Computational Convergence of Functional and Neurochemical Fingerprints of Psychiatric Drugs
Psychiatric conditions such as depression, schizophrenia, addiction and others produce the largest global burden of disease. These disorders are difficult to treat and despite the fact that more than 100 psychiatric medications are in clinical use the treatment success is modest. For optimal drug development it is critical to understand the effects of drugs on brain network activity and neurochemistry. Preclinical functional magnetic resonance imaging (fMRI) is an emerging approach to study brain network function in relation to pharmacological manipulations and disease models with a high translational value. The neural basis of neuroimaging signals is probably neuronal activity but the role of the underlying neurochemistry, defined here by the interaction of synaptic inhibition, excitation, and the neurochemical responses of the targeted neurons, is not well understood. While both functional and neurochemical investigations of drug effects suggest the presence of substance-specific activity patterns, it remains unclear how the functional observations reflect the underlying neurochemical processes.
The aim of this project is to develop a novel in silico framework to study convergent mechanisms of drug-induced MRI driven functional activity patterns and neurochemical fingerprints in the rat brain based on already existing databases for a variety of psychiatric medications.
This approach will
- (i) integrate the different system levels and multi-dimensional network activity patterns into a unified framework,
- (ii) will link global and local network activity with underlying neurochemical events and changes in connectivity,
- (iii) will provide better predictions of the effects of a new potential drug on the circuitry,
- (iv) will indicate the best functional biomarker to monitor treatment efficacy, and
- (v) will provide a better understanding of preclinical functional neuroimaging data which can then be translated into human studies.
Egenrieder, L., Mitricheva, E., Spanagel, R. and Noori, H. R. (2020). "No basal or drug-induced sex differences in striatal dopaminergic levels: a cluster and meta-analysis of rat microdialysis studies." J Neurochem. apps.webofknowledge.com/full_record.do.
Foo, J. C., Noori, H. R., Yamaguchi, I., Vengeliene, V., Cosa-Linan, A., Nakamura, T., Morita, K., Spanagel, R. and Yamamoto, Y. (2017). "Dynamical state transitions into addictive behaviour and their early-warning signals." Proceedings. Biological Sciences 284(1860). www.ncbi.nlm.nih.gov/pubmed/28768888.
Fritze, S., Spanagel, R. and Noori, H. R. (2017). "Adaptive dynamics of the 5-HT systems following chronic administration of selective serotonin reuptake inhibitors: a meta-analysis." Journal of Neurochemistry 142(5): 747-755. www.ncbi.nlm.nih.gov/pubmed/28653748.
Gambino, G., Gambino, T., Pohmann, R. and Angelovski, G. (2020). "Ratiometric 19F MR-based Method for Quantification of Ca2+ Using Responsive Paramagnetic Probes." Chem Commun. pubs.rsc.org/en/content/articlelanding/2020/cc/c9cc09977h.
Gass, N., Becker, R., Reinwald, J., Cosa-Linan, A., Sack, M., Weber-Fahr, W., Vollmayr, B. and Sartorius, A. (2019). "Differences between ketamine's short-term and long-term effects on brain circuitry in depression." Transl Psychiatry 9(1): 172. www.ncbi.nlm.nih.gov/pubmed/31253763.
Mitricheva, E., Kimura, R., Logothetis, N. K. and Noori, H. R. (2019). "Neural substrates of sexual arousal are not sex dependent." Proc Natl Acad Sci U S A 116(31): 15671-15676. www.ncbi.nlm.nih.gov/pubmed/31308220.
Noori, H. R., Cosa Linan, A. and Spanagel, R. (2016). "Largely overlapping neuronal substrates of reactivity to drug, gambling, food and sexual cues: A comprehensive meta-analysis." European Neuropsychopharmacology: The Journal of the European College of Neuropsychopharmacology 26(9): 1419-1430. www.ncbi.nlm.nih.gov/pubmed/27397863.
Noori, H. R., Mervin, L. H., Bokharaie, V., Durmus, Ö., Egenrieder, L., Fritze, S., Gruhlke, B., Reinhardt, G., Schabel, H.-H., Staudenmaier, S., Logothetis, N. K., Bender, A. and Spanagel, R. (2018). "Systemic neurotransmitter responses to clinically approved and experimental neuropsychiatric drugs." Nature Communications 9(1): 4699. www.ncbi.nlm.nih.gov/pubmed/30410047.
Noori, H. R., Mücksch, C. and Urbassek, H. M. (2019). "Ethanol-induced conformational fluctuations of NMDA receptors." Molecular Physics 117(2): 200-206. doi.org/10.1080/00268976.2018.1504135
Noori, H. R., Mücksch, C., Vengeliene, V., Schönig, K., Takahashi, T. T., Mukhtasimova, N., Bagher Oskouei, M., Mosqueira, M., Bartsch, D., Fink, R., Urbassek, H. M., Spanagel, R. and Sine, S. M. (2018). "Alcohol reduces muscle fatigue through atomistic interactions with nicotinic receptors." Communications Biology 1: 159. www.ncbi.nlm.nih.gov/pubmed/30302403.
Noori, H. R., Schöttler, J., Ercsey-Ravasz, M., Cosa-Linan, A., Varga, M., Toroczkai, Z. and Spanagel, R. (2017). "A multiscale cerebral neurochemical connectome of the rat brain." PLoS biology 15(7): e2002612. www.ncbi.nlm.nih.gov/pubmed/28671956.
Oberhofer, J. and Noori, H. R. (2017). "Quantitative evaluation of cue-induced reinstatement model for evidence-based experimental optimization." Addiction Biology. www.ncbi.nlm.nih.gov/pubmed/29239088.
Savic, T., Gambino, G., Bokharaie, V. S., Noori, H. R., Logothetis, N. K. and Angelovski, G. (2019). "Early detection and monitoring of cerebral ischemia using calcium-responsive MRI probes." Proc Natl Acad Sci U S A. www.ncbi.nlm.nih.gov/pubmed/31548425.
Shi, D., Levina, A. and Noori, H. R. (2019). "Refined parcellation of the nervous system by algorithmic detection of hidden features within communities." Phys. Rev. E 100(1): 012301. link.aps.org/doi/10.1103/PhysRevE.100.012301.
Vengeliene, V., Bespalov, A., Roßmanith, M., Horschitz, S., Berger, S., Relo, A. L., Noori, H. R., Schneider, P., Enkel, T., Bartsch, D., Schneider, M., Behl, B., Hansson, A. C., Schloss, P. and Spanagel, R. (2017). "Towards trans-diagnostic mechanisms in psychiatry: neurobehavioral profile of rats with a loss-of-function point mutation in the dopamine transporter gene." Disease Models & Mechanisms 10(4): 451-461. www.ncbi.nlm.nih.gov/pubmed/28167616.