Effects of Tang Luo Ning on diabetic peripheral neuropathy in rats revealed by LC-MS metabolomics approach

Advanced Mass Spectrometry-Based Biomarker Identification for Metabolomics of Diabetes Mellitus and Its Complications

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

Arginine Biosynthesis Pathway Found to Play a Key Role in the Neuroprotective Effect of Liu-Wei-Luo-Bi (LWLB) Granules in Diabetic db/db Mice with Peripheral Neuropathy Using an Untargeted Metabolomics Strategy

Aim

Liu-Wei-Luo-Bi (LWLB) granules was a Chinese compound prescription for treating diabetic peripheral neuropathy (DPN). The aim of this study was to investigate the effect of LWLB granules on diabetic mice with peripheral neuropathy and to elucidate the potential mechanism based on an untargeted metabolomics approach.

Methods

One hundred forty db/db mice were randomly divided into seven groups: the Control group, DPN group, Mudan (MD) granules group, Epalrestat (Epa) group, and the LWLB low, medium, or high dose (LW-l, LW-m, or LW-h) group. After 12 weeks of treatment, body weight, blood glucose, mechanical pain threshold, motor conduction velocity (MCV), sensory conduction velocity (SCV), and Pathological Organization of the Sciatic and Caudal Nerves in mice were measured. Serum samples were collected for untargeted metabolomics analysis using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) and multivariate statistics. Disease-related pathways were screened out with function enrichment analyses of candidate biomarkers.

Results

LWLB granules can improve the peripheral neuropathy of type 2 diabetic mice with peripheral nerve conduction disorders, mainly through significantly improving the nerve conduction velocity (P < 0.05) and lowering the mechanical pain threshold (P < 0.05). A total of 43 metabolites were identified as potential biomarkers related to the therapeutic effect of LWLB granules. Fifty, 4, and 26; 23, 4, and 22; and 24, 1, and 16 biomarkers were discovered in the LW-l, LW-m, and LW-h groups at the 4th, 6th, and 12th weeks, respectively. Five, three, seven, five, and four metabolic pathways were found in MD, Epa, LW-l, LW-m, and LW-h groups, respectively. The arginine biosynthesis pathway is the overlapping pathway in LW-l, LW-m, and LW-h groups.

Conclusion

LWLB granules have an obvious neuroprotective effect on diabetic peripheral neuropathy, and the metabolism mechanism of LWLB is mainly related to the arginine biosynthesis pathway on diabetic db/db mice with peripheral neuropathy.

Amino acid analysis as a method of discovering biomarkers for diagnosis of diabetes and its complications

Diabetes mellitus (DM) is a severe chronic diseases with a global prevalence of 9%, leading to poor health and high health care costs, and is a direct cause of millions of deaths each year. The rising epidemic of diabetes and its complications, such as retinal and peripheral nerve disease, is a huge burden globally. A better understanding of the molecular pathways involved in the development and progression of diabetes and its complications can facilitate individualized prevention and treatment. High diabetes mellitus incidence rate is caused mainly by lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of diabetes and its complications in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner, and effective biomarkers can greatly improve the efficiency of diabetes and its complications. By providing information on potential metabolic pathways, metabolomics can further define the mechanisms underlying the progression of diabetes and its complications, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The application of amino acid metabolomics in epidemiological studies has identified new biomarkers of diabetes mellitus (DM) and its complications, such as branched-chain amino acids, phenylalanine and arginine metabolites. This study focused on the analysis of metabolic amino acid profiling as a method for identifying biomarkers for the detection and screening of diabetes and its complications. The results presented are all from recent studies, and in all cases analyzed, there were significant changes in the amino acid profile of patients in the experimental group compared to the control group. This study demonstrates the potential of amino acid profiles as a detection method for diabetes and its complications.