Lipidomics: new insight into kidney disease - PubMed (original) (raw)

Review

Lipidomics: new insight into kidney disease

Ying-Yong Zhao et al. Adv Clin Chem. 2015.

Abstract

Due to the incidence of type-2 diabetes and hypertension, chronic kidney disease (CKD) has emerged as a major public health problem worldwide. CKD results in premature death from accelerated cardiovascular disease and various other complications. Early detection, careful monitoring of renal function, and response to therapeutic intervention are critical for prevention of CKD progression and its complications. Unfortunately, traditional biomarkers of renal function are insufficiently sensitive or specific to detect early stages of disease when therapeutic intervention is most effective. Therefore, more sensitive biomarkers of kidney disease are needed for early diagnosis, monitoring, and effective treatment. CKD results in profound changes in lipid and lipoprotein metabolism that, in turn, contribute to progression of CKD and its cardiovascular complications. Lipids and lipid-derived metabolites play diverse and critically important roles in the structure and function of cells, tissues, and biofluids. Lipidomics is a branch of metabolomics, which encompasses the global study of lipids and their biologic function in health and disease including identification of biomarkers for diagnosis, prognosis, prevention, and therapeutic response for various diseases. This review summarizes recent developments in lipidomics and its application to various kidney diseases including chronic glomerulonephritis, IgA nephropathy, chronic renal failure, renal cell carcinoma, diabetic nephropathy, and acute renal failure in clinical and experimental research. Analytical technologies, data analysis, as well as currently known metabolic biomarkers of kidney diseases are addressed. Future perspectives and potential limitations of lipidomics are discussed.

Keywords: Inflammation; Kidney diseases; Lipid profiling; Lipidomics; Mass spectrometry; Renal diseases; System biology.

PubMed Disclaimer

Cited by

Lipidomic study of kidney in a mouse model with urine flow obstruction.
Gowda D, Masum MA, B Gowda SG, Shekhar C, Rubel MZU, Kira S, Ichii O, Kon Y, Chiba H, Hui SP. Gowda D, et al. Sci Rep. 2024 Aug 5;14(1):18042. doi: 10.1038/s41598-024-68270-5. Sci Rep. 2024. PMID: 39098953 Free PMC article.
Lipid metabolism disorder in diabetic kidney disease.
Han YZ, Du BX, Zhu XY, Wang YZ, Zheng HJ, Liu WJ. Han YZ, et al. Front Endocrinol (Lausanne). 2024 Apr 29;15:1336402. doi: 10.3389/fendo.2024.1336402. eCollection 2024. Front Endocrinol (Lausanne). 2024. PMID: 38742197 Free PMC article. Review.
Integrated metabolomics and proteomics reveal biomarkers associated with hemodialysis in end-stage kidney disease.
Lin W, Mousavi F, Blum BC, Heckendorf CF, Moore J, Lampl N, McComb M, Kotelnikov S, Yin W, Rabhi N, Layne MD, Kozakov D, Chitalia VC, Emili A. Lin W, et al. Front Pharmacol. 2023 Nov 27;14:1243505. doi: 10.3389/fphar.2023.1243505. eCollection 2023. Front Pharmacol. 2023. PMID: 38089059 Free PMC article.
Untargeted metabolite profiling of serum in rats exposed to pyrraline.
Hu C, Wang J, Qi F, Liu Y, Zhao F, Wang J, Sun B. Hu C, et al. Food Sci Biotechnol. 2023 Jan 26;32(11):1541-1549. doi: 10.1007/s10068-023-01256-7. eCollection 2023 Oct. Food Sci Biotechnol. 2023. PMID: 37637845 Free PMC article.
Chronic kidney disease and gut microbiota.
Amini Khiabani S, Asgharzadeh M, Samadi Kafil H. Amini Khiabani S, et al. Heliyon. 2023 Aug 7;9(8):e18991. doi: 10.1016/j.heliyon.2023.e18991. eCollection 2023 Aug. Heliyon. 2023. PMID: 37609403 Free PMC article. Review.

Lipidomics: new insight into kidney disease - PubMed (original) (raw)