Ronghao Zhou

Genetic and Epigenetic Changes of Aging

March 24, 2021

Genetic Influence on Longevity

            Aging is a complex progressive decline in functions and homeostasis. For centuries, aging had been thought to be an inevitable outcome of wear and tear; until 1993, when Cynthia Kenyon discovered a mutation in daf-2 could double lifespan of C. elegans without sacrificing the health (Kenyon et al., 1993). In a few years, the DNA sequence of daf-2 was solved which encodes the only insulin/insulin-like grown factor-I (IGF-1) receptor in C. elegans (Kimura et al., 1997). DAF-2 shares similarities to the insulin/IGF receptors of vertebrates, and through a signaling pathway involving phosphoinositide-3-kinase (PI3K), it negatively regulates DAF-16, a transcription factor in the FOXO family (Baumeister et al., 2006; Figure 1). In wide-type C. elegans, DAF-2 deactivates DAF-16 through phosphorylation; however, in daf-2 mutant worm, DAF-2 is absent and DAF-16 becomes active, turning on genes that are involved in stress resistance and longevity (Adams et al., 2008; Figure 1)

Figure 1: Schema of DAF-2, an insulin/IGF-1 receptor negatively regulated DAF-16 through a signaling cascade involving PI3K, and DAF-16 is responsible for turning on genes that are involved in stress resistance and longevity. Figure adapted from Adams et al., 2008.

Excited by the finding that lifespan could be doubled in C. elegans, scientists have looked closely at genetic influence on longevity in human through genome-wide association studies (GWAS). GWAS are usually used to compare genomes of healthy people vs diseased patients to find gene variants that are associated with this disease, hoping to understand more about the mechanism resulting in disease phenotype and potential targetable pathway for therapy. For longevity GWAS, scientists either compare the genomes between long-lived centarians and normal controls or look at the ages of death as the continuous phenotype (Deelen et al., 2019). Apolipoprotein E (APOE) has emerged as a candidate gene for longevity, and APOE ε4 variant is not only less likely to be in long-lived cases, but also associated with increased risk for Alzheimer’s disease and vascular disease (Sebastiani et al., 2019). Another candidate gene is forkhead box O3 (FOXO3), which is active when insulin/IGF signaling is reduced and encodes a transcription factor that upregulates genes involved in stress resistance and protein homeostasis, and potentially affect lifespan (Sanese et al., 2019).

However, APOE and FOXO3 are the only two genes associated with longevity that have been replicated in multiple population. The longevity GWASs have identified only a few other significant gene candidates, and the lack of replication for most reported associations remains a problem (Singh et al., 2019). Furthermore, the exact percentage of genetic influence on human lifespan has been widely debated, with estimates from 25% based on twin studies to 12.2-16.1% based on large-scale population data (Sebastiani et al., 2019). A more recent study suggests the percentage is even lower, probably less than 7% (Ruby et al., 2018).

 

Genetic Changes of Aging

The rate of aging differs immensely among individuals and between tissues, therefore, the chronological age is not an accurate representation of the aging process, and it is better to measure physiological age in each organ/tissue. Several longitudinal studies were performed with the belief that aging is better to be studied in the same individuals throughout their lifespan (Wheeler et al., 2011). The Baltimore Longitudinal Study of Ageing (BLSA) is the longest running study of human aging in America (Ferrucci, 2008). Started in 1958, BLSA recruits healthy volunteers aged 18 and older to have their physical and cognitive changes measured every 4 years (for under 60), 2 years (for 60-79), or year (for above 80). Two major conclusions that are drawn from the data are that changes from aging do not inevitably lead to diseases, and no single chronological timetable for human aging.

Recently, multi-omic measurements, including genomic, transcriptomic, proteomic, metabolomic, and microbiomic, have been used in longitudinal studies to discover biological aging markers. Ageotype is the distinguished aging pattern for each individual (Ahadi et al., 2020). It is defined by how the molecular pathways change over time in that particular individual, reflecting personal lifestyle and medical history, and can be used to monitor and intervene the aging process in early stage (Ahadi et al., 2020).

 

Cellular Changes of Aging

In 1961, Hayflick and Moorhead reported that primary fibroblasts in culture undergo a finite number of cell divisions (Hayflick et al., 1961), which is now known as Hayflick limit or replicative senescence. Senescence, the permanent cell cycle arrest, has been found to be both a hallmark of aging and a driver of aging (Wang et al., 2021). Senescence could be induced by a variety of cellular damages, for instance, DNA damage, epigenomic alterations, oxidative stress, mitochondrial dysfunction, oncogene overexpression, and cell cycle arrest (Fujita, 2019; Figure 2), as a potential mechanism to avoid malignant transformation.

Figure 2: Inducers of senescence

Replicative senescence is caused by erosion of telomere (Figure 2), which is the repetitive nucleotide sequences at the end of linear chromosomes. During each cell division, since DNA is synthesized 5’ to 3’ and needs an RNA primer to initiate the replication, a small portion of 5’ end DNA gets lost (Shammas, 2011). When telomere length reaches a threshold, the cell undergoes senescence and/or apoptosis, to prevent from infinite division as a tumor suppressor. However, it also limits stem cell regeneration during aging, and it has been proposed a correlation between telomere shortening and somatic stem cell decline (Collado et al., 2007). Shorter telomeres have been associated with increased incidence of disease, so telomere length could serve as a biological clock to determine the lifespan (Shammas, 2011).

Besides the tumor suppressive mechanism of senescence, the dark side of senescence has also been revealed: senescence-associated secretory phenotype (SASP). Senescent cells are still metabolically active, and secrete high levels of proinflammatory cytokines, interleukins, proteases, and growth factors (Faget et al., 2019). The expression of SASP factors directly modulates local cells, has deleterious effects on the tissue microenvironment and the ability to promote tumor progression (Coppé et al., 2010). Senolytics are small molecules that selectively induce apoptosis in senescent cells, thus they could potentially treat age-related damages caused by SASP. Several senolytic agents have been translated from pre-clinical models into clinical interventions to alleviate multiple senescence-related phenotypes (Kirkland et al., 2017).

 

Epigenetic Changes & Markers of Aging

Epigenomic decides how cell types express the same genome differently to have cell-type specific phenotypes. Environmental conditions can affect cellular epigenome to regulate gene expressions and cell fate, potentially influencing the aging process (Zhang et al., 2020). Alterations in DNA methylation, histone post-translational modification, and chromatin organization and remodeling have been shown to influence healthspan and lifespan (Sen et al., 2016; Figure 3).

Figure 3: Representation of chromosome, chromatin, histone, and DNA methylation as epigenetic regulators of aging.

 

DNA methylation is the additional of a methyl group to DNA molecular. The most abundant type of DNA methylation in eukaryotes is cytosine 5-methylation, and DNA methylation in promoter tends to repress gene expression. Cross-sectional studies have revealed differences in DNA methylation associated with age, and epigenetic clocks have used DNA methylation at selected set of CpG sites (70% promoters contain CpG sites) to measure the biological age (Bell et al., 2019).

Histone is the protein that DNA wraps around to prevent tangling, protect damages, and pack DNA into tightly packed chromatin. Histones are subject to post-translational modifications such as lysine methylation and acetylation; histone 3 lysine 4 trimethylation (H3K4me3) tends to activate gene expression, and H3K27me3 represses expression (Sen et al., 2016). Histone modifications in flies have been found to influence lifespan, but the effect tends to be less global and targeted to expression changes of specific genes involved in stress tolerance (Sen et al., 2016). In yeast, the consequence of histone loss during aging is global transcriptional activation, and many of these age-related changes can be improved with increasing the histones presence (Hu et al., 2014).

Chromatin accessibility, deciding whether the gene can be expressed or not, has been found to be associated with cell type-specific gene expression programs and varies with aging (Zhang et al., 2020).

 

Healthspan

It has been long assumed that lifespan and healthspan are correlated, however, they are not. There has been a global increase in human lifespan, but longevity doesn’t mean extended healthspan (Hansen et al., 2016). A recent study published a genome-wide RNAi screen for behavioral deterioration in aging C. elegans, and have identified two genes that are conserved in human (Yuan et al., 2020). These human orthologues increase expression with age, and knock down of one of them could help with age-dependent weight gain and prevent cognitive decline in aging mouse (Yuan et al., 2020). More and more studies now aim at looking for achieving healthy aging for better life.

 

Reference:

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