Metabolomics supported osteonecrosis research

An open access publication highlighting the importance of metabolomics and lipidomics profiling in the biomarker discovery and the improvement of diagnostics and treatment of osteonecrosis is published in the Bioactive Materials journal. “Biofunctionalized composite scaffold to potentiate osteoconduction, angiogenesis, and favorable metabolic microenvironment for osteonecrosis therapy” describes developed scaffold (PLGA/nHA₃₀^VEGF) for osteonecrosis therapy. The scaffolds were implanted into the rabbit osteonecrosis model for the evaluation.

Osteonecrosis always has complex microenvironmental changes, including abnormal metabolism. Previous studies were looking into the blood and urine metabolomics, which may not accurately reflect metabolic disorders in the bone tissue microenvironment. Here, the authors looked into the metabolomics and lipidomics profiling of bone specimens, and the samples were analyzed at Metware Biotechnology facilities.

Ideally, biomaterials should serve as a dynamic control system that can correct metabolic microenvironment, thus the authors looked into metabolic pathways. It was found that the expression levels of many metabolites tended to normalize after treatment with the biofunctionalized composite scaffold. The levels of three metabolites derived from hippuric acid, caffeic acid, and shikimic acid were significantly downregulated in the model group and recovered after treatment. The authors looked deeper into the mechanisms where these compounds are involved and provided parallels with previously published expression trends. After the comparison of the normal and model groups, it was obvious that the following metabolic pathways were impacted: riboflavin metabolism, pyrimidine metabolism, folate metabolism, ABC transporter, ferroptosis, galactose metabolism, carbohydrate digestion and absorption metabolism, oxidative phosphorylation, and cysteine and methionine metabolism. The connection of some metabolic pathway with steroid therapy was brought up. The authors also discussed  other cell regulation processes, such as lipid transport and iron metabolism.

As impaired fat metabolism is one of the leading causes of osteonecrosis, authors looked more precisely into the lipid metabolites. It was found that glycerophospholipids, sphingomyelin metabolites, and other glycerolipids and fatty acyl metabolites varied between the studied groups. Glycerophospholipids are the main components of cell membranes, which regulate the transport process, protein function, signal transduction, affecting the function and metabolism of lipoproteins, promote fat metabolism, and improve blood circulation. Compared with the model group, the treatment group had nine significantly upregulated oxidized lipid metabolites. Oxidized lipids promote tissue repair and cell proliferation, improving vascular permeability and anti-oxidative stress.

KEGG pathway database was used to analyze the metabolic pathways related to the disease. The following pathways were found to be impacted: glycerophospholipid metabolism, arachidonic acid metabolism, linolenic acid metabolism, α-linolenic metabolism, and phosphatidylinositol signaling metabolism. Scaffold implantation helped to reduce an impact of osteonecrosis on some of these pathways.

Metabolomics and lipidomics profiling of bone material provided valuable insights into the microenvironmental disorders of osteonecrosis. This paper suggests that PLGA/nHA₃₀^VEGF may reverse the adverse effects of osteonecrosis by metabolism regulation.

If you are interested in performing these types of studies, Metware Biotechnology is offering the following assays at our Boston location:

TM Widely-Targeted Metabolomics for human and animal samples: a great starting point to examine the global metabolite profile. Metware's curated database of 280,000 metabolites, which includes 3000 metabolites not found in public databases, allows more annotations from high-resolution mass spec data.

Quantitative Lipidomics: a high-throughput targeted approach that simultaneously identifies and quantifies over 3000 lipids (with absolute quantification)