A network-based meta-analysis for characterizing the genetic landscape of human aging

Cross-Species and Human Inter-Tissue Network Analysis of Genes Implicated in Longevity and Aging Reveal Strong Support for Nutrient Sensing

Intensive research efforts have been undertaken to slow human aging and therefore potentially delay the onset of age-related diseases. These efforts have generated an enormous amount of high-throughput data covering different levels in the physiologic hierarchy, e.g., genetic, epigenetic, transcriptomic, proteomic, and metabolomic, etc. We gathered 15 independent sources of information about genes potentially involved in human longevity and lifespan (N = 5836) and subjected them to various integrated analyses. Many of these genes were initially identified in non-human species, and we investigated their orthologs in three non-human species [i.e., mice (N = 967), fruit fly (N = 449), and worm (N = 411)] for further analysis. We characterized experimentally determined protein-protein interaction networks (PPIN) involving each species' genes from 9 known protein databases and studied the enriched biological pathways among the individually constructed PPINs. We observed three important signaling pathways: FoxO signaling, mTOR signaling, and autophagy to be common and highly enriched in all four species (p-value ≤ 0.001). Our study implies that the interaction of proteins involved in the mechanistic target of rapamycin (mTOR) signaling pathway is somewhat limited to each species or that a "rewiring" of specific networks has taken place over time. To corroborate our findings, we repeated our analysis in 43 different human tissues. We investigated conserved modules in various tissue-specific PPINs of the longevity-associated genes based upon their protein expression. This analysis also revealed mTOR signaling as shared biological processes across four different human tissue-specific PPINs for liver, heart, skeletal muscle, and adipose tissue. Further, we explored our results' translational potential by assessing the protein interactions with all the reported drugs and compounds that have been experimentally verified to promote longevity in the three-comparator species. We observed that the target proteins of the FDA-approved drug rapamycin (a known inhibitor of mTOR) were conserved across all four species. Drugs like melatonin and metformin exhibited shared targets with rapamycin in the human PPIN. The detailed information about the curated gene list, cross-species orthologs, PPIN, and pathways was assembled in an interactive data visualization portal using RStudio's Shiny framework (https://agingnetwork.shinyapps.io/frontiers/).

Global Single Clustering of Phenotype-Associated Human Aging Genes in the Co-Expression and Physical Interaction Networks: An OMIM-Based Investigative Review

BACKGROUND

While a large wealth of literature on aging pertains to in silico, experimental, and predicted genes, many of those genes do not have validated phenotypic consequences in human. Online Mendelian Inheritance in Man (OMIM) provides an exceptional compendium of authoritative, validated aging genes and phenotypes, the interactions among which may enhance the overall perspective of aging mechanisms in human.

METHODS

Here, we reviewed and investigated the global clustering pattern of the OMIM-indexed aging genes (until April 2021) in the gene co-expression and physical interaction networks, using the two keywords "aging" and "ageing". To allow for validity check, we randomly selected six sets of genes from the human genome as control genes, each set consisting of a similar number of genes obtained from the OMIM search. STRING was implemented in the weighted setting and using the edge betweenness parameter, to construct the integrated and tissue-specific networks of the age-related and control genes.

RESULTS

286 aging (ageing) genes and a wide spectrum of 96 associated phenotypes were detected, including late-onset neurodegenerative disorders, cancers, osteoarthritis, and longevity. Despite the general terms used and the vast range of age-related phenotypes, we detected single clustering of the OMIM-extracted aging (ageing) genes in each of the integrated weighted co-expression and physical interaction networks (p<0.0005), as opposed to multiple clustering of the control genes (p≥0.04). TP53 was the overlapping hub gene in each of the networks. Three genes, TP53, APP, and SIRT1 were the consistent hub genes co-expressed across eleven selected human tissues frequently affected by age-related phenotypes.

CONCLUSION

We propose predominant single clustering of the human phenotype-associated aging genes in the co-expression and physical interaction networks, and list the top pathways and genes involved.

Proteodynamics and aging of eukaryotic cells

All aspects of each protein existence in the eukaryotic cells, starting from the pre-translation events, through translation, multiple different post-translational modifications, functional life and eventual proteostatic removal after loss of functionality and changes in physico-chemical properties, can be collectively called the proteodynamics. With aging, passing of time as well as accumulating effects of exposures, interactions and wearing-off lead to problems at each of the above mentioned stages, eventually leading to general malfunction of the proteome. This work briefly reviews and summarizes current knowledge concerning this important topic.

Weighted Gene Correlation Network Meta-Analysis Reveals Functional Candidate Genes Associated with High- and Sub-Fertile Reproductive Performance in Beef Cattle

Improved reproductive efficiency could lead to economic benefits for the beef industry, once the intensive selection pressure has led to a decreased fertility. However, several factors limit our understanding of fertility traits, including genetic differences between populations and statistical limitations. In the present study, the RNA-sequencing data from uterine samples of high-fertile (HF) and sub-fertile (SF) animals was integrated using co-expression network meta-analysis, weighted gene correlation network analysis, identification of upstream regulators, variant calling, and network topology approaches. Using this pipeline, top hub-genes harboring fixed variants (HF × SF) were identified in differentially co-expressed gene modules (DcoExp). The functional prioritization analysis identified the genes with highest potential to be key-regulators of the DcoExp modules between HF and SF animals. Consequently, 32 functional candidate genes (10 upstream regulators and 22 top hub-genes of DcoExp modules) were identified. These genes were associated with the regulation of relevant biological processes for fertility, such as embryonic development, germ cell proliferation, and ovarian hormone regulation. Additionally, 100 candidate variants (single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs)) were identified within those genes. In the long-term, the results obtained here may help to reduce the frequency of subfertility in beef herds, reducing the associated economic losses caused by this condition.

DNA methylation QTL analysis identifies new regulators of human longevity

Human longevity is a complex trait influenced by both genetic and environmental factors, whose interaction is mediated by epigenetic mechanisms like DNA methylation. Here, we generated genome-wide whole-blood methylome data from 267 individuals, of which 71 were long-lived (90-104 years), by applying reduced representation bisulfite sequencing. We followed a stringent two-stage analysis procedure using discovery and replication samples to detect differentially methylated sites (DMSs) between young and long-lived study participants. Additionally, we performed a DNA methylation quantitative trait loci analysis to identify DMSs that underlie the longevity phenotype. We combined the DMSs results with gene expression data as an indicator of functional relevance. This approach yielded 21 new candidate genes, the majority of which are involved in neurophysiological processes or cancer. Notably, two candidates (PVRL2, ERCC1) are located on chromosome 19q, in close proximity to the well-known longevity- and Alzheimer's disease-associated loci APOE and TOMM40. We propose this region as a longevity hub, operating on both a genetic (APOE, TOMM40) and an epigenetic (PVRL2, ERCC1) level. We hypothesize that the heritable methylation and associated gene expression changes reported here are overall advantageous for the LLI and may prevent/postpone age-related diseases and facilitate survival into very old age.

Network analysis of human muscle adaptation to aging and contraction

Resistance exercise (RE) remains a primary approach for minimising aging muscle decline. Understanding muscle adaptation to individual contractile components of RE (eccentric, concentric) might optimise RE-based intervention strategies. Herein, we employed a network-driven pipeline to identify putative molecular drivers of muscle aging and contraction mode responses. RNA-sequencing data was generated from young (21±1 y) and older (70±1 y) human skeletal muscle before and following acute unilateral concentric and contralateral eccentric contractions. Application of weighted gene co-expression network analysis identified 33 distinct gene clusters ('modules') with an expression profile regulated by aging, contraction and/or linked to muscle strength. These included two contraction 'responsive' modules (related to 'cell adhesion' and 'transcription factor' processes) that also correlated with the magnitude of post-exercise muscle strength decline. Module searches for 'hub' genes and enriched transcription factor binding sites established a refined set of candidate module-regulatory molecules (536 hub genes and 60 transcription factors) as possible contributors to muscle aging and/or contraction responses. Thus, network-driven analysis can identify new molecular candidates of functional relevance to muscle aging and contraction mode adaptations.

Genetics of Human Longevity Within an Eco-Evolutionary Nature-Nurture Framework

Human longevity is a complex trait, and to disentangle its basis has a great theoretical and practical consequences for biomedicine. The genetics of human longevity is still poorly understood despite several investigations that used different strategies and protocols. Here, we argue that such rather disappointing harvest is largely because of the extraordinary complexity of the longevity phenotype in humans. The capability to reach the extreme decades of human lifespan seems to be the result of an intriguing mixture of gene-environment interactions. Accordingly, the genetics of human longevity is here described as a highly context-dependent phenomenon, within a new integrated, ecological, and evolutionary perspective, and is presented as a dynamic process, both historically and individually. The available literature has been scrutinized within this perspective, paying particular attention to factors (sex, individual biography, family, population ancestry, social structure, economic status, and education, among others) that have been relatively neglected. The strength and limitations of the most powerful and used tools, such as genome-wide association study and whole-genome sequencing, have been discussed, focusing on prominently emerged genes and regions, such as apolipoprotein E, Forkhead box O3, interleukin 6, insulin-like growth factor-1, chromosome 9p21, 5q33.3, and somatic mutations among others. The major results of this approach suggest that (1) the genetics of longevity is highly population specific; (2) small-effect alleles, pleiotropy, and the complex allele timing likely play a major role; (3) genetic risk factors are age specific and need to be integrated in the light of the geroscience perspective; (4) a close relationship between genetics of longevity and genetics of age-related diseases (especially cardiovascular diseases) do exist. Finally, the urgent need of a global approach to the largely unexplored interactions between the 3 genetics of human body, that is, nuclear, mitochondrial, and microbiomes, is stressed. We surmise that the comprehensive approach here presented will help in increasing the above-mentioned harvest.

Genetic and epigenetic regulation of human aging and longevity

Here we summarize the latest data on genetic and epigenetic contributions to human aging and longevity. Whereas environmental and lifestyle factors are important at younger ages, the contribution of genetics appears more important in reaching extreme old age. Genome-wide studies have implicated ~57 gene loci in lifespan. Epigenomic changes during aging profoundly affect cellular function and stress resistance. Dysregulation of transcriptional and chromatin networks is likely a crucial component of aging. Large-scale bioinformatic analyses have revealed involvement of numerous interaction networks. As the young well-differentiated cell replicates into eventual senescence there is drift in the highly regulated chromatin marks towards an entropic middle-ground between repressed and active, such that genes that were previously inactive "leak". There is a breakdown in chromatin connectivity such that topologically associated domains and their insulators weaken, and well-defined blocks of constitutive heterochromatin give way to generalized, senescence-associated heterochromatin, foci. Together, these phenomena contribute to aging.

Computational Drug Screening Identifies Compounds Targeting Renal Age-associated Molecular Profiles

Aging is a major driver for chronic kidney disease (CKD) and the counterbalancing of aging processes holds promise to positively impact disease development and progression.

In this study we generated a signature of renal age-associated genes (RAAGs) based on six different data sources including transcriptomics data as well as data extracted from scientific literature and dedicated databases. Protein abundance in renal tissue of the 634 identified RAAGs was studied next to the analysis of affected molecular pathways. RAAG expression profiles were furthermore analysed in a cohort of 63 CKD patients with available follow-up data to determine association with CKD progression. 23 RAAGs were identified showing concordant regulation in renal aging and CKD progression. This set was used as input to computationally screen for compounds with the potential of reversing the RAAG/CKD signature on the transcriptional level. Among the top-ranked drugs we identified atorvastatin, captopril, valsartan, and rosiglitazone, which are widely used in clinical practice for the treatment of patients with renal and cardiovascular diseases. Their positive impact on the RAAG/CKD signature could be validated in an in-vitro model of renal aging.

In summary, we have (i) consolidated a set of RAAGs, (ii) determined a subset of RAAGs with concordant regulation in CKD progression, and (iii) identified a set of compounds capable of reversing the proposed RAAG/CKD signature.

Identifying Potential Ageing-Modulating Drugs In Silico

Increasing human life expectancy has posed increasing challenges for healthcare systems. As people age, they become more susceptible to chronic diseases, with an increasing burden of multimorbidity, and the associated polypharmacy. Accumulating evidence from work with laboratory animals has shown that ageing is a malleable process that can be ameliorated by genetic and environmental interventions. Drugs that modulate the ageing process may delay or even prevent the incidence of multiple diseases of ageing. To identify novel, anti-ageing drugs, several studies have developed computational drug-repurposing strategies. We review published studies showing the potential of current drugs to modulate ageing. Future studies should integrate current knowledge with multi-omics, health records, and drug safety data to predict drugs that can improve health in late life.

Using the drug-protein interactome to identify anti-ageing compounds for humans

Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established their association with ageing at multiple levels of biological action including pathways, functions and protein interactions. Finally, combining all the data, we calculated a ranked list of drugs that identified tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans.

Human life expectancy is continuing to increase worldwide, as a result of successive improvements in living conditions and medical care. Although this trend is to be celebrated, advancing age is the major risk factor for multiple impairments and chronic diseases. As a result, the later years of life are often spent in poor health and lowered quality of life. However, these effects of ageing are not inevitable, because very long-lived people often suffer rather little ill-health at the end of their lives. Furthermore, laboratory experiments have shown that animals fed with specific drugs can live longer and with fewer age-related diseases than their untreated companions. We therefore need to identify drugs with anti-ageing properties for humans. We have used publically available data and a computer-based approach to search for drugs that affect components and processes known to be important in human ageing. This approach worked, because it was able to re-discover several drugs known to increase lifespan in animal models, plus some new ones, including one that we tested experimentally and validated in this study. These drugs are now a high priority for animal testing and for exploring effects on human ageing.

Impact of Growth Hormone-Related Mutations on Mammalian Aging

Mutations of a single gene can lead to a major increase in longevity in organisms ranging from yeast and worms to insects and mammals. Discovering these mutations (sometimes referred to as “longevity genes”) led to identification of evolutionarily conserved molecular, cellular, and organismal mechanisms of aging. Studies in mice provided evidence for the important role of growth hormone (GH) signaling in mammalian aging. Mice with mutations or gene deletions leading to GH deficiency or GH resistance have reduced body size and delayed maturation, but are healthier and more resistant to stress, age slower, and live longer than their normal (wild type) siblings. Mutations of the same genes in people can provide remarkable protection from age-related disease, but have no consistent impact on lifespan. Ongoing research indicates that genetic defects in GH signaling are linked to extension of healthspan and lifespan via a variety of interlocking mechanism, including improvements in genome and stem cell maintenance, stress resistance, glucose homeostasis, and thermogenesis, along with reductions in the mechanistic target of rapamycin (mTOR) C1 complex signaling and in chronic low grade inflammation.