In both men and women, impaired glucose tolerance and cardiovascular risk factors have been implicated in fertility problems. Mendelian randomization (MR) is an important method that is based on genetic variables to measure potential causal effects without being affected by confounding factors.
A recent study posted to the medRxiv* preprint server utilized a two-sample MR-based approach to determine whether impaired glucose tolerance and cardiovascular disease risk factors lead to fertility problems.
Study: Impaired glucose tolerance and cardiovascular risk factors in relation to infertility: a Mendelian randomization analysis in the Norwegian Mother, Father and Child Cohort Study. Image Credit: Chinnapong / Shutterstock.com
*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
About the study
The researchers of the current study obtained data from the Norwegian Mother Father and Child Cohort Study (MoBa), which is a population-based pregnancy cohort designed by the Norwegian Institute of Public Health. This Norway-based cohort comprised pregnant women, who were at around 18 gestational weeks, as well as their partners, between 1999-2008.
The cohort consisted of 114,500 children, 75,200 fathers, and 95,200 mothers, of whom 68,882 women and 47,474 men were selected. The selected participants included singleton pregnancies who had available data on genotype and infertility.
Infertility was defined as couples who failed to conceive after 12 months of trying or those who utilized assisted reproductive technologies. For the control group, participants who easily conceived within 12 months were included.
In this study, about 12% of the couples reported infertility. These couples were more likely to be obese, of older age, have lower education status, and be smokers.
The genetic risk factors of impaired glucose metabolism, lipid profile, and blood pressure, based on independent single nucleotide polymorphisms (SNPs), were extracted from genome-wide association studies (GWASs).
Study findings
Based on the MR analysis, the genetically determined levels of fasting insulin, particularly in women, increased the likelihood of infertility. A higher level of maternal fasting glucose, glycated hemoglobin in women, and fasting insulin in men also increased the risk of infertility.
The prevalence of hyperinsulinemia, which is a biomarker for insulin resistance and glucose intolerance, has been previously associated with polycystic ovary syndrome (PCOS), which causes infertility. In addition, hyperinsulinemia is linked with impaired synthesis of sexual hormones in the follicle, including lower levels of progesterone and follicle-stimulating hormone and increased levels of androgens, along with follicular dysplasia.
Strengths and limitations
A key strength of this study includes the use of MR analysis for establishing the association between cardiometabolic risk factors and infertility. Additionally, in-depth MR analysis was conducted in a relatively homogeneous population, which was beneficial for drawing sound conclusions.
The current study has some limitations that include the inability to determine whether the underlying cause of infertility was in men, women, or both. Furthermore, the MoBa cohort only consisted of couples who conceived; thus, more studies, including couples who did not conceive are needed.
Since no sex-specific genetic instruments were available, the authors assumed that no sex differences prevailed. Nevertheless, this assumption may violate the first MP principle.
Taken together, the present study provided strong evidence that supported the hypothesis that hyperinsulinemia and glucose intolerance cause infertility in women. In the future, this observation must be validated with a larger study cohort.
*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.