Increased Thalamocortical Functional Connectivity on Discontinuation of Treatment in Painful Diabetic Peripheral Neuropathy

Painful diabetic peripheral neuropathy (DPN) is a common and disabling chronic complication of diabetes mellitus (1). It affects up to one-third of people with diabetes and often leads to severe and intractable pain that results in sleep impairment, mood disorders, and a poorer quality of life (2–4). Unfortunately, the currently recommended pharmacotherapeutic agents for painful DPN provide inadequate pain relief (5,6). The recent Optimal Pathway for Treating Neuropathic Pain in Diabetes Mellitus (OPTION-DM) trial demonstrated that even with combination treatment, only half of people with painful DPN achieved 50% pain relief (5). A greater understanding of the pathophysiology of painful DPN, including the cerebral mechanisms, is likely to provide key targets for therapeutic interventions (7). Furthermore, this approach may identify objective biomarkers of painful DPN that might be used as outcome measures in clinical pain trials (8).

Resting-state functional MRI (rs-fMRI) is a neuroimaging technique for investigating brain function at rest (9). It measures changes in blood oxygen level–dependent (BOLD) signals to examine neuronal activity in different regions of the brain. Using this technique, it is possible to determine regions of the brain that are functionally connected. Functional connectivity analysis involves correlating the spontaneous fluctuations in resting-state activity between remote areas of the brain. This technique has largely been used in research, but there is a huge potential for clinical application in painful DPN (10). We previously demonstrated alterations in functional connectivity in different clinical phenotypes of painful DPN, whereby individuals with the irritable nociceptor phenotype had greater thalamic-insular and reduced thalamus-primary somatosensory cortical connectivity compared with the nonirritable nociceptor phenotype (11). Additionally, self-reported neuropathic pain severity correlated with thalamic-insular cortical functional connectivity (11). We also have shown that rs-fMRI could predict the treatment response in painful DPN (12). Moreover, brain activity and functional connectivity in regions of the brain associated with pain perception have been shown to reduce with analgesic therapy in a heterogeneous group of patients with chronic pain (13,14). However, the impact of treatment on the functional connectivity of key brain regions involved in somatosensory processing of painful DPN has not been investigated to our knowledge.

We therefore performed a neuroimaging study in a subgroup of patients participating in the OPTION-DM trial in which patients were optimized to current first-line neuropathic pain agents, either as monotherapy or combination treatment, over 16 weeks (5). There is consensus, including from the ADA, that these include duloxetine, pregabalin, amitriptyline, and gabapentin. Participants underwent two rs-fMRI scans, the first while receiving optimized treatment and the second after treatment discontinuation. We hypothesized that there will be an increase in functional connectivity between key pain processing brain regions (e.g., thalamic-insular cortex [IC]) on withdrawal of treatment.

This neuroimaging substudy was part of the OPTION-DM clinical trial. The OPTION-DM trial examined three 16-week treatment pathways: oral amitriptyline supplemented with pregabalin, pregabalin supplemented with amitriptyline, and duloxetine supplemented with pregabalin (5,15). After a screening visit, participants’ existing analgesic medications were washed out over 1–2 weeks, after which baseline pain severity, according to an 11-point numeric rating scale (NRS; 0 being no pain and 10 being the worst pain imaginable). Participants were randomly allocated to the three treatment pathways, with each treatment pathway lasting 16 weeks. Each pathway had two treatment phases, each with a 2-week titration period. In the first treatment phase, participants received monotherapy for 6 weeks. Responders (defined as an NRS score <3 at week 6) continued monotherapy for an additional 10 weeks. Nonresponders (defined as an NRS score ≥3 at week 6) started the second drug in the treatment pathway. Participants enrolled in this observational study underwent an rs-fMRI scan at the final participant visit in a treatment pathway at week 16, when their pain was optimally treated (scan 1). Treatment pathway medications were then discontinued, a 1-week washout period was implemented, and participants underwent a second rs-fMRI at the end of this period (scan 2).

Sixteen consecutive right-handed individuals with painful DPN who were approaching the end of a treatment pathway in OPTION-DM were recruited at Sheffield Teaching Hospital NHS Trust (5,15). Eligible participants were aged 18 years or older and fulfilled the diagnostic criteria for diabetes according to the World Health Organization (16), had distal symmetrical polyneuropathy confirmed (17) by the modified Toronto Clinical Neuropathy Score (mTCNS; score ≥5) (18), and had daily neuropathic pain confirmed by the Douleur Neuropathique 4 questionnaire (DN4; score ≥4) (19) for at least 3 months. All participants provided written informed consent.

The full OPTION-DM trial protocol is available elsewhere (5,15), but key inclusion criteria were average daily pain intensity of at least 4 over 7 days on the NRS while off pain medication, aspartate aminotransferase and alanine aminotransferase concentrations lower than twice the upper limit of normal, an estimated glomerular filtration rate of 30 mL/min/1.73 m² or higher, and stable glucose control over the preceding 3 months with glycated hemoglobin concentrations of 12% (108 mmol/mol) or lower (5,15).

Exclusion criteria included the following: a history of epilepsy, depression requiring antidepressant medications, pregnancy and breastfeeding, postural hypotension (systolic blood pressure drop >20 mm Hg on standing for 3 min), cardiac arrhythmias and conduction abnormalities on 12-lead electrocardiogram, prostatic hypertrophy, other painful peripheral neuropathies, the concomitant presence of other painful medical conditions that were as severe as their painful DPN, major amputations of the lower limbs, active diabetic foot ulcers, and substantial suicide risk (5,15).

Additional exclusion criteria for this neuroimaging study included left-handedness, neurological disorders that may confound radiological assessments and contraindications for MRI (e.g., claustrophobia or irremovable ferromagnetic object on the participant).

At screening for the OPTION-DM trial, participants underwent a detailed structured medical history, physical and neurological examinations, and biochemical tests (e.g., urinary albumin-creatine ratio, HbA_1c, and creatinine). The mTCNS and DN4 were done to confirm the presence of DPN and neuropathic pain, respectively. Participants also completed the following questionnaires: Neuropathic Pain Symptom Inventory for subgroup analysis relating to pain phenotype (20); Hospital Anxiety and Depression score to assess for the presence of anxiety and depression (21); Insomnia Severity Index (22); and EuroQoL-5D-5L to measure health related quality of life (23).

We assessed pain severity using the NRS at three times for this neuroimaging study: 1) at OPTION-DM study baseline after analgesic medications had been withdrawn; 2) at the end of the week-16 pathway, at scan 1; and 3) after treatment pathway medications had been withdrawn and washed out for 1 week, at scan 2. The onset, severity, and duration of adverse events were recorded in patient diaries as a part of the OPTION-DM trial, and these were assessed at scans 1 and 2.

Brain imaging data were acquired using a 3.0 Tesla scanner (Ingenia; Phillips Medical Systems, Best, Holland). Anatomic data were acquired using a T1-weighted magnetization-prepared rapid acquisition gradient echo sequence with the following parameters: repetition time of 7.2 ms, echo time of 3.2 ms, flip angle of 8°, and voxel size of 0.9 mm³. The rs-fMRI sequence was obtained after participants were asked to remain as still as possible in the scanner and while they were fixated on a cross to avoid brain wandering. The scan was a T2*-weighted pulse sequence with the following parameters: repetition time, 2600 ms; echo time, 3.5 ms; in-plane pixel dimensions, 1.8 mm × 1.8 mm; and contiguous transaxial slices, 4 mm orientated in the oblique axial plane. We acquired 150 volumes with a total scan time of 6.5 min.

Image preprocessing and functional connectivity rs-fMRI analysis were performed with the Neuroimaging Tools & Resource Collaboratory Functional Connectivity (CONN) Toolbox and SPM12 (24) (Wellcome Centre for Human Neuroimaging, London, U.K.) in MATLAB 2021a (MathWorks, Natick, MA). The component based noise correction method within CONN was used for spatial and temporal preprocessing to define and remove confounds in BOLD signal to prevent the impact of physiological noise and motion in the data (24,25).

To mitigate artifacts arising from motion we used artifact detection tools and principal component filtering of signal from tissues that may not be of interest, such as white matter and cerebrospinal fluid, a method known component correction (25) provided within the CONN toolbox software package.

Fisher transformation was used to convert correlation coefficients to normally distributed scores to enable second-level general linear model analysis (26). The correlation maps were dependent on the specific location of the seed so that functionally and anatomically heterogenous regions of interest (ROIs) were dissociated to delineate functional boundaries across the cortex. Twenty-one ROIs involved in somatic and nonsomatic pain processing were chosen for analyses (27): the anterior and posterior cingulate gyrus; and the left and right of the following ROIs: the thalamus, caudate, putamen, amygdala, accumbens, primary somatosensory cortex (S1), primary motor cortex, insular and frontal orbital cortex; and the default mode network.

These regions are predefined based on atlases provided by the CONN toolbox software, which is a combination of the Harvard Oxford Atlas and the Automated Anatomical Labeling atlas (24). These ROIs were used as the seeds of interest for subject-specific ROI-to-ROI connectivity analyses. Functional connectivity measures were computed between seed areas for ROI-to-ROI analysis and to create ROI-to-ROI connectivity. The CONN toolbox used a linear measure of functional connectivity between bivariate correlation and bivariate regression coefficients, with their associated multivariate measures of semipartial-correlation and multivariate-regression coefficients to calculate functional connectivity. After each subject had ROI-to-ROI connectivity matrices, the ROI-level analyses were evaluated through F or Wilks λ statistics depending on the dimensionality of the within- and between-subjects contrasts. Connectivity contrast effect size among all ROI sources was calculated alongside t and F values, uncorrected P values, and false discovery rate (FDR)–corrected P values for each specified second-level analysis. The F test was used to calculate the multivariate connectivity strength for each threshold. The significance of ROI-to-ROI connection was determined through false-positive control FDR-corrected P values with a χ² test with two-sided inferences. Thus, using aforementioned statistical methods, the ROI-to-ROI analyses results are considered appropriately corrected for multiple comparisons across all brain and analysis voxels. We tested the interaction between scan 1, when participants were receiving optimal treatment, and scan 2, when participants had been withdrawn and washed out. Significant ROI-to-ROI connections were determined by P < 0.05 following false-positive control (FDR).

Continuous data are presented as mean (±SD) and categorical data as number (percentage). Paired t tests were used to compare clinical variables and rs-fMRI functional connectivity obtained during scans 1 and 2. In addition, z values of the difference in functional connectivity from scan 1 to scan 2 (scan 2 – scan 1 = Δ functional connectivity) were correlated to other variables using Pearson correlation. After the initial analysis, participants were stratified into subgroups based on baseline NRS pain scores to investigate the relationship of functional connectivity alterations between scans and pain severity. The baseline mean NRS pain score was 7.9 (±1.9); therefore, we stratified patients into two groups: 1) higher-than-average baseline pain (baseline NRS pain score ≥7.9); and 2) lower-than-average baseline pain (baseline NRS pain score <7.9). Independent t tests were performed to compare continuous clinical and neuroimaging parameters between these groups, and the χ² test was conducted for categorical data. Data were analyzed using SPSS, version 28.0 (IBM).

The data sets generated during and/or analyzed during this study are available from the corresponding author upon reasonable request.

A total of 16 participants were recruited and underwent the first MRI scan; however, one patient did not attend the second MRI scan and was therefore excluded from the analysis. The clinical characteristics of the participants at baseline are presented in Table 1.

There was a significant increase in NRS pain scores from scan 1 to scan 2 from a mean (± SD) of 4.0 ± 2.1 to 6.1 ± 2.4 (P = 0.044, paired t test). No participants were experiencing adverse events, and there were no changes in adverse events (i.e., analgesia withdrawal symptoms) between scans 1 and 2 that might act as a confounding factor for the neuroimaging results. Comparing the functional connectivity in scan 1 with that in scan 2 (i.e., scan 2 > scan 1), there was a significantly greater functional connectivity between the left thalamus and S1 (r β [correlation coefficient beta value] = −0.27; seed-level correction −3.57; for FDR, P = 0.041; Fig. 1A and B) and the left thalamus and IC (r β = −0.18; seed-level correction, −3.43; for FDR, P = 0.041; Fig. 1A and C). Significant results from scan 1 > scan 2 were the same as for scan 2 > scan 1 except the correlation was positive. For the rest of the article, we present the scan 2 > scan 1 results. No other significant (P < 0.05) FDR correlations between ROIs were demonstrated.

Correlation analysis was performed between Δ thalamic-S1 and thalamic-IC functional connectivity and pain variables (Supplementary Tables 1 and 2). There were significant correlations between Δ thalamic-S1 functional connectivity and baseline measures of neuropathic pain, including baseline NRS score (Pearson correlation r = 0.585; P = 0.022; Fig. 2), total NPSI (r = 0.597; P = 0.019), and the total burning NPSI subscore (r = 0.578; P = 0.024). There was also a trend toward a correlation between Δ thalamic-S1 functional connectivity and the duration of painful DPN (r = 0.489; P = 0.064) and the scan 2 NRS − scan 1 NRS (r = 0.475; P = 0.074). However, there were no correlations between Δ thalamic-IC functional connectivity and clinical variables collected at baseline. There was no relationship in rs-fMRI variables and depression or anxiety.

For the higher-than-average baseline pain subgroup, mean baseline pain NRS score ± SD was 9.0 ± 0.9); for the lower-than-average baseline pain subgroup, mean baseline pain NRS score ± SD was 5.8 ± 0.8 (for independent t test, P < 0.001). There were no significant differences in clinical or demographic variables between the two groups other than pain scores (Table 2). The NRS at scan 1 was statistically similar between the two groups (mean NRS ± SD for higher- vs. lower-than-average baseline pain at scan 1: 3.9 ± 2.1 vs. 4.2 ± 2.4, respectively; P = 0.302) but was significantly higher in the higher-than-average baseline pain group at scan 2 after discontinuation of pain medications (mean NRS ± SD for higher- vs. lower-than-average baseline pain at scan 2: 7.0 ± 1.8 vs. 4.4 ± 2.7, respectively; P = 0.006).

The Δ thalamic-S1 functional connectivity was significantly greater in the higher- compared with the lower-than-average baseline pain group (P = 0.017; Fig. 3). There was no significant group difference in the Δ S1-IC functional connectivity (P = 0.422).

In this study, we investigated whether resting state functional connectivity is altered after discontinuation of neuropathic pain treatment in the OPTION-DM trial. We found there was an increase in functional connectivity between the thalamus and S1 cortex and the thalamus and IC. The change in thalamic-S1 functional connectivity between scans also correlated with measures of baseline pain. When the participants were subgrouped on the basis of their baseline pain being greater than or lower than average, we found that participants with higher-than-average baseline pain had a greater change in thalamic-S1 functional connectivity between the two scans.

The thalamus, IC, and S1 cortex are key brain regions involved in the processing of pain and are activated during acute pain (28). The thalamocortical pathway is primarily involved in the sensory or discriminate aspect of pain detection and coding of pain intensity (29), with elevated thalamic-S1 functional connectivity found in chronic pain (30,31). We have previously shown thalamic hyperperfusion (32) and higher sensory cortical energy metabolism in painful DPN (33). In addition, we have demonstrated that thalamic-IC and thalamic-S1 cortical functional connectivity differentiated between “irritable” and “nonirritable” nociceptor (34) phenotypes in painful DPN (11) and that the IC to corticolimbic connectivity predicted response to intravenous lidocaine treatment in patients with painful DPN (12). Therefore, the findings of this study provide further evidence for the increased engagement of the thalamo-cortical pathway in painful DPN. In this study, we did not find any increased connectivity in the default mode network or other regions of the brain involved in pain perception (e.g., anterior cingulate cortex, amygdala). This could be due to the magnetic resonance modality of short scanning of rs-fMRI rather than a response to an external noxious stimulus that activates these regions.

The relationship between the thalamo-cortical functional connectivity and baseline pain severity is consistent with findings from studies of other chronic pain conditions (31). The group difference in thalamo-cortical connectivity may reflect the greater change in pain between the higher-than-average baseline pain and lower-than-average baseline pain groups, consistent with the trend toward a correlation between the change in thalamo-cortical connectivity and NRS score between the two scans. An alternative explanation could be that people with higher baseline pain have greater engagement through the thalamo-cortical pathway, with greater responsiveness to withdrawal of pain therapies.

The current treatments available for painful DPN provide less-than-optimal pain relief, with only around 50% achieving 50% pain relief with maximal combination treatment (5). Indeed, there has been little progress in the discovery of new treatments for this distressing complication of diabetes over the past decade (6), with current first-line medications unchanged over the past 20 years. Although there has been significant progress in our understanding of the pain mechanisms, including the role of peripheral and central sensitization in the initiation and maintenance of neuropathic pain, the relative contributions of peripheral and central mechanisms remain unknown (35). The lack of objective biomarkers of neuropathic pain has also hampered progress in the development of more objective end points for clinical trials (8). Current pain trials rely on self-reported pain outcomes, which are influenced by contextual factors, mood, and cognition (36). Thus, there has been considerable interest in the development of objective biomarkers as clinical end points in pain trials, including neuroimaging markers (8). In this context, these results indicate that rs-fMRI measures may have a potential as objective biomarkers for pain in clinical pain trials.

To our knowledge, only one other study has investigated neuroimaging parameters in patients with painful DPN receiving treatment or not (37). The researchers demonstrated reduced anterior cingulate cortex blood flow after 3 months of duloxetine treatment. However, that study used intravenous ¹²³I–N-isopropyl-p-iodoamphetamine single-photon emission computed tomography, which is unlikely to have widespread clinical application, because of its invasive nature and radiation. In contrast, rs-fMRI, is noninvasive, has a short scanning time (6 min), does not use ionizing radiation, and the data can be analyzed using validated techniques and may be amenable to analysis with artificial intelligence (38,39). Few studies have explored the impact of treatment upon functional connectivity using rs-fMRI, and our study is the first in painful DPN. Therapeutic interventions have demonstrated changes in functional connectivity measures in some small studies in fibromyalgia (40,41) and osteoarthritis (42). However, none of these studies demonstrated alterations in functional connectivity networks identified in our present study. The reasons for this are likely the heterogeneity in brain activation in different clinical pain conditions, small study numbers, discrepancies in investigative techniques, and different treatment modalities. Future studies with larger sample sizes and that assess the impact of neuropathic pain treatments prospectively may identify alterations in functional connectivity between other ROIs (e.g., default mode network); however, the connectivity between the thalamus and somatosensory cortex and IC appear to be the most important for coding of pain severity in painful DPN.

There are several strengths and limitations to this proof-of-concept study. A key strength is that this is the first rs-fMRI study—a relatively easy, short-duration, and noninvasive MR modality with a huge potential for clinical application—to examine alterations in functional connectivity in patients with painful DPN receiving analgesic treatment or not. The study took advantage of being conducted alongside a well-designed clinical trial in which patients were optimized to neuropathic pain treatment using a standardized protocol of dose titration over 16 weeks (5,15). Although patients were following different neuropathic pain regimens, our hypothesis was that there would be an increase in functional connectivity independent of the specific neuropathic pain treatment in this proof-of-concept study. The limitation of the study includes the lack of a control group and the small sample size. A larger sample size might have allowed study of a broader range of pain phenotypes (e.g., greater range of pain intensity, irritable, nonirritable nociceptor phenotype, duration of pain).

In conclusion, we found increased functional connectivity of the thalamus to the S1 cortex and thalamus to the IC associated with an increase in pain severity after discontinuation of analgesic agents for painful DPN. Thus, rs-fMRI measures of functional connectivity in regions of the brain associated with nociception demonstrate the potential to act as a biomarker for neuropathic pain in diabetes. Studies will need to be performed in a larger cohort, with participants randomized to receive placebo or one neuropathic pain agent before and after treatment.

Acknowledgments. The authors acknowledge the hard work, skills, and contributions of the radiographers at the University of Sheffield Magnetic Resonance Imaging Department and the OPTION-DM trial team at Sheffield Teaching Hospitals. The authors also greatly appreciate the participants who took part in this study and who spent a considerable amount of time and effort as a part of the OPTION-DM trial.

Dr. Iain D. Wilkinson, who substantially contributed to this research, died on 22 October 2020 before publication of this work. Dr. Wilkinson will be fondly remembered and sadly missed.

Funding. The Sheffield Teaching Hospitals Diabetes Charitable Trust funded this study. OPTION-DM was funded by the NIHR Health Technology Assessment Programme.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. G.S. recruited participants; undertook clinical and neurophysiological assessments; researched, analyzed, and interpreted clinical data; and wrote the manuscript. K.T. analyzed the magnetic resonance data. S.C., I.W., and D.S. made substantial contributions to the study design; acquisition, analysis, and interpretation of data; and drafting of the article and gave final approval of the version published. S.T. made substantial contributions to conception and designs, reviewed and revised the manuscript, and gave final approval of the version published. S.T. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Prior Presentation. This work was presented at the 82nd American Diabetes Association Scientific Sessions, New Orleans, LA, 3–7 June 2022; the 58th European Association for the Study of Diabetes (EASD) Annual Meeting, Stockholm, Sweden, 22 September 2022); and the hybrid Diabetes UK Professional Conference, London, U.K., and Ahmedabad, Gujarat, India, 29 March to 1 April 2022.