Circulating microRNAs in follicular fluid, powerful tools to explore in vitro fertilization process - PubMed (original) (raw)

Circulating microRNAs in follicular fluid, powerful tools to explore in vitro fertilization process

E Scalici et al. Sci Rep. 2016.

Abstract

Circulating or "extracellular" microRNAs (miRNAs) detected in biological fluids, could be used as potential diagnostic and prognostic biomarkers of several disease, such as cancer, gynecological and pregnancy disorders. However, their contributions in female infertility and in vitro fertilization (IVF) remain unknown. This study investigated the expression profiles of five circulating miRNAs (let-7b, miR-29a, miR-30a, miR-140 and miR-320a) in human follicular fluid from 91 women with normal ovarian reserve and 30 with polycystic ovary syndrome (PCOS) and their ability to predict IVF outcomes. The combination of FF miR-30a, miR-140 and let-7b expression levels discriminated between PCOS and normal ovarian reserve with a specificity of 83.8% and a sensitivity of 70% (area under the ROC curve, AUC = 0.83 [0.73-0.92]; p < 0.0001). FF samples related to low number of mature oocytes (≤2) contained significant less miR-320a levels than those related to a number of mature oocytes >2 (p = 0.04). Moreover, FF let-7b predicted the development of expanded blastocysts with 70% sensitivity and 64.3% specificity (AUC = 0.67 [0.54-0.79]; p = 0.02) and FF miR-29a potential to predict clinical pregnancy outcome reached 0.68 [0.55-0.79] with a sensitivity of 83.3% and a specificity of 53.5% (p = 0.01). Therefore, these miRNAs could provide new helpful biomarkers to facilitate personalized medical care during IVF.

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Figures

Figure 1

Figure 1. Comparison of the relative miRNA expression in follicular fluid (FF) pools from women with normal ovarian reserve (n = 91) and with polycystic ovary syndrome (PCOS, n = 30).

(A) FF miR-30a; (B) FF miR-140; (C) FF let-7b. P-values: Mann-Whitney test.

Figure 2

Figure 2

ROC curve analysis to calculate the discriminative power of the FF expression of (A) miR-30a; (B) miR-140; and (C) let-7b individually and (D) in combination to predict PCOS.

Figure 3

Figure 3

(A) Comparison of FF miR-29a and miR-140 expression level relative to the type of treatment (highly purified human menopausal gonadotropin, HP-hMG, versus recombinant follicle-stimulating hormone, r-FSH) (*p = 0.03; **p = 0.02). (B) Differential FF miR-140 expression according to the total dose of gonadotropins (<3000 versus ≥3000 IU/l) (*p = 0.03). (**C**) Comparison of FF miR-320a expression level relative to the number of retrieved mature oocytes (≤2 versus >2 mature oocytes) (*p = 0.04). These analyses included only the group of women with normal ovarian reserve (n = 91). P-values: Mann-Whitney test.

Figure 4

Figure 4

(A) ROC analysis to evaluate FF let-7b expression predictive value for blastocyst formation. (B) ROC analysis to evaluate FF let-7b expression predictive value for expanded blastocyst development. These analyses included only the group of women with normal ovarian reserve (n = 91).

Figure 5

Figure 5

(A) ROC analysis to evaluate FF miR-29a expression predictive value for clinical pregnancy outcome. (B) Comparison of the ROC curves showing the predictive value of FF miR-29a expression and top quality embryo proportion for clinical pregnancy outcome. These analyses included only the group of women with normal ovarian reserve (n = 91).

Figure 6

Figure 6. Schematic model showing that miRNA expression profiling in FF samples provides powerful tools to efficiently discriminate women with polycystic ovary syndrome (PCOS) and to predict IVF outcomes.

The expression of some FF miRNAs varies according to the gonadotropin treatment. HP-hMG, highly purified human menopausal gonadotropin; r-FSH, recombinant follicle-stimulating hormone.

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