Biological variability in serum anti-Müllerian hormone throughout the menstrual cycle in ovulatory and sporadic anovulatory cycles in eumenorrheic women.

STUDY QUESTION: Does serum anti-Müllerian hormone (AMH) vary significantly throughout both ovulatory and sporadic anovulatory menstrual cycles in healthy premenopausal women? SUMMARY ANSWER: Serum AMH levels vary statistically significantly across the menstrual cycle in both ovulatory and sporadic anovulatory cycles of healthy eumenorrheic women. WHAT IS KNOWN ALREADY: Studies to date evaluating serum AMH levels throughout the menstrual cycle have conflicting results regarding intra-woman cyclicity. No previous studies have evaluated an association between AMH and sporadic anovulation. STUDY DESIGN, SIZE, DURATION: We conducted a prospective cohort study of 259 regularly menstruating women recruited between 2005 and 2007. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women aged 18-44 years were followed for one (n = 9) or two (n = 250) menstrual cycles. Anovulatory cycles were defined as any cycle with peak progesterone concentration ≤5 ng/ml and no serum LH peak on the mid or late luteal visits. Serum AMH was measured at up to eight-time points throughout each cycle. MAIN RESULTS AND THE ROLE OF CHANCE: Geometric mean AMH levels were observed to vary across the menstrual cycle (P < 0.01) with the highest levels observed during the mid-follicular phase at 2.06 ng/ml, decreasing around the time of ovulation to 1.79 ng/ml and increasing thereafter to 1.93 (mid-follicular versus ovulation, P < 0.01; ovulation versus late luteal, P = 0.01; mid-follicular versus late luteal, P = 0.05). Patterns were similar across all age groups and during ovulatory and anovulatory cycles, with higher levels of AMH observed among women with one or more anovulatory cycles (P = 0.03). LIMITATIONS, REASONS FOR CAUTION: Ovulatory status was not verified by direct visualization. AMH was analyzed using the original Generation II enzymatically amplified two-site immunoassay, which has been shown to be susceptible to assay interference. Thus, absolute levels should be interpreted with caution, however, patterns and associations remain consistent and any potential bias would be non-differential. WIDER IMPLICATIONS OF THE FINDINGS: This study demonstrates a significant variation in serum AMH levels across the menstrual cycle regardless of ovulatory status. This variability, although statistically significant, is not large enough to warrant a change in current clinical practice to time AMH measurements to cycle day/phase. STUDY FUNDING/COMPETING INTERESTS: This research was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD (Contracts # HHSN275200403394C, HHSN275201100002I Task 1 HHSN27500001). The authors have no conflicts of interest to declare.

Estimation of gene-environment interaction by pooling biospecimens.

Case-control studies are prone to low power for testing gene-environment interactions (GXE) given the need for a sufficient number of individuals on each strata of disease, gene, and environment. We propose a new study design to increase power by strategically pooling biospecimens. Pooling biospecimens allows us to increase the number of subjects significantly, thereby providing substantial increase in power. We focus on a special, although realistic case, where disease and environmental statuses are binary, and gene status is ordinal with each individual having 0, 1, or 2 minor alleles. Through pooling, we obtain an allele frequency for each level of disease and environmental status. Using the allele frequencies, we develop a new methodology for estimating and testing GXE that is comparable to the situation when we have complete data on gene status for each individual. We also explore the measurement process and its effect on the GXE estimator. Using an illustration, we show the effectiveness of pooling with an epidemiologic study, which tests an interaction for fiber and paraoxonase on anovulation. Through simulation, we show that taking 12 pooled measurements from 1000 individuals achieves more power than individually genotyping 500 individuals. Our findings suggest that strategic pooling should be considered when an investigator designs a pilot study to test for a GXE.