Causal association of immune cells and polycystic ovarian syndrome: a Mendelian randomization study

Background

Polycystic ovarian syndrome (PCOS) is a common reproductive disorder that affects a considerable number of women worldwide. It is accompanied by irregular menstruation, hyperandrogenism, metabolic abnormalities, reproductive disorders and other clinical symptoms, which seriously endangers women's physical and mental health. The etiology and pathogenesis of PCOS are not completely clear, but it is hypothesized that immune system may play a key role in it. However, previous studies investigating the connection between immune cells and PCOS have produced conflicting results.

Methods

Mendelian randomization (MR) is a powerful study design that uses genetic variants as instrumental variables to enable examination of the causal effect of an exposure on an outcome in observational data. In this study, we utilized a comprehensive two-sample MR analysis to examine the causal link between 731 immune cells and PCOS. We employed complementary MR methods, such as the inverse-variance weighted (IVW) method, and conducted sensitivity analyses to evaluate the reliability of the outcomes.

Results

Four immunophenotypes were identified to be significantly associated with PCOS risk: Memory B cell AC (IVW: OR [95%]: 1.123[1.040 to 1.213], p = 0.003), CD39+ CD4+ %CD4+ (IVW: OR [95%]: 0.869[0.784 to 0.963], p = 0.008), CD20 on CD20- CD38-(IVW: OR [95%]:1.297[1.088 to 1.546], p = 0.004), and HLA DR on CD14- CD16+ monocyte (IVW: OR [95%]:1.225[1.074 to 1.397], p = 0.003). The results of the sensitivity analyses were consistent with the main findings.

Conclusions

Our MR analysis provides strong evidence supporting a causal association between immune cells and the susceptibility of PCOS. This discovery can assist in clinical decision-making regarding disease prognosis and treatment options, and also provides a new direction for drug development.

Modulation of the Inflammatory Response in Polycystic Ovary Syndrome (PCOS)-Searching for Epigenetic Factors

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. Despite its incidence, the syndrome is poorly understood and remains underdiagnosed, and female patients are diagnosed with a delay. The heterogenous nature of this complex disorder results from the combined occurrence of genetic, environmental, endocrine, and behavioral factors. Primary clinical manifestations of PCOS are derived from the excess of androgens (anovulation, polycystic ovary morphology, lack of or scanty, irregular menstrual periods, acne and hirsutism), whereas the secondary manifestations include multiple metabolic, cardiovascular, and psychological disorders. Dietary and lifestyle factors play important roles in the development and course of PCOS, which suggests strong epigenetic and environmental influences. Many studies have shown a strong association between PCOS and chronic, low-grade inflammation both in the ovarian tissue and throughout the body. In the vast majority of PCOS patients, elevated values of inflammatory markers or their gene markers have been reported. Development of the vicious cycle of the chronic inflammatory state in PCOS is additionally stimulated by hyperinsulinemia and obesity. Changes in DNA methylation, histone acetylation and noncoding RNA levels are presented in this review in the context of oxidative stress, reactive oxygen species, and inflammatory signaling in PCOS. Epigenetic modulation of androgenic activity in response to inflammatory signaling is also discussed.

Effect of Blood Homocysteine on the Outcome of Artificial Insemination in Women with Polycystic Ovary Syndrome

Background

Polycystic ovary syndrome (PCOS) is the major reason for women's low fertility and the most frequent endocrine disorder in women of childbearing age. Homocysteine is an amino acid that contains sulfur that has been negatively correlated with the reproductive outcome of polycystic women treated with IVF/ICSI. However, the impact of blood homocysteine levels on the outcome of artificial insemination in polycystic ovary syndrome women is unknown. The goal of this study is to examine the impact of serum homocysteine on the result of intrauterine insemination in females who have polycystic ovary syndrome (PCOS).

Methods

96 infertile women (129 cycles) treated with artificial insemination were collected, including 66 cases (87 cycles) in the case group (PCOS group) and 30 cases (42 cycles) in the control group (male factor infertility). The differences in general data amongst two groups, such as BMI, Hcy, and age, were compared. The case group has been classified into two groups based on serum Hcy level: LHcy group (Hcy < 15) and HHcy group (Hcy ≥ 15). The relationship among pregnancy and serum Hcy level outcome in PCOS women was compared.

Results

The PCOS group had substantially increased serum homocysteine levels in comparison to the control group (P = 0.019). Among PCOS women, the clinical pregnancy rates of artificial insemination in the HHcy group and LHcy group were 14.29% and 37.88%. The difference among the two groups was substantial (P = 0.044). Artificial insemination frequency, ovulation induction, BMI, infertility years, AMH, serum testosterone, HOME IR, TSH, TPOAb, hCG, daily follicle size, intimal thickness, and other factors did not differ greatly between the two groups.

Conclusion

Serum homocysteine levels are increased in women having PCOS. Their levels above the threshold will lower the clinical pregnancy rate of intrauterine insemination in PCOS women.

The effect of metformin on homocysteine levels in patients with polycystic ovary syndrome: A systematic review and meta-analysis

PURPOSE

Metformin is widely used as an insulin sensitizer in polycystic ovary syndrome (PCOS) patients. However, previous studies have found that the effect of metformin on the level of homocysteine were not consistent in PCOS patients. The aim of this review was to analyze the effect of metformin on homocysteine levels in patients with PCOS patients.

METHODS

The Cochrane Library, Pubmed, and Web of Science were searched according to predefined search terms. There is no restriction for publication time and language.

RESULTS

Eleven studies were included and the data were extracted. The homocysteine level in PCOS patients was significantly increased after taking metformin (mean difference [MD] -1.33; 95% confidence interval [CI] -2.16 to -0.49, p = 0.002). Subgroup analysis showed that the level of homocysteine was generally increased in PCOS patients with body mass index (BMI) ≥25 after taking metformin alone (MD -1.82; 95% CI -2.56 to -1.07, p < 0.00001). There was no significant change in homocysteine level in PCOS patients with BMI <25 (MD 0.69; 95% CI -0.41 to 1.79, p = 0.22). Subgroup analysis showed that there was no significant difference when taking metformin >3 months or taking metformin ≤3 months (p = 0.84). Taking metformin ≥1700 mg/days significantly increased homocysteine levels in PCOS patients (MD -2.05; 95% CI -2.40 to -1.70, p < 0.00001). When taking metformin <1700 mg/days, there was no significant difference in homocysteine level in PCOS patients (MD 0.15; 95% CI -1.06 to 1.37, p = 0.80). The difference between the two subgroups was significant (p = 0.0006). There was no significant difference in vitamin B12 level before and after metformin treatment (MD 24.70; 95% CI -22.54 to 71.93, p = 0.31). There was a decrease in serum folic acid level after metformin administration (MD 1.03; 95% CI 0.80 to 1.26, p < 0.00001).

CONCLUSION

Taking metformin alone increased homocysteine levels and decreased folic acid levels in nonpregnant PCOS patients. And, it was suggested that the dosage of metformin should be less than 1700 mg/days. The supplement of folic acid and B vitamins during metformin administration may be essential in nonpregnant PCOS patients. We should pay much attention to the potential effect of metformin in PCOS patients.

Significance of Homocysteine Levels in the Management of Polycystic Ovarian Syndrome: A Literature Review

Polycystic ovarian syndrome (PCOS) is a complex disorder involving cardiovascular, metabolic, endocrine, and reproductive systems. Even though the exact etiology is not clear, many studies suggest genetic and environmental factors play a role. Homocysteine (Hcy) is considered to be an independent risk factor for atherogenic and thrombotic components of various systems. Many studies in the past have evaluated Hcy levels in the PCOS population. This article aims to elaborate on the importance of Hcy levels in the overall management of PCOS. We conducted a PubMed data search using combined keywords PCOS and homocysteine levels and manually screened relevant articles for the review while avoiding duplication of data. After the literature review, we analyzed the relationship between homocysteine levels and various components of PCOS. Most of the studies identified a statistically significant elevation in Hcy levels in PCOS women with insulin resistance, androgen excess, elevated markers of cardiovascular risk, recurrent pregnancy loss, and metformin treatment. We also examined studies that focused on treating hyperhomocysteinemia (Hhcy) in PCOS women. However, because of the limited sample sizes and various inclusion criteria used for subjects in the studies, their clinical implication is unclear in routine practice. Furthermore, we encourage clinicians to follow up on Hcy levels in PCOS women at high risk for any complications in their management course. We believe an observational study on a larger scale in a well-defined PCOS population would be useful to uncover the prevalence of elevated Hcy levels in PCOS women, which would help pave the way for establishing treatment guidelines on serum Hcy levels in PCOS management.

Towards frailty biomarkers: Candidates from genes and pathways regulated in aging and age-related diseases

OBJECTIVE

Use of the frailty index to measure an accumulation of deficits has been proven a valuable method for identifying elderly people at risk for increased vulnerability, disease, injury, and mortality. However, complementary molecular frailty biomarkers or ideally biomarker panels have not yet been identified. We conducted a systematic search to identify biomarker candidates for a frailty biomarker panel.

METHODS

Gene expression databases were searched (http://genomics.senescence.info/genes including GenAge, AnAge, LongevityMap, CellAge, DrugAge, Digital Aging Atlas) to identify genes regulated in aging, longevity, and age-related diseases with a focus on secreted factors or molecules detectable in body fluids as potential frailty biomarkers. Factors broadly expressed, related to several "hallmark of aging" pathways as well as used or predicted as biomarkers in other disease settings, particularly age-related pathologies, were identified. This set of biomarkers was further expanded according to the expertise and experience of the authors. In the next step, biomarkers were assigned to six "hallmark of aging" pathways, namely (1) inflammation, (2) mitochondria and apoptosis, (3) calcium homeostasis, (4) fibrosis, (5) NMJ (neuromuscular junction) and neurons, (6) cytoskeleton and hormones, or (7) other principles and an extensive literature search was performed for each candidate to explore their potential and priority as frailty biomarkers.

RESULTS

A total of 44 markers were evaluated in the seven categories listed above, and 19 were awarded a high priority score, 22 identified as medium priority and three were low priority. In each category high and medium priority markers were identified.

CONCLUSION

Biomarker panels for frailty would be of high value and better than single markers. Based on our search we would propose a core panel of frailty biomarkers consisting of (1) CXCL10 (C-X-C motif chemokine ligand 10), IL-6 (interleukin 6), CX3CL1 (C-X3-C motif chemokine ligand 1), (2) GDF15 (growth differentiation factor 15), FNDC5 (fibronectin type III domain containing 5), vimentin (VIM), (3) regucalcin (RGN/SMP30), calreticulin, (4) PLAU (plasminogen activator, urokinase), AGT (angiotensinogen), (5) BDNF (brain derived neurotrophic factor), progranulin (PGRN), (6) α-klotho (KL), FGF23 (fibroblast growth factor 23), FGF21, leptin (LEP), (7) miRNA (micro Ribonucleic acid) panel (to be further defined), AHCY (adenosylhomocysteinase) and KRT18 (keratin 18). An expanded panel would also include (1) pentraxin (PTX3), sVCAM/ICAM (soluble vascular cell adhesion molecule 1/Intercellular adhesion molecule 1), defensin α, (2) APP (amyloid beta precursor protein), LDH (lactate dehydrogenase), (3) S100B (S100 calcium binding protein B), (4) TGFβ (transforming growth factor beta), PAI-1 (plasminogen activator inhibitor 1), TGM2 (transglutaminase 2), (5) sRAGE (soluble receptor for advanced glycosylation end products), HMGB1 (high mobility group box 1), C3/C1Q (complement factor 3/1Q), ST2 (Interleukin 1 receptor like 1), agrin (AGRN), (6) IGF-1 (insulin-like growth factor 1), resistin (RETN), adiponectin (ADIPOQ), ghrelin (GHRL), growth hormone (GH), (7) microparticle panel (to be further defined), GpnmB (glycoprotein nonmetastatic melanoma protein B) and lactoferrin (LTF). We believe that these predicted panels need to be experimentally explored in animal models and frail cohorts in order to ascertain their diagnostic, prognostic and therapeutic potential.