# Regulation of immune cell metabolism by therapeutic normal IgG intravenous immunoglobulin

Naresh Rambabu, Fawaz Alzaid, Boban D Andelković, Sruthi Vijaya

Retnakumar, Anupama Karnam, Srinivasa Reddy Bonam, Lucie Orliaguet,

Tina Ejlalmanesh, Dorothy Tonui, Emeline Chu-Van, et al.

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► To cite this version:

Naresh Rambabu, Fawaz Alzaid, Boban D Andelković, Sruthi Vijaya Retnakumar, Anupama Karnam, et al.. Regulation of immune cell metabolism by therapeutic normal IgG intravenous immunoglobulin. Journal of Allergy and Clinical Immunology, 2025, 156, pp.1-15. 10.1016/j.jaci.2025.05.003. anses-05242186

HAL Id: anses-05242186

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# Regulation of immune cell metabolism by therapeutic normal IgG intravenous immunoglobulin

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Naresh Rambabu, PhD, Fawaz Alzaid, PhD, Boban D. Anđelković, PhD, Sruthi Vijaya Retnakumar, PhD, Anupama Karnam, PhD, Srinivasa Reddy Bonam, PhD, et al

## GRAPHICAL ABSTRACT

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Regulation of immune cell metabolism in vitro by intravenous immunoglobulin (IVIG)

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α-KG: Alpha-ketoglutarate, ATP: Adenosine triphosphate, CoA: Coenzyme A, IVIG: Intravenous

immunoglobulin, PBMC: Peripheral blood mononuclear cells, TCA: Tricarboxylic acid

Created with Biorender.com

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**Capsule summary:** Intravenous immunoglobulin and its Fc and $F(ab')_2$ fragments target metabolism of inflammatory mediators-activated PBMCs, alter their overall metabolic landscape, and promote lipogenesis of anti-inflammatory lipids via $F(ab')_2$- and sialylated glycans-dependent mechanisms.
# Regulation of immune cell metabolism by therapeutic normal IgG intravenous immunoglobulin

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Naresh Rambabu, PhD,ª Fawaz Alzaid, PhD,ª,b,c Boban D. Anđelković, PhD,⁴ Sruthi Vijaya Retnakumar, PhD,ª

Anupama Karnam, PhD,ª Srinivasa Reddy Bonam, PhD,ª Lucie Orliaguet, MSc,ª Tina Ejlalmanesh, PhD,ª

Dorothy Tonui, MSc,ᵇ Emeline Chu-Van, BSc,ᵉ Ludovic Brunet, MSc,ᵉ Nina Bozinovic, PhD,ª Ivan Nemazanyy, PhD,ᵇ

Fabian Käsermann, PhD,⁹ Nicolas Venteclef, PhD,ª,b Srini V. Kaveri, DVM, PhD,ª Thibaut Léger, PhD,ʰ

François Fenaille, PhD,ᵉ Benoit Colsch, PhD,ᵉ and Jagadeesh Bayry, DVM, PhDª,i

Paris, Gif-Sur-Yvette, and Fougères,

France; Kuwait City, Kuwait; Belgrade, Serbia; Bern, Switzerland; and Palakkad, India

**Background:** Immune cell metabolism and metabolic end products influence the nature and magnitude of immune responses. Various autoimmune and inflammatory diseases are associated with dysregulated cellular metabolism. Intravenous immunoglobulin (IVIG), a therapeutic pooled normal IgG, is extensively used for the immunotherapy of a wide range of autoimmune and inflammatory diseases. Although several cellular and molecular mechanisms of action of IVIG have been reported, the role of IVIG in modulating the immune cell metabolism remains unknown.

**Objective:** We sought to investigate the influence of IVIG on the metabolic events of human immune cells.

**Methods:** We performed metabolic flux analyses on inflammatory mediators-stimulated human PBMCs.

Furthermore, intracellular metabolites were extracted from activated PBMCs and subjected to liquid chromatography coupled to high-resolution mass spectrometry. Untargeted global metabolic profiling of PBMCs was performed to determine the metabolic landscape of immune cells and metabolic reprogramming by IVIG. Untargeted lipidomics was used for the mechanistic studies on IVIG-induced lipogenesis.

**Results:** IVIG and its Fc and F(ab')₂ fragments regulate the Warburg effect in activated PBMCs depending on the glucose availability. Untargeted global metabolic profiling revealed that IVIG alters the overall metabolic landscape of inflammatory mediators-stimulated PBMCs, blocks prenylation of amino acid cysteine, and promotes lipogenesis of well-known anti-inflammatory lipids such as diacylglycerol and triacylglycerol by shuttling acetyl coenzyme A away from the mevalonate pathway. Mechanistically, IVIG-induced lipogenesis was mediated via F(ab')₂ fragments and was dependent on the sialylated glycans of IgG.

**Conclusions:** Our data indicate that IVIG targets immune cell metabolism and also highlight a novel mechanism of action of IVIG in the context of immunotherapy of autoimmune and inflammatory diseases. (J Allergy Clin Immunol 2025;156:418-32.)

**Key words:** IVIG, metabolism, lipogenesis, PBMC, diacylglycerol, triacylglycerol, Warburg effect, acetyl-CoA, metabolic flux, fatty acid synthesis

On activation, innate immune cells favor the generation of nicotinamide adenine dinucleotide phosphate via pentose phosphate pathway (PPP) and malate-aspartate shuttle by enhancing glycolysis and glutaminolysis.¹ Adaptive immune cells receiving activation signals favor nucleotide synthesis and lipogenesis by shunting glucose to PPP and by replenishing tricarboxylic acid (TCA) cycle intermediates.²,³ Different subsets of T helper cells have distinct metabolic demands. T<sub>H1</sub> and T<sub>H17</sub> subsets rely on fatty acid synthesis, whereas regulatory T (Treg) cells rely on fatty acid oxidation.⁴ Thus, immune cells have discrete demands for diverse metabolic pathways, which fuel the biomolecules required for their function. Dysregulated metabolism, which refers to an abnormal or impaired regulation of metabolic processes, promotes inflammatory phenotypes in immune cells. This is a characteristic feature of several autoimmune diseases such as diabetes, rheumatoid arthritis, multiple sclerosis, and lupus.⁵⁻⁹ Therefore, metabolic pathways have emerged as potential therapeutic targets to block autoimmune and inflammatory responses.¹⁰

Intravenous immunoglobulin (IVIG), a therapeutic normal IgG prepared from the pooled plasma of several thousand healthy donors, is used in the immunotherapy of a wide range of autoimmune and inflammatory diseases.¹¹⁻¹³ IVIG exerts its

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<footnote>From: ⁴Institut National de la Santé et de la Recherche Médicale, Centre de Recherche des Cordeliers, Sorbonne Université, Université Paris Cité, Paris; ⁵Institut Necker Enfants Malades (INEM), Institut National de la Santé et de la Recherche Médicale (INSERM) U1151/CNRS UMR8253, Immunity and Metabolism of Diabetes (IMMEDIAB), Université Paris Cité, Paris; ⁶Dasman Diabetes Institute, Kuwait City; ⁷the Faculty of Chemistry, University of Belgrade, Belgrade; ⁸Université Paris Saclay, CEA, INRAE, Médicaments et Technologie pour la Santé (MTS), LI-MS, MetaboHUB, Gif-Sur-Yvette; ⁹Platform for Metabolic Analyses, Structure Fédérative de Recherche Necker, INSERM US24/CNRS UAR 3633, Paris; ¹⁰CSL Behring, CSL Biologics Research Center (sitem-insel), Bern; ¹¹ANSES, Toxicology of Contaminants Unit, Fougères; and ¹²the Department of Biological Sciences & Engineering, Indian Institute of Technology Palakkad, Palakkad, Kerala.</footnote>

<footnote>Received for publication December 2, 2024; revised May 3, 2025; accepted for publication May 8, 2025.</footnote>

<footnote>Available online May 16, 2025.</footnote>

<footnote>Corresponding author: Jagadeesh Bayry, DVM, PhD, Institut National de la Santé et de la Recherche Médicale, Centre de Recherche des Cordeliers, Sorbonne Université, Université Paris Cité, 15 rue de l'Ecole de Médecine, Paris F-75006, France. E-mail: jagadeesh.bayry@crc.jussieu.fr. Or: bayry@iitpkd.ac.in.</footnote>

<footnote>The CrossMark symbol notifies online readers when updates have been made to the article such as errata or minor corrections</footnote>

<footnote>0091-6749</footnote>

<footnote>© 2025 The Authors. Published by Elsevier Inc. on behalf of the American Academy of Allergy, Asthma & Immunology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).</footnote>

<footnote>https://doi.org/10.1016/j.jaci.2025.05.003</footnote>
Abbreviations used

acetyl-CoA: Acetyl coenzyme A
AGC: Automatic gain control
AUC: Area under the curve
DAG: Diacylglycerol
DC: Dendritic cell
ECAR: Extracellular acidification rate
FA: Fatty acid
FcγR: Fc-gamma receptor
HCD: High collision-induced dissociation
HSA: Human serum albumin
IVIG: Intravenous immunoglobulin
mTOR: Mammalian target of rapamycin
OCR: Oxygen consumption rate
PC: Phosphatidylcholine
PCA: Principal-component analysis
PE: Phosphatidylethanolamine
PGE₂: Prostaglandin E₂
PPP: Pentose phosphate pathway
PS: Phosphatidylserine
QC: Quality control
SM: Sphingomyelin
TAG: Triacylglycerol
TCA: Tricarboxylic acid
TLR: Toll-like receptor

immunoregulatory effects through several mutually nonexclusive mechanisms. On the basis of the studies in patients, and *in vitro* and *in vivo* models, various mechanisms of action of IVIG have been identified. IVIG was reported to promote catabolism of autoantibodies, block activating Fc-gamma receptors (FcγRs), upregulate inhibitory FcγRIIB on macrophages, interfere with the complement and cytokine network, induce autophagy of target cells, block costimulatory molecules, neutralize pathogenic antibodies, and modulate the activation and functions of dendritic cells (DCs), macrophages, granulocytes, natural killer cells, T cells, and B cells.<sup>14-31</sup>

Although several cellular signaling pathways and molecular mechanisms of action of IVIG have been investigated, the role of IVIG in regulating the metabolism of immune cells has not been explored. In view of direct influence of metabolic activity of immune cells and their products toward quality and intensity of immune response, we aimed to investigate whether IVIG regulates the metabolism of immune cells. Our data demonstrate that IVIG promotes lipogenesis of well-known anti-inflammatory lipids by shuttling acetyl coenzyme A (acetyl-CoA) away from the mevalonate pathway. These data reveal that IVIG targets immune cell metabolism and also highlight a novel mechanism of action of IVIG in the context of immunotherapy of autoimmune diseases.

# METHODS

## Cell culture and sample preparation

PBMCs were isolated from the buffy bags of healthy donors purchased from L'Établissement Français du Sang (Centre Necker-Cabanel, Établissement Français du Sang (EFS), Paris, France; EFS-INSERM ethical committee permission no. 15/EFS/012; 18/EFS/033) using Ficoll density gradient (GE Healthcare Life Sciences, Buc, France) centrifugation. PBMCs were cultured in serum-free RPMI 1640 (Lonza, Colmar, France) at a

seeding density of $1 \times 10^6$ cells/mL. PBMCs were stimulated with inflammatory cytokine cocktail (10 ng/mL of IL-1β, TNF-α, and IL-6; all from Immuno Tools, Friesoythe, Germany) and $1 \mu g/mL$ of prostaglandin E₂ (PGE₂) (Merck, Fontenay/Sous Bois, France). After 30 minutes of stimulation with inflammatory mediators at 37°C in 5% CO₂, 25 mg/mL of IVIG (Sandoglobulin; CSL Behring, Bern, Switzerland) was added to the cells and cultures were maintained for 24 hours. We chose 24 hours to capture cumulative effects of the metabolic events regulated in PBMCs by IVIG. This time point also reflects what has been optimized in functional and molecular assays demonstrating the immune functions of IVIG. The IVIG used in the experiments has a titer of 4 for anti-A and 2 for anti-B isoagglutinins. IVIG was dialyzed before the use. The equimolar concentration of human serum albumin (HSA) (11.08 mg/mL; Laboratoire Française de Biotechnologies, Les Ulis, France) was used as an irrelevant protein control for IVIG. $F(ab')_2$ fragments of IVIG were generated as described earlier by digesting IVIG with pepsin, and the purity of the $F(ab')_2$ fragments was confirmed.<sup>15</sup> Fc fragments of IVIG were obtained from Dr M. C. Bonnet (Institut Mérieux, Lyon, France). IgG was desialylated by treating IVIG with recombinant neuraminidase as detailed earlier.<sup>32</sup> Desialylation of IgG was confirmed by lectin blotting and RP-HPLC.<sup>33</sup>

## Bioenergetic analysis

Extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) were measured using the Seahorse XF24 or XFe96 extracellular flux analyzer (Agilent Technologies, Calif). The Seahorse cell culture microplates were pretreated with $3.5 \mu g/cm^2$ of Cell-Tak (Corning, Amsterdam, Netherlands) for 20 minutes, washed with distilled water, and air-dried in a class II biosafety cabinet. Pretreated PBMCs were seeded in XF24 or XFe96 cell culture microplates at a density of $2 \times 10^6$ or $5 \times 10^5$ cells/well, respectively. Pretreated PBMCs were washed with XF base medium (Agilent Technologies, Santa Clara, Calif) or PBS to remove the residual nutrients, inflammatory mediators, HSA, or IVIG before analysis and incubated in the Seahorse XF base medium supplemented with either 2 mM L-glutamine, 10 mM glucose, and 1 mM sodium pyruvate for mitochondrial stress test or only 2 mM L-glutamine for glycolysis stress test for 1 hour at 37°C in a non-CO₂ incubator. ECAR and OCR were measured 3 times under basal conditions and in response to injections of either glucose (500 mM), oligomycin (25 µM), and 2-deoxy-D-glucose (500 mM) for the glycolysis stress test or oligomycin (25 µM), carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone (25 µM), and rotenone/antimycin A (25 µM) for the mitochondrial stress test. The metabolic flux data were analyzed using Seahorse Wave software (Agilent Technologies).

## Metabolite isolation for untargeted metabolomics

Following culturing of PBMCs under various conditions for 24 hours, the cells were washed with 50 mL of serum-free RPMI 1640 once to remove residual HSA and IVIG present in the supernatant, and the PBMC pellet was reconstituted in 10 mL of serum-free RPMI. The PBMCs were then quenched with 40 mL of quenching solution (60% methanol supplemented with 0.85% wt/vol ammonium bicarbonate at pH 7.4) at -40°C to arrest metabolism and centrifuged at 1000g for 1 minute at -20°C.
Metabolites were then extracted from the quenched cells using 2
100% methanol extractions followed by a single water extrac-
tion. ³⁴ The metabolites were concentrated using vacuum centrifu-
gation at 30°C followed by lyophilization.

Lipid isolation for untargeted lipidomics

For each experimental condition, 4 × 10⁶ cells were used. After incubation, cells were washed 3 times with cold PBS and once with cold H₂O. Final cell pellets were stored at -80°C and then used for lipid extraction. Samples were resuspended in 300 µL of ultrapure water and then sonicated 5 times for 10 seconds using a sonication probe (Vibra Cell; Bioblock Scientific, Illkirch, France). At this step, 20 µL of each sample was withdrawn for the determination of the total protein concentration (Pierce BCA Protein Assay Kit; Thermo Fisher Scientific, Illkirch-Graffenstaden, France).

Lipid extraction of the remaining 280 µL was performed according to a previously described method.³⁵ Briefly, in addition to 5 µL of internal standards, volumes of CHCl₃/MeOH (2:1 [vol/vol]) were added to the samples to reach a protein concentration of 3.5 µg/µL. Samples were vortexed for 60 seconds, sonicated for 30 seconds using an ultrasonic probe (Bioblock Scientific Vibra Cell VC 75185; Thermo Fisher Scientific, Waltham, Mass), and incubated for 2 hours at 4°C with mixing. According to volumes of CHCl₃/MeOH (2:1 [vol/vol]), H₂O was then added and samples were vortexed for 60 seconds before centrifugation at 15,000g for 15 minutes at 4°C. The upper phase (aqueous phase), containing gangliosides, lysoglycerophospholipids, and short-chain glycerophospholipids, was transferred into a glass tube and dried under a stream of nitrogen. The protein interphase was discarded, and the lower lipid-rich phase (organic phase) was pooled with the dried upper phase and the mixture dried under nitrogen. All samples were resuspended in the same initial volume of CHCl₃/MeOH (2:1 [vol/vol]), and 40 µL of each extract was 5-fold diluted in a solution of MeOH/isopropanol/H₂O (65:35:5 [vol/vol/vol]) before injection. A quality control (QC) sample was obtained by pooling 20 µL of each sample preparation. The QC sample was injected every 10 samples to evaluate signal variations of lipid species.

Mass spectrometry: Data acquisition for untargeted
metabolomics

The lyophilized metabolites were reconstituted with 40 µL of HPLC-grade water supplemented with 0.1% formic acid. The samples were then concentrated using vacuum centrifugation and reconstituted with 20 µL of acetonitrile supplemented with 0.1% formic acid (mobile phase). The samples were desalted using ZipTip µ-C18 Pipette Tips (Thermo Fisher Scientific) and transferred into the loading chamber of Orbitrap Fusion Tribrid coupled to a Nano-LC Proxeon 1000, equipped with an easy spray ion source (Thermo Fisher Scientific). Metabolites were separated by liquid chromatography with the following parameters: Acclaim PepMap100 C18 precolumn (2 cm bed length, 75 µm internal diameter [i.d.], 3 µm particle size, 100 Angstrom [A] pore size), Pepmap-RSLC Proxeon C18 column (75 cm, 75 µm i.d., 2 µm, 100 Å), and 300 nL/min flow rate, using a gradient starting from 95% solvent A (water and 0.1% formic acid) to 5% solvent B (80% acetonitrile and 0.1% formic acid) and then rising to 95% solvent B for 115 minutes followed by 95% solvent A and 95% solvent B for 5 minutes for a total of 120 minutes.

Metabolites were analyzed in the Orbitrap cell, in full ion scan mode, at a resolution of 120,000 (at m/z 200), with a mass/charge range of 150 to 1350 Da and an automatic gain control (AGC) target of $4 \times 10^5$, alternatively in positive and negative modes in the same run. A higher voltage for positive ionization (2100 V) and a slightly lower voltage for negative ionization (1900 V) were applied and the ion transfer tube temperature was maintained at 250°C. Fragments were obtained by high collision-induced dissociation (HCD) activation with a collisional energy of 28% and a quadrupole isolation window of 1.6 Da. MS/MS data were acquired in the Orbitrap cell in the top-speed mode, with a total cycle of 3 seconds at a resolution of 15,000, an AGC target of $1 \times 10^4$, and a dynamic exclusion of 60 seconds. Precursor priority was dedicated to most intense ions. Metabolites with charge states from 1 to 8 were selected for MS/MS acquisition. The maximum ion accumulation times were set to 100 ms for MS acquisition and 50 ms for MS/MS acquisition in parallelization mode.

Mass spectrometry: Data acquisition for untargeted
lipidomics

Lipidomic profiles were determined using an UltiMate 3000 liquid chromatography system (Thermo Fisher Scientific, San Jose, Calif) coupled to a high-resolution Tribrid Orbitrap Fusion spectrometer (Thermo Fisher Scientific), equipped with an electrospray ionization (ESI). Chromatographic separation was performed on a Phenomenex Kinetex C8 column (150 × 2.1 mm; 2.6 µm) at 0.4 mL/min (at 60°C) using an injection volume of 10 µL. Mobile phases A and B were H₂O/MeOH (60:40 [vol/vol]), containing 0.1% formic acid, and isopropanol/MeOH (90:10 [vol/vol]), containing 0.1% formic acid in the negative ionization mode, respectively. Ammonium formate (10 mM) was added to both mobile phases in the positive ionization mode to detect glycerolipids, cardiolipins, and cholesteryl-esters as [M + NH₄]⁺ adducts. The gradient program was as follows: solvent B was maintained for 2.5 minutes at 32%; from 2.5 to 3.5 minutes it was increased to 45%, and then from 3.5 to 5 minutes to 52%, from 5 to 7 minutes to 58%, from 7 to 10 minutes to 66%, from 10 to 12 minutes to 70%, from 12 to 15 minutes to 75%, from 15 to 19 minutes to 80%, from 19 to 22 minutes to 85%, and from 22 to 23 minutes to 95%; from 23 to 25 minutes, solvent B was maintained at 95%; and from 25 to 26 minutes, solvent B was decreased to 32% and then maintained for 4 minutes for column reequilibration. The mass resolving power of the mass spectrometer was 240,000 FWHM (at m/z 200) for MS experiments. Samples were analyzed in both positive and negative ionization modes. The ESI source parameters were as follows: the spray voltage was set to 3.7 and -3.2 kV in the positive and negative ionization modes, respectively. The heated capillary was kept at 360°C, and the sheath and auxiliary gas flow were set to 50 and 15 arbitrary units, respectively. Mass spectra were recorded in full-scan MS mode from m/z 50 to m/z 2000. After liquid chromatography coupled to high-resolution mass spectrometry analysis of samples and annotation of features, QC samples were rejected for HCD MS/MS experiments in positive and negative ion modes on the same instrument set in targeted mode using inclusion lists. The isolation width was set at 0.8 Da, the stepped normalized collision energy was set at 20% ± 10%, and the mass resolution was set at 17,500 FWHM at m/z 200. HCD mass spectra were inspected manually to confirm annotations.
Mass spectrometry: Data analysis for untargeted
metabolomics

The raw data were converted to Analysis Base File format using the Reifycs Abf converter (Reifycs, Tokyo, Japan). Data processing was performed using MS-DIAL software version 3.90 (RIKEN Center for Sustainable Resource Science, Yokohama, Japan; National Institute of Genetics, Mishima, Japan; University of California Davis, Calif).³⁶ During the preliminary investigation, we encountered chromatograms exhibiting nonlinear shift in retention time across treatment conditions as well as across different donors. This could stem from several factors, such as changes in the overall metabolism of the cells with treatment conditions, variation in cellular metabolism across different donors, changes in the quality of liquid chromatography column over time, and use of AGC to maintain constant ion flow during data acquisition. We therefore optimized the parameters and performed data analysis to compensate for the shift in retention time.

Extracted ion chromatograms were constructed with mass
tolerance of 0.01 and 0.05 Da for MS1 and MS2 spectra,
respectively. Peak detection was performed using the linear
weighted moving average algorithm with smoothing level of 3
scans and minimum peak width of 5 scans. MS2 deconvolution
was performed with a sigma window value of 0.5, using the MS-
DIAL's in-built MS2Dec algorithm. Metabolites were identified
using a manually curated spectral library from Riken Research
Institute. Although the spectral library consists of 29,269 curated
records, it was not possible to annotate most of the metabolites
that exhibited significant fold changes across treatment condi-
tions because of the limited coverage of the spectral libraries. To
overcome this limitation, we used MS-FINDER software version
3.24 (RIKEN Center for Sustainable Resource Science, Yoko-
hama, Japan; National Institute of Genetics, Mishima, Japan;
University of California Davis, Calif)³⁷ to perform formula pre-
diction, fragment annotation, and structural elucidation of metab-
olites using public spectral databases. The principal-component
analysis (PCA) was performed to visualize the metabolic distance
and relatedness across different treatment conditions.

Mass spectrometry: Data analysis for untargeted
lipidomics

The raw data files were converted to the mzXML format with the ProteoWizard software (ProteoWizard, Palo Alto, Calif).³⁸ Mass spectra were processed using the xcms R package (Scripps Research, San Diego, Calif) deployed in the Work-flow4Metabolomics Galaxy platform (Institut Français de Bio-informatique,Villejuif, France and Infrastructure Nationale en Métabolomique et Fluxomique, Toulouse, France).³⁹ Features were annotated using an in-house database on the basis of accu- rate measured masses and several filtration steps such as reten- tion time windows depending on lipid classes and relative isotopic abundance of lipid species to limit false annotations.³⁵

Statistical analysis

As detailed in the figures, each experiment was repeated
independently 4 to 5 times using different donors and sample
size was chosen on the basis of literature survey. We did not use
any specific test to ensure adequate power. The data were
presented as mean ± SEM, unless otherwise specified. Random-
ization and blinding were used while acquiring the data in mass

spectrometry. Statistical analyses were performed by a 1-way
ANOVA and the Tukey multiple comparison test or a 2-tailed
paired t test (as indicated in the figure legends) using Prism 8 soft-
ware (GraphPad, Boston, Mass). Values were denoted as statisti-
cally significant as follows: *P* < .05; **P** < .01; ***P* < .001.

RESULTS

Inflammatory mediators induce the Warburg effect
in PBMCs

In PBMCs, during quiescence, glucose undergoes complete oxidation. On activation, PBMCs exhibit a metabolic shift by enhancing glycolysis in the presence of oxygen, wherein glucose is converted to lactate,¹ a phenomenon known as the Warburg effect.⁴⁰ Because enhanced production of proinflammatory mediators is one of the hallmarks of autoimmune and inflammatory diseases, we first investigated whether a cocktail of proinflammatory cytokines (IL-1β, TNF-α, and IL-6) and PGE₂ induce the Warburg effect in PBMCs. The cocktail of inflammatory mediators and their concentrations were adapted from the previous clinical trial studies.⁴¹⁻⁴⁵

We evaluated glycolytic flux and mitochondrial respiration by measuring ECAR and OCR, respectively. This was done under conditions that favor either glycolysis or mitochondrial respiration. Glycolytic flux analysis revealed that cytokine stimulation significantly increased the ECAR of PBMCs compared with unstimulated PBMCs (Fig 1, A). Analysis of mitochondrial respiration showed that cytokine stimulation decreased the maximal OCR of PBMCs (P = .06) compared with unstimulated PBMCs (Fig 1, B). Glycolytic function measured by changes in the OCR also indicated decreased OCR of cytokine-stimulated PBMCs (see Fig E1, A, in this article's Online Repository at www.jacionline.org). These data imply that the cocktail of proinflammatory cytokines and PGE₂ induce the Warburg effect by enhancing glycolysis in the presence of oxygen.

IVIG regulates the Warburg effect depending on
glucose availability

To investigate whether IVIG exerts immune regulation on immune cells by reversing the Warburg effect or modulating cellular respiration, we treated inflammatory mediators-activated PBMCs with 25 mg/mL IVIG (equivalent of IgG concentration reached in the blood of autoimmune patients immediately following IVIG therapy) or equimolar concentration of HSA, used as a protein control. To avoid potential neutralization of inflammatory cytokines because of anticytokine autoantibodies that are known to be present in IVIG, we pretreated PBMCs with proinflammatory cytokines for 30 minutes to allow cytokine-mediated signaling to occur in the immune cells before exposing them to IVIG. Treatment of inflammatory mediators-stimulated PBMCs with IVIG resulted in significantly decreased glycolytic flux relative to HSA-treated PBMCs under conditions that privilege glycolysis (Fig 1, A). Under the experimental conditions that drive cells toward mitochondrial respiration, IVIG-treated PBMCs showed decreased glycolytic flux (Fig E1, B) and reduced basal mitochondrial respiration (P = .08) relative to HSA-treated PBMCs (Fig E1, C). The reduction in OCR is not due to either defect in the mitochondrial function or reduced mitochondrial membrane integrity, because the total ATP production and the proton leak respectively across different treatment conditions remain intact (Fig E1, D and E). Calculation of area under the
<figure><img src="image_9.png" /><figcaption>**FIG 1.** Activation of PBMCs by proinflammatory mediators induces the Warburg effect. PBMCs activated in the absence of antigenic stimuli exhibit metabolic transition toward glycolysis. PBMCs were stimulated with a cocktail of inflammatory cytokines and PGE₂. After 30 minutes of stimulation with inflammatory mediators, 25 mg/mL of IVIG or equimolar concentration of HSA was added to the PBMCs for 24 hours. A, Glycolytic function is measured by changes in the ECAR following sequential injection of glucose (Glu), oligomycin (Oligo), and 2-deoxy-D-glucose (2-DG). B, Mitochondrial maximal respiration is measured as a function of OCR following FCCP injection, but before R&A injection. Glycolytic and mitochondrial respiration functions in untreated (CA) and inflammatory mediators (CC)-activated PBMCs and in HSA (CC + HSA)- and IVIG (CC + IVIG)-treated activated PBMCs are presented (mean ± SEM; 4 independent donors performed in duplicates). FCCP, Carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone; R&A, rotenone and antimycin. \*P < .05; \*\*\*P < .001 (2-tailed paired t test).</figcaption></figure>

curve (AUC) from glycolytic flux analysis confirmed an increase in the glycolytic flux following activation of PBMCs with inflammatory mediators (Fig 2, A). The measure of AUC of glycolytic flux also showed that IVIG-treated PBMCs display lower ECAR compared with HSA-treated and inflammatory mediators-stimulated PBMCs (Fig 2, A).

Furthermore, analyses of bioenergetic profiles following the addition of glucose revealed that OCR and ECAR, the parameters of mitochondrial and glycolytic metabolism, respectively, were upregulated in activated PBMCs as well as HSA-treated cells compared with IVIG-treated and unstimulated cells (Fig 2, B). Measurement of AUCs under the conditions favoring mitochondrial respiration confirmed reduction in OCR in activated PBMCs compared with unstimulated quiescent PBMCs. However, OCR was not significantly different between HSA- and IVIG-treated cells (Fig 2, A), suggesting that depending on the glucose availability, IVIG differentially regulates metabolic pathways, in particular oxidative respiration, in immune cells.

IgG consists of an F(ab')₂ fragment, a dimeric antigen-binding fragment responsible for antigen recognition, and an Fc fragment, which is crucial for exerting effector functions by binding to FcγRs.⁴⁶ Both of these domains have been suggested to contribute

to the anti-inflammatory and immunomodulatory activities of IVIG.²⁵ We investigated whether IVIG-induced metabolic changes in PBMCs are dependent on F(ab')₂ or Fc fragments. Evaluation of glycolytic flux revealed that both F(ab')₂ and Fc fragments decrease the ECAR of cytokine-stimulated PBMCs (Fig 2, C). Similar observations were also made under the experimental conditions that drive PBMCs toward mitochondrial respiration wherein PBMCs treated with F(ab')₂ and Fc fragments decreased basal mitochondrial respiration relative to cytokine-stimulated PBMCs (Fig 2, D). Calculation of AUC and analyses of bioenergetic profiles further confirmed these observations (Fig 2, E and F).

## IVIG alters the overall metabolic landscape of human PBMCs

Next, to assess the intermediate metabolites, we performed untargeted global metabolic profiling of human PBMCs under different treatment conditions to determine the metabolic landscape of immune cells and metabolic reprogramming by IVIG.

PBMCs from 5 healthy donors were exposed to inflammatory cytokines (IL-1β, TNF-α, and IL-6) and PGE₂ for 24 hours. IVIG or HSA was added to the cells following 30 minutes of stimulation.
A

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

B

<figure><img src="image_12.png" /></figure>

C

<figure><img src="image_13.png" /></figure>

D

<figure><img src="image_14.png" /></figure>

E

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

F

<figure><img src="image_17.png" /></figure>

FIG 2. IVIG regulates the Warburg effect depending on glucose availability by F(ab')₂⁻ and Fc-dependent mechanisms. A, Measure of AUC of glycolytic and mitochondrial respiration functions and corresponding changes in ECAR and OCR during gly costress and mitostress assays in quiescent (CA) or activated (CC) PBMCs treated with either IVIG or HSA. Data are presented as mean, SEM, and lower and upper 95% CI (4 independent donors performed in duplicates). B, Energy profile (mean ± SEM; 4 independent donors performed in duplicates) of PBMCs generated by comparing the ECAR with the OCR after glucose injection. C and D, PBMCs were stimulated with inflammatory mediators. After 30 minutes of stimulation, 25 mg/mL of IVIG or equimolar concentration of F(ab')₂ or Fc was added to the PBMCs for 24 hours. Glycolytic function is measured by changes in the ECAR following sequential injection of glucose (Glu), oligomycin (Oligo), and 2-deoxy-D-glucose (2-DG) (Fig 2, C) and mitochondrial maximal respiration is measured as a function of OCR following FCCP injection, but before R&A injection (mean ± SEM; 5 independent donors performed in quas duplicates) (Fig 2, D). E, Measure of AUC of glycolytic and mitochondrial respiration functions and corre sponding changes in ECAR and OCR during gly costress and mitostress assays in activated (CC) PBMCs treated with IVIG, F(ab')₂ fragments, or Fc fragments. Data are presented as mean, SEM, and lower and up- per 95% CI (5 independent donors performed in quadruples). F, Energy profile (mean ± SEM; 5 indepen- dent donors performed in quadruples) of PBMCs (CC, CC + IVIG, CC + F(ab')₂, and CC + Fc) generated by comparing the ECAR with the OCR after glucose injection. FCCP, Carbonyl cyanide 4-(trifluoromethoxy) phenylhydrazone; R&A, rotenone and antimycin.

Intracellular metabolites were extracted and subjected to liquid chromatography coupled to high-resolution mass spectrometry. In total, 100 metabolites were annotated using the workflow (see Table E1 in this article's Online Repository at www.jacionline.org).

PCAs of the 100 annotated metabolites (Table E1) demonstrate that IVIG induces a major shift in the metabolic landscape of PBMCs compared with activated PBMCs (Fig 3, A). PCA plots clearly show that IVIG-treated PBMCs from donors 1 and 3 are closer to activated PBMCs compared with donors 2, 4, and 5.

These data suggest that donors 1 and 3 do not exhibit a major shift in cellular metabolite content upon IVIG treatment compared with donors 2, 4, and 5. However, this shift in the metabolic landscape was not seen when PBMCs were treated with HSA (Fig 3, B and C). These data suggest that shift in the metabolic landscape observed in IVIG-treated PBMCs is not due to the protein load and that IVIG has the potential to modify the metabolic landscape of PBMCs. Although activation of PBMCs exhibited enhanced glycolysis, we did not observe any major changes in the overall
<figure><img src="image_18.png" /><figcaption>**FIG 3.** PCAs of PBMC metabolites across various treatment conditions with corresponding Euclidean distance matrices. **A**, The PCA plot representing a clear separation between activated (CC, triangles) and IVIG-treated (CC + IVIG, circles) PBMCs. **B**, The score plots of activated (CC) and HSA-treated (CC + HSA, squares) PBMCs. **C**, The PCA plot representing the differences in the metabolic landscape between HSA-treated (CC + HSA) and IVIG-treated (CC + IVIG) PBMCs. **D**, The PCA plot comparing the untreated (CA, rhombus) and proinflammatory cytokines cocktail and PGE₂-activated (CC) PBMCs. **E**, The distribution of principal components and the percentage of population (metabolites) representing each principal component. **F**, The score plots representing principal components 1 and 2. **PC**, Principal component.</figcaption></figure>

metabolic landscape of activated PBMCs compared with unstimulated cells (Fig 3, D). The principal components 1 and 2 represent 70% of the total variance (Fig 3, E and F). Furthermore, we observed a sharp drop in eigenvalues in the scree plots across the PCAs, confirming the robustness of the data set. Thus, taking into consideration all the aforementioned data, IVIG does induce changes in metabolism of human immune cells. Because IVIG is pooled normal IgG of healthy donors, these data also imply the potential role of circulating normal IgG in modulating the metabolism of immune cells.

## IVIG promotes lipogenesis of anti-inflammatory lipids by shuttling acetyl-CoA away from the mevalonate pathway

Metabolome profiling revealed that cytokine stimulation increased the intracellular accumulation of geranylgeranyl cysteine (Fig 4, A). However, intracellular levels of amino acid cystine (Fig 4, B) were not significantly altered across various experimental conditions. Both IVIG and HSA treatments significantly reduced the intracellular levels of geranylgeranyl cysteine (Fig 4, A). This observation suggests that both IVIG and HSA prevent acetyl-CoA from entering the mevalonate pathway.

IVIG treatment significantly increased the intracellular accumulation of various lipid species including diacylglycerol (DAG; 41:0), triacylglycerol (TAG; 48:5), phosphatidylserine (PS; 18:3_0:0), phosphatidylcholine (PC; 20:0_26:0), phosphatidylethanolamine (PE; 36:9), and sphingomyelin (SM; 18:0_22:1) (Fig 5, A-F). This

increase in lipids was not observed in HSA-treated PBMCs, indicating that the effect was specific to IVIG (Fig 5, A-F). Interestingly, we did not detect any significant increase in levels of short- and medium-chain lipids and fatty acids (FAs) such as FA (14:0, 16:4), monoacyl-glycerol (8:0), and DAG (17:0, 25:3) (see Fig E2, A-E, in this article's Online Repository at www.jacionline.org). Also, we did not observe any significant increase in levels of lysophosphatidylcholine (16:3) and lysophosphatidylethanolamine (16:0, 20:4, 20:5, 22:6) (see Fig E3, A-E, in this article's Online Repository at www.jacionline.org), which are the markers of lipolysis. Taken together, this observation suggests that IVIG promotes lipogenesis of a specific set of anti-inflammatory lipids by shuttling acetyl-CoA away from the mevalonate pathway.

## IVIG-induced lipogenesis of DAG and TAG is mediated via F(ab')₂ fragments and dependent on the sialylated glycans of IgG

The Fc-mediated anti-inflammatory effects of IVIG were attributed to sialylated glycans at asparagine 297,²²,³²,⁴⁷,⁴⁸ although few studies have also shown that anti-inflammatory effects of IVIG can occur independently of sialylation.³³,⁴⁹,⁵⁰ Therefore, to obtain a mechanistic insight into IVIG-induced lipogenesis in PBMCs, we performed untargeted lipidomics on quiescent PBMCs alone (CA) or inflammatory mediators-stimulated PBMCs (CC). These were treated with IVIG (CC + IVIG), F(ab')₂ fragments of IVIG (CC + F(ab')₂), or desialylated IVIG (CC + DESI IVIG). As observed earlier in our untargeted
<figure><img src="image_19.png" /><figcaption>**FIG 4.** IVIG reduces the intracellular levels of geranylgeranyl cysteine. **A** and **B**, Relative intensity (mean ± SEM; n = 5 donors) of intracellular geranylgeranyl cysteine (Fig 4, A) and cystine (Fig 4, B) in quiescent (CA) or inflammatory cytokines cocktail and PGE₂-stimulated (CC) PBMCs treated with either IVIG or HSA. ***P < .001 (1-way ANOVA and the Tukey multiple comparison test).</figcaption></figure>

metabolome profiling, the relative intensities obtained in comple-
mentary untargeted lipidomics experiments that monitored 163
distinct lipid species (see Table E2 in this article's Online Repos-
itory at www.jacionline.org) showed that IVIG increases the
intracellular accumulation of DAG (Fig 6, A-C) and TAG
compared with the activated PBMCs (Fig 7, A-F). Interestingly,
F(ab')₂ fragments also induced similar intracellular accumulation
of DAG and TAG in PBMCs (Figs 6 and 7). However, PBMCs
treated with desialylated IVIG exhibited only basal intracellular
accumulation of DAG and TAG (Figs 6 and 7), thus indicating
that IgG sialylation is indispensable for IVIG-mediated regula-
tion of lipogenesis.

DISCUSSION

Fundamental metabolic pathways such as glycolysis, TCA cycle, amino acid metabolism, and fatty acid synthesis/oxidation are shown to be differentially regulated across different immune cells depending on their activation status, the signals they receive, and their functions. Our immune system consists of diverse immune cells and each of these immune cells could be activated with distinct stimuli *in vitro* such as anti-CD3 and anti-CD28 antibodies for T-cell receptor-mediated T-cell activation,⁵¹,⁵² anti-IgM and IgG for B-cell receptor-mediated B-cell activation,⁵³ and LPS for Toll-like receptor (TLR4)-mediated monocyte, M1 macrophages, or DC activation.⁵⁴ However, signaling by IL-1β, TNFα, and IL-6 is critically involved in inflammation and these cytokines can stimulate both innate and adaptive immune cells.⁴¹,⁴⁵,⁵⁵⁻⁵⁷ On activation, all these immune cells undergo metabolic shift from quiescent respiration to enhanced aerobic glycolysis,¹ a phenomenon known as the Warburg effect. Enhanced aerobic glycolysis is essential for immune cells to mount effective immune responses against antigen insults. DCs, monocytes, and M1 macrophages, on sensing antigen via pattern recognition receptors, and effector CD4⁺ T cells and B cells, on activation by T- and B-cell receptors, exhibit phosphoinositide 3-kinase (PI3K)-mediated increase in glycolysis.⁵⁸⁻⁶⁰ Immunometabolism plays the main role in immune homeostasis and host defense against invading pathogens by fueling various metabolic end products, which profoundly influence the process of transcription, translation, and the function of proteins in immune cells.

IVIG has been used as one of the key immunotherapeutic drugs for treating a large number of autoimmune and inflammatory diseases. The expanding horizon of diseases that could benefit from IVIG immunotherapy also led to the exploration of cellular and molecular mechanisms of IVIG. These mechanisms have suggested that IVIG could target the metabolism of immune cells to exert beneficial effects. In fact, microarray analysis on the PBMCs of patients with Kawasaki disease undergoing IVIG therapy reported a 12-fold reduction in the transcripts of hexokinase-3, a key enzyme in the upstream of glycolysis pathway.⁶¹ Boolean analysis of transcriptomic data from patients with Kawasaki disease has implicated a role for metabolic pathways in determining the response to IVIG therapy.⁶² Our recent report demonstrates that IVIG induces autophagy in inflammatory innate immune cells by suppressing the activation of the mammalian target of rapamycin (mTOR), a serine/threonine protein kinase, which has a key function in supporting glycolysis.¹⁵ In experimental models of autoimmune diseases such as experimental autoimmune encephalomyelitis, expansion of pathogenic T<sub>H</sub>17 cells depends on the glycolytic pathways⁶³ and IVIG reduces the mTOR kinase in the CD4<sup>+</sup> T cells from mice with experimental autoimmune encephalomyelitis.⁶⁴ Furthermore, in TLR-activated macrophages, IVIG reduces nitric oxide,⁶⁵ a metabolic product released by nitric oxide synthase-mediated oxidation of L-arginine.⁶⁶ In TLR-activated neutrophils, therapeutic concentrations of IVIG inhibit reactive oxygen species,⁶⁷ which is contributed by both glycolysis and glutaminolysis.⁶⁸⁻⁷¹ All these evidences clearly indicate that IVIG affects the metabolism of various immune cells depending on the signals they receive.

Our present study based on the metabolic flux analyses of inflammatory mediators-stimulated PBMCs reveals that depending on the glucose availability, IVIG differentially regulates metabolic pathways, in particular oxidative respiration, in immune cells. These IVIG-induced metabolic changes are dependent on both F(ab')₂ and Fc fragments. The observed results are not due to differences in the types of immune cells harvested at 24 hours because the composition of T-cell subsets (CD4 and CD8), monocytes/macrophages, and B cells and their viability were mostly similar across the conditions.

Although metabolic flux analysis provides valuable information on the glycolysis and mitochondrial respiration status of
<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /></figure>

<figure><img src="image_24.png" /></figure>

<figure><img src="image_25.png" /></figure>

FIG 5. IVIG promotes lipogenesis of anti-inflammatory lipids. A-F, Relative intensity (mean ± SEM; n = 5 donors) of intracellular DAG (41:0) (Fig 5, A), TAG (48:5) (Fig 5, B), PS (18:3 [6Z, 9Z, 12Z]/13:0) (Fig 5, C), PC (20:0/26:0) (Fig 5, D), PE (36:9) (Fig 5, E), and SM (d18:0/22:1[13Z][OH]) (Fig 5, F) in quiescent (CA) or in- flammatory cytokines cocktail and PGE₂-stimulated (CC) PBMCs treated with either IVIG or HSA. \*P < .05; \*\*P < .01 (1-way ANOVA and the Tukey multiple comparison test).

cells, this approach is not useful for evaluating the intermediate metabolites of these pathways. It has been shown that immune cells have different fuel choices for feeding the TCA cycle depending on whether they are in a resting (quiescent) state or an activated state.⁹ Resting immune cells use glucose derivatives to fuel the TCA cycle, but on activation, glucose entering glycolysis is converted to lactate and the TCA cycle is rather fueled by glutamine-derived α-ketoglutarate.¹,⁹ Because the functional assays are based on the byproducts of these metabolic pathways, it is impossible to study such intricate mechanisms of metabolic regulation by immune cells using metabolic flux analysis.

Therefore, to have an insight into the influence of IVIG toward metabolic reprogramming of immune cells, we performed untargeted global metabolic profiling. Interestingly, untargeted metabolite profiling revealed slight reduction in the intracellular levels of fructose 1,6-bisphosphate following IVIG treatment, suggesting an acceleration in the depletion of glycolytic intermediates, which might be the consequence of increased rate of glycolysis. Unlike metabolic flux analysis, in which the preconditioned cells were starved before ECAR and OCR measurements and exposed to 25 mM glucose and stressors (2-deoxy-D-glucose, oligomycin, carbonyl cyanide
<figure><img src="image_26.png" /><figcaption>**FIG 6.** Induction of DAGs by IVIG is mediated via F(ab')₂ fragments and is dependent on the sialylated glycans of IgG. **A-C**, Relative intensity (mean ± SEM; n = 6 donors) of intracellular DAG (34:2) (Fig 6, A), DAG (36:2) (Fig 6, B), and DAG (36:3) (Fig 6, C) in quiescent PBMCs alone (CA) or inflammatory cytokines cocktail and PGE₂-stimulated PBMCs (CC) treated with either IVIG (CC + IVIG), F(ab')₂ (CC + F(ab')₂), or desialylated IVIG (CC + DESI IVIG). \*P < .05; \*\*P < .01 (2-tailed paired t test).</figcaption></figure>

4-(trifluoromethoxy) phenylhydrazone, rotenone, and antimycin) in a sequential manner to study live metabolic flux, untargeted global metabolic profiling was performed on stimulated cells by arresting the metabolism. Despite these limitations, untargeted metabolic profiling sheds light on the metabolic pathways that bifurcate inflammatory mediators–activated immune cells and IVIG-conditioned cells. When PBMCs were activated, there was an increase in the intracellular accumulation of geranylgeranyl cysteine. However, IVIG abrogates this prenylation process and promotes lipogenesis of DAG, TAG, PS, PC, PE, and SM. These data suggest that IVIG shunts acetyl-CoA from entering the mevalonate pathway in PBMCs. Although HSA has also reduced geranylgeranyl cysteine levels, it is likely due to its higher affinity binding to geranylgeranyl cysteine because we did not observe lipogenesis with HSA treatment. In fact, HSA exhibits properties of binding and transportation of numerous endogenous molecules.⁷² Although this noncovalent adduct could, in principle, be detected by mass spectrometry, the addition of methanol in the metabolomics sample preparation protocol should precipitate it, thereby preventing its subsequent detection by mass spectrometry.

Previous reports suggest that fatty acid metabolism is implicated in modulating the nature of immune response.

Accumulation of polyunsaturated fatty acids was reported to favor the production of noninflammatory cytokines.⁷³ Phosphorylation of DAG to phosphatidic acid by DAG kinases is known to induce T-cell tolerance.⁷⁴ Accumulation of lipids such as TAG protects *Dgat1*⁻¹⁻ mice from palmitate-mediated lipotoxicity.⁷⁵ Phospholipids such as PS, PC, and PE also induce anti-inflammatory response. Externalization of PS acts as an immunosuppressive signal that prevents systemic immune activation by promoting apoptosis.⁷⁶ PC and PE were shown to promote tolerance in carrageenan-induced pleurisy by blocking nitric oxide synthase and xanthine oxidoreductase activity.⁷⁷ Sphingolipids such as SM have been shown to protect the plasma membrane integrity by preventing the oxidation of PC.⁷⁸

Previous metabolomics studies have shown that activation of immune cells leads to metabolic modulation within glycolysis, thereby altering the fate of glucose. Although initially glucose is converted to lactate, later as cells enter the S phase, glucose-derived glucose-6-phosphate is shuttled to PPP to promote nucleotide synthesis.⁵⁸ Interestingly, stimulation of PBMCs with inflammatory mediators did not alter the levels of intracellular nucleotides, indicating that in the absence of antigenic stimuli, glucose-6-phosphate does not shuttle to PPP. We could not detect lactate in any of the treatment conditions. Because lactate
<figure><img src="image_27.png" /></figure>

TAG 48:3

<figure><img src="image_28.png" /></figure>

TAG 48:5

<figure><img src="image_29.png" /></figure>

TAG 50:3

<figure><img src="image_30.png" /></figure>

TAG 50:4

<figure><img src="image_31.png" /></figure>

TAG 56:5

<figure><img src="image_32.png" /></figure>

TAG 56:7

**FIG 7.** F(ab')₂ fragments and IgG sialylated glycans-dependent induction of TAGs by IVIG. A-F, Relative intensity (mean ± SEM; n = 6 donors) of intracellular TAG (48:3) (Fig 7, A), TAG (48:5) (Fig 7, B), TAG (50:3) (Fig 7, C), TAG (50:4) (Fig 7, D), TAG (56:5) (Fig 7, E), and TAG (56:7) (Fig 7, F) in quiescent PBMCs alone (CA) or inflammatory cytokines cocktail and PGE₂-stimulated PBMCs (CC) treated with either IVIG (CC + IVIG), F(ab')₂ (CC + F(ab')₂), or desialylated IVIG (CC + DESI IVIG). \*P < .05 (2-tailed paired *t* test).

is secreted into the supernatant, they might have been washed during intracellular metabolite isolation.

Our recent study has highlighted that IVIG suppresses the activation of key kinases implicated in the metabolism such as mTOR.¹⁵ Previous reports have shown that IVIG recognizes proteins implicated in glycolysis such as alpha-enolase,⁷⁹,⁸⁰ suggesting that IgG directly interacts with components of metabolic machinery to exert changes. Of interest, our untargeted lipidomic

profiling shows that F(ab')₂ fragments of IVIG contribute to the intracellular accumulation of anti-inflammatory lipids. However, sialylation of IgG was essential for the lipogenesis of anti-inflammatory lipids, because desialylated IVIG failed to induce the accumulation of DAG and TAG in PBMCs. Human IgG anti-bodies share a conserved N-glycosylation site at asparagine 297 in the Fc portion. Asparagine 297-linked α(2,6)-sialylation has been reported to play a role in the anti-inflammatory actions of
IVIG.⁴⁷,⁸¹ Other reports, however, also demonstrate a significant amount of sialylation in the Fab region of IVIG that contributes to the anti-inflammatory effects.⁸² Because metabolic flux data indicated that IVIG-induced metabolic changes are dependent on both F(ab')₂ and Fc fragments, these data together suggest that sialylated glycans of both Fab and Fc regions contribute to the induction of DAG and TAG in PBMCs.

Induction of DAG has been shown to activate the protein kinase C, Ras, and extracellular signal-regulated kinase pathways. Although the direct impact of induction of DAG by IVIG on the functions of immune cells is not known, we could speculate few possibilities on the basis of the current literature. Our recent data show that IVIG induces autophagy in human PBMCs,¹⁵ and DAG-induced activation of the extracellular signal-regulated kinase pathway could represent one of the pathways implicated in this process.⁸³ In addition, various reports including ours demonstrate that IVIG promotes Treg-cell activation and proliferation by diverse mechanisms.⁸⁴ IVIG-induced DAG might represent an additional mechanism implicated in Treg-cell proliferation via the protein kinase C-Ras pathway.⁸⁵ Moreover, we showed that IVIG induces Treg-cell expansion by inducing PGE₂ in human DCs.²⁴ By serving as a precursor for arachidonic acid, a key substrate involved in the synthesis of PGE₂, DAG could indirectly contribute to the production of PGE₂.

Altered metabolic processes of immune cells, such as enhanced glycolysis, are the classical features of autoimmune and inflammatory diseases.⁶³,⁸⁶⁻⁸⁹ Therefore, metabolic pathways have emerged as novel therapeutic targets for controlling the pathogenic immune responses in autoimmune and inflammatory diseases. Several approaches are under investigation and at various stages of clinical evaluations for the pathologies, including multiple sclerosis, lupus, rheumatoid arthritis, transplantation, and others.¹⁰,⁹⁰,⁹¹ The data from this report and from the literature highlight that IVIG exerts multifaceted mechanisms including the alteration of immune cell metabolism to exert potent immunoregulatory effects in autoimmune and inflammatory diseases.

## DISCLOSURE STATEMENT

Disclosure of potential conflict of interest: F. Käsermann is an employee of CSL Behring AG. The rest of the authors declare that they have no relevant conflicts of interest.

### Key messages

* IVIG alters the overall metabolic landscape of human PBMCs.

* IVIG and its Fc and F(ab')₂ fragments regulate the Warburg effect depending on glucose availability.

* IVIG promotes lipogenesis of anti-inflammatory lipids.

* IVIG-induced lipogenesis is mediated via F(ab')₂ fragments and is dependent on the sialylated glycans of IgG.

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