DNA methylation clocks include tissue-specific age models as well as age prediction models for multiple tissues/cells. Multi-tissue/cell age prediction uses a unified methylation prediction model to predict the biological age of different tissues/cell types, which uses a large number of DNA methylation data of different cells to find and identify age prediction biomarkers. This prediction model also has high accuracy in most tissues and cells, which also shows the rationality and potential value of its development. Predicting the methylation age of different cells may be used as a standardized tool to be applied in aging and related research.
CD BioSciences is committed to providing a full range of solutions for aging and longevity. In the field of biological age research, we can provide a DNA methylation clock technology platform and sample age prediction services to predict the biological age of different cell samples for specific applications in various fields.
Our Services of DNA Methylation-Based Age Prediction from Various Cells
We utilize multi-cell age prediction models to predict DNA methylation age for common cell types. These models analyze DNA methylation datasets of different cell types and are constructed to solve some questions in aging research and related diseases.
DNA methylation-based age prediction of healthy cells
We select datasets of different types of healthy cells, including stem cells, lymphocytes, brain cells, dermal fibroblasts, buccal epithelial cells, etc., and analyze the DNA methylation data of these cells, employ age prediction models for biological age measurement of cells in a wide range of human tissues.
DNA methylation-based age prediction of cancer cells
Based on the DNA methylation data of different cancer cell samples, we use age prediction models based on DNA methylation levels, which can be used to describe the methylation age of tumor cells and help cancer development research by comparing the predicted age with the biological age.
Applications of DNA Methylation-Based Age Prediction from Various Cells in Aging Studies
- Disease susceptibility and risk assessment
Our analysis of DNA methylation patterns in various cell types provides crucial information regarding age-related disease susceptibility. By examining the epigenetic aging process in different tissues, researchers can assess the risk of age-related diseases, potentially enabling early intervention tailored to specific cell populations.
- Biomarker discovery
Our DNA methylation-based age prediction facilitates the identification and validation of aging-related biomarkers across various cell types. These biomarkers serve as valuable indicators of cellular aging, potentially offering applications in targeted therapeutic interventions for age-related conditions.
Our Advantages
- Our services are suitable for a wide range of human cell types.
- Our technology allows clients to compare the ages of different tissues/cells from the same individual, which can allow the identification of parts of aging due to external conditions or disease.
- Our predicted age of DNA methylation in different cell types can be used as some therapeutic evaluation indicators to replace some samples that are difficult to obtain and detect.
CD BioSciences has a full range of technology platforms and expertise to help clients successfully initiate and complete DNA methylation analysis programs that meet the desired functionality. From the design of the preliminary plan to the formulation of the service plan, feedback, and report submission, we will actively communicate with you in every link, allowing you to participate in every link and understand your project progress and real situation. We insist on winning customers' trust and cooperation with professionalism. Please feel free to contact us for more information about our services.
Reference
- Steve H. DNA methylation age of human tissues and cell types. Genome Biology, 2013.
All of our services and products are intended for preclinical research use only and cannot be used to diagnose, treat or manage patients.
