Mode of pulsatile follicle-stimulating hormone secretion in gonadal hormone-sufficient and -deficient women--a clinical research center study

Ultradian rhythms in heart rate variability and distal body temperature anticipate onset of the luteinizing hormone surge

The menstrual cycle is characterized by predictable patterns of physiological change across timescales. Although patterns of reproductive hormones across the menstrual cycle, particularly ultradian rhythms, are well described, monitoring these measures repeatedly to predict the preovulatory luteinizing hormone (LH) surge is not practical. In the present study, we explored whether non-invasive measures coupled to the reproductive system: high frequency distal body temperature (DBT), sleeping heart rate (HR), sleeping heart rate variability (HRV), and sleep timing, could be used to anticipate the preovulatory LH surge in women. To test this possibility, we used signal processing to examine these measures in 45 premenopausal and 10 perimenopausal cycles alongside dates of supra-surge threshold LH and menstruation. Additionally, urinary estradiol and progesterone metabolites were measured daily surrounding the LH surge in 20 cycles. Wavelet analysis revealed a consistent pattern of DBT and HRV ultradian rhythm (2-5 h) power that uniquely enabled anticipation of the LH surge at least 2 days prior to its onset in 100% of individuals. Together, the present findings reveal fluctuations in distal body temperature and heart rate variability that consistently anticipate the LH surge, suggesting that automated ultradian rhythm monitoring may provide a novel and convenient method for non-invasive fertility assessment.

Evidence for a Coupled Oscillator Model of Endocrine Ultradian Rhythms

Whereas long-period temporal structures in endocrine dynamics have been well studied, endocrine rhythms on the scale of hours are relatively unexplored. The study of these ultradian rhythms (URs) has remained nascent, in part, because a theoretical framework unifying ultradian patterns across systems has not been established. The present overview proposes a conceptual coupled oscillator network model of URs in which oscillating hormonal outputs, or nodes, are connected by edges representing the strength of node-node coupling. We propose that variable-strength coupling exists both within and across classic hormonal axes. Because coupled oscillators synchronize, such a model implies that changes across hormonal systems could be inferred by surveying accessible nodes in the network. This implication would at once simplify the study of URs and open new avenues of exploration into conditions affecting coupling. In support of this proposed framework, we review mammalian evidence for (1) URs of the gut-brain axis and the hypothalamo-pituitary-thyroid, -adrenal, and -gonadal axes, (2) UR coupling within and across these axes; and (3) the relation of these URs to body temperature. URs across these systems exhibit behavior broadly consistent with a coupled oscillator network, maintaining both consistent URs and coupling within and across axes. This model may aid the exploration of mammalian physiology at high temporal resolution and improve the understanding of endocrine system dynamics within individuals.

AutoDecon, a deconvolution algorithm for identification and characterization of luteinizing hormone secretory bursts: description and validation using synthetic data

Hormone signaling is often pulsatile, and multiparameter deconvolution procedures have long been used to identify and characterize secretory events. However, the existing programs have serious limitations, including the subjective nature of initial peak selection, lack of statistical verification of presumed bursts, and user-unfriendliness of the application. Here we describe a novel deconvolution program, AutoDecon, which addresses these concerns. We validate AutoDecon for application to serum luteinizing hormone (LH) concentration time series using synthetic data mimicking real data from normal women and then comparing the performance of AutoDecon with the performance of the widely employed hormone pulsatility analysis program Cluster. The sensitivity of AutoDecon is higher than that of Cluster ( approximately 96% vs. 80%, P=0.001). However, Cluster had a lower false-positive detection rate than did AutoDecon (6% vs. 1%, P=0.001). Further analysis demonstrated that the pulsatility parameters recovered by AutoDecon were indistinguishable from those characterizing the synthetic data and that sampling at 5- or 10-min intervals was optimal for maximizing the sensitivity rates for LH. Accordingly, AutoDecon presents a viable nonsubjective alternative to previous pulse detection algorithms for the analysis of LH data. It is applicable to other pulsatile hormone concentration time series and many other pulsatile phenomena. The software is free and downloadable at http://mljohnson.pharm.virginia.edu/home.html.

Follicle-stimulating hormone is secreted more irregularly than luteinizing hormone in both humans and sheep

Recently introduced statistical tools capable of discerning differences between the pattern of luteinizing hormone (LH) secretion and that of follicle-stimulating hormone (FSH) could be valuable in understanding ovulation and menopause, and ultimately in making diagnostic decisions and treating infertility and polycystic ovary syndrome. We assessed the validity and scope of the hypothesis that FSH is secreted more irregularly than LH in ewes and fertile women. We compared secretory irregularity of LH to that of FSH in both ovariectomized ewes (n = 7) and women of proven fertility (n = 5) during the follicular and luteal phases of their reproductive cycles. In each sheep, time series from both hypophyseal portal blood (HPB) and peripheral blood were evaluated in 72 samples obtained every 5 min; in each human, both luteal and follicular periods were studied in 192 samples obtained every 7.5 min. To quantify serial irregularity, we used approximate entropy (ApEn), a scale- and model-independent statistic. FSH secretion was consistently more irregular than that of LH in each subject. For sheep HPB, ApEn(FSH) = 1.415+/-0.097 was larger than ApEn(LH) = 0. 822+/-0.213, P < 0.0001 (mean+/-SD, paired t test). This difference persisted peripherally: ApEn(FSHper) = 1.431+/-0.101 > ApEn(LHper) = 1.252+/-0.086, P = 0.024. In women, ApEn(FSH) = 1.467+/-0.217 > ApEn(LH) = 0.923+/- 0.305, P < 0.0001. ApEn(FSH) > ApEn(LH) in 100% of women (peripheral) and sheep HPB. Secretion during the follicular phase was more irregular than during the luteal phase for both FSH and LH (P < 0.01). LH mean level secretion showed a wake/sleep difference in women, P < 0.005, with higher values awake. The consistency and statistical significance of these findings suggest that this LH/FSH difference may be broadly based within higher mammals. Ranges of normative and abnormal regularity values of LH, FSH, and their difference can be used in a number of settings, both (currently) research and (potentially ultimately) clinical milieus.