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Genomic Translation Across Species Core (GTASC)

Core Overview

The Genomic Translation Across Species Core (GTASC) Core, led by Eileen Crimmins and Em Arpawong at USC, will overcome a historical barrier of connecting geroscience research in model systems to human health and aging. The core will provide researchers utilizing model-organisms (yeast, worms, flies, fish, and mice) the ability to interrogate rich resources of human genomic, methylation, and expression data from large-scale, longitudinal, ethnically diverse, population-based datasets of aging. Evaluating hypotheses that are driven by findings from model-organisms in deeply phenotyped human data will provide important results in the context of human aging and facilitate innovative research directions across models.

Translation of findings in model organisms from biologists to clinicians in order to directly validate genetic, transcriptomic, or epigenetic associations with age-specific indicators of mortality, disease, and functionality in humans occurs very slowly for multiple reasons, as does bringing findings back to model systems for experimental manipulation to test for causality. The GTASC has a unique set of resources and expertise with which to facilitate these translational processes in diverse groups of normal aging samples, with a range of ages from 50 to 109, thereby enabling the potential to accelerate the rate of therapeutic discovery for many aging-related diseases.

Cores

The GTASC leverages expertise in the methods and analysis of the normal aging processes measured repeatedly in large-scale human-population aging-cohorts and makes these population-level resources accessible to biologists.

Depicted in Figure 1 is a simplified illustration of the cycle of research with model organisms, and where collaboration with the GTASC core can occur, at stage 3, after primary research and findings with regard to gene candidates or other molecular targets have been identified.

The GTAS core offers direct, efficient, and scalable translation of findings by:

  • Invoking expertise in curating phenotypes and hallmarks of human aging in large-scale, longitudinal and natural studies of human aging for validating findings from model organisms
  • Offering direct interrogation of hypotheses that harness genomic, epigenomic, and transcriptomic data that require high-performance computing resources and programming expertise
  • Providing recommendations with which to interrogate hypotheses in humans including both sex/genders, substantial race/ethnic diversity to consider population substructure, and behavioral and contextual differences in lifespan health
  • Employing methods for data analyses that utilize repeated measures for constructing more reliable phenotypes and that maximize statistical power
  • Conducting pathway analyses to predict empirically the downstream effects of a marker of interest (gene, protein, receptor, etc.) on biological and disease processes, predict activation and inhibition from upstream transcription factors, and compare affected pathways and phenotypes that have been manipulated in different testing conditions in order to inform genomic interrogation projects

Examples of pilot projects with GTASC can include genetic association analysis, gene-by-environment (GxE) and gene-by-gene (GxG) interaction analyses, differential gene expression, and pathway analysis. In human cohorts, for instance, a GxE analysis will define the “E” as a plausible moderator of genetic effects on a phenotype, such as behavioral modifiers (e.g., physical activity, BMI, biomarker for a metabolic factor).

A key component of the GTASC is to provide a unique service to internal investigators at USC/Buck and to external investigators who could benefit from our data analysis pipelines across a range of phenotypes and methods to support the design of new and innovative studies that will advance research on the biology of aging.

Core Leaders

Em Arpawong

GTASC Lead, The USC Leonard Davis School

Eileen Crimmins

GTASC Lead, The USC Leonard Davis School