Considerations for reproducible omics in aging research

Abstract

Technical advancements over the past two decades have enabled the measurement of the panoply of molecules of cells and tissues including transcriptomes, epigenomes, metabolomes and proteomes at unprecedented resolution. Unbiased profiling of these molecular landscapes in the context of aging can reveal important details about mechanisms underlying age-related functional decline and age-related diseases. However, the high-throughput nature of these experiments creates unique analytical and design demands for robustness and reproducibility. In addition, 'omic' experiments are generally onerous, making it crucial to effectively design them to eliminate as many spurious sources of variation as possible as well as account for any biological or technical parameter that may influence such measures. In this Perspective, we provide general guidelines on best practices in the design and analysis of omic experiments in aging research from experimental design to data analysis and considerations for long-term reproducibility and validation of such studies.

Figure 1:. Considerations for the use of “omics” in aging research.

In addition to general considerations for “omics” experiments, aging “omics” requires additional care in experimental design and data processing due to unique challenges. Important biological variables can interact with aging signatures and should be controlled for carefully (e.g. sex). In addition, due to timescales involved in aging research, there are also important technical issues to take into account (e.g. batch effects). Both biological considerations and technical considerations should be taken into account during data processing to extract features of aging at the “omic” level. Some elements created with BioRender.com.