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Guixue G, Yifu P, Xiaofeng T, Qian S, Yuan G, Wen Y, Conghui H, Zuobin Z. Investigating the causal impact of polycystic ovary syndrome on gestational diabetes mellitus: a two-sample Mendelian randomization study. Front Endocrinol (Lausanne) 2024; 15:1337562. [PMID: 38375192 PMCID: PMC10875069 DOI: 10.3389/fendo.2024.1337562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 01/16/2024] [Indexed: 02/21/2024] Open
Abstract
Introduction Determining the causal relationship between polycystic ovary syndrome (PCOS) and gestational diabetes mellitus (GDM) holds significant implications for GDM prevention and treatment. Despite numerous observational studies suggesting an association between PCOS and GDM, it remains unclear whether a definitive causal relationship exists between these two conditions and which specific features of PCOS contribute to increased incidence of GDM. Methods The causal relationship between polycystic ovary syndrome (PCOS), its characteristic indices, and gestational diabetes mellitus (GDM) was investigated using a two-sample Mendelian randomization study based on publicly available statistics from genome-wide association studies (GWAS). The inverse-variance weighted method was employed as the primary analytical approach to examine the association between PCOS, its characteristic indices, and GDM. MR Egger intercept was used to assess pleiotropy, while Q values and their corresponding P values were utilized to evaluate heterogeneity. It is important to note that this study adopts a two-sample MR design where PCOS and its characteristic indices are considered as exposures, while GDM is treated as an outcome. Results The study results indicate that there is no causal relationship between PCOS and GDM (all methods P > 0.05, 95% CI of OR values passed 1). The IVW OR value was 1.007 with a 95% CI of 0.906 to 1.119 and a P value of 0.904. Moreover, the MR Egger Q value was 8.141 with a P value of 0.701, while the IVW Q value was also 8.141 with a P value of 0.774, indicating no significant heterogeneity. Additionally, the MR Egger intercept was 0.0004, which was close to zero with a P value of 0.988, suggesting no pleiotropy. However, the study did find a causal relationship between several other factors such as testosterone, high-density lipoprotein, sex hormone-binding globulin, body mass index, waist-hip ratio, apolipoprotein A-I, number of children, diabetes illnesses of mother, father and siblings, hemoglobin A1c, fasting insulin, fasting blood glucose, years of schooling, and GDM based on the IVW method. Conclusion We observed no association between genetically predicted PCOS and the risk of GDM, implying that PCOS itself does not confer an increased susceptibility to GDM. The presence of other PCOS-related factors such as testosterone, high-density lipoprotein, and sex hormone-binding globulin may elucidate the link between PCOS and GDM. Based on these findings, efforts aimed at preventing GDM in individuals with PCOS should prioritize those exhibiting high-risk features rather than encompassing all women with PCOS.
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Affiliation(s)
- Guan Guixue
- Department of Gynecology, The First People’s Hospital of Lianyungang, Lianyungang, Jiangsu, China
- Department of Gynecology, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu, China
- Department of Gynecology, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China
| | - Pu Yifu
- Laboratory of Genetic Disease and Perinatal Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tang Xiaofeng
- Prenatal Diagnosis Center, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Sun Qian
- Department of Gynecology, The First People’s Hospital of Lianyungang, Lianyungang, Jiangsu, China
- Department of Gynecology, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu, China
- Department of Gynecology, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China
| | - Gao Yuan
- Department of Gynecology, The First People’s Hospital of Lianyungang, Lianyungang, Jiangsu, China
- Department of Gynecology, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu, China
- Department of Gynecology, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China
| | - Yang Wen
- Department of Gynecology, The First People’s Hospital of Lianyungang, Lianyungang, Jiangsu, China
- Department of Gynecology, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, Jiangsu, China
- Department of Gynecology, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, China
| | - Han Conghui
- Department of Urology, Xuzhou Central Hospital, Xuzhou, Jiangsu, China
- Department of Urology, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Zhu Zuobin
- Xuzhou Engineering Research Center of Medical Genetics and Transformation, Key Laboratory of Genetic Foundation and Clinical Application, Department of Genetics, Xuzhou Medical University, Xuzhou, Jiangsu, China
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Slouha E, Alvarez VC, Gates KM, Ankrah NMN, Clunes LA, Kollias TF. Gestational Diabetes Mellitus in the Setting of Polycystic Ovarian Syndrome: A Systematic Review. Cureus 2023; 15:e50725. [PMID: 38234933 PMCID: PMC10793469 DOI: 10.7759/cureus.50725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2023] [Indexed: 01/19/2024] Open
Abstract
Gestational diabetes mellitus (GDM) is the most common complication of pregnancy that arises in the 2nd and 3rd trimesters, leading to significant complications for the mother and her neonates, such as an increased rate of pregnancy-induced hypertension and miscarriages, while neonates may have a large birth weight, hypoglycemia, or macrosomnia. Numerous risk factors can lead to GDM; however, a significant one is polycystic ovarian syndrome (PCOS). PCOS is the most common endocrine pathology beginning before puberty, and due to significant hormonal changes, it is not diagnosed until after puberty. PCOS requires at least three of the following symptoms: hyperandrogenism, menstrual irregularities, or polycystic ovary morphology. While it is agreed that women with PCOS are at a significantly increased risk of GDM, no publication to our knowledge has evaluated the full relationship of GDM in the setting of PCOS. This paper aimed to assess this relationship and determine how it may differ for pregnant women with only GDM by determining the prevalence of GDM, the variations within phenotypes, the influence of fertilization methods, specific risk factors, maternal outcomes, and neonatal outcomes. The prevalence of GDM was significantly increased in women with PCOS compared to healthy controls, and some studies have found that phenotype A may be more likely to lead to GDM. Risk factors were similar to pregnant women with only GDM, but with GDM and PCOS specifically, preconception low sex hormone-binding globulin, increased BMI > 25 kg/m2, and preconception impaired glucose tolerance were specific. While maternal outcomes were similar to pregnant women with only GDM, women with GDM and PCOS were even more likely to develop pregnancy-induced hypertension and early miscarriage. Neonates from mothers with GDM and PCOS were more likely to have low birth weights compared to mothers with just GDM who had high birth weights. The evaluation of the relationship between GDM and PCOS allows for illumination of the need to evaluate influences that currently lack research, such as phenotype variation and influences of fertilization method. This also promotes the need to develop predictive algorithms based on risk factors to prevent these adverse outcomes for mothers and neonates.
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Affiliation(s)
- Ethan Slouha
- Anatomical Sciences, St. George's University School of Medicine, St. George's, GRD
| | - Vanessa C Alvarez
- Pharmacology, St. George's University School of Medicine, St. George's, GRD
| | - Kaitlyn M Gates
- Pharmacology, St. George's University School of Medicine, St. George's, GRD
| | | | - Lucy A Clunes
- Pharmacology, St. George's University, St. George's, GRD
| | - Theofanis F Kollias
- Microbiology, Immunology, and Pharmacology, St. George's University School of Medicine, St. George's, GRD
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