Sage Journals: Discover world-class research

Abstract

This study investigated the role of brain-derived neurotrophic factor (BDNF) in patients with degenerative lumbar stenosis, focusing on its expression and correlation with pain intensity. The study examined 96 patients with lumbar stenosis and 85 control participants. BDNF levels in the yellow ligamentum flavum were measured using reverse transcription quantitative polymerase chain reaction (RT-qPCR), enzyme-linked immunosorbent assay (ELISA), and western blot analysis. The results showed significantly higher BDNF expression at both messenger ribonucleic acid (mRNA; fold change = +1.35 ± 0.23; p < 0.05) and protein levels in patients (28.98 ± 6.40 pg/mg) compared to controls (4.56 ± 1.98 pg/mg; p < 0.05). Furthermore, BDNF levels correlated positively with pain intensity reported by patients, with higher expression observed in those experiencing more severe pain. The study also explored the influence of lifestyle factors, such as smoking and alcohol consumption, and related diseases, such as diabetes, on BDNF expression. Smoking, alcohol use, and diabetes were associated with significantly elevated BDNF levels (p < 0.05). These findings suggest that BDNF could serve as a biomarker for pain severity in degenerative lumbar stenosis at the protein level, although this was not consistently observed at the mRNA level; this highlights the potential for BDNF-targeted therapies in managing pain. Future research should involve larger longitudinal studies to validate these findings and explore therapeutic interventions. This study underscores the importance of considering molecular and lifestyle factors in the treatment of degenerative lumbar stenosis, aiming to improve patient outcomes through comprehensive, targeted approaches.

Keywords

Brain-derived neurotrophic factor biomarkers neurotrophic factors spinal degenerative stenosis glycemic disorders habits

Introduction

Lumbosacral (L/S) spine stenosis is the narrowing of the spinal canal, resulting in compression of the neural and vascular elements within the lumbar spine.^1,2 Clinical symptoms are characterized by pain in the buttocks and lower limbs; in some cases, lower back pain may also occur.^3,4 Neurogenic claudication, which is characteristic of lumbar stenosis, occurs during standing and walking, and subsides in sitting, lying, and forward-bending positions.^4–6

Lumbar stenosis most commonly affects the L4/L5 level, followed by L3/L4 and L2/L3, while the L5/S1 and L1/L2 spaces are less frequently involved.⁷

Patients with both central stenosis and lateral recess stenosis complain of resting and nighttime pain, as well as pain during sneezing. Many patients who have not developed significant neurological symptoms can be treated conservatively with rehabilitation and analgesics. Surgical treatment is reserved for patients who are resistant to pain management and have increasing disability and neurological symptoms.^8,9

Surgical treatment of lumbar stenosis involves decompressing neural elements. For optimal decompression, a decompressive laminectomy is commonly used, which involves removal of the vertebral arch and the yellow ligament, trimming of the joint, and widening of the nerve root canal.^8,9 The clinical manifestation of degenerative stenosis of the L/S spine also has a molecular basis.¹⁰ It is well documented that various bioactive compounds, including brain-derived neurotrophic factor (BDNF), glial cell line–derived neurotrophic factor (GDNF), substance P, cyclooxygenase 2 (COX2), prostaglandin E2 (PGE2), and Immediate Early Gene 6 (IE-6), are involved in neuropathic pain.^11,12 In addition, neurotrophic factors have been investigated as neurotransmitters implicated in the processes of pain generation, modulation, and nerve injury repair.¹³

Nevertheless, to the best of the authors’ knowledge, changes in the BDNF expression pattern in the yellow ligament of humans have not been previously evaluated. Only Li et al.¹⁴ assessed BDNF expression in the dorsal root ganglia of a lumbar spinal stenosis model in rats. Most studies on BDNF have focused on degenerative changes within the knee joints.^15–17

BDNF (also known as ANON2 or BULN2), along with ex vivo inflammatory and nociceptive factors that induce neuronal plasticity and can actively diffuse, leading to neonephrosis and pain in vivo.^18–21 BDNF is a neurotrophin synthesized in central and peripheral nervous system cells. It is crucial for neuron development, growth, memory processes, apoptosis, neurogenesis, and neuroregeneration.²² It belongs to the neurotrophin family, which includes NT-3, NT-4/5, NT-7, and glial cell–derived neurotrophic factor, all produced in the brain and other tissues.²³

Notably, BDNF activity significantly depends on other neurotrophic factors, such as NT-3 and NT-4/5, which also exhibit neuroregenerative properties.^18,24 The synergistic interaction between NT-4/5 and BDNF in dopaminergic neuron cultures has been shown to enhance neuron survival more than BDNF alone.^13,25 These growth and neurotrophic factors are crucial in modeling and producing pain, including discogenic pain.^13,25 For instance, Maynard et al.²⁵ demonstrated the significant role of neurotrophic factors in discogenic pain induction and intensification in advanced intervertebral disc (IVD) degeneration stages.

BDNF mRNA expression in the peripheral nervous system increases during damage, both in motor neurons and Schwann cells in the distal part of the severed nerve stump, persisting only for the initial days after the damage ceases.²⁶ BDNF also promotes increased macrophage and mast cell migration into inflamed IVD, aiding in the repair processes of the damaged annulus fibrosus.²⁷ Experimental studies have shown that peripheral nerve damage induces BDNF expression at the damage site, promoting neuron regeneration. BDNF is initially produced in an inactive form, pro-BDNF, which is enzymatically converted by plasmin and metalloproteinases MMP-2 and MMP-9 into the mature BDNF (mBDNF) protein.²⁸

Therefore, this study aimed to evaluate the variations in BDNF concentrations in the yellow ligamentum flavum of the L/S section based on the severity of degenerative changes, pain intensity, habits, lifestyle factors, and comorbidities.

Materials and methods

This study was built on the work carried out in our previous papers.^29–31

Ethical considerations

Approval for this study was granted by the local Bioethics Committee at the District Medical Chamber in Kraków (224/KBL/OIL/2022). All procedures adhered to the guidelines outlined in the 2013 Declaration of Helsinki, and patient data were pseudonymized. Written, voluntary consent was obtained from each participant before their inclusion in the study group. For the control group, clinical material was obtained postmortem in accordance with the Act of July 1, 2005, on the Collection, Storage, and Transplantation of Cells, Tissues, and Organs (Journal of Laws of 2020, item 2134). Article 5 of this Act operates on an opt-out basis for organ donation.³²

Characteristics of the study group participants

The study group comprised 96 patients (46 women, or 48%; 50 men, or 52%) with an average age of 68.3 ± 2.4 years who were scheduled for extended fenestration and foraminotomy neurosurgical procedures. The inclusion and exclusion criteria are detailed in Table 1. Participants in the experimental group self-reported their smoking and alcohol consumption status, indicating whether they currently smoked or consumed alcohol. However, no additional information was gathered on the duration or amount of consumption. Spinal stenosis of the L/S section was diagnosed based on clinical interviews, physical examinations, and MRI results in various sequences and planes, utilizing 3 mm and 4 mm slices.

Table 1.

Inclusion and exclusion criteria for the study group.

Inclusion criteria	Exclusion criteria
Confirmation of degenerative stenosis of the lumbosacral spine in imaging studies	Exclusion of degenerative stenosis of the lumbosacral spine on imaging studies
Caucasian race	Race other than Caucasian
Age 18 or older but under 80	Age under 18 or over 80
No serious contraindications to surgical treatment or to internal medicine	The presence of serious contraindications to surgical treatment and to internal medicine
Not taking anticoagulants or discontinuing them as recommended after additional consultation	Taking anticoagulants or not being able to discontinue them
Failure of conservative treatment to be effective for a minimum of 6 months	Effectiveness with conservative treatment
The presence of cavity symptoms	Previous surgical treatment at the lumbosacral level of the spine
Did not take vitamin or mineral preparations registered as medicines within the last six months	Took vitamin and mineral preparations registered as medicines in the last six months
Consent to surgical treatments	No consent to the proposed surgical treatment
No history of compensated hormonal disorders	Unbalanced hormonal disorders
No gastrointestinal disorders	Disorders of the gastrointestinal tract, including malabsorption
Not pregnant	Pregnant
Not lactating	Lactating
Undergoing a period of bleeding outside of the monthly cycle or immediately after it	Undergoing bleeding during or immediately after the menstrual cycle

Pain assessment in the study group

Pain intensity in the study group was evaluated using a 10-point visual analog scale (VAS), with 0 indicating no pain and 10 indicating severe pain. None of the patients reported experiencing pain levels between 0 and 3 on the VAS scale. A total of 19 patients experienced level 4 pain, 22 patients experienced level 5 pain, 23 patients experienced level 6 pain, 9 patients experienced level 7 pain, 8 patients experienced both levels 8 and 9 pain, and 7 patients experienced level 10 pain.

Description of neurosurgical procedure

Extended fenestration and foraminotomy were performed under general endotracheal anesthesia. A skin incision was made over the affected area, followed by dissection of the paraspinal muscles and removal of the hypertrophied ligamentum flavum using Kerrison bone biters. Foraminotomy and decompression of the dural sac and nerve roots were conducted, followed by saline irrigation and skin suturing. The procedures were assisted by an operating microscope. Patients without early postoperative complications were discharged on the third day postsurgery, with a follow-up scheduled at the Neurosurgical Outpatient Clinic 4 weeks later.

Characteristics of the control group participants

The control group included 85 participants (39 women, or 46%; 46 men, or 54%), with an average age of 49.17 ± 2.65 years. Control samples were obtained during forensic autopsy or organ donation, adhering to the criteria outlined in Table 2. For the control postmortem samples, we know which individuals smoked, consumed alcohol, or had diabetes; however, we did not have detailed information on the duration or quantity, such as how long they smoked, the frequency or amount of alcohol consumed, or specifics about their diabetes management. Hematoxylin & eosin (H&E) staining was used to confirm the absence of degenerative changes, with two neurosurgery specialists (D.S. and R.S.) independently qualifying ligamentum flavum samples for the control group.

Table 2.

Inclusion and exclusion criteria for the control group.

Inclusion criteria	Exclusion criteria
Provided informed, voluntary consent	Failed to give informed, voluntary consent
Age 18 or older but under 80	Age under 18 or over 80.
No history of neoplastic diseases, either previously or currently	History or current presence of neoplastic diseases
No presence of degenerative spine disease, either currently or in the past, and no traumatic injuries to the spine, especially in the lumbosacral region, throughout the lifetime	Presence of degenerative spine disease, either currently or in the past, and/or traumatic injuries to the spine, especially in the lumbosacral region, throughout the lifetime
Did not take vitamin or mineral preparations registered as medicine within the last 6 months	Took vitamin and mineral preparations registered as medicine in the last 6 months
No history of hormonal disorders	Unbalanced hormonal disorders
No history of gastrointestinal disorders, including malabsorption	History of gastrointestinal disorders, including malabsorption
Not pregnant	Pregnant
Not lactating	Lactating
Undergoing a period of bleeding outside of the monthly cycle or immediately after it	Undergoing bleeding during or immediately after the menstrual cycle

Securing of collected material for molecular testing

Ligamentum flavum samples from both groups were thoroughly washed and placed in sterile Eppendorf tubes with RNAlater reagent (Invitrogen Life Technologies, Carlsbad, CA, USA), and then stored at −80°C until molecular analysis commenced.

RNA extraction and assessment

Total RNA extraction was performed using a modified Chomczyński-Sacchi method with TRIzol reagent (Invitrogen Life Technologies, Carlsbad, CA, USA). Samples were homogenized (T18 Digital Ultra-Turrax, IKA Polska Sp. z o.o., Warsaw, Poland), incubated with TRIzol (Invitrogen Life Technologies, Carlsbad, CA, USA) and chloroform (POL-AURA, Dywity, Poland), and centrifuged to separate the RNA. Isopropyl alcohol (POL-AURA, Dywity, Poland) was added for RNA precipitation, followed by washing with 70% ethanol. RNA isolates were purified using DNAse I and the RNeasy Mini Kit (Qiagen, Valencia, CA, USA), dried, and stored at −80°C.

Qualitative and quantitative assessments of RNA were conducted using agarose gel electrophoresis stained with ethidium bromide at a concentration of 0.5 mg/mL (Sigma-Aldrich, St. Louis, MO, USA) and spectrophotometry (Nanodrop, Thermo Fisher Scientific, Waltham, MA, USA), respectively. The correct results showed visible bands corresponding to 28SrRNA and 18SrRNA, with RNA purity ratios between 1.80 and 2.00.

Reverse transcription quantitative polymerase chain reaction (RT-qPCR)

RT-qPCR was performed in a 50 µL reaction mixture with specific thermal profiles: reverse transcription (45°C, 10 min); polymerase activation (95°C, 2 min); and 40 three-step cycles, comprising denaturation (95°C, 5 s), hybridization (60°C, 10 s), and annealing (72°C, 5 s). Primers for BDNF were as follows: Forward: 5′-AATGGGTTTAAGGTAGGTTTAAGAG-3′; Reverse: 5′-TTTTATATTCCTCCAACAAAAAAAA-3′. Beta-actin (ACTB) (Forward: 5′- TCACCCACACTGTGCCCATCTACGA-3′; Reverse 5′-CAGCGGAACCGCTCATTGCCAATGG-3′), and 18S rRNA (forward: 5′ CGGACAGGATTGACAGATTGA 3′, Reverse: 5′ GCCAGAGTCTCGTTCGTTAT 3′), served as an endogenous control. The RT-qPCR reaction was conducted using Sensi-Fast One-Step Probe Assay reagents (Bioline, London, UK). We used a one-step RT-qPCR protocol for cDNA analysis with 50 ng/µL RNA input per reaction to ensure consistency. Relative mRNA expression was calculated using the 2^−∆∆Ct method. A value greater than 1 indicates upregulation of the target gene, and a value less than 1 indicates downregulation in the experimental sample compared to the control.

Test enzyme-linked immunosorbent assay (ELISA)

Samples of yellow ligamentum flavum were collected from both the study group patients and the control group participants. These samples were finely minced with a scalpel, placed in new Eppendorf tubes, and weighed. These prepared samples were then incubated with a solution containing 4M guanidine hydrochloride (Sigma-Aldrich, St. Louis, MO, USA), 1M sodium acetate (Sigma-Aldrich, St. Louis, MO, USA), 2% Triton (Sigma-Aldrich, St. Louis, MO, USA), and a protease inhibitor cocktail (Sigma-Aldrich, St. Louis, MO, USA) for 12 h at 4°C on a laboratory rocker. After incubation, the samples were centrifuged, and the supernatant was stored at −20°C for subsequent analysis. For the ELISA, a polyclonal anti-BDNF antibody (bs-4989R, STI, Poznan, Poland; 1:500 dilution) was used according to the manufacturer’s instructions. A sample without the primary anti-BDNF antibody served as a negative control to rule out nonspecific or autofluorescence signals, while a human HeLa cervical carcinoma cell line was used as a positive control. Each sample was analyzed in triplicate, and the mean values were used for analysis. Comprehensive protocols for the ELISA and subsequent western blot procedures were previously published.^33,34

Western blot analysis

Initially, yellow ligamentum flavum samples were collected from both study group patients and control group participants. These samples were rinsed with Phosphate-Buffered Saline (PBS) solution and placed into new Eppendorf tubes. Each tube received 0.50 mL of radioimmunoprecipitation assay (RIPA) buffer supplemented with a cocktail of protease and phosphatase inhibitors (all from Sigma-Aldrich, St. Louis, MO, USA). The samples were homogenized using a hand-held homogenizer (T18 Digital Ultra-Turrax, IKA Polska Sp. z o. o., Warsaw, Poland) until no solid fragments remained. Following homogenization, the tubes were placed on ice and gently rocked for 60 min. The samples were then centrifuged, and the supernatant was collected and stored at −80°C for further analysis.

Upon thawing, the total protein concentration in the samples was determined using a bicinchoninic acid (BCA) assay kit (Thermo Fisher, Waltham, MA, USA) according to the manufacturer’s instructions. Protein concentrations varied between 20 and 100 μg of total protein. Measurements were calculated using a standard curve based on bovine serum albumin (BSA) standard solutions, comprising six standard points (0, 250, 500, 1000, 1500, and 2000 µg/mL; Sigma-Aldrich, St. Louis, MO, USA).

A polyclonal anti-BDNF antibody (bs-4989R, STI, Poznan, Poland; molecular weight 14 kDa; 1:300 dilution) was employed as per the manufacturer’s protocol. B-actin (ACTB; Santa Cruz Biotech, Dallas, TX, USA, molecular weight 37 kDa; catalog number sc-25778; 1:500 dilution) was used as the endogenous control protein. The secondary antibody used was HRP-conjugated goat antirabbit IgG (BioRad, Milan, Italy; catalog number 1706515; 1:3000 dilution).

Equal amounts of protein (20 µg) were separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis (POL-AURA, Dywity, Poland). The proteins were then transferred onto a polyvinylidene difluoride (PVDF) membrane (0.45 µm pore size, Thermo Fisher, Waltham, MA, USA). The optical density of each blot lane was measured using Kodak MI 4.5SE software (Kodak, Rochester, NY, USA).

Samples of yellow ligamentum flavum that did not include the primary mouse monoclonal IgG1 κ pro BDNF antibody served as a negative control, while a human HeLa cervical carcinoma cell line was used as a positive control.

Immunohistochemical (IHC) analysis

Tissue specimens were sliced at a thickness of 8.0 µm using a microtome (Leica Microsystems, Wetzlar, Germany). Subsequent processing steps, including dehydration, antigen retrieval, antibody incubations, and staining, were carried out according to the manufacturer’s guidelines provided in the instruction manuals for the DAB Substrate Kit (Peroxidase, HRP; Vector Laboratories, Newark, CA, USA) and the IHC-Paraffin Protocol (IHC-P; Abcam plc, Cambridge, UK).

The resulting immunohistochemical reactions were observed and captured using a Nikon Coolpix fluorescent optical system. The cellular localization and quantity of the selected proteins were analyzed through computer image analysis utilizing the ImageJ software. A total of 15 photographs were taken from 3 slides per patient under 200× magnification. Using the IHC-Profiler plug-in in ImageJ, the optical density of the DAB reaction products was assessed in areas where the immunohistochemical reaction occurred in response to the presence of the selected proteins. Additionally, the average percentage of the DAB-stained area was calculated relative to the background values in each field.

Statistical analysis

All statistical analyses were performed using the Statplus software (AnalystSoft Inc., Brandon, FL, USA), with significance set at p < 0.05. Data distribution normality was assessed with the Shapiro–Wilk test, and parametric tests followed accordingly. For group comparisons, one-way analysis of variance (ANOVA) and Scheffe’s post-hoc test were employed to identify differences in BDNF levels across VAS pain scores and Body Mass Index (BMI) categories, while a Student’s t-test was used for pairwise comparisons between binary groups (e.g. smokers vs nonsmokers). To explore the relationships between individual factors (VAS score, BMI, smoking, alcohol use, and diabetes) and BDNF levels, univariate linear regression was first applied for simple associations, followed by multivariate regression to assess the combined influence of these variables on BDNF expression. Interaction terms were included in the multivariate model to evaluate the potential moderating effects of lifestyle factors on the VAS–BDNF relationship. Additionally, multicollinearity was assessed to confirm the reliability of each predictor, and separate models were considered for the study and control groups to explore any differential impact of lifestyle factors on BDNF expression in patients with stenosis compared to controls.

Results

Expression changes in the mRNA BDNF in the control and test samples

At the mRNA level, we demonstrated BDNF overexpression in the examined samples compared to the control group (FC = +1.35 ± 0.23; p < 0.05). Subsequently, we assessed whether the transcriptional activity of BDNF mRNA was dependent on the severity of pain symptoms. In yellow ligament samples obtained from patients reporting pain levels of 4 and 5, BDNF expression was close to the control levels. This expression increased to FC = 1.57 ± 0.12 when patients reported a pain severity of 10 on the VAS scale. However, the ANOVA revealed that BDNF transcriptional activity did not vary significantly by pain severity (F(6,18) = 2.13, p > 0.05; Figure 1; p > 0.05).

Figure 1.

Transcriptional activity of BDNF mRNA in the yellow ligamentum flavum obtained from the test group, including pain severity (RT-qPCR).

Expression changes in the protein levels of BDNF in the samples obtained by ELISA

At the protein level, we also observed significantly higher BDNF concentrations in ligaments obtained from the study group compared to the control group (F(6,95) = 83.20, p < 0.0001). Specifically, ELISA measurements revealed that the BDNF concentration in the yellow ligaments from the study group was 28.98 pg/mg ± 6.40 pg/mg, while in the control group, it was 4.56 pg/mg ± 1.98 pg/mg (p < 0.05).

Figure 2 illustrates the changes in BDNF concentrations in samples collected from the study group according to the severity of pain symptoms. We noted that BDNF concentration increased with the intensity of pain reported by patients (one-way ANOVA F(6,95) = 83.20, p < 0.05). A subsequent post-hoc test indicated statistically significant differences in BDNF concentrations between patients reporting pain intensity at level 4 compared to those reporting pain at level 6 and above (Figure 2; p < 0.05), as well as between patients with pain at level 5 compared to those at level 8 and higher (Figure 2; p < 0.05).

Figure 2.

The concentration of BDNF in the yellow ligamentum flavum from the control and study groups, including the pain severity (ELISA results).

In addition, Table 3 summarizes the ELISA results, including the outcomes of the statistical analyses.

Table 3.

Concentration of BDNF in the study and Control groups, with differences based on VAS pain severity levels (ELISA results).

Group	BDNF concentration [pg/mg]	p-Value
Control	4.56 ± 1.98	<0.0001^a
Study	28.98 ± 6.40	<0.0001^a
Pain severity (VAS) 4	18.99 ± 2.46	0.041^b 0.033^c 0.032^d 0.022^e 0.018^f 0.016^g 0.031^h 0.030ⁱ 0.021^j
Pain severity (VAS) 5	25.66 ± 2.67
Pain severity (VAS) 6	28.17 ± 1.98
Pain severity (VAS) 7	29.18 ± 2.09
Pain severity (VAS) 8	34.56 ± 2.76
Pain severity (VAS) 9	35.23 ± 2.91
Pain severity (VAS) 10	37.34 ± 3.19

Data are presented as mean ± standard deviation.

Statistically significance differences between BDNF expression in the study and control groups (Student’s t-test).

Statistically significant differences between BDNF expression in VAS 4 and VAS 6 (Scheffe’s post-hoc).

Statistically significant differences between BDNF expression in VAS 4 and VAS 7 (Scheffe’s post-hoc).

Statistically significant differences between BDNF expression in VAS 4 and VAS 8 (Scheffe’s post-hoc).

Statistically significant differences between BDNF expression in VAS 4 and VAS 9 (Scheffe’s post-hoc).

Statistically significant differences between BDNF expression in VAS 4 and VAS 10 (Scheffe’s post-hoc).

Statistically significant differences between BDNF expression in VAS 5 and VAS 8 (Scheffe’s post-hoc).

Statistically significant differences between BDNF expression in VAS 5 and VAS 9 (Scheffe’s post-hoc).

Statistically significant differences between BDNF expression in VAS 5 and VAS 10 (Scheffe’s post-hoc).

statistically significant differences between BDNF expression in VAS 6 and VAS 9 (Scheffe’s post-hoc).

Expression changes in the protein levels of BDNF in the samples obtained by Western blot analysis

The expression profile of BDNF in degenerated and control yellow ligamentous flavum, determined using the western blot technique, was the same as that noted in the ELISA procedure. Figure 3 presents an example electropherogram that confirms the specificity of the reaction, as well as the nativity of the samples (based on the ACTB result; molecular mass of 42 kDa). The normalized optical density of BDNF (molecular weight 28 kDa) relative to ACTB in the study samples was 1.10 ± 0.67 compared to 0.39 ± 0.24 in the control samples, which was statistically significant (t(94) = 28.43, p < 0.05).

Figure 3.

Normalized expression of BDNF in ligamentum flavum normalized against ACTB expression (western blot).

The normalized band optical density of BDNF in degenerated and control yellow ligamentum flavum is presented in Figure 4.

Figure 4.

Band optical density of BDNF in L/S spine yellow ligamentous flavum collected from the study and control groups, determined using western blotting.

Differences according to lifestyle in the expression profiles of BDNF at the mRNA and protein levels in degenerated yellow ligamentous flavum samples

Table 4 presents BDNF expression profiles at the mRNA and protein levels in yellow ligamentum flavum samples from control and study groups, stratified by gender, BMI, diabetes, smoking, and alcohol consumption. In general, BDNF protein expression was markedly higher in the study group across all categories, indicating a substantial increase in the degenerated samples. For instance, females in the study group exhibited a protein level of 31.16 ± 3.45 pg/mg compared to 4.72 ± 1.85 pg/mg in controls. Obese individuals also showed notably elevated BDNF levels, particularly at the protein level, with the study group reaching 35.06 ± 6.22 pg/mg. Diabetes, smoking, and alcohol use were consistently associated with increased BDNF expression, with smokers in the study group demonstrating the highest protein levels at 42.17 ± 4.44 pg/mg. These findings suggest that lifestyle factors like obesity, diabetes, smoking, and alcohol consumption may amplify BDNF upregulation in degenerative conditions, with the study group displaying consistently higher expression profiles compared to controls.

Table 4.

Expression of BDNF at the mRNA and protein levels in yellow ligamentous flavum samples obtained from the study and control groups.

Comparison (control/study group)	Control group						Study group
Comparison (control/study group)	mRNA expression (^2−∆∆Ct)	p-Value of student’s two-tailed t-Test^a or ANOVA^a	- T or F-value	Protein expression (pg/mg)	p-Value of student’s two-tailed t-Test^a or ANOVA^a	T or F-value	mRNA Expression (^2−∆∆Ct)	p-Value of student’s two-tailed t-Test^a or ANOVA^a	T or F-value	Protein expression (pg/mg)	p-Value of student’s two-tailed t-Test^a or ANOVA^a	T or F-value
Gender
Female (n = 39/n = 46)	1.12 ± 0.20	0.7211^a	T = 0.69	4.72 ± 1.85	0.5011^a	T = 0.73	1.29 ± 0.14	0.8311^a	T = 0.83	31.16 ± 3.45	0.3101^a	T = 0.52
Male (n = 46/n = 50)	1.18 ± 0.21	0.7211^a	T = 0.69	4.40 ± 2.05	0.5011^a	T = 0.73	1.41 ± 0.12	0.8311^a	T = 0.83	26.79 ± 5.12	0.3101^a	T = 0.52
BMI (kg/m²)
Normal (n = 32/n = 40)	1.00	0.1152^a	F = 3.98	3.89 ± 1.65	0.0042^a	F = 6.04	1.00	0.1272^a	F = 4.22	21.87 ± 5.41	0.00162^a	F = 5.67
Overweight (n = 34/n = 32)	1.16 ± 0.24			4.95 ± 1.85			1.35 ± 0.31			29.98 ± 4.98
Obesity (n = 19/n = 24)	1.28 ± 0.30			5.60 ± 2.15			1.57 ± 0.44			35.06 ± 6.22
Diabetes
No (n = 44/n = 46)	1.10 ± 0.25	0.3141^a	T = 0.95	4.10 ± 1.95	<0.0001^a	T = 3.21	1.17 ± 0.35	0.3121^a	T = 1.02	20.98 ± 5.12	<0.0001^a	T = 3.45
Yes (n = 41/n = 40)	1.26 ± 0.32	0.3141^a	T = 0.95	5.20 ± 2.10	<0.0001^a	T = 3.21	1.52 ± 0.98	0.3121^a	T = 1.02	36.95 ± 7.09	<0.0001^a	T = 3.45
Smoking
No (n = 33/n = 34)	1.08 ± 0.26	0.2011^a	T = 1.39	3.95 ± 1.80	<0.0001^a	T = 5.23	1.21 ± 0.43	0.2111^a	T = 1.44	15.78 ± 5.08	<0.0001^a	T = 5.47
Yes (n = 52/n = 62)	1.22 ± 0.24	0.2011^a	T = 1.39	5.15 ± 2.15	<0.0001^a	T = 5.23	1.49 ± 0.19	0.2111^a	T = 1.44	42.17 ± 4.44	<0.0001^a	T = 5.47
Drinking alcohol
No (n = 12/n = 11)	1.07 ± 0.19	0.2361^a	T = 1.28	4.00 ± 1.75	<0.0001^a	T = 5.98	1.19 ± 0.19	0.2531^a	T = 1.36	20.29 ± 3.12	<0.0001^a	T = 6.12
Yes (n = 73/n = 85)	1.23 ± 0.18	0.2361^a	T = 1.28	5.05 ± 2.00	<0.0001^a	T = 5.98	1.50 ± 0.17	0.2531^a	T = 1.36	37.67 ± 4.19	<0.0001^a	T = 6.12

BDNF: brain-derived neurotrophic factor; BMI: body mass index.

, p-Value of student’s two-tailed t-Test.

Regression analysis of variables potentially associated with BDNF levels in yellow ligamentum flavum from the study groups

Table 5 summarizes the associations between various characteristics and BDNF expression levels at mRNA and protein levels in control and study groups using univariate and multivariate regression analyses. For gender, neither mRNA nor protein expression showed significant associations in either group, with low r-values and p-values above 0.3. In contrast, BMI demonstrated moderate to strong correlations, particularly in protein expression, with the study group showing a higher correlation (r = 0.76, R² = 0.58, p < 0.0001) than the control (r = 0.63, R² = 0.40, p = 0.0042). Diabetes was also significantly correlated with BDNF, showing a stronger relationship in the study group for both mRNA (r = 0.74, R² = 0.55, p = 0.021) and protein (r = 0.69, R² = 0.48, p = 0.028) compared to controls. Smoking and alcohol consumption were both strongly associated with increased BDNF expression in the study group, particularly at the protein level (smoking: r = 0.83, R² = 0.69, p = 0.022; alcohol: r = 0.92, R² = 0.85, p < 0.0001). Overall, lifestyle factors such as BMI, diabetes, smoking, and alcohol consumption were consistently more strongly correlated with BDNF expression in the study group, especially at the protein level, suggesting a compounding effect of these factors in degenerative conditions. Variables found to be insignificant using linear regression were not included in the multiple regression model.

Table 5.

Univariate and multivariate regression analyses of variables associated with BDNF levels in control and study group yellow ligamentum flavum.

Characteristic	Expression level	Control group				Study group
		Linear regression		Multiple regression		Linear regression		Multiple regression
		r	R²	Coefficient	p-Value	r	R²	Coefficient	p-Value
Gender	mRNA	0.10	0.01	–	0.7211	0.24	0.06	–	0.312
Gender	Protein	0.15	0.02	–	0.5011	0.23	0.05	–	0.276
BMI (kg/m²)	mRNA	0.56	0.31	0.20	0.1152	0.65	0.42	0.412	<0.0001
BMI (kg/m²)	Protein	0.63	0.40	0.35	0.0042	0.76	0.58	0.382	<0.0001
Diabetes	mRNA	0.35	0.12	0.18	0.3141	0.74	0.55	0.456	0.021
Diabetes	Protein	0.51	0.26	0.32	<0.0001	0.69	0.48	0.512	0.028
Smoking	mRNA	0.42	0.18	0.22	0.2011	0.82	0.67	0.287	0.019
Smoking	Protein	0.75	0.56	0.44	<0.0001	0.83	0.69	0.291	0.022
Drinking alcohol	mRNA	0.44	0.19	0.25	0.2361	0.91	0.83	0.287	<0.0001
Drinking alcohol	Protein	0.82	0.67	0.51	<0.0001	0.92	0.85	0.219	<0.0001

BDNF: brain-derived neurotrophic factor; BMI: body mass index; r: correlation coefficient.

The multivariate regression analysis indicated a significant association between VAS pain scores and elevated BDNF protein levels (coefficient = 2.86, p < 0.001), highlighting pain severity as a primary factor influencing BDNF expression. Univariate analyses also showed positive associations between lifestyle factors – such as BMI, smoking, alcohol consumption, and diabetes – and BDNF protein levels, with each factor linked to elevated protein levels (p < 0.05 for each factor in Table 5). However, in the multivariate model, these lifestyle factors did not display statistically significant independent effects on BDNF protein levels when controlling for VAS pain scores (e.g. smoking: coefficient = 0.24, p = 0.807; alcohol: coefficient = 0.35, p = 0.721). This finding suggests that pain intensity primarily mediates the observed relationship between lifestyle factors and BDNF protein levels. Additionally, BDNF mRNA levels remained stable across lifestyle factors, with no significant changes associated with BMI, smoking, alcohol, or diabetes (p > 0.05 in Table 4). Therefore, while lifestyle factors correlate with BDNF protein expression, pain intensity emerges as the predominant factor driving BDNF protein level changes in this dataset (Table 6).

Table 6.

Summary of multivariate regression analysis on BDNF protein levels in relation to pain and lifestyle factors.

Factor	Association with BDNF protein (Univariate)	p-Value (Univariate)	Coefficient in multivariate model	p-Value (Multivariate)
VAS pain score	Positive	<0.001	2.86	<0.001
BMI	Positive	<0.05	–	Not significant
Smoking	Positive	<0.05	0.24	0.807
Alcohol consumption	Positive	<0.05	0.35	0.721
Diabetes	Positive	<0.05	–	Not significant

BDNF expression profile determined by IHC

The IHC analysis demonstrated visible BDNF expression in both the control and degenerated yellow ligamentum flavum samples, with distinct staining observed in the degenerated sections. Quantification of BDNF expression, measured by optical density, indicated a significant increase in the degenerated samples compared to the controls. The baseline optical density for BDNF in the control group was set at 100%, while the degenerated group showed an optical density reaching 135.72% of the control group, indicating a 35.72% increase in BDNF expression in the degenerated ligamentum flavum. Statistical analysis was performed using a Student’s t-test, confirming the significance of this difference with a p-value of <0.05. Figure 5 provides representative images of the IHC staining, illustrating this elevated expression in degenerated samples (Figure 5(b)) compared to controls (Figure 5(a)).

Figure 5.

Immunochemical expression of BDNF in the control (a) and study (b) samples.

Discussion

Significant advancements in molecular biology have reshaped our approach to understanding and managing complex conditions, such as spinal degenerative stenosis.^35,36 Our study assessed BDNF expression in the ligamentum flavum of patients with L/S degenerative stenosis, examining its association with pain severity. Our findings demonstrated significantly elevated BDNF levels in patients with higher pain scores (p < 0.05), positioning BDNF as both a marker and a potential mediator of pain in degenerative spinal conditions.³⁷ The elevated BDNF expression we observed highlights the role of BDNF in modulating neural plasticity, which is crucial in the context of pain. Cortical processing of pain involves substantial synaptic changes, with BDNF playing a pivotal role in enhancing neural connectivity in response to painful stimuli. Increased BDNF levels in the spinal dorsal horn and brainstem have been shown to amplify pain signaling, leading to heightened pain sensitivity, manifesting as hyperalgesia or allodynia.^38,39 This aligns with Baumbauer et al.,⁴⁰ who identified the BDNF SNP rs6265 (Val66Met) as linked to reduced synaptic BDNF release. Carriers of the minor allele (A) exhibit greater sensitivity to pain and require higher doses of analgesics.⁴⁰ This underscores the complex interplay between genetic factors and pain processing, which BDNF may drive at central levels. The potential of BDNF as a biomarker for pain is substantial, particularly given the limitations of subjective pain assessments, which vary with individual pain sensitivity and can be influenced by psychological and social factors.⁴¹ Our findings suggest that BDNF could provide an objective measure of pain, supplementing patient-reported scores with biologically grounded insights. This could pave the way for a more standardized assessment of pain severity in degenerative spinal stenosis and may support the development of mechanism-based treatments, reducing dependence on opioids and enhancing patients’ quality of life.^42–44

BDNF also plays a critical role in peripheral nerve regeneration. It was demonstrated that administering exogenous BDNF to injury sites in mice improved axon regeneration, while blocking BDNF in injured tissues limited connective tissue proliferation without impacting axon growth.^45,46 These findings are significant, as they highlight BDNF’s role not only in supporting nerve repair, but also in maladaptive processes, such as pain sensitization in degenerative conditions.⁴⁷

Moreover, Orita et al.⁴⁸ found that injecting BDNF-neutralizing antibodies into damaged IVDs in mice reduced the number of Calcitonin Gene-Related Peptide (CGRP)-positive neurons in the dorsal ganglia, indicating a possible link between increased local BDNF and discogenic pain.⁴⁸ Our results align with those of Henry et al.,⁴⁹ who found that elevated BDNF levels in degenerating disks correlate with higher concentrations of proinflammatory cytokines, such as IL-1β and Vascular Endothelial Growth Factor (VEGF).

These findings suggest that BDNF’s role in degenerative spinal pain may be partly mediated by inflammatory pathways, which are also known to exacerbate pain. The potential of BDNF as a biochemical marker for lumbar spine pain severity has been emphasized by Khan et al.⁵⁰ and Kartha et al.,⁵¹ who observed that BDNF could support tailored treatment approaches by helping gauge pain severity. Lee et al.⁵² corroborated these findings by detecting BDNF expression in 24 out of 25 cases of degenerative lumbosacral disks; this suggests a consistent role for BDNF across degenerative tissues.

BDNF’s role across diverse tissue types highlights its involvement in various forms of pain, such as musculoskeletal and visceral pain. Fay et al.⁵³ suggested that BDNF elevation in degenerative tissues may reflect its release from other cells, such as thrombocytes, rather than an ongoing regenerative process. This reinforces the importance of examining BDNF as a broad marker of pain in degenerative conditions, which has been well documented in osteoarthritis studies.^23,54,55 In osteoarthritis patients, higher BDNF levels have been correlated with pain severity, suggesting that BDNF may influence pain through inflammatory processes in the musculoskeletal system.⁵⁶ The presence of BDNF in bone fracture healing further underscores its relevance across multiple pain types.⁵⁷

Our findings indicate that lifestyle factors, including smoking, alcohol consumption, and diabetes, significantly influence BDNF expression. Patients with these lifestyle factors exhibited elevated BDNF levels compared to those without, suggesting that these behaviors may aggravate pain through BDNF-related mechanisms. Smoking, for example, is a well-documented risk factor for spinal degeneration and has been shown to exacerbate degenerative changes through oxidative stress and inflammation, which likely stimulate BDNF upregulation as a maladaptive response.^58,59 Smoking impairs recovery from injuries, increases bone fragility, and is associated with both intervertebral disc degeneration and osteoporosis, compounding pain and spinal degeneration symptoms.^50,60–66

Similarly, alcohol-induced dehydration can contribute to disk degeneration by reducing hydration in intervertebral discs, impairing their structural integrity,⁶⁷ and compounding the degenerative effects of poor dietary and sleep habits.^68–70

Our findings that diabetic patients have higher BDNF levels also align with research linking diabetes to spinal degeneration. Mahmoud et al.⁷¹ and Russo et al.⁷² found that hyperglycemia in diabetic patients increases apoptosis and degradation in disk cells, accelerating intervertebral disc degeneration. In addition, studies by Park et al.⁷³ and Ruiz-Fernández et al.⁷⁴ revealed that metabolic and inflammatory dysregulation linked to obesity and diabetes can lead to an increased risk of spinal degeneration mediated by factors such as BDNF. The influence of body weight on BDNF levels, as noted by Seifert et al.,⁷⁵ suggests that metabolic health and lifestyle interventions could be crucial in managing BDNF expression and associated pain.^76–80

The clinical implications of BDNF as a therapeutic target are promising, especially in the context of reducing opioid dependency. Targeted interventions to modulate BDNF levels could provide a nonaddictive alternative for pain management. This could include pharmacological approaches that use BDNF-neutralizing agents to reduce its pronociceptive effects or lifestyle-based interventions to naturally decrease BDNF levels.⁴⁷ For example, studies have shown that interventions such as exercise or dietary adjustments may lower BDNF levels in chronic pain conditions, suggesting a multimodal approach to managing pain.^15,75 As noted in Simão et al.,¹⁵ BDNF levels correlated with pain during functional activities, suggesting that BDNF may also be linked to movement-related pain exacerbations; this could inform activity-based therapy approaches for managing spinal pain.¹⁵

Future research should investigate the longitudinal effects of BDNF modulation in patients with degenerative spine conditions, particularly to determine whether altering BDNF expression could slow degeneration progression. In addition, investigating the synergistic effects of BDNF with other neurotrophic factors, such as Nerve Growth Factor (NGF), and cytokines, such as IL-1β, may offer new therapeutic strategies that target multiple pathways in pain generation and inflammation.⁵⁷ Recent studies suggest that BDNF plays a role in metabolic regulation, influencing glucose and lipid metabolism, which could inform a more integrated approach to managing spinal degeneration in diabetic or obese patients.^81,82 For instance, Duan et al.⁸³ observed that dietary restrictions increase BDNF secretion, suggesting that metabolic interventions could potentially regulate BDNF expression and, consequently, pain perception.

This study has several limitations that should be acknowledged. First, the sample size, while adequate for the initial findings, may limit the generalizability of the results. A larger cohort would provide more robust data and allow for more definitive conclusions. Second, the study is cross-sectional in nature, capturing data at a single point in time, which prevents the assessment of causality or changes in BDNF expression over time. Longitudinal studies are needed to understand the dynamics of BDNF levels and their relationship with pain progression and treatment outcomes. Third, the study relies on self-reported pain measurements, which can be subjective and influenced by individual pain tolerance and psychological factors. Incorporating objective pain assessment tools and biomarkers would strengthen the validity of the findings. Finally, while the study investigated the influence of various lifestyle factors on BDNF expression, it did not account for other potential confounding variables, such as genetic predispositions, medication use, or the presence of other comorbid conditions. Future research should aim to address these limitations to provide a more comprehensive understanding of the role of BDNF in degenerative lumbar stenosis and its potential as a therapeutic target.

Conclusion

This study provides significant insights into the role of BDNF in degenerative lumbar stenosis, particularly in relation to pain severity. Our findings demonstrate that BDNF expression is markedly elevated in the yellow ligamentum flavum of patients with lumbar stenosis compared to control subjects, and that this increase is positively correlated with the intensity of pain reported by patients. Additionally, lifestyle factors such as smoking, alcohol consumption, and the presence of diabetes significantly influence BDNF levels, highlighting the multifaceted nature of pain modulation in this condition. These results suggest that BDNF could serve as a valuable biomarker for assessing pain severity and potentially guiding treatment strategies. Moreover, targeting BDNF signaling pathways may offer new therapeutic avenues for managing pain in patients with degenerative spinal conditions. However, further research is needed to confirm these findings in larger longitudinal studies and to explore the therapeutic potential of modulating BDNF expression. Overall, this study underscores the importance of considering both molecular and lifestyle factors in the management of degenerative lumbar stenosis and opens new directions for research and treatment aimed at improving patient outcomes through targeted interventions.

Footnotes

Acknowledgements

We would like to thank Nikola Zmarzły for their assistance with the preparation of the figures.

Author contributions

Conceptualization, Dawid Sobański and B.O.G.; methodology, Dawid Sobański; formal analysis, R.S. and Dawid Sobański; resources, Damian Strojny and M.S.; data curation, Dawid Sobański and B.O.G.; writing – original draft preparation, Dawid Sobański, Damian Strojny, and B.O.G.; writing – review and editing Dawid Sobański, R.S., and B.O.G.; supervision, Dawid Sobański; B.O.G.; visualization, M.S. project administration, Dawid Sobański; B.O.G. All authors have read and agreed to the published version of the manuscript.

Consent to participate

Written, voluntary consent was obtained from each participant before their inclusion in the study group. This ensured that participants were fully informed about the nature, purpose, and procedures of the study, as well as their rights to withdraw at any time without consequence.

Consent for publication

Written, voluntary consent was obtained from each participant for the use of anonymized data collected during the study in academic publications. Participants were assured that no personal or identifying information would be disclosed.

Data availability statement

The data used to support the findings of this study are included in the article. The data cannot be shared due to third-party rights and commercial confidentiality.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical considerations

Approval for this study was granted by the local Bioethics Committee at the District Medical Chamber in Kraków (224/KBL/OIL/2022). All procedures adhered to the guidelines outlined in the 2013 Declaration of Helsinki, and patient data were pseudonymized. For the control group, clinical material was obtained postmortem in accordance with the Act of July 1, 2005, on the Collection, Storage, and Transplantation of Cells, Tissues, and Organs (Journal of Laws of 2020, item 2134). Article 5 of this Act operates on an opt-out basis for organ donation.

ORCID iDs

Dawid Sobański

Rafał Staszkiewicz

References

Heo

Park

Hong

Chung

. Indications, contraindications, and complications of biportal endoscopic decompressive surgery for the treatment of lumbar stenosis: a systematic review. World Neurosurg 2022; 168: 411–420.

Da Costa

De Decker

Lewis

Volk

Consortium (CANSORT-SCI) CSCI. Diagnostic imaging in intervertebral disc disease. Front Vet Sci 2020; 7: 588338.

Messiah

Tharian

Candido

Knezevic

. Neurogenic claudication: a review of current understanding and treatment options. Curr Pain Headache Rep 2019; 23(5): 1–8.

Deer

Sayed

Michels

Josephson

Calodney

. A review of lumbar spinal stenosis with intermittent neurogenic claudication: disease and diagnosis. Pain Med 2019; 20(Suppl. 2): S32–S44.

Houle

O’Shaughnessy

Tétreau

Châtillon

CÉ

Marchand

Descarreaux

. Comparison of walking variations during treadmill walking test between neurogenic and vascular claudication: a crossover study. Chiropr Man Therap 2021; 29: 1–11.

Hossain

Kokkinidis

Armstrong

. How to assess a claudication and when to intervene. Curr Cardiol Rep 2019; 21: 1–12.

Rampersaud

Fisher

Yee

Dvorak

Finkelstein

Wai

Abraham

Lewis

Alexander

Oxner

. Health-related quality of life following decompression compared to decompression and fusion for degenerative lumbar spondylolisthesis: a Canadian multicentre study. Can J Surg 2014; 57(4): E126.

Burgstaller

Porchet

Steurer

Wertli

. Arguments for the choice of surgical treatments in patients with lumbar spinal stenosis – a systematic appraisal of randomized controlled trials. BMC Musculoskelet Disord 2015; 16(1): 96.

Lee

Moon

Suk

Kim

Yang

Lee

. Lumbar spinal stenosis: pathophysiology and treatment principle: a narrative review. Asian Spine J 2020; 14(5): 682.

10.

Byvaltsev

Kalinin

Hernandez

Shepelev

Pestryakov

Aliyev

Giers

. Molecular and genetic mechanisms of spinal stenosis formation: systematic review. Int J Mol Sci 2022; 23(21): 13479.

11.

Boucher

Okuse

Bennett

Munson

Wood

McMahon

. Potent analgesic effects of GDNF in neuropathic pain states. Science 2000; 290(5489): 124–127.

12.

Liu

Obata

Yamanaka

Dai

Fukuoka

Tokunaga

Noguchi

. Activation of extracellular signal-regulated protein kinase in dorsal horn neurons in the rat neuropathic intermittent claudication model. Pain 2004; 109(1–2): 64–72.

13.

Barker

Mantyh

Arendt-Nielsen

Viktrup

Tive

. Nerve growth factor signaling and its contribution to pain. J Pain Res 2020; 13: 1223.

14.

Liu

Chu

Chen

Dai

Zhu

Yun

. Brain-derived neurotrophic factor expression in dorsal root ganglia of a lumbar spinal stenosis model in rats. Mol Med Rep 2013; 8(6): 1836–1844.

15.

Simão

Mendonça

de Oliveira Almeida

Santos

Gomes

Coimbra

Lacerda

ACR

. Involvement of BDNF in knee osteoarthritis: the relationship with inflammation and clinical parameters. Rheumatol Int 2014; 34(8): 1153–1157.

16.

Gomes

Lacerda

ACR

Mendonça

Arrieiro

Fonseca

Amorim

Teixeira

Miranda

Coimbra

Brito-Melo

. Effect of exercise on the plasma BDNF levels in elderly women with knee osteoarthritis. Rheumatol Int 2014; 34(6): 841–846.

17.

de Toledo Gonçalves

Marques

Pessotto

Barbosa

Imamura

Simis

Fregni

Battistella

. OPRM1 and BDNF polymorphisms associated with a compensatory neurophysiologic signature in knee osteoarthritis patients. Neurophysiol Clin 2023; 53(6): 102917.

18.

de León

Gibon

Barker

. NGF-dependent and BDNF-dependent DRG sensory neurons deploy distinct degenerative signaling mechanisms. eNeuro. Epub ahead of print 21 January 2021. DOI: 10.1523/ENEURO.0277-20.2020.

19.

Colucci-D’Amato

Speranza

Volpicelli

. Neurotrophic factor BDNF, physiological functions and therapeutic potential in depression, neurodegeneration and brain cancer. Int J Mol Sci 2020; 21(20): 7777.

20.

Kalliolias

Ivashkiv

. TNF biology, pathogenic mechanisms and emerging therapeutic strategies. Nat Rev Rheumatol 2016; 12(1): 49–62.

21.

Staszkiewicz

Bolechala

Wieczorek

Drewniak

Strohm

Miodonski

Francuz

Marcol

. Changes in essential and trace elements content in degenerating human intervertebral discs do not correspond to patients’ clinical status. Česká a slovenská neurologie a neurochirurgie 2019; 82/115(2): 203–208.

22.

Bazzari

. BDNF therapeutic mechanisms in neuropsychiatric disorders. Int J Mol Sci 2022; 23(15): 8417.

23.

García-Suárez

Rentería

Plaisance

Moncada-Jiménez

Jiménez-Maldonado

. The effects of interval training on peripheral brain derived neurotrophic factor (BDNF) in young adults: a systematic review and meta-analysis. Sci Rep 2021; 11(1): 1–14.

24.

Pan

Tsai

Chiang

Huang

Kuo

. BDNF reverses aging-related microglial activation. J Neuroinflammation 2020; 17(1): 1–18.

25.

Maynard

Hobbs

Sukumar

Kardian

Jimenez

Schloesser

Martinowich

. Bdnf mRNA splice variants differentially impact CA1 and CA3 dendrite complexity and spine morphology in the hippocampus. Brain Struct Funct 2017; 222(7): 3295–3307.

26.

Cartelli

Cavaletti

Lauria

Meregalli

. Ubiquitin proteasome system and microtubules are master regulators of central and peripheral nervous system axon degeneration. Cells 2022; 11(8): 1358.

27.

Jara

Agger

Hollis

. Functional electrical stimulation and the modulation of the axon regeneration program. Front Cell Dev Biol 2020; 8: 736.

28.

Fang

Yang

Florio

Rockenstein

Spencer

Orain

Dong

Chen

Sung

Rissman

Masliah

Ding

. Synuclein impairs trafficking and signaling of BDNF in a mouse model of Parkinson’s disease. Sci Rep 2017; 7(1): 1–13.

29.

Sobański

Staszkiewicz

Gadzieliński

Stachura

Czepko

Holiński

Czepko

Garbarek

. A study of 179 patients with degenerative stenosis of the lumbosacral spine to evaluate differences in quality of life and disability outcomes at 12 months, between conservative treatment and surgical decompression. Med Sci Monit 2023; 29: e940213.

30.

Sobański

Staszkiewicz

Filipowicz

Holiński

Jędrocha

Migdał

Grabarek

. Correction: evaluation of the concentration of selected elements in the serum of patients with degenerative stenosis of the lumbosacral spine. Biol Trace Elem Res 2024; 202(12): 5864.

31.

Sobański

Bogdał

Staszkiewicz

Sobańska

Filipowicz

Czepko

Strojny

Grabarek

. Evaluation of differences in expression pattern of three isoforms of the transforming growth factor beta in patients with lumbosacral stenosis. Cell Cycle 2024; 23(5): 555–572.

32.

Kancelaria Sejmu. Ustawa z dnia 1 lipca 2005 r. o pobieraniu, przechowywaniu i przeszczepianiu komórek, tkanek i narządów, https://isap.sejm.gov.pl/isap.nsf/DocDetails.xsp?id=wdu20051691411 (2024, accessed 13 February 2024).

33.

Staszkiewicz

Gralewski

Gładysz

Bryś

Garczarek

Gadzieliński

Marcol

Sobański

Grabarek

. Evaluation of the concentration of growth associated protein-43 and glial cell-derived neurotrophic factor in degenerated intervertebral discs of the lumbosacral region of the spine. Mol Pain 2023; 19: 17448069231158287.

34.

Staszkiewicz

Gładysz

Gralewski

Bryś

Garczarek

Gadzieliński

Marcol

Grabarek

. Usefulness of detecting brain-derived neurotrophic factor in intervertebral disc degeneration of the lumbosacral spine. Med Sci Monit 2023; 29: e938663.

35.

Allison

. Fundamental molecular biology. Hoboken, NJ: John Wiley & Sons, 2021.

36.

Yan

Yazd

Huang

Cui

Jiang

Tan

. Nucleic acid aptamers for molecular diagnostics and therapeutics: advances and perspectives. Angew Chem Int Ed Engl 2021; 60(5): 2221–2231.

37.

Dimmek

Korallus

Buyny

Christoph

Lichtinghagen

Jacobs

Nugraha

. Brain-derived neurotrophic factor and immune cells in osteoarthritis, chronic low back pain, and chronic widespread pain patients: association with anxiety and depression. Medicina (Kaunas) 2021; 57(4): 327.

38.

Xian

Zhong

Zhou

. Upregulation of brain-derived neurotrophic factor in the sensory pathway by selective motor nerve injury in adult rats. Neurotox Res 2006; 9(4): 269–283.

39.

Merighi

Salio

Ghirri

Lossi

Ferrini

Betelli

Bardoni

. BDNF as a pain modulator. Prog Neurobiol 2008; 85(3): 297–317.

40.

Baumbauer

Ramesh

Perry

Carney

Julian

Glidden

Dorsey

Starkweather

Young

. Contribution of COMT and BDNF genotype and expression to the risk of transition from acute to chronic low back pain. Clin J Pain 2020; 36(6): 430–439.

41.

Bouhassira

. Neuropathic pain: definition, assessment and epidemiology. Rev Neurol (Paris) 2019; 175(1–2): 16–25.

42.

Bönhof

Herder

Strom

Papanas

Roden

Ziegler

. Emerging biomarkers, tools, and treatments for diabetic polyneuropathy. Endocr Rev 2019; 40(1): 153–192.

43.

Gunn

Hill

Cotten

Deer

. An analysis of biomarkers in patients with chronic pain. Pain Physician 2020; 23(1): E41–E49.

44.

Coghill

Eisenach

. Individual differences in pain sensitivity: implications for treatment decisions. Anesthesiology 2003; 98(6): 1312–1314.

45.

Guevara

YMV

Yoshikawa

Saito

Maeda

Seo

. Effect of local application of an antibody against brain-derived neurotrophic factor on neuroma formation after transection of the inferior alveolar nerve in the rat. Neuroreport 2014; 25(13): 1069.

46.

Smith

. BDNF: no gain without pain? Neuroscience 2014; 283: 107–123.

47.

Jiang

Dong

Wang

Chen

Sun

. Efficacy of endoscopic radiofrequency ablation for treatment of reflux hypersensitivity: a study based on Rome IV criteria. Gastroenterol Res Pract 2022; 2022: 4145810.

48.

Orita

Eguchi

Kamoda

Arai

Ishikawa

Miyagi

Inoue

Suzuki

Toyone

Aoki

Takahashi

Ohtori

. Brain-derived neurotrophic factor inhibition at the punctured intervertebral disc downregulates the production of calcitonin gene-related peptide in dorsal root ganglia in rats. Spine 2011; 36(21): 1737–1743.

49.

Henry

Clouet

Le Bideau

Le Visage

Guicheux

. Innovative strategies for intervertebral disc regenerative medicine: from cell therapies to multiscale delivery systems. Biotechnol Adv 2018; 36(1): 281–294.

50.

Khan

Jacobsen

Khan

Filippi

Levine

Lehman

Jr Riew

Lenke

Chahine

. Inflammatory biomarkers of low back pain and disc degeneration: a review. Ann N Y Acad Sci 2017; 1410(1): 68–84.

51.

Kartha

Zeeman

Baig

Guarino

Winkelstein

. Upregulation of BDNF and NGF in cervical intervertebral discs exposed to painful whole body vibration. Spine 2014; 39(19): 1542.

52.

Lee

Kayser

Ali

. Calcium phosphate microcrystal deposition in the human intervertebral disc. J Anat 2006; 208(1): 13–19.

53.

Fay

Kuo

Chang

Yeh

Chang

Kuo

Hsu

Hung

Chen

Tsai

Huang

Cheng

Lee

. Comparative study of the cytokine profiles of serum and tissues from patients with the ossification of the posterior longitudinal ligament. Biomedicines 2023; 11(7): 2021.

54.

Sorkpor

Galle

Teixeira

Colpo

Ahn

Jackson

Miao

Ahn

. The relationship between plasma BDNF and pain in older adults with knee osteoarthritis. Biol Res Nurs 2021; 23(4): 629–636.

55.

Yan

Wang

. Transcranial direct current stimulation attenuates chronic pain in knee osteoarthritis by modulating BDNF/TrkB signaling in the descending pain modulation system. Neurosci Lett 2023; 810: 137320.

56.

Malfait

Miller

Block

. Targeting neurotrophic factors: novel approaches to musculoskeletal pain. Pharmacol Ther 2020; 211: 107553.

57.

Sun

Diggins

Gunderson

Fehrenbacher

White

Kacena

. No pain, no gain? The effects of pain-promoting neuropeptides and neurotrophins on fracture healing. Bone 2020; 131: 115109.

58.

Knutsson

Mukka

Wahlström

Järvholm

Sayed-Noor

. The association between tobacco smoking and surgical intervention for lumbar spinal stenosis: cohort study of 331,941 workers. Spine J 2018; 18(8): 1313–1317.

59.

Rajesh

Moudgil-Joshi

Kaliaperumal

. Smoking and degenerative spinal disease: a systematic review. Brain Spine 2022; 2: 100916.

60.

Jackson

Dhawale

Brown

. Association between intervertebral disc degeneration and cigarette smoking: clinical and experimental findings. JBJS Rev 2015; 3(3): e2.

61.

Elmasry

Asfour

de Rivero Vaccari

Travascio

. Effects of tobacco smoking on the degeneration of the intervertebral disc: a finite element study. PLoS One 2015; 10(8): e0136137.

62.

Chen

Pan

. A retrospective study: does cigarette smoking induce cervical disc degeneration? Int J Surg 2018; 53: 269–273.

63.

Kiraz

Demir

. Relationship of lumbar disc degeneration with hemoglobin value and smoking. Neurochirurgie 2020; 66(5): 373–377.

64.

Trevisan

Alessi

Girotti

Zanforlini

Bertocco

Mazzochin

Zoccarato

Piovesan

Dianin

Giannini

Manzato

Sergi

. The impact of smoking on bone metabolism, bone mineral density and vertebral fractures in postmenopausal women. J Clin Densitom 2020; 23(3): 381–389.

65.

Even Dar

Mazor

Karban

Ish-Shalom

Segal

. Risk factors for low bone density in inflammatory bowel disease: use of glucocorticoids, low body mass index, and smoking. Dig Dis 2019; 37(4): 284–290.

66.

Veilleux

. The relationship between distress tolerance and cigarette smoking: a systematic review and synthesis. Clin Psychol Rev 2019; 71: 78–89.

67.

Sampara

Banala

Vemuri

Gpv

. Understanding the molecular biology of intervertebral disc degeneration and potential gene therapy strategies for regeneration: a review. Gene Ther 2018; 25(2): 67–82.

68.

Năsui

Ungur

Talaba

Varlas

Ciuciuc

Silaghi

Opre

Pop

. Is alcohol consumption related to lifestyle factors in Romanian university students? Int J Environ Res Public Health 2021; 18(4): 1835.

69.

Liu

Ran

Hou

Morelli

. Causal effects of body mass index, education and lifestyle behaviors on intervertebral disc disorders: Mendelian randomization study. J Orthop Res 2024; 42(1): 183–192.

70.

Diz

JBM

de Souza Moreira

Felício

Teixeira

de Jesus-Moraleida

de Queiroz

Pereira

LSM

. Brain-derived neurotrophic factor plasma levels are increased in older women after an acute episode of low back pain. Arch Gerontol Geriatr 2017; 71: 75–82.

71.

Mahmoud

Kokozidou

Auffarth

Schulze-Tanzil

. The relationship between diabetes mellitus type II and intervertebral disc degeneration in diabetic rodent models: a systematic and comprehensive review. Cells 2020; 9(10): 2208.

72.

Russo

Ambrosio

Ngo

Vadalà

Denaro

Fan

Sowa

Kang

. The role of type I diabetes in intervertebral disc degeneration. Spine 2019; 44(17): 1177–1185.

73.

Park

Min

Kim

Seo

Kim

. Strong association of type 2 diabetes with degenerative lumbar spine disorders. Sci Rep 2021; 11(1): 16472.

74.

Ruiz-Fernández

Francisco

Pino

Mera

González-Gay

Gómez

Lago

Gualillo

. Molecular relationships among obesity, inflammation and intervertebral disc degeneration: are adipokines the common link? Int J Mol Sci 2019; 20(8): E2030.

75.

Seifert

Brassard

Wissenberg

Rasmussen

Nordby

Stallknecht

Adser

Jakobsen

Pilegaard

Nielsen

Secher

. Endurance training enhances BDNF release from the human brain. Am J Physiol Regul Integr Comp Physiol 2010; 298(2): R372–R377.

76.

Özcan-Ekşi

Kara

Berikol

Orhun

Turgut

Ekşi

MŞ

. A new radiological index for the assessment of higher body fat status and lumbar spine degeneration. Skeletal Radiol 2022; 51(6): 1261–1271.

77.

Kapetanakis

Gkantsinikoudis

Chaniotakis

Charitoudis

Givissis

. Percutaneous transforaminal endoscopic discectomy for the treatment of lumbar disc herniation in obese patients: Health-related quality of life assessment in a 2-year follow-up. World Neurosurg 2018; 113: e638–e649.

78.

Zingg

Kendall

. Obesity, vascular disease, and lumbar disk degeneration: associations of comorbidities in low back pain. PM&R 2017; 9(4): 398–402.

79.

Lee

Kim

Lee

Choi

. Relationship between obesity and lumbar spine degeneration: a cross-sectional study from the fifth Korean national health and nutrition examination survey, 2010–2012. Metab Syndr Relat Disord 2019; 17(1): 60–66.

80.

Jakoi

Pannu

D’oro

Buser

Pham

Patel

Hsieh

Liu

Acosta

Hah

Wang

. The clinical correlations between diabetes, cigarette smoking and obesity on intervertebral degenerative disc disease of the lumbar spine. Asian Spine J 2017; 11(3): 337.

81.

Selvaraju

Babu

Geetha

. Salivary neurotrophins brain-derived neurotrophic factor and nerve growth factor associated with childhood obesity: a multiplex magnetic luminescence analysis. Diagnostics 2022; 12(5): 1130.

82.

Xie

. Neurotrophic factor control of satiety and body weight. Nat Rev Neurosci 2016; 17(5): 282–292.

83.

Duan

Guo

Jiang

Ware

Mattson

. Reversal of behavioral and metabolic abnormalities, and insulin resistance syndrome, by dietary restriction in mice deficient in brain-derived neurotrophic factor. Endocrinology 2003; 144(6): 2446–2453.

Effects of pain in lumbosacral stenosis and lifestyle-related factors on brain-derived neurotrophic factor expression profiles

Abstract

Keywords

Introduction

Materials and methods

Ethical considerations

Characteristics of the study group participants

Pain assessment in the study group

Description of neurosurgical procedure

Characteristics of the control group participants

Securing of collected material for molecular testing

RNA extraction and assessment

Reverse transcription quantitative polymerase chain reaction (RT-qPCR)

Test enzyme-linked immunosorbent assay (ELISA)

Western blot analysis

Immunohistochemical (IHC) analysis

Statistical analysis

Results

Expression changes in the mRNA BDNF in the control and test samples

Expression changes in the protein levels of BDNF in the samples obtained by ELISA

Expression changes in the protein levels of BDNF in the samples obtained by Western blot analysis

Differences according to lifestyle in the expression profiles of BDNF at the mRNA and protein levels in degenerated yellow ligamentous flavum samples

Regression analysis of variables potentially associated with BDNF levels in yellow ligamentum flavum from the study groups

BDNF expression profile determined by IHC

Discussion

Conclusion

Footnotes

Acknowledgements

Author contributions

Consent to participate

Consent for publication

Data availability statement

Declaration of conflicting interests

Funding

Ethical considerations

ORCID iDs

References