Serotonin 2A (5-HT2A) receptors and dopamine D2 receptors are intimately related to the physiology and pathophysiology of neuropsychiatric disorders. A large number of studies have reported the effectiveness of psychotropic agents targeting 5-HT2A and D2 receptors in these disorders. In addition to the individual functions of these receptors, the interaction between the two neurotransmitter systems has been studied in the living brain. However, little is known about their regional relationship in individual human brains. We investigated regional relationships between 5-HT2A and D2 receptors using positron emission tomography (PET) and a bicluster analysis of the correlation matrix of individual variation in the two receptor densities to identify groups of distinctive regional correlations between the two receptors. Methods: Seven healthy volunteers underwent PET scans with [18F]altanserin and [11C]FLB 457 for 5-HT2A and D2 receptors, respectively. As a measure of receptor density, a binding potential (BP) was calculated from PET data for 76 cerebral cortical regions. A correlation matrix was calculated between the binding potentials of [18F]altanserin and [11C]FLB 457 for those regions. The regional relationships were investigated using a bicluster analysis of the correlation matrix with an iterative signature algorithm. Results: We identified two clusters of regions. The first cluster identified a distinct profile of correlation coefficients between 5-HT2A and D2 receptors, with the former in regions related to sensorimotor integration (supplementary motor area, superior parietal gyrus, and paracentral lobule) and the latter in most cortical regions. The second cluster identified another distinct profile of correlation coefficients between 5-HT2A receptors in the bilateral hippocampi and D2 receptors in most cortical regions. Conclusions: The observation of two distinct clusters in the correlation matrix suggests regional interactions between 5-HT2A and D2 receptors in sensorimotor integration and hippocampal function. A bicluster analysis of the correlation matrix of these neuroreceptors may be beneficial in understanding molecular networks in the human brain.
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