BACKGROUND. Resting brain connectivity is a crucial component of human behavior demonstrated by disruptions in psychosexual and emotional disorders. Kisspeptin, a recently identified critical reproductive hormone, can alter activity in certain brain structures but its effects on resting brain connectivity and networks in humans remain elusive. METHODS. We determined the effects of kisspeptin on resting brain connectivity (using functional neuroimaging) and behavior (using psychometric analyses) in healthy men, in a randomized double-blinded 2-way placebo-controlled study. RESULTS. Kisspeptin’s modulation of the default mode network (DMN) correlated with increased limbic activity in response to sexual stimuli (globus pallidus r = 0.500, P = 0.005; cingulate r = 0.475, P = 0.009). Furthermore, kisspeptin’s DMN modulation was greater in men with less reward drive (r = –0.489, P = 0.008) and predicted reduced sexual aversion (r = –0.499, P = 0.006), providing key functional significance. Kisspeptin also enhanced key mood connections including between the amygdala-cingulate, hippocampus-cingulate, and hippocampus–globus pallidus (all P < 0.05). Consistent with this, kisspeptin’s enhancement of hippocampus–globus pallidus connectivity predicted increased responses to negative stimuli in limbic structures (including the thalamus and cingulate [all P < 0.01]). CONCLUSION. Taken together, our data demonstrate a previously unknown role for kisspeptin in the modulation of functional brain connectivity and networks, integrating these with reproductive hormones and behaviors. Our findings that kisspeptin modulates resting brain connectivity to enhance sexual and emotional processing and decrease sexual aversion, provide foundation for kisspeptin-based therapies for associated disorders of body and mind. FUNDING. NIHR, MRC, and Wellcome Trust.
Alexander N. Comninos, Lysia Demetriou, Matthew B. Wall, Amar J. Shah, Sophie A. Clarke, Shakunthala Narayanaswamy, Alexander Nesbitt, Chioma Izzi-Engbeaya, Julia K. Prague, Ali Abbara, Risheka Ratnasabapathy, Lisa Yang, Victoria Salem, Gurjinder M. Nijher, Channa N. Jayasena, Mark Tanner, Paul Bassett, Amrish Mehta, John McGonigle, Eugenii A. Rabiner, Stephen R. Bloom, Waljit S. Dhillo
Usage data is cumulative from December 2023 through December 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 323 | 135 |
54 | 43 | |
Figure | 73 | 1 |
Supplemental data | 25 | 0 |
Citation downloads | 37 | 0 |
Totals | 512 | 179 |
Total Views | 691 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.