Abstract
Sickle cell disease (SCD) is an inherited hemolytic disorder accompanied by chronic pain and recurrent acute painful episodes known as vaso-occlusive crises (VOCs). Increased Glx (glutamate+glutamine) and lowered GABA concentration have been reported in the insula of patients with fibromyalgia, a nociplastic chronic pain condition, and may affect the pathophysiology of pain-related syndromes. Therefore, proton magnetic resonance spectroscopy (1H-MRS) was conducted to measure levels of Glx and other brain metabolites using a single voxel (size: 2×3×3 cm3) in the right posterior insula cortex (PIC) in 17 individuals with SCD and 17 ethnicity-, age- and sex-matched healthy controls (HCs). The frequency of VOCs in the preceding 12 months was recorded. The concentration of Glx (p=0.019) and the ratio of Glx to tCr (total creatine, p=0.035) in the PIC were significantly higher in patients with SCD as compared to matched HCs (n=17). Secondary analyses with the unpaired full sample of 24 SCD also showed a significantly higher level of Glx/tCr than HCs (n=19), with a positive correlation between the level of Glx/tCr and the number of VOCs (p=0.034, r=0.476), as well as a negative correlation between Glx and sensory sensitivity assessed by tonic pressure pain in gastrocnemius area of the non-dominant leg (p=0.040, r=−0.462). The unpaired full sample additionally revealed a significant difference in sensory sensitivity (p=0.050). Altered metabolites such as GABA and myoinositol were also observed between SCD and HCs. These results suggest that elevated excitatory neurotransmission in the insula might contribute to nociplastic pain in SCD.
Perspective:
Our work highlighted the innovative finding of elevated levels of the excitatory neurotransmitter glutamate with glutamine in patients with SCD compared to healthy controls. The positive relationship between Glx/tCr and the frequency of VOCs suggests that an excitatory brain neurotransmitter imbalance may be involved in VOCs.
Keywords: sickle cell disease, 1H-MRS, vaso-occlusive crisis, pain, glutamate, brain metabolites
1. Introduction
Sickle cell disease (SCD) is an inherited hemolytic disorder complicated by acute nociceptive and chronic nociplastic pain. Acute vaso-occlusive crises (VOCs) associated with SCD are extremely painful episodes that are recurrent, unpredictable, and frequently require hospitalization and opioids for pain control. Clinical pain management in SCD is largely unmet due to undefined objective diagnostic guidelines and limited treatment approaches. Although the precise mechanisms for pain in SCD are emerging, recent data from our group and others suggests that central neurobiological factors may promote pain in these patients.1,2 Altered functional and morphological neuroimaging associated with pain in fibromyalgia (FM),3–6 a nociplastic pain condition, is also seen in our previous functional and morphological studies associated with pain and VOCs in SCD patients.1,7 These data suggest that some individuals with SCD may have mechanistic similarities with FM. In support of this hypothesis, SCD and FM patients share many clinical features, including multisite hyperalgesia, fatigue, sleep problems, and evidence of central sensitization on experimental pain testing.8–12
Proton magnetic resonance spectroscopy (1H-MRS) is a non-invasive technique for measuring in vivo concentrations of neurotransmitter metabolites, including excitatory glutamate (typically reported with glutamine and abbreviated as Glx) and inhibitory GABA. 1H-MRS studies have identified unique changes in GABA and glutamate in different pain conditions. Studies from our team demonstrated elevated levels of insular Glx in FM patients,13 and insular Glx is positively associated with increased experimental pain in patients with FM.14 In addition, FM patients exhibit reduced levels of insular GABA compared to controls.15 Taken together, these findings suggest an excitatory-inhibitory imbalance may contribute to the FM phenotype. Altered brain glutamate and GABA were also observed in other chronic pain conditions. One study from our colleagues observed similar findings of lowered GABA levels at the anterior cingulate cortex (ACC) in patients with pelvic pain,16 whereas another study identified reduced glutamate at the ACC in chronic lower back pain,17 suggesting abnormal changes in excitatory and inhibitory neurotransmitters may contribute to the maintenance of chronic pain. However, no studies to date have examined brain metabolite concentrations and their relations with pain and VOCs in SCD.
Here, we examine the levels of glutamate and other metabolites in the posterior insula cortex (PIC) of SCD patients as compared to age-, sex-, and ethnicity-matched pain-free healthy controls (HCs) using 1H-MRS. We hypothesized that SCD patients, similar to those with FM, would exhibit elevated levels of Glx in the PIC.
2. Materials and Methods
Study design and participants
Initially, 29 participants with SCD and 20 HCs were screened, enrolled, and completed an MRI scan. Six participants (n=5 SCD and n=1 HC) were excluded due to artifacts (n=2 SCD, n=1 HC) or change of medication use within 24 h before the scan (n=3 SCD). 17 participants with SCD as well as 17 pain-free ethnicity-, age- and sex-matched HCs without SCD, were included for primary analysis. Detailed study design and timeline are displayed in Supplementary Figure 1. Secondary analyses including all 24 SCD and 19 HCs with viable data were also performed. Demographic information of all subgroups is shown in Table 1. The main inclusion eligibility criteria for SCD included: 1) experiencing chronic pain in the past 6 months or at least one VOC in the past 12 months, 2) no recent history of initiating or adjusting the dose of stimulant medications, 3) willing to maintain current treatments and not introduce any new medications or treatment modalities for control of pain symptoms during the study. Detailed inclusion and exclusion criteria can be found in Supplementary Table 1. Concomitant medications are listed in Supplementary Table 2.
Table 1.
Demographics
| Matched Sample Analysis | Full Sample Analysis | |||||
|---|---|---|---|---|---|---|
| Subject Characteristics | SCD (n=17) | Healthy Controls (n=17) | P-values | SCD (n=24) | Healthy Controls (n=19) | P-values |
| Age (mean ± SD, years) (range) | 35.3 ± 14.5 (17 – 73) | 33.7 ± 15.8 (17 – 62) | 0.652 | 32.6 ± 14.5 (12 – 73) | 35.3 ± 16.3 (17 – 62) | 0.641 |
| Females, n (%) | 7 (41.2%) | 7 (41.2%) | >0.999 | 13 (54.2%) | 9 (47.4%) | 0.763 |
| Height (cm) (mean ± SD) (range) | 172.1 ± 8.8 (151.1 – 185.2) | 172.2 ± 8.3 (157.1 – 188.0) | 0.805 | 170.3 ± 8.0 (151.1 – 185.2) | 171.6 ± 8.4 (157.1 – 188.0) | 0.694 |
| Weight (kg) (mean ± SD) (range) | 74.6 ± 17.1 (37.6 – 112.6) | 75.8 ± 16.9 (53.1 – 126.9) | >0.999 | 72.5 ± 15.5 (37.6 – 112.6) | 76.9 ± 17.9 (53.1 – 126.9) | 0.549 |
| Silent Cerebral or other infarct, n (%) | 1 (5.9%) | -- | 3 (12.5%) | -- | ||
| SCD Type Diagnosis | ||||||
| SCD genotype (SS/SC/Sβ+ thalassemia), n | 13/2/2 | -- | 16/6/2 | -- | ||
| Hematological Indexes | ||||||
| WBC (k/cumm), mean ± SD | 9.55 ± 4.88 | 5.49 ± 2.18 | 0.004 | 9.10 ± 4.4 | 5.48 ± 2.1 | 0.001 |
| RBC (million/cumm), mean ± SD | 3.12 ± 0.94 | 4.71 ± 0.69 | <0.001 | 3.11 ± 0.9 | 4.70 ± 0.6 | <0.001 |
| Hgb (GM/dL), mean ± SD | 9.69 ± 1.93 | 13.34 ± 1.66 | <0.001 | 9.67 ± 1.8 | 13.32 ± 1.6 | <0.001 |
| Hct (%), mean ± SD | 28.14 ± 5.60 | 40.00 ± 4.77 | <0.001 | 27.95 ± 5.4 | 39.93 ± 4.5 | <0.001 |
| Reticulocyte Count (%), mean ± SD | 6.19 ± 3.68 | 1.26 ± 0.45 | <0.001 | 5.92 ± 4.0 | 1.27 ± 0.4 | <0.001 |
| Hemoglobin A %, mean ± SD | 19.75 ± 10.64 | 97.47± 0.15 | 0.005 | 19.99 ± 9.6 | 85.49 ± 19.2 | 0.001 |
| Hemoglobin S %, mean ± SD | 66.70 ± 15.52 | -- | 65.97 ± 15.7 | -- | ||
| Hemoglobin F %, mean ± SD | 14.82 ± 9.06 | -- | 14.10 ± 10.5 | -- | ||
| Disease-modifying Therapy | ||||||
| Chronic transfusion, n (%) | 2 (11.8%) | -- | 4 (16.7%) | -- | ||
| Hydroxyurea, n (%) | 11 (64.7%) | -- | 15 (62.5%) | -- | ||
| Patient-Reported Outcome Measure | ||||||
| Patient-reported number of VOCs in the preceding 12 months (mean ± SD) (range) | 4.5 ± 3.5 (0 - 13) | -- | 5.0 ± 4.5 (0 – 20) | -- | ||
Subject characteristics (age, sex (assigned at birth), height, and weight) did not significantly differ between SCD and HCs in either sample set. Levels of hematological indexes were significantly different in SCD from HCs. SCD genotype, use of disease-modifying therapies, and number of VOCs in the preceding 12 months among SCD are also reported. Abbreviations: SCD, sickle cell disease; HCs, healthy controls; WBC, white blood cells; RBC, red blood cells; Hgb, hemoglobin; Hct, hematocrit; VOCs, vasoocclusive crises.
Each participant underwent one magnetic resonance imaging (MRI) scan, including 1H-MRS, following the administration of patient-reported outcome measures (PROMs) and a routine laboratory test for complete blood cell count, reticulocytes, and hemoglobin electrophoresis. The study was approved by the Institutional Review Board at Indiana University. Written consent was obtained from each participant before scanning. Participants were not involved in the design and conduct of this research.
Frequency of VOCs prior to 1H-MRS
The frequency of VOCs (including both hospitalization and self-managed VOCs) in the preceding 12 months was recorded for each participant based on the participants’ verbal report and medical record.1,7
Sensory sensitivity assessment prior to 1H-MRS
A tonic pressure pain stimulus, individually calibrated to evoke moderately intense pain (i.e., a rating of approximately 40 on a 0–100 numerical rating scale; P40), was delivered via an MR-compatible pressure cuff (D. E. Hokanson, Inc., Bellevue, WA, USA) to the gastrocnemius muscle of the non-dominant leg for 8 min right before a 1H-MRS scan. Higher pressure intensity (measured as mmHg) required to evoke P40 indicates lower pressure pain sensitivity.
1H-MRS measurement in the posterior insula cortex
1H-MRS spectra were acquired on a Siemens Prisma 3 T scanner using a 64-channel head coil following the tonic pressure pain stimuli from a single voxel (size: 2×3×3 cm3) located within the right (radiological convention) PIC (Figure 1A), as our previous study showed elevated Glx in fibromyalgia patients in this region.13 The 1H-MRS voxel dimensions used were based on our previous study.13 Single-voxel point-resolved spectroscopy (PRESS) (TR/TE = 3000/25 ms, Averages = 128) was used to measure several metabolites, including glutamine + glutamate (Glx), total creatine (tCr), N-acetyl aspartate (NAA), total choline (tCho), and myo-inositol (MI) (Figure 1B). A separate GABA+–edited Mescher-Garwood–PRESS (MEGA-PRESS) (TR/TE = 3000 ms/68 ms, Averages = 256), which co-edits signals from macromolecules and homocarnosine, was conducted to estimate GABA+ levels (Figure 1C).18 LCModel19 was used for PRESS analysis to obtain concentration values of each metabolite. Ratios of each metabolite to total creatine (tCr) were also calculated. MEGA-PRESS spectra were processed in Gannet version 3.1.5,20 a MATLAB-based toolbox specifically developed for edited 1H-MRS, to estimate GABA+. The final GABA+ estimates were expressed in arbitrary institutional units (AIU), which approximates millimolar concentrations of GABA+. GABA+ was also expressed as a ratio with respect to the total creatine (GABA+/tCr). Tissue correction for cerebrospinal fluid was performed for each voxel using the tissue composition estimated from SPM12.21 For all subjects, the Cramer-Rao Lower Bounds for each metabolite analyzed with LCModel was less than 20%.
Figure 1. Measurements of brain metabolites in posterior insula cortex (PIC).
(A) A single voxel (size: 2×3×3 cm3) is placed in the right PIC using PRESS and MEGA-PRESS. (B) An example of a representative PRESS spectra (raw data are plotted as a thin black curve) fitted with LCModel (the thick red curve) for assessment of Glx. (C) MEGA-PRESS is fit with Gannet for assessment of GABA+. The raw data are plotted in the blue curve, and the Gannet model is in red. Abbreviations: GABA, γ-aminobutyric acid; Glx, Glu + Gln; MEGA-PRESS, Mesher-Garwood point-resolved spectroscopy; ppm, parts per million; PRESS, point-resolved spectroscopy.
Statistical analysis
Demographic and clinical variables are summarized by means (standard deviations and ranges) for continuous variables and counts (percentages, %) for categorical variables. The primary analyses focused on comparing continuous variables of 17 pairs of sex- and age-matched SCD and HCs using the Wilcoxon signed-rank test. With N=17 matched SCD and HC pairs, we have an 80% power to detect an effect size 0.7 at type I error level 0.05 using the Wilcoxon signed-rank test.
Wilcoxon rank-sum tests were used to compare continuous variables in a sensitivity analysis of the full sample of 24 SCD participants and 19 HCs. Spearman’s partial coefficients were calculated to quantify the associations between Glx or Glx/tCr and the frequency of VOCs while controlling the effects of age, sex (assigned at birth), SCD genotype, and the use of hydroxyurea as covariables. With 24 SCD and 19 HCs, the detectable effects size is 0.9 at type I error level 0.05 and power level 80% using the Wilcoxon rank-sum test. Within the N=24 SCD participants, we have an 80% power to detect a Spearman correlation of no less than 0.59. A p<0.05 level was set for the statistical significance of all the analyses in the present work.
3. Results
Demographics
The demographic information of all subjects is shown in Table 1. In total, 17 SCD participants, with a mean age of 35.3 years (range, 17–73 years; 7 Females) and 17 ethnicity-, age- and sex-matched HCs without SCD with a mean age of 33.7 (range, 17–62 years; 7 Females) were analyzed. For the full sample analysis, there were 24 SCD participants with a mean age of 32.6 years (range, 12–73 years; 13 Females) and 19 HCs without SCD with a mean age of 35.3 years (range, 17–62 years; 9 Females). There was no significant difference in demographic parameters between SCD participants and HCs in age, sex, height, or weight. SCD participants presented with higher WBC and reticulocyte count, as well as lower RBC, Hgb, Hct, and Hgb A.
Elevated Glx and Glx/tCr levels in SCD patients and their relations with VOC frequency and sensory sensitivity
Matched sample analysis.
The concentration of Glx (p=0.019, Figure 2A) and Glx/tCr (p=0.035, Figure 2B) in PIC was significantly higher in 17 SCD participants as compared to the 17 paired HCs.
Figure 2. Elevated Glx and Glx/tCr in SCD compared to matched HCs at PIC.
The Glx concentration (A) and Glx/tCr ratio (B) are significantly higher in SCD (red dots) compared with 17 HCs (green dots). Wilcoxon rank sum test is performed between SCD and HCs. Significance is set at a p-value of 0.05. Abbreviations: SCD, sickle cell disease; HCs, healthy controls.
Full sample analysis.
In comparison, the significance was observed in the level of Glx/tCr (p=0.007) but not in the concentration of Glx (p=0.094) in the full sample analysis of 24 SCD and 19 HCs (Supplementary Table 3). Subsequent correlation analyses using the full sample of 24 SCD showed that there was a positive correlation between the ratio of Glx/tCr and the number of VOCs (r= 0.476, p=0.034, Supplementary Figure 2A), and a clear trend of positive correlation between Glx concentration and the number of VOCs (r=0.397, p=0.083, Supplementary Figure 2B). In addition, there is a significant increased sensory sensitivity (increased P40 pressure in SCD as compared to control (p=0.050, Supplementary Figure 3A), and the increased sensory sensitivity correlates with the decreased Glx (r=0.462, p=0.040, Supplementary Figure 3B).
Alterations of other metabolites
Matched sample analysis.
As shown in Supplementary Table 3, within the paired 17 SCD and HCs, there is a clear trend of significantly reduced GABA+ in SCD as compared to HCs (p= 0.076). No significance or trend of significance was observed in other metabolites.
Full sample Analysis.
In comparison, the full sample analyses (n=24 SCD and n=19 HCs) identified the markedly reduced metabolite MI concentration in SCD as compared to the HCs (p= 0.040). No significant differences were detected in tCho, tCr, NAA, NAA/tCr, tCho/tCr, though there is a clear trend of significantly reduced GABA+ in SCD as compared to HCs (p= 0.085), as well as a marginal significance of lowered MI/tCr (p= 0.080) in SCD as compared to HCs (Supplementary Table 3).
4. Discussion
To our knowledge, this is the first examination of in vivo neurotransmitter metabolite levels in SCD. Consistent with findings in FM,13 we observed an increase in Glx and Glx/tCr levels in the PIC of patients with SCD as compared to matched pain-free HCs.
The PIC is a brain region known to be involved in the sensory dimension of pain. Our results suggest that elevated Glx in SCD may be related to enhanced pain processing. In support of this hypothesis elevated glutamate and/or Glx following an experimental pain stimulus has also been observed in healthy subjects.22 Elevated Glx in the PIC in response to experimental pain stimuli in patients with FM,13 and a strong positive correlation between Glx/tCr level and pain intensity in Crohn’s disease patients have also been observed.23 These results suggest that the neural mechanisms of SCD patients in pain processing may be closely associated with increased levels of excitatory neurotransmitters such as Glx, which may be a cause or consequence of increased pain sensitivity.
We did not find a significant difference between SCD and HCs in this study for GABA+ concentration though there was a trend of reduction in 24 SCD compared to the 19 HCs (Supplementary Table 3). GABA+ levels have been shown to be decreased in the anterior insula in FM patients15 and in patients with chronic musculoskeletal pain24 and abdominal pain.23 There is also one report25 showing no significant GABA+ differences between patients with musculoskeletal pain conditions and chronic pain syndromes compared with HCs; however, lower GABA+ levels were associated with greater self-reported pain,24 and tonic heat pain stimulation increased GABA+ levels in the prefrontal cortex.26
Although these studies link cerebral GABA+ levels with chronic and acute pain, the directionality of the change of GABA+ is less consistent. Therefore, further study with a larger sample size may clarify the role of the inhibitory neurotransmitter GABA+ in the neural mechanism of pain in SCD patients.
Collectively, our preliminary results provide evidence of a link between elevated excitatory neurotransmission within the insula of patients with SCD and reveal new information for a potential brain marker of SCD, thus opening a new potential avenue for treatment. Interventions such as pregabalin reducing brain Glx3 or acupuncture modulating the somatosensory functional connectivity associated with insular GABA+27 may be effective at reducing pain in SCD.
This study has limitations. Firstly, changes in metabolites in regions outside the PIC were not examined, so our findings cannot be generalized to the whole brain. That said, the PIC was chosen based on our previous studies in fibromyalgia. Secondly, the sample size of this study was small, and the non-significant correlation between Glx and the frequency of VOC was likely not sufficiently powered. Third, we did not adjust for multiple comparisons in the present analysis because this is a small-exploratory/hypothesis-generating study aiming to find novel brain neurochemistry markers instead of confirming pre-defined hypotheses. Future analyses with larger samples are needed to confirm these findings. Finally, our study arises from a single site in the Midwest of the United States, so our SCD sample may not be representative of the global population of patients with this condition.
5. Conclusions
Management of pain in SCD remains very challenging in part due to a lack of understanding of the underlying mechanisms and pathophysiology of pain syndromes in those with SCD. Cerebral excitatory neurotransmitters and their relationship with pain have been largely unexplored in SCD. As far as we know, we are the first to study the levels of brain Glx and GABA+ in patients with SCD. More work is needed to understand the relationship between other clinical outcomes and endogenous brain neurotransmitters as a potential objective outcome measure in SCD.
Supplementary Material
Highlights.
Insular glutamate is elevated in patients with sickle cell disease.
Elevated glutamate correlates with more frequent onset of vasoocclusive crisis.
Elevated glutamate correlates with increased sensory sensitivity.
Sickle patients have altered brain metabolites profile.
Acknowledgments
The authors extend their gratitude to Brandon Alec Reyes, Tyler James Barrett, Nayana Dutt, and Payton Mittman for their assistance in experiment performance, Drs Yu-Chien Wu and Syed Salman Shahid for MRI sequence setup, and all the providers affiliated with Indiana University Health and Indiana Hemophilia & Thrombosis Center for patient referral to this study. The authors also thank the Clinical Research Center and Indiana Institute for Biomedical Imaging Sciences at Indiana University for resource support.
This research received support from the NIH K99/R00 award (Grant # 5R00AT010012) and funding from the Indiana University Health – Indiana University School of Medicine Strategic Research Initiative awarded to Y.W.
Footnotes
Disclosures
S.E.H. has consulted for Aptinyx, Memorial Sloan Kettering Cancer Institute, Dana Farber Cancer Institute, Wayne State University, Indiana University Indianapolis, and University of Glasgow and has received grant funding from NIH, Arbor Medical Innovations, and Aptinyx. R.E.H. has previously consulted for Pfizer and Aptinyx Inc. and has received grant funding from Pfizer, Aptinyx, Cerephex, and the National Institutes of Health (NIH). The remaining authors declare no competing interests.
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Data Availability
All data is available upon reasonable request from author Y.W.
REFERENCES
- 1.Darbari DS, Hampson JP, Ichesco E, et al. Frequency of Hospitalizations for Pain and Association With Altered Brain Network Connectivity in Sickle Cell Disease. J Pain. Nov 2015;16(11):1077–86. doi: 10.1016/j.jpain.2015.07.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Joo P, Kim M, Kish B, et al. Brain network hypersensitivity underlies pain crises in sickle cell disease. Sci Rep. Mar 27 2024;14(1):7315. doi: 10.1038/s41598-024-57473-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Harris RE, Napadow V, Huggins JP, et al. Pregabalin rectifies aberrant brain chemistry, connectivity, and functional response in chronic pain patients. Anesthesiology. Dec 2013;119(6):1453–64. doi: 10.1097/ALN.0000000000000017 [DOI] [PubMed] [Google Scholar]
- 4.Ichesco E, Schmidt-Wilcke T, Bhavsar R, et al. Altered resting state connectivity of the insular cortex in individuals with fibromyalgia. J Pain. Aug 2014;15(8):815–826 e1. doi: 10.1016/j.jpain.2014.04.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Schmidt-Wilcke T, Ichesco E, Hampson JP, et al. Resting state connectivity correlates with drug and placebo response in fibromyalgia patients. Neuroimage Clin. 2014;6:252–61. doi: 10.1016/j.nicl.2014.09.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Schmidt-Wilcke T, Luerding R, Weigand T, et al. Striatal grey matter increase in patients suffering from fibromyalgia--a voxel-based morphometry study. Pain. Nov 2007;132 Suppl 1:S109–S116. doi: 10.1016/j.pain.2007.05.010 [DOI] [PubMed] [Google Scholar]
- 7.Wang Y, Hardy SJ, Ichesco E, Zhang P, Harris RE, Darbari DS. Alteration of grey matter volume is associated with pain and quality of life in children with sickle cell disease. Transl Res. Feb 2022;240:17–25. doi: 10.1016/j.trsl.2021.08.004 [DOI] [PubMed] [Google Scholar]
- 8.Adam SS, Flahiff CM, Kamble S, Telen MJ, Reed SD, De Castro LM. Depression, quality of life, and medical resource utilization in sickle cell disease. Blood Adv. Oct 24 2017;1(23):1983–1992. doi: 10.1182/bloodadvances.2017006940 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ameringer S, Elswick RK Jr., Smith W. Fatigue in adolescents and young adults with sickle cell disease: biological and behavioral correlates and health-related quality of life. J Pediatr Oncol Nurs. Jan-Feb 2014;31(1):6–17. doi: 10.1177/1043454213514632 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Campbell CM, Moscou-Jackson G, Carroll CP, et al. An Evaluation of Central Sensitization in Patients With Sickle Cell Disease. J Pain. May 2016;17(5):617–27. doi: 10.1016/j.jpain.2016.01.475 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Whitfield A KK. Evaluating Causes of Back Pain in Patients with Sickle Cell Disease. Blood. 2015;126 (23):4593 ( 10.1182/blood.V126.23.4593.4593). [DOI] [Google Scholar]
- 12.Schlesinger N. Clues to pathogenesis of fibromyalgia in patients with sickle cell disease. J Rheumatol. Mar 2004;31(3):598–600. [PubMed] [Google Scholar]
- 13.Harris RE, Sundgren PC, Craig AD, et al. Elevated insular glutamate in fibromyalgia is associated with experimental pain. Arthritis Rheum. Oct 2009;60(10):3146–52. doi: 10.1002/art.24849 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Harris RE, Sundgren PC, Pang Y, et al. Dynamic levels of glutamate within the insula are associated with improvements in multiple pain domains in fibromyalgia. Arthritis Rheum. Mar 2008;58(3):903–7. doi: 10.1002/art.23223 [DOI] [PubMed] [Google Scholar]
- 15.Foerster BR, Petrou M, Edden RA, et al. Reduced insular gamma-aminobutyric acid in fibromyalgia. Arthritis Rheum. Feb 2012;64(2):579–83. doi: 10.1002/art.33339 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Harper DE, Ichesco E, Schrepf A, et al. Relationships between brain metabolite levels, functional connectivity, and negative mood in urologic chronic pelvic pain syndrome patients compared to controls: A MAPP research network study. Neuroimage Clin. 2018;17:570–578. doi: 10.1016/j.nicl.2017.11.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Gussew A, Rzanny R, Gullmar D, Scholle HC, Reichenbach JR. 1H-MR spectroscopic detection of metabolic changes in pain processing brain regions in the presence of non-specific chronic low back pain. Neuroimage. Jan 15 2011;54(2):1315–23. doi: 10.1016/j.neuroimage.2010.09.039 [DOI] [PubMed] [Google Scholar]
- 18.Mescher M, Merkle H, Kirsch J, Garwood M, Gruetter R. Simultaneous in vivo spectral editing and water suppression. NMR Biomed. Oct 1998;11(6):266–72. doi: 10.1002/(sici)1099-1492(199810)11:6<266::aid-nbm530>3.0.co;2-j [DOI] [PubMed] [Google Scholar]
- 19.Provencher SW. Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med. Dec 1993;30(6):672–9. doi: 10.1002/mrm.1910300604 [DOI] [PubMed] [Google Scholar]
- 20.Edden RA, Puts NA, Harris AD, Barker PB, Evans CJ. Gannet: A batch-processing tool for the quantitative analysis of gamma-aminobutyric acid-edited MR spectroscopy spectra. J Magn Reson Imaging. Dec 2014;40(6):1445–52. doi: 10.1002/jmri.24478 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Ashburner J, Friston KJ. Unified segmentation. Neuroimage. Jul 1 2005;26(3):839–51. doi: 10.1016/j.neuroimage.2005.02.018 [DOI] [PubMed] [Google Scholar]
- 22.Archibald J, MacMillan EL, Graf C, Kozlowski P, Laule C, Kramer JLK. Metabolite activity in the anterior cingulate cortex during a painful stimulus using functional MRS. Sci Rep. Nov 5 2020;10(1):19218. doi: 10.1038/s41598-020-76263-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Lv K, Song W, Tang R, et al. Neurotransmitter alterations in the anterior cingulate cortex in Crohn’s disease patients with abdominal pain: A preliminary MR spectroscopy study. Neuroimage Clin. 2018;20:793–799. doi: 10.1016/j.nicl.2018.09.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Cruz-Almeida Y, Forbes M, Cohen RC, et al. Brain gamma-aminobutyric acid, but not glutamine and glutamate levels are lower in older adults with chronic musculoskeletal pain: considerations by sex and brain location. Pain Rep. Sep-Oct 2021;6(3):e952. doi: 10.1097/PR9.0000000000000952 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Peek AL, Rebbeck T, Puts NA, Watson J, Aguila MR, Leaver AM. Brain GABA and glutamate levels across pain conditions: A systematic literature review and meta-analysis of 1H-MRS studies using the MRS-Q quality assessment tool. Neuroimage. Apr 15 2020;210:116532. doi: 10.1016/j.neuroimage.2020.116532 [DOI] [PubMed] [Google Scholar]
- 26.Kupers R, Danielsen ER, Kehlet H, Christensen R, Thomsen C. Painful tonic heat stimulation induces GABA accumulation in the prefrontal cortex in man. Pain. Mar 2009;142(1–2):89–93. doi: 10.1016/j.pain.2008.12.008 [DOI] [PubMed] [Google Scholar]
- 27.Mawla I, Ichesco E, Zollner HJ, et al. Greater Somatosensory Afference With Acupuncture Increases Primary Somatosensory Connectivity and Alleviates Fibromyalgia Pain via Insular gamma-Aminobutyric Acid: A Randomized Neuroimaging Trial. Arthritis Rheumatol. Jul 2021;73(7):1318–1328. doi: 10.1002/art.41620 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data is available upon reasonable request from author Y.W.