Background: Premutations in the Fragile X Messenger Ribonucleoprotein 1 (FMR1) gene, defined as between 55 and 200 CGGs, have been implicated in fragile X-associated primary ovarian insufficiency (FXPOI). Only 20% of female premutation carriers develop early ovulatory dysfunction, the reason for this incomplete penetrance is unknown. This study validated the mathematical model in premutation alleles, after assigning each allele a score representing allelic complexity. Subsequently, allelic scores were used to investigate the impact of allele complexity on age at amenorrhea for 58 premutation cases (116 alleles) previously published. Methods: The allelic score was determined using a formula previously described by our group. The impact of each allelic score on age at amenorrhea was analyzed using Pearson’s test and a contour plot generated to visualize the effect. Results: Correlation of allelic score revealed two distinct complexity behaviors in premutation alleles. No significant correlation was observed between the allelic score of premutation alleles and age at amenorrhea. The same lack of significant correlation was observed regarding normal-sized alleles, despite a nearly significant trend. Conclusions: Our results suggest that the use of allelic scores combination have the potential to explain female infertility, namely the development of FXPOI, or ovarian dysfunction, despite the lack of correlation with age at amenorrhea. Such a finding is of great clinical significance for early identification of females at risk of ovulatory dysfunction, enhancement of fertility preservation techniques, and increasing the probability for a successful pregnancy in females with premutations. Additional investigation is necessary to validate this hypothesis.

X-chromosome inactivation (XCI) is a developmental process to compensate the imbalance in the dosage of X-chromosomal genes in females. A skewing of the XCI pattern may suggest a carrier status for an X-linked disease or explain the presence of a severe phenotype. In these cases, it is important to determine the XCI pattern, conventionally using the gold standard Human Androgen-Receptor Assay (HUMARA), based on the analysis of the methylation status at a polymorphic CAG region in the first exon of the human androgen receptor gene (AR). The aim of this study was to evaluate whether the methylation status of the fragile mental retardation protein translational regulator gene (FMR1) can provide an XCI pattern similar to that obtained by HUMARA. A set of 48 female carriers of FMR1 gene normal-sized alleles was examined using two assays: HUMARA and a FMR1 methylation PCR (mPCR). Ranges were defined to establish the XCI pattern using the methylation pattern of the FMR1 gene by mPCR. Overall, a 77% concordance of the XCI patterns was obtained between the two assays, which led us to propose a set of key points and a stepwise analysis towards obtaining an accurate result for the XCI pattern and to minimize the underlying pitfalls.

We investigated whether FMR1 allelic complexity—integrating CGG repeat length with the number and pattern of AGG interspersions—can be used as a predictor of ovarian reserve and in vitro fertilization (IVF) success. This cohort study included 124 females with infertility attributed to female factors undergoing intracytoplasmic sperm injection (ICSI). The total CGG repeat lengths and AGG interspersion patterns of the FMR1 gene were determined by conventional polymerase chain reaction (PCR) and triplet-primed PCR. The allelic complexity (allelic score) was calculated using a previously described formula by combining the allelic scores, allowing for the stratification of samples into equivalent and dissimilar groups. No statistically significant differences were observed in ovarian reserve markers or overall IVF outcomes between the two groups. However, within the dissimilar group, the allelic score of allele 1 was significantly correlated with the number of both injected metaphase II and two-pronuclei oocytes. These findings suggest that FMR1 allelic complexity may contribute to predicting IVF success, particularly in females classified in the dissimilar group, who appear more susceptible to IVF failure than those in the equivalent group. Further research into the predictive utility of FMR1 could provide valuable insights for fertility assessment and enhance assisted reproductive technologies.

Premature ovarian insufficiency (POI) affects 1–3.7% of women and causes infertility and long-term morbidity. Next-generation sequencing has identified more than 130 POI-associated genes. The diagnostic yield of genetic testing depends on cohort size and the quality and scope of the genetic analysis, reaching 29.3% in our largest international cohort reported to date. Major biological pathways involve meiosis/DNA repair, follicular growth, and mitochondrial/metabolic functions. Meiosis/DNA-repair defects can impair fetal establishment of the ovarian reserve and, depending on the gene, variant, and allelic state, may be associated with chromosomal instability or cancer predisposition. This could enable early identification of selected at-risk patients, oncogenetic assessment, and cancer-prevention strategies. In contrast, alterations affecting follicular growth, metabolism, or mitochondrial function may be associated with persistence of a residual follicular pool, revealing a limited window of opportunity for timely fertility preservation in selected patients and at-risk relatives. Genetic diagnosis provides actionable information for etiological classification, and can reveal a syndromic condition, guide family screening, and, in selected genotypes, inform comorbidity assessment and early fertility preservation. It may also guide future mechanism-based therapies. By translating molecular findings into individualized reproductive and long-term care, POI provides a paradigmatic model of precision medicine in female infertility and reproductive endocrinology.