A combined clinical and specific genes' model to predict live birth for in vitro fertilization and embryo transfer patients

Abstract

Background: We aimed to develop an accurate model to predict live birth for patients receiving in vitro fertilization and embryo transfer (IVF-ET) treatment.

Methods: This is a prospective nested case-control study. Women aged between 18 and 38 years, whose body mass index (BMI) were between the range of 18.5-24 kg/m², who had an endometrium of ≥ 8 mm at the thickest were enrolled from 2018/9 to 2020/8. All patients received IVF-ET treatment and were followed up until Jan. 2022 when they had reproductive outcomes. Endometrial samples during the window of implantation (LH + 6 to 9 days) were subjected to analyze specific endometrial receptivity genes' expression using real-time PCR (RT-PCR). Patients were divided into live birth group and non-live birth group based on IVF-ET outcomes. Clinical signatures relevant to live birth were collected, analyzed, and used to establish a predictive model for live birth by univariate analysis (clinical model). Specific endometrial receptivity genes' expression was analyzed, selected, and used to construct a predictive model for live birth by The Least Absolute Shrinkage and Selection Operator (LASSO) analysis (gene model). Finally, significant clinical factors and genes were used to construct a combined model for predicting live birth using multivariate logistical regression (combined model). Different models' Area Under Curve (AUC) were compared to identify the most predictive model.

Results: Thirty-nine patients were enrolled in the study, twenty-four patients had live births, fifteen did not. In univariate analysis, the odds of live birth for women with ovulation dysfunction was 4 times higher than that for women with other IVF-ET indications (OR = 4.0, 95% CI: 1.125 - 8.910, P = 0.018). Age, body mass index, duration of infertility, primary infertility, repeated implantation failure, antral follicle counting, ovarian sensitivity index, anti-Mullerian hormone, controlled ovarian hyperstimulation protocol and duration, total dose of FSH/hMG, number of oocytes retrieved, regiment of endometrial preparation, endometrium thickness before embryo transfer, type of embryo transferred were not associated with live birth (P > 0.05). Only ovulation dysfunction was used to construct the clinical model and its AUC was 0.688. In lasso analysis, GAST, GPX3, THBS2 were found to promote the risk of live birth. AUCs for GAST, GPX3, THBS2 reached to 0.736, 0.672, and 0.678, respectively. The gene model was established based on these three genes and its AUC was 0.772. Ovulation dysfunction, GAST, GPX3, and THBS2 were finally used to construct the combined model, reaching the highest AUC (AUC = 0.842).

Conclusions: Compared to the single model, the combined model of clinical (Ovulation dysfunction) and specific genes (GAST, GPX3, THBS2) was more accurate to predict live birth for IVF-ET patients.

Keywords: Endometrial receptivity; Gene expression; LASSO regression; Live birth; Ovulation dysfunction.

Fig. 1

The flow chart of the study design and analysis

Fig. 2

Results of univariate analysis of clinical features and live birth. Ovulation dysfunction was associated with live birth. Ovarian sensitivity index = log (number of eggs recovered × 1,000/total dose of FSH)

Fig. 3

The process of selecting targeted genes by LASSO regression model. The LASSO analysis includes 21 genes. When log lambda ranges from -1.0 to -3.0, three genes: GAST, GPX3, THBS2, were selected

Fig. 4

ROC curves for individual predictive genes and combined genes associated with live birth. AUC of single gene (AUC _GAST = 0.736, AUC_GPX3 = 0.672, AUC_THBS2 = 0.678) was lower than combined genes model (AUC = 0.772) in predicting live birth

Fig. 5

Comparison of predictive models for live birth. Risk model of clinical and gene features can achieve the highest accuracy (AUC = 0.842) compared with combined genes model (AUC = 0.772) and ovulation dysfunction model (AUC = 0.688) in predicting live birth