Assessment of THADA gene polymorphisms in a sample of Colombian women with polycystic ovary syndrome: A pilot study

Association of candidate gene (INSR & THADA) polymorphism with polycystic ovary syndrome: meta-analysis and statistical power analysis

Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder that impacts women before reaching menopause. In addition to notable features (irregular ovulation, elevated androgen levels, and the existence of numerous ovarian cysts), individuals with PCOS frequently encounter diverse metabolic, cardiovascular, and psychological conditions. The onset of PCOS is influenced by a combination of factors, and various genetic variations are believed to play a significant role in its progression. The objective of the current study was to explore the link between genetic variations in the candidate genes thyroid-adenoma-associated (THADA) gene and insulin receptor (INSR) and susceptibility to developing PCOS. We conducted an extensive search across various databases, including Google Scholar, PubMed, Science Direct, Scopus, and EMBASE, to compile relevant case-control studies and literature reviews for subsequent statistical analysis. In the present study, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was followed, a guideline for Systematic Reviews and Meta-Analysis. While a previous meta-analysis explored the correlation between INSR rs1799817 and THADA rs13429458 and their association with susceptibility to PCOS, our current study did not integrate any findings from these prior investigations. Our research encompassed articles published between 2017 and 2023, and we employed MetaGenyo software to assess the collected data. Statistical power analysis was performed using G*Power 3.1 software. Odds ratios and their corresponding 95% confidence intervals were calculated for each genetic model. Fifteen studies that met the criteria were analyzed. Out of these, ten studies, involving 1,189 cases and 1,005 controls, examined the INSR rs1799817 gene polymorphism, while five studies, including 783 cases and 553 controls, investigated the THADA rs13429458 gene polymorphism. The meta-analysis results indicated that there was no statistically significant association between the INSR rs1799817 gene polymorphism and the risk of PCOS (p>0.05). In contrast, the THADA rs13429458 gene polymorphism showed a significant association with PCOS risk under the over-dominant model (p<0.05). The present meta-analysis demonstrated a notable association between the THADA rs13429458 gene polymorphism and the likelihood of developing PCOS. Further rigorous studies with expanded sample sizes and diverse ethnic representation will be important to comprehensively evaluate and validate these findings.

Exploring Genetic Interactions in Colombian Women with Polycystic Ovarian Syndrome: A Study on SNP-SNP Associations

Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disorder with high prevalence in women around the world. The identification of single-nucleotide polymorphisms (SNPs) through genome-wide association studies has classified it as a polygenic disease. Most studies have independently evaluated the contribution of each SNP to the risk of PCOS. Few studies have assessed the effect of epistasis among the identified SNPs. Therefore, this exploratory study aimed to evaluate the interaction of 27 SNPs identified as risk candidates and their contribution to the pathogenesis of PCOS. The study population included 49 control women and 49 women with PCOS with a normal BMI. Genotyping was carried out through the MassARRAY iPLEX single-nucleotide polymorphism typing platform. Using the multifactor dimensionality reduction (MDR) method, the interaction between SNPs was evaluated. The analysis showed that the best interaction model (p < 0.0001) was composed of three loci (rs11692782-FSHR, rs2268361-FSHR, and rs4784165-TOX3). Furthermore, a tendency towards synergy was evident between rs2268361 and the SNPs rs7371084-rs11692782-rs4784165, as well as a redundancy in rs7371084-rs11692782-rs4784165. This pilot study suggests that epistasis may influence PCOS pathophysiology. Large-scale analysis is needed to deepen our understanding of its impact on this complex syndrome affecting thousands of women.

Population Pharmacokinetic Analysis of Follicle-Stimulating Hormone During Ovarian Stimulation: Relation with Weight, Prolactin and Gene Polymorphism in THADA and ADIPOQ

BACKGROUND

Personalisation strategies of ovarian stimulation for in vitro fertilisation (IVF)/ intracytoplasmic sperm injection (ICSI) treatments using exogenous follicle-stimulating hormone (FSH) have been extensively studied over the past 20 years. This research aimed to develop a FSH population pharmacokinetic (PPK) model taking into account the contribution of gene polymorphisms in Chinese reproductive-age women.

METHODS

Data from 173 patients undergoing GnRH agonist down-regulation long protocols of IVF/ICSI treatment were collected. PPK analysis was subsequently conducted using the nonlinear mixed-effect model (NONMEM) software. Several covariates, including 18 single nucleotide polymorphisms, demographic factors and biological characteristics, were evaluated. The final PPK model was extensively validated using bootstrapping and normalised prediction error distribution, as well as external validation on an independent group of 35 patients.

RESULTS

FSH PPK was accurately described by a one-compartment model with first-order absorption. The typical population value of apparent clearance was estimated to be 0.81 L/h [relative standard errors (RSE) 5.3%] with an inter-individual variability (IIV) of 16.0%. The typical apparent distribution volume was 8.36 L (RSE 9.7%, 59.7% IIV), and the absorption rate constant was estimated to be 0.0444 h-1 (RSE 9.1%). Body weight, basal prolactin concentration and the gene ADIPOQ (rs1501299) showed a significant covariate effect on the FSH clearance rate and exposure concentration. Genotypes of THADA (rs12478601) significantly influenced the distribution volume. Simulation results indicated that patients with the TT genotype of THADA (rs12478601) required a longer time to reach steady state and had less fluctuation in FSH levels. Model evaluations showed that the final model accurately and precisely described the observed data and demonstrated effective prediction performance.

CONCLUSION

PPK models of FSH have been developed, which could potentially be used for FSH dosage individualisation in the clinical setting.

CLINICAL TRIAL REGISTRATION

This study has been registered with the Chinese Clinical Trials Registry (ChiCTR2100049142).