Influences of metabolism and lipid homeostasis on regulatory vs. conventional T cells and implications for autoimmunity

Abstract

Regulatory T cells are essential for suppressing an overactive immune system, especially concerning autoimmune disease, tumor growth, and inflammatory disease. This suppressive nature of regulatory T cells is largely due to their metabolic profiles determined by metabolic reprogramming upon activation and subsequent differentiation. As regulatory T cells tend to process and cycle energy differently from other T cell subsets, we are interested in what metabolic processes support regulatory T cell function. This review will consider how regulatory T cells compare with conventional T cells in terms of their participation in distinct metabolic pathways and how the presence of regulatory T cell-specific molecules influences proliferation and suppressive function. Additionally, this review will identify possible metabolic targets of regulatory T cells that could be targeted for development of autoimmune disease therapies.

Keywords: autoimmune disease; lipid metabolism; mTOR; metabolic reprograming; mevalonate (MVA) pathway; regulatory T cells.

Figure 1

Generalized overview of primary lipid metabolism participation and metabolic reprogramming of T cell subsets upon activation and differentiation. Inactivated CD4 or CD8 T cells that originate from the thymus do not rely heavily on metabolism for function. Upon activation, a shift in glycolysis is observed, especially for CD4 T cells, while OXPHOS and FAO levels remain stable. CD4 memory T cells lessen reliance on glycolysis in favor of FAO and especially OXPHOS, whereas CD8 memory T cells similarly shift reliance to OXPHOS and especially FAO. CD8 effector T cells have enhanced glycolysis and glutaminolysis. CD4 effector Th1 and Th17 cells rely on glycolysis and glutaminolysis after differentiation via mTORC1, and CD4 effector Th2 cells also rely on glycolysis and glutaminolysis after differentiation, but via mTORC2. Regulatory T cells, which reprogram via mTORC1 and the MVA pathways to rely more on OXPHOS, FAO, and DNL. iTregs, which differentiate from activated CD4 T cells, rely on FAO more than nTregs, which differentiate from the thymus. Created in BioRender. Nguyen, M. (2025) https://BioRender.com/la11dgt.

Figure 2

Influences of protein, small molecules, and metabolic pathways in regulatory T cells. Extracellular lipid droplets are uptaken, facilitated by CD36. CD36 activity is upregulated by PPAR-β and PPAR-γ (via interactions with FOXP3). PPAR-γ upregulates other small molecules: SLC27A2, lipase E, SCD1, CPT1A, DGAT1, and perilipin-2. LKB1 regulates the mevalonate pathway, which upregulates FOXP3 expression and phosphorylates SMAD3 to enhance TGFβ signaling. TGFβ signaling, in turn, downregulates SMAD3 expression. The MVA pathway is connected to various pathways indirectly. This includes a positive feedback loop between glycolysis and the MVA pathway. The MVA pathway activates OXPHOS while OXPHOS inhibits the MVA pathway. FAO and glycolysis have a negative feedback loop and both feed into OXPHOS. mTORC1 suppresses FOXP3 expression. OXPHOS and mTORC1 have a positive feedback loop while mTORC1 produces HIF-1α activating glycolysis. TGFβ is also a suppressor of HIF-1α. mTORC1 upregulates IL-10, ICOS, and CTLA-4. Leptin can form a complex with mTORC1 to activate the pathway. mTORC1 can form another complex, PI3K-AKT-mTORC1 to activate glycolysis. In relation to mTORC2, PI3K activates AKT, which suppresses TSC1 to inhibit mTORC1. mTORC1 phosphorylates S6K1, which inhibits mTORC2. mTORC2 suppresses SOCS5 to activate IL-4/STAT6 signaling. AMPK inhibits mTORC1 and mTORC2 to upregulate OXPHOS. FABP5 and FABP4 also facilitate uptake of extracellular lipids. FABP5 feeds into lipogenesis mediated by ACC-1. FABP1-Δ9-THC forms a complex within regulatory T cells. Created in BioRender. Nguyen, M. (2025) https://BioRender.com/me864o9.