Atrophy of hypothalamic subregions increases migraine risk: cross-sectional study and mendelian randomization analysis

Abstract

Background

The hypothalamus is a versatile structure comprising several nuclei that play key roles in regulating various biological processes associated with migraine, including hormone secretion, metabolism, circadian rhythm, and autonomic nervous system functions. However, the involvement of hypothalamic subregions in migraine remains unclear.

Methods

Based on T1-weighted MRI data from 76 migraine patients (23 episodic migraine [EM], 53 chronic migraine [CM]) and 35 healthy controls (HCs), we examined group differences in the volume of five hypothalamic subregions. To clarify causal relationships between migraine and hypothalamic volume, we conducted Mendelian randomization (MR) analyses. Mediation analysis was further performed to assess the role of gut microbiota composition in this association.

Results

Compared to HCs, migraine patients exhibited significantly reduced total hypothalamic volume (813.53 ± 66.46 mm³ vs. 831.86 ± 57.91 mm³; FDR q = 0.048) and inferior tuberal hypothalamic volume (255.26 ± 30.17 mm³ vs. 265.29 ± 23.32 mm³; FDR q = 0.046). These reductions were particularly pronounced in patients with CM, whereas no significant differences were observed in those with EM. MR analysis revealed causal effects of total hypothalamic volumes (OR = 0.80, FDR q = 7.28 × 10⁻⁵) and inferior tuberal hypothalamic volumes (OR = 0.85, FDR q = 2.61 × 10⁻²) on migraine, providing causal evidence to support the observational findings from the cross-sectional study. Furthermore, specific gut microbiome (genus DefluviitaleaceaeUCG011, genus Eubacteriumruminantiumgroup, and family FamilyXIII) were identified as partial mediators of the hypothalamus–migraine link (FDR q < 0.05).

Conclusions

This study suggests that atrophy of the inferior tuberal subregion of the hypothalamus plays a pivotal role in increasing migraine risk, and that this effect is partially mediated through alterations in gut microbiome composition.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10194-025-02119-8.

Introduction

Migraine is a highly prevalent neurological disorder affecting around 1 billion people worldwide and ranking as the second leading cause of global disability [1]. In addition to recurrent moderate-to-severe headaches accompanied by sensory and autonomic symptoms [2], migraine is frequently associated with dysfunctions in pain modulation, circadian rhythms, autonomic regulation, and hormonal balance. As a key regulator of these processes, the hypothalamus is believed to play a central role in migraine pathophysiology [3–5].

Neuroimaging has been shown to provide important insights into the neural mechanisms of various brain disorders [6, 7]. Recent neuroimaging studies have revealed both structural and functional alterations of the hypothalamus in migraine patients [8–10]. For instance, high-resolution Magnetic resonance imaging (MRI) has shown significantly reduced hypothalamic volume in individuals with migraine compared to healthy controls (HCs) [10]. However, it remains unclear whether these hypothalamic alterations play a causal role in migraine pathophysiology or are merely secondary consequences. Clarifying this distinction is critical for determining the therapeutic relevance of hypothalamic targets. Furthermore, most studies have treated the hypothalamus as a homogeneous structure, neglecting its functional heterogeneity. Given its diverse regulatory roles, investigating hypothalamic subregions is essential to uncover their specific contributions to migraine pathophysiology. Beyond neuroanatomical changes, growing evidence suggests that the gut microbiota may contribute to migraine pathogenesis. This likely occurs through the gut–brain axis, involving immune, metabolic, and neuroendocrine pathways [11, 12]. Yet, it remains unclear whether gut microbiota may mediate the influence of hypothalamic structure on migraine susceptibility.

Mendelian randomization (MR) is a powerful genetic epidemiological approach that leverages genetic variants as instrumental variables to infer causal relationships between modifiable exposures and disease outcomes [13–15]. MR relies on three core assumptions: the genetic variants are associated with the exposure (relevance), are independent of confounders (independence), and influence the outcome only through the exposure (exclusion restriction). By integrating genome-wide association study (GWAS) data of migraine and imaging-derived hypothalamic phenotypes, MR provides an opportunity to determine whether alterations in hypothalamic structure are not merely correlated with migraine but indeed contribute causally to its pathogenesis. Simultaneously, the rapid advancement of deep learning has enabled precise segmentation of brain structures in neuroimaging. A recent study applied deep convolutional neural networks to MRI data to segment the hypothalamus into five distinct subregions, uncovering their genetic and functional heterogeneity [16]. This methodological breakthrough provides a foundation for exploring the specific roles of hypothalamic subregions in migraine.

Building on these advances, the present study aimed to elucidate the role of hypothalamic subregions in migraine susceptibility. We first assessed the associations between migraine and volumetric alterations across five distinct hypothalamic subregions. Then, we employed two-sample MR analysis to further clarify their causal associations. Finally, we examined whether gut microbiota serve as potential mediators in the hypothalamus–migraine pathway.

Methods

Standard protocol approvals, registrations, and patient consents

An overview of the study design is presented in Fig. 1. This study was approved by the Ethics Committee of Beijing Tiantan Hospital, Capital Medical University (approval number: KY2022-044), as a sub-study of the ongoing China HeadAche DIsorders RegiStry Study (CHAIRS; NCT05334927). Written informed consent was obtained from all participants in accordance with the Declaration of Helsinki.

Fig. 1.

Study design flowchart. Deep learning-based MRI segmentation of the hypothalamus combined with Mendelian randomization analysis provides imaging and genetic evidence for the impacts of the hypothalamus on migraines. Abbreviations: CM, chronic migraine; EM, episiod migraine; HC, healthy control

Participants for neuroimaging analysis

This observational, cross-sectional study included 111 participants recruited consecutively from the Headache Outpatient Unit of Beijing Tiantan Hospital, Capital Medical University, between October 2020 and March 2023. The cohort comprised 53 individuals with chronic migraine (CM), 23 with episodic migraine (EM), and 35 HCs. All migraine diagnoses were made according to the International Classification of Headache Disorders, 3rd edition (ICHD-3) [2]. Eligible participants were aged 14 to 60 years, capable of completing MRI, and had not received preventive treatment in the preceding three months. There was no acute medication the day before the MRI scan. General exclusion criteria for both patients and HC included the presence of other primary headache or pain syndromes, pregnancy or lactation, neurological, cardiovascular, or endocrine disorders, substance abuse, a first-degree relative with a headache disorder, poor-quality MRI scans (e.g., artefacts or incomplete data).

Demographic assessment

Data collected from all patients included demographics, age (years), body mass index (BMI), gender (female/male), attack frequency (days/month), headache duration (years), Visual Analogue Scale (VAS) scores. Headache-related disability was quantified using the Headache Impact Test-6 (HIT-6).

Hypothalamic imaging acquisition and segmentation

High-resolution 3D T1-weighted structural MRI data were acquired at the National Neurological Center of Beijing Tiantan Hospital using a 3.0 Tesla GE Signa Premier scanner (GE Healthcare) equipped with a 48-channel head coil. Participants were instructed to remain still with their eyes closed throughout the scan. Imaging parameters for the magnetization-prepared rapid gradient echo (MP-RAGE) sequence included: preparation time = 880 ms, acquisition time = 4 min, recovery time = 400 ms, field of view = 250 × 250 mm², acceleration factor = 2, flip angle = 8°, 192 sagittal slices, and isotropic spatial resolution of 1 × 1 × 1 mm³.

Volumes of the hypothalamus and its five subregions—including the anterior superior (a-sHyp), anterior inferior (a-iHyp), superior tuberal (supTub), inferior tuberal (infTub), and posterior (posHyp) subunits—were delineated using a fully automated segmentation tool [16]. This tool is based on a deep convolutional neural network trained on T1-weighted MRI scans from 37 manually labeled subjects. To artificially increase the number of training samples and avoid preprocessing, the MRI scans were first subjected to data augmentation. The network adopts a 3D U-Net architecture, featuring a symmetric encoder–decoder structure with skip connections. By processing the full 3D context of input scans, it preserves spatial continuity across slices, enabling more accurate delineation of complex anatomical structures. Its symmetric encoder–decoder design with skip connections allows for precise localization by integrating both low-level spatial detail and high-level semantic information. Moreover, 3D U-Net supports end-to-end learning, performs effectively on small datasets with appropriate data augmentation, and can be flexibly applied to multiclass segmentation tasks. These characteristics make it particularly well-suited for robust and reproducible segmentation in brain MRI analyses. This method demonstrated high reproducibility and did not require additional preprocessing. After segmenting the hypothalamus into five subregions, the total hypothalamic volume was calculated as the sum of the volumes of these subregions.

Statistical analysis for demographic, clinical and neuroimaging data

Statistical analyses were performed using IBM SPSS Statistics 27.0. During the comparison of demographic characteristics, continuous variables were assessed for normality using the Shapiro–Wilk test. Normally distributed data are presented as mean ± standard deviation (SD), while non-normally distributed data are presented as median with interquartile range (IQR). Categorical variables are summarized as frequencies and percentages. Group comparisons between two groups were conducted using independent samples t-tests for normally distributed variables and Mann-Whitney U tests for non-normally distributed variables. Categorical variables were analyzed using Pearson’s χ² test or the continuity-corrected χ² test where appropriate. For comparisons among three groups (HC, EM, and CM), one-way analysis of variance (ANOVA) was used for normally distributed continuous variables, and the Kruskal–Wallis test was used when variables violated normality assumptions.

For comparisons of hypothalamic volumes between the HC and migraine groups, linear regression models were used, adjusting for age, gender, BMI, and total intracranial volume (TIV). For comparisons of hypothalamic volumes across clinical stage of migraine (HC to EM to CM), analysis of covariance (ANCOVA) was conducted, adjusting for age, gender, BMI, and TIV. Type III sum of squares was used to account for unbalanced design. Post hoc pairwise comparisons were conducted using estimated marginal means (emmeans) with FDR correction. Pearson correlation analyses performed between significantly different volumetric measures and clinical scores in the patient group.

GWAS of the hypothalamus and migraine

GWAS summary statistics for the volume of the hypothalamus and its five subregions were obtained from a previous study involving MRI and genetic data from 32,956 individuals [17]. This study employed the same segmentation procedure as the present study and performed GWAS, identifying 23 loci associated with hypothalamic volume, which were enriched for genes involved in intracellular trafficking and steroid metabolism.

GWAS smmary statistics for migraine were obtained from the largest GWAS to date (N_case = 79,495, N_control = 1,259,808), which also provided subtype-specific data for migraine with aura (MA; N_case = 16,603, N_control = 1,336,517) and without aura (MO; N_case = 11,718, N_control = 1,330,747) [18]. These participants were recruited from one tertiary headache clinics (N = 280,844) and five population-based cohorts (N = 1,058,459) through various methods, such as advertisements, the project’s website, national media campaigns, and referrals from headache centers. Detailed recruitment information is available in the respective cohort descriptions. All GWAS included in the present study were exclusively conducted among participants of European ancestry.

Mendelian randomization analysis

We used the TwoSampleMR package (https://github.com/MRCIEU/TwoSampleMR) to evaluate bidirectional causal relationships between the volumes of hypothalamic regions identified as significant in imaging analyses and the risk of migraine and its subtypes (MO and MA). The forward MR analysis was performed with hypothalamic volume as exposure and migraine as outcome. Conversely, the reverse MR analysis was performed with migraine as exposure and hypothalamic volume as outcome. Genetic instrumental variables (IVs) were defined as genome-wide significant (p < 5 × 10⁻⁸) Single Nucleotide Polymorphisms (SNPs) with a minor allele frequency (MAF) > 0.01. To reduce bias from weak instruments, only SNPs with F-statistics > 10 were retained [19, 20]. The resulting genetic IVs were pruned to high independence with a r² threshold of 0.001 and a window size of 10 Mb. To improve instrument quality, heterogeneity and outliers were assessed using ivw_radial and egger_radial functions in RadialMR (v0.4, https://github.com/WSpiller/RadialMR), applying Q and Q′ statistics at a nominal significance level of 0.05. Ambiguous or palindromic variants were corrected or excluded during harmonization to ensure allele alignment.

Causal estimates were obtained using the inverse variance-weighted (IVW) method, with a random-effects model for traits with more than three instruments and a fixed-effects model for those with two or three [21, 22]. Where only one SNP was available, the Wald ratio was applied [23]. Odds ratios (ORs) for disease risk were reported per standard deviation (SD) increase in hypothalamic volume. FDR correction was applied to address multiple comparisons.

Sensitivity analyses were performed to assess potential pleiotropy and heterogeneity. Horizontal pleiotropy was evaluated using MR-Egger regression and the MR-PRESSO Global test [24, 25], while Cochran’s Q statistic was used to assess heterogeneity among instrumental variables [26].

Mediation analysis of hypothalamus, gut microbiome, and migraine

Given the emerging role of the gut microbiome in migraine pathophysiology [11, 27] and recent evidence linking hypothalamic structure to gut microbial composition [28], we conducted a two-step MR mediation analysis to investigate whether gut microbiota mediate the relationship between hypothalamic volume and migraine risk. Microbiome GWAS summary statistics were obtained from the MiBioGen consortium [29]. This study analyzed 16 S rRNA gene sequencing and genotype data from 18,340 individuals across 24 cohorts in multiple countries, identifying associations between host genetic variation and gut microbial taxa. The dataset included 211 taxa across 131 genera, 35 families, 20 orders, 16 classes, and 9 phyla [29].

First, we assessed the causal effect of hypothalamic volume on gut microbial taxa using MR. We applied FDR correction to account for multiple testing. Second, taxa showing significant associations were tested for causal effects on migraine. Due to the limited number of genome-wide significant variants for microbial traits, we used a locus-wide significance threshold (p < 1.0 × 10⁻⁵) for instrument selection.

Mediation was quantified using the “product of coefficients” method [30], where the indirect effect was calculated as the product of the MR estimates from hypothalamic volume to microbiota and from microbiota to migraine. Standard errors were computed using the delta method [31], and the proportion mediated was defined as the ratio of the indirect effect to the total effect. A p-value < 0.05 was considered statistically significant for mediation testing.

Results

Demographics and clinical characteristics

A total of 111 participants were enrolled in the initial cohort, comprising 53 patients with CM, 23 with EM, and 35 HCs (Fig. 1). No significant differences were observed among three groups in terms of age, BMI, gender, or TIV (p > 0.05, respectively). No significant differences were observed between the two groups in disease duration and headache intensity (Table 1).

Table 1.

Demographic and clinical data

	Controls (n = 35)	EM (n = 23)	CM (n = 53)	P value
Ages (years)	36.89 ± 10.75	38.22 ± 13.20	42.00 (33.00-52.50)	0.166a
BMI	22.86 (20.70-24.81)	22.23 (20.82–23.94)	23.13 ± 3.26	0.786a
Gender (female/male)	22/13	17/6	36/17	0.677b
Intracranial volume	1452.53 ± 139.93	1453.51 ± 111.38	1478.64 ± 110.66	0.535c
Attack frequency (days/month)f	/	5.57 ± 2.82	30.00 (20.00–30.00)	< 0.001d
Disease duration (years)	/	11.00 (4.00–20.00)	20.00 (9.00–30.00)	0.078d
Headache intensity (VAS)	/	6.57 ± 1.72	7.22 ± 1.41	0.093e
HIT-6 score/(n)	/	64.88 ± 7.74/(17)	66.00 (63.50–72.00)/(33)	0.467d

EM Episodic migraine, CM Chronic migraine, BMI Body mass index, VAS Visual analogue scale, HIT-6 Headache Impact Test-6, n number

^aKruskal-Wallis test,

^bChi-square test,

^cOne-way ANOVA,

^dMann–Whitney U test,

^eIndependent samples t test

^fmonthly headache days

Migraine patients exhibited reduced hypothalamic volume relative to HC

The spatial characteristics of hypothalamic subregion segmentation are shown in Fig. 2A. A flowchart illustrating the hypothalamus segmentation process is provided in Supplementary Fig. 1. The specific nuclei contained within each hypothalamic subregion are listed in Table 2. To assess volumetric differences in the hypothalamus, patients with EM and CM were combined into a single migraine group and compared with HCs. Total hypothalamic volume was significantly reduced in the migraine group compared to HCs (813.53 ± 66.46 mm³ vs. 831.86 ± 57.91 mm³; FDR q = 0.048). Subregional analysis revealed smaller volumes in the inferior tubular (255.26 ± 30.17 vs. 265.29 ± 23.32 mm³; p = 0.009) and inferior anterior (33.97 ± 6.64 vs. 36.87 ± 5.05 mm³; p = 0.030) hypothalamic regions among migraine patients. After correction for multiple comparisons, the difference in the inferior tubular region remained statistically significant (Fig. 2B, FDR q = 0.046).

Fig. 2.

Migraine patients exhibited reduced hypothalamic volume relative to HC. A The hypothalamus is divided into the following five subregions: anterior superior (a-sHyp), anterior inferior (a-iHyp), superior tuberal (supTub), inferior tuberal (infTub) and posterior (posHyp). B Total and inferior tubular hypothalamic volumes were significantly reduced in the migraine group compared to HCs. Statistical analysis was adjusted for age, gender, BMI, and total intracranial volume

Table 2.

Grouping of the hypothalamic nuclei into subregions

Subregions	Nuclei included
Anterior-superior (a-sHyp)	preoptic area; paraventricular nucleus (PVN)
Anterior-inferior (a-iHyp)	suprachiasmatic nucleus; supraoptic nucleus (SON)
Superior tubular (supTub)	dorsomedial nucleus; PVN; lateral hypothalamus
Inferior tubular (infTub)	infundibular (or arcuate) nucleus; ventromedial nucleus; SON; lateral tubular nucleus; tuberomamillary nucleus (TMN)
Posterior (posHyp)	mamillary body (including medial and lateral mamillary nuclei); lateral hypothalamus; TMN

Hemispheric analyses further revealed significant volume loss in the left inferior tubular region (133.53 ± 17.16 mm³ vs. 140.26 ± 13.48 mm³; FDR q = 0.046). Additional lateralized volume decreases were observed in the right superior tubular (120.21 ± 11.45 mm³ vs. 125.70 ± 12.25 mm³; FDR q = 0.046) and right anterior inferior subregions (16.38 ± 3.98 mm³ vs. 18.32 ± 3.40 mm³; FDR q = 0.046) (Fig. 2B).

Progressive hypothalamic atrophy with the clinical stage of migraine

When comparing hypothalamic whole and subregion volumes across the three groups, significant differences were observed in the whole hypothalamus (F = 4.722, FDR q = 0.011) and the inferior tuberal subregion (F = 5.014, FDR q = 0.008). Further side-specific analyses revealed significant group differences in the left inferior tuberal (F = 5.137, FDR q = 0.007), right superior tuberal (F = 4.894, FDR q = 0.009), and right anterior inferior subregions (F = 3.380, FDR q = 0.038) (Table 3).

Table 3.

Volume comparison of hypothalamus and its subregions in migraine subtypes

Region	HC (n = 35)	EM (n = 23)	CM (n = 53)	F	P	β1	P1	β2	P2	β3	P3
Whole	831.86 ± 57.91	819.73 ± 61.33	810.84 ± 68.95	4.722	0.011	27.361	0.005	8.530	0.367	18.831	0.051
Inferior tubular	265.29 ± 23.32	258.29 ± 25.26	253.94 ± 32.20	5.014	0.008	14.122	0.003	5.532	0.268	8.590	0.082
Left inferior tubular	140.26 ± 13.48	134.69 ± 12.04	133.03 ± 19.04	5.137	0.007	9.303	0.005	5.183	0.209	4.120	0.209
Right inferior tubular	125.04 ± 11.36	123.60 ± 15.23	120.91 ± 16.39	2.500	0.087	4.820	0.144	0.349	0.904	4.470	0.152
Superior tubular	241.52 ± 23.57	237.60 ± 21.89	233.59 ± 21.46	2.205	0.115	8.562	0.063	2.652	0.563	5.910	0.185
Left superior tubular	115.82 ± 14.30	115.02 ± 12.25	114.41 ± 12.07	0.276	0.759	1.628	0.835	−0.066	0.983	1.694	0.835
Right superior tubular	125.70 ± 12.25	122.58 ± 11.06	119.18 ± 11.56	4.894	0.009	6.934	0.008	2.718	0.319	4.215	0.149
Anterior inferior	36.87 ± 5.05	33.59 ± 7.80	34.14 ± 6.14	2.441	0.092	2.731	0.054	3.160	0.054	−0.429	0.814
Left anterior inferior	18.54 ± 3.11	16.84 ± 4.62	17.92 ± 3.62	1.188	0.309	0.499	0.549	1.530	0.386	−1.031	0.407
Right anterior inferior	18.32 ± 3.40	16.76 ± 4.23	16.22 ± 3.89	3.380	0.038	2.232	0.034	1.631	0.180	0.601	0.537
Anterior superior	46.83 ± 5.98	45.37 ± 7.33	45.78 ± 6.85	0.404	0.669	1.133	0.550	1.480	0.245	−0.347	0.757
Left anterior superior	23.69 ± 3.29	22.51 ± 3.65	23.18 ± 3.19	0.674	0.512	0.309	0.678	1.025	0.588	−0.716	0.588
Right anterior superior	23.13 ± 3.39	22.86 ± 4.46	22.60 ± 4.40	0.396	0.674	0.824	0.724	0.455	0.724	0.369	0.724
Posterior	241.36 ± 28.82	244.88 ± 19.04	243.39 ± 27.67	0.468	0.628	0.812	0.823	−4.295	0.498	5.107	0.164
Left posterior	118.19 ± 14.34	120.95 ± 10.40	120.57 ± 15.92	0.411	0.664	−0.829	0.765	−2.959	0.739	2.131	0.739
Right posterior	123.17 ± 17.36	123.93 ± 11.53	122.82 ± 14.31	0.481	0.620	1.641	0.693	−1.336	0.693	2.977	0.693

EM Episodic migraine, CM Chronic migraine, F, P Differences between three groups (ANCOVA). β1, P1: HC vs. CM. β2, P2: HC vs. EM. β3, P3: EM vs. CM. P1, P2, P3: FDR q

Subsequently, pairwise comparisons were performed for the whole hypothalamus and its five subregions. Patients with CM demonstrated significantly reduced total hypothalamic volume (β = 27.361, FDR q = 0.005) and inferior tubular volume (β = 14.122, FDR q = 0.003) compared to HCs. Further side-specific analyses demonstrated significant volume differences between the HC and CM groups in the left inferior tuberal (β = 9.303, FDR q = 0.005), right superior tubular (β = 6.934, FDR q = 0.008), and right anterior inferior subregions (β = 2.232, FDR q = 0.034). It is noteworthy that, despite the lack of statistically significant differences between EM and HCs, an decreasing trend in total and inferior tubular hypothalamic volume was observed from HCs (831.86 mm³, 265.29 mm³) to EM (819.73 mm³, 258.29 mm³), and subsequently to CM (810.84 mm³, 253.94 mm³). The relatively small sample size in the EM group may have limited the statistical power to detect significant differences.

Associations between hypothalamic volume and clinical symptom

After adjusting for age, gender, BMI, and TIV, we found a significant negative association between inferior tubular volume and migraine attack frequency (Pearson’s r = −0.232, p = 0.043), suggesting smaller volumes in this subregion were linked to higher migraine attack frequency.

Causal relationships between hypothalamic volumes and migraine

The forward MR analysis revealed a significant causal relationship between reduced total hypothalamic volume and increased migraine risk (Fig. 3A, OR = 0.80, FDR q = 7.28 × 10⁻⁵). Subregional analysis identified a similar association for the inferior tubular region (Fig. 3A, OR = 0.85, FDR q = 2.61 × 10⁻²). In migraine subtype analysis, the same pattern was observed for MO, where both reduced total hypothalamic volume (Fig. 3A, OR = 0.83, FDR q = 1.83 × 10⁻²) and inferior tubular volume (Fig. 3A, OR = 0.77, FDR q = 1.83 × 10⁻²) were significantly associated with elevated MO risk. No significant causal associations were found for MA (Fig. 3A, Table S1). The reverse MR analysis indicated that MO was associated with reduced total hypothalamic volume (p = 0.031). However, after the FDR correction, there was no significant reverse causal relationship (Fig. 3B, Table S2).

Fig. 3.

Bidirectional MR results between hypothalamic volume and migraine. A Decreased total and inferior tubular hypothalamic volume showed a causal association with an increased risk of migraine and MO. B No causal relationship was found between migraine and MO and total or inferior tubular hypothalamic volume. Abbreviations: MO, migraine without aura; OR, odds ratios

Mediation effect of hypothalamic volume on migraine via gut microbiome

We identified significant causal relationships between hypothalamic volume and several gut microbial taxa. Specifically, reduced total hypothalamic volume was associated with lower abundance of genus Eubacteriumruminantiumgroup and genus DefluviitaleaceaeUCG011 (FDR q = 0.021 and 0.049, respectively), while decreased inferior tubular volume was associated with increased abundance of family FamilyXIII (FDR q = 0.011). The remaining results can be found in Table S3. Subsequent analyses revealed that reduced abundance of genus DefluviitaleaceaeUCG011 was significantly associated with increased risk of migraine, and lower abundance of genus Eubacteriumruminantiumgroup was associated with elevated risk of MO (p = 0.048 and 0.009, respectively). In contrast, higher abundance of family FamilyXIII was linked to decreased MO risk (p = 0.003; Table S4). Mediation analysis further showed that genus DefluviitaleaceaeUCG011 and genus Eubacteriumruminantiumgroup partially mediated the effects of total hypothalamic volume on migraine and MO, accounting for 5.2% (Fig. 4A, p = 0.047) and 11.8% (Fig. 4B, p = 0.021) of the total effect, respectively. Moreover, family FamilyXIII exhibited a suppressive mediation effect, accounting for 20.9% (Fig. 4C; Table 4, p = 0.027) of the association between inferior tubular volume and MO risk.

Fig. 4.

Mediation analyses to quantify the effects of hypothalamus volume on migraine via gut microbiome. A Causal effect of total hypothalamic volume on migraine is mediated by genus DefluviitaleaceaeUCG011. B Causal effect of total hypothalamic volume on migraine is mediated by genus Eubacteriumruminantiumgroup. C Causal effect of total hypothalamic volume on migraine is mediated by Family FamilyXIII. Abbreviations: β_EM, effects of exposure on mediator; β_MO, effects of mediator on outcome; β_EO, effects of exposure on outcome

Table 4.

The mediation effect of volume of hypothalamus on migraine via affecting gut Microbiome

Migraine
Volume of hypothalamus	gut microbiome	β1	se1	β2	se2	p_value	mediation_effect	se	total_effect	Proportion
Whole	Genus DefluviitaleaceaeUCG011	0.23	0.07	−0.05	0.02	0.047	−0.012	0.006	−0.22	5.2%

MO
Whole	Genus Eubacteriumruminantiumgroup	0.29	0.08	−0.09	0.03	0.021	−0.026	0.011	−0.22	11.8%
Inferior tubular	Family FamilyXIII	−0.15	0.04	−0.22	0.08	0.027	0.033	0.015	−0.16	20.9%

β1 and se1 denotes the MR effect of volume of hypothalamus on gut microbiome. β2 and se2 represents the MR effect of these gut microbiome on migraine. total_effect represents the MR effect of volume of hypothalamus on migraine

Results of sensitivity analysis

The robustness of the primary MR findings was confirmed through multiple sensitivity analyses. No evidence of heterogeneity was detected in the significant hypothalamus–migraine associations (p > 0.05; Table S5). The MR-Egger intercept (p > 0.05) and MR-PRESSO global test (p > 0.05; Table S5) indicated the absence of horizontal pleiotropy.

Discussion

In this study, we integrated neuroimaging and MR approaches to investigate the role of the hypothalamus in migraine pathophysiology. Applying deep learning techniques on T1-weighted MRI data, we identified reduced total hypothalamic volume and inferior tubular hypothalamic volume in migraine patients, particularly in CM patients. These alterations were most pronounced in the left inferior tubular subregion. MR analyses further supported causal effects of decreased hypothalamic volume on increased migraine risk, with the strongest effects observed for the MO subtype. Notably, we found that specific gut microbial taxa (such as genus DefluviitaleaceaeUCG011, genus Eubacteriumruminantiumgroup, and family FamilyXIII) partially mediated the effect of hypothalamic atrophy on migraine susceptibility. These findings suggest that alterations in hypothalamic structure causally influence migraine via the brain–gut axis, offering new insights into migraine pathophysiology and potential microbiota-targeted interventions.

The hypothalamus, though small in size, plays a central role in regulating essential bodily functions. Through extensive communication with other brain regions, it orchestrates key metabolic processes and governs autonomic nervous system activities, including circadian rhythms, appetite, blood pressure, and heart rate [32]. Previous studies have implicated the hypothalamus in the pathophysiology of migraine [33, 34]. Moreover, recent evidence suggests that the hypothalamus may play a critical role in migraine chronification [35]. In addition, there are neuroimaging studies have shown hypothalamic activation before migraine attacks and structural abnormalities, especially in the posterior region [36]. In line with these findings, we observed volume reductions in the whole hypothalamus and the left inferior tuberal subregion, aligning with the respective roles in neuroendocrine regulation. The inferior tubular subregion, particularly on the left side, exhibited significant volume loss in CM. This region encompasses nuclei integral to hypothalamic–pituitary–adrenal (HPA) axis regulation, and its atrophy may represent structural consequences of chronic stress exposure—such as cortisol rhythm disruptions and neuroendocrine dysregulation—that are characteristic of migraine chronification [37]. Moreover, its proximity to autonomic regulatory centers may underlie gastrointestinal and other vegetative symptoms often accompanying migraine. These lateralized structural alterations may contribute to the transition from episodic to chronic migraine through maladaptive plasticity in distinct hypothalamic subdomains.

Unlike previous cross-sectional studies, our use of Mendelian randomization provides genetic support for a directional relationship between hypothalamic atrophy and migraine risk. This extends the current literature by suggesting a potentially causal role of hypothalamic structure, especially when considering gut microbiota as a mediator. However, this interpretation should be made with caution. MR relies on key assumptions, including no horizontal pleiotropy and valid instrumental variables. Although sensitivity analyses support the robustness of our findings, the possibility of unmeasured confounding or horizontal pleiotropy cannot be entirely ruled out. In addition, we found a negative association between inferior tubular volume and migraine attack frequency. Notably, a progressive decline in left inferior tubular volume was observed across the clinical continuum—from HCs to EM and then to CM—although the difference between EM and CM did not reach statistical significance, possibly due to limited sample size. This volumetric trend suggests that hypothalamic atrophy may contribute to disease progression and could serve as a potential imaging biomarker for migraine chronification. In our MR analysis, reduced volumes of the whole hypothalamus and inferior tubular region were causally associated with increased risk of migraine and MO, but not with MA. This finding is consistent with previous structural imaging studies reporting hypothalamic atrophy in MO [10]. Notably, abnormal activation of hypothalamic regions has been observed even during the interictal phase in MO [9], suggesting maladaptive neuroplastic changes that may underlie structural remodeling. In contrast, neuroimaging studies have not consistently identified hypothalamic alterations in MA, possibly reflecting distinct pathophysiological mechanisms. While MO appears to involve central regulatory structures such as the hypothalamus in headache initiation and chronification [35], MA may be more closely linked to transient cortical dysfunction, particularly in visual processing regions.

The association between inferior tubular atrophy and migraine risk may be driven by dysfunction within key nuclei embedded in this subregion, including the infundibular (arcuate) nucleus (ARC), ventromedial nucleus (VMH), supraoptic nucleus (SON), lateral tubular nucleus, and tuberomammillary nucleus (TMN). The hypothalamic ARC may contribute to migraine pathogenesis through an integrated neuroendocrine-metabolic network [38]. ARC neurons project to the periaqueductal gray (PAG), where glutamatergic and galaninergic pathways mediate anti-nociceptive effects [39, 40]. The ARC also regulates metabolic signals via neuropeptides (α-MSH, NPY) and hormones (leptin, insulin), linking metabolic dysregulation (such as obesity) to migraine susceptibility [41]. Animal and molecular studies further reveal that ARC dysfunction may underlie the higher prevalence of migraine in women through neuroendocrine mechanisms [42]. Collectively, the ARC likely serves as a hub integrating pain, metabolic, and hormonal pathways to drive migraine pathophysiology. The ventromedial hypothalamus (VMH) plays a key role in metabolic regulation, with lesion studies showing that VMH damage increases insulin and decreases glucagon levels [43], potentially promoting migraine chronification via impaired glucose homeostasis [44]. PACAP mRNA expression in leptin-sensitive VMH neurons negatively correlates with diet-induced weight gain, and PACAP receptor antagonism attenuates leptin’s hypophagic and thermogenic effects [45, 46]. PACAP infusion can trigger migraine-like attacks [47], and the ventromedial hypothalamus (VMH) regulates autonomic and metabolic functions relevant to migraine. Therefore, impaired PACAP signaling in the VMH may serve as a mechanistic link between metabolic dysregulation and increased migraine susceptibility. The supraoptic nucleus (SON), a major source of oxytocin (OXT), may contribute to migraine regulation through widespread OXTergic projections and receptor distribution [48]. Central OXT signaling is emerging as a potential key factor in migraine pathophysiology, with evidence suggesting that endogenous OXT can alleviate acute trigeminal allodynia by shortening its duration [49]. A deeper understanding of hormonal influences on migraine mechanisms is essential for improving migraine management, particularly in women. Interestingly, vasopressin (VAP), another output of the supraoptic nucleus (SON), acts on trigeminal, spinal, and midbrain regions involved in migraine. This suggests that VAP and its receptors may contribute to hormonal modulation of migraine susceptibility in females [50]. The lateral tuberal nucleus remains relatively understudied, and no direct association with migraine has yet been identified. However, it contains receptors for corticotropin-releasing factor, somatostatin, muscarinic cholinergic transmission, benzodiazepines, and N-methyl-D-aspartate (NMDA), suggesting its potential involvement in neuroendocrine and neurotransmitter regulation. Notably, the lateral tuberal nucleus is affected in several human neurodegenerative diseases, highlighting its vulnerability and possible relevance to broader neurological dysfunction [51]. The tuberomammillary nucleus (TMN), the brain’s primary source of histamine, promotes wakefulness by activating basal forebrain cholinergic and raphe serotonergic neurons via H₁ receptors [52]. Given that sleep disturbances are common migraine triggers, TMN dysfunction may contribute to migraine susceptibility. Central histamine H3 receptor signaling negatively regulates autoimmune inflammation in the CNS [53], suggesting a link between histaminergic pathways and neuroinflammatory mechanisms involved in migraine pathogenesis. TMN dysfunction has also been associated with various neurological disorders, including cognitive impairment, Alzheimer’s disease [54], and schizophrenia [55], underscoring its broader relevance to brain health.

Our results support a model in which hypothalamic structural alterations modulate migraine susceptibility, in part through downstream effects on gut microbial composition. As a central integrator of autonomic, neuroendocrine, and metabolic signals [32], the hypothalamus exerts top-down influence on gastrointestinal function via the HPA axis [28], the vagus nerve [56], and enteric neuropeptide pathways [57]. Dysregulation of these circuits (especially in nuclei within the inferior tubular region, such as the arcuate and ventromedial nuclei) can impair gut motility, permeability, immune responses, and mucosal secretion. These changes may in turn alter the composition of the gut microbiota [43, 58]. Emerging experimental evidence further supports a bidirectional hypothalamus–microbiota–migraine axis. Kasarello et al. highlighted how gut microbiota influence hypothalamic and trigeminal pathways via microbial metabolites, HPA axis signaling, and neurotransmitters [59]. Supporting this, Sudo et al. showed that early-life microbial colonization programs HPA axis responsiveness through hypothalamic regulation [60]. Tang et al. further demonstrated that gut dysbiosis enhances migraine-like pain via TNFα upregulation in the spinal trigeminal nucleus, reversible by microbiota restoration [61]. These studies provide direct mechanistic evidence for the hypothalamus–microbiota–migraine axis. Our findings show that reduced hypothalamic volume is associated with both a lower abundance of key microbial taxa (e.g., genus DefluviitaleaceaeUCG011, genus Eubacteriumruminantiumgroup) and an increased risk of migraine. This suggests that structural vulnerability in the hypothalamus may initiate or worsen gut dysbiosis, which in turn may amplify neuroinflammatory and nociceptive signaling involved in migraine attacks. Moreover, chronic dysbiosis may reinforce hypothalamic dysfunction via systemic inflammation or metabolic stress [62], potentially establishing a self-perpetuating feedback loop. These findings highlight the hypothalamus as a key upstream regulator in the brain–gut–migraine axis and point toward the therapeutic potential of preserving hypothalamic integrity and microbial homeostasis in migraine prevention.

Several limitations should be acknowledged in this study. First, the relatively small sample size of the EM subgroup may have limited the statistical power to detect subtle differences in hypothalamic volume. Second, the neuroimaging data were derived exclusively from Asian participants, which may limit the generalizability of the findings to other ethnic populations. Future studies involving larger and more ethnically diverse cohorts are warranted to validate and extend the present results. Third, there was a mismatch between imaging and genetic subgroup classifications. Due to limited MA cases, imaging analyses focused on the progression stages (EM and CM), whereas MR relied on publicly available GWAS data distinguishing only MO and MA, without separating EM from CM. Although this limited direct comparability, it also allowed complementary perspectives—capturing both clinical progression (EM vs. CM) and biological subtype (MO vs. MA)—thereby enhancing the multidimensional interpretation of hypothalamic involvement in migraine. Finally, although our mediation analysis suggests a potential gut microbial pathway linking hypothalamic structure to migraine, the underlying mechanisms remain to be elucidated and require validation through dedicated experimental studies.

In summary, this study integrates neuroimaging, genetic, and microbiome data to reveal that structural alterations in the hypothalamus (particularly within the left inferior tubular subregion) are causally associated with increased migraine risk and frequency. Furthermore, we provide initial evidence that gut microbial composition may partially mediate this relationship, supporting the existence of a hypothalamus–microbiota–migraine axis. These findings advance our understanding of the neurobiological and systemic underpinnings of migraine and highlight the hypothalamus as a potential therapeutic target.

Abbreviations

EM

Episodic migraine

CM

Chronic migraine

HCs

Healthy controls

MR

Mendelian randomization

GWAS

Genome-wide association study

ICHD-3

International Classification of Headache Disorders, 3rd edition

BMI

Body mass index

VAS

Visual Analogue Scale

HIT-6

Headache Impact Test-6

TIV

Total intracranial volume

FDR

False discovery rate

MA

Migraine with aura

MO

Migraine without aura

MAF

Minor allele frequency

IVW

Inverse variance weighted

ORs

Odds ratios

SD

Standard deviation

ARC

Arcuate nucleus

VMH

Ventromedial nucleus of hypothalamus

SON

Supraoptic nucleus

TMN

Tuberomammillary nucleus

PAG

Periaqueductal gray

SON

Supraoptic nucleus

OXT

Oxytocin

VAP

Vasopressin

NMDA

N-methyl-D-aspartate

HPA

Hypothalamic–pituitary–adrenal

Authors’ contributions

All authors contributed to the study conception and design. ZHX and LZ wrote the original draft. ZHX, LZ, GYL, DQ, YLM, XSL, ZG, PZ, MTZ and TSG analyzed the data. ZHX prepared Figures and tables. YGW, LZ, GYL, DQ, YLM, XSL, ZG, PZ, MTZ, TSG, JJS, XL reviewed and edited the final draft. All authors contributed to the article and approved the submitted version.

Funding

This study was supported by the Beijing Natural Science Foundation (Grant Number: Z200024), National Key R&D Program of China (2024YFC2510100), Joint Funds of the National Natural Science Foundation of China (U24A20683), National Natural Science Foundation of China (32170752), and Beijing Natural Science Foundation (F252058).

Data availability

All data generated or analysed during this study are included in this published article and its supplementary information files. The summary statistics obtained from the genome-wide association are publicly available. The summary statistics for hypothalamus can be obtained from figshare (https://figshare.com/projects/GWAS_summary_data_of_hypothalamus/165589). The GWAS summary statistics for the migraine GWAS meta-analyses are available at https://www.decode.com/summarydata/. Full GWAS summary statistics for gut microbiome mbQTLs are available at www.mibiogen.org.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Beijing Tiantan Hospital, Capital Medical University (approval number: KY2022-044), as a sub-study of the ongoing China HeadAche DIsorders RegiStry Study (CHAIRS; NCT05334927). Written informed consent was obtained from all participants in accordance with the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.