The amygdala, a key upstream regulator of the hypothalamic GnRH pulse generator
Lead Research Organisation:
UNIVERSITY OF EXETER
Department Name: Mathematics
Abstract
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Technical Summary
The GnRH pulse generator, the central regulator of the reproduction, comprises KNDy neurones in the hypothalamic arcuate nucleus. Stress suppresses this KNDy neural oscillator, but the underlying mechanisms are not well established. This project will focus on the amygdala, a part of the limbic brain typically associated with emotions and anxiety, which has strong projections to the KNDy system. Our discovery that kisspeptin signalling in the amygdala is an upstream regulator of GnRH pulse generator frequency, has facilitated the recent surge of interest in the amygdala's control of reproduction. We have shown in preliminary studies that amygdala kisspeptin operates through GABAergic signalling and that psychological stress-induced suppression of GnRH pulse generator is mediated by urocortin 3 in the amygdala. Recent developments in intersectional genetically encoded tools have enabled independent manipulation of a least two variables (eg. using Cre- or Flp-dependent constructs) in the same mouse. Capitalising these tools, this project will use simultaneous in-vivo optogenetic manipulation and gradient-index (GRIN) lens microendoscopic monitoring of GCaMP-expressing neurones in combination with mathematical modelling to, (i) examine the functional relationship between kisspeptin, GABA and glutamate neurocircuitry within the amygdala that underlies upstream regulation of hypothalamic GnRH pulse generator frequency, (ii) interrogate how the KNDy oscillator integrates the dynamic tone of inhibitory GABAergic and stimulatory glutamatergic output projections from the amygdala to regulate its rhythmic frequency, and (iii) determine how stress activated urocortin 3 neurones regulate the kisspeptin-GABA/glutamate neurocircuits in the amygdala to suppress GnRH pulse generator frequency. These studies will improve our understanding of how the higher-order limbic brain regulates the hypothalamic GnRH pulse generator that contributes to stress-dependent suppression of fertility.
Organisations
Publications
Ivanova D
(2024)
NK3R signalling in the posterodorsal medial amygdala is involved in stress-induced suppression of pulsatile LH secretion in female mice
in Journal of Neuroendocrinology
Lass G
(2022)
GnRH pulse generator frequency is modulated by kisspeptin and GABA-glutamate interactions in the posterodorsal medial amygdala in female mice.
in Journal of neuroendocrinology
Nechyporenko K
(2024)
Neuronal network dynamics in the posterodorsal amygdala: shaping reproductive hormone pulsatility.
in Journal of the Royal Society, Interface
Plain Z
(2022)
Modelling KNDy neurons and gonadotropin-releasing hormone pulse generation.
in Current opinion in endocrine and metabolic research
| Description | LEAP (Leadership Engagement Acceleration & Partnership) - an EPSRC Digital Health Hub |
| Amount | £3,290,617 (GBP) |
| Funding ID | EP/X031349/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 09/2023 |
| End | 09/2026 |
| Description | Lorentz Center workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Other audiences |
| Results and Impact | Uncertainty Quantification for Healthcare and Biological Systems Monday 17 till Friday 21 April 2023 Lorentz Center@Snellius The Netherlands Computer models of biological systems have proven to be useful in underpinning complex diseases with the potential to support clinical decisions from designing the personalised healthcare solutions for patients with deliberating health problems to performing in silico clinical trials. However, incorporating computer models into the clinical settings must be done in a robust, transparent and formalised way with a proper consideration of the various sources of uncertainty. Uncertainty Quantification is a field that focuses around quantifying and taking account of uncertainties for mathematical and computer models that describe real-world processes with engineering and physical models being well represented in the field. Healthcare and biological systems models differ significantly from the complex computer models traditionally considered in UQ, and therefore quantifying the uncertainty in healthcare models can pose very different challenges. The aim of this workshop is to identify UQ challenges for mechanistic healthcare models by bringing applied mathematicians, statisticians and healthcare modelers together. |
| Year(s) Of Engagement Activity | 2023 |
| URL | https://www.lorentzcenter.nl/uncertainty-quantification-for-healthcare-and-biological-systems.html |
| Description | Times Higher Education's Digital Universities UK 2024, |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Professional Practitioners |
| Results and Impact | Enabling international and interdisciplinary collaboration in research with digital tools Digital technologies have made it easier for researchers to collaborate across distances and disciplines. This session will bring together leaders of research and innovation in universities to determine how to take advantage of the numerous benefits that collaboration offers. Collaborating on platforms and online resources to facilitate easy sharing and access to research resources Fostering global collaborations and accessing international funding Supporting interdisciplinary collaborations across common digital platforms to drive innovation and simplify coordination, communication and data sharing Taking advantage of open science platforms to share research findings, collaborate with other researchers and engage with the broader public |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.timeshighered-events.com/digital-universities-uk-2024/agenda/speakers/3230450 |