Sage Journals: Discover world-class research

Abstract

Background

Hippocampus (HIP) was an important limbic structure, and concurrent emotion disorders may occur in medication-overuse headache patients. The aim of this study is to investigate altered HIP and HIP subfields volume in relation with the anxiety in medication-overuse headache patients using a state-of-the-art hippocampal segment method.

Results

The current study presented that a significant lower HIP and HIP subfields volume were identified in medication-overuse headache compared with that in normal controls except right HIP tail, bilateral parasubiculums, and HIP fissure. The left HIP and right subiculum presented negative correlation with headache variables, and the right subiculum, Cornu Ammonis 4, granule cell layer of dentate gyrus, bilateral Cornu Ammonis 1, molecular layer, and whole HIP presented negative correlation with Hamilton Anxiety Scale score, which were further confirmed by the linear regression analysis with the exclusion of psychological variables and headache variables, respectively.

Conclusions

The lower HIP and HIP subfields volume were identified in medication-overuse headache patients, and negatively related with anxiety condition. The potential mechanism for the comorbidity medication-overuse headache and anxiety might be interpreted as the reciprocal causation relationship and co-occurrence relationship.

Keywords

Hippocampal segment hippocampal subfields volumetry hippocampal structural imaging migraine magnetic resonance imaging

Introduction

Hippocampus (HIP) was an important medial temporal lobe structure and mainly included dentate gyrus (DG), subiculum, presubiculum, parasubiculum, and Cornu Ammonis (CA), which played key roles in the memory¹ and healthy aging.² Besides, HIP was also an important one of limbic structure as like cingulate cortex, amygdala, and olfactory cortex, which could be associated with the mood disorders.^3,4 Some previous studies demonstrated that different hippocampal subfields would participate in the different mood disorders, e.g., volume reductions of CA One (CA1) and the DG in schizophrenia,⁵ volume loss of subiculum and CA Two–CA Three (CA2–3) in medication-naïve female patients with major depressive disorder (MDD),⁶ and multiple hippocampal subfields volume reduction in bipolar disorder and MDD.³ Therefore, these findings suggested that HIP was not a uniform structure, and the precise structural changes of hippocampal subfields may provide more information on the neuromechanism of the brain disorder.

Medication-overuse headache (MOH) was one of chronic headache characterized by repetitive and excessive overconsumption of analgesics or acute anti-migraine drugs.⁷ In a previous study, functional connectivity increased between precuneus and HIP, and voxel-based morphometry did not detect any significant brain volume change in this MOH patient entity.⁸ The other structure studies identified that volume gain of periaqueductal gray matter (PAG) presented in MOH patients,^9,10 and one study confirmed that there was no significant brain volume changes in MOH patients.¹¹ However, the elaborate hippocampal subfields measurement were not performed in MOH patients up to now.

Headache perception may include physiological and psychological factors, and the increased functional connectivity of HIP indicated that HIP might participate in the emotion control,⁸ but the link between the hippocampal subfield volume and the MOH had not been investigated.

The previous studies recognized that MOH was associated with mood disorders in 27%–85% and anxiety disorders in 61%–83%.^12,13 The voxel-based morphometry study demonstrated that the increased volume in PAG was positively correlated with anxiety scores, and anxiety might be associated with the dysfunction of antinociceptive system in MOH.¹⁰ A recent review study suggested that the affective and anxiety disorders had an increased risk in migraine patients compared with non-migraine patients, and prevailed in patients with chronic forms or transform of headache and substance use than in patients with migraine alone.¹⁴ However, the neuromechanism of migraine concomitant with anxiety was not totally understood.

The current study is aimed to investigate the relationship between MOH and anxiety. We hypothesize that HIP volume change may be associated with MOH. To address this hypothesis, we prospectively obtained high-resolution structural images from 31 MOH patients and 31 normal controls (NCs) to calculate and analyze total HIP and hippocampal subfield volume change using a state-of-the-art hippocampal segmentation approach.¹⁵ The generalized linear model was used to compute the linear regression equation to determine the effect of the headache variables, anxiety, depression, and cognitive variables on the HIP volume change in MOH patients.

Materials and methods

Subjects

Thirty-one MOH patients were recruited from the International Headache Center, Department of Neurology, Chinese PLA General Hospital. The diagnostic criteria of MOH was based on the International Classification of Headache Disorders, third Edition (beta version) (ICHD-III beta),¹⁶ including the diagnosis of 8.2 MOH, 1.1, and 1.2 migraine. The inclusion criteria should be included as follows: (1) no migraine preventive medication used in the past three months; and (2) patient’s willingness to engage in the study. The patients with the following criteria should be excluded out: (1) with any chronic disorders, including hypertension, diabetes mellitus, cardiovascular diseases, etc.; and (2) with cranium trauma, illness interfering with central nervous system function, psychotic disorder, and regular use of a psychoactive or hormone medication. Thirty-one NCs were recruited, who had the same inclusion and exclusion criteria with MOH patients. NCs should never have any primary headache disorders or other types of headache in the past year. General demographic and headache information were registered and evaluated in our headache database. Additionally, we evaluated anxiety, depression, and cognitive function of all the participants by using the Hamilton Anxiety Scale (HAMA),¹⁷ the Hamilton Depression Scale (HAMD),¹⁸ and the Montreal Cognitive Assessment (MoCA) Beijing Version (www.mocatest.org). The study protocol was approved by the Ethical Committee of Chinese PLA General Hospital and complied with the Declaration of Helsinki. Informed consents were obtained from all participants before the study. Magnetic resonance imaging (MRI) scans were taken at least three days after a migraine attack for MOH patients. All the patients were assessed using the Visual Analogue Scale (VAS) and Migraine Disability Assessment (MIDAS). All the subjects were right-handed and underwent conventional MRI examination to exclude the subjects with cerebral infarction, malacia, or occupying lesions. Alcohol, nicotine, caffeine, and other substances were avoided for at least 12 h before MRI examination.

MRI acquisition

The brain structure images and conventional MR images were obtained from a GE three-tesla MR system (DISCOVERY MR750, GE Healthcare, Milwaukee, WI, USA), and a conventional eight-channel quadrature head coil was used. All subjects were instructed to lie in a supine position, and formed padding was used to limit head movement. An axial three-dimensional T1-weighted fast spoiled gradient recalled echo (3D T1-FSPGR) sequence was performed with the following parameters: TR (repetition time) = 6.3 ms, TE (echo time) = 2.8 ms, flip angle = 15°, FOV (field of view) = 25.6 cm × 25.6 cm, Matrix = 256 × 256, NEX (number of acquisition) = 1. Conventional T2-weighted imaging (T2WI), T1 fluid-attenuated inversion recovery (T1-FLAIR) weighted imaging, and diffusion weighted imaging (DWI) were also acquired. All imaging protocols were identical for all subjects. No obvious structural damage and T2-visible lesion were observed based on the conventional MR images.

MR image processing

All MR structural image data were processed using the hippocampal subfield segmentation package in Freesurfer image analysis software (http://surfer.nmr.mgh.harvard.edu/) (stable v6.0.0)^15,19–20 running under Ubuntu 12.04.2. The image processing included following steps: (1) The structural images were performed with volumetric and surface processing using Freesurfer recon-all—all pipeline;²¹ (2) The segmentation of individual hippocampal subfields was performed using Freesurfer hippocampal-subfields-T1 pipeline, which included the following steps: (1) Whole HIP segment were performed from the automated pipeline for volumetric segmentation of subcortical structures implemented in Freesurfer; (2) HIP subfields segment was performed using a Bayesian inference approach according to a novel atlas of the HIP built in Freesurfer; (3) HIP was segmented into 12 subfields: hippocampal tail, subiculum, presubiculum, parasubiculum, Cornu Ammonis 1 (CA1), CA2/3, CA4, granule cell layer of dentate gyrus (GC-DG), molecular layer, fimbria, HIP-amygdala-transition-area, and hippocampal fissure (Figure 1).^15,19 (4) The final hippocampal subfields volume and brain parenchymal volume were measured for the statistical analysis.

Figure 1.

The 12 hippocampal subfields were segmented and labeled with different colors. CA: Cornu Ammonis; GC-DG: granule cell layer of dentate gyrus; HATA: hippocampus-amygdala-transition-area; HP: hippocampus.

Statistical analysis

The statistical analysis was performed by using PASW Statistics 18.0. The significant differences of hippocampal volume between MOH group and NC group were compared with general linear model (independent univariate t-test with age, sex, and total brain parenchymal volume as covariates). The Pearson's correlation analysis was applied between hippocampal volume and the clinical variables in MOH. The age, HAMD, and MoCA were performed with independent samples t-test, HAMA was performed with Welch test because of variance nonhomogeneity, and sex was performed with Chi-Square test. Linear regression (Backward method) was performed between the volume of HIP and HIP subfields and the clinical variables including disease duration (DD), headache days per month (HDPM), VAS, MIDAS, drug pills taken (DP), HAMA, HAMD, and MoCA, which would be used to identify the clinical parameters participating in the hippocampal volume changes. The linear regression analysis over the whole brain was performed by QDEC tool of Freesurfer 6.0 software (with Monte Carlo simulations for multiple comparisons correction). Significant difference was set at a P value of < 0.05.

Results

The clinical characteristics of MOH and NCs

There was no significant difference for age between MOH (42.55 ± 10.31 years old) and NC (45.09 ± 10.50 years old), and there was a significant difference for sex between two groups. There were significant high scores of HAMA and HAMD and lower MoCA in MOH than that in NC (P < 0.05). The disease duration was 18.32 ± 9.45 years, and the scores of VAS and MIDAS were 8.23 ± 1.61 and 136.10 ± 72.10, respectively. Table 1 shows that HDPM was 27.58 ± 4.57 days and the number of drug pills taken per day was 5.76 ± 4.43.

Table 1.

The clinical characteristics of MOH and normal controls.

	MOH	NC	t value	P value
Num (F/M)a	31 (27/4)	31 (19/12)	5.391	0.02
Age	44.06 ± 9.28	41.06 ± 10.95	1.16	0.25
HAMAb	18.84 ± 9.73	10.26 ± 3.00	22.03	0.00
HAMDb	20.70 ± 13.16	8.16 ± 4.34	24.65	0.00
MoCA	23.55 ± 3.76	27.13 ± 2.35	20.24	0.00
MMSE	26.42 ± 4.11	28.19 ± 0.91	2.35	0.02
DD (years)	18.32 ± 9.45
HDPM (d/M)	27.58 ± 4.57
VAS	8.23 ± 1.61
MIDAS	136.10 ± 72.10
DP	5.76 ± 4.43

Note: HAMA: Hamilton Anxiety Scale; HAMD: Hamilton Depression Scale; MoCA: Montreal Cognitive Assessment; DD: disease duration; HDPM: headache days per month; VAS: Visual Analogue Scale; MIDAS: Migraine Disability Assessment; DP: the number of drug pills taken per day; MOH: medication-overuse headache; NC: normal control; MMSE: Mini-mental State Examination.

^aPearson Chi-Square test with Chi-Square value 5.391.

^bWelch test because of variance nonhomogeneity.

Comparison of hippocampal subfields volume between MOH and NC

There was a significant lower hippocampal subfields volume in MOH than that in NC (P < 0.05) except right HIP tail, bilateral parasubiculums, and HIP fissure (P > 0.05) (Table 2). Figure 2 shows that bilateral whole HIPs had lower volume in MOH than that in NC (P < 0.05).

Table 2.

Comparison of the volume of hippocampal subfields between MOH and NC.

	Left hippocampus				Right hippocampus
	MOH	NC	t value	P value	MOH	NC	t value	P value
HIP_tail	0.526 ± 0.064	0.563 ± 0.074	2.134	0.037	0.572 ± 0.067	0.585 ± 0.068	0.756	0.453
Subiculuma	0.426 ± 0.031	0.471 ± 0.057	14.972	0.000	0.431 ± 0.037	0.472 ± 0.052	3.574	0.001
Presubiculum	0.303 ± 0.028	0.326 ± 0.042	2.520	0.014	0.290 ± 0.028	0.311 ± 0.036	2.575	0.013
Parasubiculum	0.055 ± 0.008	0.059 ± 0.009	1.948	0.056	0.053 ± 0.007	0.057 ± 0.008	1.945	0.057
CA1	0.602 ± 0.051	0.651 ± 0.071	3.136	0.003	0.624 ± 0.064	0.669 ± 0.072	2.566	0.013
CA2/3	0.199 ± 0.021	0.214 ± 0.024	2.536	0.014	0.220 ± 0.023	0.234 ± 0.028	2.083	0.041
CA4	0.257 ± 0.019	0.279 ± 0.026	3.831	0.000	0.269 ± 0.018	0.292 ± 0.028	3.782	0.000
GC-DG	0.297 ± 0.021	0.324 ± 0.030	4.105	0.000	0.310 ± 0.021	0.339 ± 0.033	4.066	0.000
Molecular_layer	0.558 ± 0.038	0.608 ± 0.058	3.997	0.000	0.576 ± 0.044	0.621 ± 0.059	3.358	0.001
Fimbria	0.082 ± 0.015	0.092 ± 0.022	2.051	0.045	0.081 ± 0.013	0.089 ± 0.014	2.414	0.019
HATA	0.053 ± 0.008	0.057 ± 0.009	2.138	0.037	0.055 ± 0.007	0.060 ± 0.008	2.418	0.019
HIP_fissure	0.146 ± 0.024	0.148 ± 0.022	0.331	0.742	0.154 ± 0.025	0.158 ± 0.024	0.72	0.474
Whole_HIP	3.358 ± 0.212	3.645 ± 0.326	4.106	0.000	3.482 ± 0.241	3.729 ± 0.330	3.354	0.001

Note: HIP: hippocampus; CA: Cornu Ammonis; GC-DG: granule cell layer of dentate gyrus; HATA: hippocampus-amygdala-transition-area; MOH: medication-overuse headache; NC: normal control.

^aWelch test because of variance nonhomogeneity.

Figure 2.

The hippocampal subfields and whole hippocampus volume in MOH and NC. MOH: Medication-overuse headache; NC: normal controls; CA: Cornu Ammonis; GC-DG: granule cell layer of dentate gyrus; HATA: hippocampus-amygdala-transition-area; HIP: hippocampus.

Correlation analysis between hippocampal subfields volume and the clinical variables

Table 3 shows that left HIP tail showed a negative correlation with VAS score (r = −0.361, P = 0.046), and right subiculum and presubiculum had a negative correlation with HDPM (r = −0.384 and P = 0.033, r = −0.363 and P = 0.045, respectively). Besides these, right CA4 identified a positive correlation with disease duration (r = 0.375, P = 0.038) (Figure 3).

Table 3.

Correlation analysis between the volume of hippocampal subfields and the clinical variables about headache information for MOH patients.a

		DD		VAS		HDPM		MIDAS		DP
		r	P value	r	P value	r	P value	r	P value	r	P value
HIP_tail	Left	0.083	0.657	−0.361	0.046	1.139	0.456	−0.214	0.256	−0.175	0.364
HIP_tail	Right	0.187	0.313	−0.242	0.189	0.160	0.389	−0.220	0.243	0.023	0.907
Subiculum	Left	0.025	0.894	0.062	0.739	−0.198	0.287	−0.077	0.686	−0.046	0.814
Subiculum	Right	0.213	0.250	0.034	0.855	−0.384	0.033	−0.036	0.852	−0.174	0.367
Presubiculum	Left	−0.039	0.836	−0.018	0.924	0.356	0.050	−0.118	0.534	−0.280	0.141
Presubiculum	Right	0.082	0.659	0.106	0.569	−0.363	0.045	−0.087	0.647	−0.233	0.223
Parasubiculum	Left	−0.092	0.623	0.136	0.464	−0.312	0.088	−0.052	0.786	−0.297	0.118
Parasubiculum	Right	−0.185	0.320	0.328	0.071	0.093	0.617	0.206	0.276	−0.113	0.558
CA1	Left	0.053	0.776	0.085	0.647	0.032	0.864	−0.158	0.403	−0.006	0.975
CA1	Right	0.063	0.736	0.059	0.754	−0.153	0.410	−0.310	−0.096	−0.162	0.402
CA2/3	Left	0.178	0.339	0.047	0.803	0.135	0.469	−0.162	0.393	0.115	0.552
CA2/3	Right	0.267	0.146	0.140	0.452	0.061	0.746	−0.198	0.294	0.075	0.698
CA4	Left	0.077	0.682	0.111	0.551	−0.051	0.784	−0.100	0.599	0.113	0.559
CA4	Right	0.375	0.038	0.115	0.537	−0.043	0.818	−0.090	0.635	0.100	0.697
GC-DG	Left	0.031	0.868	0.112	0.547	−0.111	0.553	−0.119	0.531	0.005	0.981
GC-DG	Right	0.345	0.057	0.094	0.614	−0.128	0.491	−0.097	0.608	−0.006	0.975
Molecular_layer	Left	0.066	0.724	0.070	0.709	−0.048	0.797	−0.143	0.452	−0.022	0.911
Molecular_layer	Right	0.212	0.253	0.037	0.845	−0.204	0.271	−0.206	0.274	−0.127	0.511
Fimbria	Left	−0.055	0.769	0.020	0.913	0.212	0.252	−0.035	0.855	0.043	0.823
Fimbria	Right	−0.033	0.861	−0.077	0.680	−0.054	0.774	0.107	0.573	−0.123	0.525
HATA	Left	0.009	0.963	0.041	0.827	−0.025	0.894	−0.208	0.271	0.061	0.755
HATA	Right	−0.085	0.649	0.091	0.626	−0.195	0.294	−0.320	0.085	−0.022	0.911
HIP_fissure	Left	0.140	0.452	0.086	0.646	0.011	0.952	0.056	0.770	0.051	0.794
HIP_fissure	Right	0.151	0.419	0.116	0.533	−0.255	0.166	−0.214	0.256	−0.177	0.357
Whole_HIP	Left	0.069	0.712	−0.036	0.847	−0.033	0.858	−0.203	0.282	−0.087	0.653
Whole_HIP	Right	0.225	0.224	0.011	0.952	−0.148	0.425	−0.229	0.224	−0.100	0.607

Note: DD: disease duration; VAS: visual analogue scale; HDPM: headache days per month; HIP: hippocampus; CA: Cornu Ammonis; GC-DG: granule cell layer of dentate gyrus; HATA: hippocampus-amygdala-transition-area; MIDAS: Migraine Disability Assessment; DP: the number of drug pills taken per day.

^aThe significance was set as P value > 0.05 with r > 0.3.

Figure 3.

The scatter plot between the clinical variables about headache information and hippocampal subfields. HIP: hippocampus; CA: Cornu Ammonis; DD: disease duration; VAS: Visual Analogue Scale; HDPM: headache days per month.

The negative correlation with HAMA score was confirmed in the right subiculum, CA4, GC-DG, bilateral CA1, molecular layer, and whole HIP (Table 4 and Figure 4). The other neuropsychological tests showed no significant correlation (HAMD and MoCA) with hippocampal subfields (P > 0.05).

Table 4.

Correlation analysis between the volume of hippocampal subfields and the clinical variables about psychological evaluation for MOH patients.a

		HAMA		HAMD		MoCA
		r	P value	r	P value	r	P value
HIP_tail	Left	−0.222	0.083	−0.178	0.170	0.214	0.095
HIP_tail	Right	−0.063	0.627	0.067	0.607	−0.089	0.492
Subiculum	Left	−0.239	0.061	−0.170	0.191	0.164	0.203
Subiculum	Right	−0.334	0.008	−0.220	0.089	0.209	0.102
Presubiculum	Left	−0.150	0.245	−0.058	0.657	0.030	0.819
Presubiculum	Right	−0.249	0.051	−0.114	0.383	0.148	0.251
Parasubiculum	Left	−0.125	0.332	−0.139	0.287	0.143	0.267
Parasubiculum	Right	−0.050	0.698	−0.021	0.874	0.077	0.551
CA1	Left	−0.350	0.005	−0.268	0.037	0.199	0.120
CA1	Right	−0.39	0.003	−0.253	0.049	0.207	0.107
CA2/3	Left	−0.235	0.067	−0.206	0.110	0.235	0.066
CA2/3	Right	−0.207	0.106	−0.189	0.144	0.161	0.211
CA4	Left	−0.231	0.071	−0.182	0.160	0.185	0.150
CA4	Right	−0.325	0.010	−0.267	0.038	0.205	0.110
GC-DG	Left	−0.258	0.043	−0.217	0.093	0.179	0.163
GC-DG	Right	−0.352	0.005	−0.299	0.019	0.232	0.070
Molecular_layer	Left	−0.319	0.011	−0.249	0.053	0.212	0.098
Molecular_layer	Right	−0.358	0.004	−0.248	0.054	0.188	0.143
Fimbria	Left	−0.116	0.368	−0.121	0.352	0.213	0.097
Fimbria	Right	−0.141	0.273	−0.202	0.119	0.206	0.108
HATA	Left	−0.196	0.127	−0.169	0.192	0.064	0.621
HATA	Right	−0.227	0.076	−0.135	0.298	0.146	0.258
HIP_fissure	Left	−0.034	0.793	0.182	0.161	−0.160	0.214
HIP_fissure	Right	−0.298	0.018	−0.115	0.379	0.126	0.329
Whole_HIP	Left	−0.318	0.012	−0.245	0.057	0.229	0.073
Whole_HIP	Right	−0.336	0.008	−0.216	0.094	0.180	0.161

Note: HIP: hippocampus; CA: Cornu Ammonis; GC-DG: granule cell layer of dentate gyrus; HATA: hippocampus-amygdala-transition-area; HAMA: Hamilton Anxiety Scale; HAMD: Hamilton Depression Scale; MoCA: Montreal Cognitive Assessment.

^aThe significance was set as P value > 0.05 with r > 0.3.

Figure 4.

The scatter plot between the psychological scale scores and the hippocampal subfields. a, R_Subiculum vs HAMA; b, L_CA1 vs HAMA; c, R_CA1 vs HAMA; d, R_CA4 vs HAMA; e, R_GC-DG vs HAMA; f, L_Molecular_layer vs HAMA; g, R_Molecular_layer vs HAMA; h, L_Whole_HIP vs HAMA; i, R_Whole_HIP vs HAMA CA: Cornu Ammonis; GC-DG: granule cell layer of dentate gyrus; HIP: hippocampus; HAMA: Hamilton Anxiety Scale.

Linear regression analysis for the hippocampal subfields with significant correlation with the clinical variables

The left HIP_tail presented a negative linear relationship with VAS scores and the linear regression equation was Volume_{left_HIP_tail} = −0.015 × VAS + 0.648 (P_VAS = 0.049) (Table 5). Right presubiculum showed a negative linear relationship with HDPM (Volume_{right_presubiculum} = −0.002 × HDPM + 0.357, P_HDPM = 0.024). The other clinical variables were excluded from these two equations (P > 0.05).

A significant negative linear relationship with HAMA score was identified in the bilateral CA1 and right GC_DG, molecular layer, and whole HIP. The linear regression equations were Volume_{L_CA1} = −0.002 × HAMA + 0.651 (P_HAMA = 0.011), Volume_{R_CA1} = −0.003 × HAMA + 0.674 (P_HAMA = 0.016), Volume_{R_GC_DG} = −0.001 × HAMA + 0.331 (P_HAMA = 0.020), Volume_{R_Molecular_layer} = −0.002 × HAMA + 0.610 (P_HAMA = 0.025), and Volume_{R_Whole_HIP} = −0.02 × HAMA + 3.656 (P_HAMA = 0.010). Only HAMA scores entered these five linear equations, and the other clinical variable including DD, VAS, HDPM, MIDAS, DP, HAMD, and MoCA did not show any contribution for these equations (P > 0.05).

The right subiculum showed a negative linear equation with HDPM and HAMA with linear equation Volume_{R_Subiculum} = −0.003 × HDPM−0.002 × HAMA + 0.540 (P_HDPM = 0.013, P_HAMA = 0.015). The right CA4, left molecular layer, and whole HIP did not presented a linear regression equation (P > 0.05).

Table 5.

Linear regression analysis for the hippocampal subfields with significant correlation with the clinical variables.

Hippocampal subfields	Regression equation	P value*
L_HIP_tail	Volume = −0.015 × VAS + 0.648	P_VAS = 0.049
R_Subiculum	Volume = −0.003 × HDPM−0.002 × HAMA + 0.540	P_HDPM = 0.013,P _HAMA = 0.015
R_Presubiculum	Volume = −0.002 × HDPM + 0.357	P_HDPM = 0.024
L_CA1	Volume = −0.002 × HAMA + 0.651	P_HAMA = 0.011
R_CA1	Volume = −0.003 × HAMA + 0.674	P_HAMA = 0.016
R_CA4	Volume = −0.001 × HAMA + 0.001DD + 0.271	P_HAMA = 0.069,P _DD = 0.071
R_GC_DG	Volume = −0.001 × HAMA + 0.331	P_HAMA = 0.020
L_Molecular layer	Volume = −0.001 × HAMA + 0.583	P_HAMA = 0.08
R_Molecular layer	Volume = −0.002 × HAMA + 0.610	P_HAMA = 0.025
L_Whole_HIP	Volume = −0.008 × HAMA + 3.506	P_HAMA = 0.069
R_Whole_HIP	Volume = −0.02 × HAMA + 3.656	P_HAMA = 0.010

Note: HAMA: Hamilton Anxiety Scale; HDPM: headache days per month; VAS: Visual Analogue Scale; HIP: hippocampus; CA: Cornu Ammonis; GC-DG: granule cell layer of dentate gyrus; HATA: hippocampus-amygdala-transition-area.

*The P value for all the constants was 0.000.

Discussion

In this study, the total HIP and multiple hippocampal subfields detected a decreased volume in MOH compared with NC, which suggested that the lower HIP volume may be associated with MOH itself or the concomitant mood changes. Further correlation analysis demonstrated that some parts of HIP (left HIP_tail, right subiculum, and presubiculum) presented a negative correlation with headache variables, right CA4 showed a positive correlation with headache variables, and multiple HIP subfields (right subiculum, bilateral CA1, molecular layer and whole HIP, right CA4, and GC-DG) presented a negative relation with anxiety scores. The correlation analysis indicated that anxiety may be the main reason of the lower HIP volume.

In the previous studies, the brain morphometric changes were mainly located in the PAG^9,22 and left prefrontal cortex,²³ and the HIP and HIP subfield volume changes were not reported up to now. However, a one-year follow-up evaluation study detected the hippocampal volume reduction in episodic migraine.²⁴ The current study first confirmed the HIP subfield volume decreased in MOH patients, which may present the key value of HIP in understanding the neuromechanism of MOH. A previous study⁸ demonstrated that the decreased functional connectivity was detected between the right HIP and the left precuneus in MOH patients, which was positively related with the number of pills per month. Therefore, the lower HIP subfields volume may be associated with default mode networks, which would be sensitive to the cognitive states,²⁵ and altered in the pain population, such as chronic pain^26,27 and diabetic neuropathic pain.²⁸

The correlation analysis indicated that the headache variables and mood variables participated in the decreased HIP subfields volume. The previous study⁸ identified that the right HIP volume was negatively correlated with the migraine duration; however, only the right CA4 region showed positive correlation with migraine duration in MOH patients in the current study. HIP was a complex and heterogeneous structure, and different subfield present different organization and interconnections between the subfields.²⁹ Regional gray matter volume changes reflected the local extracellular changes in water or the concentration of proteins in neurons and glia.²⁴ The volume alteration of CA4 regions with migraine duration prolongation may be associated with gliosis.³⁰ The left HIP_tail, right subiculum, and presubiculum also presented negative correlation with VAS and HDPM, which might be associated with repetitive and frequent exposure to medication.⁸

Table 4 shows that multiple HIP subfields was negatively related with HAMA scores, which suggested that anxiety might be an important comorbid psychiatric disorder. The presence of the psychiatric disorder was a risk factor for the transformation of migraine into a chronic form,³¹ and anxiety was commonly seen in migraine patients and their relatives.³² The previous study indicated that MDD had an increased prevalence in migraine patients,³³ and multiple HIP subfield presented decreased volume in MDD.^3,6 However, only HAMA scores showed a negative relation with the lower HIP and HIP subfield volume in MOH in the current study. The potential mechanism for the comorbidity between migraine and anxiety may be associated with reciprocal causation relationship or co-occurrence.¹⁴

Therefore, this was a “the chicken or the egg?” question, i.e., the anxiety was generated from MOH itself or the anxiety would lead to the MOH genesis. The further linear regression analysis demonstrated that bilateral CA1, right GC-DG, molecular layer, and right whole HIP had significant linear relationship with HAMA (P < 0.05), and the headache variables, depression, and cognitive variables were excluded from the linear equations (P > 0.05). The linear relationship existence identified that the anxiety was the main reason of the multiple lower HIP volume changes, which indicated that anxiety might play an important role in the development of migraine.¹⁴ Besides these, left HIP_tail and right presubiculum presented the significant linear relation with headache variables (VAS and HDPM), which suggested that MOH could lead to these HIP regions volume decrease and indicated that MOH might be featured on the development of anxiety, i.e., the pain episode might facilitate the development of anticipatory anxiety.¹⁴ The common HIP subfield with decreased volume was the right subiculum resulted from the headache itself and anxiety, which indicated that co-occurrence of MOH and anxiety might share the same etiological factors and determinants.¹⁴

Limitations of this study include the following: First, this study was a cross-sectional study, and the longitudinal observation should be performed to validate the main effect on the HIP for the concurrent anxiety in MOH patients; Second, the anti-anxiety therapy should be investigated to observe the HIP volume changes with the improvement of the anxiety condition, which would be helpful to understand the neuromechanism of lower HIP subfield volume in MOH concurrent with anxiety. Last, the anxiety and depressed patients without migraine should be compared with MOH patients with anxiety in the future study.

In conclusion, the lower HIP and HIP subfields volume were observed in MOH patients and negatively related with anxiety condition. The potential mechanism for the comorbidity MOH and anxiety might be interpreted as the reciprocal causation relationship and co-occurrence relationship.

Footnotes

Authors' contributions

LM and SY contributed to the conception and design; ZC, ML, and XC contributed to the acquisition of data; ZC contributed to the analysis and interpretation of data and drafting the article; and LM and SY revised it for intellectual content. All authors read and approved the final manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Special Financial Grant from the China Postdoctoral Science Foundation (2014T70960) and the Foundation for Medical and Health Sci & Tech Innovation Project of Sanya (2016YW37).

References

Squire

LR.

Memory for relations in the short term and the long term after medial temporal lobe damage. Hippocampus 2017; 27: 608–612.

de Flores

La Joie

and Chetelat

Structural imaging of hippocampal subfields in healthy aging and Alzheimer's disease. Neuroscience 2015; 309: 29–50.

Cao

Passos

Mwangi

Amaral-Silva H, Tannous J, Wu MJ, Zunta-Soares GB, Soares JC. Hippocampal subfield volumes in mood disorders. Mol Psychiatry 2017; 22: 1352–1358.

Jorge

Acion

Starkstein

Magnotta V. Hippocampal volume and mood disorders after traumatic brain injury. Biol Psychiatry 2007; 62: 332–338.

Ota

Sato

Hidese

Teraishi T, Maikusa N, Matsuda H, Hattori K, Kunugi H. Structural differences in hippocampal subfields among schizophrenia patients, major depressive disorder patients, and healthy subjects. Psychiatry Res 2017; 259: 54–59.

Han

Won

Sim

Tae WS. Hippocampal subfield analysis in medication-naive female patients with major depressive disorder. J Affect Disord 2016; 194: 21–29.

Tepper

SJ.

Medication overuse headache. Headache 2014; 54: 1821–1825.

Chanraud

Di Scala

Dilharreguy

Schoenen J, Allard M, Radat F. Brain functional connectivity and morphology changes in medication-overuse headache: clue for dependence-related processes? Cephalalgia 2014; 34: 605–615.

Chen

Liu

Liu S, Ma L, Yu S. Volume gain of periaqueductal gray in medication-overuse headache. J Headache Pain 2017; 18: 12.

10.

Riederer

Marti

Luechinger

Lanzenberger R, von Meyenburg J, Gantenbein AR, Pirrotta R, Gaul C, Kollias S, Sandor PS. Grey matter changes associated with medication-overuse headache: correlations with disease related disability and anxiety. World J Biol Psychiatry 2012; 13: 517–525.

11.

Schmidt-Wilcke

Leinisch

Straube

Kampfe N, Draganski B, Diener HC, Bogdahn U, May A. Gray matter decrease in patients with chronic tension type headache. Neurology 2005; 65: 1483–1486.

12.

Radat

Sakh

Lutz

Amrani ME, Maurice Ferreri MD, Marie-Germaine Bousser MD. Psychiatric comorbidity is related to headache induced by chronic substance use in migraineurs. Headache 1999; 39: 477–480.

13.

Cupini

Costa

Mancini M, Eusebi P, Sarchielli P, Calabresi P. Obsessive-compulsive disorder and migraine with medication-overuse headache. Headache 2009; 49: 1005–1013.

14.

Antonaci

Nappi

Galli

Manzoni GC, Calabresi P, Costa A. Migraine and psychiatric comorbidity: a review of clinical findings. J Headache Pain 2011; 12: 115–125.

15.

Iglesias

Augustinack

Nguyen

Player CM, Player A, Wright M, Roy N, Frosch MP, Mckee AC, Wald LL. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: application to adaptive segmentation of in vivo MRI. Neuroimage 2015; 115: 117–137.

16.

Headache Classification Committee of the International Headache Society. The International Classification of Headache Disorders, 3rd edition (beta version). Cephalalgia 2013; 33: 629–808.

17.

Maier

Buller

Philipp

Heuser I. The Hamilton Anxiety Scale: reliability, validity and sensitivity to change in anxiety and depressive disorders. J Affect Disord 1988; 14: 61–68.

18.

Hamilton

Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol 1967; 6: 278–296.

19.

Wisse

Biessels

and Geerlings

MI.

A critical appraisal of the hippocampal subfield segmentation package in freesurfer. Front Aging Neurosci 2014; 6: 261.

20.

Van Leemput

Bakkour

Benner

Wiggins G, Wald LL, Augustinack J, Dickerson BC, Golland P, Fischl B. Automated segmentation of hippocampal subfields from ultra-high resolution in vivo MRI. Hippocampus 2009; 19: 549–557.

21.

Chen

Sun

Yang

Lou X, Wang YL, Wang Y, Ma L. Cortical thinning in type 2 diabetes mellitus and the recovering effect of insulin therapy. J Clin Neurosci 2015; 22: 275–279.

22.

Riederer

Gantenbein

Marti

Luechinger R, Kollias S, Sandor PS. Decrease of gray matter volume in the midbrain is associated with treatment response in medication-overuse headache: possible influence of orbitofrontal cortex. J Neurosci 2013; 33: 15343–15349.

23.

Riederer

Schaer

Gantenbein

Luechinger R, Michels L, Kaya M, Kollias S, Sandor PS. Cortical alterations in medication-overuse headache. Headache 2017; 57: 255–265.

24.

Liu

Lan

Yan X, Nan J, Xiong S, Yin Q, von Deneen KM, Gong Q, Liang F, Qin W, Tian J. Migraine-related gray matter and white matter changes at a 1-year follow-up evaluation. J Pain 2013; 14: 1703–1708.

25.

Simpson

Jr Snyder

Gusnard

Raichle ME. Emotion-induced changes in human medial prefrontal cortex: I. During cognitive task performance. Proc Natl Acad Sci U S A 2001; 98: 683–687.

26.

Farmer

Baliki

and Apkarian

AV.

A dynamic network perspective of chronic pain. Neurosci Lett 2012; 520: 197–203.

27.

Baliki

Geha

Apkarian

Chialvo DR. Beyond feeling: chronic pain hurts the brain, disrupting the default-mode network dynamics. J Neurosci 2008; 28: 1398–1403.

28.

Cauda

Sacco

Duca

Cocito D, D'Agata F, Geminiani GC, Canavero S. Altered resting state in diabetic neuropathic pain. PLoS One 2009; 4: e4542.

29.

Foo

Mak

Chander

Ng A, Au WL, Sitoh YY, Tan LC, Kandiah N. Associations of hippocampal subfields in the progression of cognitive decline related to Parkinson's disease. Neuroimage Clin 2017; 14: 37–42.

30.

Peixoto-Santos

Velasco

Assirati

Carlotti CG, Scandiuzzi RC, Salmon CEG, Santos AC, Leite JP. 055 — (PEI0174) Astrogliosis is associated with increased in vivo and ex vivo MRI T2 relaxation times in the hippocampus of patients with TLE. Epilepsy Behav 2014; 38: 205–206.

31.

Lipton

RB.

Tracing transformation: chronic migraine classification, progression, and epidemiology. Neurology 2009; 72: S3–S7.

32.

Merikangas

and Angst

Headache syndromes and psychiatric disorders: association and familial transmission. J Psychiatr Res 1993; 27: 197–210.

33.

Radat

and Swendsen

Psychiatric comorbidity in migraine: a review. Cephalalgia 2005; 25: 165–178.

Lower hippocampal subfields volume in relation to anxiety in medication-overuse headache

Abstract

Background

Results

Conclusions

Keywords

Introduction

Materials and methods

Subjects

MRI acquisition

MR image processing

Statistical analysis

Results

The clinical characteristics of MOH and NCs

Comparison of hippocampal subfields volume between MOH and NC

Correlation analysis between hippocampal subfields volume and the clinical variables

Linear regression analysis for the hippocampal subfields with significant correlation with the clinical variables

Discussion

Footnotes

Authors' contributions

Declaration of conflicting interests

Funding

References