Integrated Multi-Omics Analysis in Aging

The recent progress made in high-throughput technologies has paved the way for omics studies that offer new avenues to comprehend the mechanisms underlying aging and the pathological progression of diverse, complex age-related diseases. Multiple biological pathways, including genome, transcriptome, proteome, and metabolome, typically act together within the intricate process of aging to influence and execute biological operations.

Fig. 1 Schematic diagram of an integrated multi-omics approach to the research. (Wu L, et al., 2022)

Single omics techniques can only shed limited light on the biological mechanisms of aging and disease. To change this, CD Bioscience can systematically reveal the molecular mechanisms of aging at a multimolecular level by integrating multi-omics technologies.

Overview of Our Multi-Omics Analysis

Our multi-omics analysis refers to the integration of multiple omics technologies, such as genomics, transcriptomics, proteomics, immunomics, metabolomics, epigenomics, single-cell omics, and spatial omics to provide a comprehensive understanding of the aging process. So, we can capture a wide range of biological information at different levels, including genetic variations, gene expression patterns, protein abundance, metabolite profiles, epigenetic modifications, and more!

Systems-level network analysis of the aging process

Through multi-omic analysis, we explore molecular interaction networks and regulatory pathways associated with aging to uncover key molecular players and interactions driving aging processes.

Comparative multi-omics aging analysis

We provide a comparative analysis of multi-omics data between healthy aging and age-related disease cohorts to elucidate differences in molecular signatures and pathways.

Workflow for Analysis of Aging Multi-Omics Data

• Data generation and preprocessing
  We employ various technologies to generate high-quality omics data from aging samples. Then, our team of experts performs rigorous data preprocessing steps, including quality control, data normalization, and removal of technical biases, to ensure the reliability and accuracy of the data.
• Data integration
  Integration of multi-omics data is a critical step in our analysis pipeline. We employ advanced computational methods and statistical models to integrate different omics datasets. Considering the complexity and heterogeneity of aging, we not only provide static maps of molecules but are also used to characterize the mutual changes of molecules over time.
• Integrated data analysis
  Once the data is integrated, we perform comprehensive statistical analyses and bioinformatics approaches, primarily data dimensionality reduction and normalization methods such as multifactor analysis or partial least squares regression analysis.

Applications of Multi-Omics in Aging Studies

We have successfully applied multi-omics approaches to various aspects of aging research, leading to significant advancements in the field.

Identification of aging biomarkers

Through the analysis of multi-omics data, CD BioSciences has identified a range of biomarkers associated with aging. These biomarkers can serve as indicators of biological age and provide valuable insights into the aging process.

Characterization of age-related pathways

CD BioSciences has contributed to the elucidation of key pathways involved in aging through multi-omics analysis, such as those related to oxidative stress, inflammation, mitochondrial dysfunction, and cellular senescence. Understanding these pathways provides a foundation for the development of therapeutics targeting age-related diseases.

Drug discovery and novel anti-aging targets

By integrating omics data from aging samples with drug target information and molecular databases, CD BioSciences has been able to identify potential drug candidates for age-related diseases. Additionally, multi-omics analysis can uncover new therapeutic targets and provide insights into the mechanisms of action of existing drugs.

CD BioSciences has harnessed the potential of multi-omics analysis to advance our knowledge of aging and its associated diseases. If you are interested in our services, please feel free to contact us or make an online inquiry.

Reference

1. Wu L, et al. Integrated Multi-Omics for Novel Aging Biomarkers and Antiaging Targets. Biomolecules, 2022; 12 (1): 39.