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Metformin attenuates symptoms of osteoarthritis: role of genetic diversity of Bcl2 and CXCL16 in OA

Arthritis Research & Therapy volume 25, Article number: 35 (2023) Cite this article

Abstract

Objective

This study aimed to evaluate the effectiveness of metformin versus placebo in overweight patients with knee osteoarthritis (OA). In addition, to assess the effects of inflammatory mediators and apoptotic proteins in the pathogenesis of OA, the genetic polymorphisms of two genes, one related to apoptosis (rs2279115 of Bcl-2) and the other related to inflammation (rs2277680 of CXCL-16), were investigated.

Methods

In this double-blind placebo-controlled clinical trial, patients were randomly divided to two groups, one group receiving metformin (n = 44) and the other one receiving an identical inert placebo (n = 44) for 4 consecutive months (starting dose 0.5 g/day for the first week, increase to 1 g/day for the second week, and further increase to 1.5 g/day for the remaining period). Another group of healthy individuals (n = 92) with no history and diagnosis of OA were included in this study in order to evaluate the role of genetics in OA. The outcome of treatment regimen was evaluated using the Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire. The frequency of variants of rs2277680 (A181V) and rs2279115 (938C>A) were determined in extracted DNAs using PCR-RFLP method.

Results

Our results indicated an increase in scores of pain (P ≤ 0.0001), activity of daily living (ADL) (P ≤ 0.0001), sport and recreation (Sport/Rec) (P ≤ 0.0001), and quality of life (QOL) (P = 0.003) and total scores of the KOOS questionnaire in the metformin group compared to the placebo group. Susceptibility to OA was associated with age, gender, family history, CC genotype of 938C>A (Pa = 0.001; OR = 5.2; 95% CI = 2.0–13.7), and GG+GA genotypes of A181V (Pa = 0.04; OR = 2.1; 95% CI = 1.1–10.5). The C allele of 938C>A (Pa = 0.04; OR = 2.2; 95% CI = 1.1–9.8) and G allele of A181V (Pa = 0.02; OR = 2.2; 95% CI = 1.1–4.8) were also associated with OA.

Conclusion

Our findings support the possible beneficial effects of metformin on improving pain, ADL, Sport/Rec, and QOL in OA patients. Our findings support the association between the CC genotype of Bcl-2 and GG+GA genotypes of CXCL-16 and OA.

Introduction

Osteoarthritis (OA) is a multifactorial progressive degenerative disease that is associated with synovial inflammation and bone remodeling and leads to impaired functional characteristics of the joint cartilage [1]. Inflammatory mediators and factors such as cytokines and chemokines disturb the extracellular matrix (ECM) homeostasis which has a vital role in the pathogenesis of OA [2]. Development of articular cartilage degeneration leads to progressive joint space narrowing and is associated with disability and pain in the joints [3]. OA occurs most commonly in the knee joints, which severely affects the quality and quantity of life of patients [4]. The prevalence of OA significantly increases with age with higher rates in women over 45 [5].

Racial/ethnic disparities in OA are well-recognized. Several studies have shown that non-Hispanic Black (NHB) individuals experience higher rates of symptomatic and radiographic OA, higher age-related average pain intensity, and higher levels of disability than their non-Hispanic White (NHW) counterparts, in addition to higher pain sensitivity [6,7,8]. The role of genetics in various illnesses has been well documented [9,10,11,12,13]. In addition, role of genetics in OA has been supported by many studies, predominantly the single nucleotide polymorphisms (SNPs). Genetic variations could be associated with the OA progression or response to drug therapy among different ethnicities. Since different pathways and molecular mechanisms are involved in the pathogenesis of OA, various genes can affect one’s risk for developing OA [14,15,16].

Bcl-2 is an anti-apoptotic protein that suppresses apoptosis by inhibiting the action of Bcl-2 associated X protein (BAX), a member of the Bcl-2 family that promotes apoptosis via the mitochondrial-mediated pathway. The ratio of Bcl-2 to BAX expression indicates cellular susceptibility to apoptosis [17,18,19]. In a report studying the effects of an autophagy inhibitor in the induced-OA animal models, increased autophagy in cartilages of knee joints was associated with inhibition of the Akt/mTOR signaling pathway and increased Bcl-2/Bax ratio [20]. Higher level of apoptotic cartilage death in the OA involved area than in the non-involved area better reflect their role in the pathogenesis of OA [21]. In fact, a negative correlation was observed between Bcl-2/BAX ratio, aging, and OA development [22,23,24,25].

The Bcl-2 polymorphism (-938 C> A, rs2279115), a functional SNP on chromosome 18q21.33, is located in the P2 promoter region. It has been reported that the wild type of this SNP may inhibit gene transcription and thus negatively affect Bcl-2 levels [26,27,28]. However, no study has yet evaluated the association of the Bcl-2 rs2279115 gene polymorphism with susceptibility and severity of knee OA.

Various studies have shown that the occurrence and development of OA are closely associated with the abnormal balance between autophagy and apoptosis in the cartilage [29,30,31]. Recent studies have shown that the regulation of autophagy is associated with the AMPK/mTORC1 signaling pathways. Upregulation of mTOR leads to the inhibition of autophagy, while the apoptosis of OA chondrocytes is increased which plays an important role in the pathogenesis of OA [32,33,34,35]. AMPK is a regulator of cellular energy that maintains a balance between catabolism and anabolism. Decreased control of AMPK over mTOR leads to increased mTOR activity, which may eventually lead to several age-related diseases, including diabetes and OA [36,37,38,39,40]. Inhibition of autophagy has been shown to increase inflammatory activity and lead to increased IL-1β production, which increases mTOR expression in OA chondrocytes [41, 42].

CXCL-16 is a chemokine secreted by synovial macrophages and fibroblasts that mediates the chemo-attraction of neutrophils, lymphocytes, and monocytes into the synovium [43,44,45]. Soluble CXCL-16, when bound to CXCR6, activates Akt, which may, directly and indirectly, activate its downstream key protein, serine/threonine kinase, mTOR [46, 47]. In studies, serum levels of CXCL-16 were associated with areas of bone apposition/reparative proliferation in temporomandibular joint osteoarthritis (TMJOA) and chronic rheumatoid arthritis-induced inflammation [45, 48]. Studies have reported significant expression of CXCL-16 mRNA in synovial tissue and fluid of OA compared with controls [44, 49]. The CXCL-16 functional SNP, called A181V (rs2277680) on chromosome 17p13, is located in exon 4 of the gene encoding the CXCL16 stalk and encodes the A3V mutation, in which it converts alanine to valine at codon 181 (A181V), and has a strong effect on the structure of the CXCL-16 protein [50, 51]. To date, no study has evaluated the association of A181V (rs2277680) SNP with knee OA.

Metformin is a safe and tolerable oral drug known as the first-line treatment for type 2 diabetes [52]. It can also be beneficial for a number of illness from metabolic to age-related diseases due to its effect on cellular processes [53,54,55,56,57,58,59]. According to the role of AMPK in cartilage homeostasis, metformin as an AMPK activator can protect inflammatory cell death of chondrocytes and attenuate cartilage degeneration and development of OA, as evidenced by in vivo and in vitro results [60,61,62,63].

To date, there has been no effective non-surgical treatment for OA, and existing therapies such as analgesics and nonsteroidal anti-inflammatory drugs (NSAIDs) are only used to reduce pain and swelling. It is noteworthy that surgical therapy is the last option for patients with end-stage OA [64].

To evaluate the outcome of any therapeutic interventions for knee OA, it is recommended to use multi-item knee-specific outcome measures, such as knee injury and osteoarthritis outcome score (KOOS) to provide a broader picture of the clinical condition [65,66,67].

The aim of this study was to assess the effect of metformin versus placebo on symptoms of knee OA in overweight patients diagnosed with knee OA in a randomized, double-blind, placebo-controlled trial in a 4-month period using the KOOS questionnaire. Moreover, considering the role of autophagy, AMPK, and the mTOR pathways in OA as well as the effect of Bcl-2, and CXCL-16 in regulation of the mTOR pathway, we aimed to investigate the role of genetic diversity of Bcl-2 and CXCL-16 in OA.

Methods and materials

Participants and treatment protocol

This study was a randomized double-blind placebo-controlled clinical trial with the IRCT code of IRCT20150202020908N2. Ethical approval was obtained from the Research Ethics Committee of Shiraz University of Medical Sciences with the ethical code of IR.SUMS.REC.1398.1010. This study was conducted in accordance with the Declaration of Helsinki.

The participants were selected among the patients with knee pain referred to knee clinic of Motahari complex, Shiraz, Iran.

All patients were examined by an orthopedic knee surgeon during the first visit, and a focused physical examination and history taking were performed. Standard standing anteroposterior (AP) and lateral radiograph were taken and grade of OA was defined according to Kellgren-Lawrence (K-L) classification. Those who had grade 4 were scheduled for total knee replacement surgery. Analgesics and physical rehabilitation were prescribed for patients with K-L grade ≤ 3 who had not received any treatment prior to their referral. In case the patients were not responsive to the above-mentioned treatment protocol, they were reassessed to determine whether they are eligible to enter the study.

Inclusion criteria included BMI > 25 and grade ≤ 3 of OA according to the K-L classification. Exclusion criteria included patients < 18 years of age, cancer, autoimmune diseases, type 2 diabetes, alcoholism, inflammatory bowel disease (IBD), hepatic or renal dysfunction, previous intra-articular knee injections, and metformin use or history of use in the last 2 months. Regarding medication history, patients did not use any anti-inflammatory agent or any other drugs with anti-inflammatory properties except for NSAIDs.

All participants filled out the informed consent form prior to entry of the study. Demographic variables of the participants such as age, sex, BMI, family history, medical conditions, and drug history were collected (Table 1).

Table 1 Demographic data of OA patients and healthy controls
Full size table

A total of 88 cases diagnosed with OA were enrolled in this study; OA patients were randomly divided to two groups, one group receiving metformin (n = 44) and the other group receiving an identical inert placebo (n = 44) for 4 consecutive months (starting dose 0.5 g/day for the first week, increase to 1 g/day for the second week, and further increase to 1.5 g/day for the remaining period).

Allocation of patients was based on a simple randomization method of two sets of envelopes with the name of the drug/placebo prescribed inside. Envelopes were shuffled, and the clinician sequentially opened the envelopes to determine the treatment group for each patient. Both the prescribing physician and the patients were blinded to the treatment as well as the analyst who measured the response rate.

In order to assess the possible association of genetic variants of Bcl-2 and CXCL-16 and OA, healthy people with no history of disease were invited to enroll the study by a public announcement at Motahari Medical Complex. Absence of OA was confirmed by physical examination, use of the KOOS questionnaire, and complementary radiologic evaluation when there was a doubt. Finally, 92 healthy non-OA participants were included as a negative control group.

Questionnaire

KOOS, a valid and reliable questionnaire that has been developed for use in practice and research to evaluate the short-term and long-term outcomes of knee injury such as osteoarthritis, was used to assess the effect of treatment on OA outcome. The questionnaire comprises 42 items in 5 subscales which include pain, other symptoms, function in daily living [3], function in sport and recreation (Sport/Rec), and knee-related quality of life (QOL) [65]. The participants completed the paper versions of the KOOS at the beginning and at the end of the study period. All items were scored on a scale of 0 to 4 and summed, where 0 indicates no difficulty and 4 indicates severe difficulty. The initial raw data from each subscale was converted to a scale from 0 to 100 (worst to best) [68].

Genotyping

Alongside, another group of healthy individuals (n = 92) with no history and diagnosis of OA was included in this study in order to evaluate the role of genetics in OA. Blood sample was collected from each participant in an EDTA tube, and genomic DNA was extracted from whole blood leukocytes by the salting out extraction method previously described [69]. The quality of extracted DNA was assessed using NanoDrop®, which ensured high-quality DNA for subsequent genotyping experiments. The detailed sequence information of the study SNPs is mentioned in Table 2. Analysis of SNP of polymorphism rs2277680 and rs2279115 were carried out via the polymerase chain reaction-restricted fragment length polymorphism (PCR-RFLP) method. Genotyping of both SNPs was carried out with a slight modification of previously described protocols [51, 70]. A total of 50 ng genomic DNA was mixed with 0.2 pmol of each PCR primer in a total volume of 25 μl containing 12.5 μl Master Mix (2X) (Ampliqon, Denmark). PCR cycling conditions were as follows: an initial denaturation at 95 °C for 5min, followed by 35 cycles at 95 °C for 40–45 s, 64 °C for 40 s, and 72 °C for the 30s (rs2277680), and 30 cycles at 95 °C for 45 s, 58°C for 40 s, 72 °C for the 30s (rs2279115), and a final extension at 72 °C for 7 min (rs2277680) and 72 °C for 10 min (rs2279115). After PCR amplification, PCR products of rs2277680 and rs2279115 polymorphisms were incubated with restriction enzymes PvuII (Fermentas, Lithuania) at 37 °C, for 16 h, and BccI (New England Biolabs, England) at 37 °C for 1 h. Digested fragments were separated by electrophoresis on a 3% agarose gel (Invitrogen® Ultra-Pure, Waltham, Massachusetts) and visualized in a UV transilluminator.

Table 2 List of forward and reverse primers for PCR-RFLP of rs2277680 and rs2279115 and their associated restriction enzymes and DNA fragments
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Statistical analysis

Data were analyzed using the SPSS® 21.0 for Windows (SPSS Inc., Chicago, Illinois) software. Due to a number of dropouts in the metformin group, an intent-to-treat analysis was performed. Continuous variables are demonstrated as mean ± SD, and categorical variables are presented in percentages (%). Mann-Whitney test was used to analyze non-parametric data, while t-test was used for parametric data analysis. In order to rule out the false positive issue in the analysis of the KOOS subscales, T2-Hotelling multivariate test was performed. Gene-disease association was assessed using odds ratio (OR) and 95% confidence interval (CI) estimation based on the following genetic contrast/models: (1) allele contrast (C-allele vs A-allele, and G-allele vs A-allele); (2) recessive model (CC vs CA+AA and GG vs GA+AA); (3) dominant model (CC+CA vs AA and GG+GA vs AA) for the genetic polymorphisms of the two SNPs, rs2279115 of Bcl-2 and rs2277680 of CXCL-16, respectively. Distributions of genotypes was calculated by chi-square (χ2) test. Adjusted P-values were calculated using multiple logistic regression analysis. P-value < 0.05 was considered as statistically significant.

Results

A total of 88 patients diagnosed with OA based on KOOS scale were enrolled in our randomized clinical trial. Ninety-two healthy participants were recruited as well. Twenty-seven patients in the metformin group and 44 patients in the placebo group completed the study. The drop-out in the metformin group was because of lack of tolerance due to side effects of metformin such as dizziness, lightheadedness, lethargy, or digestive problems which occurred by increase in the dosage of the drug up to 1500 mg/day.

All the enrolled participants completed the KOOS questionnaire (Table 1). Among the total of 180 enrolled participants, 44 were metformin users (age, 49.3 ± 9.3 years; 77.3% female, 22.7% male), 44 were placebo users (age, 47.3 ± 9.0 years; 68.2 female, 31.8 male), and 92 were healthy controls (age, 33.0 ± 7.7 years; 44.6 female, 55.4 male). The mean BMI of the metformin, placebo, and healthy control group were 29.1 ± 3.0 kg/m2, 29.0 ± 3.8 kg/m2, and 25.6 ± 4.9 kg/m2 respectively.

In terms of age, gender, and family history, there was a significant difference between OA patients (metformin and placebo) and healthy controls (P ≤ 0.001, P ≤ 0.005, and P ≤ 0.003, respectively) (Table 1), while no significant difference was observed between metformin and placebo groups (P ≥ 0.05) regarding these parameters (Table 3). Also, there was no significant differences between OA patients and healthy control regarding smoking status (P = 0.890). Additionally, the use of metformin for 4 months did not cause significant differences in BMI or weight change between participants in metformin group (P = 0.951).

Table 3 Demographic data of metformin and placebo groups
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The mean baseline KOOS scores of patients in metformin, placebo, and healthy control groups were 52.7 ± 18.4, 52.7 ± 19.0, and 86.8 ± 10.0, respectively. There was a significant difference between symptoms, pain, ADL, Sport/Rec, and QOL scores in patients with OA and the healthy control group at baseline (P ≤ 0.0001), as expected. The mean total KOOS scores of patients in the metformin and placebo group at the end of the study were 65.8 ± 19.8 and 51.0 ± 18.2, respectively (P ≤ 0.0001), while there was no significant difference in the mean of KOOS scores between the two groups prior to intervention (P ≥ 0.05) (Table 4). Treatment with metformin resulted in a significant improvement in pain, ADL, Sport/Rec, and QOL scores of the KOOS questionnaire at the end of the study compared to the pre-treatment time (time 0) within the same group (P ≤ 0.0001) (Table 4).

Table 4 The KOOS scores pre and post-treatment in metformin and placebo groups
Full size table

In detail, a significant increase in the item of swelling in symptoms score was observed in the metformin group between time zero and the end of the study (P = 0.006); however, in the total score of symptoms, no significant difference was observed. Treatment with placebo resulted in a reduction in the symptoms and Sport/Rec scores compared to the pre-treatment values (P = 0.014, and P ≤ 0.001, respectively). There was no significant difference in all calculated KOOS scores in metformin and placebo groups at zero time (P ≥ 0.05), while after treatment, all scores except for symptom scores were significantly different, and the beneficial effects of metformin treatment compared to placebo treatment were clear (P ≤ 0.05) (Table 4). The P-value of T2-Hotelling test was < 0.001. As expected, the scores of metformin users at the end of the study were still significantly different from the healthy subjects (P ≤ 0.0001).

Genotype and allele distribution of Bcl-2 and CXCL-16 gene polymorphism are presented in Table 5. P-values after adjusting for confounders (age, sex, and family history) are provided as Pa. As shown, for Bcl-2 gene, significant association with OA was found in a recessive model (Pa = 0.001; OR = 5.2; 95% CI = 2–13.7 for CC vs CA+AA). For CXCL-16 gene, significant association with OA was found in a dominant model (Pa = 0.04; OR = 2.1; 95% CI = 1.1–10.5 for GG+GA vs AA).

Table 5 Genotype and allele distribution in OA patients and healthy controls
Full size table

The C allele of 938C>A (Pa = 0.04; OR = 2.2; 95% CI = 1.1–9.8) and G allele of A181V (Pa = 0.02; OR = 2.2; 95% CI = 1.1–4.8) were associated with OA.

Discussion

In this study, we conducted a double-blind placebo-controlled clinical trial to determine whether metformin intervention can affect OA, ameliorate signs, and pain or modify activity in overweight non-diabetic knee OA patients within 4 months of treatment. We also assessed the role of genetic variations of Bcl-2 and CXCL-16 in OA. The results of our study demonstrated significant beneficial effects of metformin on the general conditions of OA patients. Metformin also caused a significant reduction in knee swelling. On the other hand, placebo treatment did not produce beneficial effects on the condition of OA patients.

The results of another clinical trial in OA patients confirm the beneficial effects of metformin such as changes in western Ontario and McMaster universities osteoarthritis index (WOMAC) score and visual analog scale (VAS) knee pain with a maximum dose of 2 g/day for 24 months [71]. In another study, the results showed that metformin (1000 mg/day for 12 weeks) in combination with meloxicam (15 mg/day) significantly improved KOOS components compared to the setting that meloxicam was used alone in OA patients [72]. Recently, some studies have reported the therapeutic influence of metformin on reducing cartilage degeneration and joint pain in animal models and cohort studies [73,74,75,76]. In our study, with pain reduction following metformin administration, pain consequences such as a disability in activities of daily living, exercise, physical reactions, and quality of life also improved in OA patients. In this regard, the effects of metformin in reducing pain and edema which was observed in our study can be attributed to many factors, including its anti-inflammatory and antioxidant effects [77,78,79]. mTOR signaling has been reported to sensitize the nervous system in conditions such as chronic pain along provoking inflammation [80, 81]. Additionally, the role of AMPK in reduction of pain and inflammation is clear. As known, metformin inhibits the mTOR pathway and its downstream pathways by enhancing AMPK phosphorylation. It also maintains the balance between apoptosis and autophagy of chondrocytes and other cells by activating AMPK and reduces cartilage degeneration by affecting the mTOR pathway and its downstream pathways [39, 61,62,63, 74]. As a result, metformin reduces pain and edema by inhibiting apoptosis, reducing oxidative stress, and increasing autophagy [79, 81,82,83].

Other findings of our study were that the carriers of CC genotype of 938C>A were significantly more prone to OA. Bcl-2 gene consists of two promoters, P1 and P2; the P2 promoter plays a regulatory role on the P1 promoter and reduces its activity. The SNP 938C>A is located on the P2 promoter. Previous studies suggest that the C allele increases the activity of the P2 promoter and thus inhibits gene transcription by the P1 promoter and promotes apoptosis by reducing Bcl-2 gene expression [26,27,28]. The A allele is reported to be associated with increased cancer risk by increasing the expression level of Bcl-2 and inhibiting apoptosis [28, 84,85,86]. According to different studies, Bcl-2 mRNA expression level is significantly decreased in the cartilage tissue of patients with high degree of OA or in animal models; however, in other studies, this reduction of Bcl-2 level was not supported statistically [22, 87,88,89]. The only SNP studied previously in OA patients is the Bcl-2 -717 C>A polymorphism where its homozygous mutant genotype was reported to be associated with decreased expression of Bcl-2, promotion of apoptosis, and development of OA [90]. Bcl-2 is one of the important elements of interaction between the apoptotic and autophagy systems [91]. It has been reported that binding of the autophagy protein Atg4B to Bcl-2 leads to degradation of Bcl-2-Beclin-1 and induces Bcl-2-Beclin1 dissociation. The release of Beclin-1 and the subsequent binding to PI3KC3 regulates autophagy initiation which finally leads to switch from apoptosis to autophagy [92,93,94]. According to the effect of CC genotype in increasing apoptosis by reducing the production of Bcl-2, the probability of developing OA may increase in individuals carrying this genotype [22, 88, 90].

Regarding CXCL16 genetic variant, A181V, our results advocate the association between GG+GA genotypes as well as its associated allele, the G allele, and OA. Missense mutation of rs2277680 (A181V) causes G→A substitutions at positions 4585312 on chromosome 17, resulting in an alanine to valine substitution at codon 181 (A181V) of the CXCL-16 protein which is at its mucin-type stalk region [51]. This substitution is located in the interior of the CXCL-16 protein and affects the conformation of the chemokine domain and reduces the size of its active site, which is associated with a loss of CXCR6-mediated adhesion in human monocytes and chemotactic activity [51, 95]. The presence of this mutation was reported to be associated with an increased risk for the development of sepsis and multiple organ dysfunction syndrome (MODS) in patients with major trauma as well as acute liver failure (ALF) in patients with Hepatitis B virus (HBV) infection, as a result of lack of natural killer T (NKT) cells activation [95]. CXCL-16 is a pro-inflammatory cytokine with angiogenic properties which stimulates synovial neovascularization [96, 97]. In chronic joint inflammation of OA, the balance between pro- and anti-inflammatory cytokines is tilted towards pro-inflammatory cytokines, which ultimately leads to the initiation of angiogenesis and bone remodeling [98, 99]. Neovascularization plays an important role in the pathology of OA, and its degree is related to the degree of OA [100, 101]. The formation of new vessels, in turn, leads to increased leukocyte recruitment and migration of neurons to the joint. These new neurons are sensitized to pain through mechanical stress, hypoxia, and inflammation. Finally, the stimulation of synovial neovascularization leads to the recurrence of pain and inflammation in the joint and exacerbation of OA [102, 103]. One study demonstrated that CXCL-16/CXCR6 chemokine signaling is associated with invasive growth and angiogenic activities in PCa cells by inducing the activation of Akt/mTOR pathways [104].

The G allele of A181V has been reported to result in the production of CXCL-16 protein with an effective protein-receptor interaction site (CXCL-16/CXCR6). This effective binding increases synovial inflammation and neovascularization induced by CXCL-16 in individuals carrying these genotypes, which eventually leads to the development of OA [95, 97, 98].

It is noteworthy that metformin modulates Beclin1–Bcl-2 complex dissociation, which regulates initiation of autophagy leading to switch from apoptosis to autophagy in an AMPK-dependent and AMPK-independent manners. In the AMPK-dependent manner, metformin phosphorylates MAPK8 which mediates Bcl-2 phosphorylation and in the AMPK-independent manner metformin inactivates STAT3, an upstream protein of Bcl-2 [105,106,107]. Alternatively, metformin can inhibit mTOR phosphorylation leading to the activation of ULK1, which phosphorylates Beclin-1, thus enhancing Beclin-1-PI3KC3 complex formation and autophagy induction [80, 108]. Moreover, it has been reported that metformin decreases the mRNA expression and plasma levels of CXCL-16 (108-110). Accordingly, if our study be replicated in a larger population of patients with OA, it is possible that patients respond in different degrees to metformin. Hence, the role of studied variants of Bcl-2 and CXCL-16, as targets of metformin, in response to metformin treatment can be assessed in future studies.

As the study limitation, we should allude to the relatively small sample size of the enrolled subjects. However, positive results showing the beneficial effects of somewhat short-term treatment of OA in non-diabetic patients opens up a venue to explore the effect of metformin in larger sample sizes. Alongside, the association between genetic variants of Bcl-2 and CXCL-16 and OA was investigated for the first time which may provide preliminary insights for further investigations in various ethnicities and larger study groups.

Conclusion

A 4-month period of treatment of non-diabetic OA patients with metformin provided significant beneficial effects. Due to good safety profile and limited and mostly tolerable side effects of metformin, this oral hypoglycemic agent may be considered as an alternative or adjuvant treatment of OA patients. Additionally, significant associations with OA susceptibility were observed in carriers of different variants of 938C>A and A181V polymorphisms. We identified a possible risk genotype, wild genotype (CC) of Bcl-2 and wild allele (G) of CXCL-16 for OA susceptibility. Assessing patients more at risk of OA based on their genetic pattern may provide clues for considering preventive options in patients more at risk.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

OA:

Osteoarthritis

KOOS:

Knee Injury and Osteoarthritis Outcome Score

ADL:

Activity of daily living

Sport/Rec:

Sport and Recreation

QOL:

Quality of life

ECM:

Extracellular matrix

NHB:

Non-Hispanic Black

NHW:

Non-Hispanic White

SNPs:

Single nucleotide polymorphisms

BAX:

Bcl-2 associated X protein

TMJOA:

Temporomandibular joint osteoarthritis

NSAIDs:

Non-steroidal anti-inflammatory drugs

K-L:

Kellgren-Lawrence

IBD:

Inflammatory bowel disease

BMI:

Body mass index

PCR:

Polymerase chain reaction

PCR-RFLP:

PCR--restricted fragment length polymorphism

OR:

Odds ratio

CI:

Confidence interval

WOMAC:

Western Ontario and McMaster universities osteoarthritis index

MODS:

Multiple organ dysfunction syndrome

ALF:

Acute liver failure

HBV:

Hepatitis B virus

NKT:

Natural killer T

IRCT:

Iranian Registry of Clinical Trials

References

  1. Sun K, Luo J, Guo J, Yao X, Jing X, Guo F. The PI3K/AKT/mTOR signaling pathway in osteoarthritis: a narrative review. Osteoarthr Cartil. 2020;28(4):400–9.

    Article  CAS  Google Scholar 

  2. Charlier E, Deroyer C, Ciregia F, Malaise O, Neuville S, Plener Z, et al. Chondrocyte dedifferentiation and osteoarthritis (OA). Biochem Pharmacol. 2019;165:49–65.

    Article  PubMed  Google Scholar 

  3. Woloszynski T, Podsiadlo P, Stachowiak G, Kurzynski M, Lohmander L, Englund M. Prediction of progression of radiographic knee osteoarthritis using tibial trabecular bone texture. Arthritis Rheum. 2012;64(3):688–95.

    Article  CAS  PubMed  Google Scholar 

  4. Xu H, Zhao G, Xia F, Liu X, Gong L, Wen X. The diagnosis and treatment of knee osteoarthritis: a literature review. Int J Clin Exp Med. 2019;12(5):4589–99.

    CAS  Google Scholar 

  5. Litwic A, Edwards M, Dennison E, Cooper C. Epidemiology and burden of osteoarthritis. Br Med Bull. 013;105(1):85–199.

  6. Allen KD, Helmick CG, Schwartz TA, DeVellis RF, Renner JB, Jordan JM. Racial differences in self-reported pain and function among individuals with radiographic hip and knee osteoarthritis: the Johnston County Osteoarthritis Project. Osteoarthr Cartil. 2009;17(9):1132–6.

    Article  CAS  Google Scholar 

  7. Kim HJ, Yang GS, Greenspan JD, Downton KD, Griffith KA, Renn CL, et al. Racial and ethnic differences in experimental pain sensitivity: systematic review and meta-analysis. pain. 2017;158(2):194–211.

    Article  PubMed  Google Scholar 

  8. Vina E, Ran D, Ashbeck E, Kwoh CK. Natural history of pain and disability among African–Americans and whites with or at risk for knee osteoarthritis: a longitudinal study. Osteoarthr Cartil. 2018;26(4):471–9.

    Article  CAS  Google Scholar 

  9. Firouzabadi N, Tajik N, Bahramali E, Bakhshandeh H, Maadani M, Shafiei M. Gender specificity of a genetic variant of angiotensin-converting enzyme and risk of coronary artery disease. Mol Biol Rep. 2013;40(8):4959–65.

    Article  CAS  PubMed  Google Scholar 

  10. Bahramali E, Firouzabadi N, Jonaidi-Jafari N, Shafiei M. Renin–angiotensin system genetic polymorphisms: lack of association with CRP levels in patients with coronary artery disease. J Renin-Angiotensin-Aldosterone Syst. 2014;15(4):559–65.

    Article  CAS  PubMed  Google Scholar 

  11. Silman AJ, Pearson JE. Epidemiology and genetics of rheumatoid arthritis. Arthritis Res Ther. 2002;4(3):1–8.

    Google Scholar 

  12. Firouzabadi N, Ghazanfari N, Alavi Shoushtari A, Erfani N, Fathi F, Bazrafkan M, et al. Genetic variants of angiotensin-converting enzyme are linked to autism: a case-control study. PLoS One. 2016;11(4):e0153667.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Nouraei H, Firouzabadi N, Mandegary A, Zomorrodian K, Bahramali E, Shayesteh MRH, et al. Glucocorticoid receptor genetic variants and response to fluoxetine in major depressive disorder. J Neuropsychiatry Clin Neurosci. 2018;30(1):45–50.

    Article  PubMed  Google Scholar 

  14. Sharma L. Osteoarthritis year in review 2015: clinical. Osteoarthr Cartil. 2016;24(1):36–48.

    Article  CAS  Google Scholar 

  15. Valdes AM, McWilliams D, Arden NK, Doherty SA, Wheeler M, Muir KR, et al. Involvement of different risk factors in clinically severe large joint osteoarthritis according to the presence of hand interphalangeal nodes. Arthritis Rheum. 2010;62(9):2688–95.

    Article  PubMed  Google Scholar 

  16. Warner SC, Valdes AM. The genetics of osteoarthritis: a review. J Functional Morphol Kinesiol. 2016;1(1):140–53.

    Article  Google Scholar 

  17. Johnson EO, Charchandi A, Babis GC, Soucacos PN. Apoptosis in osteoarthritis: morphology, mechanisms, and potential means for therapeutic intervention. J Surg Orthop Adv. 2008;17(3):147–52.

    PubMed  Google Scholar 

  18. Cory S, Adams JM. The Bcl2 family: regulators of the cellular life-or-death switch. Nat Rev Cancer. 2002;2(9):647–56.

    Article  CAS  PubMed  Google Scholar 

  19. Thomadaki H, Scorilas A. BCL2 family of apoptosis-related genes: functions and clinical implications in cancer. Crit Rev Clin Lab Sci. 2006;43(1):1–67.

    Article  CAS  PubMed  Google Scholar 

  20. Zhang G, Cao J, Yang E, Liang B, Ding J, Liang J, et al. Curcumin improves age-related and surgically induced osteoarthritis by promoting autophagy in mice. Biosci Rep. 2018;38(4):1–11.

  21. Kim HA, Lee YJ, Seong S-C, Choe KW, Song YW. Apoptotic chondrocyte death in human osteoarthritis. J Rheumatol. 2000;27(2):455–62.

    CAS  PubMed  Google Scholar 

  22. Karaliotas GI, Mavridis K, Scorilas A, Babis GC. Quantitative analysis of the mRNA expression levels of BCL2 and BAX genes in human osteoarthritis and normal articular cartilage: an investigation into their differential expression. Mol Med Rep. 2015;12(3):4514–21.

    Article  CAS  PubMed  Google Scholar 

  23. Jalilian J, Behpour N, Hosseeinpoor Delavar S, Farzanegi P. The study of the effect of the aerobic training together with stem cells on the ievels of some of the apoptosis indices of the heart tissue of the male Wistar rats of osteoarthritis model. Jundishapur Sci Med J. 2020;18(6):585–602.

    Google Scholar 

  24. Miao G, Zang X, Hou H, Sun H, Wang L, Zhang T, et al. Bax targeted by miR-29a regulates chondrocyte apoptosis in osteoarthritis. Biomed Res Int. 2019;2019:1–9.

  25. Wang J, Chen L, Jin S, Lin J, Zheng H, Zhang H, et al. MiR-98 promotes chondrocyte apoptosis by decreasing Bcl-2 expression in a rat model of osteoarthritis. Acta Biochim Biophys Sin. 2016;48(10):923–9.

    Article  CAS  PubMed  Google Scholar 

  26. Li W, Qian C, Wang L, Teng H, Zhang L. Association of BCL2-938C> A genetic polymorphism with glioma risk in Chinese Han population. Tumor Biol. 2014;35(3):2259–64.

    Article  CAS  Google Scholar 

  27. Young RL, Korsmeyer SJ. A negative regulatory element in the bcl-2 5'-untranslated region inhibits expression from an upstream promoter. Mol Cell Biol. 1993;13(6):3686–97.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Bachmann HS, Heukamp LC, Schmitz KJ, Hilburn CF, Kahl P, Buettner R, et al. Regulatory BCL2 promoter polymorphism (− 938C> A) is associated with adverse outcome in patients with prostate carcinoma. Int J Cancer. 2011;129(10):2390–9.

    Article  CAS  PubMed  Google Scholar 

  29. Caramés B, Hasegawa A, Taniguchi N, Miyaki S, Blanco FJ, Lotz M. Autophagy activation by rapamycin reduces severity of experimental osteoarthritis. Ann Rheum Dis. 2012;71(4):575–81.

    Article  PubMed  Google Scholar 

  30. Musumeci G, Castrogiovanni P, Trovato FM, Weinberg AM, Al-Wasiyah MK, Alqahtani MH, et al. Biomarkers of chondrocyte apoptosis and autophagy in osteoarthritis. Int J Mol Sci. 2015;16(9):20560–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Lotz MK, Carames B. Autophagy and cartilage homeostasis mechanisms in joint health, aging and OA. Nat Rev Rheumatol. 2011;7(10):579–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Cui H, Wu S, Shang Y, Li Z, Chen M, Li F, et al. Pleurotus nebrodensis polysaccharide (PN50G) evokes A549 cell apoptosis by the ROS/AMPK/PI3K/AKT/mTOR pathway to suppress tumor growth. Food Funct. 2016;7(3):1616–27.

    Article  CAS  PubMed  Google Scholar 

  33. Cejka D, Hayer S, Niederreiter B, Sieghart W, Fuereder T, Zwerina J, et al. Mammalian target of rapamycin signaling is crucial for joint destruction in experimental arthritis and is activated in osteoclasts from patients with rheumatoid arthritis. Arthritis Rheum. 2010;62(8):2294–302.

    Article  CAS  PubMed  Google Scholar 

  34. Wu J, Kuang L, Chen C, Yang J, Zeng W-N, Li T, et al. miR-100-5p-abundant exosomes derived from infrapatellar fat pad MSCs protect articular cartilage and ameliorate gait abnormalities via inhibition of mTOR in osteoarthritis. Biomaterials. 2019;206:87–100.

    Article  CAS  PubMed  Google Scholar 

  35. Hwang HS, Kim HA. Chondrocyte apoptosis in the pathogenesis of osteoarthritis. Int J Mol Sci. 2015;16(11):26035–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Zhou S, Lu W, Chen L, Ge Q, Chen D, Xu Z, et al. AMPK deficiency in chondrocytes accelerated the progression of instability-induced and ageing-associated osteoarthritis in adult mice. Sci Rep. 2017;7(1):1–14.

    Google Scholar 

  37. Johnson SC, Rabinovitch PS, Kaeberlein M. mTOR is a key modulator of ageing and age-related disease. Nature. 2013;493(7432):338–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Yan H, Zhou H-f, Hu Y, Pham CT. Suppression of experimental arthritis through AMP-activated protein kinase activation and autophagy modulation. J Rheumatic Dis Treat. 2015;1(1):5.

    Google Scholar 

  39. Wang Y, Xu W, Yan Z, Zhao W, Mi J, Li J, et al. Metformin induces autophagy and G0/G1 phase cell cycle arrest in myeloma by targeting the AMPK/mTORC1 and mTORC2 pathways. J Exp Clin Cancer Res. 2018;37(1):1–12.

    Article  Google Scholar 

  40. Yao F, Zhang M, Chen L. 5'-Monophosphate-activated protein kinase (AMPK) improves autophagic activity in diabetes and diabetic complications. Acta Pharm Sin B. 2016;6(1):20–5.

    Article  PubMed  Google Scholar 

  41. Shi C-S, Shenderov K, Huang N-N, Kabat J, Abu-Asab M, Fitzgerald KA, et al. Activation of autophagy by inflammatory signals limits IL-1β production by targeting ubiquitinated inflammasomes for destruction. Nat Immunol. 2012;13(3):255–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Tchetina EV, Poole AR, Zaitseva EM, Sharapova EP, Kashevarova NG, Taskina EA, et al. Differences in Mammalian target of rapamycin gene expression in the peripheral blood and articular cartilages of osteoarthritic patients and disease activity. Arthritis. 2013;2013:1–14.

  43. Nanki T, Shimaoka T, Hayashida K, Taniguchi K, Yonehara S, Miyasaka N. Pathogenic role of the CXCL16–CXCR6 pathway in rheumatoid arthritis. Arthritis Rheum. 2005;52(10):3004–14.

    Article  CAS  PubMed  Google Scholar 

  44. Ruth JH, Haas CS, Park CC, Amin MA, Martinez RJ, Haines GK III, et al. CXCL16-mediated cell recruitment to rheumatoid arthritis synovial tissue and murine lymph nodes is dependent upon the MAPK pathway. Arthritis Rheum. 2006;54(3):765–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Van Der Voort R, Van Lieshout AW, Toonen LW, Slöetjes AW, Van Den Berg WB, Figdor CG, et al. Elevated CXCL16 expression by synovial macrophages recruits memory T cells into rheumatoid joints. Arthritis Rheum. 2005;52(5):1381–91.

    Article  PubMed  Google Scholar 

  46. Deng L, Chen N, Li Y, Zheng H, Lei Q. CXCR6/CXCL16 functions as a regulator in metastasis and progression of cancer. Biochimica et Biophysica Acta (BBA)-Reviews on. Cancer. 2010;1806(1):42–9.

    CAS  Google Scholar 

  47. Wang J, Lu Y, Wang J, Koch AE, Zhang J, Taichman RS. CXCR6 induces prostate cancer progression by the AKT/mammalian target of rapamycin signaling pathway. Cancer Res. 2008;68(24):10367–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Shoukri B, Prieto J, Ruellas A, Yatabe M, Sugai J, Styner M, et al. Minimally invasive approach for diagnosing TMJ osteoarthritis. J Dent Res. 2019;98(10):1103–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Li C-h, Xu L-l, Zhao J-x, Sun L, Yao Z-q, Deng X-l, et al. CXCL16 upregulates RANKL expression in rheumatoid arthritis synovial fibroblasts through the JAK2/STAT3 and p38/MAPK signaling pathway. Inflamm Res. 2016;65(3):193–202.

    Article  CAS  PubMed  Google Scholar 

  50. Petit SJ, Chayen NE, Pease JE. Site-directed mutagenesis of the chemokine receptor CXCR6 suggests a novel paradigm for interactions with the ligand CXCL16. Eur J Immunol. 2008;38(8):2337–50.

    Article  CAS  PubMed  Google Scholar 

  51. Petit SJ, Wise EL, Chambers JC, Sehmi J, Chayen NE, Kooner JS, et al. The CXCL16 A181V mutation selectively inhibits monocyte adhesion to CXCR6 but is not associated with human coronary heart disease. Arterioscler Thromb Vasc Biol. 2011;31(4):914–20.

    Article  CAS  PubMed  Google Scholar 

  52. Aroda VR, Knowler WC, Crandall JP, Perreault L, Edelstein SL, Jeffries SL, et al. Metformin for diabetes prevention: insights gained from the diabetes prevention program/diabetes prevention program outcomes study. Diabetologia. 2017;60(9):1601–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Novelle MG, Ali A, Diéguez C, Bernier M, de Cabo R. Metformin: a hopeful promise in aging research. Cold Spring Harbor Perspect Med. 2016;6(3):a025932.

    Article  Google Scholar 

  54. Alimoradi N, Firouzabadi N, Fatehi R. Metformin and insulin-resistant related diseases: emphasis on the role of microRNAs. Biomed Pharmacother. 2021;139:111662.

    Article  CAS  PubMed  Google Scholar 

  55. Hassani B, Goshtasbi G, Nooraddini S, Firouzabadi N. Pharmacological approaches to decelerate aging: a promising path. Oxidative Med Cell Longev. 2022;2022:1–25.

  56. Alimoradi N, Firouzabadi N, Fatehi R. How metformin affects various malignancies by means of microRNAs: a brief review. Cancer Cell Int. 2021;21(1):1–13.

    Article  Google Scholar 

  57. Zarkesh K, Entezar-Almahdi E, Ghasemiyeh P, Akbarian M, Bahmani M, Roudaki S, et al. Drug-based therapeutic strategies for COVID-19-infected patients and their challenges. Future Microbiol. 2021;16(18):1415–51.

    Article  CAS  PubMed  Google Scholar 

  58. Dorvash MR, Khoshnood MJ, Saber H, Dehghanian A, Mosaddeghi P, Firouzabadi N. Metformin treatment prevents gallstone formation but mimics porcelain gallbladder in C57Bl/6 mice. Eur J Pharmacol. 2018;833:165–72.

    Article  CAS  PubMed  Google Scholar 

  59. Fatehi R, Rashedinia M, Akbarizadeh AR, Firouzabadi N. Metformin enhances anti-cancer properties of resveratrol in MCF-7 breast cancer cells via induction of apoptosis, autophagy and alteration in cell cycle distribution. Biochem Biophys Res Commun. 2023;644:130–9.

    Article  CAS  PubMed  Google Scholar 

  60. Yue Y, Lian J, Wang T, Luo C, Yuan Y, Qin G, et al. Interleukin-33-nuclear factor-κB-CCL2 signaling pathway promotes progression of esophageal squamous cell carcinoma by directing regulatory T cells. Cancer Sci. 2020;111(3):795.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Li J, Zhang B, Liu W-X, Lu K, Pan H, Wang T, et al. Metformin limits osteoarthritis development and progression through activation of AMPK signalling. Ann Rheum Dis. 2020;79(5):635–45.

    Article  CAS  PubMed  Google Scholar 

  62. Feng X, Pan J, Li J, Zeng C, Qi W, Shao Y, et al. Metformin attenuates cartilage degeneration in an experimental osteoarthritis model by regulating AMPK/mTOR. Aging (Albany NY). 2020;12(2):1087.

    Article  CAS  PubMed  Google Scholar 

  63. Guo H, Ding D, Wang L, Yan J, Ma L, Jin Q. Metformin attenuates osteoclast-mediated abnormal subchondral bone remodeling and alleviates osteoarthritis via AMPK/NF-κB/ERK signaling pathway. PLoS One. 2021;16(12):e0261127.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Xu K, He Y, Moqbel SAA, Zhou X, Wu L, Bao J. SIRT3 ameliorates osteoarthritis via regulating chondrocyte autophagy and apoptosis through the PI3K/Akt/mTOR pathway. Int J Biol Macromol. 2021;175:351–60.

    Article  CAS  PubMed  Google Scholar 

  65. Roos EM, Lohmander LS. The Knee injury and Osteoarthritis Outcome Score (KOOS): from joint injury to osteoarthritis. Health Qual Life Outcomes. 2003;1(1):1–8.

    Article  Google Scholar 

  66. Altman R, Brandt K, Hochberg M, Moskowitz R, Bellamy N, Bloch DA, et al. Design and conduct of clinical trials in patients with osteoarthritis: recommendations from a task force of the Osteoarthritis Research Society: results from a workshop. Osteoarthr Cartil. 1996;4(4):217–43.

    Article  CAS  Google Scholar 

  67. Bellamy N, Kirwan J, Boers M, Brooks P, Strand V, Tugwell P, et al. Recommendations for a core set of outcome measures for future phase III clinical trials in knee, hip, and hand osteoarthritis. Consensus development at OMERACT III. J Rheumatol. 1997;24(4):799–802.

    CAS  PubMed  Google Scholar 

  68. Medzhitov R. Toll-like receptors and innate immunity. Nat Rev Immunol. 2001;1(2):135–45.

    Article  CAS  PubMed  Google Scholar 

  69. MWer S, Dykes D, Polesky H. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. 1988;16(3):1215.

    Article  Google Scholar 

  70. Chen K, Hu Z, Wang L-E, Sturgis EM, El-Naggar AK, Zhang W, et al. Single-nucleotide polymorphisms at the TP53-binding or responsive promoter regions of BAX and BCL2 genes and risk of squamous cell carcinoma of the head and neck. Carcinogenesis. 2007;28(9):2008–12.

    Article  CAS  PubMed  Google Scholar 

  71. Ruan G, Yuan S, Lou A, Mo Y, Qu Y, Guo D, et al. Can metformin relieve tibiofemoral cartilage volume loss and knee symptoms in overweight knee osteoarthritis patients? Study protocol for a randomized, double-blind, and placebo-controlled trial. BMC Musculoskelet Disord. 2022;23(1):1–10.

    Article  CAS  Google Scholar 

  72. Mohammed MM, Al-Shamma KJ, Jassim NA. Evaluation of the clinical use of metformin or pioglitazone in combination with meloxicam in patients with knee osteoarthritis; using knee injury and osteoarthritis outcome score. Iraqi J Pharm Sci. 2014;23(2):13–23 (P-ISSN: 1683-3597, E-ISSN: 2521-3512).

    Google Scholar 

  73. Yan J, Ding D, Feng G, Yang Y, Zhou Y, Ma L, et al. Metformin reduces chondrocyte pyroptosis in an osteoarthritis mouse model by inhibiting NLRP3 inflammasome activation. Exp Ther Med. 2022;23(3):1–10.

    Article  CAS  Google Scholar 

  74. Wang C, Yao Z, Zhang Y, Yang Y, Liu J, Shi Y, et al. Metformin mitigates cartilage degradation by activating AMPK/SIRT1-mediated autophagy in a mouse osteoarthritis model. Front Pharmacol. 2020;11:1114.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Na HS, Kwon JY, Lee S-Y, Lee SH, Lee AR, Woo JS, et al. Metformin attenuates monosodium-iodoacetate-induced osteoarthritis via regulation of pain mediators and the autophagy–lysosomal pathway. Cells. 2021;10(3):681.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Lu C-H, Chung C-H, Lee C-H, Hsieh C-H, Hung Y-J, Lin F-H, et al. Combination COX-2 inhibitor and metformin attenuate rate of joint replacement in osteoarthritis with diabetes: a nationwide, retrospective, matched-cohort study in Taiwan. PLoS One. 2018;13(1):e0191242.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Łabuzek K, Liber S, Suchy D, Okopień B. A successful case of pain management using metformin in a patient with adiposis dolorosa. Int J Clin Pharmacol Ther. 2013;51(6):517–24.

    PubMed  Google Scholar 

  78. Pandey A, Kumar VL. Protective effect of metformin against acute inflammation and oxidative stress in rat. Drug Dev Res. 2016;77(6):278–84.

    Article  CAS  PubMed  Google Scholar 

  79. Ma J, Yu H, Liu J, Chen Y, Wang Q, Xiang L. Metformin attenuates hyperalgesia and allodynia in rats with painful diabetic neuropathy induced by streptozotocin. Eur J Pharmacol. 2015;764:599–606.

    Article  CAS  PubMed  Google Scholar 

  80. Youssef ME, El-Fattah A, Eslam E, Abdelhamid AM, Eissa H, El-Ahwany E, et al. Interference with the AMPKα/mTOR/NLRP3 signaling and the IL-23/IL-17 axis effectively protects against the dextran sulfate sodium intoxication in rats: a new paradigm in empagliflozin and metformin reprofiling for the management of ulcerative colitis. Front Pharmacol. 2021;12:1–16.

  81. Price TJ, Dussor G. AMPK: An emerging target for modification of injury-induced pain plasticity. Neurosci Lett. 2013;557:9–18.

    Article  CAS  PubMed  Google Scholar 

  82. Kiałka M, Doroszewska K, Janeczko M, Milewicz T. Metformin: new potential medicine in pain treatment? Przegl Lek. 2017;74(2):81–3.

  83. Wu H, Ding J, Li S, Lin J, Jiang R, Lin C, et al. Metformin promotes the survival of random-pattern skin flaps by inducing autophagy via the AMPK-mTOR-TFEB signaling pathway. Int J Biol Sci. 2019;15(2):325.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Chatterjee K, De S, Roy SD, Sahu SK, Chakraborty A, Ghatak S, et al. BAX-248 G> A and BCL2-938 C> A variant lowers the survival in patients with nasopharyngeal carcinoma and could be associated with tissue-specific malignancies: a multi-method approach. Asian Pac J Cancer Prev. 2021;22(4):1171.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Al-Koofee DAF, Ismael JM. Genotyping of the BCL2 gene polymorphism rs2279115 shows associations with eukemia tendencies in the Iraqi population. J Pure Appl Microbiol. 2018;12(4):1899–904.

    Article  Google Scholar 

  86. Nückel H, Frey UH, Bau M, Sellmann L, Stanelle J, Dürig J, et al. Association of a novel regulatory polymorphism (− 938C> A) in the BCL2 gene promoter with disease progression and survival in chronic lymphocytic leukemia. Blood. 2007;109(1):290–7.

    Article  PubMed  Google Scholar 

  87. Kourtis A, Adamopoulos PG, Papalois A, Iliopoulos DC, Babis GC, Scorilas A. Quantitative analysis and study of the mRNA expression levels of apoptotic genes BCL2, BAX and BCL2L12 in the articular cartilage of an animal model of osteoarthritis. Ann Transl Med. 2018;6(12):1–12.

  88. Yagi R, McBurney D, Laverty D, Weiner S, Horton WE Jr. Intrajoint comparisons of gene expression patterns in human osteoarthritis suggest a change in chondrocyte phenotype. J Orthop Res. 2005;23(5):1128–38.

    Article  CAS  PubMed  Google Scholar 

  89. Mistry D, Oue Y, Chambers M, Kayser M, Mason R. Chondrocyte death during murine osteoarthritis. Osteoarthr Cartil. 2004;12(2):131–41.

    Article  CAS  Google Scholar 

  90. Ma G, Jiang D, Huang J. Genetic association of the polymorphisms in apoptosis-related genes with osteoarthritis susceptibility in Chinese Han population. Int J Clin Exp Pathol. 2018;11(4):2221.

    PubMed  PubMed Central  Google Scholar 

  91. Singh K, Briggs JM. Functional implications of the spectrum of BCL2 mutations in lymphoma. Mutat Res Rev Mutat Res. 2016;769:1–18.

    Article  CAS  PubMed  Google Scholar 

  92. Pattingre S, Tassa A, Qu X, Garuti R, Liang XH, Mizushima N, et al. Bcl-2 antiapoptotic proteins inhibit Beclin 1-dependent autophagy. Cell. 2005;122(6):927–39.

    Article  CAS  PubMed  Google Scholar 

  93. Kang R, Zeh H, Lotze M, Tang D. The Beclin 1 network regulates autophagy and apoptosis. Cell Death Differ. 2011;18(4):571–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Li Z, Li Q, Lv W, Jiang L, Geng C, Yao X, et al. The interaction of Atg4B and Bcl-2 plays an important role in Cd-induced crosstalk between apoptosis and autophagy through disassociation of Bcl-2-Beclin1 in A549 cells. Free Radic Biol Med. 2019;130:576–91.

    Article  CAS  PubMed  Google Scholar 

  95. Keech C, Albert G, Cho I, Robertson A, Reed P, Neal S, et al. Phase 1–2 trial of a SARS-CoV-2 recombinant spike protein nanoparticle vaccine. N Engl J Med. 2020;383(24):2320–32.

    Article  CAS  PubMed  Google Scholar 

  96. Korbecki J, Bajdak-Rusinek K, Kupnicka P, Kapczuk P, Simińska D, Chlubek D, et al. The role of CXCL16 in the pathogenesis of cancer and other diseases. Int J Mol Sci. 2021;22(7):3490.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Isozaki T, Arbab AS, Haas CS, Amin MA, Arendt MD, Koch AE, et al. Evidence that CXCL16 is a potent mediator of angiogenesis and is involved in endothelial progenitor cell chemotaxis: studies in mice with K/BxN serum–induced arthritis. Arthritis Rheum. 2013;65(7):1736–46.

    Article  CAS  PubMed  Google Scholar 

  98. Costa C, Incio J, Soares R. Angiogenesis and chronic inflammation: cause or consequence? Angiogenesis. 2007;10(3):149–66.

    Article  PubMed  Google Scholar 

  99. Talaie R, Torkian P, Clayton A, Wallace S, Cheung H, Chalian M, et al. Emerging targets for the treatment of osteoarthritis: new investigational methods to identify neo-vessels as possible targets for embolization. Diagnostics. 2022;12(6):1403.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Saito M, Sasho T, Yamaguchi S, Ikegawa N, Akagi R, Muramatsu Y, et al. Angiogenic activity of subchondral bone during the progression of osteoarthritis in a rabbit anterior cruciate ligament transection model. Osteoarthr Cartil. 2012;20(12):1574–82.

    Article  CAS  Google Scholar 

  101. Mapp P, Walsh D, Bowyer J, Maciewicz R. Effects of a metalloproteinase inhibitor on osteochondral angiogenesis, chondropathy and pain behavior in a rat model of osteoarthritis. Osteoarthr Cartil. 2010;18(4):593–600.

    Article  CAS  Google Scholar 

  102. Ashraf S, Walsh DA. Angiogenesis in osteoarthritis. Curr Opin Rheumatol. 2008;20(5):573–80.

    Article  PubMed  Google Scholar 

  103. Mapp PI, Walsh DA. Mechanisms and targets of angiogenesis and nerve growth in osteoarthritis. Nat Rev Rheumatol. 2012;8(7):390–8.

    Article  CAS  PubMed  Google Scholar 

  104. Wang J, Lu Y, Wang J, Koch AE, Zhang J, Taichman RS. CXCR6 induces prostate cancer progression by the AKT/mammalian target of rapamycin signaling pathway. Cancer Res. 2008;68(24):10367–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Feng Y, Ke C, Tang Q, Dong H, Zheng X, Lin W, et al. Metformin promotes autophagy and apoptosis in esophageal squamous cell carcinoma by downregulating Stat3 signaling. Cell Death Dis. 2014;5(2):e1088-e.

    Article  Google Scholar 

  106. Zou M-H, Xie Z. Regulation of interplay between autophagy and apoptosis in the diabetic heart: new role of AMPK. Autophagy. 2013;9(4):624–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. He C, Zhu H, Li H, Zou M-H, Xie Z. Dissociation of Bcl-2–Beclin1 complex by activated AMPK enhances cardiac autophagy and protects against cardiomyocyte apoptosis in diabetes. Diabetes. 2013;62(4):1270–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Russell RC, Tian Y, Yuan H, Park HW, Chang Y-Y, Kim J, et al. ULK1 induces autophagy by phosphorylating Beclin-1 and activating VPS34 lipid kinase. Nat Cell Biol. 2013;15(7):741–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

We would like to acknowledge Shiraz University of Medical sciences for financially supporting this project (Grant NO; 17594).

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Author notes

  1. Nahid Alimoradi and Negar Firouzabadi contributed equally to this work.

Authors and Affiliations

  1. Department of Pharmacology & Toxicology, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran

    Nahid Alimoradi & Negar Firouzabadi

  2. Bone and Joint Disease Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

    Mohammad Tahami

  3. Department of Biostatistics, Medical School, Shiraz University of Medical Sciences, Shiraz, Iran

    Elham Haem

  4. Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Science, Shiraz, Iran

    Amin Ramezani

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  1. Nahid Alimoradi
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Contributions

Nahid Alimoradi: Substantial contribution in the acquisition, analysis and interpretation of data; drafting the manuscript, approval of the submitted version, agreed to be personally accountable for her contributions and has ensured that questions related to the accuracy or integrity of any part of the work, even the ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. Mohammad Tahami: Substantial contribution in the acquisition of data; drafting the manuscript, approval of the submitted version, agreed to be personally accountable for her contributions and has ensured that questions related to the accuracy or integrity of any part of the work, even the ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. Negar Firouzabadi: Substantial contribution in the conception and design of the work, acquisition, analysis and interpretation of data; drafting the manuscript, approval of the submitted version, agreed to be personally accountable for her contributions and has ensured that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. Elham Haem: Substantial contribution in the analysis of data; approval of the submitted version, agreed to be personally accountable for her contributions and has ensured that questions related to the accuracy or integrity of any part of the work, even the ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. Amin Ramezani: Contribution in the interpretation of data; approval of the submitted version, agreed to be personally accountable for her contributions and has ensured that questions related to the accuracy or integrity of any part of the work, even the ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.

Corresponding author

Correspondence to Negar Firouzabadi.

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Ethical approval was obtained from the Research Ethics Committee of Shiraz University of Medical Sciences with the ethical code of IR.SUMS.REC.1398.1010 and the Iranian Registry of Clinical Trials (IRCT) code of IRCT20150202020908N2.

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Prior to the enrolment of participants, written consent was obtained from the subjects or their legal guardians.

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Alimoradi, N., Tahami, M., Firouzabadi, N. et al. Metformin attenuates symptoms of osteoarthritis: role of genetic diversity of Bcl2 and CXCL16 in OA. Arthritis Res Ther 25, 35 (2023). https://doi.org/10.1186/s13075-023-03025-7

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  • DOI: https://doi.org/10.1186/s13075-023-03025-7

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Arthritis Research & Therapy

ISSN: 1478-6362

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