An fMRI-based neural marker for migraine without aura
Yiheng Tu, Fang Zeng, Lei Lan, Zhengjie Li, Nasim Maleki, Bo Liu, Jun Chen, Chenchen Wang, Joel Park, Courtney Lang, Gao Yujie, Mailan Liu, Zening Fu, Zhiguo Zhang, Fanrong Liang, Jian Kong
Abstract
OBJECTIVE: To identify and validate an fMRI-based neural marker for migraine without aura (MwoA) and to examine its association with treatment response. METHODS: We conducted cross-sectional studies with resting-state fMRI data from 230 participants and machine learning analyses. In studies 1 through 3, we identified, cross-validated, independently validated, and cross-sectionally validated an fMRI-based neural marker for MwoA. In study 4, we assessed the relationship between the neural marker and treatment responses in migraineurs who received a 4-week real or sham acupuncture treatment, or were waitlisted, in a registered clinical trial. RESULTS: In study 1 (n = 116), we identified a neural marker with abnormal functional connectivity within the visual, default mode, sensorimotor, and frontal-parietal networks that could discriminate migraineurs from healthy controls (HCs) with 93% sensitivity and 89% specificity. In study 2 (n = 38), we investigated the generalizability of the marker by applying it to an independent cohort of migraineurs and HCs and achieved 84% sensitivity and specificity. In study 3 (n = 76), we verified the specificity of the marker with new datasets of migraineurs and patients with other chronic pain disorders (chronic low back pain and fibromyalgia) and demonstrated 78% sensitivity and 76% specificity for discriminating migraineurs from nonmigraineurs. In study 4 (n = 116), we found that the changes in the marker responses showed significant correlation with the changes in headache frequency in response to real acupuncture. CONCLUSION: We identified an fMRI-based neural marker that captures distinct characteristics of MwoA and can link disease pattern changes to brain changes.