization study

Understanding the etiological risk factors for retinal vascular occlusion (RVO) is critical for prevention and treatment. While the effects of cardiovascular events, hypertension, glaucoma, obesity and glycemic risk factors on RVO are still controversial. This study employed two-sample Mendelian randomization (MR) analysis to investigate these causal risk factors. Single-nucleotide polymorphisms (SNPs) were used as instrumental variables (IVs). Genetic instruments for hypertension, glaucoma, obesity, cardiovascular events and glycemic risk factors were obtained from published genome-wide association studies (GWASs). Summary-level data for RVO and hypertension were obtained from the FinnGen consortium. MR analysis primarily utilized the inverse variance weighted (IVW) method, with MR-Egger and weighted median as supplementary approaches. Multivariable MR (MVMR) adjusting for hypertension or glaucoma of RVO were conducted. Heterogeneity was assessed using Cochrane's Q test and I2, while MR-Egger intercept and MR-PRESSO tested horizontal pleiotropy. All MR analyses were performed within R software (4.1.3) using the R packages "TwoSampleMR" and "MR-PRESSO." Genetic instruments for hypertension and glaucoma were significantly associated with RVO risk. A one-standard deviation (SD) increase in hypertension was associated with a higher risk of RVO [OR = 1.577, 95% CI = (1.342, 1.854), P < .001], while a one-SD increase in the log odds of genetically predicted glaucoma was associated with a higher risk of RVO [OR = 1.24, 95% CI = (1.115, 1.379), P < .001]. Meanwhile, hypertension and glaucoma were still significant in multivariable MR. There was not sufficient evidence to suggest cardiovascular events and obesity were associated with RVO risk. This MR study provided genetic evidence supporting that hypertension and glaucoma were causally associated with the risk of RVO. It may help guide clinical decisions in the management of RVO patients with hypertension and glaucoma.

Multi-omics analysis to explore the molecular mechanisms related to keloid

BACKGROUND

Keloid is a benign skin tumor that result from abnormal wound healing and excessive collagen deposition. The pathogenesis is believed to be linked to genetic predisposition and immune imbalance, although the precise mechanisms remain poorly understood. Current therapeutic approaches may not consistently yield satisfactory outcomes and are often accompanied by potential side effects and risks. The high recurrence rate and refractory nature of keloid nodules present significant challenges and uncertainties in their management. Given the lack of effective treatment strategies, it is essential to identify key molecular pathways and potential therapeutic targets for keloid.

OBJECTIVE

This study aimed to identify the potential pathogenic mechanisms, hub genes, and immune cell involvement in keloid formation, with the goal of providing novel insights for targeted therapies.

METHODS

We utilized a combination of bulk RNA sequencing to analyze gene expression profiles in keloid tissues. Differentially expressed genes (DEGs) were identified and subjected to pathway enrichment analysis to reveal key biological processes involved in keloid pathogenesis. Mendelian randomization was performed to investigate the causal relationship between genetic factors and keloid formation, identifying potential hub genes. Immune infiltration analysis was conducted to determine the role of specific immune cells in keloid development. Subsequently, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed to investigate the functional pathways associated with the hub genes. Network analysis was employed to identify transcription factors, miRNAs, and potential drugs in the Connectivity Map associated with the hub genes. Single-cell RNA sequencing was also used to identify cell-specific expression patterns of these genes.

RESULTS

Pathway enrichment analysis highlighted the association of keloid pathogenesis with cell proliferation and division, providing insights into the molecular processes involved. Mendelian randomization revealed that DUSP1 acts as an inhibitor of keloid formation, while HOXA5 promotes keloid pathogenesis. Immune infiltration analysis suggested that mast cells and macrophages play critical roles in the disease's progression. Based on hub gene analysis, the IL17 signaling pathway emerged as a key pathway implicated in keloid development. Further drug prediction models identified 9-methyl-5H-6-thia-4, 5-diaza-chrysene-6, 6-dioxide, zebularine, temozolomide and valproic acid targeting these hub genes.

CONCLUSION

DUSP1 and HOXA5 are hub genes in keloid pathogenesis, with DUSP1 acting as an inhibitor and HOXA5 as a promoter of disease progression. Targeting the regulatory networks associated with these genes could provide novel therapeutic strategies. Mast cells and macrophages are identified as critical immune cell types involved in the disease process. Additionally, the IL17 signaling pathway plays a crucial role in keloid development, highlighting its potential as a therapeutic target. These findings suggest that a multi-target approach focusing on these pathways could offer effective treatment options for keloid patients.

Multiomics and Systematic Analyses Reveal the Roles of Hemoglobin and the HIF-1 Pathway in Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) affects reproductive and cardiometabolic health, yet its pathogenesis remains unclear. Emerging evidence links hemoglobin levels to metabolic disorders, suggesting a potential role in PCOS development. Here, we integrated a large-scale cohort study, Mendelian randomization (A genetic tool to infer causal relationships), bioinformatics analyses, and in vitro experiments to investigate the relationship between hemoglobin levels and PCOS. In a cohort of 20 602 women, each 10 g L-1 elevation in hemoglobin levels is associated with 22% higher odds of PCOS (adjusted odds ratio: 1.22, 95% confidence interval: 1.15-1.29, P < 0.001) and PCOS manifestations, particularly hyperandrogenism. Mendelian randomization analysis confirms that higher hemoglobin levels are associated with increased PCOS risk and elevated testosterone levels. The hypoxia-inducible factor 1 (HIF-1) pathway is enriched, identifying three testosterone-associated genes (nuclear factor kappa B (NFKB1), insulin receptor (INSR), protein kinase C alpha. Colocalization and druggability analysis supports shared genetic regions and confirmed these genes as druggable targets. Upregulation of NFKB1 and INSR are confirmed in both blood and ovarian granulosa cells of PCOS patients. The findings demonstrate that higher-end normal hemoglobin levels are associated with increased PCOS risk, potentially through a mechanism of elevating testosterone levels involving the HIF-1 pathway.

Caloric restriction prevents inheritance of polycystic ovary syndrome through oocyte-mediated DNA methylation reprogramming

Polycystic ovary syndrome (PCOS) is a prevalent metabolic and reproductive endocrine disorder with strong heritability. However, the independent role of oocytes in mediating this heritability remains unclear. Utilizing in vitro fertilization-embryo transfer and surrogacy, we demonstrated that oocytes from androgen-exposed mice (F1) transmitted PCOS-like traits to F2 and F3 generations. Notably, caloric restriction (CR) in F1 or F2 effectively prevented this transmission by restoring disrupted DNA methylation in oocyte genes related to insulin secretion and AMPK signaling pathways. Further detection in adult tissues of offspring revealed dysregulated DNA methylation and expression of those genes (e.g., Adcy3, Gnas, and Srebf1) were reversed by maternal CR. Moreover, similar benefits of CR were observed in aberrant embryonic methylome of women with PCOS. These findings elucidate the essential role of CR in preventing PCOS transmission via methylation reprogramming, emphasizing the importance of preconception metabolic management for women with PCOS.

Menstrual disorder is associated with blood type in PCOS patients: evidence from a cross-sectional survey

BACKGROUND

Previous studies have shown a correlation between ABO blood type and the occurrence of certain diseases. However, there is limited research on the potential association between ABO blood group and polycystic ovary syndrome (PCOS). This study aims to investigate the potential connection between ABO blood type and the regularity of menstrual cycles, menstrual bleeding level, and additional metabolic indicators among individuals diagnosed with PCOS.

METHODS

This cross-sectional study involved 312 PCOS patients and 133 healthy controls whose menstruation and blood type were investigated by questionnaires. Their blood lipid content and hormone levels were also measured. We assessed the association between ABO blood type distribution in different groups and the occurrence of menstrual conditions in PCOS patients.

RESULTS

445 women participated in the study. There was a statistically significant difference in ABO blood type distribution among PCOS patients with varying menstrual levels (P = 0.036). Compared with other blood type groups, PCOS patients with blood type O exhibited statistically significant differences in BMI (P = 0.033), E2 levels (P < 0.001), LH levels (P = 0.022), and FSH levels (P < 0.001), and showed a higher tendency towards greater menstrual bleeding.

CONCLUSION

There exists a correlation between ABO blood type and menstrual bleeding level among PCOS patients. In particular, individuals with blood type O display a heightened likelihood of experiencing greater menstrual bleeding with more favorable endocrine status compared to non-O blood types in the population.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT04264832 ( https://clinicaltrials.gov ). Registered on February 7, 2020.

Single-cell multi-omics analysis identifies SPP1+ macrophages as key drivers of ferroptosis-mediated fibrosis in ligamentum flavum hypertrophy

BACKGROUND

Ligamentum flavum hypertrophy (LFH) is a primary contributor to lumbar spinal stenosis. However, a thorough understanding of the cellular and molecular mechanisms driving LFH fibrotic progression remains incomplete.

METHODS

Single-cell RNA sequencing (scRNA-seq) was performed to construct the single-cell map of human ligamentum flavum (LF) samples. An integrated multi-omics approach, encompassing scRNA-seq, bulk RNA sequencing (bulk RNA-seq), and Mendelian randomization (MR), was applied to conduct comprehensive functional analysis. Clinical tissue specimens and animal models were employed to further confirm the multi-omics findings.

RESULTS

ScRNA-seq provided a single-cell level view of the fibrotic microenvironment in LF, revealing significantly increased proportions of fibroblasts, myofibroblasts, and macrophages in LFH. Using transmission electron microscopy, single-cell gene set scoring, and MR analysis, ferroptosis was identified as a critical risk factor and pathway within LFH. Subcluster analysis of fibroblasts revealed functional heterogeneity among distinct subpopulations, highlighting the functional characteristics and the metabolic dynamics of fibroblast with a high ferroptosis score (High Ferro-score FB). The quantification of gene expression at single-cell level revealed that ferroptosis increased along with fibrosis in LFH specimens, a finding further validated in both human and mice tissue sections. Consistently, bulk RNA-seq confirmed increased proportions of fibroblasts and macrophages in LFH specimens, underscoring a strong correlation between these cell types through Spearman correlation analysis. Notably, subcluster analysis of the mononuclear phagocytes identified a specific subset of SPP1+ macrophages (SPP1+ Mac) enriched in LFH, which exhibited activation of fibrosis and ferroptosis-related metabolic pathways. Cell-cell communication analysis highlighted that SPP1+ Mac exhibited the strongest outgoing and incoming interactions among mononuclear phagocytes in the LFH microenvironment. Ligand-receptor analysis further revealed that the SPP1-CD44 axis could serve as a key mediator regulating the activity of High Ferro-score FB. Multiplex immunofluorescence confirmed substantial Collagen I deposition and reduced Ferritin Light Chain expression in regions with SPP1-CD44 co-localization in LFH specimens.

CONCLUSIONS

Our findings indicated that SPP1+ Mac may contribute to LFH fibrosis by regulating ferroptosis in High Ferro-score FB through the SPP1-CD44 axis. This study enhances our understanding of the cellular and molecular mechanisms underlying LFH progression, potentially improving early diagnostic strategies and identifying new therapeutic targets.

Anti-Müllerian hormone regulates ovarian granulosa cell growth in PCOS rats through SMAD4

OBJECTIVE

Polycystic ovary syndrome (PCOS) is a diverse condition with an unknown cause. The precise mechanism underlying ovulatory abnormalities in PCOS remains unclear. It is widely believed that malfunction of granulosa cells is the primary factor contributing to aberrant follicular formation in PCOS.

METHODS

A DHEA-induced PCOS rat model was established, and ovarian granulosa cells were extracted and identified. Anti-Müllerian hormone (AMH) and SMAD family member 4 (SMAD4) expression was detected in the serum, ovarian tissue and ovarian granulosa cells of each group, and proliferating cell nuclear antigen (PCNA), BCL2-associated 2 (BAX), cleaved caspase-3 and BCL-2 protein expression was detected by Western blot in ovarian granulosa cells. Recombinant anti-Müllerian hormone (rAMH) was administered at different concentrations to act on normal rat ovarian granulosa cells, cell proliferation was detected by cell counting kit-8 (CCK-8), apoptosis was detected by flow cytometry, and SMAD4, caspase-3, BCL-2 and cyclin A proteins were detected by Western blot. SMAD4-siRNA was transfected into rat ovarian granulosa cells of the PCOS group, and PCNA and BAX were detected by Western blot.

RESULTS

Compared with those in the control group, the expression of AMH and SMAD4 was increased in the ovarian tissues and granulosa cells of rats in the PCOS group, the expression of PCNA and BCL-2 proteins was decreased in the ovarian granulosa cells of the PCOS group, the expression of BAX proteins was increased, and the expression of cleaved caspase-3 was increased. Western blot results indicated that rAMH upregulated SMAD4 and caspase-3 protein expression in granulosa cells and downregulated cyclin A and BCL-2 protein expression. CCK-8 and flow cytometry results indicated that AMH decreased granulosa cells proliferation and increased apoptosis. SiRNA knockdown of SMAD4 gene increased PCNA and BCL-2 protein expression in the granulosa cells of PCOS rats and decreased BAX and cleaved caspase-3 protein expression.

CONCLUSION

AMH may be involved in regulating impaired ovarian granulosa cells development in PCOS rats via SMAD4.

Causal relationship between IgA nephropathy and common neuropsychiatric disorders: A two-sample Mendelian randomization analysis

OBJECTIVE

Utilizing two-sample Mendelian randomization (TSMR), this study seeks to determine the causal relationship between IgA nephropathy and five prevalent neuropsychiatric disorders. By exploring the genetic associations between IgA nephropathy and neuropsychiatric disorders, this research aims to contribute to the prevention of neuropsychiatric disorders in patients with IgA nephropathy.

METHODS

Public genome-wide association study databases were searched, with IgA nephropathy as the exposure factor, including 15,587 patients with IgA nephropathy and 462,197 healthy controls. The outcome factors were five common neuropsychiatric disorders (bipolar disorder, depressive disorder, schizophrenia, anorexia nervosa, and Alzheimer's disease), with outcome data drawn from five datasets in the PGC and GWAScatalog databases. Inverse-variance weighting served as the primary method for causal effect estimation, supplemented by MR-Egger, weighted median, weighted mode, and simple mode methods. Heterogeneity was tested using Cochran's Q test, and sensitivity analysis was conducted using MR-Egger and MR-presso.

RESULTS

MR analysis indicated a positive causal relationship between IgA nephropathy and depressive disorder (OR = 1.010, 95%CI: 1.003-1.017, P = 3.27 × 10-3), and a potential positive causal relationship between IgA nephropathy and anorexia nervosa (OR = 1.165, 95%CI: 1.030-1.319, P = 0.015).

CONCLUSION

There is a positive causal relationship between IgA nephropathy and depressive disorder, and a potential positive causal relationship with anorexia nervosa. No causal relationship was found with schizophrenia, bipolar disorder, or Alzheimer's disease.

Causal relationship between dyslipidemia and diabetic neuropathy: a mendelian randomization study

Some studies have shown an association between dyslipidemia and diabetic neuropathy (DN), but the genetic association has not been clarified. Therefore, the present study aimed to investigate the genetic causal association between dyslipidemia and DN through a Mendelian randomization (MR) approach. Genetic causal associations between total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL) and DN were investigated by MR to provide a basis for the prevention and treatment of DN. Significant and independent single-nucleotide polymorphisms (SNPs) identified in genome-wide association studies were selected as instrumental variables (IVs) for MR analysis. Inverse variance weighted (IVW), MR‒Egger regression, weighted median (WME), simple mode (SM), and weighted mode (WM) methods were used to analyze causal associations. Heterogeneity and multiplicity tests were also performed and analyzed using the leave-one-out method to assess the stability of the results. Genetically predicted TC and DN (OR = 0.793, 95% CI = 0.655⁓0.961, P = 0.019) and LDL and DN (OR = 0.842, 95% CI = 0.711⁓0.998, P = 0.049) may be causally associated, but no causal associations were found between TG and DN (OR = 0.837, 95% CI = 0.631⁓1.111, P = 0.221) or between HDL and DN (OR = 1.192, 95% CI = 0.940⁓1.510, P = 0.149). TC and LDL may have genetic causal associations with DN, though no genetic causal associations were found for TG or HDL with DN. However, this study may have several limitations, and further clinical studies are needed to expand the sample size for future validation.

Logistic regression analysis of risk factors for anxiety and depression in patients with coronary heart disease and subclinical hypothyroidism

We sought to explore the risk factors for anxiety and depression in patients with coronary heart disease and subclinical hypothyroidism through logistic regression analysis. A retrospective analysis was conducted on 168 patients with coronary heart disease and subclinical hypothyroidism admitted to the Department of Cardiology of our hospital from February 2020 to November 2022. Patients were categorized into the control group, anxiety group, and depression group based on the Hamilton Anxiety Scale (HAMA) and Hamilton Depression Rating Scale (HAMD) scores. All participants were informed about the protocol and provided signed informed consent upon inclusion. The study examined influencing factors for anxiety and depression in patients with coronary heart disease and subclinical hypothyroidism. Collect patients' gender, age, presence or absence of chronic diseases (including Diabetes, hypertension and hyperthyroidism), sleep quality, dietary habits, psychosocial stress, living environment, social support, education level, and blood TSH levels. The linear relationship between anxiety, depression, and each influencing factor was quantified using the Pearson correlation coefficient. Blood level of TSH and free T4 were detected by chemiluminescence immunoassay. Multiple logistic regression was applied to analyze the factors influencing anxiety and depression in these patients. Various factors were identified as significant influencers of anxiety and depression in patients with coronary heart disease and subclinical hypothyroidism. For anxiety, presence or absence of chronic diseases, sleep quality, dietary habits, psychosocial pressure, living environment, and blood TSH levels were found to be influential (P < 0.05). Similarly, for depression, presence or absence of chronic diseases, sleep quality, social support, quality of life, social support, education level, and blood TSH levels were identified as significant factors (P < 0.05). The study revealed positive correlations between presence or absence of chronic diseases, psychosocial stress, and TSH levels with anxiety symptoms in patients with coronary heart disease and subclinical hypothyroidism (P < 0.05). Conversely, sleep quality, dietary patterns, and living environment showed negative correlations with anxiety symptoms (P < 0.05).Gender and age had no correlation with anxiety levels (P > 0.05). Presence or absence of chronic diseases and TSH levels were positively correlated with depressive symptoms in patients with coronary heart diseaseand subclinical hypothyroidism (P < 0.05). On the other hand, sleep quality, social support, quality of life, and educational level were negatively correlated with anxiety symptoms (P < 0.05). Gender and age had no correlation with depression (P > 0.05). Notably, TSH levels in both the anxiety and depression groups were higher than those in the control group (P < 0.05), with no significant difference in free T4 levels among the groups (P > 0.05). The combination of chronic illness types, living habits (sleep quality, dietary habits), psychosocial pressure, living environment, and TSH levels emerged as risk factors for anxiety in patients with coronary heart disease and subclinical hypothyroidism (P < 0.05). Similarly, the combination of chronic illness types, sleep quality, social support, quality of life, education level, and TSH levels were identified as risk factors for depression in these patients (P < 0.05). This logistic regression analysis underscores the significant impact of factors such as types of chronic illness, sleep quality, social support, living environment, education level, and TSH levels on anxiety and depression symptoms in patients with coronary heart disease and subclinical hypothyroidism. These findings highlight the importance of considering these multiple risk factors collectively when devising treatment and management strategies to reduce the risk of mental health issues in this patient population.

Physical activities and breast cancer: a Mendelian randomization study

Introduction

Previous research suggests a potential association between physical activity (PA) and breast cancer (BC), but the causal relationship remains uncertain. The aim of this study was to explore the causal relationship between PA and BC through Mendelian randomization (MR) analysis.

Material and methods

Genome-wide association studies utilizing data from the UK Biobank baseline were employed to analyze PA phenotypes, encompassing 460,376 participants. Summary data for BC, comprising 122,977 cases and 105,974 controls, were obtained from the BC Association Consortium. The cases were further categorized based on estrogen receptor status into estrogen receptor-positive breast cancer (ER+ BC) and estrogen receptor-negative breast cancer (ER- BC). The inverse variance weighted method was employed as the primary approach for two-sample MR. Additionally, the MR-PRESSO (MR-Pleiotropy RESidual Sum and Outlier) method was utilized to eliminate outliers. Tests for heterogeneity and pleiotropy were conducted to enhance result accuracy. Furthermore, multivariable Mendelian randomization was performed, adjusting for potential confounders to ensure result stability.

Results

MR analysis was employed to assess the causal link between PA and BC. Two-sample MR analysis revealed a genetic prediction indicating that walking for pleasure was associated with decreased risk of ER+ BC (odds ratio (OR) = 0.302, 95% CI = 0.105-0.872, p = 0.027), while other physical activities were not significantly correlated with BC, ER+ BC and ER- BC. These findings remained reliable and consistent in the sensitivity analysis, including Cochran's Q and MR-Egger regression. Furthermore, reverse MR analysis suggested that BC did not exert a notable impact on PA.

Conclusions

Our findings suggest that engaging in leisure walking is associated with a reduced risk of ER+ BC. Nevertheless, additional research is warranted to comprehensively elucidate the underlying mechanisms and strengthen the causal relationship.

Genetic associations of metabolic factors and therapeutic drug targets with polycystic ovary syndrome

INTRODUCTION

Polycystic ovary syndrome (PCOS) is frequently accompanied with metabolic dysfunctions, yet the causal relationships between metabolic factors and PCOS remain to be conclusively established and etiology-based therapies are lacking.

OBJECTIVES

To comprehensively identify the metabolic causal factors and potential drug targets for PCOS.

METHODS

This genetic association study was conducted using bidirectional two-sample Mendelian Randomization (MR), multivariable MR (MVMR) and drug-target MR. Considering metabolic sexual dimorphism, female-specific genome-wide association studies (GWASs) for metabolic factors were obtained. To ensure the robustness of the findings, an additional independent PCOS GWAS dataset was utilized for replication.

RESULTS

The PCOS cohort included 10,074 PCOS cases (mean age 28 to 45 years) and 103,164 controls (mean age 27 to 60 years) of European ancestry. All participants were female. Employing two-sample MR analysis, we found that genetically proxied body mass index (BMI) (OR = 3.40 [95 % CI, 2.65-4.36]), triglyceride (TG) (OR = 1.54 [95 % CI, 1.17-2.04]), low-density lipoprotein cholesterol (LDL-c) (OR = 1.37 [95 % CI, 1.07-1.76]), and type 2 diabetes (T2D) (OR = 1.24 [95 % CI, 1.09-1.41]) were significantly associated with an increased risk of PCOS, whereas genetically predicted high-density lipoprotein cholesterol (HDL-c) (OR = 0.61 [95 % CI, 0.47-0.80]) decreased the odds of PCOS. Stepwise MVMR established a hierarchy of interactions among these metabolic factors, identifying BMI and HDL-c as the most prominent causal factors. Notably, drug-target MR analysis identified incretin-based therapeutics, PCSK9 inhibitors, LPL gene therapy, sulfonylureas, and thiazolidinediones as potential therapeutics for PCOS. All these findings were validated in an independent dataset.

CONCLUSION

This study offered insights into the roles of obesity, diabetes, and dyslipidemia in PCOS etiology and therapeutics, underscoring the necessity for managing metabolic health in women and paving the way for tailored therapeutic strategies for PCOS based on its metabolic underpinnings.

No Association of Polycystic Ovary Syndrome with Pancreatic Cancer: A Mendelian Randomization Study

Recently, there has been a debate regarding the association between polycystic ovary syndrome (PCOS) and pancreatic cancer (PC). In order to examine the causal relationship between PCOS and PC, we conducted a Mendelian randomization study, which utilized 12 single nucleotide polymorphisms (SNPs) identified from a genome-wide association study (GWAS) meta-analysis that included 10,074 PCOS cases and 103,164 controls of European ancestry as instrumental variables (IVs). The outcome data were obtained from the FinnGen database (including 605 cases and 218,187 controls). We demonstrate that genetically predicted PCOS is not causally associated with PC risk in Europeans (odds ratio = 0.99, 95% confidence interval (CI) = 0.72-1.36, p > 0.05). Sensitivity analysis showed horizontal pleiotropy (intercept p > 0.05), heterogeneity (Cochran Q p > 0.05), and the leave-one-out sensitivity test showed that individual SNP effects had no influence on the results. In conclusion, our study did not provide evidence of a causal link between PCOS and PC.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-024-00156-y.

Bioinformatics analysis of the role of RNA modification regulators in polycystic ovary syndrome

Purpose

Polycystic ovary syndrome (PCOS) is the most common metabolic and endocrine disorder affecting women of reproductive age. The pathogenesis of PCOS is influenced by factors such as race, genetics, environment, hyperandrogenemia, hyperinsulinemia, and obesity. However, the molecular mechanisms linking RNA modification and PCOS remain underexplored. This study aims to investigate the potential genetic and molecular pathways connecting RNA modification with PCOS through bioinformatics analyses.

Methods

The GSE34526, GSE5850, and GSE98421 datasets were obtained from the National Center for Biotechnology Information Gene Expression Omnibus database. We identified intersecting differentially expressed genes (DEGs) and RNA modification-related genes within the GSE34526 dataset and visualized the overlaps using a Venn diagram. Subsequent analyses included Gene Ontology (GO), pathway enrichment (Kyoto Encyclopedia of Genes and Genomes), gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and immune infiltration analysis. Additionally, we constructed a protein-protein interaction network as well as mRNA-miRNA, mRNA-RNA binding protein, and mRNA-transcription factor (TF) regulatory networks. The expression and receiver operating characteristic curves of hub genes were also identified.

Results

The expression of several RNA modification-related DEGs (RMRDEGs) (ALYREF, NUDT1, AGO2, TET2, YTHDF2, and TRMT61B) showed significant differences in PCOS patients. GSEA and GSVA indicated that RMRDEGs were enriched in the hedgehog, MAPK, JAK STAT, and Notch pathways. Key transcription factors, including SP7, KLF8, HCFC1, IRF1, and MLLT1, were identified in the TF regulatory networks.

Conclusions

These findings suggest that there are gene and miRNA profile alterations exist in PCOS patients and highlight immune-related differences. This knowledge could pave the way for new research directions in the diagnosis and treatment of PCOS.

Elucidating the role of hepatic enzymes in spontaneous abortion: a Mendelian randomization approach

Background

While the hepatic enzymes Aspartate Aminotransferase (AST) and Alanine Aminotransferase (ALT) are crucial for liver function, their role in Spontaneous Abortion (SA) has not been thoroughly explored. Utilizing Mendelian Randomization (MR), this study aims to clarify the putative causal relationship between AST/ALT levels and SA.

Methods

Genome-wide association study (GWAS) summary data for SA (finn-b-O15_ABORT_SPONTAN), AST (ukb-d-30650_raw), and ALT (ukb-d-30620_raw) were acquired from the Integrative Epidemiology Unit OpenGWAS database. Bidirectional MR analysis was conducted using MR-Egger, Weighted Median, Simple Mode, Weighted Mode, and Inverse Variance Weighted (IVW) algorithms, and the robustness of MR results was assessed through sensitivity analyses including Heterogeneity, Horizontal Pleiotropy, and Leave-One-Out (LOO) tests. The causal role of AST and ALT's coaction in SA was explored via multivariable MR (MVMR) analysis.

Results

The MR results via the IVW algorithm revealed a causal relation between both AST and ALT and SA (AST: P = 0.013; ALT: P = 0.017), identifying them as risk factors for SA (AST: odd ratio (OR) = 1.019; ALT: OR = 1.012). Sensitivity analysis substantiated the reliability of these results. Moreover, not notably causality was found between SA and AST/ALT (P > 0.05). Through MVMR analysis, AST and ALT demonstrated functional complementarity in the occurrence of SA, attributable to counterbalanced causalities (AST: P = 0.128; ALT: P = 0.899).

Conclusion

The study substantiates a causal linkage between transaminase levels and SA, enhancing our understanding of their biological interaction and the regulatory mechanisms at play. These insights could have implications for identifying novel biomarkers and therapeutic targets for SA.

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.