scholarly journals Assessment of Bidirectional Relationships Between Polycystic Ovary Syndrome and Periodontitis: Insights From a Mendelian Randomization Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Pengfei Wu ◽  
Xinghao Zhang ◽  
Ping Zhou ◽  
Wan Zhang ◽  
Danyang Li ◽  
...  

BackgroundObservational studies have indicated an association between polycystic ovary syndrome (PCOS) and periodontitis, but it is unclear whether the association is cofounded or causal. We conducted a two-sample Mendelian randomization (MR) study to investigate the bidirectional relationship between genetically predicted PCOS and periodontitis.MethodsFrom two genome-wide association studies we selected 13 and 7 single nucleotide polymorphisms associated with PCOS and periodontitis, respectively, as instrumental variables. We utilized publicly shared summary-level statistics from European-ancestry cohorts. To explore the causal effect of PCOS on periodontitis, 12,289 cases of periodontitis and 22,326 controls were incorporated, while 4,890 cases of PCOS and 20,405 controls in the reverse MR. Inverse-variance weighted method was employed in the primary MR analysis and multiple sensitivity analyses were implemented.ResultsGenetically determined PCOS was not causally associated with risk of periodontitis (odds ratio 0.97; 95% confidence interval 0.88–1.06; P = 0.50) per one-unit increase in the log-odds ratio of periodontitis. Similarly, no causal effect of periodontitis on PCOS was shown with the odds ratio for PCOS was 1.17 (95% confidence interval 0.91–1.49; P = 0.21) per one-unit increase in the log-odds ratio of periodontitis. Consistent results were yielded via additional MR methods. Sensitivity analyses demonstrated no presence of horizontal pleiotropy or heterogeneity.ConclusionThe bidirectional MR study couldn’t provide convincing evidence for the causal relationship between genetic liability to PCOS and periodontitis in the Europeans. Triangulating evidence across further observational and genetic-epidemiological studies is necessary.

Author(s):  
Yuexin Gan ◽  
Donghao Lu ◽  
Chonghuai Yan ◽  
Jun Zhang ◽  
Jian Zhao

Abstract Background Observational associations between maternal polycystic ovary syndrome (PCOS) and offspring birth weight (BW) have been inconsistent and the causal relationship is still uncertain. Objective We conducted a two-sample Mendelian randomization (MR) study to estimate the causal effect of maternal PCOS on offspring BW. Methods We constructed genetic instruments for PCOS with 14 single nucleotide polymorphisms (SNPs) which were identified in the genome-wide association study (GWAS) meta-analysis including 10,074 PCOS cases and 103,164 controls of European ancestry from seven cohorts. The genetic associations of these SNPs with the offspring BW were extracted from summary statistics estimated by the Early Growth Genetics (EGG) consortium (n = 406,063 European-ancestry individuals) using the weighted linear model (WLM), an approximation method of structural equation model (SEM), which separated maternal genetic effects from fetal genetic effects. We used a two-sample MR design to examine the causal relationship between maternal PCOS and offspring BW. Sensitivity analyses were conducted to assess the robustness of the MR results. Results We found little evidence for a causal effect of maternal PCOS on offspring BW (-6.1 g, 95% confidence interval [CI]: -16.8 g, 4.6 g). Broadly consistent results were found in the sensitivity analyses. Conclusion Despite the large scale of this study, our results suggested little causal effect of maternal PCOS on offspring BW. MR studies with a larger sample size of women with PCOS or more genetic instruments that would increase the variation of PCOS explained are needed in the future.


2020 ◽  
Author(s):  
Oskar Hougaard Jefsen ◽  
Maria Speed ◽  
Doug Speed ◽  
Søren Dinesen Østergaard

AbstractAimsCannabis use is associated with a number of psychiatric disorders, however the causal nature of these associations has been difficult to establish. Mendelian randomization (MR) offers a way to infer causality between exposures with known genetic predictors (genome-wide significant single nucleotide polymorphisms (SNPs)) and outcomes of interest. MR has previously been applied to investigate the relationship between lifetime cannabis use (having ever used cannabis) and schizophrenia, depression, and attention-deficit / hyperactivity disorder (ADHD), but not bipolar disorder, representing a gap in the literature.MethodsWe conducted a two-sample bidirectional MR study on the relationship between bipolar disorder and lifetime cannabis use. Genetic instruments (SNPs) were obtained from the summary statistics of recent large genome-wide association studies (GWAS). We conducted a two-sample bidirectional MR study on the relationship between bipolar disorder and lifetime cannabis use, using inverse-variance weighted regression, weighted median regression and Egger regression.ResultsGenetic liability to bipolar disorder was significantly associated with an increased risk of lifetime cannabis use: scaled log-odds ratio (standard deviation) = 0.0174 (0.039); P-value = 0.00001. Genetic liability to lifetime cannabis use showed no association with the risk of bipolar disorder: scaled log-odds ratio (standard deviation) = 0.168 (0.180); P-value = 0.351. The sensitivity analyses showed no evidence for pleiotropic effects.ConclusionsThe present study finds evidence for a causal effect of liability to bipolar disorder on the risk of using cannabis at least once. No evidence was found for a causal effect of liability to cannabis use on the risk of bipolar disorder. These findings add important new knowledge to the understanding of the complex relationship between cannabis use and psychiatric disorders.


2021 ◽  
Author(s):  
Yanfei Zhang ◽  
Vani C. Movva ◽  
Marc S Williams ◽  
Ming Ta Michael Lee

Purpose Polycystic ovary syndrome (PCOS) is a complex disorder with heterogenous phenotypes and unclear etiology. A recent phenotypic clustering study identified metabolic and reproductive subtypes of PCOS. We attempted to deconstruct the PCOS heterogeneity from a genetic perspective. Methods We applied k-means clustering to categorize the genome-wide significant PCOS variants into clusters based on their associations with selected quantitative traits that likely reflect PCOS etiological pathways. We evaluated the association of each cluster with PCOS related traits and disease outcomes. We then applied Mendelian randomization to estimate the causal effect of the traits on PCOS and PCOS on disease outcomes. Results Clustering analysis suggested three categories of variants: adiposity, insulin resistant, and reproductive. Significant associations were observed for variants in the adiposity cluster with body mass index (BMI), waist circumference and breast cancer, and variants in insulin resistant cluster with fasting insulin and glucose values, and homeostatic model assessment of insulin resistance (HOMA-IR). Sex hormone binding globulin (SHBG) has strong association with all three clusters. Mendelian randomization supported the causal role of BMI and SHBG on PCOS. No causal associations were observed for PCOS on disease outcomes. Main Conclusions Our study provides genetic evidence for the heterogeneity in PCOS etiologies, corresponding to the reported phenotypic subtypes. Such studies will improve the current PCOS diagnosis criteria that do not distinguish the heterogeneity. Classification of women with PCOS to inform appropriate treatment will be more accurate in the future with improvements in clustering analysis for PCOS.


2021 ◽  
Vol 12 ◽  
Author(s):  
Jack C. M. Ng ◽  
C. Mary Schooling

Background: Basal metabolic rate is associated with cancer, but these observations are open to confounding. Limited evidence from Mendelian randomization studies exists, with inconclusive results. Moreover, whether basal metabolic rate has a similar role in cancer for men and women independent of insulin-like growth factor 1 increasing cancer risk has not been investigated.Methods: We conducted a two-sample Mendelian randomization study using summary data from the UK Biobank to estimate the causal effect of basal metabolic rate on cancer. Overall and sex-specific analysis and multiple sensitivity analyses were performed including multivariable Mendelian randomization to control for insulin-like growth factor 1.Results: We obtained 782 genetic variants strongly (p-value < 5 × 10–8) and independently (r2 < 0.01) predicting basal metabolic rate. Genetically predicted higher basal metabolic rate was associated with an increase in cancer risk overall (odds ratio, 1.06; 95% confidence interval, 1.02–1.10) with similar estimates by sex (odds ratio for men, 1.07; 95% confidence interval, 1.002–1.14; odds ratio for women, 1.06; 95% confidence interval, 0.995–1.12). Sensitivity analyses including adjustment for insulin-like growth factor 1 showed directionally consistent results.Conclusion: Higher basal metabolic rate might increase cancer risk. Basal metabolic rate as a potential modifiable target of cancer prevention warrants further study.


2021 ◽  
Author(s):  
Qian Sun ◽  
Yuan Gao ◽  
Jingyun Yang ◽  
Jiayi Lu ◽  
Wen Feng ◽  
...  

Research question: Polycystic ovary syndrome (PCOS) is a common endocrine disorder with unclear etiology. Are there any genes that are pleiotropically or potentially causally associated with PCOS? Design: We applied the summary data-based Mendelian randomization (SMR) method integrating genome-wide association study (GWAS) for PCOS and expression quantitative trait loci (eQTL) data to identify genes that were pleiotropically associated with PCOS. We performed separate SMR analysis using eQTL data in the ovary and whole blood. Results: Although no genes showed significant pleiotropic association with PCOS after correction for multiple testing, some of the genes exhibited suggestive significance. RPS26 showed the strongest suggestive pleiotropic association with PCOS in both SMR analyses (β[SE]=0.10[0.03], PSMR=1.72*10-4 for ovary; β[SE]=0.11[0.03], PSMR=1.40*10-4 for whole blood). PM20D1 showed the second strongest suggestive pleiotropic association with PCOS in the SMR analysis using eQTL data for the whole blood, and was also among the top ten hit genes in the SMR analysis using eQTL data for the ovary. Two other genes, including CTC-457L16.2 and NEIL2, were among the top ten hit genes in both SMR analyses. Conclusion: We identified multiple genes that were potentially involved in the pathogenesis of PCOS. Our findings provided helpful leads to a better understanding of the mechanisms underlying PCOS, and revealed potential therapeutic targets for the effective treatment of PCOS.


2020 ◽  
Author(s):  
Songzan Chen ◽  
Fangkun Yan ◽  
Tian Xu ◽  
Yao Wang ◽  
Kaijie Zhang ◽  
...  

Abstract Background Although several observational studies have shown an association between birth weight (BW) and atrial fibrillation (AF), controversy remains. In this study, we aimed to explore the role of elevated BW on the etiology of AF. Methods A two-sample Mendelian randomization (MR) study was designed to infer the causality. The genetic data on the associations of single nucleotide polymorphisms (SNPs) with BW and AF were separately obtained from two large-scale genome-wide association study with up to 321,223 and 1,030,836 individuals respectively. SNPs were identified at a genome-wide significant level (p-value < 5 × 10− 8). The inverse variance-weighted (IVW) with fixed effects method was performed to obtain causal estimates as our primary analysis. MR-Egger regression was conducted to assess the pleiotropy and sensitivity analyses with various statistical methods were applied to evaluate the robustness of the results. Results In total, 122 SNPs were identified as the genetic instrumental variables. MR analysis revealed a causal effect of elevated BW on AF (OR = 1.21, 95% CI = 1.13–1.29, p-value = 2.39 × 10− 8). The MR-Egger regression suggested no evidence of directional pleiotropy (intercept = 0.00, p-value = 0.62). All the results in sensitivity analyses were consistent with the primary result, which confirmed the causal association between BW and AF. Conclusions The findings from the two-sample MR study indicate a causal effect of elevated BW on AF. This suggests a convenient and effective method to ease the burden of AF by reducing the number of newborns with elevated BW.


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