Variability in follicular fluid high density lipoprotein particle components measured in ipsilateral follicles

Contribution of key elements of nutritional metabolism to the development of cystic ovarian disease in dairy cattle

The alteration of signaling molecules involved in the general metabolism of animals can negatively influence reproduction. In dairy cattle, the development of follicular cysts and the subsequent appearance of ovarian cystic disease (COD) often lead to decreased reproductive efficiency in the herd. The objective of this review is to summarize the contribution of relevant metabolic and nutritional sensors to the development of COD in dairy cows. In particular, we focus on the study of alterations of the insulin signaling pathway, adiponectin, and other sensors and metabolites relevant to ovarian functionality, which may be related to the development of follicular persistence and follicular formation of cysts in dairy cattle. The results of these studies support the hypothesis that systemic factors could alter the local scenario in the follicle, generating an adverse microenvironment for the resumption of ovarian activity and possibly leading to the persistence of follicles and to the development and recurrence of COD.

Characterizing the follicular fluid metabolome: quantifying the correlation across follicles and differences with the serum metabolome

OBJECTIVE

To compare the variability in metabolomes between the serum and follicular fluid, as well as across 3 dominant follicles.

DESIGN

Prospective cohort study.

SETTING

An academic fertility clinic in the northeastern United States, 2005-2015.

PATIENTS

One hundred thirty-five women undergoing in vitro fertilization treatment who provided a serum sample during ovarian stimulation and up to 3 follicular fluid samples during oocyte retrieval.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Samples were analyzed using liquid chromatography with high-resolution mass spectrometry and 2 chromatography columns (C18 hydrophobic negative and hydrophilic interaction chromatography [HILIC] positive). We calculated overall, feature-specific, and subject-specific correlation coefficients to describe how strongly the intensity of overlapping metabolic features were associated between the serum and follicular fluid and between the 1st-2nd, 1st-3rd, and 2nd-3rd follicles. Feature-specific correlations were adjusted for age, body mass index, infertility diagnosis, ovarian stimulation protocol, and year.

RESULT(S)

From the C18-negative column and the high-resolution mass spectrometry, 7,830 serum features and 10,790 follicular fluid features were detected in ≥20% of samples. After screening retention times and checking for 1:1 matching, 1,928 features overlapped between the 2 metabolomes. From the HILIC-positive column and the high-resolution mass spectrometry, after applying the same exclusion criteria, there were 9,074 serum features, 5,542 follicular fluid features, and 1,149 features that overlapped. When comparing the feature intensity of overlapping metabolites in the serum and the follicular fluid, the overall (C18, 0.45; HILIC, 0.63), median feature-specific (C18, 0.35; HILIC, 0.37), and median subject-specific (C18, 0.42; HILIC, 0.59) correlations were low to moderate. In contrast, among the overlapping features across all 3 follicles, the overall (C18, all 0.99; HILIC, all 0.99), median feature-specific (C18, 0.74-0.81; HILIC, 0.79-0.85), and median subject-specific (C18, 0.88-0.89; HILIC, 0.90-0.91) correlations between follicular fluid metabolomics features within a woman were high.

CONCLUSION(S)

We observed minimal overlap and weak-to-moderate correlation between metabolomic features in the serum and follicular fluid but a large overlap and strong correlation between metabolomic features across follicles within a woman. The follicular fluid appears to represent a novel matrix, distinct from serum, which may be a rich source of biologic predictors of female fertility and reproductive outcomes.

Associations between PON1 enzyme activities in human ovarian follicular fluid and serum specimens

The importance of high-density lipoprotein (HDL) particle components to reproduction is increasingly recognized, including the constituent paraoxonase 1 (PON1). However, the reliability characteristics of PON1 enzymes in ovarian follicular fluid (FF) as biomarkers for clinical and epidemiologic studies have not been described. Therefore, we characterized PON1 enzymes in FF and serum and assessed the impact of the PON1 Q192R polymorphism on associations between enzyme activities in two compartments. We also evaluated associations between HDL particle size and enzyme activities. We collected FF and serum from 171 women undergoing in vitro fertilization. PON1 activities were measured as paraoxonase and arylesterase activities, and HDL particle size was determined by ¹H NMR spectrometry. Reliability indices for PON1 activities were characterized and we evaluated HDL particle sizes as predictors of PON1 enzyme activities. We found that PON1 enzyme activities were correlated between compartments, but higher in serum than in FF. For FF, the index of individuality (II) was low and the coefficient of variation (CV%) was high for paraoxonase activity overall (0.12 and 11.51%, respectively). However, IIs increased (0.33–1.30) and CV%s decreased (5.58%-8.52%) when stratified by PON1 Q192R phenotype. The intraclass correlation coefficient (ICC) for FF paraoxonase activity was high overall (0.89) but decreased when stratified by PON1 Q192R phenotype (0.43–0.75). We found similar, although more modest, patterns for FF arylesterase activity. For enzyme activities in serum, ICCs were close to 1.00 across all phenotypes. Additionally, different HDL particle sizes predicted PON1 enzyme activities according to PON1 Q192R phenotype. Overall, stratification by PON1 Q192R phenotype improved the reliability characteristics of FF PON1 enzymes as biomarkers for use in clinical investigations but diminished usefulness for epidemiologic studies. Thus, we recommend stratification by PON1 Q192R phenotype for clinical but not epidemiologic investigations, when employing FF PON1 enzyme activity biomarkers.