Concordance of cortical morphological anomalies with genetic predisposition to multisite chronic pain in females

Abstract

Background

Multisite chronic pain (MCP) is a debilitating condition disproportionately affecting females, yet its underlying biological basis, particularly the connection to brain structure and the specific role of genetic factors, remains incompletely understood.

Methods

This study delves into the genetic correlation between MCP in females and cerebral cortical morphology, specifically concentrating on cortical thickness (CT) and surface area (SA). Leveraging genome-wide association study (GWAS) data, the investigation establishes significant genetic correlations between female MCP and diverse cerebral cortical regions.

Results

The outcomes underscored that diminished CT in the frontal pole, increased CT in the rostral middle frontal cortex, and reduced SA in the superior frontal cortex exhibited nominal associations with increased susceptibility to MCP in females (P < 0.05). Conversely, MCP susceptibility demonstrated a nominal causal association with reduced CT in the parahippocampal gyrus and postcentral gyrus. Gene enrichment analysis suggests potential correlations between these genetic loci and biological pathways related to body mass index and pain phenotypes.

Conclusions

This study provided exploratory evidence of potential shared genetic pathways influencing both MCP susceptibility and cerebral cortex structure. The results suggested that alterations in brain morphology in females may have a bidirectional relationship with susceptibility to chronic pain.

INTRODUCTION

Multisite chronic pain (MCP) is a common clinical symptom that affects millions of people worldwide, with a significantly higher proportion of patients in females [1]. The disease is characterized by chronic or cyclical pain in at least three body parts lasting more than three months. Compared to patients with local chronic pain, MCP patients are more likely to suffer from complications such as limited mobility, sleep disorders, and emotional problems, leading to more serious negative impacts on their quality of life [2]. Recent scientific studies have revealed that the pathological mechanism of MCP may be related to various systemic factors. The main factors in the central nervous system are neuroepithelial cell remodeling and central pain sensitization caused by chronic inflammatory responses [3]. These processes may lead to abnormal amplification of normal sensory stimuli or mild pain stimuli in perception, causing persistent and unbearable pain experiences. Therefore, further research on MCP is important for improving patient prognosis and reducing the social and medical burden.

MCP has a significant genetic predisposition, highlighting the important role of genetic factors in the pathogenesis of MCP. Some progress has been made in analyzing the genetic risk factors for MCP. Studies based on genetics have found that the heritability for chronic pain in twin groups was 63% [4]. In addition, a longitudinal study involving 7,654 adult individuals and their parents found that when both parents had three or more chronic pain sites, the risk of their children developing additional pain sites was significantly increased [5]. Genome-wide association studies (GWASs) revealed that the heritability of single nucleotide polymorphisms (SNPs) in MCP exceeds 10%, with slightly higher heritability in female patients than in male patients [6]. The latest genomic analysis indicated that there were 113 genes associated with MCP inheritance, which were widely involved in key biological processes such as neurogenesis, synaptic plasticity, and nervous system development [7]. Therefore, MCP demonstrates substantial genetic variation and is intricately associated with genetic diversity within the nervous system.

Neuroimaging techniques have become essential scientific tools for investigating the relationship between disease phenotypes and neurobiology. These techniques allow us to visualize changes in brain structure and function, providing valuable evidence for understanding the central mechanisms of disease. Previous studies have shown that MCP patients had morphological and structural abnormalities in multiple brain regions, including reduced gray matter volume in brain regions such as the insula, anterior and posterior cingulate, thalamus, hippocampus, and basal ganglia [1,8] and reduced cortical surface area (SA) in regions such as the dorsolateral prefrontal cortex, lateral temporal lobe, and parietal lobe. Recent advancements in GWAS have enhanced our comprehension of diseases by associating specific genetic variations with alterations in brain structure and function [9]. This integrated genetic and neuroimaging approach has proven effective in the study of neurodegenerative diseases such as Parkinson’s [10] and Alzheimer’s diseases [11]. However, there is a lack of studies that combine brain imaging data with genetic data to explore the genetic loci in brain regions associated with MCP pathology and the interaction mechanisms between genes, brain structure, and MCP.

Sex disparities constitute a critical element in the epidemiology and pathophysiology of MCP [12]. A series of population-based studies on MCP revealed that females displayed elevated pain prevalence across nearly all anatomical regions, suggesting a broader distribution and increased susceptibility to MCP in this demographic [13]. Biological investigations further elucidate sex-specific mechanisms underlying these disparities. Females generally exhibit lower pain thresholds and reduced pain tolerance, predisposing them to heightened pain intensity and enhanced affective unpleasantness [14]. Genetic analyses have identified sexually dimorphic contributions of pain-associated loci, with emerging evidence indicating that the regulatory effects of genetic variants on nociceptive processing are sex-dependent [15]. Notably, a recent proteomic study identified 1,354 brain proteins displaying sex-differentiated abundance, among which 150 proteins harbored sex-biased protein quantitative trait loci. This finding underscores the profound influence of sex on gene expression regulation at the protein level, thereby revealing distinct neurobiological substrates for pain perception between sexes [16]. Clinically, females report higher levels of pain-associated disability compared to males, a phenomenon that significantly compromises quality of life and imposes disproportionate demands on healthcare resources [17]. These observations underscore the imperative to delineate the female MCP pathogenesis mechanisms.

The primary objective of this research was to investigate the genetic correlation between female patients with MCP and variations in brain structure. Due to the intricate nature of MCP’s pathological mechanism and the notable divergence in pain perception between sexes, this study aimed to integrate genetic and neuroimaging evidence to reveal the neurobiological basis of MCP that is unique to females.

MATERIALS AND METHODS

1. Female MCP GWAS

In the study, the authors used the summary statistical study data from GWAS analysis for the female MCP data [6]. The analysis included 209,093 female participants. Genetic quality control measures were utilized, and for the GWAS analysis, SNPs exhibiting imputation quality scores < 0.3, minor allele frequencies < 0.01, and Hardy–Weinberg equilibrium test P values < 10-6 were omitted. This stringent filtering guaranteed that the genetic variants under investigation possessed adequate statistical power and held significant biological relevance.

2. Cerebral cortex GWAS data

The cerebral cortex GWAS data were obtained from the Enhancing Neuroimaging Genetics Meta-Analysis consortium [18]. It included a range of volume-adjusted covariates, including age, sex, four-dimensional scaling, intracranial volume, and site-specific measurements. The cortical thickness (CT) and SA, as well as the brain magnetic resonance imaging data from 51,665 individuals from 60 different cohorts around the world were used. Approximately 94% of the participants were of European ancestry. These data were combined to define 34 brain regions and provided precise anatomical divisions of the entire cerebral cortex using the Desikan–Killiany cortical atlas [19]. The entire brain had weighted estimates of the phenotype and calculated the average values of CT (in millimeters) and SA (in square millimeters) for the left and right hemispheres. In addition, all data underwent rigorous quality control and standardization to ensure the accuracy and reliability of the analysis results.

3. Genetic correlations

The Linkage Disequilibrium Score Regression (LDSC) method was a powerful method for estimating heritability and genetic correlations using GWAS statistics. This method quantified the contribution of each genetic variant to a trait by examining the relationship between the statistic and the LDSC score, thereby determining whether there was a common genetic basis between different traits [20]. The application of LDSC revealed true polygenicity and distinguished potential confounding biases, such as those caused by population stratification and recessive associations. In this study, the authors used a bivariate LDSC method to evaluate the genetic correlation between female MCP and cerebral cortex structure. Genetic correlation analysis was performed for each “female MCP-cerebral cortex” pair using the LDHub [21] (https://github.com/bulik/LDSC) platform using LDSC. A total of 136 different genetic correlation analyses were performed independently in this study. Bonferroni correction was used and the significance threshold was set to 3.68 × 10−4 (0.05/136). At this correction level, results with a P value less than 0.05 were considered nominally significant and statistically significant evidence for a potential causal effect [22].

4. GWAS-pairwise (GWAS-PW)

We applied the GWAS-PW approach to identify specific segments of the genome that influence female MCP and the brain structural parameters with statistically significant genetic associations [23]. The authors performed GWAS-PW analyses separately for MCP and for each of the brain structural parameters. This approach split the genome into 1703 LD-independent regions. For each region, GWAS-PW estimated the posterior probability of association (PPA) for four different models: (1) the region was uniquely associated with MCP, (2) the region was uniquely associated with the brain structural parameter, (3) the region contributed to the etiology of both phenotypes via the same genetic variant, and (4) the region contributed to the etiology of both phenotypes via different genetic variants. For this analysis, the authors selected genomic segments with a PPA > 0.5 for model three (the region contributes to the etiology of both phenotypes via the same genetic variant) because this threshold has been used in previous studies using the GWAS-PW approach [24].

5. FUMA functional annotation

We used the Functional Mapping and Annotation (FUMA) online platform (v1.5.2) [23] to perform functional annotation of the entire genome. Then, functional information was extracted for specific genomic fragments identified by GWAS-PW. The FUMA platform identified independent significant SNPs and their surrounding genomic loci based on LD structure, and defined lead SNPs and genomic risk loci. Independent significant SNPs, along with SNPs in LD with these independent significant SNPs, were annotated to understand their functional impact on gene function. Gene-based association testing was performed using MAGMA (v1.08) [25]. Significant genes were selected after applying Bonferroni multiple testing correction.

6. Genetically informed causal inference analysis

The study used a two-sample Mendelian randomization (MR) analysis to systematically explore the bidirectional causal relationship between cerebral cortical traits (thickness and SA) and female MCP. The MR analysis used SNPs as instrumental variables (IVs) to address potential confounding factors and reverse causality. The authors used three methods for MR analysis: inverse variance weighting (IVW), MR-Egger, and weighted median methods [26]. They followed strict criteria to ensure the accuracy and reliability of the results: (1) Correlation assumption: The selected IVs must be significantly correlated with the exposure factor (P < 1.0 × 10⁻⁵) [27]. In addition, they used the F statistic to evaluate the strength of each genetic instrument, which measures the extent to which the SNP explained the exposure factors. The F statistic was calculated using the following formula:

$$F=\beta 2/SE2$$

Where β represents the genetic effect size of the exposure and SE represents its standard error. IVs must satisfy F > 10 to indicate a strong correlation with the exposure. (2) Exclusion restriction hypothesis: IVs should affect the outcome only through the exposure factor, not through other pathways [28]. (3) Independence hypothesis: Confounding factors should be independent of the selected IVs. To further exclude potential bias, the authors used PhenoScanner (v2, an expanded tool for searching human genotype-phenotype associations) to identify and exclude bias. We used the Bonferroni correction and set the significance threshold to 3.68 × 10⁻⁴ (0.05/136). At this correction level, results with a P value less than 0.05 were considered nominally significant and statistically significant evidence for a potential causal effect [22].

Further, multiple sensitivity analyses were performed, including Cochran’s Q test to assess heterogeneity, and MR-Egger and MR-PRESSO regression tests were performed to detect and exclude the existence of horizontal pleiotropy. All statistical analyses were performed in the RStudio 4.3.1 (Posit Software), using the TwoSampleMR 0.5.11 (IEU OpenGWAS) and MR-PRESSO packages (developed by Marie Verbanck).

RESULTS

1. Genetic correlations

We performed a detailed analysis of the genetic correlation between female MCP and cerebral cortex thickness and SA using the LDSC method (Table 1, Fig. 1, and Supplementary Table 1). Although the observed associations did not survive Bonferroni correction for multiple comparisons, several outcomes demonstrated nominally significant effects at the conventional threshold (P < 0.05). Our results showed that there was a nominally significant positive correlation between female MCP genetic susceptibility and CT in multiple brain regions, including the rostral middle frontal cortex (rg = 0.161, P = 0.018), caudal middle frontal cortex (rg = 0.158, P = 0.039), superior parietal cortex (rg = 0.142, P = 0.002), and inferior parietal cortex (rg = 0.140, P = 0.039). This finding suggested that greater CT in these regions may be associated with genetic risk factors for female MCP. In terms of negative genetic correlation, we found a nominally significant negative correlation between CT in the transverse temporal cortex (rg = –0.150, P = 0.007) and the genetic susceptibility of female MCP patients.

Table 1.

The genetic correlations between female MCP and cortical thickness and cortical surface

Trait1	Trait2	rg	SE	P value
Cortical thickness
Rostral middle frontal cortex	female MCP	0.161	0.068	0.018
Caudal middle frontal cortex	female MCP	0.158	0.077	0.039
Superior parietal cortex	female MCP	0.142	0.046	0.002
Inferior parietal cortex	female MCP	0.140	0.068	0.039
Transverse temporal cortex	female MCP	–0.150	0.056	0.007
Cortical surface area
Parsorbitalis cortex	female MCP	0.116	0.052	0.024
Superior frontal cortex	female MCP	0.114	0.051	0.025
Parstriangularis cortex	female MCP	0.109	0.055	0.049
Superior parietal cortex	female MCP	0.105	0.047	0.027
Inferior temporal cortex	female MCP	–0.140	0.050	0.005
Post central cortex	female MCP	–0.120	0.051	0.019
Middle temporal cortex	female MCP	–0.119	0.045	0.008

MCP: multifocal chronic pain, SE: standard error.

Fig. 1.

The genetic correlations between female MCP and cortical thickness and cortical surface. MCP: multisite chronic pain, LDSC: Linkage Disequilibrium Score Regression, CT: cortical thickness, SA: surface area.

Moreover, in the genetic correlation analysis of the cerebral cortical SA, there was a nominally significant positive correlation between the cortical SA in multiple brain regions and the genetic susceptibility of female MCP patients, including the parsorbitalis cortex (rg = 0.116, P = 0.024), superior frontal cortex (rg = 0.114, P = 0.025), parstriangularis cortex (rg = 0.108, P = 0.049), and superior parietal cortex (rg = 0.104, P = 0.027), which may indicate that larger cortical SA in these brain regions were associated with the risk of female MCP. On the other hand, the authors observed a nominally significant negative correlation between the cortical SA of inferior temporal cortex (rg = –0.140, P = 0.005) and the genetic susceptibility of female MCP patients, suggesting a lower inferior temporal cortex of the cortex SA may be associated with a genetically greater risk of female MCP. Meanwhile, the post central cortex (rg = –0.120, P = 0.018) and middle temporal cortex (rg = –0.119, P = 0.008) also showed nominally negative genetic correlations with the risk of female MCP.

2. GWAS-PW

Upon further investigation, we explored the association between female MCP and the morphometric measurements of 12 brain structures that exhibit notable genetic correlations using GWAS-PW. We identified 131 genomic segments associated with MCP etiology and at least one of the four brain structural parameters through the same genetic variants (paired results). The number of shared genomic segments varied by brain structure (Supplementary Table 2). The cortical SA of the pars orbitalis cortex shared the largest number of genomic segments with female MCP (8 segments), followed by the CT of the rostral middle frontal cortex (1 segment), caudal middle frontal cortex (1 segment), and transverse temporal cortex (1 segment). These results and sensitivity analysis results are detailed in Fig. 2.

Fig. 2.

Ideogram highlighting shared genomic segments between brain structures and multisite chronic pain.

3. Functional annotation

In this study, the cortical SA of the parsorbitalis, the thickness of the rostral middle frontal cortex, and the thickness of the caudal middle frontal cortex were enriched with 131, 10, and 10 genes, respectively. It is noteworthy that solute carrier family 39 member 8 (SLC39A8) is enriched on chromosome 4 and is closely related to MCP. This gene is shared with MCP between the cortical SA of the parsorbitalis, the thickness of the rostral middle frontal cortex and the thickness of the caudal middle frontal cortex. In addition, fibroblast growth factor 18 (FGF18), extracellular matrix protein 1 (ECM1), mitochondrial ribosomal protein S21 (MRPS21), threonyl-TRNA synthetase 2 (TARS2), myelin protein zero-like protein (MLN), olfactomedin 4 (OLFM4), and nucleophosmin 1 (NPM1) were enriched in the SA of the pars orbitalis cortex and MCP. These results and sensitivity analysis results were detailed in Supplementary Tables 3–5, Supplementary Fig. 1, and Table 2.

Table 2.

Some genes in shared genomic segments are associated with both MCP and the volume of subcortical brain structures

Gene associated with MCP	Brain structures associated with the gene	Biological relevance of the gene
SLC39A8	The cortical surface area of pars orbitalis The cortical thickness of rostral middle frontal The cortical thickness of caudal middle frontal	As a metal ion transporter, it may be involved in maintaining intracellular metal ion balance, which may affect a variety of cellular functions, including pain-related neurotransmission processes
LAMTOR3	The cortical surface area of pars orbitalis The cortical thickness of rostral middle frontal The cortical thickness of caudal middle frontal	As part of the mTOR signaling pathway, it may be involved in regulating cell growth, metabolism, and autophagy, processes that have been implicated in the development of chronic pain, especially in neuropathic pain
DNAJB14	The cortical surface are of pars orbitalis The cortical thickness of rostral middle frontal The cortical thickness of caudal middle frontal	Member of the heat shock protein family that may be involved in the response to cellular stress, including that caused by injury or inflammation, which may affect the transmission of pain signals
FGF18	The cortical surface area of pars orbitalis	FGF18 plays an important role in cell proliferation, differentiation, inflammatory response and cell protection, and may indirectly affect the occurrence and development of chronic pain in multiple sites through these mechanisms.
ECM1	The cortical surface area of pars orbitalis	The role of ECM1 in the extracellular matrix and inflammatory response may indirectly affect the occurrence and development of chronic pain through multiple mechanisms.
MRPS21	The cortical surface area of pars orbitalis	MRPS21 plays an important role in mitochondrial protein synthesis, and its dysfunction may indirectly affect the occurrence and development of chronic pain by affecting mitochondrial function.
TARS2	The cortical surface area of pars orbitalis	TARS2 plays an important role in protein synthesis and cell function. Its dysfunction may indirectly affect the occurrence and development of chronic pain in multiple sites by affecting cell metabolism and mitochondrial function.

MCP: multisite chronic pain, SLC39A8: solute carrier family 39 member 8, FGF18: fibroblast growth factor 18, ECM1: extracellular matrix protein 1, MRPS21: mitochondrial ribosomal protein S21, TARS2: threonyl-TRNA synthetase 2.

4. Bidirectional MR

In this study, MR methods were used to explore the bidirectional causal genetic effects between female MCP and CT and SA (Supplementary Tables 6, 7). Although the results were not corrected by Bonferroni correction, several of the results were nominally significant (P < 0.05). Forward MR analysis showed that the genetically predicted cortical traits had a nominally significant causal effect on female MCP. Specifically, lower cortical SA in the superior frontal cortex (β = –0.099 mm², P_IVW = 0.019) was causally associated with greater risk of female MCP. In addition, lower CT in the frontal pole cortex (β = –0.238 mm, P_IVW = 0.006) and greater CT in the rostral middle frontal cortex (β = 0.567 mm, P_IVW = 0.044) were nominally significantly causally associated with greater risk of female MCP. These results and sensitivity analysis results were detailed in Fig. 3 and Supplementary Fig. 2.

Fig. 3.

The forest map of cerebral cortex- F_MCP with causal bidirectional MR outcomes. F_MCP: female multisite chronic pain, MR: Mendelian randomization, SNP: single nucleotide polymorphism, IVW: inverse variance weighting, CT: cortical thickness, SA: surface area, SFC: superior frontal cortex, FPC: frontal pole cortex, RMF: rostral middle frontal cortex, PHC: parahippocampal cortex, PCC: post central cortex, LCI: lower confidence interval, UCI: upper confidence interval.

Reverse MR analysis revealed the effects of genetically predicted female MCP on cortical traits. Results showed that higher female MCP risk was nominally, significantly, and causally associated with lower CT in the in the parahippocampal cortex (β = –0.029 mm², P_IVW = 0.019) and post central cortex (β = –0.088 mm, P_IVW = 0.048). These results and sensitivity analysis results were detailed in Fig. 3 and Supplementary Fig. 2.

DISCUSSION

In this study, we explored the genetic relationship between female MCP and brain structure. The analyses suggested nominal positive genetic correlations (P < 0.05) between female MCP and the CT of several brain regions, including the rostral middle frontal cortex, caudal middle frontal cortex, superior parietal cortex, inferior parietal cortex, and parstriangularis cortex. Moreover, we also found that MCP showed a nominally positive genetic correlation with the cortical SA of specific brain regions, such as parsorbitalis cortex, superior frontal cortex, and superior parietal cortex. In addition, MCP had a nominally significant negative genetic correlation at the genome-wide level with certain cerebral cortex thicknesses, such as transverse temporal, and the cortical SAs of inferior temporal cortex, post central cortex, and middle temporal cortex. These exploratory findings suggested that genetic effects may contribute to the observed associations between female MCP and brain structure. Further genetic analysis revealed that many genomic regions possibly contribute to the pathophysiology of female MCP and the characteristics of at least one brain structure.

Gene-based testing of shared genomic fragments between female MCP and brain structures found 4 enriched genes in female MCP. These include NPM1 on chromosome 5, which plays a key role in cellular stress response, chromosome stability, cell proliferation, and apoptosis. The experience of chronic pain often stems from persistent nerve and tissue damage, compounded by an inflammatory response. NPM1 possesses the capacity to modulate pain perception through its involvement in regulating cellular stress and apoptosis within these biological processes [29]. The gene SLC39A8 on chromosome 4 is responsible for encoding a zinc transporter pivotal in transporting zinc ions, which are essential for neurotransmission and inflammatory processes. Zinc, in its ionic form (Zn2+), which is highly enriched at many but not all glutamatergic nerve terminals, is released upon neuronal activity, and is crucial to the control of physiological and pathophysiological brain functions [30]. Consequently, the SLC39A8 gene may impact the initiation and progression of chronic pain by modulating the zinc ion equilibrium within the nervous system. FGF18 on chromosome 5 exerts a significant influence on the development of bone and cartilage. It is postulated that FGF18 may be implicated in chronic pain through its impact on tissue repair and regeneration, as enduring tissue damage and reparative processes are pivotal in chronic pain pathology. The presence of FGF18 on chromosome 5 significantly influences the development of bone and cartilage. It is hypothesized that FGF18 may be involved in chronic pain due to its impact on tissue repair and regeneration. Persistent tissue damage and reparative processes are believed to play a crucial role in the pathology of chronic pain [31]. The present research has revealed that chronic pain constitutes a multifaceted disease state involving various cellular and molecular mechanisms. Cell stress response, ion transport, tissue repair, and inflammatory response are pivotal in both the manifestation and perpetuation of chronic pain. A holistic intervention directed at these mechanisms holds promise for effective chronic pain management.

In our analysis, we have further elucidated the common genetic framework linking female MCP and brain structure, identifying four specific genomic regions that are shared between the two. Gene-based testing identified 131 genes in these regions. One of the most common brain regions epidemiologically associated with female MCP is the frontal lobe. Several studies have reported a relationship between chronic pain and the frontal lobe [32]. The prefrontal cortex, located in the frontal lobe, serves a pivotal role in the perception and regulation of pain. This region of the brain plays a critical role in cognitive functions such as decision-making, emotion regulation, and attention, all of which have an impact on an individual’s perception and handling of pain. Individuals experiencing persistent pain may display structural and functional alterations in the prefrontal cortex, potentially resulting in increased pain sensitivity or reduced ability to regulate pain perceptions. Furthermore, the prefrontal cortex interacts with other brain regions and is susceptible to the influence of psychosocial factors such as stress, anxiety, and depression, which can impact its neuroplasticity and thereby affect the long-term processing and perception of pain. The present study revealed the presence of three significant shared genomic regions between MCP and the frontal lobe, housing the mitochondrial-related genes MRPS21 and TARS2. TARS2 is accountable for the synthesis of aspartate tRNA within mitochondria, a crucial process for protein synthesis and mitochondrial function. Dysfunctional mitochondria can lead to lower adenosine triphosphate production and heightened oxidative stress, factors believed to be associated with chronic pain development. MRPS21, a small mitochondrial subunit protein essential for mitochondrial protein synthesis, can also be impacted by impaired mitochondrial function. Disorders in mitochondrial energy metabolism may lead to reduced ATP production, impacting cellular function and potentially triggering or exacerbating chronic pain [33]. Previous studies have shown that macrophages actively control the resolution of inflammatory pain by transferring mitochondria to sensory neurons [34]. Potential mechanisms of mitochondrial-targeted therapy for chronic pain include regulating mitochondrial respiratory function, alleviating oxidative stress, inhibiting NLRP3 inflammasome activation, and promoting mitochondrial transplantation, which have demonstrated efficacy in modulating neuronal excitability and central sensitization in neuropathic pain models. Current research bottlenecks lie in constructing cell-type-specific mitochondrial-targeted delivery systems, necessitating solutions to challenges such as low drug enrichment efficiency in the inner mitochondrial membrane, transmembrane transport barriers, and selective suborganelle distribution [35]. This study further supports the close association between mitochondrial function and chronic pain, offering potential insights for chronic pain treatment.

GWAS-PW results showed that the shared gene set between female MCP and brain structure have multiple enriched gene sets, mainly including genes for body mass index and genes for pain phenotypes, such as LEMD2, MLN, and OLFM4. The co-occurrence of obesity and multi-site chronic pain is a phenomenon that can be anticipated. It is well-documented that obesity is often linked to enduring low-level inflammation. Adipose tissue, especially visceral fat, secretes a large amount of proinflammatory cytokines, including TNF-α, IL-6, and CRP. These inflammatory factors have the potential to induce systemic inflammation, thereby exacerbating chronic pain. Obesity can trigger neuroinflammation, and studies have shown that structural changes in the brain, such as reduced gray matter volume, have also been associated with obesity [36]. The LEMD2 protein plays a critical role in the regulation of various cellular signaling pathways, including the MAP kinase and AKT kinase signaling pathways. These pathways are essential for controlling cellular growth, differentiation, and responses to stress. By regulating of these signaling pathways, LEMD2 may indirectly influence metabolic processes and the maintenance of weight [37]. The motilin hormone aids in the movement of food along the digestive tract, thereby facilitating gastrointestinal motility. This function is crucial for the maintenance of normal digestion and absorption processes and has previously been associated with severe obesity in scientific literature [38]. OLFM4 regulates cell proliferation and apoptosis, impacting metabolic balance, weight, and tissue health [39]. Gene set enrichment analysis showed that identified genes are associated with the regulation of cell proliferation and apoptosis. Dysregulation of these cellular processes may lead to chronic inflammation, which is a significant contributor to chronic pain across multiple sites.

The research has identified nominal causal associations between cortical morphology, including reduced thickness in the frontal pole, increased thickness in the rostral middle frontal cortex, and reduced SA in the superior frontal cortex, and susceptibility to female MCP. These regions of the cortex are essential parts of the prefrontal cortex, which is crucial in the perception and emotional processing of chronic pain. Each cerebral cortex performs distinct functions as part of a broader pain network [40]. The frontal pole cortex, situated in the anterior part of the frontal lobe, is associated with the emotional and cognitive evaluation of pain, affecting the perception and response to painful stimuli [41]. The rostral middle frontal cortex regulates attention and emotional responses to pain due to its close connection with the limbic system [42]. Research has indicated a positive correlation between the CT of the rostral middle frontal cortex and perceived stress and levels of depressive symptoms [43]. Apkarian’s meta-analysis highlighted the association of chronic pain with reduced gray matter volume in the aforementioned three brain regions [44]. These structural changes are believed to result from poor neuroplasticity due to prolonged pain experience, leading to a reduction in gray matter volume. The interactions of the frontal pole cortex, rostral middle frontal cortex, and superior frontal cortex with subcortical regions such as the amygdala and thalamus integrate the sensory and affective aspects of pain [45]. The findings of prior research have posited that the observed structural alterations are attributable to diminished neuroplasticity resulting from prolonged experiences of pain, thereby causing a decline in gray matter volume. Nonetheless, the present investigation has indicated that these structural changes within the identified brain regions may function as a predisposing factor for the development of chronic pain.

Furthermore, MCP can lead to cortical volume reductions in specific brain regions, with potential mechanisms involving abnormal interactions of inflammatory cytokines leading to neurodegeneration, neuronal or glial cell apoptosis, and synaptic loss [46]. The present study demonstrated that MCP was associated with reduced parahippocampal and postcentral gyrus CT, which was consistent with previous reports of gray matter reductions in these regions of MCP [47]. MCP may disrupt the balance of cytokine networks through neuroinflammation mediated by inflammatory factors, while inhibiting nerve cell regeneration, thereby exacerbating structural changes and gray matter atrophy [48]. Notably, multiple studies have reported partial recovery of gray matter volume in pain-related brain regions following pain alleviation, suggesting that these structural alterations may be reversible [49,50]. Therefore, future research should elucidate the mechanisms underlying the reversibility of these cortical changes and explore potential interventions aimed at promoting the restoration of brain plasticity.

To the authors’ knowledge, this is the first study to investigate the genetic relationship between female MCP and brain structure. This study adopted a multiple-methods approach to unveil the underlying genetic mechanism of the genetic correlation between female MCP and brain structure. An essential aspect of this study is the effective utilization of genetic methods, which serve to mitigate potential confounding impacts of environmental factors. Firstly, the LDSC method demonstrated a significant advantage in quantifying shared genetic architecture between structural features of the brain and chronic pain. Secondly, paired GWAS studies were effective in identifying genetic loci that may influence both brain structure and MCP. Additionally, pathway enrichment analysis furthered the biological interpretation of these findings by identifying key molecular pathways and biological processes involved in brain structure and pain perception. Lastly, MR studies improved causal inferences by assessing directional relationships between genetic variants. However, several limitations must be acknowledged. Firstly, the most intriguing findings were nominally significant and did not survive rigorous multiple comparison correction. This implies a heightened risk of false positives and means that the results are suggestive rather than conclusive. Future studies with larger sample sizes are essential to confirm the reliability of these genetic associations and causal inferences. Secondly, although these datasets were broad in coverage, they may contain population-specific biases and fail to fully capture the genetic diversity of the target population. Future research should aim to include more diverse populations to improve the generalizability of the study.

In summary, this study provided preliminary insights into the potential genetic relationship between female MCP and brain structure by employing genetic association analysis, paired GWAS analysis, pathway enrichment, and MR approaches. The comprehensive methodologies suggested the possibility of shared genetic components, raising the hypothesis that structural changes in certain brain regions may be related to chronic pain susceptibility. Future large-scale and replication studies are needed to further clarify their biological significance.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.3344/kjp.25253.