Investigating the KNDy hypothesis in humans by co-administration of kisspeptin, neurokinin B and naltrexone in men

Context: A subpopulation of hypothalamic neurons co-localise three neuropeptides namely kisspeptin, neurokinin B (NKB) and dynorphin collectively termed KNDy neurons. Animal studies suggest they interact to affect pulsatile GnRH release (KNDy hypothesis); kisspeptin stimulates, NKB modulates and dynorphin (an opioid) inhibits. Objective: To investigate the KNDy hypothesis in humans, we assessed for the first time the effects of co-administration of kisspeptin-54, NKB and an opioid receptor antagonist, naltrexone on LH pulsatility (surrogate marker for GnRH pulsatility) and gonadotropin release. Design, setting and participants: Ethically approved prospective, single-blinded placebo-controlled study. Healthy male volunteers (n=5/group) attended our research facility for 8 study visits. Intervention and main outcome measure: After 1h baseline blood sampling, participants received a different intervention at each visit: oral 50mg naltrexone (NAL), 8h intravenous infusions of vehicle, 2.56nmol/kg/h NKB (NKB), 0.1nmol/kg/h kissspeptin-54 (KP) alone and in combination. Frequent blood sampling to measure plasma gonadotropins and sex steroids was conducted and LH pulsatility was determined using blinded deconvolution analysis. Results: All kisspeptin and naltrexone containing groups potently increased LH and LH pulsatility (p<0.001 vs vehicle). NKB alone did not affect gonadotropins. NKB+KP had significantly lower increases in gonadotropins compared with kisspeptin alone (p<0.01). NAL+KP was the only group to significantly increase LH pulse amplitude (p<0.001 vs vehicle). Conclusions: Our results suggest significant interactions between the KNDy neuropeptides on LH pulsatility and gonadotropin release in humans. This has important implications for improving our understanding of GnRH pulse generation in humans

Measuring luteinising hormone pulsatility with a robotic aptamer-enabled electrochemical reader

Normal reproductive functioning is critically dependent on pulsatile secretion of luteinising hormone (LH). Assessment of LH pulsatility is important for the clinical diagnosis of reproductive disorders, but current methods are hampered by frequent blood sampling coupled to expensive serial immunochemical analysis. Here, we report the development and application of a Robotic APTamer-enabled Electrochemical Reader (RAPTER) electrochemical analysis system to determine LH pulsatility. Through selective evolution of ligands by exponential enrichment (SELEX), we identify DNA aptamers that bind specifically to LH and not to related hormones. The aptamers are integrated into electrochemical aptamer-based (E-AB) sensors on a robotic platform. E-AB enables rapid, sensitive and repeatable determination of LH concentration profiles. Bayesian Spectrum Analysis is applied to determine LH pulsatility in three distinct patient cohorts. This technology has the potential to transform the clinical care of patients with reproductive disorders and could be developed to allow real-time in vivo hormone monitoring

Determining the relationship between hot flushes and LH pulses in menopausal women using mathematical modelling

Background Hypothalamic kisspeptin/neurokinin B/dynorphin (KNDy) neurones regulate LH pulsatility. It is widely accepted that the menopausal hot flush (HF) consistently synchronises with the LH pulse. This suggests that the hypothalamic KNDy neurones are implicated in generating LH pulsatility and HF. Using a modern immunoassay and mathematical modelling we investigated if the HF and LH pulse was consistently synchronised in menopausal women. Methods Eleven menopausal women (51-62yrs experiencing ≥7 HF/24hrs) attended for an 8 hour study where they self-reported HF and underwent peripheral blood sampling every 10 mins. LH pulsatility was determined using two mathematical models: blinded deconvolution analysis and Bayesian spectrum analysis. The probability that the LH pulse and HF event intervals matched was estimated using the interval distributions observed in our data. Results Ninety-six HF were self-reported, and 82 LH pulses were identified by blinded deconvolution analysis. Using both models, the probability that the two event intervals matched was low in the majority of participants (mean P=0.24 (P=1 reflects perfect association)). Interpretation Our data challenges the widely accepted dogma that HF consistently synchronise with an LH pulse, and so has clinically important therapeutic and mechanistic implications

HormoneBayes: A novel Bayesian framework for the analysis of pulsatile hormone dynamics

This is the final version.Available on open access from Public Library of Science via the DOI in this recordData Availability Statement: Code can be downloaded from https://git.exeter.ac.uk/mv286/hormonebayesThe hypothalamus is the central regulator of reproductive hormone secretion. Pulsatile secretion of gonadotropin releasing hormone (GnRH) is fundamental to physiological stimulation of the pituitary gland to release luteinizing hormone (LH) and follicle stimulating hormone (FSH). Furthermore, GnRH pulsatility is altered in common reproductive disorders such as polycystic ovary syndrome (PCOS) and hypothalamic amenorrhea (HA). LH is measured routinely in clinical practice using an automated chemiluminescent immunoassay method and is the gold standard surrogate marker of GnRH. LH can be measured at frequent intervals (e.g., 10 minutely) to assess GnRH/LH pulsatility. However, this is rarely done in clinical practice because it is resource intensive, and there is no open-access, graphical interface software for computational analysis of the LH data available to clinicians. Here we present hormoneBayes, a novel open-access Bayesian framework that can be easily applied to reliably analyze serial LH measurements to assess LH pulsatility. The framework utilizes parsimonious models to simulate hypothalamic signals that drive LH dynamics, together with state-of-the-art (sequential) Monte-Carlo methods to infer key parameters and latent hypothalamic dynamics. We show that this method provides estimates for key pulse parameters including inter-pulse interval, secretion and clearance rates and identifies LH pulses in line with the widely used deconvolution method. We show that these parameters can distinguish LH pulsatility in different clinical contexts including in reproductive health and disease in men and women (e.g., healthy men, healthy women before and after menopause, women with HA or PCOS). A further advantage of hormoneBayes is that our mathematical approach provides a quantified estimation of uncertainty. Our framework will complement methods enabling real-time in-vivo hormone monitoring and therefore has the potential to assist translation of personalized, data-driven, clinical care of patients presenting with conditions of reproductive hormone dysfunction.Engineering and Physical Sciences Research Council (EPSRC)Biotechnology and Biological Sciences Research Council (BBSRC)Medical Research Council (MRC)National Institute for Health and Care Research (NIHR)Expanding Excellence in England (E3) - Exeter Diabetes Research Uni

T cell and reticular network co-dependence in HIV infection

Fibroblastic reticular cells (FRC) are arranged on a network in the T cell zone of lymph nodes, forming a scaffold for T cell migration, and providing survival factors, especially interleukin-7 (IL- 7). Conversely, CD4+ T cells are the major producers of lymphotoxin-_ (LT-_), necessary for the construction and maintenance of the FRC network. This interdependence creates the possibility of a vicious cycle, perpetuating loss of both FRC and T cells. Furthermore, evidence that HIV infection is responsible for collagenation of the network suggests that long term loss of network function might be responsible for the attenuated recovery in T cell count seen in HIV patients undergoing antiretroviral therapy (ART). We present computational and mathematical models of this interaction mechanism and subsequent naive CD4+ T-cell depletion in which (1) collagen deposition impedes access of naive T cells to IL-7 on the FRC and loss of IL-7 production by loss of FRC network itself, leading to the depletion of naive T cells through increased apoptosis; and (2) depletion of naive T cells as the source of LT-_ on which the FRC depend for survival, leads to loss of the network, thereby amplifying and perpetuating the cycle of depletion of both naive T cells and stromal cells. Our computational model explicitly includes an FRC network and its cytokine exchange with a heterogeneous T-cell population. We also derive lumped models, in terms of partial differential equations and reduced to ordinary differential equations, that provide additional insight into the mechanisms at work. The central conclusions are that 1) damage to the reticular network, caused by HIV infection, is a plausible mechanism for attenuated recovery post-ART; 2) within this, the production of T cell survival factors by FRCs may be the key rate-limiting step; and 3) the methods of model reduction and analysis presented are useful for both immunological studies and other contexts in which agent-based models are severely limited by computational cost

Pharmacokinetic/pharmacodynamic modelling approaches in paediatric infectious diseases and immunology.

Pharmacokinetic/pharmacodynamic (PKPD) modelling is used to describe and quantify dose-concentration-effect relationships. Within paediatric studies in infectious diseases and immunology these methods are often applied to developing guidance on appropriate dosing. In this paper, an introduction to the field of PKPD modelling is given, followed by a review of the PKPD studies that have been undertaken in paediatric infectious diseases and immunology. The main focus is on identifying the methodological approaches used to define the PKPD relationship in these studies. The major findings were that most studies of infectious diseases have developed a PK model and then used simulations to define a dose recommendation based on a pre-defined PD target, which may have been defined in adults or in vitro. For immunological studies much of the modelling has focused on either PK or PD, and since multiple drugs are usually used, delineating the relative contributions of each is challenging. The use of dynamical modelling of in vitro antibacterial studies, and paediatric HIV mechanistic PD models linked with the PK of all drugs, are emerging methods that should enhance PKPD-based recommendations in the future