Metabolomic Analysis in Aging Research

Metabolomics can add important insight by providing detailed metabolite profiles and metabolomic functions that change with age, which is a very useful and powerful tool in aging research. CD BioSciences provides comprehensive quantitative analysis of aging-related metabolites to understand the biology of aging through quantitative metabolite profiling.

Introduction of Metabolomics in Aging Research

Aging is a complex biological process that manifests itself not only in changes at the molecular level but also in changes in systemic metabolism. Many metabolic processes in the human body produce molecular damage, which accumulates gradually with age and is a major factor contributing to the onset of aging.

Fig. 1 Metabolism-related mechanisms of aging. (Kondoh H, et al. 2020)

Overview of Our Metabolomics Analysis Services in Aging Studies

We provide analysis services of the metabolomic profile of aging, which can help us better understand the mechanisms of aging. The development of sensitive metabolomic technologies also further advances the analysis and characterization of metabolite levels associated with biological aging.

Metabolite profiling

We utilize advanced analytical techniques such as mass spectrometry to identify and quantify a wide range of metabolites in biological samples, which provide valuable information about the metabolic changes associated with aging.

Pathway analysis

We also perform comprehensive pathway analysis to understand the interconnected metabolic pathways and their role in aging. This can help in identifying potential targets for interventions to modulate aging processes.

Sample Requirements

• Sample type: accept various biological samples, blood, urine, various tissues, etc.
• Sample volume: ≥ 200 μL
• Transportation method: dry ice refrigeration
• Sample tubes should be clearly labeled, either with stickers or barcodes.

Our Workflow of Metabolomics Analysis Services

We can explore the metabolomics of aging using a variety of metabolomics approaches, including untargeted and targeted metabolomics. Non-targeted approaches can analyze metabolites globally to understand the overall metabolic profile, while targeted approaches can delve into some specific aging-related metabolic pathways.

• MS analysis
  We identify all detectable metabolites in the sample with high sensitivity, high resolution, high throughput, and wide dynamic range mass spectrometry to analyze the overall metabolic profile of aging and discover the metabolic mechanisms behind it.
• Data analysis
  We efficiently analyze large datasets generated by sequencing through software, to perform statistics and eliminate systematic biases that can accurately identify compounds and detect specific changes. We typically provide feature extraction, molecular identification, statistical analysis, and functional annotation of metabolomics data.

Our Advantages

• Ability to perform targeted and untargeted metabolomics analysis.
• Automated high-throughput sample processing improves workflow standardization and efficiency.
• Sample collection and input homogenization to reduce intra-sample variation and improve reliability.
• Measure thousands of metabolites in a variety of biological samples.
• Make the most of your data according to your statistical analysis needs.
• All data (raw mass spectrometry files, processed data, and final data) are submitted to the clients.

At CD BioSciences, our services aim to use mass spectrometry-based metabolomics to identify and quantify various age-related metabolites. We can use untargeted metabolomics or targeted metabolomics methods to obtain high-resolution, accurate quality metabolic composition and quantitative data depending on the client's needs. If you are interested in our services, please feel free to contact us or make an online inquiry.

References

1. Srivastava S. Emerging Insights into the Metabolic Alterations in Aging Using Metabolomics. Metabolites, 2019, 9 (12).
2. Kondoh H, et al. Whole Blood Metabolomics in Aging Research. International Journal of Molecular Sciences, 2020, 22 (1): 175.