Neuroprotective effect of Val variant of BDNF Val66Met polymorphism on hippocampus is modulated by the severity of menstrual pain

Scientific Knowledge Graph of Dysmenorrhea: A Bibliometric Analysis from 2001 to 2021

Purpose

This study aims to help researchers master the most active hotspots and trends quickly through bibliometric analysis in the field of dysmenorrhea.

Methods

We retrieved literature on Web of Science from 2001 to 2021, and bibliometric analysis software CiteSpace was used in combination with VOSviewer.

Results

We finally acquired 944 papers and an upward trend in articles continued in this field overall. Through the map, China contributed the most, followed by the USA and Turkey. For institutions, Beijing University of Chinese Medicine in China contributed the most, followed by National Yang-Ming University in Taiwan, China. Hsieh JC and Hellman KM were both the most prolific authors with 14 articles. Five major research groups, respectively, with Hsieh JC, Hellman KM, Zhu J, Liang F and Dun W were the key group. Dawood MY was the most dominant author and most frequently cited author. The Cochrane Database of Systematic Reviews Journal was the most productive, and the Fertility and Sterility Journal was the most cited. Advances in pathogenesis and management for primary dysmenorrhea written by Dawood MY was most cited and influential. Pathophysiology, the potential central mechanism, syndrome, evaluation index, diagnosis of adenomyosis-associated dysmenorrhea, treatment, etc., were the main trends and hotspots.

Conclusion

Dysmenorrhea research has received a lot of attention from scholars. Strengthening international cooperation may promote the development of this field. The pathophysiology of dysmenorrhea, its impact on public health and its treatment are current research hotspots and are likely to be the focus of future study.

OPRM1 A118G polymorphism modulating motor pathway for pain adaptability in women with primary dysmenorrhea

Introduction

Primary dysmenorrhea (PDM) is a common condition among women of reproductive age, characterized by menstrual pain in the absence of any organic causes. Previous research has established a link between the A118G polymorphism in the mu-opioid receptor (OPRM1) gene and pain experience in PDM. Specifically, carriers of the G allele have been found to exhibit maladaptive functional connectivity between the descending pain modulatory system and the motor system in young women with PDM. This study aims to explore the potential relationship between the OPRM1 A118G polymorphism and changes in white matter in young women with PDM.

Methods

The study enrolled 43 individuals with PDM, including 13 AA homozygotes and 30 G allele carriers. Diffusion tensor imaging (DTI) scans were performed during both the menstrual and peri-ovulatory phases, and tract-based spatial statistics (TBSS) and probabilistic tractography were used to explore variations in white matter microstructure related to the OPRM1 A118G polymorphism. The short-form McGill Pain Questionnaire (MPQ) was used to access participants' pain experience during the MEN phase.

Results

Two-way ANOVA on TBSS analysis revealed a significant main effect of genotype, with no phase effect or phase-gene interaction detected. Planned contrast analysis showed that during the menstrual phase, G allele carriers had higher fractional anisotropy (FA) and lower radial diffusivity in the corpus callosum and the left corona radiata compared to AA homozygotes. Tractographic analysis indicated the involvement of the left internal capsule, left corticospinal tract, and bilateral medial motor cortex. Additionally, the mean FA of the corpus callosum and the corona radiata was negatively correlated with MPQ scales in AA homozygotes, but this correlation was not observed in G allele carriers. No significant genotype difference was found during the pain-free peri-ovulary phase.

Discussion

OPRM1 A118G polymorphism may influence the connection between structural integrity and dysmenorrheic pain, where the G allele could impede the pain-regulating effects of the A allele. These novel findings shed light on the underlying mechanisms of both adaptive and maladaptive structural neuroplasticity in PDM, depending on the specific OPRM1 polymorphism.

Altered metabolic connectivity between the amygdala and default mode network is related to pain perception in patients with cancer

We investigated the neural correlates for chronic cancer pain conditions by retrospectively analyzing whole brain regions on 18F-fluoro-2-deoxyglucose-positron emission tomography images acquired from 80 patients with head and neck squamous cell carcinoma and esophageal cancer. The patients were divided into three groups according to perceived pain severity and type of analgesic treatment, namely patients not under analgesic treatment because of no or minor pain, patients with good pain control under analgesic treatment, and patients with poor pain control despite analgesic treatment. Uncontrollable cancer pain enhanced the activity of the hippocampus, amygdala, inferior temporal gyrus, and temporal pole. Metabolic connectivity analysis further showed that amygdala co-activation with the hippocampus was reduced in the group with poor pain control and preserved in the groups with no or minor pain and good pain control. The increased although imbalanced activity of the medial temporal regions may represent poor pain control in patients with cancer. The number of patients who used anxiolytics was higher in the group with poor pain control, whereas the usage rates were comparable between the other two groups. Therefore, further studies should investigate the relationship between psychological conditions and pain in patients with cancer and analyze the resultant brain activity.Trial registration: This study was registered at clinicaltrials.gov on 9/3/20 (NCT04537845).

The Use of Neuroimaging for Predicting Sumatriptan Treatment Response in Patients With Migraine

Objectives

To identify the neuroimaging predictors for the responsiveness of patients to sumatriptan and use an independent cohort for external validation.

Methods

Structuralized headache questionnaire and 3-Tesla brain magnetic resonance imaging were performed in migraine patients. Regional brain volumes were automatically calculated using FreeSurfer version 6.0, including bilateral amygdala, anterior cingulated cortex, caudate, putamen, precuneus, orbitofrontal cortex, superior frontal gyri, middle frontal gyri, hippocampus, and parahippocampus. A sumatriptan-responder was defined as headache relief within 2 h after the intake of sumatriptan in at least two out of three treated attacks. We constructed a prediction model for sumatriptan response using the regional brain volume and validated it with an independent cohort of migraine patients.

Results

A total of 105 migraine patients were recruited, including 73 sumatriptan responders (69.5%) and 32 (30.5%) non-responders. We divided the migraine patients into derivation (n = 73) and validation cohorts (n = 32). In the derivation cohort, left hippocampal volume was larger in sumatriptan responders (responders vs. non-responders: 3,929.5 ± 403.1 vs. 3,611.0 ± 389.9 mm³, p = 0.002), and patients with a larger left hippocampal volume had a higher response rate to sumatriptan (>4,036.2 vs. ≤4,036.2 mm³: 92.0 vs. 56.3%, p = 0.001). Based on the findings, we constructed a prediction model using the cutoff value of 4,036.2 mm³, and we found that patients with a left hippocampal volume >4,032.6 mm³ had a higher response rate to sumatriptan than those with a left hippocampal volume ≤4,032.6 mm³ (84.6 vs. 42.1%, odds ratio [OR] = 7.6 [95% confidence interval = 1.3–44.0], p = 0.013) in the validation cohort.

Conclusion

Our study showed that left hippocampal volume is helpful to identify sumatriptan non-responders. This proof-of-concept study shows that left hippocampal volume could be used to predict the treatment response to sumatriptan in migraine patients.

Human Brain Resilience: A Call to Action

At present, resilience refers to a highly heterogeneous concept with ill-defined determinants, mechanisms, and outcomes. This call for action argues for the need to define resilience as a person-centered multidimensional metric, informed by a dynamic lifespan perspective and combining observational and interventional experimental studies to identify specific neural markers and correlated behavioral measures. The coronavirus disease 2019 (COVID-19) pandemic highlights the urgent need of such an effort with the ultimate goal of defining a new vital sign, an individual index of resilience, as a life-long metric with the capacity to predict an individual's risk for disability in the face of a stressor, insult, injury, or disease. ANN NEUROL 2021.