Application of PPAR Ligands and Nanoparticle Technology in Metabolic Steatohepatitis Treatment

Abstract

Metabolic dysfunction-associated steatotic liver disease/steatohepatitis (MASLD/MASH) is a major disease worldwide whose effective treatment is challenging. Peroxisome proliferator-activated receptors (PPARs) belong to the nuclear receptor superfamily and function as ligand-activated transcription factors. To date, three distinct subtypes of PPARs have been characterized: PPARα, PPARβ/δ, and PPARγ. PPARα and PPARγ are crucial regulators of lipid metabolism that modulate the transcription of genes involved in fatty acid (FA), bile acid, and cholesterol metabolism. Many PPAR agonists, including natural (FAs, eicosanoids, and phospholipids) and synthetic (fibrate, thiazolidinedione, glitazar, and elafibranor) agonists, have been developed. Furthermore, recent advancements in nanoparticles (NPs) have led to the development of new strategies for MASLD/MASH therapy. This review discusses the applications of specific cell-targeted NPs and highlights the potential of PPARα- and PPARγ-targeted NP drug delivery systems for MASLD/MASH treatment.

Keywords: MASH; MASLD; PPAR; drug delivery; nanoparticles.

Figure 1

PPAR targets and contributing factors in MASLD/MASH. C1Q and collagen domain containing adiponectin (ADIPOQ) is a key insulin regulator whose secretion from the adipose tissue into the liver is regulated by PPARγ. Insulin regulates SREBP-1C via the PI3K/AKT signaling pathway in the liver. PPARα regulates the essential glycolytic enzymes ACC and FAS that play key roles in the synthesis of TGs. ChREBP is also involved in TG synthesis. LPL and APOC3 promote TG hydrolyzation into FAs. CPT1/2, SLC27A1, ACAD, HMGCS2, and EHHADH are involved in mitochondrial β-oxidation. In the presence of ACC, acetyl-CoA is converted to malonyl-CoA (de novo lipogenesis). Peroxisomal β-oxidation is enhanced via ACOX and DGAT1/2. Excess TG is transported to adipose tissue by VLDL facilitated by the expression of apolipoproteins, APOE and APOC2, and MTTP. In adipose tissues, FAs are converted into TGs via FABP4, CD36, LPL, MOGAT1, and FSP27. FA accumulation can cause autophagy controlled by ATA and TFEB. In MASH, downregulation of TGF-β, TNF-α, and MCP1 levels triggers hepatic inflammation, which subsequently activates the hepatic stellate cells and can lead to fibrosis.

Figure 2

Single-nuclei RNA sequencing of PPARα and -γ expression levels in human hepatic cells. (A) Uniform manifold approximation and projection (UMAP) plots show the annotations for different cell types. (B) Violin plots of PPARα and PPARγ expression levels with marker genes for nine distinct cell types. (C) Feature plots. Abbreviations: BANK1, B cell scaffold protein with ankyrin repeats 1; KLRF1, killer cell lectin receptor F1; DCN, decorin; KRT7, keratin 7; STAB2, stabilin 2; TAT, tyrosine aminotransferase; CYP3A4, cytochrome P450 family 3 A member 4. Methods: Gene expression patterns of hepatic cells were investigated via single-nucleus RNA-sequencing in healthy individuals and patients with MASLD. Data were obtained from the Gene Expression Omnibus (GEO; accession number GSE174748). The Seurat package (version 5.0.1) was used to analyze the single-cell RNA sequencing data [63]. Filtering was used to remove the cells with ovecellsochondrial genes or fewer than 200 genes. Cells were normalized and clustered using Seurat. The samples were integrated using a harmony approach [64]. Cell types were annotated based on the expression levels of specific gene markers. UMAP, features, and violin plots were generated using the R statistical software (version 4.3.2).

Figure 3

Schematic diagram of the main types of NPs.

Figure 4

Passive targeting nanoparticles mechanism.