Decoding Pain Sensitivity in Migraine With Multimodal Brainstem-based Neurosignature

Migraine

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.

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

Taiwan