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. 2020 Sep 8:11:621.
doi: 10.3389/fendo.2020.00621. eCollection 2020.

Causal Effects of Genetically Determined Metabolites on Risk of Polycystic Ovary Syndrome: A Mendelian Randomization Study

Shuliu Sun  1 , Minjie Jiao  1 , Chengcheng Han  1 , Qian Zhang  1 , Wenhao Shi  2 , Juanzi Shi  2 , Xiaojuan Li  1
Affiliations

Causal Effects of Genetically Determined Metabolites on Risk of Polycystic Ovary Syndrome: A Mendelian Randomization Study

Shuliu Sun et al. Front Endocrinol (Lausanne). .

Abstract

Background: Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder that is influenced by both genetic and environmental factors. However, the etiology of PCOS remains unclear. Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effects of genetically determined metabolites (GDMs) on the risk of PCOS. We used summary level data of a genome-wide association study (GWAS) on 486 metabolites (n = 7,824) as exposure and a PCOS GWAS consisting of 4,138 cases and 20,129 controls as the outcome. Both datasets were obtained from publicly published databases. For each metabolite, a genetic instrumental variable was generated to assess the relationship between the metabolite and PCOS. For MR analysis, we primarily used the standard inverse variance weighted (IVW) method, while three additional methods-the MR-Egger, weighted median, and MR-PRESSO (pleiotropy residual sum and outlier) methods-were performed as sensitivity analyses. Results: Using genetic variants as predictors, we observed a robust relationship between epiandrosterone sulfate (EPIA-S) and PCOS (PIVW = 0.0186, PMR-Egger = 0.0111; PWeighted-median = 0.0154, and PMR-PRESSO = 0.0290). Similarly, 3-dehydrocarnitine, 4-hydroxyhippurate, hexadecanedioate, and β-hydroxyisovalerate may also have causal effects on PCOS development. Conclusions: We identified metabolites that might have causal effects on PCOS development. Our study emphasizes the role of genetic factors underlying the causal relationships between metabolites and PCOS and provides novel insights through the integration of metabolomics and genomics to better understand the mechanisms involved in human disease pathogenesis.

Keywords: epiandrosterone sulfate; genetically determined metabolites; mendelian randomization; polycystic ovary syndrome; rs13222543.

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Figures

Figure 1
Figure 1
Mendelian randomization (MR) association of serum metabolites on the risk of polycystic ovary syndrome (PCOS). Causal estimates are obtained using metabolite-related single-nucleotide polymorphisms (SNPs) as instrumental variables using the inverse variance weighted (IVW) method. Odds ratio (OR) and 95% confidence intervals (95% CIs) are provided for PCOS per 1-s.d. higher level of specific metabolite.
Figure 2
Figure 2
Mendelian randomization (MR) plots for relationship of epiandrosterone sulfate (EPIA-S) with polycystic ovary syndrome (PCOS). (A) Scatter plot of potential effects of single-nucleotide polymorphisms (SNPs) on EPIA-S vs. PCOS, with the slope of each line corresponding to the estimated MR effect per method. SNPs showing negative signals with EPIA-S are plotted after orientation to the exposure-increasing allele. SNPs with higher effects on both metabolites and PCOS are marked on the plots. (B) Forest plot of individual and combined effects of EPIA-S related SNPs on PCOS. Data are expressed as raw β values with 95% confidence interval (CI).
Figure 3
Figure 3
Scatter plots of genetic associations with four suggestive metabolites vs. the associations with polycystic ovary syndrome (PCOS). (A) 3-Dehydrocarnitine; (B) hexadecanedioate; (C) 4-hydroxyhippurate; (D) β-hydroxyisovalerate. Each of the single-nucleotide polymorphisms (SNPs) associated with metabolites are represented by a black dot with the error bar depicting the standard error of its association with metabolite (horizontal) and PCOS (vertical). The slopes of each line represent the causal association for each method. SNPs showing negative signals with metabolites are plotted after orientation to the exposure-increasing allele.
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