Evidence of a causal relationship between genetic tendency to gain muscle mass and uterine leiomyomata

Sliz, Eeva; Tyrmi, Jaakko; Rahmioğlu, Nilüfer; Zondervan, Krina T.; Becker, Christian M.; FinnGen,; Uimari, Outi; Kettunen, Johannes

doi:10.1101/2021.08.20.21262098

Cited by 4 publications

(5 citation statements)

References 69 publications

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“…Less well-characterized relationships included a positive association between genetically predicted lactate levels and benign neoplasm of uterus. This potentially causal association is concordant with a recent GWAS that linked genetic tendency to gain muscle mass with uterine fibroids 51 . We also found an inverse association between genetically predicted circulating glycine levels and blood pressure, which is supported by a strong observational association with hypertension 52 and by genetic data 53 .…”

Section: Mendelian Randomizationsupporting

confidence: 87%

Genome-wide characterization of circulating metabolic biomarkers

Karjalainen,

Karthikeyan,

Oliver-Williams

et al. 2024

Nature

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Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1–7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8–11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases.

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Section: Mendelian Randomizationsupporting

confidence: 87%

Genome-wide characterization of circulating metabolic biomarkers

Karjalainen,

Karthikeyan,

Oliver-Williams

et al. 2024

Nature

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“…The new locus on chromosome 17 is on an intronic region of TP53 , a tumor suppressor gene. This variant has been reported to increase risk of uterine fibroids, gliomas, and lean mass, while other variants on TP53 are inked to levels of SHBG and testosterone [21, 22, 23]. The rs78378222 locus is a significant eQTL for TP53 in several tissues including adipose tissue.…”

Section: Resultsmentioning

confidence: 99%

Understanding and Predicting Polycystic Ovary Syndrome through Shared Genetics with Testosterone, SHBG, and Chronic Inflammation

Petersen,

Brixi,

et al. 2023

Preprint

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Polycystic ovary syndrome (PCOS) is a common hormonal disorder that affects one out of eight women and has high metabolic and psychological comorbidities. PCOS is thought to be associated with increased systemic low-grade inflammation, but the underlying mechanisms remain unclear. Here we study the genetic relationship between PCOS and obesity, testosterone, sex hormone binding globulin (SHBG), and chronic inflammation. First we create a large meta-analysis of PCOS (7,747 PCOS cases and 498,227 controls) and identify four novel genetic loci associated with PCOS. These novel loci have been previously associated with changes in gene expression in multiple tissues including the thyroid and ovary. We then analyze the PCOS meta analysis alongside GWASs for obesity (n=681,275), SHBG (n=190,366), testosterone (n=176,687), and meta-analyses of 130 inflammatory biomarkers (average n=30,000). We replicate potential causal relationships (via Mendelian randomization) from obesity and SHBG to PCOS and find extensive genetic correlations and causality between these traits and inflammatory biomarkers. We identify significant genetic correlations between PCOS and eight inflammatory biomarkers, including new relationships such as a strong correlation to death receptor 5 (LDSC rg=0.54, FDR=0.043). Although these results point to a shared genetic architecture between PCOS and inflammation, we did not find statistically significant causality between them; however, we did find 27 inflammatory biomarkers with significant causal effects on SHBG and four biomarkers with significant causal effects on testosterone. These results support the hypothesis that chronic inflammation can influence androgen and SHBG levels, though more research is needed to verify these results. Finally, we show that combining the polygenic risk scores of PCOS-related traits improves genetic prediction of PCOS cases in the UK Biobank and MGB Biobank compared to using only PCOS risk scores (0.72 AUC from 0.59 AUC and 0.61 AUC from 0.59 AUC in each biobank respectively).

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“…Large GWAS of endometriosis [ 45 , 46 ], UF [ 1 , 47 – 50 ], and PCOS [ 51 ] have previously been conducted, and so the results for these meta-analyses are presented using supplementary tables and figures only, with details of their genome-wide significant loci and MAGMA-identified genes provided in online supplementary Tables S6–S10 and enriched tissues illustrated in online supplementary Figures S3, S4. Full details of the results for meta-analyses of ovarian cysts, menopausal symptoms, menorrhagia, pelvic inflammatory disease, genital polyps, and dysmenorrhoea are described in the supplementary note, with details of their genome-wide significant loci and MAGMA-identified genes provided in online supplementary Tables S11–S15 and enriched tissues illustrated in online supplementary Figures S5–S7.…”

Section: Resultsmentioning

confidence: 99%

“…These disorders are listed in Table 3, which includes the number of loci found, the most significant locus with associated genes, and other disorders that reported genome-wide significance for the same locus. Large GWAS of endometriosis [45,46], UF [1,[47][48][49][50], and PCOS [51] have previously been conducted, and so the results for these meta-analyses are presented using supplementary tables and figures only, with details of their genome-wide significant loci and MAGMAidentified genes provided in online supplementary Fig. 2.…”

Section: Meta-analysis Of Reproductive Disordersmentioning

confidence: 99%

A Common Genetic Factor Underlies Genetic Risk for Gynaecological and Reproductive Disorders and Is Correlated with Risk to Depression

Kiewa,

Mortlock,

Meltzer-Brody

et al. 2023

Neuroendocrinology

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Introduction Sex steroid hormone fluctuations may underlie both reproductive disorders and sex difference in lifetime depression prevalence. Previous studies report high comorbidity among reproductive disorders and between reproductive disorders and depression. This study sought to assess the multivariate genetic architecture of reproductive disorders and their loading onto a common genetic factor, and investigated whether this latent factor shares a common genetic architecture with female depression, including perinatal depression (PND). Method Using UK Biobank and FinnGen data, genome-wide association meta-analyses were conducted for nine reproductive disorders, and genetic correlation between disorders estimated. Genomic Structural Equation Modelling identified a latent genetic factor underlying disorders, accounting for their significant genetic correlations. SNPs significantly associated with both latent factor and depression were identified. Results Excellent model fit existed between a latent factor underlying five reproductive disorders (2 (5)=6.4; AIC=26.4; CFI=1.00; SRMR=0.03) with high standardised loadings for menorrhagia (0.96, SE=0.05); ovarian cysts (0.94, SE=0.05); endometriosis (0.83, SE=0.05); menopausal symptoms (0.77, SE=0.10); and uterine fibroids (0.65, SE=0.05). This latent factor was genetically correlated with perinatal depression (PND) (rG = 0.37, SE=0.15, P=1.4e-03), depression in females only (rG=0.48, SE=0.06, P=7.2e-11) and depression in both males and females (MD) (rG=0.35, SE=0.03, P=1.8e-30), with its top locus associated with FSHB/ARL14EP (rs11031006; P=9.1e-33). SNPs intronic to ESR1, significantly associated with the latent factor, were also associated with PND, female depression, and MD. Discussion/Conclusion A common genetic factor, correlated with depression, underlies risk to reproductive disorders, with implications for etiology and treatment. Genetic variation in ESR1 is associated with reproductive disorders and depression, highlighting the importance of estrogen signalling to both reproductive and mental health.

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Evidence of a causal relationship between genetic tendency to gain muscle mass and uterine leiomyomata

Cited by 4 publications

References 69 publications

Genome-wide characterization of circulating metabolic biomarkers

Genome-wide characterization of circulating metabolic biomarkers

Understanding and Predicting Polycystic Ovary Syndrome through Shared Genetics with Testosterone, SHBG, and Chronic Inflammation

A Common Genetic Factor Underlies Genetic Risk for Gynaecological and Reproductive Disorders and Is Correlated with Risk to Depression

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