The results of this study demonstrate that controlled ovarian stimulation influences the metabolic signature of human serum, especially in the amino acid pathway, lipid pathway and fatty acid pathway. For the first time, we established a model of serum metabolites to predict response to controlled ovarian stimulation, as judged by FOI. We found that glycine and acetylglycine, combined with lipids, can predict different responses to controlled ovarian stimulation.
A proper response to ovarian stimulation is crucial for IVF success. The Follicle-to-oocyte index (FOI), as a qualitative marker, can reflect the nature of follicle growth and its response to gonadotropin [11]. This index is usually applied to describe women who have a hypo-response to ovarian stimulation and to predict the success of IVF cycles for these women [12]. In general, a normal FOI is defined as > 0.5 and low as ≤ 0.5 [6]. Nevertheless, accurate biomarkers that can predict the response to ovarian stimulation are still needed for women with a normal or hyper response such that proper oocytes and better clinical results can be obtained. The patients in our research were all young and had good ovarian reserve; for all, there were at least thirteen antral follicle counts and eleven follicles retrieved. Therefore, we used FOI ≥1 and FOI < 1 to separate groups.
Glycine is a conditional essential amino acid for humans [13], and deficiency in this amino acid causes immune defects, low growth rates and altered nutrient metabolism [14]. Moreover, low circulating glycine has been associated with type 2 diabetes [15], insulin resistance [16] and metabolic syndrome [17]. Glucose metabolism is critical for follicle growth. Cumulus cells convert glucose to pyruvate; and lactate, which are then metabolized via the tricarboxylic pathway (TCA) followed by oxidative phosphorylation to provide the energy needed for oocyte development [18,19]. Any alteration in glucose metabolism may affect follicular growth. Insulin is produced by pancreatic beta cells, increasing plasma glucose levels [20]. Insulin resistance correlates with a decrease in insulin sensitivity and disables the ability of cells to take up and utilize glucose [21]. A higher concentration of insulin, which correlates with T2DM and metabolic syndrome, dose not elicit an appropriate response to stimulate glycogen synthesis [22] and causes abnormal follicle development. Our study found lower circulating glycine in patients with FOI < 1, which would result in a poor response to ovarian stimulation via glucose metabolism pathway. This founding was in accordance with the study of Chahal, et al [23].
Phosphatidylcholines (PCs), a kind of lipid, play vital roles in membrane construction and energy storage. One study [24] compared the follicular fluid between poor and normal responders and found increased PCs in the latter, suggesting that alterations in lipid balance might reflect ovarian response to hormones. Follicle fluid lipid profiling also demonstrated that PCs are increased in PCOS patients and those with hyper response to controlled ovarian stimulation compared to subject with a normal COS response [25]. Interestingly, our results also showed abundant PCs in women with FOI ≥1, and PC is an accurate biomarker able to predict response to controlled ovarian stimulation, in accordance with Montani’s research [26]. A possible explanation for this is the increase LH that accompanies the development of follicles, which may stimulate PC generation. Increased PC in human cumulus cells may be a consequence of a proper response to LH administration during IVF [27]. Moreover, two previous studies have demonstrated that LH supplementation influences follicular fluid steroid composition and contributes to improving of ovarian response in poor- responding women [28,29].
There are some limitations in our study. First, this was a retrospective study, which might cause some selection bias. However, the baseline characteristics of the patients were comparable between the two groups, which would minimize selection bias. Second, although our data indicated some alterations in the amino pathway, further investigations using large sample size are still needed for confirmation.
In conclusion, our study shows that serum metabolism can reflect the response to ovarian stimulation. Higher glycine and PC may be good predictors of response to gonadotropin in ovarian stimulation via glycose and lipid pathways. Further randomized controlled trials may provide strong proof for this, and new therapies will be explored to improve the outcome of controlled ovarian stimulation.