Sex-specific alterations in brain network topology in methamphetamine use disorder: A graph theory-based fMRI study

As a potent central nervous system stimulant, chronic methamphetamine use can lead to methamphetamine use disorder (MUD), which significantly impairs individuals' neurocognitive function (Jayanthi et al., 2021). A large number of neuroscience researchers have used functional magnetic resonance imaging (fMRI) technology to study the neural dysfunction of MUD. A previous study has suggested that patients with MUD have abnormal functional connections between the dorsal default mode network (DMN) and other brain regions (Dong et al., 2021). Another study found that compared with healthy controls (HCs), patients with MUD had lower functional connectivity scores within the cerebellar network, higher functional connectivity scores within the posterior salience network, and functional connectivity scores within the right anterior cingulate cortex, which were associated with emotional symptoms such as anxiety and depression (Jiang et al., 2021). Studies have also confirmed that, after acute administration, methamphetamine increases functional connectivity between the nucleus accumbens and medial frontal regions, and between the fusiform nucleus and left inferior frontal gyrus, and decreases functional connectivity between the nucleus accumbens and inferior pre-cingulate cortex in HCs (Weafer et al., 2020). However, accumulated studies revealed that brain regions and neural circuits associated with MUD pathology have not yet established a clear pathological neural mechanism, as many brain regions and neural circuits are involved.

Emerging graph-theoretical frameworks suggest that the pathological mechanisms underlying MUD may stem from alterations in global neural network organization, rather than dysfunction within isolated brain regions or specific neural circuits (Bullmore and Sporns, 2009). According to graph theory, the brain is a large-scale complex network with tight and complex interactions between brain regions. Graph theory methods can reveal the global and local topological characteristics of brain networks, and the complex functional connection patterns between different brain regions, providing a deeper and more systematic understanding of the functional organization of brain networks (Bassett and Bullmore, 2006). A limited number of studies have employed graph theory to explore the neural mechanisms of MUD. One study found that the nodes of the DMN of participants with MUD showed abnormal topological structure (Cheng et al., 2023). Another small clinical study based on 19 male participants with MUD found that participants with MUD have small-world functional networks, but significantly reduced functional connectivity in brain regions related to learning and memory, auditory/visual perception, cognition, and emotional regulation. This suggests that in addition to brain regions associated with emotional and cognitive functions, brain regions associated with vision and hearing also play an important role in MUD (Liu et al., 2022). In contrast, another study based on 46 male participants with MUD found that the global efficiency, small-worldness, and normalized clustering coefficient of the brain were significantly reduced, while the nodal efficiency of the right amygdala and hippocampus was significantly increased in patients with MUD (Li et al., 2022). Another study also employed graph-theoretical analysis to compare methamphetamine abstainers (after six months of withdrawal) with healthy controls, and found significant alterations in both global and local network metrics (Li et al., 2023). These differences primarily involved the ventral and dorsal attention networks, somatosensory network, visual network, and DMN. These findings suggest that cognitive and perceptual functions, such as visual processing and memory, may remain impaired after prolonged abstinence, potentially increasing the risk of recurrence when exposed to drug-related cues. A recent large-sample clinical study further investigated the functional connectivity metrics of brain networks in 96 male patients with MUD and the neural mechanisms underlying the effects on the core clinical symptom of hyperactivity (Luo et al., 2024). The main findings of the study were that patients with MUD had lower resting-state brain network small-world metrics, weakened functional connectivity in the frontal-parietal network, and that the small-world metrics of patients with MUD mediated the effect of frequency of drug use on hyperactivity. Despite these studies, results from graph theory analyses of patients with MUD remain inconsistent.

Most previous graph-theoretical studies on patients with MUD have included only male participants, limiting the generalizability of their findings. While inconsistencies across these studies have been noted, it remains unclear whether these are attributable to sex differences, as comparative data are lacking. Besides, previous studies have shown that due to differences in hormone levels between males and females, individuals of different sexes have different addiction processes and sensitivities to drugs (Becker and Chartoff, 2019), and a recent paper found that there are sex differences in the relationship between addiction severity and brain functional connectivity in addicted individuals (Cousijn et al., 2025). Some studies have also suggested that males and females differ in their purposes for and responses to methamphetamine use. For example, methamphetamine use among females appears to be more related to emotional issues (Dluzen and Liu, 2008). Given the ongoing controversy surrounding changes in global and local brain network metrics in patients with MUD, and the potential influence of sex as a key moderating variable, the present study addresses this gap by including both male and female participants in a balanced design to investigate sex-specific alterations in brain network topology.