Age Prediction Based on MetabolomeInquiry
Two individuals of the same age may have different biological aging states, and by capturing this difference may constitute a powerful age predictor. Metabolomics can be used to characterize the differences in changes with aging and has also been applied to predict and characterize common age-related diseases such as cancer, diabetes, Parkinson's disease, etc. Thus, the metabolome can be a powerful tool for age prediction and aging assessment.
The metabolome can provide us with information about biological age by measuring and identifying such potentially differential metabolomics molecules as predictors. CD BioSciences provides metabolome-based age prediction research services that measure and characterize the metabolome and apply it in predictive models of biological age.
The metabolome can characterize all small molecules of biological systems and changes with age. Therefore, we provide research services aimed at identifying metabolomic features associated with biological aging to construct biological age prediction models.
We measure metabolomic data to identify metabolomic features associated with biological age, including some relevant metabolites such as amino acids, fatty acids, acylcarnitine, etc. These predictors are used to develop a metabolomic-based age prediction model, which has important implications for the analysis of aging mechanisms. Our specific service process is shown in the figure below. For more information, please contact us.
Our services are oriented towards,
- Biotechnology industry
- Biomedical industry
- Animal husbandry industry
- Other related research institutions
Metabolomics Data Analysis
- Quality control - data results for the quantification and characterization of sample metabolites.
- Differential metabolite screening - univariate, multivariate analysis of all identified metabolites.
- Metabolic pathway analysis of differential metabolites - functional annotation analysis, clustering analysis and enrichment analysis of differential metabolites.
- Biomarker discovery - metabolite differential correlation analysis, biomarker ROC analysis.
Biological Age Model Construction
Biological age is calculated using our screened and determined metabolomic parameters via basic equations, that is, age prediction equation models are constructed by linear regression estimating the linear relationship between each parameter and the actual age. We reduce model bias and overfitting to accurately assess the calculated biological age.
Why Choose CD BioSciences?
- The aging metabolomics platform integrates metabolomic testing and age prediction model building in a single solution for rapid and accurate screening and establishment of predictive metabolic factors.
- We provide additional insights containing selected unique variant metabolomics data from various biological populations that can be used to confirm and validate predictors.
- High-throughput metabolomics-based approaches allow us to continuously discover new and highly specific biomarkers for future use as tools to diagnose aging and age-related diseases and monitor the effectiveness of treatments.
Based on metabolomics techniques, we perform qualitative and quantitative analyses of all metabolites in a sample under general or specific conditions to discover and identify different metabolites with predictive potential, capturing such age-related differential metabolomics measurements constituting predictive models.
CD BioSciences, as one of the few professional aging research technology service providers in the world, relies on our rich service experience and advanced technology platform to provide one-stop metabolomic age prediction services. If you have any questions about our related services, please feel free to contact us and we will get back to you as soon as possible!
- Johnson L C, et al. The plasma metabolome as a predictor of biological aging in humans. GeroScience, 2019, 41(6):895-906.
Our services are for research use only and not for any clinical use.
We are a comprehensive technology platform company integrating aging DNA methylation, telomere, transcriptome, proteome, and metabolome research.