Opioid addiction remains a pervasive and challenging public health issue, characterized by high levels of abuse and associated mortality (1). Opioid-related deaths continue to increase at unprecedented rates in many regions of the world (2). Various treatment options have been explored and implemented worldwide, with opioid substitution therapy having emerged as a cornerstone in managing heroin addiction (3). Methadone is the most widely used medication in China (4) for reducing illicit drug use, minimizing withdrawal symptoms, and promoting long-term recovery. It plays a crucial role in harm reduction and treatment (5). However, numerous challenges in methadone maintenance treatment (MMT) still affect patient quality of life and long-term treatment outcomes (6, 7).

Sleep disturbances, such as insomnia, hypersomnia, and fragmented sleep patterns, are commonly reported among individuals with opioid dependence (8–11), further exacerbating the challenges of withdrawal and recovery. It is also a common problem self-reported by MMT patients (10, 11) and can impact patients' compliance (12) and long-term effectiveness. Moreover, recent studies have highlighted the complex relationship between addiction, withdrawal symptoms, and sleep disturbance. Sleep disturbance not only exacerbates the challenges of withdrawal but also contributes to a cycle of vulnerability (13), as poor sleep quality is linked to an increased risk of relapse (14). The psychological issues and changes in brain function resulting from prolonged sleep disturbance may increase the likelihood of relapse and negative outcomes (15). Addressing sleep disturbance not only improves patients' quality of life adherence to therapy and promotes long-term recovery but also disrupts the detrimental cycle of sleep disturbance and addiction.

A recent study has begun to report on the impact of regional cerebral blood flow (CBF) in neuropsychiatric disorders (16). Acute effects of opioid receptor agonists increase CBF (17), whereas long-term heroin dependence results in a significant decrease in regional CBF (18), which can be used as an imaging marker to distinguish drug users (19). Patients with sleep disturbance or sleep deprivation show significant changes in CBF (20–22), demonstrating the complexity of CBF's role. The paracentral lobule, a brain region implicated in motor control and cognitive functions (23), plays a crucial role in shaping the neural landscape of addiction (24) and sleep disturbance (25). However, some studies have reported conflicting results, indicating the need for further research (26–28). The relationship between CBF in the paracentral lobule and sleep disturbance in MMT patients is poorly understood (29).

In this context, we explored the relationship between regional CBF and sleep disturbance in MMT patients. Our analysis revealed an independent association between paracentral lobular CBF and subjective sleep quality in MMT patients. This study provides insights into the mechanisms of substance use disorder (SUD) and sleep disturbances. Understanding the neurobiological mechanism of sleep disturbances in MMT patients can inform the development of strategies to address the multifaceted challenges posed by SUD and advance evidence-based interventions for its management.

The CBF of the right paracentral lobule positively correlated with the total PSQI (β = 0.11355, p = 0.032341). This remained an independent factor (β = 0.12764, p = 0.040545) for the total PSQI after correcting for confounding factors such as gender, age, BMI, history of hypertension, history of hyperlipidemia, history of diabetes, and MMT withdrawal status (Figure 2D, Table 2). We further analyzed the associations between CBF of the right paracentral lobule and PSQI sleep component domains using the multinomial logistic regression model. No significant association was found (Supplementary Table S1). We also found no significant associations between other regional CBF and total PSQI scores before or after correction for the confounding factors.

The present study discusses the issue of sleep disturbance in patients receiving MMT, which is a prevalent problem in such patients (30). Sleep disorders in MMT patients are associated with poor quality of life, increased impulsivity, and higher relapse rates (31), highlighting the need for greater attention to this issue. These sleep disorders are not merely subjective experiences; objective evidence also exists, including respiratory disorders during sleep (32) and daily sleep EEG abnormalities (33). The present study explored the relationship between regional CBF and poor subjective sleep quality, as assessed using the PSQI, in MMT patients, particularly focusing on the paracentral lobule, caudate nucleus, and cerebelum_3.

This study showed that regional CBF in the identified ROIs was significantly higher in MMT patients with poor subjective sleep quality. Further subgroup analyses showed that increased rCBF was particularly notable in patients who had withdrawn from MMT. Additionally, the regional CBF of the right paracentral lobule was independently associated with PSQI scores, as determined using the generalized linear regression model.

This result suggests that methadone administration activates brain regions rich in opioid receptors, modulating their functional connectivity and leading to increased cerebral perfusion and disrupted sleep patterns. This finding aligns with previous studies indicating that the paracentral lobule is closely related to sleep disturbances (27, 34–37). However, some studies have reported opposite results, showing reduced regional CBF in areas such as the cerebellum, vermis, right hippocampus, and left parahippocampal gyrus, as well as a negative relationship with insomnia severity (28).

Differences across studies could also be due to the different study populations. For example, Xu et al. (28) studied patients with chronic insomnia disorder and comorbid major depressive disorder. The percentage of rapid eye movement (REM%) sleep duration was correlated with improvements in depressive symptoms through the regulation of CBF in the bilateral paracentral lobule (25). This result also deepens the understanding that perfusion contributes to the brain network and is related to sleep disturbances (38).

The study employed LASSO regression to identify brain regions associated with sleep quality, a widely accepted method for minimizing potential collinearity and isolating key variables. The contralateral brain regions of the selected ROI were also included. Finally, the study confirmed an independent correlation between the rCBF of the paracentral lobular and PSQI scores. Additionally, increased rCBF in the right paracentral lobule was identified in patients with Internet addiction (39), highlighting the significance of the paracentral lobules in addiction.

Both MMT and long-term sleep disturbance lead to significant changes in brain function and structural network, potentially causing abnormalities in cerebral perfusion and poor sleep quality. These findings suggest that the paracentral lobules play a crucial role in addiction and related behaviors. Further research in this area could provide novel insights into the mechanisms underlying addiction and potentially enhance treatment strategies for patients with sleep disturbances.

Several limitations may be considered. First, the available sleep-related data are limited to the PSQI, lacking objective sleep quality evaluation tools such as polysomnography or the Athens Insomnia Scale. Although some studies have reported consistency between subjective sleep quality and objective evidence in MMT patients (32), the lack of objective evidence remains a limitation. Nevertheless, the PSQI is a widely used questionnaire in MMT patients (40, 41). Second, the percentage of subjects (97.33%) with smoking status raises the possibility of residual confounding.

Similarly, although we used multivariate regression, we cannot exclude the potential confounding effect of other variables due to the data characters. Third, the enrolled subjects were 35–65 years old, with a mean age of 51.8 ± 5.7 years. Although age was adjusted for as a covariate in the analysis, the representativeness of the conclusions still needs to be interpreted with caution. Fourth, the control group without a history of MMT was not included in our study, which limits our ability to determine whether our results are specific to patients with a history of MMT or are more generally related to poor subjective sleep quality. A subsequent study observed a correlation between CBF in the bilateral paracentral lobule and REM% in patients diagnosed with major depressive disorder (MDD) (25).

Interestingly, no significant correlation was found between brain blood flow in this region and sleep patterns in healthy individuals aged between 30 and 53 years. Despite variations in age groups and medical conditions, similar correlations were identified. Furthermore, recent research has indicated that functional connectivity in this specific brain region is linked to PSQI scores in individuals with sleep disorders (34). Consequently, it is hypothesized that changes in CBF in the paracentral lobule may be attributed to sleep disorders, although further investigation is required to confirm this.

Furthermore, the inclusion of emotional factors, such as depression, in the analysis should be considered another limitation. Finally, reverse causation cannot be excluded due to the cross-sectional design. It has been reported that long-term sleep disturbance and sleep deprivation could lead to changes in the structural and functional networks of the paracentral lobule, possibly leading to perfusion alterations, which is an important topic that deserves further exploration.

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding authors.

The studies involving humans were approved by the Ethical Committee from the Clinical Research Ethics Committee, First Affiliated Hospital of Kunming Medical University (2021-l-2). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

JS: Writing – review & editing, Writing – original draft, Validation, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. YL: Investigation, Formal analysis, Data curation, Writing – review & editing, Writing – original draft, Methodology. DK: Resources, Conceptualization, Writing – original draft, Formal analysis, Data curation. WL: Software, Methodology, Writing – original draft, Resources, Formal analysis. JD: Validation, Investigation, Writing – original draft, Resources. GW: Conceptualization, Writing – original draft, Resources, Investigation. XM: Supervision, Project administration, Writing – original draft, Resources, Investigation. CL: Writing – review & editing, Funding acquisition, Conceptualization, Writing – original draft, Supervision, Resources, Project administration. KW: Methodology, Investigation, Writing – review & editing, Writing – original draft, Funding acquisition, Conceptualization. MZ: Supervision, Software, Project administration, Data curation, Writing – review & editing, Writing – original draft, Funding acquisition. YX: Writing – review & editing.