The muscarinic M1 receptor modulates associative learning and memory in psychotic disorders.

BACKGROUND: Psychotic disorders are characterized by prominent deficits in associative learning and memory for which there are currently no effective treatments. Functional magnetic resonance imaging (fMRI) studies in psychotic disorders have identified deficits in fronto-temporal activation during associative learning and memory. The underlying pathology of these findings remains unclear. Postmortem data have suggested these deficits may be related to loss of muscarinic M1 receptor mediated signaling. This is supported by an in-vivo study showing improvements in these symptoms after treatment with the experimental M1/4 receptor agonist xanomeline. The current study tests whether reported deficits in fronto-temporal activation could be mediated by loss of M1 receptor signaling in psychotic disorders. METHODS: Twenty-six medication-free subjects diagnosed with a psychotic disorder and 29 age-, gender-, and IQ-matched healthy controls underwent two functional magnetic resonance imaging (fMRI) sessions, one under placebo and one under selective M1 antagonist biperiden, while performing the paired associated learning task. M1 binding potentials (BPND) were measured in the dorsolateral prefrontal cortex (DLPFC) and hippocampus using 123I-IDEX single photon emission computed tomography. RESULTS: In the subjects with psychotic disorders DLPFC hypoactivation was only found in the memory phase of the task. In both learning and memory phases of the task, M1 antagonism by biperiden elicited significantly greater hyperactivation of the parahippocampal gyrus and superior temporal gyrus in subjects with a psychotic disorders compared to controls. Greater hyperactivation of these areas after biperiden was associated with greater hippocampal M1 receptor binding during learning, with no association found with M1 receptor binding in the DLPFC. M1 receptor binding in the DLPFC was related to greater functional sensitivity to biperiden of the cingulate gyrus during the memory phase. CONCLUSION: The current study is the first to show differences in M1 receptor mediated functional sensitivity between subjects with a psychotic disorder and controls during a paired associate learning and memory task. Results point to subjects with psychotic disorders having a loss of M1 receptor reserve in temporal-limbic areas

A growing understanding of the role of muscarinic receptors in the molecular pathology and treatment of schizophrenia

Pre-clinical models, postmortem and neuroimaging studies all support a role for muscarinic receptors in the molecular pathology of schizophrenia. From these data it was proposed that activation of the muscarinic M1 and/or M4 receptor would reduce the severity of the symptoms of schizophrenia. This hypothesis is now supported by results from two clinical trials which indicate that activating central muscarinic M1 and M4 receptors can reduce the severity of positive, negative and cognitive symptoms of the disorder. This review will provide an update on a growing body of evidence that argues the muscarinic M1 and M4 receptors have critical roles in CNS functions that are dysregulated by the pathophysiology of schizophrenia. This realization has been made possible, in part, by the growing ability to visualize and quantify muscarinic M1 and M4 receptors in the human CNS using molecular neuroimaging. We will discuss how these advances have provided evidence to support the notion that there is a sub-group of patients within the syndrome of schizophrenia that have a unique molecular pathology driven by a marked loss of muscarinic M1 receptors. This review is timely, as drugs targeting muscarinic receptors approach clinical use for the treatment of schizophrenia and here we outline the background biology that supported development of such drugs to treat the disorder

Effects of copy number variations on brain structure and risk for psychiatric illness: large-scale studies from the ENIGMA working groups on CNVs

The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.Funding information: European Union's Horizon2020 Research and Innovation Programme, Grant/Award Number: CoMorMent project; Grant #847776; KG Jebsen Stiftelsen; National Institutes of Health, Grant/Award Number: U54 EB020403; Norges Forskningsråd, Grant/Award Number: #223273; South-Eastern Norway Regional Health Authority, Grant/Award Number: #2020060ACKNOWLEDGMENTS: The ENIGMA Consortium is supported by the NIH Big Data to Knowledge (BD2K) program under consortium grant number U54 EB020403 (PI: Thompson). OAA is supported by the Research Council of Norway, South East Norway Health Authority, KG Jebsen Stiftelsen, EU H2020. C. A. has been funded by the Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III (SAM16PE07CP1, PI16/02012, PI19/ 024), co-financed by ERDF Funds from the European Commission, “A way of making Europe”, CIBERSAM; Madrid Regional Government (B2017/BMD-3740 AGES-CM-2), European Union Structural Funds; European Union Seventh Framework Program under grant agreements FP7-4-HEALTH-2009-2.2.1-2-241,909 (Project EU-GEI), FP7- HEALTH-2013-2.2.1-2-603,196 (Project PSYSCAN) and FP7- HEALTH-2013- 2.2.1-2-602,478 (Project METSY); and European Union H2020 Program under the Innovative Medicines Initiative two Joint Undertaking (grant agreement No 115916, Project PRISM, and grant agreement No 777394, Project AIMS-2-TRIALS), Fundación Familia Alonso and Fundación Alicia Koplowitz. R. A-A is funded by a Miguel Servet contract from the Carlos III Health Institute (CP18/00003). G. B. is supported by the Dutch Organization for Health Research and Development ZonMw (grants 91112002 & 91712394). A. S. B. is supported by the Dalglish Family Chair in 22q11.2 Deletion Syndrome, Canadian Institutes of Health Research (CIHR) grants MOP-79518, MOP89066, MOP-97800 and MOP-111238, and NIMH grant number U01 MH101723–01(3/5). C. E. B. is also supported by the National Institute of Mental Health: RO1 MH085953, R01 MH100900 and 1U01MH119736. N. E. B. is granted the KNAW Academy Professor Award (PAH/6635). V. D. C. is supported by NIH R01 MH094524. S. C. is supported by the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3); Helmholtz Initiative and Networking Fund. C. R. K. C. is supported by NIA T32AG058507. E. W. C. C. is supported by the Canadian Institutes of Health Research, Ontario Mental Health Foundation grant MOP-74631 and NIMH grant U01MH101723–01(3/5). S. Ci. has received funding from the European Union's Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3). M. C. C. is supported by the Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. N. A. C. is supported by Agencia Nacional de Investigación y Desarrollo (ANID Chile) PIA ACT192064. GId. Z. is supported by the NHMRC. J. L. D. and D. E. J. L. are supported by the Wellcome Trust. T. B. C. is supported by NICHD grant PO1-HD070454, NIH grant UO1-MH191719, and NIMH grant R01 MH087636-01A1. AMD is supported by U24DA041147. B. D. is supported by the Swiss National Science Foundation (NCCR Synapsy, project grant numbers 32003B_135679, 32003B_159780, 324730_192755 and CRSK3_190185), the Leenaards Foundation and the Roger De Spoelberch Foundation. SE is supported by the NARSAD-Young Investigator Grant “Epigenetic Regulation of Intermediate Phenotypes in Schizophrenia”. B. E. S. is supported by the NIH (NIMH). D. C. G. is supported by NIH grant numbers MH078143, MH083824, AG058464. W. R. K. is supported by NIH/MH R0106824. R. E. G. is supported by NIH/NIMH grant numbers MH087626, MH119737. DMMcD-McG is supported by National Institutes of Mental Health (NIMH), grant numbers MH119737-02; MH191719; and MH087636-01A1. S. E. M. is supported by NHMRC grants APP1103623; APP1158127; APP1172917. TM is supported by Research Council of Norway - grant number 273345. D. G. M. is supported by the National Institute for Health Research Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London and S (European Autism Interventions)/EU AIMS-2-TRIALS, a European Innovative Medicines Initiative Joint Undertaking under grant agreements 115300 and 777394. T. N. was supported by Stiftelsen KG Jebsen under grant number SKGJ-MED-021. R. A. O. is supported by NIMH R01 MH090553. S. Y. S. has been funded by the Canadain Institutes of Health Research. M. J. O. is supported by MRC Centre grant MR/L010305/1 and Wellcome Trust grant 100,202/Z/12/Z; Dr. Owen has received research support from Takeda. Z. P. is supported by CIHR, CFI, HSFC. B. G. P. is supported by CIHR FDN 143290 and CAIP Chair. G. M. R. is supported by Fondecyt-Chile #1171014 and ANID-Chile ACT192064. A. Re. was supported by a grant from the Swiss National Science Foundation (31003A_182632). DRR is supported by R01 MH120174 (PI: Roalf). This report represents independent research funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London (to J. J. R). PSS is supported by NHMRC (Australia) program grant 1093083. J. E. S. is supported by NIH K01-ES026840. S. M. S. is supported by the Epilepsy Society. T. J. S. is supported by NIH grants R01MH107108, R01HD042794, and HDU54079125. I. E. S. is supported by South-Eastern Norway Regional Health Authority (#2020060), European Union's Horizon2020 Research and Innovation Programme (CoMorMent project; grant #847776) and the KG Jebsen Foundation (SKGJ-MED-021). V. M. S. is supported by Research Council of Norway (CoE funding scheme, grant number 223273). D. J. S. is supported by the SA MRC. C. K. T. is supported by Research Council of Norway (#230345, #288083, #223273) and South-Eastern Norway Regional Health Authority (#2019069, #2021070, #500189). D. T.-G. was supported by the Instituto de Salud Carlos III (PI14/00639 and PI14/00918) and Fundación Instituto de Investigación Marqués de Valdecilla (NCT0235832 and NCT02534363). Dvd. M. is supported by Research Council of Norway #276082. F. V. R. is supported by the Michael Smith Foundation for Health Research Scholar Award. deCODE genetics has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreements' no. 115008 (NEWMEDS) and no. 115300 (EUAIMS), of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union's Seventh Framework Programme (EU-FP7/ 2007–2013). L. T. W. is supported by Research Council of Norway, European Research Council. The IDIVAL neuroimage unit is supported by Instituto de Salud Carlos III PI020499, research funding SCIII-INT13/0014, MICINN research funding SAF2010-20840-C02- 02, SAF2013-46292-R. The TOP/NORMENT study are supported by the Research Council of Norway (#223273). The GOBS study data collection was supported in part by the National Institutes of Health (NIH) grants: R01 MH078143, R01 MH078111, and R01 MH083824 with work conducted in part in facilities constructed under the support of NIH grant number C06 RR020547. The Sydney Memory and Ageing Study has been funded by three National Health & Medical Research Council (NHMRC) Program Grants (ID No. ID350833, ID568969, and APP1093083). We thank the participants and their informants for their time and generosity in contributing to this research. We also acknowledge the MAS research team: https://cheba.unsw.edu.au/researchprojects/sydney-memory-and-ageing-study. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/ project/older-australian-twins-study) to this study. The OATS study has been funded by a National Health & Medical Research Council (NHMRC) and Australian Research Council (ARC) Strategic Award Grant of the Aging Well, Aging Productively Program (ID No. 401162); NHMRC Project (seed) Grants (ID No. 1024224 and 1025243); NHMRC Project Grants (ID No. 1045325 and 1085606); and NHMRC Program Grants (ID No. 568969 and 1093083). We thank the participants for their time and generosity in contributing to this research. This research was facilitated through access to Twins Research Australia, a national resource supported by a Centre of Research Excellence Grant (ID No. 1079102) from the National Health and Medical Research Council. The NCNG sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the KG Jebsen Foundation, the Research Council of Norway, to S. L. H., V. M. S., A. J. L., and T. E. The authors thank Dr. Eike Wehling for recruiting participants in Bergen, and Professor Jonn-Terje Geitung and Haraldplass Deaconess Hospital for access to the MRI facility. Additional support by RCN grants 177458/V50 and 231286/F20. The Betula study was supported by a Wallenberg Scholar Grant (KAW). The HUNT Study is a collaboration between HUNT Research Centre (Faculty of Medicine and Health Sciences, NTNU—Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. Research for the GAP cohort was supported by the Department of Health via the National Institute for Health Research (NIHR) Specialist Biomedical Research Center for Mental Health award to South London and Maudsley NHS Foundation Trust (SLaM) and the Institute of Psychiatry at King's College London, London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. S.J. is supported by Calcul Quebec (http:// www.calculquebec.ca), Compute Canada (http://www.computecanada. ca), the Brain Canada Multi investigator research initiative (MIRI), the Institute of Data Valorization (Canada First Research Excellence Fund), CHIR, Canada Research Chairs and the Jeanne et Jean Louis Levesque Foundation. The NTR cohort was supported by the Netherlands Organization for Scientific Research (NWO), MW904-61-193 (de Geus & Boomsma), MaGWnr: 400-07-080 (van 't Ent), MagW 480-04-004 (Boomsma), NWO/SPI 56-464-14,192 (Boomsma), the European Research Council, ERC-230374 (Boomsma), and Amsterdam Neuroscience. Funding for genotyping was obtained from the National Institutes of Health (NIMH U24 MH068457-06; Grand Opportunity grants 1RC2 MH089951, and 1RC2 MH089995); the Avera Institute for Human Genetics, Sioux Falls, South Dakota (USA). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. The Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Boomsma), 51.02.060 (Hilleke Hulshoff Pol), 668.772 (Boomsma & Hulshoff Pol); NWO/SPI 56-464-14192 (Boomsma), the European Research Council (ERC230374) (Boomsma), High Potential Grant Utrecht University (Hulshoff Pol), NWO Brain and Cognition 433-09-220 (Hulshoff Pol). SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide SNP typing in SHIP and MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The ENIGMA-22q11.2 Deletion Syndrome Working Group wishes to acknowledge our dear colleague Dr. Clodagh Murphy, who sadly passed away in April 2020. Open access funding enabled and organized by Projekt DEAL

A phase 1b/2a multicenter study of the safety and preliminary pharmacodynamic effects of selective muscarinic M1 receptor agonist HTL0018318 in patients with mild-to-moderate Alzheimer's disease.

Funder: Allergan Incorporated (now AbbVie)INTRODUCTION: This study examined the safety and pharmacodynamic effects of selective muscarinic M1 receptor orthosteric agonist HTL0018318 in 60 patients with mild-to-moderate Alzheimer's disease (AD) on background donepezil 10 mg/day. METHODS: A randomized, double-blind, placebo-controlled 4-week safety study of HTL0018318 with up-titration and maintenance phases, observing exploratory effects on electrophysiological biomarkers and cognition. RESULTS: Treatment-emergent adverse events (TEAEs) were mild and less frequently reported during maintenance versus titration. Headache was most commonly reported (7-21%); 0 to 13% reported cholinergic TEAEs (abdominal pain, diarrhea, fatigue, nausea) and two patients discontinued due to TEAEs. At 1 to 2 hours post-dose, HTL0018318-related mean maximum elevations in systolic and diastolic blood pressure of 5 to 10 mmHg above placebo were observed during up-titration but not maintenance. Postive effects of HTL0018318 were found on specific attention and memory endpoints. DISCUSSION: HTL0018318 was well tolerated in mild-to-moderate AD patients and showed positive effects on attention and episodic memory on top of therapeutic doses of donepezil

Source‐based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome

22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1‐weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source‐based morphometry (SBM) pipeline (SS‐Detect) to generate structural brain patterns (SBPs) that capture co‐varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV‐SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel‐based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs; however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities converge with previously reported cortical surface area abnormalities, suggesting disturbances of early neurodevelopment as the most likely underlying mechanism

Large-scale mapping of cortical alterations in 22q11.2 deletion syndrome: Convergence with idiopathic psychosis and effects of deletion size

The 22q11.2 deletion (22q11DS) is a common chromosomal microdeletion and a potent risk factor for psychotic illness. Prior studies reported widespread cortical changes in 22q11DS, but were generally underpowered to characterize neuroanatomic abnormalities associated with psychosis in 22q11DS, and/or neuroanatomic effects of variability in deletion size. To address these issues, we developed the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta-Analysis) 22q11.2 Working Group, representing the largest analysis of brain structural alterations in 22q11DS to date. The imaging data were collected from 10 centers worldwide, including 474 subjects with 22q11DS (age = 18.2 ± 8.6; 46.9% female) and 315 typically developing, matched controls (age = 18.0 ± 9.2; 45.9% female). Compared to controls, 22q11DS individuals showed thicker cortical gray matter overall (left/right hemispheres: Cohen’s d = 0.61/0.65), but focal thickness reduction in temporal and cingulate cortex. Cortical surface area (SA), however, showed pervasive reductions in 22q11DS (left/right hemispheres: d = −1.01/−1.02). 22q11DS cases vs. controls were classified with 93.8% accuracy based on these neuroanatomic patterns. Comparison of 22q11DS-psychosis to idiopathic schizophrenia (ENIGMA-Schizophrenia Working Group) revealed significant convergence of affected brain regions, particularly in fronto-temporal cortex. Finally, cortical SA was significantly greater in 22q11DS cases with smaller 1.5 Mb deletions, relative to those with typical 3 Mb deletions. We found a robust neuroanatomic signature of 22q11DS, and the first evidence that deletion size impacts brain structure. Psychotic illness in this highly penetrant deletion was associated with similar neuroanatomic abnormalities to idiopathic schizophrenia. These consistent cross-site findings highlight the homogeneity of this single genetic etiology, and support the suitability of 22q11DS as a biological model of schizophrenia

Reformacija kao proces uspostavljanja i obnavljanja odnosa s Bogom

22q11.2 deletion syndrome (22q11DS)—a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22—is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but small samples and variable methods have led to contradictory results. Here we present the largest study ever conducted of dMRI-derived measures of WM microstructure in 22q11DS (334 22q11.2 deletion carriers and 260 healthy age- and sex-matched controls; age range 6–52 years). Using harmonization protocols developed by the ENIGMA-DTI working group, we identified widespread reductions in mean, axial and radial diffusivities in 22q11DS, most pronounced in regions with major cortico-cortical and cortico-thalamic fibers: the corona radiata, corpus callosum, superior longitudinal fasciculus, posterior thalamic radiations, and sagittal stratum (Cohen’s d’s ranging from −0.9 to −1.3). Only the posterior limb of the internal capsule (IC), comprised primarily of corticofugal fibers, showed higher axial diffusivity in 22q11DS. 22q11DS patients showed higher mean fractional anisotropy (FA) in callosal and projection fibers (IC and corona radiata) relative to controls, but lower FA than controls in regions with predominantly association fibers. Psychotic illness in 22q11DS was associated with more substantial diffusivity reductions in multiple regions. Overall, these findings indicate large effects of the 22q11.2 deletion on WM microstructure, especially in major cortico-cortical connections. Taken together with findings from animal models, this pattern of abnormalities may reflect disrupted neurogenesis of projection neurons in outer cortical layers

Lessons learned from using fMRI in the early clinical development of a mu-opioid receptor antagonist for disorders of compulsive consumption

Functional magnetic resonance imaging (fMRI) has been widely used to gain a greater understanding of brain circuitry abnormalities in CNS disorders. fMRI has also been used to examine pharmacological modulation of brain circuity and is increasingly being used in early clinical drug development as functional pharmacodynamic index of target engagement, and to provide early indication of clinical efficacy. In this short review, we summarize data from experimental medicine and early clinical development studies of a mu-opioid receptor antagonist, GSK1521498 developed for disorders of compulsive consumption including binge eating in obesity. We demonstrate how fMRI can be used to answer important questions of early clinical drug development relating to; (1) target engagement, (2) dose response relationships, (3) differential efficacy and (4) prediction of behavioural and clinically relevant outcomes. We also highlight important methodological factors that need to be considered when conducting fMRI studies in drug development given the challenges faced with small sample sizes in Phase 1 and early proof of mechanism studies. While these data highlight the value of fMRI as a biomarker in drug development, its use for making Go/No-go decisions is still faced with challenges given the variability of responses, interpretation of brain activation changes and the limited data linking drug induced changes in brain activity to clinical or behavioural outcome. These challenges need to be addressed to fulfil the promise of fMRI as a tool in clinical drug development

Targeting the type 5 metabotropic glutamate receptor: a potential therapeutic strategy for neurodegenerative diseases?

The type 5 metabotropic glutamate receptor, mGlu5, has been proposed as a potential therapeutic target for the treatment of several neurodegenerative diseases. In preclinical neurodegenerative disease models, novel allosteric modulators have been shown to improve cognitive performance and reduce disease-related pathology. A common pathological hallmark of neurodegenerative diseases is a chronic neuroinflammatory response, involving glial cells such as astrocytes and microglia. Since mGlu5 is expressed in astrocytes, targeting this receptor could provide a potential mechanism by which neuroinflammatory processes in neurodegenerative disease may be modulated. This review will discuss current evidence that highlights the potential of mGlu5 allosteric modulators to treat neurodegenerative diseases, including Alzheimer’s disease, Huntington’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. Furthermore, this review will explore the role of mGlu5 in neuroinflammatory responses, and the potential for this G protein-coupled receptor to modulate neuroinflammation