There is considerable growth in omics fields deriving from slices of proteomics, the study of the proteome, the proteins generated by a cell, and genomics, the study of the genome, the DNA that encodes those proteins. This means that the naming convention these days for areas of interest in molecular biochemistry, a particular subsection of the overall set of genes and proteins, is to coin new portmanteau terms ending in -ome and -omics. So here we have an open access paper that attempts a start on unifying on the one hand programmed aging theories in which aging is caused by genetic programs and on the other hand the more mainstream views on aging as an accumulation of damage that occurs as a side-effect of the normal operation of metabolism. In this paper the conceptual collection of genes, proteins, and alterations relevant to the regulation of aging or damage of aging are termed the deleteriome - relating to deleterious changes.
Different theories posit that aging is caused by molecular damage, genetic programs, continued development, hyperfunction, antagonistic pleiotropy alleles, mutations, trade-offs, incomplete repair, etc. Here, I discuss that these ideas can be conceptually unified as they capture particular facets of aging, while being incomplete. Their respective deleterious effects impact fitness at different levels of biological organization, adjusting progression through aging, rather than causing it. Living is associated with a myriad of deleterious processes, both random and deterministic, which are caused by imperfectness, exhibit cumulative properties, and represent the indirect effects of biological functions at all levels, from simple molecules to systems.
From this, I derive the deleteriome, which encompasses cumulative deleterious age-related changes and represents the biological age. This term encompasses molecular damage, consequences of additional deleterious processes, as well as increased disorder at all levels, from simple molecules to cells and organs. The organismal deleteriome consists of the deleteriomes of cells, organs, and systems, which change along roughly synchronized trajectories and may be assessed through biomarkers of aging. Aging is then a progressive decline in fitness due to the increasing deleteriome, adjusted by genetic, environmental, and stochastic processes.
Contributions of various factors to biological aging can be illustrated by the metaphor of an aging car. Here, the length of an organismal lifespan is analogous to the mileage driven over the car's lifespan. It is influenced by the make/model of the car (analogous to the effects of genetics) and road conditions, weather, and fuel quality (representing the effects of environment). Better built cars, like better road conditions, milder weather, and better fuel, will be associated with longevity. In addition, random processes influence lifespan. These stochastic events include internal processes of the car leading to damage accumulation, gradually increasing the chance the car breaks, as well as random events associated with driving (stopping, accelerating, turning, accidents, etc.). For example, a car driven on highways is expected to accrue more miles than when it is driven in city. Likewise, biological aging is influenced by genetics, which is a major contributor when aging is considered across species and genetically heterogeneous populations, environment, and stochastic processes.
As the deleteriome consists of diverse forms of damage and other deleterious processes, it is currently not accessible in its entirety. Difficulty in measurement notwithstanding, the deleteriome may be viewed as a measure of biological age of the cell, organ, or system. This implies that the best markers of aging would be the measures of the deleteriome. Such markers have not been well defined, as the focus of previous research has been on particular age-related changes, such as telomere length, oxidative damage, and expression of a limited number of genes. But such limited assays would be misleading in representing organismal aging and comparison across organisms and cell types. However, recent research shows that the candidate markers that best represent the deleteriome, because they include measurements of many diverse age-related parameters simultaneously, for example, genomewide epigenetic changes, mutations, nontargeted metabolite profiling and gene expression, offer the best predictive models of the progression through aging.