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. 2024 Oct 9;155(2):445–452. doi: 10.1016/j.tjnut.2024.10.013

In Vitro Treatment with Metformin Significantly Reduces Senescent B Cells Present in the Adipose Tissue of People with Obesity

Maria Romero 1, Andrew Gelsomini 1, Kate Miller 1, Dhananjay Suresh 1, Seth Thaller 2, Daniela Frasca 1,3,⁎
PMCID: PMC11867121  PMID: 39389182

Abstract

Background

Our previous work has shown that senescent B cells accumulate in the human adipose tissue (AT) of people with obesity, where they express transcripts for markers associated with the senescence-associated secretory phenotype (SASP) and secrete multiple inflammatory mediators. These functions of AT-derived B cells are metabolically supported.

Objectives

To show that Metformin (MET), a widely used hypoglycemic and antidiabetic drug, is able at least in vitro to decrease frequencies, secretory profile, and metabolic requirements of senescent B cells isolated from the AT of people with obesity.

Methods

We recruited adult females with obesity (n = 8, age 40 ± 2 y, BMI range: 33–42) undergoing breast reduction surgery, who donated their discarded subcutaneous AT. B cells from stromal vascular fractions isolated after collagenase digestion of the AT were evaluated after in vitro incubation with MET (1 mM × 106 B cells) or with a control medium without MET for the following measures: expression of transcripts for SASP-associated markers (p16INK4a and p21CIP1/WAF1) measured by quantitative polymerase chain reaction (qPCR); secretion of inflammatory cytokines (TNF-α, IL-6, IFN-γ and IL-17A) measured by a Cytometric Bead Array); metabolic characteristics as identified by a glycolytic test and Seahorse technology, and by the expression of transcripts for glucose transporters and metabolic enzymes involved in glucose metabolic pathways, measured by qPCR. To examine differences between MET-treated compared with untreated groups, paired Student’s t tests (two-tailed) were employed.

Results

MET in vitro was able to reduce frequencies and numbers of senescent B cells, as identified by staining with β-galactosidase, as well as the secretion of inflammatory cytokines, the expression of transcripts for SASP, and metabolic markers that support intrinsic B cell inflammation.

Conclusions

Our results provide evidence to support the beneficial effects of MET in reducing AT-related inflammation through its effects on senescent B cells.

Keywords: adipose tissue, B cells, inflammation, metabolism, senescence

Introduction

The adipose tissue (AT) undergoes profound changes under conditions associated with overnutrition, becoming the largest organ of the body in individuals with overweight or obesity. Senescent cells accumulate in the AT of people with obesity where they secrete multiple factors that constitute the senescence-associated secretory phenotype (SASP) [1]. The SASP includes soluble inflammatory factors (cytokines, chemokines, and micro-RNAs) and receptors (TNF receptors), nonprotein soluble factors (nitric oxide), growth factors (Epidermal Growth Factor, Vascular Endothelial Growth Factor, and Nerve Growth Factor), and extracellular matrix macromolecules (fibronectin, collagens, and laminin) [2]. The SASP represents the major communication tool between senescent cells and the microenvironment. Senescent cells are characterized by a long-lasting, irreversible arrest of proliferation, known to be induced by cellular stressors like DNA damage and telomere shortening, X-rays, reactive metabolites, mitogenic and metabolic stressors, chronic viral infections, gut dysbiosis, environmental toxicants, and cancer chemotherapeutics with genotoxic and cytotoxic effects [3,4]. Despite experiencing irreversible growth arrest, senescent cells are transcriptionally and metabolically active, and undergo characteristic morphological, transcriptional, epigenetic, and functional changes.

There is no universal marker to identify senescent cells, but p16INK4a and p21CIP1/WAF1 (the cyclin-dependent kinase inhibitors 2A and 1A, respectively) are widely used to identify senescent cells both in vivo and in vitro [5]. Senescent cells can also express senescence-associated β-galactosidase (SA-β-gal) [5], the enzyme that catalyzes the hydrolysis of β-galactosidase into monosaccharides. SA-β-gal detected at pH 6.0 allows the identification of senescent cells in culture and in tissues. Cells that have been shown to undergo senescence and secrete products of the SASP are endothelial and epithelial cells, liver stellate cells [6], and immune cells [[7], [8], [9]].

Our previous work has identified and characterized several mechanisms through which the AT of individuals with obesity induces inflammatory B cells that are autoimmune and pathogenic, as shown in mouse studies [10]. AT-derived B cells secrete autoimmune IgG antibodies with multiple specificities [11], many of which are present in the blood of healthy elderly individuals [12]. The identified pathways in the secretion of autoimmune antibodies include cell death (by hypoxia, cell cytotoxicity, lipolysis, and DNA damage) and release of “self” antigens, which undergo antigen presentation by macrophages or adipocytes to T cells, allowing B cell activation, germinal center formation, and plasma cell differentiation [13]. The amount of autoimmune IgG antibodies present in the blood of individuals with obesity is significantly reduced by weight loss [14].

We have previously shown that senescent B cells accumulate in the AT of individuals with obesity. In the present paper, we have further characterized AT-derived senescent B cells, isolated from the subcutaneous AT of individuals undergoing weight reduction surgeries. We have measured the frequencies and numbers, the secretory profile, and the metabolic requirements of senescent B cells, identified as cells expressing SA-β-gal and transcripts for p16INK4a and p21CIP1/WAF1. We have also evaluated the effects of Metformin (MET), the hypoglycemic and antidiabetic drug, in reducing at least in vitro frequency and numbers of senescent B cells as well as their inflammatory function.

Methods

Subjects

We recruited adult female participants with obesity (n = 8) undergoing body contouring surgery postmassive weight loss (breast reduction) at the Division of Plastic and Reconstructive Surgery at the University of Miami Hospital. The study was done in women as <1% of the recruited participants were males. Study participants donated their discarded subcutaneous AT and provided written informed consent. The study was reviewed and approved by the Institutional Review Board (protocol #20160542), which reviews all human research conducted under the auspices of the University of Miami Miller School of Medicine. All donors were screened for diseases known to alter the immune response such as cancer, chronic infectious diseases, autoimmune, cardiovascular, and renal and hepatic diseases, and were excluded if they had 1 of them. Characteristics of recruited participants are presented in Table 1.

TABLE 1.

Characteristics of recruited participants (n = 8)

Sex Female
Age (years ± SE) 40 ± 2
BMI, mean ± SE (range) 38 ± 2 (33-42)
Ethnicity Hispanic
Race White (n = 4)
African American (n = 4)
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Seven participants out of 8 are taking anti-depression, antihypertension, and antipain drugs, and only 1 participant is not taking medications.

Mean weight loss 1 mo after surgery is 30%.

Isolation of immune cells from the subcutaneous AT

Subcutaneous AT was harvested from surgery patients, weighed, washed with 1× Hanks’ balanced salt solution first and then resuspended in 1× High Dulbecco’s modified Eagle’s Medium (DMEM), supplemented with 15 mM HEPES, 1 mM sodium pyruvate, 100 U/mL Penicillin-Streptomycin, 1% BSA, and 200 nM Adenosine. AT was then minced into small pieces, passed through a 70 μm filter, and digested with collagenase type I (SIGMA C-9263) for 1 h in a 37° C water bath. Digested cells were passed through a 300 μm filter, and centrifuged at 300 × g to separate the nonimmune cells (adipocytes) from the immune cells in the stromal vascular fraction (SVF). SVF was resuspended in ammonium-chloride-potassium for 3 min at room temperature to lyse the erythrocytes and washed with DMEM before use.

Flow cytometry

The SVFs (5 × 105) were stained for 20 min at room temperature with a Live/Dead detection kit (InVitrogen 1878898), anti-CD45 (Biolegend 368540), anti-CD19 (BD 348794), anti-CD27 (BD 555441), and anti-IgD (BD 555778) antibodies to measure naive (IgD+CD27-), IgM memory (IgD+CD27+), switched memory (IgD-CD27+), and DN (IgD-CD27-) B cells. After membrane staining, cells were washed with Flow Cytometry Cell Sorter (FACS) buffer. Then they were stained for an additional 20 min at room temperature with SA-β-gal, using the Cellular Senescence detection kit SPiDER β-Gal (Dojindo Molecular Technologies SG04). Working concentrations were recommended by the manufacturer. In every experiment, we acquired up to 105 events in the B cell gate on an LSR-Fortessa (BD). Analyses of flow data were performed using FlowJo 10.5.3 software. Single color controls were included in every experiment for compensation. Isotype controls were also used in every experiment to set up the gates.

Cytokine secretion

Culture supernatants of SVF-sorted B cells, left unstimulated in culture for 48 h, were collected to measure the secretion of the proinflammatory cytokines TNF-α, IL-6, IFN-γ and IL-17A by BDTM Cytometric Bead Array (CBA) human TH1/TH2/TH17 kit (BD 560484).

B cell sorting

The SVFs were stained with anti-CD45 (Biolegend 368540) and anti-CD19 (BD 555415) antibodies. CD19+ B cells were sorted in a Sony SH800 cell sorter. Cell preparations were typically >95% pure.

In vitro treatment with MET

SVFs or B cells at the concentration of 106 cells/mL were incubated with DMEM without MET (control) or DMEM+MET (1 mM). MET was purchased from EMD Millipore (317240). In vitro concentrations of MET were determined in our preliminary experiments in which we tested 0.1–10 mM/106 cells. The dose of 1 mM of MET was selected because it was the most effective dose in reducing intrinsic inflammation (expression of transcripts for the proinflammatory cytokines TNF-α, IL-6, IL-8) in both blood-derived and SVF-derived B cells, similar to what has been published by other groups [15,16].

RNA extraction and quantitative (q)PCR

SVF-sorted B cells, left unstimulated, were centrifuged, the pellet was resuspended in TRIzol (Ambion) (105 cells/100 μL), and then the RNA was extracted for quantitative (q)PCR. Total RNA was isolated according to the manufacturer’s protocol, eluted into 10 μL distilled water and stored at −80° C until use. RT reactions were performed in a Mastercycler Eppendorf Thermocycler. Briefly, 2 μL of RNA at the concentration of 0.5 μg/μL were used as template for cDNA synthesis in the RT reaction. Conditions were: 40 min at 42° C and 5 min at 65° C. For miRs quantification, RT reactions were performed in the presence of specific primers. The qPCRs were conducted in MicroAmp 96-well plates and run in the ABI 7500 machine. Calculations were made with ABI software. Briefly, we determined the cycle number at which transcripts reached a significant threshold (Ct). A value for the amount of the target gene, relative to Glyceraldehyde 3-phosphate Dehydrogenase (GAPDH), was calculated and expressed as ΔCt. Reagents and primers for qPCR amplification, all from Thermo Fisher, were: GAPDH, Hs99999905_m1; Glut1/SLC2A1, Hs00892681; Glut2/SLC2A2, Hs01096908_m1; Glut3/SLC2A3, Hs00359840_m1; Glut4/SLC2A4, Hs00168966_m1; hexokinase 2 (HK2), Hs00606086_m1; member of the pyruvate dehydrogenase (PDHX), Hs00185790_m1, Hs00892681_m1; acetyl-CoA carboxylase (ACACB), Hs01565914_m1; and lactate dehydrogenase A (LDHA), Hs01378790_g1.

Glycolytic test

SVF-sorted B cells, left unstimulated, were incubated in a Seahorse XF DMEM Medium without glucose. The first injection is 10 mM of glucose (saturating concentration); the second injection is oligomycin (3.5 μM), needed to inhibit mitochondrial ATP production and to shift energy production to glycolysis, with the subsequent increase in extracellular acidification rates (ECAR) revealing the cellular maximum glycolytic capacity; the final injection is 20 mM of 2-deoxy-glucose (2-DG), a glucose analog that inhibits glycolysis through competitive binding to hexokinase, the first enzyme in the glycolytic pathway, with the resulting decrease in ECAR, confirming that the ECAR produced in the experiment is due to glycolysis.

Statistical analyses

To examine differences between groups, paired Student’s t tests (two-tailed) were employed. AUC was employed to compare Seahorse profiles. Analyses were performed using GraphPad Prism version 10.1.0 software, which was used to construct all graphs.

Results

MET decreases SA-β-gal expressing B cells in the AT of people with obesity

We first stained freshly isolated SVFs to identify B cells expressing SA-β-gal, a marker of cell senescence. SVFs were incubated overnight with DMEM without MET (control) or DMEM+MET, then stained for SA-β-gal expression. Figure 1A shows gating strategies. Figure 1B and C show that MET is able to significantly decrease not only the frequencies and numbers of SA-β-gal-positive B cells but also SA-β-gal-specific MFI, as compared with controls incubated with DMEM.

FIGURE 1.

FIGURE 1

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MET decreases SA-β-gal expressing B cells in the AT of people with obesity. SVFs were incubated overnight with DMEM without MET (control) or with DMEM+MET, and then stained for SA-β-gal expression. (A) Gating strategies to identify B cells in the SVFs of AT samples. (B) The SVFs (5 × 105) were stained for 20 min at room temperature with Live/Dead kit, and with anti-CD45/anti-CD19 fluorochrome-conjugated antibodies, followed by staining with SA-β-gal and Bafilomycin A. Negative controls are SVFs stained with Bafilomycin A. Left. Representative histograms from one sample treated with DMEM without MET (control) and one treated with DMEM+MET. Right. Cumulative MFI results of SA-β-gal-positive B cells from all individuals (gated on Live CD45+CD19+ cells). (C) Frequencies (left) and numbers (right) of SA-β-gal-positive B cells from all individuals (gated on Live CD45+CD19+ cells). Mean comparisons between samples treated with DMEM without MET (control) and DMEM+MET were performed by paired Student’s t test (two-tailed). ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001. DMEM, Dulbecco’s modified Eagle’s medium; MET, Metformin; SVF, stromal vascular fraction.

All B cell subsets express SA-β-gal. MET is effective in decreasing the frequencies of SA-β-gal-positive memory B cells and increasing those of naïve B cells. Frequencies of SA-β-gal-positive cells in control compared with MET are: 33 ± 5 compared with 58 ± 7 (naïve, P = 0.0049), 15 ± 3 compared with 6 ± 2 (IgM memory, P = 0.0088), 19 ± 3 compared with 10 ± 2 (switched memory, P = 0.0011), 42 ± 3 compared with 20 ± 4 (DN B cells, P < 0.0001).

MET decreases the expression of SASP transcripts in SVF-sorted B cells as well as secretion of inflammatory cytokines

Next, we sorted B cells from the SVFs to evaluate the effects of MET on the expression of transcripts associated with cell senescence, such as p16INK4a and p21CIP1/WAF1. SVF-sorted B cells were incubated with DMEM without MET (control) or with DMEM+MET overnight (for transcript expression) or for 48 h (for cytokine evaluation in culture supernatants). Figure 2A shows that MET, as expected, is effective in reducing p16INK4a and p21CIP1/WAF1 transcripts to a significant extent. SVF-sorted B cells were also left unstimulated in culture for 48 h, then supernatants collected to evaluate the secretion of the pro-inflammatory cytokines TNF-α, IL-6, IFN-γ and IL-17A by CBA. Figure. 2B shows that MET is also significantly decreasing secretion of these cytokines, as compared with DMEM-treated controls. No effects of MET were observed on the secretion of the other cytokines measured by CBA such as IL-2, IL-4, and IL-10 (data not shown).

FIGURE 2.

FIGURE 2

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MET decreases the expression of transcripts associated with cell senescence in SVF-sorted B cells as well as secretion of inflammatory cytokines. SVF-sorted B cells were incubated with DMEM without MET (control) or with DMEM+MET overnight (for transcript expression) or for 48 h (for cytokine evaluation in culture supernatants). (A) SVF-sorted B cells were resuspended in TRIzol, then the RNA was extracted and the expression of p16INK4a and p21CIP1/WAF1 detected by qPCR. Results show qPCR values, measures of RNA expression of target genes, relative to GAPDH, calculated as 2-ΔCts. (B) SVF-sorted B cells were left unstimulated in culture for 48 h, then supernatants collected to evaluate the secretion of TNF-α, IL-6, IFN-γ, and IL-17A by CBA. Mean comparisons between samples treated with DMEM without MET (control) and DMEM+MET were performed by paired Student’s t test (two-tailed). ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001. DMEM, Dulbecco’s modified Eagle’s medium; MET, Metformin; SVF, stromal vascular fraction.

MET decreases the expression of transcripts for metabolic markers in SVF-sorted B cells

We have previously demonstrated that AT-derived B cells are highly inflammatory and secrete several products associated with the SASP, and this intrinsic B cell inflammation is metabolically supported [8,17,18]. Therefore, we wanted to measure the effects of MET on the expression of transcripts for metabolic markers in SVF-sorted B cells. SVF-sorted B cells were incubated with DMEM without MET (control) or with DMEM+MET overnight. First, we measured the RNA expression of glucose transporters (Glut1, Glut2, Glut3, and Glut4). Figure 3A shows that MET significantly decreases the expression of all Gluts, with more significant effects being observed on Glut1 and Glut4, which are the major Gluts on SVF-sorted B cells, as compared with Glut2 and Glut3. Then, we assessed the effects of MET on the expression of transcripts for enzymes involved in metabolic pathways downstream of glucose, such as HK2, a key glycolytic enzyme that phosphorylates glucose; PDHX, a member of the pyruvate dehydrogenase complex, that converts pyruvate into acetyl CoA, a marker of oxidative phosphorylation (OXPHOS) and a link between glycolysis and the Kreb’s cycle; ACACB, a regulator of fatty acid synthesis; and LDHA, lactate dehydrogenase A, that converts pyruvate into lactate. Figure 3B shows that MET significantly decreases RNA expression of all these metabolic markers. The best effect of MET was observed on LDHA RNA expression.

FIGURE 3.

FIGURE 3

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MET decreases the expression of transcripts for metabolic markers in SVF-sorted B cells. SVF-sorted B cells were incubated with DMEM without MET (control) or with DMEM+MET overnight. Then, SVF-sorted B cells were resuspended in TRIzol, the RNA was extracted and the expression of Glut1/SLC2A1, Glut2/SLC2A2, Glut3/SLC2A3, Glut4/SLC2A4 (A) or of HK-2, PDHX, ACACB, and LDHA (B) was detected by qPCR. Results show qPCR values, measures of RNA expression of target genes, relative to GAPDH, calculated as 2-ΔCts. Mean comparisons between samples treated with DMEM without MET (control) and DMEM+MET were performed by paired Student’s t test (two-tailed). ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001. ACACB, acetyl-CoA carboxylase; DMEM, Dulbecco’s modified Eagle’s medium; LDHA, lactate dehydrogenase A; MET, Metformin; qPCR, quantitative polymerase chain reaction; PDHX, a member of the pyruvate dehydrogenase complex; SVF, stromal vascular fraction.

MET decreases the hyperglycolytic status of SVF-sorted B cells

Because we observed a significant reduction of RNA expression of LDHA, involved in anaerobic glycolysis and lactate secretion, our goal was to evaluate if MET was also able to decrease the glycolytic phenotype of SVF-sorted B cells using Seahorse technology. Briefly, SVF-sorted B cells were incubated with DMEM without MET (control) or with DMEM+MET overnight. Then, cells were loaded into the wells of an extracellular flux analyzer at the concentration of 2 × 105/well and run in a glycolytic test performed with sequential addition of glucose, oligomycin, and 2-DG. Figure 4A shows that MET significantly decreases the glycolytic phenotype of SVF-sorted B cells, as evaluated by calculations of AUC (control compared with MET: 1926 ± 15 compared with 1452 ± 12, P < 0.05), and by a significant decrease of maximal ECAR values Figure 4B.

FIGURE 4.

FIGURE 4

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MET decreases the hyperglycolytic status of SVF-sorted B cells. SVF-sorted B cells were incubated with DMEM without MET (control) or with DMEM+MET overnight. Then, cells were seeded into the wells of an extracellular flux analyzer at the concentration of 2 × 105/well and run in a Seahorse glycolytic test. (A) Results from a representative experiment in which 1 sample of SVF-sorted B cells incubated with DMEM without MET (grey symbols) or DMEM+MET (red symbols) are shown. (B) Maximal ECAR values. Mean comparisons between samples treated with DMEM without MET (control) and DMEM+MET were performed by paired Student’s t test (two-tailed). ∗∗∗∗P < 0.0001. DMEM, Dulbecco’s modified Eagle’s medium; ECAR, extracellular acidification rate; MET, Metformin; SVF, stromal vascular fraction.

Discussion

MET is a hypoglycemic and antidiabetic drug, widely given as first-line medication for patients with type-2 diabetes mellitus (T2DM). MET is a synthetic product of guanidine (dimethyl biguanide), initially isolated from the extracts of a plant with antidiabetic effects (Galega officinalis) [19]. MET is known to influence cellular processes associated with the development of conditions of old age such as inflammaging, oxidative damage, increased glycation of proteins, cell senescence, and apoptosis [[20], [21], [22]]. Although not fully understood, the pleiotropic effects of MET seem to be mediated at least in part by the activation of AMPK [5′-adenosine monophosphate (AMP)-activated protein kinase]. The activation of AMPK via phosphorylation is inhibited in senescent cells [23]. MET-induced activation of AMPK, conversely, prevents the development of a senescent status in different cell types [[23], [24], [25], [26]], supporting its healthspan-promoting and pro-longevity characteristics. We can hypothesize that the observed effects of MET on AT-derived B cells are also linked to AMPK activation.

Our initial work performed on peripheral blood B cells has shown that T2DM patients taking MET have optimal B cell function and humoral immunity to the seasonal influenza vaccine as compared with healthy individuals [27]. In our more recent work, aimed at the identification of mechanisms through which MET improves B cell function, we have shown that MET significantly decreases the frequencies of circulating proinflammatory B cell subsets, as well as their intrinsic inflammation and metabolic requirements [28], which are needed to support the expression of transcripts for SASP markers [8] and the secretion of autoimmune antibodies [13]. Other studies above showing that MET regulates crucial immunopathological pathways involved in systemic autoimmune diseases suggest that it may also have effects on the regulation of pathways that lead to the secretion of pathogenic antibodies in the AT, such as germinal center formation and regulation of the balance TH17/Tregulatory cells.

The effects of MET on human AT-derived immune cells have not been investigated yet. It is known that MET decreases stress-induced senescence in AT stromal cells [29], promotes adipogenesis [30], and increases secretion of adiponectin [31]. The human AT of people with obesity is infiltrated by various types of inflammatory immune cells, recruited from the blood by chemokines released by nonimmune cells (adipocytes) and immune cells, both resident and infiltrating, which together contribute to the establishment and maintenance of a positive inflammatory loop [13]. B cells are among the first immune cell types that infiltrate the human AT of people with obesity. B cells, like other immune cells, are localized in the so-called “crown-like structures” around the adipocytes, where they secrete inflammatory molecules and autoimmune pathogenic antibodies [13,17,18]. When we compared AT-derived B cells from individuals undergoing weight reduction surgeries with blood-derived B cells from age- and gender-matched individuals with obesity, we found increased expression of SASP markers (inflammatory cytokines, chemokines, micro-RNAs, and markers of cell cycle arrest) in AT-derived B cells as compared with those from the peripheral blood, providing the first evidence of the presence of senescent B cells in the human AT from people with obesity [8]. These AT-derived B cells were also engaged in OXPHOS and anaerobic glycolysis, and express higher RNA levels of transcripts for enzymes involved in metabolic pathways as compared with blood-derived B cells, to support increased energetic demands of the senescent program, increased immune activation, secretion of SASP factors that fuel local and systemic inflammation and survival. The release of survival factors like the B cell activating factor by hypertrophic adipocytes present in the AT of people with obesity, also contributes to the survival of B cells in the hostile inflammatory environment of the AT [32].

In agreement with our results on AT-derived B cells, studies in mice have clearly shown that the depletion of systemic [10] or AT [33] B cells, through intra-peritoneal or intra-AT injection with a B cell depleting antibody, significantly improves metabolic and immunological function of the AT, with a reduction in pathogenic B cell numbers and function, as well as increased glucose and insulin tolerance. In addition, consistent with a role for B cells in regulating the AT-derived T cells and macrophages, a significant decrease in the secretion of the proinflammatory cytokines IFN-γ and TNF-α was also observed in the AT of treated mice [10].

In conclusion, our results show the effects of MET on AT-derived B cells with a senescent phenotype. In particular, MET decreases the frequency and number of senescent B cells, the expression of transcripts for SASP markers, and the secretion of inflammatory cytokines. All these features are supported metabolically, with a phenotype mainly associated with anaerobic glycolysis. These results suggest the possibility of targeting AT dysfunctional B cells using MET. Although we believe that the results herein have contributed to expand the knowledge of the effects of MET to another human tissue, providing additional support to the several already existing clinical applications of MET, there are still limitations. For example, we can hypothesize that the observed effects of MET are linked to AMPK activation, but this still needs to be evaluated in mechanistic studies that require large numbers of SVF-sorted B cells, not always available, unfortunately. Another limitation is that our results need to be extended to other immune cell types as well as to other subcutaneous AT depots of the body. We hope that this study will promote more research in the field.

Author contributions

The authors’ responsibilities were as follows – DF: wrote the paper. MR and DF: designed the experiments. MR, AG, KM, DF: performed the experiments, acquire and analyze data. ST: consented patients and provided surgical samples. DF: was involved in funding acquisition. All authors have read and approved the manuscript. MR, AG, KM, DS, ST, and DF: have read and approved the final version.

Funding

This study was supported by NIH award AG059719 (to DF) and by CFAR Emerging Opportunity-FY2022-xx award (to DF).

Data availability

The data and materials that support the findings of this study are available upon request to the corresponding author.

Conflict of interest

The authors report no conflicts of interest.

Acknowledgements

The authors would like to thank the volunteers with obesity who participated in this study donating their discarded adipose tissue, and the nurses and staff of the Ambulatory Surgery. The authors also thank Dr. Bonnie Blomberg for sharing lab space and reagents.

References

  • 1.Tchkonia T., Morbeck D.E., Von Zglinicki T., Van Deursen J., Lustgarten J., Scrable H., et al. Fat tissue, aging, and cellular senescence. Aging Cell. 2010;9(5):667–684. doi: 10.1111/j.1474-9726.2010.00608.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Campisi J. Cellular senescence: putting the paradoxes in perspective. Curr. Opin. Genet. Dev. 2011;21(1):107–112. doi: 10.1016/j.gde.2010.10.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.He S., Sharpless N.E. Senescence in health and disease. Cell. 2017;169(6):1000–1011. doi: 10.1016/j.cell.2017.05.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Huang W., Hickson L.J., Eirin A., Kirkland J.L., Lerman L.O. Cellular senescence: the good, the bad and the unknown. Nat. Rev. Nephrol. 2022;18(10):611–627. doi: 10.1038/s41581-022-00601-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Hernandez-Segura A., Nehme J., Demaria M. Hallmarks of cellular senescence. Trends Cell Biol. 2018;28(6):436–453. doi: 10.1016/j.tcb.2018.02.001. [DOI] [PubMed] [Google Scholar]
  • 6.Coppe J.P., Desprez P.Y., Krtolica A., Campisi J. The senescence-associated secretory phenotype: the dark side of tumor suppression. Annu. Rev. Pathol. 2010;5:99–118. doi: 10.1146/annurev-pathol-121808-102144. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Frasca D., Diaz A., Romero M., Blomberg B.B. Human peripheral late/exhausted memory B cells express a senescent-associated secretory phenotype and preferentially utilize metabolic signaling pathways. Exp. Gerontol. 2017;87(Pt A):113–120. doi: 10.1016/j.exger.2016.12.001. [DOI] [PubMed] [Google Scholar]
  • 8.Frasca D., Romero M., Diaz A., Garcia D., Thaller S., Blomberg B.B. B cells with a senescent-associated secretory phenotype accumulate in the adipose tissue of individuals with obesity. Int. J. Mol. Sci. 2021;22(4):1839. doi: 10.3390/ijms22041839. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Sikora E., Arendt T., Bennett M., Narita M. Impact of cellular senescence signature on ageing research. Ageing Res. Rev. 2011;10(1):146–152. doi: 10.1016/j.arr.2010.10.002. [DOI] [PubMed] [Google Scholar]
  • 10.Winer D.A., Winer S., Shen L., Wadia P.P., Yantha J., Paltser G., et al. B cells promote insulin resistance through modulation of T cells and production of pathogenic IgG antibodies. Nat. Med. 2011;17(5):610–617. doi: 10.1038/nm.2353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Frasca D., Diaz A., Romero M., Garcia D., Jayram D., Thaller S., et al. Identification and characterization of adipose tissue-derived human antibodies with “anti-self” specificity. Front Immunol. 2020;11:392. doi: 10.3389/fimmu.2020.00392. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Frasca D., Romero M., Garcia D., Diaz A., Blomberg B.B. Obesity accelerates age-associated defects in human B cells through a metabolic reprogramming induced by the fatty acid palmitate. Front Aging. 2021;2 doi: 10.3389/fragi.2021.828697. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Frasca D., Diaz A., Romero M., Thaller S., Blomberg B.B. Secretion of autoimmune antibodies in the human subcutaneous adipose tissue. PLOS ONE. 2018;13(5) doi: 10.1371/journal.pone.0197472. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Frasca D., Romero M., Diaz A., Blomberg B.B. Obesity accelerates age defects in B cells, and weight loss improves B cell function. Immun Ageing. 2023;20(1):35. doi: 10.1186/s12979-023-00361-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Hartwig J., Loebel M., Steiner S., Bauer S., Karadeniz Z., Roeger C., et al. Metformin attenuates ROS via FOXO3 activation in immune cells. Front Immunol. 2021;12 doi: 10.3389/fimmu.2021.581799. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Postler T.S., Peng V., Bhatt D.M., Ghosh S. Metformin selectively dampens the acute inflammatory response through an AMPK-dependent mechanism. Sci. Rep. 2021;11(1) doi: 10.1038/s41598-021-97441-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Frasca D., Diaz A., Romero M., Thaller S., Blomberg B.B. Metabolic requirements of human pro-inflammatory B cells in aging and obesity. PLOS ONE. 2019;14(7) doi: 10.1371/journal.pone.0219545. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Frasca D., Garcia D., Diaz A., Romero M., Thaller S., Blomberg B.B. Phenotypic and functional features of B cells from two different human subcutaneous adipose depots. PLOS ONE. 2023;18(4) doi: 10.1371/journal.pone.0285025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Ursini F., Russo E., Pellino G., D'Angelo S., Chiaravalloti A., De Sarro G., Manfredini R., De Giorgio R. Metformin and autoimmunity: a “new deal” of an old drug. Front Immunol. 2018;9:1236. doi: 10.3389/fimmu.2018.01236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Barzilai N., Crandall J.P., Kritchevsky S.B., Espeland M.A. Metformin as a tool to target aging. Cell Metab. 2016;23(6):1060–1065. doi: 10.1016/j.cmet.2016.05.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Chen S., Gan D., Lin S., Zhong Y., Chen M., Zou X., et al. Metformin in aging and aging-related diseases: clinical applications and relevant mechanisms. Theranostics. 2022;12(6):2722–2740. doi: 10.7150/thno.71360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Novelle M.G., Ali A., Dieguez C., Bernier M., de Cabo R. Metformin: a hopeful promise in aging research. Cold Spring Harb. Perspect. Med. 2016;6(3) doi: 10.1101/cshperspect.a025932. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Salminen A., Kaarniranta K. AMP-activated protein kinase (AMPK) controls the aging process via an integrated signaling network. Ageing Res Rev. 2012;11(2):230–241. doi: 10.1016/j.arr.2011.12.005. [DOI] [PubMed] [Google Scholar]
  • 24.Burkewitz K., Zhang Y., Mair W.B. AMPK at the nexus of energetics and aging. Cell Metab. 2014;20(1):10–25. doi: 10.1016/j.cmet.2014.03.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Li L., Zhu Y.Q., Jiang L., Peng W. Increased autophagic activity in senescent human dental pulp cells. Int. Endod. J. 2012;45(12):1074–1079. doi: 10.1111/j.1365-2591.2012.02064.x. [DOI] [PubMed] [Google Scholar]
  • 26.Rastaldo R., Vitale E., Giachino C. Dual role of autophagy in regulation of mesenchymal stem cell senescence. Front Cell Dev. Biol. 2020;8:276. doi: 10.3389/fcell.2020.00276. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Frasca D., Diaz A., Romero M., Mendez N.V., Landin A.M., Ryan J.G., Blomberg B.B. Young and elderly patients with type 2 diabetes have optimal B cell responses to the seasonal influenza vaccine. Vaccine. 2013;31(35):3603–3610. doi: 10.1016/j.vaccine.2013.05.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Frasca D., Diaz A., Romero M., Blomberg B.B. Metformin enhances B cell function and antibody responses of elderly individuals with Type-2 diabetes mellitus. Front Aging. 2021;2 doi: 10.3389/fragi.2021.715981. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Le Pelletier L., Mantecon M., Gorwood J., Auclair M., Foresti R., Motterlini R., et al. Metformin alleviates stress-induced cellular senescence of aging human adipose stromal cells and the ensuing adipocyte dysfunction. Elife. 2021;10 doi: 10.7554/eLife.62635. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Chen D., Wang Y., Wu K., Wang X. Dual effects of metformin on adipogenic differentiation of 3T3-L1 preadipocyte in AMPK-dependent and independent manners. Int. J. Mol. Sci. 2018;19(6):1547. doi: 10.3390/ijms19061547. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Zulian A., Cancello R., Girola A., Gilardini L., Alberti L., Croci M., et al. In vitro and in vivo effects of metformin on human adipose tissue adiponectin. Obes. Facts. 2011;4(1):27–33. doi: 10.1159/000324582. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Muller N., Schulte D.M., Hillebrand S., Turk K., Hampe J., Schafmayer C., et al. B Lymphocyte stimulator (BLyS) is expressed in human adipocytes in vivo and is related to obesity but not to insulin resistance. PLOS ONE. 2014;9(4) doi: 10.1371/journal.pone.0094282. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Camell C.D., Gunther P., Lee A., Goldberg E.L., Spadaro O., Youm Y.H., et al. Aging induces an Nlrp3 inflammasome-dependent expansion of adipose B cells that impairs metabolic homeostasis. Cell Metab. 2019;30(6):1024–10239 e6. doi: 10.1016/j.cmet.2019.10.006. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data and materials that support the findings of this study are available upon request to the corresponding author.

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