Influence of Ginger Root Extract Supplementation on the Microbiota-Gut-Brain Axis in Individuals with Sciatica: Study Protocol for a Double-Blind, Placebo-Controlled Randomized Trial

Abstract

Neuropathic pain (NP) is caused by damage to the peripheral or central nervous system and is associated with adverse complex sensory and affective symptoms. There are few current treatment options for NP, and opioid analgesics have severe side effects which can lead to opioid abuse. Therefore, the development of innovative, effective, and safe alternatives is urgently needed. This study will assess the effects of ginger root extract’s anti-inflammatory and anti-oxidant properties on individuals with sciatica via the microbiome-gut-brain axis. Eighty participants (18–85 years) with chronic sciatica, classified as lean (n=40, BMI <25 kg/m²) or obese (n=40, BMI ≥30 kg/m²), will be stratified by age, sex, and BMI to receive 2,000 mg/day of ginger extract or placebo for eight weeks. Primary outcomes are pain-associated outcomes and brain neuroplasticity by assessing functional (resting state-fMRI) and structural (Diffusion Tensor Imaging) connectivity. Secondary outcomes include gut function (gut microbiota composition using 16S rRNA sequencing analysis, intestinal permeability assessing concentrations of plasma lipopolysaccharide binding protein and fecal zonulin, and fecal metabolites using LC-MS/MS analysis) and neuroinflammation: nCounter^® Neuroinflammation Panel analysis. We will evaluate outcomes at baseline and end of study. We will employ intention-to-treat principle and per-protocol for data analysis. Hierarchical linear modeling is utilized to estimate ginger supplementation’s effects while properly accounting for data dependency and identified covariates. This study was approved by the Bioethics Committee of the Texas Tech University Health Sciences Center, Lubbock, TX. Participants will sign an informed consent form before enrolling in the study. Our team will actively disseminate the results from this trial through academic conference presentations and peer-reviewed journals. We are now actively recruiting subjects for this study.

Introduction

Neuropathic pain (NP) is caused by damage to the peripheral nervous system (PNS) or central nervous system (CNS) and is associated with complex sensory and affective symptoms, as well as comorbid anxiety and depression [1]. NP is a mechanistic pain state arising from damage or irritation of nervous tissue. Sciatica represents a specific clinical syndrome of radiating leg pain caused by compression or irritation of the sciatic nerve, e.g., through lumbosacral nerve-root pathology. In that sense pain in sciatica is a form of NP. Importantly, both NP and sciatica conditions engage peripheral and central mechanisms by driving neuroinflammation, altered neuron-glia signaling, and peripheral and central sensitization. Following neural injury, glial activation induces chemokine production under transcriptional control of factors such as NF-κB [2–6], disrupting excitatory–inhibitory balance and promoting neuronal hyperexcitability and NP symptoms [7]. Excessive mitochondria-derived oxidative stress further amplifies neuroinflammation in PNS and CNS cells critical for nociceptive processing [8]. Sciatica and other NP conditions have been linked to neuroinflammatory changes in the brain [9, 10], an area that remains understudied despite evidence that cortico-limbic neuroplasticity shapes affective pain processing, prediction, and modulation [11–14]. Microglia, astrocytes, and satellite glial cells contribute to these maladaptive changes through synaptic remodeling, growth-factor release, and autocrine/paracrine signaling [15–17], ultimately driving persistent neuroplasticity across the PNS and CNS that sustains chronic NP [18].

Growing evidence indicates that the gut plays an important role in NP and sciatica, in part through alterations in the gut microbiota, the community of microorganisms residing in the gastrointestinal tract, distinct from the “microbiome,” which refers to their collective genomes. Gut dysbiosis, defined as an imbalance in the composition or function of these microbial communities, has been linked to NP development and progression [19–22]. Dysbiosis can exacerbate spinal inflammation, impair neurological recovery, and alter gut-associated lymphoid immune activation during NP [23–25]. In the PNS, gut microbiota–derived metabolites and signaling molecules can directly sensitize or inhibit dorsal root ganglion (DRG) neurons through actions on receptors and ion channels, or indirectly modulate DRG excitability via immune-cell–derived pro- or anti-inflammatory mediators [20, 26, 27]. In the CNS, neurons, microglia, astrocytes, and infiltrating immune cells respond to gut microbiota-derived mediators/metabolites/by-products that modulate neuroinflammation [28–30] and contribute to the induction and maintenance of central sensitization, including through effects on blood-brain barrier cellular activation [21] to regulate induction and maintenance of central sensitization [20, 26, 27]. Activated microglia and astrocytes release cytokines, chemokines, and modulators of glutamatergic and GABAergic signaling, promoting hyperexcitability and pain hypersensitivity [2, 31–33], contributing to central sensitization and eventually pain hypersensitivity [27]. Thus, gut dysbiosis can modulate the transmission of “pain signals” from the periphery to the brain.

The gut barrier is a critical regulator of these processes, maintaining intestinal homeostasis by preventing the entry of pathogens, toxins, and inflammatory stimuli. When barrier integrity is compromised, increased intestinal permeability (“leaky gut”) allows luminal stressors to enter the circulation, triggering systemic inflammation and immune activation [34–36]. Although dysbiosis and increased permeability often co-occur, they represent distinct processes: one involving microbial imbalance and the other involving physical barrier dysfunction. NP has been associated with both reduced microbial diversity and shifts in microbial composition [34, 35]. These gut-derived influences on neuroimmune signaling are central to the microbiota-gut-brain axis, a bidirectional communication network linking microbial metabolites, immune pathways, endocrine signals, and neural circuits. Through this axis, gut microbiota-derived neuromodulators, neurotransmitters, and primary/secondary metabolites can shape neuroplasticity in both the PNS and CNS, influencing peripheral and central sensitization, hyperexcitability, and pain persistence [20, 26–38]. Importantly, obesity, common in patients with chronic pain, can worsen dysbiosis, impair gut barrier integrity, and amplify systemic inflammation, thereby further sensitizing nociceptive pathways and exacerbating pain modulation [39–41]. Together, these findings suggest that an intervention targeting the gut microbiota and its metabolites may offer a promising therapeutic strategy for NP and sciatica while addressing critical gaps in understanding the microbiota–gut–brain axis in pain management.

Limited treatment options are available for NP management. Opioid analgesics have severe side effects which can lead to opioid abuse [42]. Therefore, developing innovative, safe and effective alternatives is urgently needed. Ginger (Zingiber officinalis Roscoe) is a potential candidate owing to its anti-oxidant and/or anti-inflammatory properties. Ginger consists of a mixture of bioactive components, including 6-, 8-, 10, and 12-, 6-, 8-, and 12-shogaols, and paradols, which all have anti-oxidant and anti-inflammatory properties [43] that are determined by the length of side chain [44]. Via passive diffusion, ginger’s bioactive compounds are able to pass through the blood-brain barrier to act on the CNS [45]. Ginger attenuates the LPS-stimulated neuroinflammation in microglial cells via the nuclear factor kappa-B (NF-κB)/MAPK signaling cascades [46]. 6-shogaol has anti-inflammatory properties in animals with neuroinflammation [47]. Ginger has been shown to decrease intestinal inflammation and improve intestinal integrity. For instance, 6-gingerol, ginger root extract’s most abundant bioactive component, restored colonic permeability [48] and decreased colonic injury in animals [49] by suppressing inflammation and oxidative stress [48–50]. 6-shogaol prevented tumor necrosis factor-alpha (TNF-α)-induced loss of blood-brain barrier via suppression of NF-κB and PI3K/Akt signaling cascades [51]. In our animal studies, we reported that ginger root extract administration (i) lessened sensory, emotional, and spontaneous pain and pain-associated anxiety behaviors; (ii) improved intestinal integrity and decreased the gene expression of NF-κB and TNF-α gene expression in the colon and amygdala [52]; and (iii) improved gut microbiota composition and decreased gut microbiome-derived pro-inflammatory fecal metabolites [53]. Our recent preclinical data further show that multiple doses of oral ginger extract administration (i) attenuated hypersensitivity in NP rats by improving gut microbiome composition and reversing molecular signatures of amygdala neuroimmune signaling, and (ii) mitigated neuroinflammation cytokines in male NP rats [54]. Furthermore, ginger improved mitochondrial function of intestines through enhanced expression of antioxidant genes and decreased oxidation [21, 55]. Ginger root extract administration decreased mRNA expression of mitochondrial fusion (mitofusin 1), fission (fission 1), biogenesis (peroxisome proliferator-activated receptor gamma coactivator-1, mitochondrial transcription factor A), mitophagy (microtubule-associated protein 1 light chain 3B, PTEM-induced kinase 1), and inflammation (NF-κB) in the intestines of diabetic NP rats [56].

Obesity and excessive adiposity–induced chronic low-grade inflammation increase the risk for back pain (a form of NP) [40] and NP after spinal injury [39]. Accumulating evidence further suggests that a pathologically altered gut microbiome such as an increased abundance of Adlercreutzia is associated with a substantial degree of back pain in obese individuals [41], who also exhibit increased intestinal permeability compared to lean individuals [57]. Together, these findings indicate that obesity significantly influences gut-brain interactions in NP states. Our preclinical studies support this concept: obese diabetic NP rats demonstrated greater mechanical hypersensitivity, glial activation in the spinal cord and colon, gut dysbiosis, and intestinal permeability than lean diabetic NP rats, whereas supplementation with ginger root extract mitigated pain by suppressing diabetic NP–induced glial activation and reversing gut dysbiosis [56]. In a separate NP model induced by spinal nerve ligation (SNL) of the L5 root, ginger root extract also mitigated pain, improved gut function, and suppressed neuroinflammation [52, 53]. Despite these findings, it remains unknown whether the effects of ginger root extract on the gut microbiome differ between obese and lean individuals with sciatic pain (a form of NP). The present study addresses this important knowledge gap.

Based on previous research (including ours), we propose translating these preclinical findings to a clinical trial to address the following research questions in individuals with NP sciatica: Can ginger root extract improve gut function (dysbiosis, impaired intestinal permeability, and pro-inflammatory metabolites)? Can ginger root extract modulate molecular signature genes of neuroinflammation systemically? Does ginger extract have beneficial effects on brain neuroplasticity and connectivity? The goal of this study is to better understand the role of microbiota-gut-brain connections/interactions by administering ginger root extract supplementation to individuals with sciatica in a randomized, double-blinded, placebo-controlled trial. This study has 3 specific aims (SA). SA 1: determine if and how ginger root extract supplementation affects gut function in lean individuals with sciatica (LS) and obese individuals with sciatica (OS); SA 2: evaluate ginger root extract supplementation’s impact on neuroinflammation in LS and OS; SA 3: determine ginger root extract supplementation’s effects on pain-associated outcomes and brain neuroplasticity, as well as the correlations between pain and gut function, neuroinflammation, and brain neuroplasticity. In this paper, we reported the study design and discussed potential challenges. We will not analyze the effects of ginger on LS and OS separately but examine their difference in a whole group analysis. In addition, we will report the study results after study completion based on Consolidation of Standards for Reporting Trials guidelines.

METHODS

Study design

This is a randomized, double-blinded, placebo-controlled trial using a factorial 2 (placebo vs. ginger) × 2 (lean vs. obese) design in which a placebo and ginger are compared in lean (BMI <25 kg/m²) and obese (BMI ≥30 kg/m²) individuals with sciatica. We will examine the impacts of two independent variables (body weight: lean vs. obese and intervention: placebo vs. ginger) and their interactions on dependent variables. The primary outcomes include pain sensitivity and brain neuroplasticity and the secondary outcomes include gut microbiota, intestinal permeability, fecal metabolites, and neuroinflammation. We will monitor safety via assessing liver function [total bilirubin, aminotransferase (ALT), and aspartate aminotransferase (AST)] and kidney function [blood urea nitrogen (BUN) and serum creatinine] at baseline and after 8-week study intervention. Participants will complete food intake and physical activity questionnaires at baseline and 8 weeks. The study team will be blinded to study group assignment. This study is an FDA-investigational new drug (IND, number 172991) clinical trial. The clinical study has received ethical approval (protocol number: IRB-FY2024–270) from the Institutional Review Board, Texas Tech University Health Sciences Center (TTUHSC). The timeline for all participant-related actions is listed in Table 1.

Table 1.

Timetable of activities planned during the course of the study directly related to participants

Parameters	Before Baseline	Baseline (0 week)	After 8 weeks
BEFORE STUDY BEGINS: Clinics
PRESCREENING: Survey	×
CONSENT/COLLECTION of MEDICAL HISTORY:	×
IFC+HIPAA
Medical history questionnaires
Blood test: CMP (AST, ALT, total bilirubin, BUN, creatinine)
Urine pregnancy test, if applicable
fMRI safety screening survey
CONFIRMATION of CRITERIA with CRI/Shen	×
Randomization		X
Intervention BEGINS: give study pills and perform assessments		×
ASSESSMENTS
Pain-associated outcomes by survey: BPI SF-MPQ		×	×
Brain activity: fMRI
Gut function: Stool sample collection (gut microbiota, fecal metabolites, fecal zonulin) Fasted blood (plasma LBP)		×	×
Neuroinflammation: Fasted whole blood (neuroinflammation panel)		×	×
MONITORING:		×	×
Food intake: Food and supplement Diary form
Physical activity survey (IPAQ-short form)
Quality of life survey (SF-36)
FASTED blood: safety
Placebo and Ginger Pill Counts

Recruitment

Lean individuals with sciatic pain and obese individuals with sciatic pain. Individuals with sciatic pain, irrespective of ethnicity/race/gender, will be recruited from Lubbock, Texas. Recruitment methods include TTUHSC Lubbock Clinics/Grace Clinic of our study physicians, TTUHSC Lubbock electronic medical records, advertisements through newspaper (Lubbock Avalanche-Journal), senior newsletters (Lubbock Senior Link Magazine), and listservs. In addition, direct person-to-person solicitation will be conducted in the TTUHSC Lubbock clinics, health fairs (Healthwise Expo), and campus announcements.

Determination of the presence of sciatica is based on self-reported questions that are listed under inclusion and exclusion criteria for sciatic pain. The majority of patients have been clinically diagnosed with sciatica and subsequently referred to our study. Based on a report by Koes et al. [58], sciatica is a clinical diagnosis based on historical and physical examination. Neither MRI nor other radiological testing is required to make this diagnosis. In fact, MRI is not recommended until conservative management measures, including medication and physical therapy, have failed to treat the condition. An MRI merely provides supporting information to determine whether referral to other specialists or invasive treatments are necessary [58]. For this reason, insurance companies typically do not pay for an MRI until conservative therapies have proven ineffective. Since this study is designed to explore ginger’s effects on pain and its underlying mechanisms in patients with sciatic pain and to disseminate the results to the general public as a guide for daily ginger supplementation for pain, the clinical diagnosis for sciatic pain is sufficient, and no lumbar MRI is necessary for recruitment.

In this study, we noted that diabetic neuropathy, muscle pain, bone pain, and other causes (i.e., abnormal levels of o calcium, phosphorus, magnesium, vitamin B12, and folate) could contribute neuropathic symptoms. Since sciatica is a very specific type of pain in a particular nerve root distribution, a diagnosis of sciatica is made based on a detailed medical history, physical exam, past medical/surgical history, and sometimes lab/radiological studies before enrollment. Diabetic neuropathy, muscle pain, bone pain, as well as abnormal levels of calcium, phosphorus, magnesium, vitamin B12, and folate, don’t typically present in the aforementioned manner. However, in this study, we will (i) measure fasting blood glucose at prescreening, baseline, and end of trial visits, and (ii) conduct a Comprehensive Metabolic Panel laboratory test at prescreening to recruit the participants within the normal range and same panel will be tested again at baseline, and end of study. In addition, the participants are advised not to alter their lifestyle or dietary habits during the intervention period. Since an 8-week clinical intervention is generally considered short-term in the context of clinical research trials, we will monitor their lifestyle or dietary habits at the baseline visit and end of study.

Pre-screening and consenting visit

Interested individuals may contact the study team to determine eligibility. After passing the prescreening, the subjects will attend an information session and sign both consent form and Health Insurance Portability and Accountability Act form before filling out medical history questionnaires for their eligibility.

Inclusion criteria:

• 18–85 years old men and women with BMI < 25 or ≥ 30 kg/m².

• self-reported prior clinical diagnosis of sciatica, characterized by low back or gluteal pain radiating past the knee into the leg(s), with chronic symptoms defined as sciatic pain persisting for at least 3 months

• during the past 24 hours, a pain scale rating of > 3 out of 10 with 0 for no pain at all and 10 for worst imaginable pain

• willingness to accept randomization

• women of childbearing potential need to agree to use an effective contraceptive during the study intervention

Exclusion criteria:

Sciatica aspects:

• known or suspected serious spinal pathology (e.g., spinal fracture, cauda equina syndrome)

• being considered or scheduled for interventional procedures or spinal surgery for sciatica management during study intervention

• focal neurological deficits with disabling or progressive symptoms

• low back pain without sciatica

GI aspects:

• unstable GI disorder

• history of chronic or systemic autoimmune diseases involved with GI

• recent (<1 month) appearance of diarrhea or hematochezia before study begins

• recent (<1 month) exposure to antibiotics before study start.

Other exclusion considerations:

• women who are pregnant or breast-feeding

• women of child-bearing potential will take urine pregnancy test prior to the baseline MRI visit and administration of any study supplement. The clinical research coordinator will run the pregnancy test and inform the patient of the results. If the test is positive, they will be withdrawn from study participation.

• cognitive impairment, history of psychiatric conditions indicating mental health instability or incapacity

• likeliness of moving during the trial, lack of transportation, or unavailability at sample collection times.

• presence of a bleeding diathesis

• taking anticoagulant medications (e.g. heparin, warfarin)

• taking dual antiplatelet medications (e.g. aspirin + plavix)

• taking an antiplatelet drug (i.e. aspirin, non-steroidal anti-inflammatory drug, Plavix, Ticlid) with clinically significant findings of complete blood count (CBC) and platelet function assay (PFA-100) as reviewed by study physicians. Participants taking antiplatelet medications will be screened using CBC and PFA-100, and those with clinically significant abnormalities will be excluded. Throughout the intervention period, adverse events, including any bruising or bleeding, will be monitored through scheduled visits and weekly check-ins. These procedures provide appropriate safety oversight while allowing the study to evaluate ginger’s effects within a clinically relevant population.

• participants with clinically significant laboratory abnormities of liver and kidney function. Definition of clinically significant for liver function is ALT or AST ≥ 3.0x upper limit of normal and for kidney function is serum creatinine > 2.0 mg/dl and BUN > 1.5x upper limit of normal.

The nurse study coordinator and study physician will review all inclusion/exclusion criteria to verify their eligibility. The study coordinator will inform potential participants of clinically significant laboratory abnormalities and positive urine pregnancy.

Sample size and power analysis

This early-phase mechanistic trial used a 2×2 factorial design (lean vs. obese; ginger vs. placebo) with n=20 per cell. Given the modest sample size, statistical models focused on prespecified main effects, with interaction terms treated as exploratory. Neuroimaging analyses will use region-of-interest and other dimensionality-reduction approaches, and microbiome analyses will emphasize diversity indices and prespecified taxa/metabolic pathways to reduce multiple-comparison burden and inter-individual variability.

An initial sample size of 80 subjects (40 LS and 40 OS) with an estimated attrition rate of 15% during the study period is expected to produce a final sample size of 68 subjects. We calculated the minimum detectable effect size (MDES) for the smallest ‘true’ effect for which this study can find statistical significance with the final sample size of N=68. When a correlation of 0.3 is reasonably assumed between pre- and post-measurements, the estimated MDES is Cohen’s f=0.28 or d=0.56 (moderate), indicating that this study will achieve ≥80% power if the effects being tested are at least moderate. In fact, previous studies demonstrated medium to large effects of obesity on clinical intestinal permeability biomarkers (plasma lipopolysaccharide binding protein [LBP]) (f=0.36, power=0.95), fecal zonulin (f=0.22, power=0.60) [57], and sex difference on lactulose/mannitol ratio (an intestinal permeability marker) (f =0.23, power=0.64) [59], suggesting that the proposed sample size will provide adequate power for assessing SA 1 gut function. In our previous clinical study, we also observed d=0.99 and 0.72 (power=1.00) for resting state functional MRI (rs-fMRI) and Diffusion Tensor Imaging (DTI) connectivity in cortico-limbic circuits involving the amygdala and mPFC [60]. Therefore, the proposed study will be sufficiently powered to detect statistical significance in the SA 3 brain neuroplasticity biomarkers. Similarly, based on published work, this sample size would be sufficient for assessing SA 2 neuroinflammation [61]. Since there is no data in the literature, power calculation was not applicable for assessing sex differences in neuroinflammation and pain outcomes. This study will examine potential sex differences in study outcomes rather than conducting separate analyses for males and females. Therefore, this study will serve as an initial trial providing preliminary effect size estimates for future research to use in sample size and power calculations when considering potential sex differences. We plan to consent up to 200 patients, recruit 80 qualified subjects, and have a final of 68 subjects who complete study.

In terms of baseline equivalence, the distributional properties of demographic characteristics and baseline clinical outcomes will be inspected within the whole sample and between participant subgroups (e.g., LS vs. OS, placebo vs. ginger, age groups, and sex groups). We will control for variables that demonstrate significant statistical nonequivalence between participant subgroups in the hypothesis testing to improve accuracy of our inferences. Additionally, we will minimize any systematic bias due to attrition by controlling for variables that significantly differ between participants who dropped out of the trial and those who did not.

Randomization and allocation concealment

After the subject meets the screening criteria and has signed consent, we will randomize the subject 1:1 to the placebo or ginger group. A stratified randomization method will be employed in order to prevent imbalance between treatment groups for relevant prognostic factors (i.e., type I error) and improve statistical power of the trial. Subjects will be stratified by their age (<50 years old or ≥50 years old), sex (men or women), and BMI (< 25 kg/m² or ≥ 30 kg/m²) and randomly assigned to either placebo group or ginger group. Randomization will be conducted internally by the study biostatistician using coded study IDs, and the study coordinator will dispense identically labeled bottles (A or B) without knowledge of their contents, with no third-party involvement in randomization, allocation concealment, or blinding.

Intervention

Study supplement

Placebo capsules and ginger capsules of the same lot will be provided from Sabinsa Corporation, East Windsor, NJ and are registered Investigational New Drug (IND) number 172991 by U.S. Food and Drug Administration. Each placebo capsule contains 500 mg of microcrystalline cellulose, hydroxypropyl methylcellulose, and a minimal quantity of rice flour as a flow agent, were utilized as a chemically inert control to ensure no confounding prebiotic effects on the gut microbiota. Each ginger capsule contains 500 mg ginger root extract consisting of 5% gingerols. Ginger rhizomes are cleaned of dirt with water, dried under shade, pulverized to pass through #10 mesh but retained on #20 mesh, and extracted with super critical CO₂ to obtain ginger soft extract containing 5% gingerols. The bioactive components of the ginger extract were quantified by HPLC analysis. The method was used to determine the concentrations of 6-gingerol (3.86–4.16%), 8-gingerol (0.59–0.64%), and 10-gingerol (0.86–0.95%), ensuring a total gingerol content of ≥ 5.0% (w/w). Additionally, total shogaols were measured within a range of 0.86–0.97% (w/w). The study capsules will be analyzed in batches for actual contents. Placebo capsules will have the same appearance (size, color, and taste) as the ginger capsules. All study supplements will be packaged in light-protective, fully labeled, and child-resistant bottles.

Treatment groups

There are two treatment groups in this study. Participants in the placebo group will take 2,000 mg of cellulose (500 mg cellulose/capsule, 2 capsules after breakfast and another 2 capsules after dinner) orally on a daily basis for 8 weeks. Participants in the ginger group will take 2,000 mg of ginger root extract (500 mg ginger root extract/capsule, 2 capsules after breakfast and another 2 capsules after dinner) orally on a daily basis for 8 weeks. Supplements will be dispensed double-masked and distributed by a study coordinator to subjects according to their identification numbers.

A supplement regimen of 2,000 mg ginger root extract daily is based on the following observations. We previously reported that administration of ginger root extract at 200 mg/kg body weight mitigated intestinal permeability, improved gut microbiome composition, and normalized the molecular signature of neuroinflammation, and decreased pain in animals with neuropathic pain [54, 62]. Based on the use of body surface area for dose translation from rats to humans, ginger root extract at 200 mg/kg body weight in rats corresponds to ginger extract at 2,000 mg in a humans of 65 kg body weight. Thus, we selected the ginger root extract at 2,000 mg daily for this clinical study.

We selected an 8-week intervention length based on the following observations. (i) Supplementation of ginger root extract at 500–4,000 mg daily for a range of 6 weeks to 3 months reduced pain in a wide spectrum of chronic pain conditions (e.g., osteoarthritis, low back pain, and migraine) clinically [63, 64]; and (ii) supplementation of α-lipoic acid (a neurotrophic factor), commonly used as a non-pharmacological treatment for sciatic individuals, for 2 months significantly reduced pain and improved functional abilities in individuals with sciatica [65, 66]. Although no study we found investigated the effect of ginger root extract on patients with sciatica, given the similar neurotrophic functions of ginger root extract and α-lipoic acid [67], it is reasonable to select a 8-week intervention period for the effect of ginger root extract on sciatic pain conditions.

Blinding/unblinding/confidentiality

All study personnel will be blinded to group assignment. De-identified data with codes for assigned conditions will facilitate blinded data analysis. The principal investigator will make the determination whether to unblind a study subject’s treatment group as necessary.

Sample collection

After 8-hour overnight fasting, the blood will be drawn from a superficial arm vein and allowed to clot at room temperature for at least 30 minutes. After centrifugation, the plasma samples will be aliquoted and stored in −80°C freezers for later analysis. In addition, whole blood (3 mL) will be drawn into the Tempus Blood RNA Tube (Thermo Fisher Scientific, Catalog number 4342792) containing 6 mL of stabilizer to inactivate cellular RNases and stored at −80°C prior to neuroinflammation panel analysis. Stool samples will be collected at home using a standardized kit, immediately frozen in participants’ home freezers, and transported to the clinic in an insulated freezer bag with ice packs; upon receipt, samples will be promptly stored at −80°C to preserve microbial and metabolite integrity.

Compliance and monitoring

We will count the capsules consumed at baseline and after 8-week intervention to assess compliance and adherence. At the prescreening, baseline, and end of study visits, we will measure vital signs (blood pressure, heart rate, temperature, height, and weight) on participants. Safety monitoring will be assessed via liver and kidney function based on the blood laboratory tests at baseline and end of study. Self-reported adverse events and medical emergencies will be recorded throughout the study period.

To ensure high participant compliance and minimize the burden of record-keeping, dietary intake will be monitored via the Automated Self-Administered 24-hour (ASA24^®) Dietary Assessment Tool (version 2024, National Cancer Institute, Bethesda, MD) at baseline and Week 8. The ASA24 is a validated, high-resolution instrument utilizing the USDA Food and Nutrient Database for Dietary Studies to provide precise nutrient and food group quantification through an automated, multi-pass recall method. This approach is selected to minimize interviewer bias and reduce participant reporting fatigue, thereby ensuring high data integrity across the 8-week intervention. To further support dietary stability and assess potential dietary drift, participants are instructed to maintain their baseline eating patterns throughout the study duration. Physical activity will be assessed using the International Physical Activity Questionnaire for participants under the age of 69 and with the IPAQ-Elderly_English_self-admin_short form for those over the age of 69 [68, 69] at baseline and the end of study.

Concomitant medication, over-the-counter supplements, and therapies will be closely monitored and documented using a pain and medication diary during the study intervention period. Study participants may continue concomitant medications (including analgesics) as long as the dosage has been stable for 30 days before the start of the intervention [70]. Use of as-needed (PRN) analgesics and NSAIDs will be recorded through participant logs documenting medication name, dose, and timing. These variables will be incorporated as covariates in statistical analyses to account for potential effects on inflammation-related and gut-related outcomes. No other pain interventions will be started during the study intervention period; if considered necessary, subjects with unmanageable pain will be withdrawn from the trial.

Outcome measures

Primary outcomes include pain sensitivity [Brief Pain Inventory (BPI) and Short-Form McGill Pain Questionnaire (SF-MPQ)] and brain neuroplasticity (rs-fMRI connectivity), Secondary outcomes include gut microbiota, intestinal permeability, fecal metabolites, and neuroinflammation. We will evaluate every participant at baseline and after 8-week study intervention.

Pain assessment and brain neuroplasticity

Rationale.

BPI [66, 71] and SF-MPQ [71–73] are well validated clinical tools to assess pain-associated sensory and affective outcomes in individuals with sciatica. Resting-state functional (rs-fMRI) and structural (Diffusion Tensor Imaging, DTI) connectivity between amygdala and mPFC can serve as an important neuro-biomarker of chronic pain [74], and particularly of the transition to chronic pain from sub-acute pain states [5]. Amygdala-mPFC functional connectivity is significantly lower in patients with chronic pain and fibromyalgia, compared to healthy controls [75, 76]. There may be subregion-specific differences in mPFC connectivity.

Methods.

Pain outcomes will be assessed using the Brief Pain Inventory (BPI) and the Short-Form McGill Pain Questionnaire (SF-MPQ); consistent with established recommendations for chronic low back and radicular pain, a ≥30% reduction from baseline is used as the Minimal Clinically Important Difference (MCID) to indicate clinically meaningful improvement [77, 78]. Using this benchmark allows us to distinguish statistically significant changes from those that represent meaningful improvement in patients’ pain experience and functional impact. A BPI (9-item) questionnaire will evaluate a patient’s pain severity and its impact on daily functioning [66, 71]. SF-MPQ will evaluate NP conditions with sensory, affective, and evaluative pain scale [71–73]. The rs-fMRI connectivity will be examined between the left/ right amygdala seed regions and the broader bilateral mPFC, defined using the probabilistic Harvard-Oxford Subcortical Structural Atlas in FSL [74–76, 79–81]. We will address subregion-specific differences in mPFC connectivity patterns. We will search for clusters showing intervention-related changes in functional connectivity between amygdala and mPFC regions. Structural connectivity between the amygdala (right and left) and the mPFC will be examined using DTI data. Our data collection protocol is based on previously published works [60]. Each subject will undergo two fMRI scanning sessions scheduled at baseline and after 8-week study intervention.

Gut microbiota composition, intestinal permeability, and untargeted metabolomics

Rationale.

Neuropathic pain is associated with gut dysbiosis, resulting in increased intestinal permeability [60, 82], bacterial translocation from the gut, and loss of sympathetic tone [82]. Obese individuals with lower back pain (a form of NP) had unfavorable compositions of gut microbiota (dysbiosis) [41]. In a cohort study, compared to lean individuals, obese individuals had higher plasma LBP and fecal zonulin levels (clinical biomarkers of intestinal permeability) [57]. Gut microbiota and their metabolites are considered a key regulator in immune, neural, and endocrine systems, in addition to the metabolic signaling pathways that affect the development of NP directly and indirectly [35]. The gut microbiota-derived metabolites could regulate glial cell activity directly and indirectly. Gut microbiota modifications by dietary factors (i.e., bioactive compounds), mucus layer alterations, and epithelial damage can alter intestinal permeability, resulting in translocation of luminal content to the inner layers of the intestinal wall [34]. Thus, targeting gut microbiota composition, intestinal permeability, and fecal metabolites through ginger root extract in LS and OS represents a novel strategy to better understand mechanisms of gut dysregulation in NP [27].

Methods.

We will determine the composition of gut microbiota in extracted fecal genomic DNA using 16S rRNA amplicon sequencing based on our published work [53]. We will determine intestinal permeability using plasma LBP and fecal zonulin ELISA kits (Immunodiagnosik, Manchester, NH). We will determine untargeted metabolomics in feces by LC-MS analysis (Q-exactive HF mass spectrometer using a Vanquish LC-system and Compound Discoverer Software, version 3.1) to identify and quantify metabolites as described in our published work [53].

Neuroinflammation profile

Rationale.

Sciatica instigates neuroinflammation of the sciatic nerve. Pro- and anti-inflammatory proteins have been found in whole blood, serum, cerebrospinal fluid, and biopsies of patients with sciatica [83]. Molecular neuroinflammation research on sciatica requires a comprehensive and integrative view of neurotransmission, neuroinflammation, neuron-glia interactions, neuroplasticity, cell integrity, and metabolism.

Methods.

We will employ the same approach (nCounter^® Neuroinflammation Panel) as in our previous animal study [54]. 100 ng of whole blood mRNA will be extracted using Qiagen RNeasy mini kits. The hybridized RNA samples will be processed on the nCounter GEN2 Analysis System at the Cleveland Clinic Center, Cleveland, OH.

Statistical Analysis

Hierarchical linear models (HLM) will be estimated using a parsimonious covariate strategy to minimize the risk of over-fitting given the modest sample size per arm. Only prespecified covariates with strong theoretical and empirical justification, age, sex, and baseline pain severity, will be included, and additional covariates will be added only if clear baseline imbalances between treatment groups are observed after randomization. Missing data will be handled using full information maximum likelihood (FIML), which incorporates all available observations and provides unbiased parameter estimates under a missing-at-random assumption for repeated-measures Hierarchical Linear Modeling. As a sensitivity analysis, multiple imputation will also be conducted using all available outcome measures and baseline covariates as auxiliary variables prior to model fitting, and multiple imputation-based estimates will be compared with those obtained via FIML.

Analysis of microbiomes datasets.

We will use QIIME2 software for data quality control and processing. After reads of quality control with DADA2 (a bioinformatics tool used for denoising and analyzing gut microbiome data), we will determine the exact amplicon sequence variants (ASVs). Silva database version 138, 16S rRNA gene, will be used for taxonomy assignment. Relative abundance of individual taxa will be compared among groups using the LOCOM (a logistic regression model that is used to test differential abundance in compositional microbiome data with false discovery rate control).

Analysis of plasma LBP and fecal zonulin.

We will deposit the raw sequencing data at the National Center for Biotechnology Information (NCBI). HLM will be conducted to examine the impact of ginger on gut barrier function (i.e., plasma LBP and fecal zonulin), while properly accounting for (a) the dependency of observations, i.e., correlation of repeated measurements (level 1) within subjects (level 2) and (b) the baseline characteristics imbalanced between participant subgroups. For each outcome, we will apply HLM to examine the difference between LS and OS (body weight effect), the difference between the placebo and ginger (treatment effect), the difference between men and women (sex effect), the change over time (time effect), and the potential interactions between them all. Statistical significance of the main effects and interactions will be determined at 0.05 alpha level, and estimated marginal means will be compared at an alpha level corrected for Type I error inflation. Models will be specified with a proper link function based on the distribution of the outcome. The analysis will be conducted using SAS 9.4 software (SAS Institute Inc., Cary, NC).

Analysis of fecal metabolites.

We will perform Principal Component Analysis (PCA) to evaluate the different profiling of the metabolites between treatment groups. We will identify, quantify, and analyze data (peak areas of metabolites) using Compound Discoverer Software^™ 3.3 (Thermo Fisher Scientific, Waltham, MA). Compound Discoverer software^™ 3.3 will detect metabolites with “Predicted Formula”, followed by an automatic online library search against mzCloud and ChemSpider databases. We will check the metabolites that identified from the mzCloud library using the mirror plot of MS/MS spectra of identified metabolite with library standards. For quantitative analysis, we will calculate the area under the peak for each identified metabolite using proper peak alignment parameters described below. Bivariate tests (e.g., t-test, chi-square) will be performed to determine SA 1 outcomes in LS vs. OS, placebo vs. ginger, men vs. women, and time effect.

Analysis of neuroinflammation

We will analyze the raw datasets using the ROSALIND^® platform (https://rosalind.bio/) according to our published work [53]. In brief, sample gene transcript counts will be normalized by dividing counts within a lane by the geometric mean of the normalizer probes from the same lane. Housekeeping probes to be used for normalization will be selected based on the geNorm algorithm using NormqPCR R package [84]. We will calculate the abundance of various cell populations using the Nanostring Cell Type Profiling Module within ROSALIND. ROSALIND performs a filtering of Cell Type Profiling results to include results that have scores with a P-value ≥ 0.05. Hypergeometric distribution will be used to analyze the enrichment of pathways, gene ontology, domain structure, and other ontologies. We will calculate NanoString annotations term enrichment relative to a set of background genes. Gene expression will be considered significantly different if their fold change > 2 and P < 0.05. Bivariate tests (e.g., t-test, chi-square) will be performed to determine neuroinflammation genes in LS vs. OS, placebo vs. ginger, men vs. women, and time effect.

Analysis of BPI and SF-MPQ.

We will perform HLM to examine the impact of ginger on BPI and SF-MPQ and its interference of daily function. For each outcome, HLM will examine differences between LS and OS (body weight effect), placebo and ginger (treatment effect), men and women (sex effect), change over time (time effect), as well as interactions amidst these factors. Estimated marginal means will be compared at an alpha level corrected for Type I error inflation.

Analysis of fMRI.

We will convert structural, rs-fMRI- and DTI-weighted raw data images to NIfTI format using the dcm2nii converter [85]. We will pre-process (i) structural images using Statistical Parametric Mapping 12 (SPM12) software with MATLAB code to reduce temporal signal drift in fMRI timeseries, and (ii) functional images using tools in the FMRIB Software Library (FSL, Oxford, UK). We will apply the preprocessing steps: motion correction [86], skull-stripping [87], registration to high resolution structural space [88], spatial smoothing, and FILM pre-whitening [89]. We will analyze rs-fMRI data using seed-based correlations with probability masks of right and left amygdalae [74, 75, 79–81, 90] that converted to functional space for each subject [91]. We will extract time-course of each seed region of baseline- and after 8-week intervention scan. We will analyze rs-fMRI data using a standard two-level pipeline in FSL. In level 1 analysis, subject level correlations between each seed region’s time series and rs-fMRI data of the entire brain will be examined using the Feat tool in FSL. Level 2 analysis will be the non-parametric equivalent of a two-level (i.e. LS vs. OS), two-factor (i.e. placebo vs. ginger) mixed effects ANOVA model performed using the randomize function in FSL including level 1 estimates for each seed region as inputs (i.e., left or right amygdala). We will perform bivariate tests to determine pain and rs-fMRI in LS vs. OS, placebo vs. ginger, men vs. women, and time effect. We will conduct correlation analysis to examine the associations between pain level, gut function, neuroinflammation genes, and rs-fMRI and DTI outcomes using R software. In addition, we will perform Fisher’s Z-test to compare the correlations between LS vs. OS, as well as the partial correlations controlled for ginger root extract treatment compliance status. Similarly, the test will compare the correlations between non-ginger subjects vs. ginger subjects, as well as the partial correlations controlled for body weight (LS, OS). In a subsequent, underpowered test, we will compare the correlations between the four participant subgroups (LS non-ginger vs. OS non-ginger vs. LS ginger vs. OS ginger).

Our intent-to-treat (ITT) analysis will not discard subjects who dropped out, but utilize all available data from partial measurements to achieve asymptotically optimal estimates of model parameters and smallest possible standard errors [92]. All data (regardless of compliance) will be included for analysis. Given our prior experience conducting dietary supplement intervention clinical studies, in which participant compliance consistently exceeded 90% [93, 94], we do not anticipate compliance issues in the present study. Accordingly, we will not establish a threshold percentage of recommended supplement doses as a criterion for compliance. Instead, supplement dosage will be incorporated as a covariate in the statistical analyses to account for potential variability in intake. As a secondary ITT analysis, if applicable, missing data will be handed by Monte Carlo Markov Chain (MCMC) multiple imputation [95]. A large number of complete (imputed) datasets will be created via expectation-maximization algorithm, providing prior estimates for a subsequent MCMC procedure. We will then combine analysis results from each imputed dataset to make valid statistical inferences.

Data collection and management

Researchers will keep study information confidential except as required by law. We will encode all study documents and keep them in locked cabinets. Only authorized study team members can access to the files linking a participant’s study de-identified number to his/her name.

Principal investigator will oversee data management of the study. An independent certified monitor will assist the principal investigator in monitoring data collection process prior to data analysis. Data of eligibility, medical records, questionnaires, outcome parameters, laboratory data, and attrition/compliance rate will be entered into an Excel database. Data queries including missing values will be referred to the principal investigator. The principal investigator will have access to the final trial dataset and disclosure of contractual agreements. The principal investigator will also incorporate any correction or addition into the datasets. Finally, a clean de-identified dataset will be available to the biostatistician for statistical analysis.

Ethics

The study protocol along with study-related documents including consent form have been approved by the TTUHSC IRB, Lubbock, TX. All participants will sign informed consent form before enrolling in the study. We will report any protocol modification that may benefit the study participants or affect their safety to the IRB. All study-related documentation will be kept securely at the study site and databases will be secured with a password-protected access system.

Patient and Public Involvement

Participants and the public will not be involved in the design, trial execution, and outcomes assessment. Recruitment information (study flyers) is available at local clinics and health fair events. Such information will allow potential participants to contact our research coordinator. We will monitor participants with adverse outcomes throughout study intervention period and refer them to healthcare experts if needed. We will seek feedback from all participants to evaluate the burden of the study intervention and to help develop future trials.

DISCUSSION

Chronic sciatica remains a challenging NP condition with limited effective treatment options and substantial impact on daily functioning, disability, and opioid exposure [42]. This clinical trial addresses that gap by evaluating a safe, non-opioid botanical intervention, standardized ginger extract, selected for its anti-inflammatory, antioxidant, and emerging neuroimmune-modulating properties [43]. By integrating patient-reported pain outcomes with advanced fMRI neuroimaging measures of functional and structural neuroplasticity, the study directly examines whether ginger supplementation can influence central sensitization, a core mechanism underlying NP persistence. The addition of gut microbiota composition, intestinal permeability markers, fecal metabolomics, and neuroinflammatory gene expression further enhances the clinical relevance by capturing biological pathways increasingly implicated in pain chronification and gut-brain communication. This multidimensional approach moves beyond symptom-based assessment toward a mechanistic understanding of how a nutritional intervention may modulate the microbiota–gut–brain axis to improve NP outcomes.

BMI stratification is a key strength of this protocol and substantially enhances its scientific and translational value. Obesity is consistently associated with gut dysbiosis, increased intestinal permeability, heightened systemic inflammation, altered microbial metabolite production, and greater NP severity [39–41, 57]. These metabolic and microbial differences may meaningfully influence treatment response to nutritional or botanical interventions. By enrolling lean and obese participants in parallel and stratifying randomization by age and sex, the study is positioned to determine whether metabolic phenotype modifies the biological or clinical effects of ginger supplementation. This design directly supports the development of personalized nutritional or adjunctive therapies, as individuals with obesity may exhibit distinct microbiome signatures, inflammatory profiles, and neuroplasticity patterns that shape therapeutic efficacy.

Beyond its clinical implications, this protocol advances current knowledge in the microbiota–gut–brain axis field by integrating gut microbiome, permeability, and metabolomics, systemic neuroinflammatory, and neuroimaging endpoints within a rigorously controlled clinical trial. Few studies have simultaneously examined these mechanistic domains in the context of NP, and even fewer have done so while testing a targeted nutritional intervention [96]. The resulting dataset will provide a rare opportunity to link mechanistic biomarkers with patient-centered outcomes, offering insights into how peripheral inflammatory and microbial processes interface with central pain networks. These findings have the potential to inform precision-based strategies for chronic sciatica and related NP conditions, including the tailoring of dietary interventions to individual metabolic and microbial profiles. By grounding the trial in mechanistic rationale, stratified design, and multimodal assessment, this study strengthens its translational significance and positions its findings to meaningfully influence both clinical practice and the broader scientific understanding of neuroimmune and microbiota-mediated pain modulation.

DISSEMINATION

We will present study results at relevant national and international conferences and publish in peer-referred journals. The effectiveness of ginger root extract supplementation for sciatica-associated parameters in individuals with sciatica is still unclear. This study will address a research knowledge gap in the sciatic field. In addition, we will evaluate the safety and efficacy of ginger root extract supplementation in lean and obese individuals with sciatica to manage their NP progression.

Strength and limitations of this study.

• This is the first randomized, double-blind, placebo-controlled trial to investigate the effects of dietary ginger root extract on sciatica-related outcomes in lean and obese individuals with sciatic pain

• This study will be performed at a single research center with experience in conducting independent, investigator-initiated, randomized controlled trials in nutrition research.

• There is no long-term follow-up.