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Decoding Pain Sensitivity in Migraine With Multimodal Brainstem-based Neurosignature

Phase 4
Recruiting
Conditions
Migraine
Interventions
Other: healthy control
Registration Number
NCT04702971
Lead Sponsor
Taipei Veterans General Hospital, Taiwan
Brief Summary

Migraine is a highly prevalent and disabling neurological disease, which has a tremendous impact on sufferers, healthcare systems, and the economy. According to the 2016 WHO report, migraine is the second leading cause of years lived with disability, greater than all other neurological diseases combined. Yet, the treatment in migraine is far from optimum; the sufferers often abuse painkillers and complicated with medication overuse headache. Migraine is characterized by the hypersensitivity of the sensory system, potentially attributed to dysfunctional pain modulatory networks located in the deep brain structures, particularly the brainstem. However, the current understanding of these deeply seated, dysregulated pain modulatory circuits in migraine is limited due to technological constraints. Besides, studies with an in-depth analysis of the clinical manifestations (i.e., deep phenotyping) are lacking, and there is no corresponding animal model readily available for translational research. In this project, the investigators propose a multimodal approach to address these issues by applying the technologies and platforms developed by our team to explore the correlation between pain sensitivity and dysregulated connectivities from brainstem to other brain regions. In this four-year project, the investigators will recruit 400 migraine patients and 200 healthy subjects. The investigators aim at decomposing the key brainstem mechanisms underlying dysmodulated pain sensitivity in migraine from 5 comprehensive perspectives: (1) clinical deep phenotyping, (2) high-resolution brainstem structural MRI and functional connectivity analysis, (3) innovative brainstem EEG signal detecting technique, (4) multimodal data fusion platform with neural network analysis, and (5) ultrahigh-resolution brainstem-based connectomes, intravital manipulations and recording, and connectome-sequencing in animal models. Moreover, the investigators will collaborate with Taiwan Semiconductor Research Institute to develop a wearable high-density EEG equipment, integrated with a System-on-Chip capable of edge-computing the signal using algorithms derived from our brainstem decoding platform. The ultimate goal is to build a real-time brainstem decoding system for clinical application.

Detailed Description

Migraine causes a tremendous disease burden around the world. Migraine is one of the most prevalent neurological disorders and is reported by the WHO as the second leading cause of disease-related disabilities globally (No. 1 in the population under the 50s). There has been no much change in the ranking of disability for migraine for the past two decades, reflecting an unmet need for better treatment options. Even with the recently available calcitonin-gene related peptide (CGRP)-based treatment, the treatment response versus placebo is still disappointing (6.4-17.6% in acute treatment, 10.2-23.7% in preventive treatment). There is an urgent need to push further the current understanding of the pathophysiology of migraine, based on which novel treatment strategies can be developed. The lack of appropriate research tools hinders the acceleration of migraine research. As a neurological disorder, many neuroimaging studies have been focused on brain alterations; however, the majority focused on the cerebrum. Limited by the currently available neuroimaging and electrophysiological technologies, the deep brain structures especially the brainstem involved in the sensory and nociceptive neurotransmission in migraine, such as the trigeminal nucleus, could only be investigated to a limited extent. Obviously, there is an unmet need for novel technologies that can be used to delineate structural or functional alterations in the brainstem. Elucidation of the role of these deep brain structures may fill the gap in the current understanding of migraine pathophysiology, and pave the way to precise and efficient treatment. Studies restricted to single methodologies are insufficient for the complexity of migraine. Migraine is a complex and dynamic disorder. However, most prior studies were limited to single methodologies and provided limited insights into such a multifaceted disorder. Studies with an integrated approach are lacking. An exhaustive examination of the discrete components of a phenotype, i.e., 'deep phenotyping', can help understand different aspects of its clinical manifestations, and facilitate patient classification. Coupled with neuroimaging and electrophysiological research methodologies, a multi-modal decoding approach would help identify a constellation of migraine-specific biosignatures, rather than just one. This can not only provide clues to decipher migraine pathophysiology in various dimensions but also serve as the basis of the development of a prediction algorithm that can be applied in clinical practice. To pursue the overall goal, the present project schemes as a composition of the following 5 aims:

Aim 1: Deep phenotyping for sensory processing in patients with migraine Aim 2: Brainstem-based functional and structural connectomics in migraine Aim 3: Capturing brainstem electro-neurosignature in migraine Aim 4: Constructing a data fusion platform and developing an EEG cap with a built-in analytic chip Aim 5: Exploring brainstem-based connectome sequencing in migraine animal model

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
600
Inclusion Criteria

Not provided

Exclusion Criteria

Not provided

Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
healthy controlhealthy controlhealthy control
patients with migraineFlunarizinepatient with migraine will be prescribed with flunarizine or routine clinical care per clinician's decision based on the condition of each individual patient
Primary Outcome Measures
NameTimeMethod
Clinical change after treatment (1) headache frequency6 months

clinical change (headache frequency) after treatment unit: attacks per month analysis: comparing the mean headache frequency in each month after treatment (M1/M2/M3/M4/M5/M6) to that before treatment (M0)

Clinical change after treatment (2) headache intensity6 months

clinical change (headache intensity) after treatment unit: NRS (numeric rating scale, 0-10) analysis: comparing the mean headache intensity in each month after treatment (M1/M2/M3/M4/M5/M6) to that before treatment (M0)

Clinical change after treatment (3) headache duration6 months

clinical change (headache duration) after treatment unit: hours/day analysis: comparing the mean headache duration (hours/day) in each month after treatment (M1/M2/M3/M4/M5/M6) to that before treatment (M0)

Secondary Outcome Measures
NameTimeMethod
EEG change after treatment (3) Nonlinear analysis of EEG before and after treatment12 months

evoked potential amplitude change of EEG before and after treatment

• Four EEG sessions will be arranged. The first one is done before treatment, and the 2nd/3rd/4th one will be done after a 3-month/6-month/12-month treatment course, respectively.

fMRI change after treatment (1)12 months

functional connectivity change of fMRI before and after treatment

• Three fMRI sessions will be arranged. The first one is done before treatment, and the 2nd/3rd one will be done after a 6-month/12-month treatment course, respectively.

EEG change after treatment (1) Linear analysis of EEG before and after treatment12 months

power spectral density change of EEG before and after treatment

• Four EEG sessions will be arranged. The first one is done before treatment, and the 2nd/3rd/4th one will be done after a 3-month/6-month/12-month treatment course, respectively.

EEG change after treatment (2) Nonlinear analysis of EEG before and after treatment12 months

functional connectivity change of EEG before and after treatment

• Four EEG sessions will be arranged. The first one is done before treatment, and the 2nd/3rd/4th one will be done after a 3-month/6-month/12-month treatment course, respectively.

Sensory threshold change after treatment12 months

Using quantitative sensory testing (QST) to evaluate the sensory threshold before and after treatment

• Four standard QST sessions will be arranged. The first one is done before treatment, and the 2nd/3rd/4th one will be done after a 3-month/6-month/12-month treatment course, respectively.

fMRI change after treatment (2)12 months

activation change of fMRI before and after treatment

• Three fMRI sessions will be arranged. The first one is done before treatment, and the 2nd/3rd one will be done after a 6-month/12-month treatment course, respectively.

MRI change after treatment (1)12 months

VBM changes of MRI before and after treatment

• Three MRI sessions will be arranged. The first one is done before treatment, and the 2nd/3rd one will be done after a 6-month/12-month treatment course, respectively.

MRI change after treatment (2)12 months

SBM changes of MRI before and after treatment

• Three MRI sessions will be arranged. The first one is done before treatment, and the 2nd/3rd one will be done after a 6-month/12-month treatment course, respectively.

Humoral change after treatment (1)12 months

Test the cytokine level using ELISA kit to evaluate the status before and after treatment

• Four blood test sessions and saliva collection will be arranged. The first one is done before treatment, and the 2nd/3rd/4th one will be done after a 3-month/6-month/12-month treatment course, respectively.

Humoral change after treatment (2)12 months

Test the hormone level using ELISA kit to evaluate the status before and after treatment

• Four blood test sessions and saliva collection will be arranged. The first one is done before treatment, and the 2nd/3rd/4th one will be done after a 3-month/6-month/12-month treatment course, respectively.

Genetic variance5 minutes

Genetic variants associated with baseline demographics and treatment response as assessed with genome-wide association study using the genotyping data derived from the Axiom Genome-wide array

• Blood draw before the treatment to extract DNA for further sequencing

Trial Locations

Locations (1)

Headache Center, Teipei Veterans General Hospital

🇨🇳

Taipei, Taiwan

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