Dataset Information

The causal association between polycystic ovary syndrome and susceptibility and severity of COVID-19: a bidirectional Mendelian randomization study using genetic data.

ABSTRACT:

Introduction

Observational studies have reported an association between polycystic ovary syndrome (PCOS) and COVID-19, but a definitive causal relationship has not been established. This study aimed to assess this association using two-way two-sample Mendelian randomization (MR).

Methods

A summary of PCOS characteristics was compiled using the PCOS summary statistics from the Apollo University of Cambridge Repository. COVID-19 susceptibility and severity statistics, including hospitalization and extremely severe disease, were obtained from genome-wide association studies from the COVID-19 Host Genetics Initiative. The primary analysis used the inverse variance-weighted method, supplemented by the weighted median, MR-Egger, and MR-PRESSO methods.

Results

The forward MR analysis showed no significant impact of PCOS on COVID-19 susceptibility, hospitalization, or severity (OR = 0.983, 1.011, 1.014; 95% CI = 0.958-1.008, 0.958-1.068, 0.934-1.101; and p = 0.173, 0.68, 0.733; respectively). Similarly, reverse MR analysis found no evidence supporting COVID-19 phenotypes as risk or protective factors for PCOS (OR = 1.041, 0.995, 0.944; 95% CI = 0.657-1.649, 0.85-1.164, 0.843-1.058; and p = 0.864, 0.945, 0.323; respectively). Consequently, no significant association between any COVID-19 phenotype and PCOS was established.

Conclusion

This MR study suggested that PCOS is not a causal risk factor for the susceptibility and severity of COVID-19. The associations identified in previous observational studies might be attributable to the presence of comorbidities in the patients.

SUBMITTER: Si Y

PROVIDER: S-EPMC10515223 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The causal association between polycystic ovary syndrome and susceptibility and severity of COVID-19: a bidirectional Mendelian randomization study using genetic data.

Si Yu Y Fei Yuye Y Ma Hua H Xu Yating Y Ning Li L Li Xiu X Ren Qingling Q

Frontiers in endocrinology 20230908

<h4>Introduction</h4>Observational studies have reported an association between polycystic ovary syndrome (PCOS) and COVID-19, but a definitive causal relationship has not been established. This study aimed to assess this association using two-way two-sample Mendelian randomization (MR).<h4>Methods</h4>A summary of PCOS characteristics was compiled using the PCOS summary statistics from the Apollo University of Cambridge Repository. COVID-19 susceptibility and severity statistics, including hosp ...[more]

PMID: 37745707

Similar Datasets

Project description:Polycystic ovary syndrome (PCOS) is defined as a chronic low-grade inflammatory reproductive endocrine disorder. PCOS can induce various metabolic disorders, which are associated with a state of mild and slow-acting inflammation. Nevertheless, the causal relationship between polycystic ovary syndrome and inflammatory factors is uncertain. The causality between inflammatory cytokines and PCOS was analyzed by bidirectional Mendelian randomization (MR) in this current probe. We performed an interactive MR study to assess the causal relationships between 91 inflammatory cytokines and PCOS using Genome Wide Association Study (GWAS) data. We underwent dual-sample MR analysis with inverse variance weights (IVW) as the predominant MR methodology with multiple validity and heterogeneity analyses. MR-Egger, weighted median, simple mode, weighted mode and MR-PRESSO were analyzed as multiple likelihood sensitivity analyses to enhance the final results.The results came out interleukin-1-alpha (IL-1 A) levels (odds ratio [OR] = 1.051, 95% fiducial interval [95% CI] = 1.009-1.095, P = 0.02) and oncostatin-M (OSM) levels ( [OR] = 1.041, [95% CI] = 1.001-1.082, P = 0.04) were positively associated with the development of PCOS. Moreover, interleukin-7 (IL-7) levels ([OR] = 0.935, [95% CI] = 0.884-0.989, P = 0.02); interleukin-15 receptor subunit alpha (IL15RA) levels ([OR] = 0.959, [95% CI] = 0.929-0.99, P = 0.01); and C-X-C motif chemokine 11 (CXCL11) levels ([OR] = 0.959, [95% CI] = 0.922-0.996. P = 0.03) were strongly negatively associated with PCOS. However, we did not find any strong positive results in the reverse analysis, suggesting that although inflammatory factors contribute to the pathogenesis of PCOS, PCOS itself does not trigger inflammatory factor production.Our study provides genetic evidence for the connection between systemic inflammatory regulators and PCOS. Treatments targeting specific inflammatory factors may help to mitigate the risk of PCOS. The levels of five of the 91 inflammatory factors included in this study, namely, IL1A and OSM, were associated with PCOS. IL1A and OSM contribute to the progression of PCOS while IL-7, IL15RA, and CXCL11 levels are negatively correlated with the development of PCOS.

Project description:Study questionWhat are the causal relationships between polycystic ovary syndrome (PCOS) and body mass index (BMI)?Summary answerBidirectional Mendelian randomization analyses suggest that increased BMI is causal for PCOS while the reverse is not the case.What is known alreadyThe contribution of obesity to the pathogenesis of PCOS is controversial. To date, published genetic studies addressing this question have generated conflicting results and have not utilized the full extent of known single nucleotide polymorphisms associated with body mass index (BMI).Study design, size, durationThis cross-sectional Mendelian randomization (MR) and genetic association study was conducted in 750 individuals of European origin and with PCOS and 1567 BMI-matched controls.Participants/materials, setting, methodsCases and controls were matched for BMI as well as for distribution of weight categories (normal weight, overweight, obese). Two-sample MR using inverse variance weighting (IVW) was conducted using a 92-SNP instrument variable for BMI with PCOS as the outcome, followed by two-sample MR with a 16-SNP instrument variable for PCOS with BMI as the outcome. Sensitivity analyses included MR-Egger and maximum likelihood methods. Secondary analyses assessed associations of genetic risk scores and individual SNPs with PCOS, BMI and quantitative androgen-related and glucose homeostasis-related traits.Main results and the role of chanceEach standard deviation genetically higher BMI was associated with a 4.89 (95% CI 1.46-16.32) higher odds of PCOS. Conversely, genetic risk of PCOS did not influence BMI. Sensitivity analyses yielded directionally consistent results. The genetic risk score of 92 BMI SNPs was associated with the diagnosis of PCOS (OR 1.043, 95% CI 1.009-1.078, P = 0.012). Of the 92 BMI risk variants evaluated, none were associated individually with PCOS after considering multiple testing. The association of FTO SNP rs1421085 with BMI was stronger in women with PCOS (β = 0.071, P = 0.0006) than in controls (β = 0.046, P = 0.065).Limitations, reasons for cautionThe current sample size, while providing good power for MR and genetic risk score analyses, had limited power to demonstrate association of individual SNPs with PCOS. Cases and controls were not matched for age; however, this was mitigated by adjusting analyses for age. Dietary and lifestyle data, which could have been used to explore the greater association of the FTO SNP with BMI in women with PCOS, was not available.Wider implications of the findingsIncreasing BMI appears to be causal for PCOS but having PCOS does not appear to affect BMI. This study used the most comprehensive set of SNPs for BMI currently available. Prior studies using fewer SNPs had yielded conflicting results and may have been confounded because cases and controls were not matched for weight categories. The current results highlight the potential utility of weight management in the prevention and treatment of PCOS.Study funding/competing interest(s)National Institutes of Health Grants R01-HD29364 and K24-HD01346 (to R.A.), Grant R01-DK79888 (to M.O.G.), Grant U54-HD034449 (to R.S.L.), Grant U19-HL069757 (to R.M.K.). The funders had no influence on the data collection, analyses or conclusions of the study. No conflict of interests to declare.Trial registration numberN/A.

Dataset Information

The causal association between polycystic ovary syndrome and susceptibility and severity of COVID-19: a bidirectional Mendelian randomization study using genetic data.

Introduction

Methods

Results

Conclusion

Publications

The causal association between polycystic ovary syndrome and susceptibility and severity of COVID-19: a bidirectional Mendelian randomization study using genetic data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets