Simply Put
In this project, the long-standing expertise of the Artyomov lab in the field of system-level multi-omics will be used for the creation of a multi-functional research center. The center will focus on understanding and manipulating human immune aging using cutting-edge approaches in spatial and single-cell transcriptional profiling, data mining, and computational biology and immunology.
The Human Aging Hub, developed at the Washington University in St.Louis, will establish 4 core research directions:
- Deep immunophenotyping of the human PBMC using multidimensional approaches such as mass-cytometry, proteomics, metabolomics, single-cell RNA-sequencing, DNA methylation profiling etc.
- Integrated spatial profiling of human tissues at various ages on the level of protein imaging and spatial transcriptomics.
- Interventional clinical trial in healthy aging adults with agent(s) directed against immune aging.
- Establish centralized effort for meta-analysis of the available and newly generated data in human aging and development of the cutting-edge computational pipelines.
These four directions are closely linked. Not only will they address specific research directions but will also enable points of community growth by providing optimized resources such as optimized human blood immunophenotyping panels, complete protocols and panels for human tissue protein and transcriptome imaging, computational resources for the data meta-analysis and collaborative data-heavy projects within the community.
Description
a. Deep Immunophenotyping of PBMC and tissue samples from sedentary and physically active young/aged individuals
The Artyomov lab will serve as omics center for high-throughput data generation and analysis for the samples from the cross-sectional cohorts of sedentary and active aging that are collected in the project led by Prof. Stephen Harridge and Prof. Janet Lord. The complete cohort includes ~290 individuals. The collected plasma and PBMCs will be profiled using proteomics, clinical biochemistry, cytokine panel, metabolomic and lipidomic profiling for plasma samples and using multidimensional cytometry for PBMC samples. Additionally, the Artyomov lab will perform single-cell resolution transcriptional and epigenetic profiling along with bulk DNA methylation and RNA-seq profiling of the tissue samples collected by the Harridge lab. The data from skin, adipose and muscle tissues will be compared between samples from young and old individuals for the subset of the donors from the same cohort.
Resulting data will be analyzed to establish age-associated differences within the individual features (DNA methylation, cell proportion, transcript levels, accessible chromatin, cytokine levels etc) as well as to establish interrelations between different layers of regulation.
b. Integrated spatial profiling of human tissues between young and old individuals.
Three solid tissues (e.g., lung, liver and colon) – will be profiled and compared between healthy young and old groups. Each age group will include 30 samples equally split between sexes. All samples will be profiled using three technologies: single-nuclei RNA-seq, spatial transcriptomics and spatial protein profiling with ~40-50 selected protein markers (CODEX). This integrated approach will yield unprecedented level of resolution for the tissue-specific features of aging, which will be defined in a spatially resolved manner, integrating cellular (e.g., immune infiltration) and structural (e.g., collagenization) changes associated with aging.
The three profiling techniques are complimentary approaches that comprehensively describe aging tissue architecture. Specifically, single-nuclei RNA-seq will yield comprehensive description of the tissue cell types, their fractional changes and cell-specific markers. This data will be used to analyze spatial transcriptomic profiles which cover large area yet do not allow for the single-cell resolution, i.e. individual transcriptional spots will have to be computationally deconvolved to define cell types located in dedicated areas. Transcriptional profiling will provide unbiased picture of the tissue aging, which would still be limited in terms of the spatial resolution. Therefore, CODEX spatial protein profiling will be applied in order to achieve spatial profiling at a single-cell resolution. Spatial protein profiling is limited by simultaneous identification of 40-50 protein markers, and snRNA-seq and spatial transcriptomics data will be critical to create informative panel of protein profiling/imaging targets.
c. Interventional human anti-aging clinical trial.
The previous work at the Artyomov Lab, as well as work from other labs, has demonstrated various aspects of age-associated remodelling of the human immune system. Some lifestyle interventions, such as active exercise or calorie restriction, have recently been shown to “rejuvenate” the immune system to some degree. Given the range of recently developed immunomodulatory approaches (especially in the context of anti-cancer immunotherapy), it is conceivable that interventional perturbations with biologically active molecules can have a positive effect on the aging immune system.
The key determinants of immune aging in the blood previously established in the Artyomov Lab will help to evaluate clinical interventions in terms of efficacy against immune aging. Our priority will be to investigate how supplements with the potential to restore redox balance in older individuals can affect immune system aging.
d. Computational center operations.
Altogether, there will be three computational scientists working on the specific projects. This type of dedicated computational work usually focuses on the specific data types and analysis of specific biological processes (transcription, DNA methylation, etc.) with limited cross-platform data analysis. Given the wealth of various data types, a dedicated computational scientist will oversee data infrastructure, data sharing, and management and focus scientifically on integrative data analysis across multiple projects and broad access to public repositories (e.g., dbGAP for human RNA-seq data availability). Altogether, computational scientists will operate as an integrated computational unit.
Results
a) Direct and consistent interactions between Steve Harridge (King’s College, UK) lab and Artyomov Lab (WashU, US) have been established. The initial set of samples from the Harridge Lab has been received. A number of PBMC samples have been profiled using a new cytometry panel developed at the Artyomov Lab.
b) Initial sets of tissue samples were acquired and CODEX panel of 47 proteins (for spatial protein imaging) has been assembled and scheduled to profile these samples in fall 2023. In the context of transcriptional spatial profiling, the protocol has been successfully optimized using mouse samples. The next step will be to assemble a corresponding human panel of 500 genes and to perform pilot runs of transcriptional profiling of collected tissues.
c) The IRB for the clinical trial has been approved, and the first batch of supplements has been produced in August 2023. The blood and urine collection pipeline has been tested, and the overall study’s logistics has been finalized with the Clinical Study Coordinator.