Age Prediction Based on DNA Methylation

INQUIRY

DNA methylation levels across the genome and at specific sequences were associated with age-related changes, with methylation levels at sites such as CpG islands increasing with age. This discovery drives the development of age prediction models that allow us to build models based on the correlation between changes in DNA methylation levels and chronological age, using these models as a predictive benchmark to measure the true biological age. DNA methylation may be the most potential predictor of age, which can be used in health detection, disease prediction, and longevity research.

CD BioSciences can help our clients achieve greater success in biological age prediction and aging and longevity research by providing DNA methylation age clock technology services.

Sample Requirements

Sample types	Quantity	Requirements
Blood sample	> 3 mL	EDTA anticoagulation tube collection, invert, and mix.
Saliva sample	> 2 mL	Use a commercial saliva collection kit and rinse your mouth before collection.
Cell sample	> 10⁶ cells	Remove the culture medium and freeze in liquid nitrogen.
Tissue sample	> 500 mg	Divide into 50 mg size, quick-frozen in liquid nitrogen.
DNA sample	> 1 μg	No pollution and no residue, concentration ≥ 20 ng/μL.

Overview of Our DNA Methylation-Based Age Prediction Services

We collect datasets including samples from different tissues/cells, analyze genomic DNA methylation status on a large scale with array/sequencing-based methods, calculate correlations between age and methylation levels by statistical analysis, and further develop age prediction models.

Human Age Prediction Based on DNA Methylation

Human Age Prediction Based on DNA Methylation

We employ age prediction models and various statistical methods to determine the biological age based on age-related methylation changes at specific CpG loci. Our clients can provide blood, saliva, skin, or other tissue/cell samples according to their specific needs.

Animal Age Prediction Based on DNA Methylation

Animal Age Prediction Based on DNA Methylation

Beyond human studies, CD BioSciences extends its DNA methylation-based age prediction services to diverse animal species. Our comprehensive approach encompasses mammals, birds, reptiles, and fish, offering valuable insights into the aging processes across different organisms. Through these services, our clients can unravel the intricacies of aging and develop potential interventions for promoting healthy aging in animals.

Applications of DNA Methylation-Based Age Prediction

Aging research
We utilize DNA methylation age prediction as a valuable tool for studying the aging process at the molecular level. It enables researchers to understand the biological mechanisms underlying aging, identify age-related changes, and explore potential interventions to promote healthy aging.
Longevity studies
By predicting biological age based on DNA methylation patterns, our clients can assess the effects of different interventions on lifespan and longevity. Our services can lead to the development of strategies for extending healthy lifespan and mitigating age-related diseases.
Age-related disease research
We employ DNA methylation age prediction in studying age-related diseases such as cancer, neurodegenerative disorders, and cardiovascular diseases. Our services allow researchers to investigate the relationship between epigenetic changes, biological age, and disease onset, potentially leading to the identification of new therapeutic targets.

With an innovative technology platform, a first-class experimental team, and years of service experience, we can provide customers with high-quality research services in multiple fields and better meet their needs. The scientists at CD BioSciences are committed to bringing together advanced and innovative DNA methylation clock technical experience to help our clients start their research journeys on aging and longevity. For more details, please contact us.

All of our services and products are intended for preclinical research use only and cannot be used to diagnose, treat or manage patients.