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Research

Aim and Vision

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10 May 2017
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The aim of NeuroPharm is to develop and validate new human experimental medicine models in brain disorders in order to identify ways to safely assess novel treatments and intervention outcomes in humans. This will be done by studying brain neurobiology and the brain’s response to neuropharmacological interventions.

The research in NeuroPharm is divided into four work packages (NP1-4) and the specific scientific objectives of these are to:

  • predict the outcome of a pharmacological intervention (NP1)
  • assess novel treatment interventions for brain disorders (NP2)
  • develop and validate neuroimaging methods for experimental medicine approach (NP3)
  • build statistical and predictive models of outcomes (NP4)

 
By means of positron emission tomography (PET) and magnetic resonance (MR) brain scanning we will image brain receptors, receptor occupancy, and the brains regional interactions, i.e., functional connectivity. The ability to simultaneously measure drug occupancy and brain reactivity directly in humans provides a completely novel approach to assess interventional effects. We will employ these brain imaging tools in patients with, e.g., depression and migraine. We will make use of existing data and biological samples to be analysed in the context of a multivariate data analysis framework. Generation of predictive statistical models will allow for a more informed use of data acquired within the Center and will provide a foundation for better study designs. Through this research, we expect to answer pertinent and basic questions regarding human brain disease mechanisms and predict brain responses to categories of neuromodulatory interventions as well as treatment efficacy.

The diagram to the right summarizes the overall framework of NeuroPharm, in the context of drug assessments where the main goal is to identify target involvement. Based on data outcome from the various methods available within the Center, e.g., brain imaging techniques we will gain novel insight into the specific patterns characteristic for individual brain-targeting drugs (Drug signatures). The same endophenotype data can also critically aid to stratify patients and categorize disease subtypes (Disease classifiers) which will enhance prediction of treatment efficacy (Clinical drug effects). Conversely, individuals’ clinical outcome after drug intervention can itself be part of the drug signature and can help inform the disease classification.

The vision of NeuroPharm is to establish itself as an internationally leading hub for experimental medicine in brain disorders.

NP1: Treatment outcome in Major Depressive Disorder (MDD)

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10 May 2017
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Work package leader: Vibe G. Frøkjør, NRU

Major depressive disorder (MDD) most likely comprises a heterogeneous collection of different biological entities, which calls for studies that can inform a targeted treatment and potentially a new etiological classification. Most antidepressants act on the serotonin (5-HT) system but less than 50% of MDD patients respond successfully to 5-HT acting drugs. Identification of biological features that enables a relevant stratification of MDD patients would, importantly, allow for individualized treatment and can help facilitate more efficient clinical drug trials.

The goal of this work package is to identify neurobiological and other predictors of response to pharmacological treatment of depression. The research will illuminate basic mechanisms of action of pharmacological treatment of MDD and will, in the long term, provide a rationale for tailored treatment choice for MDD patients based on quantitative measures of brain function, rather than - as is the case today - rely exclusively on clinical assessment. The NP1 project is carried out in a close collaboration between NRU and the Psychiatric Center Copenhagen and it includes a newly established PET-based marker of the brain serotonin system (5-HT4 receptor binding determined by 11C-SB207145 PET), various MRI techniques, EEG, neuropsychological testing, blood and saliva sampling enabling genotyping and determination of cortisol awakening response, inflammatory markers as well as epigenetic variations across the study period.

We will enroll 100 MDD patients and examine how these markers relate to the outcome of a standard antidepressant treatment. Patients will be treated with standard antidepressant treatment, i.e., a selective serotonin reuptake inhibitor (SSRI), escitalopram, adjusted contingent on effects and side effects. They will have follow-up sessions at week 1, 2, 4, 8, and 12 where a trained psychiatrist will rate their depressive symptoms. Brain imaging with 11C-SB207145 PET, structural and functional MRI with resting state fMRI (rs-fMRI), and EEG will be conducted in all patients before pharmacological intervention is initiated and repeated at week 8 in 40 patients with variable antidepressant response.

The first part of the project is a GCP-monitored clinical trial. A description of this part can be found here at ClinicalTrials.gov.

 

NP2: 5-HT2AR modulation effects on neurobiology, cognition and mood

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10 May 2017
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Work package leader: Patrick Fisher, NRU

Serotonin 2A receptor (5-HT2AR) agonists, which have hallucinogenic properties, have emerged as an intriguing novel treatment for MDD and other mood and anxiety disorders. 5-HT2AR agonists such as psilocybin result in both acute and lasting improvements in well-being. Psilocybin has been found to produce sustained antidepressant-like effects in patients and well-being in healthy volunteers and changes in brain activity that are consistent with effective antidepressant interventions. Thus, a better understanding of psilocybin’s brain effects with PET and MRI will advance our understanding of serotonergic mechanisms implicated in depression and treatment. Comparing 5- HT2AR agonist effects against drugs with opposing pharmacological actions (e.g., ketanserin, a 5- HT2AR antagonist) would further elucidate the role 5-HT2AR in these processes.

In this work package, we will with PET (11C-Cimbi36) and rs-fMRI investigate healthy individuals to establish dose-dependent drug effects of psilocybin and pimavanserin on cerebral 5-HT2AR binding and determine if psilocybin and ketanserin have opposing effects on brain connectivity. Also, we will determine the neurobiological effects of the interventions and relate those to effects on cognition and mood. This will generate important insights into aspects of the neuromodulatory effects of 5-HT2AR on cognition and mood and will provide a direction for the development of this and other potential future treatments.

More information (in Danish) in this article on videnskab.dk about the project.

 

NP3: Novel neuroimaging methods for an experimental medicine approach

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10 May 2017
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Work package leader: Hanne D. Hansen, NRU

In non-human primates (NHPs), we have previously found that targeted binding of an antagonist to dopamine D2 receptors elicits a hemodynamic response that is coupled to receptor occupancy. However, the hemodynamic response is not only dependent on receptor occupancy but also on the functionality of the drug, i.e. whether the drug is an agonist or an antagonist. Together with our collaborating partner at the Martinos Center in USA, we have shown that the 5-HT1BR partial agonist AZ10419369 elicited a dose-dependent biphasic hemodynamic response that was related to the 5-HT1BR occupancy. By contrast, injection of the antagonist GR127935 did not elicit significant hemodynamic responses, even at a 5-HT1BR cerebral occupancy similar to the one obtained with a high dose of AZ10419369. These results suggest that simultaneous PET-MRI opens for the possibility of testing novel drug compounds for their blood-brain-barrier passage, their brain occupancy and their functionality, based upon the hemodynamic response.

In our investigations of cerebral spatial and temporal response to triptans following experimental induction of migraine, we have completed the data collection and are now analysing the data. In this project, all patients have got three PET scans with 11C-AZ10419369: an interictal baseline scan and two scans after provocation of migraine.

Last but not least, we will settle a long-debated issue, namely to establish if migraine patients without aura (MO) symptoms have reduced brain serotonin levels. For this purpose, 16 MO patients will be scanned and compared to 16 matched healthy controls. The data collection and the data analysis is now finalized and a manuscript has been drafted of the results.

 

NP4: Bioinformatics, statistical and predictive models

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10 May 2017
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Work package leader: Brice Ozenne, NRU

In order to meet the clinical need of robust diagnostic and prognostic classifiers for the individual at risk or with a manifest brain disorder, we will in this work package make use of existing data either from our Cimbi database or from collaborators to be analyzed in the context of a multivariate data analysis framework and subsequently test the identified key variables for their predictive value in new data sets. We will use machine-learning techniques and seek to define a set of parallel biomarkers that can optimize the prediction of treatment response with high validity. In addition, statistical assistance for the other three work packages will be provided, both in terms of study design and optimal statistical analyses.

We hypothesize that generation of predictive statistical models will allow for a more informed use of data and will provide a framework for optimized study designs in the future. For this purpose, recent advances in high-dimensional statistics and machine-learning are employed. Depression and certain other brain disorders are characterized by differences in functional brain connectivity as determined by rs-fMRI; this approach may offer a sensitive measure for disease classification. Data acquired in NP1-NP3 will be used to extract resting-state brain networks and we will use multivariate statistical analysis applied to discover networks that, e.g., predict recovery from depression before initiation of drug intervention. A validated prediction model may serve as an important step in translating the knowledge gathered from NP1-NP3 into directly clinically applicable tools.

 

PhD projects

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03 August 2017
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The NeuroPharm-related PhD projects are listed below.

Work package Student Project Supervisors Date of Enrollment Deadline
NP1

Cheng Teng Ip
NRU and H.Lundbeck A/S

EEG and ERP biomarkers for prediction of antidepressant treatment response Gitte Moos Knudsen
Søren Rahn Christensen
Sandor Beniczky
Bastian Epp
01.07.2016 30.06.2019
NP1

Kristin Köhler-Forsberg
NRU and Psychiatric Centre Copenhagen

A novel marker of brain serotonin as predictor of respons to antidepressant therapy Martin Balslev Jørgensen
Vibe G. Frøkjær
Gitte Moos Knudsen
Anders Jørgensen
01.03.2016 28.02.2019
NP1

Vibeke Dam
NRU

Affective and social cognition as neurocognitive predictors of antidepressant treatment response Gitte Moos Knudsen
Vibe Gedsø Frøkjær
Dea Siggaard Stenbæk
01.12.2017 30.11.2020
NP2 Martin Korsbak Madsen
NRU
Neurobiological effects of 5-HT2AR modulation Gitte Moos Knudsen
Patrick M Fisher
David Erritzoe
01.01.2017 31.12.2019
NP2 & NP3 Lene Lundgaard Donovan
NRU
In vivo imaging of cerebral epigenetic changes following 5HT-2AR modulation Gitte Moos Knudsen
Jacob Hooker
Hanne D. Hansen
Kristian Helin
01.01.2017 31.12.2019
NP3 Marie Deen Christensen
NRU and Danish Headache Center
Investigation of serotonin receptor binding in the migraine brain using positron emission tomography Messoud Ashina
Gitte Moos Knudsen
Anders Hougaard
01.06.2015 31.05.2018
NP4 Martin Nørgaard
NRU
Optimizing preprocessing pipelines in PET/MRI neuroimaging Gitte Moos Knudsen
Claus Svarer
Stephen C. Strother
Melanie Ganz
Morten Mørup
01.08.2016 31.07.2019

Postdoc projects

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03 August 2017
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The NeuroPharm-related postdoc projects are listed below.

Work package Fellow Project Collaborators Project start Project end
NP3 & NP4

Sebastian Holst
NRU

Sleep loss, adrenergic inhibition, cognitive performance and cerebral water diffusion in humans Gitte Moos Knudsen
Maiken Nedergaard
01.01.2017 31.12.2019
NP4 Brice Ozenne
NRU and Section of Biostatistics, University of Copenhagen
Statistical modelling for predicting patient response to depression therapy Gitte Moos Knudsen
Esben Budtz-Jørgensen
01.05.2017 30.04.2020
NP4 Melanie Ganz-Benjaminsen
NRU
Exploring a multimodal serotonin atlas with the help of machine learning methods Gitte Moos Knudsen
Doug Greve
01.07.2015 30.06.2018

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