LongevityMap: a database of human genetic variants associated with longevity

Maximum lifespan and brain size in mammals are associated with gene family size expansion related to immune system functions

Mammals exhibit an unusual variation in their maximum lifespan potential, measured as the longest recorded longevity of any individual in a species. Evidence suggests that lifespan increases follow expansion in brain size relative to body mass. Here, we found significant gene family size expansions associated with maximum lifespan potential and relative brain size but not in gestation time, age of sexual maturity, and body mass in 46 mammalian species. Extended lifespan is associated with expanding gene families enriched in immune system functions. Our results suggest an association between gene duplication in immune-related gene families and the evolution of longer lifespans in mammals. These findings explore the genomic features linked with the evolution of lifespan in mammals and its association with life story and morphological traits.

Robust and Adaptive Non-Parametric Tests for Detecting General Distributional Shifts in Gene Expression

Differential expression analysis is crucial in genomics, yet existing methods primarily focus on detecting mean shifts. Variance shifts in gene expression are well-documented in studies of cellular signaling pathways, and more recently they have characterized aging, thus motivating the need for flexible detection approaches that include tests of expression variance changes. In this work, we present QRscore (Quantile Rank Score), a general method for detecting distributional shifts in gene expression by extending the Mann-Whitney test into a flexible family of rank-based tests. Here, we focus on implementing QRscore to detect shifts in mean and variance in gene expression, using weights designed from negative binomial (NB) and zero-inflated negative binomial (ZINB) models to combine the strengths of parametric and non-parametric approaches. We show through simulations that QRscore not only achieves high statistical power while controlling the false discovery rate (FDR), but also outperforms existing methods in detecting variance shifts and mean shifts. Applying QRscore to bulk RNA-seq data from the Genotype-Tissue Expression (GTEx) project, we identified numerous differentially dispersed genes and differentially expressed genes across 33 tissues. Notably, many genes have significant variance shifts but non-significant mean shifts. QRscore augments the genome bioinformatics toolkit by offering a powerful and flexible approach for differential expression analysis. QRscore is available in R, at https://github.com/songlab-cal/QRscore.

Investigation of human aging at the single-cell level

Human aging is characterized by a gradual decline in physiological functions and an increased susceptibility to various diseases. The complex mechanisms underlying human aging are still not fully elucidated. Single-cell sequencing (SCS) technologies have revolutionized aging research by providing unprecedented resolution and detailed insights into cellular diversity and dynamics. In this review, we discuss the application of various SCS technologies in human aging research, encompassing single-cell, genomics, transcriptomics, epigenomics, and proteomics. We also discuss the combination of multiple omics layers within single cells and the integration of SCS technologies with advanced methodologies like spatial transcriptomics and mass spectrometry. These approaches have been essential in identifying aging biomarkers, elucidating signaling pathways associated with aging, discovering novel aging cell subpopulations, uncovering tissue-specific aging characteristics, and investigating aging-related diseases. Furthermore, we provide an overview of aging-related databases that offer valuable resources for enhancing our understanding of the human aging process.

Oxidative stress-induced gene expression changes in prostate epithelial cells in vitro reveal a robust signature of normal prostatic senescence and aging

Oxidative stress has long been postulated to play an essential role in aging mechanisms, and numerous forms of molecular damage associated with oxidative stress have been well documented. However, the extent to which changes in gene expression in direct response to oxidative stress are related to actual cellular aging, senescence, and age-related functional decline remains unclear. Here, we ask whether H2O2-induced oxidative stress and resulting gene expression alterations in prostate epithelial cells in vitro reveal gene regulatory changes typically observed in naturally aging prostate tissue and age-related prostate disease. While a broad range of significant changes observed in the expression of non-coding transcripts implicated in senescence-related responses, we also note an overrepresentation of gene-splicing events among differentially expressed protein-coding genes induced by H2O2. Additionally, the collective expression of these H2O2-induced DEGs is linked to age-related pathological dysfunction, with their protein products exhibiting a dense network of protein-protein interactions. In contrast, co-expression analysis of available gene expression data reveals a naturally occurring highly coordinated expression of H2O2-induced DEGs in normally aging prostate tissue. Furthermore, we find that oxidative stress-induced DEGs statistically overrepresent well-known senescence-related signatures. Our results show that oxidative stress-induced gene expression in prostate epithelial cells in vitro reveals gene regulatory changes typically observed in naturally aging prostate tissue and age-related prostate disease.

Circadian-driven tissue specificity is constrained under caloric restricted feeding conditions

Tissue specificity is a fundamental property of an organ that affects numerous biological processes, including aging and longevity, and is regulated by the circadian clock. However, the distinction between circadian-affected tissue specificity and other tissue specificities remains poorly understood. Here, using multi-omics data on circadian rhythms in mice, we discovered that approximately 35% of tissue-specific genes are directly affected by circadian regulation. These circadian-affected tissue-specific genes have higher expression levels and are associated with metabolism in hepatocytes. They also exhibit specific features in long-reads sequencing data. Notably, these genes are associated with aging and longevity at both the gene level and at the network module level. The expression of these genes oscillates in response to caloric restricted feeding regimens, which have been demonstrated to promote longevity. In addition, aging and longevity genes are disrupted in various circadian disorders. Our study indicates that the modulation of circadian-affected tissue specificity is essential for understanding the circadian mechanisms that regulate aging and longevity at the genomic level.

Genetics of human longevity: From variants to genes to pathways

The current increase in lifespan without an equivalent increase in healthspan poses a grave challenge to the healthcare system and a severe burden on society. However, some individuals seem to be able to live a long and healthy life without the occurrence of major debilitating chronic diseases, and part of this trait seems to be hidden in their genome. In this review, we discuss the findings from studies on the genetic component of human longevity and the main challenges accompanying these studies. We subsequently focus on results from genetic studies in model organisms and comparative genomic approaches to highlight the most important conserved longevity-associated pathways. By combining the results from studies using these different approaches, we conclude that only five main pathways have been consistently linked to longevity, namely (1) insulin/insulin-like growth factor 1 signalling, (2) DNA-damage response and repair, (3) immune function, (4) cholesterol metabolism and (5) telomere maintenance. As our current approaches to study the relevance of these pathways in humans are limited, we suggest that future studies on the genetics of human longevity should focus on the identification and functional characterization of rare genetic variants in genes involved in these pathways.

Open Genes-a new comprehensive database of human genes associated with aging and longevity

The Open Genes database was created to enhance and simplify the search for potential aging therapy targets. We collected data on 2402 genes associated with aging and developed convenient tools for searching and comparing gene features. A comprehensive description of genes has been provided, including lifespan-extending interventions, age-related changes, longevity associations, gene evolution, associations with diseases and hallmarks of aging, and functions of gene products. For each experiment, we presented the necessary structured data for evaluating the experiment's quality and interpreting the study's findings. Our goal was to stay objective and precise while connecting a particular gene to human aging. We distinguished six types of studies and 12 criteria for adding genes to our database. Genes were classified according to the confidence level of the link between the gene and aging. All the data collected in a database are provided both by an API and a user interface. The database is publicly available on a website at https://open-genes.org/.

Human Ageing Genomic Resources: updates on key databases in ageing research

Ageing is a complex and multifactorial process. For two decades, the Human Ageing Genomic Resources (HAGR) have aided researchers in the study of various aspects of ageing and its manipulation. Here, we present the key features and recent enhancements of these resources, focusing on its six main databases. One database, GenAge, focuses on genes related to ageing, featuring 307 genes linked to human ageing and 2205 genes associated with longevity and ageing in model organisms. AnAge focuses on ageing, longevity, and life-history across animal species, containing data on 4645 species. DrugAge includes information about 1097 longevity drugs and compounds in model organisms such as mice, rats, flies, worms and yeast. GenDR provides a list of 214 genes associated with the life-extending benefits of dietary restriction in model organisms. CellAge contains a catalogue of 866 genes associated with cellular senescence. The LongevityMap serves as a repository for genetic variants associated with human longevity, encompassing 3144 variants pertaining to 884 genes. Additionally, HAGR provides various tools as well as gene expression signatures of ageing, dietary restriction, and replicative senescence based on meta-analyses. Our databases are integrated, regularly updated, and manually curated by experts. HAGR is freely available online (https://genomics.senescence.info/).

scDiffCom: a tool for differential analysis of cell-cell interactions provides a mouse atlas of aging changes in intercellular communication

Dysregulation of intercellular communication is a hallmark of aging. To better quantify and explore changes in intercellular communication, we present scDiffCom and scAgeCom. scDiffCom is an R package, relying on approximately 5,000 curated ligand-receptor interactions, that performs differential intercellular communication analysis between two conditions from single-cell transcriptomics data. Built upon scDiffCom, scAgeCom is an atlas of age-related cell-cell communication changes covering 23 mouse tissues from 58 single-cell RNA sequencing datasets from Tabula Muris Senis and the Calico murine aging cell atlas. It offers a comprehensive resource of tissue-specific and sex-specific aging dysregulations and highlights age-related intercellular communication changes widespread across the whole body, such as the upregulation of immune system processes and inflammation, the downregulation of developmental processes, angiogenesis and extracellular matrix organization and the deregulation of lipid metabolism. Our analysis emphasizes the relevance of the specific ligands, receptors and cell types regulating these processes. The atlas is available online ( https://scagecom.org ).

A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures

Accurately measuring biological age is crucial for improving healthcare for the elderly population. However, the complexity of aging biology poses challenges in how to robustly estimate aging and interpret the biological significance of the traits used for estimation. Here we present SCALE, a statistical pipeline that quantifies biological aging in different tissues using explainable features learned from literature and single-cell transcriptomic data. Applying SCALE to the "Mouse Aging Cell Atlas" (Tabula Muris Senis) data, we identified tissue-level transcriptomic aging programs for more than 20 murine tissues and created a multitissue resource of mouse quantitative aging-associated genes. We observe that SCALE correlates well with other age indicators, such as the accumulation of somatic mutations, and can distinguish subtle differences in aging even in cells of the same chronological age. We further compared SCALE with other transcriptomic and methylation "clocks" in data from aging muscle stem cells, Alzheimer's disease, and heterochronic parabiosis. Our results confirm that SCALE is more generalizable and reliable in assessing biological aging in aging-related diseases and rejuvenating interventions. Overall, SCALE represents a valuable advancement in our ability to measure aging accurately, robustly, and interpretably in single cells.

DNA methylation abnormalities induced by advanced maternal age in villi prime a high-risk state for spontaneous abortion

BACKGROUND

Advanced maternal age (AMA) has increased in many high-income countries in recent decades. AMA is generally associated with a higher risk of various pregnancy complications, and the underlying molecular mechanisms are largely unknown. In the current study, we profiled the DNA methylome of 24 human chorionic villi samples (CVSs) from early pregnancies in AMA and young maternal age (YMA), 11 CVSs from early spontaneous abortion (SA) cases using reduced representation bisulfite sequencing (RRBS), and the transcriptome of 10 CVSs from AMA and YMA pregnancies with mRNA sequencing(mRNA-seq). Single-cell villous transcriptional atlas presented expression patterns of targeted AMA-/SA-related genes. Trophoblast cellular impairment was investigated through the knockdown of GNE expression in HTR8-S/Vneo cells.

RESULTS

AMA-induced local DNA methylation changes, defined as AMA-related differentially methylated regions (DMRs), may be derived from the abnormal expression of genes involved in DNA demethylation, such as GADD45B. These DNA methylation changes were significantly enriched in the processes involved in NOTCH signaling and extracellular matrix organization and were reflected in the transcriptional alterations in the corresponding biological processes and specific genes. Furthermore, the DNA methylation level of special AMA-related DMRs not only significantly changed in AMA but also showed more excessive defects in CVS from spontaneous abortion (SA), including four AMA-related DMRs whose nearby genes overlapped with AMA-related differentially expressed genes (DEGs) (CDK11A, C19orf71, COL5A1, and GNE). The decreased DNA methylation level of DMR near GNE was positively correlated with the downregulated expression of GNE in AMA. Single-cell atlas further revealed comparatively high expression of GNE in the trophoblast lineage, and knockdown of GNE in HTR8-S/Vneo cells significantly impaired cellular proliferation and migration.

CONCLUSION

Our study provides valuable resources for investigating AMA-induced epigenetic abnormalities and provides new insights for explaining the increased risks of pregnancy complications in AMA pregnancies.

Genetic Networks of Alzheimer's Disease, Aging, and Longevity in Humans

Human genomic analysis and genome-wide association studies (GWAS) have identified genes that are risk factors for early and late-onset Alzheimer's disease (AD genes). Although the genetics of aging and longevity have been extensively studied, previous studies have focused on a specific set of genes that have been shown to contribute to or are a risk factor for AD. Thus, the connections among the genes involved in AD, aging, and longevity are not well understood. Here, we identified the genetic interaction networks (referred to as pathways) of aging and longevity within the context of AD by using a gene set enrichment analysis by Reactome that cross-references more than 100 bioinformatic databases to allow interpretation of the biological functions of gene sets through a wide variety of gene networks. We validated the pathways with a threshold of p-value < 1.00 × 10^-5 using the databases to extract lists of 356 AD genes, 307 aging-related (AR) genes, and 357 longevity genes. There was a broad range of biological pathways involved in AR and longevity genes shared with AD genes. AR genes identified 261 pathways within the threshold of p < 1.00 × 10^-5, of which 26 pathways (10% of AR gene pathways) were further identified by overlapping genes among AD and AR genes. The overlapped pathways included gene expression (p = 4.05 × 10^-11) including ApoE, SOD2, TP53, and TGFB1 (p = 2.84 × 10^-10); protein metabolism and SUMOylation, including E3 ligases and target proteins (p = 1.08 × 10^-7); ERBB4 signal transduction (p = 2.69 × 10^-6); the immune system, including IL-3 and IL-13 (p = 3.83 × 10^-6); programmed cell death (p = 4.36 × 10^-6); and platelet degranulation (p = 8.16 × 10^-6), among others. Longevity genes identified 49 pathways within the threshold, of which 12 pathways (24% of longevity gene pathways) were further identified by overlapping genes among AD and longevity genes. They include the immune system, including IL-3 and IL-13 (p = 7.64 × 10^-8), plasma lipoprotein assembly, remodeling and clearance (p < 4.02 × 10^-6), and the metabolism of fat-soluble vitamins (p = 1.96 × 10^-5). Thus, this study provides shared genetic hallmarks of aging, longevity, and AD backed up by statistical significance. We discuss the significant genes involved in these pathways, including TP53, FOXO, SUMOylation, IL4, IL6, APOE, and CEPT, and suggest that mapping the gene network pathways provide a useful basis for further medical research on AD and healthy aging.

Pan-cancer transcriptomic analysis identified six classes of immunosenescence genes revealed molecular links between aging, immune system and cancer

Aging is a complex process that significantly impacts the immune system. The aging-related decline of the immune system, termed immunosenescence, can lead to disease development, including cancer. The perturbation of immunosenescence genes may characterize the associations between cancer and aging. However, the systematical characterization of immunosenescence genes in pan-cancer remains largely unexplored. In this study, we comprehensively investigated the expression of immunosenescence genes and their roles in 26 types of cancer. We developed an integrated computational pipeline to identify and characterize immunosenescence genes in cancer based on the expression profiles of immune genes and clinical information of patients. We identified 2218 immunosenescence genes that were significantly dysregulated in a wide variety of cancers. These immunosenescence genes were divided into six categories based on their relationships with aging. Besides, we assessed the importance of immunosenescence genes in clinical prognosis and identified 1327 genes serving as prognostic markers in cancers. BTN3A1, BTN3A2, CTSD, CYTIP, HIF1AN, and RASGRP1 were associated with ICB immunotherapy response and served as prognostic factors after ICB immunotherapy in melanoma. Collectively, our results furthered the understanding of the relationship between immunosenescence and cancer and provided insights into immunotherapy for patients.

New Insights into the Genetics and Epigenetics of Aging Plasticity

Biological aging is characterized by irreversible cell cycle blockade, a decreased capacity for tissue regeneration, and an increased risk of age-related diseases and mortality. A variety of genetic and epigenetic factors regulate aging, including the abnormal expression of aging-related genes, increased DNA methylation levels, altered histone modifications, and unbalanced protein translation homeostasis. The epitranscriptome is also closely associated with aging. Aging is regulated by both genetic and epigenetic factors, with significant variability, heterogeneity, and plasticity. Understanding the complex genetic and epigenetic mechanisms of aging will aid the identification of aging-related markers, which may in turn aid the development of effective interventions against this process. This review summarizes the latest research in the field of aging from a genetic and epigenetic perspective. We analyze the relationships between aging-related genes, examine the possibility of reversing the aging process by altering epigenetic age.

Network analyses unveil ageing-associated pathways evolutionarily conserved from fungi to animals

The genetic roots of the diverse paces and shapes of ageing and of the large variations in longevity observed across the tree of life are poorly understood. Indeed, pathways associated with ageing/longevity are incompletely known, both in terms of their constitutive genes/proteins and of their molecular interactions. Moreover, there is limited overlap between the genes constituting these pathways across mammals. Yet, dedicated comparative analyses might still unravel evolutionarily conserved, important pathways associated with longevity or ageing. Here, we used an original strategy with a double evolutionary and systemic focus to analyse protein interactions associated with ageing or longevity during the evolution of five species of Opisthokonta. We ranked these proteins and interactions based on their evolutionary conservation and centrality in past and present protein-protein interaction (PPI) networks, providing a big systemic picture of the evolution of ageing and longevity pathways that identified which pathways emerged in which Opisthokonta lineages, were conserved, and/or central. We confirmed that longevity/ageing-associated proteins (LAPs), be they pro- or anti-longevity, are highly central in extant PPI, consistently with the antagonistic pleiotropy theory of ageing, and identified key antagonistic regulators of ageing/longevity, 52 of which with homologues in humans. While some highly central LAPs were evolutionarily conserved for over a billion years, we report a clear transition in the functionally important components of ageing/longevity within bilaterians. We also predicted 487 novel evolutionarily conserved LAPs in humans, 54% of which are more central than mTOR, and 138 of which are druggable, defining new potential targets for anti-ageing treatments in humans.

Comparative Senescence and Lifespan

The word senescence is derived from the Latin word “senex” (meaning old). In biology, senescence is a process by which a cell ages and permanently stops dividing. Senescence is a natural universal phenomenon affecting all living organisms (e.g., humans, animals, and plants). It is the process of growing old (aging). The underlying mechanisms of senescence and aging at the cellular level are not fully understood. Senescence is a multifactorial process that can be induced by several stimuli including cellular stress, DNA damage, telomere shortening, and oncogene activation. The most popular theory to explain aging is the free radical theory. Senescence plays a role in the development of several age-related chronic diseases in humans (e.g., ischemic heart disease, osteoporosis, and cancer). Lifespan is a biological characteristic of every species. The lifespan of living organisms ranges from few hours (with mayfly) to potential eternity (with jellyfish and hydra). The maximum theoretical lifespan in humans is around 120 years. The lifespan in humans is influenced by multiple factors including genetic, epigenetic, lifestyle, environmental, metabolic, and endocrine factors. There are several ways to potentially extend the lifespan of humans and eventually surpass the maximum theoretical lifespan of 120 years. The tools that can be proposed include lifestyle, reduction of several life-threatening diseases and disabilities, hormonal replacement, antioxidants, autophagy inducers, senolytic drugs, stem cell therapy, and gene therapy.

The combination of DNA methylome and transcriptome revealed the intergenerational inheritance on the influence of advanced maternal age

BACKGROUND

The number of women delivering at advanced maternal age (AMA; > = 35) continuously increases in developed and high-income countries. Large cohort studies have associated AMA with increased risks of various pregnancy complications and adverse pregnancy outcomes, which raises great concerns about the adverse effect of AMA on the long-term health of offspring. Specific acquired characteristics of parents can be passed on to descendants through certain molecular mechanisms, yet the underlying connection between AMA-related alterations in parents and that in offspring remains largely uncharted.

METHODS

We profiled the DNA methylomes of paired parental peripheral bloods and cord bloods from 20 nuclear families, including 10 AMA and 10 Young, and additional transcriptomes of 10 paired maternal peripheral bloods and cord bloods.

RESULTS

We revealed that AMA induced aging-like changes in DNA methylome and gene expression in both parents and offspring. The expression changes in several genes, such as SLC28A3, were highly relevant to the disorder in DNA methylation. In addition, AMA-related differentially methylated regions (DMRs) identified in mother and offspring groups showed remarkable similarities in both genomic locations and biological functions, mainly involving neuron differentiation, metabolism, and histone modification pathways. AMA-related differentially expressed genes (DEGs) shared by mother and offspring groups were highly enriched in the processes of immune cell activation and mitotic nuclear division. We further uncovered developmental-dependent dynamics for the DNA methylation of intergenerationally correlated DMRs during pre-implantation embryonic development, as well as diverse gene expression patterns during gametogenesis and early embryonic development for those common AMA-related DEGs presenting intergenerational correlation, such as CD24. Moreover, some intergenerational DEGs, typified by HTRA3, also showed the same significant alterations in AMA MII oocyte or blastocyst.

CONCLUSIONS

Our results reveal potential intergenerational inheritance of both AMA-related DNA methylome and transcriptome and provide new insights to understand health problems in AMA offspring.

Characterization of the SGLT2 Interaction Network and Its Regulation by SGLT2 Inhibitors: A Bioinformatic Analysis

Background: Sodium–glucose cotransporter 2 (SGLT2), also known as solute carrier family 5 member 2 (SLC5A2), is a promising target for a new class of drugs primarily established as kidney-targeting, effective glucose-lowering agents used in diabetes mellitus (DM) patients. Increasing evidence indicates that besides renal effects, SGLT2 inhibitors (SGLT2i) have also a systemic impact via indirectly targeting the heart and other tissues. Our hypothesis states that the pleiotropic effects of SGLT2i are associated with their binding force, location of targets in the SGLT2 networks, targets involvement in signaling pathways, and their tissue-specific expression.

Methods: Thus, to investigate differences in SGLT2i impact on human organisms, we re-created the SGLT2 interaction network incorporating its inhibitors and metformin and analyzed its tissue-specific expression using publicly available datasets. We analyzed it in the context of the so-called key terms ( autophagy, oxidative stress, aging, senescence, inflammation, AMPK pathways, and mTOR pathways) which seem to be crucial to elucidating the SGLT2 role in a variety of clinical manifestations.

Results: Analysis of SGLT2 and its network components’ expression confidence identified selected organs in the following order: kidney, liver, adipose tissue, blood, heart, muscle, intestine, brain, and artery according to the TISSUES database. Drug repurposing analysis of known SGLT2i pointed out the influence of SGLT1 regulators on the heart and intestine tissue. Additionally, dapagliflozin seems to also have a stronger impact on brain tissue through the regulation of SGLT3 and SLC5A11. The shortest path analysis identified interaction SIRT1-SGLT2 among the top five interactions across six from seven analyzed networks associated with the key terms. Other top first-level SGLT2 interactors associated with key terms were not only ADIPOQ, INS, GLUT4, ACE, and GLUT1 but also less recognized ILK and ADCY7. Among other interactors which appeared in multiple shortest-path analyses were GPT, COG2, and MGAM. Enrichment analysis of SGLT2 network components showed the highest overrepresentation of hypertensive disease, DM-related diseases for both levels of SGLT2 interactors. Additionally, for the extended SGLT2 network, we observed enrichment in obesity (including SGLT1), cancer-related terms, neuroactive ligand–receptor interaction, and neutrophil-mediated immunity.

Conclusion: This study provides comprehensive and ranked information about the SGLT2 interaction network in the context of tissue expression and can help to predict the clinical effects of the SGLT2i.

Evolutionarily conserved transcription factors as regulators of longevity and targets for geroprotection

Aging is the single largest risk factor for many debilitating conditions, including heart diseases, stroke, cancer, diabetes, and neurodegenerative disorders. While far from understood in its full complexity, it is scientifically well-established that aging is influenced by genetic and environmental factors, and can be modulated by various interventions. One of aging's early hallmarks are aberrations in transcriptional networks, controlling for example metabolic homeostasis or the response to stress. Evidence in different model organisms abounds that a number of evolutionarily conserved transcription factors, which control such networks, can affect lifespan and healthspan across species. These transcription factors thus potentially represent conserved regulators of longevity and are emerging as important targets in the challenging quest to develop treatments to mitigate age-related diseases, and possibly even to slow aging itself. This review provides an overview of evolutionarily conserved transcription factors that impact longevity or age-related diseases in at least one multicellular model organism (nematodes, flies, or mice), and/or are tentatively linked to human aging. Discussed is the general evidence for transcriptional regulation of aging and disease, followed by a more detailed look at selected transcription factor families, the common metabolic pathways involved, and the targeting of transcription factors as a strategy for geroprotective interventions.

A high-quality chromosome-level genome of the endangered roughskin sculpin provides insights into its evolution and adaptation

The cottids (Cottidae) are a taxonomically diverse and ecologically important component of many marine and freshwater ecosystems. Despite recent breakthroughs in long-read sequencing, high quality genomic resources are still limited for studies of ecological and evolutionary processes in cottids. Here we generated a high-quality, chromosome-scale genome assembly (521.26 Mb) of the catadromous roughskin sculpin (Trachidermus fasciatus Heckel) with a contig N50 of 2.93 Mb and a scaffold N50 of 24.06 Mb. Approximately 21.97% of the genome was composed of repetitive elements. A total of 21,872 protein-coding genes were predicted, of which 19,900 genes (90.98%) were functionally annotated. Phylogenetic analysis supported the validity of Scorpaenoidei and Cottioidei as two suborders of the Perciformes. Chromosome-scale collinearity analyses identified four chromosome fusions leading to the reduction of chromosome number in T. fasciatus. Gene families related to cell apoptosis and cell death were expanded and those related to immune system were contracted, suggesting that these gene families might be relevant to a host of phenotypic differences between T. fasciatus and other teleosts. Gene families associated with osmoregulation were also expanded, which might be associated with its catadromous life history. A total of 50 aging-associated genes were found to be under positive selection, which might be associated with the short lifespan of T. fasciatus. The high-quality genome assembly and annotation will promote researches into the evolution of catadromous life history and short lifespan for T. fasciatus and facilitate comparative genomic studies of cottids in the near future.

A collective analysis of lifespan-extending compounds in diverse model organisms, and of species whose lifespan can be extended the most by the application of compounds

Research on aging and lifespan-extending compounds has been carried out using diverse model organisms, including yeast, worms, flies and mice. Many studies reported the identification of novel lifespan-extending compounds in different species, some of which may have the potential to translate to the clinic. However, studies collectively and comparatively analyzing all the data available in these studies are highly limited. Here, by using data from the DrugAge database, we first identified top compounds in terms of their effects on percent change in average lifespan of diverse organisms, collectively (n = 1728). We found that, when data from all organisms studied were combined for each compound, aspirin resulted in the highest percent increase in average lifespan (52.01%), followed by minocycline (27.30%), N-acetyl cysteine (17.93%), nordihydroguaiaretic acid (17.65%) and rapamycin (15.66%), in average. We showed that minocycline led to the highest percent increase in average lifespan among other compounds, in both Drosophila melanogaster (28.09%) and Caenorhabditis elegans (26.67%), followed by curcumin (11.29%) and gluconic acid (5.51%) for D. melanogaster and by metformin (26.56%), resveratrol (15.82%) and quercetin (9.58%) for C. elegans. Moreover, we found that top 5 species whose lifespan can be extended the most by compounds with lifespan-extending properties are Philodina acuticornis, Acheta domesticus, Aeolosoma viride, Mytilina brevispina and Saccharomyces cerevisiae (211.80%, 76%, 70.26%, 55.18% and 45.71% in average, respectively). This study provides novel insights on lifespan extension in model organisms, and highlights the importance of databases with high quality content curated by researchers from multiple resources, in aging research.

Biomarkers of geroprotection and cardiovascular health: An overview of omics studies and established clinical biomarkers in the context of diet

The slowdown, inhibition, or reversal of age-related decline (as a composite of disease, dysfunction, and, ultimately, death) by diet or natural compounds can be defined as dietary geroprotection. While there is no single reliable biomarker to judge the effects of dietary geroprotection, biomarker signatures based on omics (epigenetics, gene expression, microbiome composition) are promising candidates. Recently, omic biomarkers started to supplement established clinical ones such as lipid profiles and inflammatory cytokines. In this review, we focus on human data. We first summarize the current take on genetic biomarkers based on epidemiological studies. However, most of the remaining biomarkers that we describe, whether omics-based or clinical, are related to intervention studies. Then, because of their promising potential in the context of dietary geroprotection, we focus on the effects of berry-based interventions, which up to now have been mostly described employing clinical markers. We provide an aggregation and tabulation of all the recent systematic reviews and meta-analyses that we could find related to this topic. Finally, we present evidence for the importance of the "nutribiography," that is, the influence that an individual's history of diet and natural compound consumption can have on the effects of dietary geroprotection.

Gonadotropin-releasing hormone receptor pathway affects the function of human EBV-transformed B lymphocytes in an age-independent way

Immune system function changes during aging, but the molecular mechanisms of this phenomenon are not fully understood. The present study identified pathways that are associated with age-associated changes in human B lymphocytes. Initial in silico analysis of 1355 genes involved in aging revealed the strongest association (p = 4.36E-21) with the gonadotropin-releasing hormone receptor (GnRHR) pathway. Extended analysis of 2736 aging-related genes using updated databases confirmed such association (p = 2.41E-16). Genes involved in both aging and the GnRHR pathway were significantly involved in lymphocyte B and T activation and aging-related phenotypes, including hyperinsulinemia and diabetes, arthritis, cerebrovascular disease, and cancers. We, therefore, examined non-tumorigenic Epstein-Barr virus (EBV)-transformed B-lymphocyte cell lines that originated from 12 young subjects (20-31 years old) and 10 centenarians (100-102 years old). Gonadotropin-releasing hormone I (GnRH-I) and GnRHR levels did not depend on the age of the cell donors. Inhibition of the GnRHR pathway age-independently decreased cell proliferation (p < 0.001) and increased apoptosis (p < 0.001). However, the decrease in immunoglobulin G synthesis (p < 0.01) was twice as high in centenarian cells than in young cells. In conclusion, the GnRHR pathway regulated essential properties of B lymphocytes. However, upon EBV transformation, memory class-switched B cells became the dominant cell subpopulation. Therefore, the observed effects of GnRHR inhibition were attributable to this subpopulation.

Omics in a Digital World: The Role of Bioinformatics in Providing New Insights Into Human Aging

Background

Aging is a complex phenotype influenced by a combination of genetic and environmental factors. Although many studies addressed its cellular and physiological age-related changes, the molecular causes of aging remain undetermined. Considering the biological complexity and heterogeneity of the aging process, it is now clear that full understanding of mechanisms underlying aging can only be achieved through the integration of different data types and sources, and with new computational methods capable to achieve such integration.

Recent Advances

In this review, we show that an omics vision of the age-dependent changes occurring as the individual ages can provide researchers with new opportunities to understand the mechanisms of aging. Combining results from single-cell analysis with systems biology tools would allow building interaction networks and investigate how these networks are perturbed during aging and disease. The development of high-throughput technologies such as next-generation sequencing, proteomics, metabolomics, able to investigate different biological markers and to monitor them simultaneously during the aging process with high accuracy and specificity, represents a unique opportunity offered to biogerontologists today.

Critical Issues

Although the capacity to produce big data drastically increased over the years, integration, interpretation and sharing of high-throughput data remain major challenges. In this paper we present a survey of the emerging omics approaches in aging research and provide a large collection of datasets and databases as a useful resource for the scientific community to identify causes of aging. We discuss their peculiarities, emphasizing the need for the development of methods focused on the integration of different data types.

Future Directions

We critically review the contribution of bioinformatics into the omics of aging research, and we propose a few recommendations to boost collaborations and produce new insights. We believe that significant advancements can be achieved by following major developments in bioinformatics, investing in diversity, data sharing and community-driven portable bioinformatics methods. We also argue in favor of more engagement and participation, and we highlight the benefits of new collaborations along these lines. This review aims at being a useful resource for many researchers in the field, and a call for new partnerships in aging research.

Analysis of aging-related protein interactome and cross-network module comparisons across tissues provide new insights into aging

Delaying the human aging process and thus eliminating the risk factors for age-related diseases is one of the prime objectives. While various aging-associated genes and proteins have been characterized, which provide a significant understanding of the human aging process, a significant success in regulating aging is not achieved yet. Understanding how aging proteins interact with each other and also with other proteins could provide important insights into the underlying mechanisms governing the aging process. Therefore, in this work, information of gene expression was included to the static aging-related protein interactome to understand the network-based relationships among aging-related essential (AE) proteins, aging-related non-essential (ANE) proteins, and housekeeping-proteins that could regulate or influence aging. Comprehensive analyses provided various systems-level insights into the regulatory characteristics of aging; for example, (i) network-based correlation analysis predicted functional relationships among AE proteins and ANE proteins; (ii) network variability analysis predicted aging to affect different tissues in strikingly different ways by differentially regulating various regulatory interactions; (iii) cross-network comparisons identified two aging-related modules to be significantly conserved across most of the tissues. Overall, the findings obtained during this study could be helpful for researchers to delay, prevent, or even reverse various aspects of the aging.

KibioR & Kibio: a new architecture for next-generation data querying and sharing in big biology

MOTIVATION

The growing production of massive heterogeneous biological data offers opportunities for new discoveries. However, performing multi-omics data analysis is challenging, and researchers are forced to handle the ever-increasing complexity of both data management and evolution of our biological understanding. Substantial efforts have been made to unify biological datasets into integrated systems. Unfortunately, they are not easily scalable, deployable and searchable, locally or globally.

RESULTS

This publication presents two tools with a simple structure that can help any data provider, organization or researcher, requiring a reliable data search and analysis base. The first tool is Kibio, a scalable and adaptable data storage based on Elasticsearch search engine. The second tool is KibioR, a R package to pull, push and search Kibio datasets or any accessible Elasticsearch-based databases. These tools apply a uniform data exchange model and minimize the burden of data management by organizing data into a decentralized, versatile, searchable and shareable structure. Several case studies are presented using multiple databases, from drug characterization to miRNAs and pathways identification, emphasizing the ease of use and versatility of the Kibio/KibioR framework.

AVAILABILITY

Both KibioR and Elasticsearch are open source. KibioR package source is available at https://github.com/regisoc/kibior and the library on CRAN at https://cran.r-project.org/package=kibior.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ageing transcriptome meta-analysis reveals similarities and differences between key mammalian tissues

By combining transcriptomic data with other data sources, inferences can be made about functional changes during ageing. Thus, we conducted a meta-analysis on 127 publicly available microarray and RNA-Seq datasets from mice, rats and humans, identifying a transcriptomic signature of ageing across species and tissues. Analyses on subsets of these datasets produced transcriptomic signatures of ageing for brain, heart and muscle. We then applied enrichment analysis and machine learning to functionally describe these signatures, revealing overexpression of immune and stress response genes and underexpression of metabolic and developmental genes. Further analyses revealed little overlap between genes differentially expressed with age in different tissues, despite ageing differentially expressed genes typically being widely expressed across tissues. Additionally we show that the ageing gene expression signatures (particularly the overexpressed signatures) of the whole meta-analysis, brain and muscle tend to include genes that are central in protein-protein interaction networks. We also show that genes underexpressed with age in the brain are highly central in a co-expression network, suggesting that underexpression of these genes may have broad phenotypic consequences. In sum, we show numerous functional similarities between the ageing transcriptomes of these important tissues, along with unique network properties of genes differentially expressed with age in both a protein-protein interaction and co-expression networks.

Association of TGFβ1 codon 10 (T>C) and IL-10 (G>C) cytokine gene polymorphisms with longevity in a cohort of Italian population

Longevity is a complex process controlled by both environmental and genetic factors. We evaluated the association of four cytokine gene polymorphisms with longevity in an Italian cohort. A sample of 1019 subjects aged 10 to 100 and belonging to the North-Italian population was genotyped for IL-6 (G>C, rs1800796), IL-10-1082 (G>A, rs1800896), TNF-α-308 (G>A, rs1800629), and TGFβ1 codon 10 (T>C, rs1800471) gene polymorphisms. The association between cytokine gene polymorphisms and longevity was evaluated by dividing the sample into four age groups: 10 to 24, 25 to 49, 50 to 85, and 86 to 100. We observed a significant decrease in the frequency of IL-10 A allele in the 25 to 49 (P = 1.1 × 10^-3 ), 50 to 85 (P < 1 × 10^-4 ), and 86 to 100 (P = 2 × 10^-3 ) age groups compared to that in the youngest age group. Similarly, we found a significant decrease (P < 1 × 10^-4 ) in the frequency of TGFβ1 C allele in the 50 to 85 and 86 to 100 age groups compared to that in the 10 to 24 and 25 to 49 age groups. Previously, high levels of TGFβ1 were detected in elderly subjects, suggesting that this cytokine could counterbalance the harmful effects of inflammation. Similarly, IL-10 has strong anti-inflammatory properties and can inhibit the production of proinflammatory cytokines. In the literature, the lowest levels of functional cytokines were found to be associated with TGFβ1 (T>C) and IL-10 (G>A) gene polymorphisms, with consequent increase in the duration of inflammation and cancer risk. For these reasons, it is plausible to observe low rates of these mutations in elderly subjects, as found in our study.

Genetics of frailty: A longevity perspective

Frailty is a complex late life phenotype characterized by cumulative declines in multiple physiological systems that increases the risk for disability and mortality. The biological changes associated with aging are risk factors for frailty as well as for complex diseases; whereas longevity is assumed to be an outcome of protective biological mechanisms. Understanding the interplay between biological alterations associated with aging and protective mechanisms associated with longevity in the context of frailty may help guide development of interventions to increase healthspan and promote successful aging. The complexity of these phenotypes and relatively low heritability in studies are the main roadblocks in deciphering genetic mechanisms of these age associated conditions. We review genetic research related to frailty, and discuss the possible intertwined biology of frailty and longevity.

Whole-genome sequencing of Chinese centenarians reveals important genetic variants in aging WGS of centenarian for genetic analysis of aging

Background

Genetic research on longevity has provided important insights into the mechanism of aging and aging-related diseases. Pinpointing import genetic variants associated with aging could provide insights for aging research.

Methods

We performed a whole-genome sequencing in 19 centenarians to establish the genetic basis of human longevity.

Results

Using SKAT analysis, we found 41 significantly correlated genes in centenarians as compared to control genomes. Pathway enrichment analysis of these genes showed that immune-related pathways were enriched, suggesting that immune pathways might be critically involved in aging. HLA typing was next performed based on the whole-genome sequencing data obtained. We discovered that several HLA subtypes were significantly overrepresented.

Conclusions

Our study indicated a new mechanism of longevity, suggesting potential genetic variants for further study.

Redox-mediated regulation of aging and healthspan by an evolutionarily conserved transcription factor HLH-2/Tcf3/E2A

Physiological aging is a complex process, influenced by a plethora of genetic and environmental factors. While being far from fully understood, a number of common aging hallmarks have been elucidated in recent years. Among these, transcriptomic alterations are hypothesized to represent a crucial early manifestation of aging. Accordingly, several transcription factors (TFs) have previously been identified as important modulators of lifespan in evolutionarily distant model organisms. Based on a set of TFs conserved between nematodes, zebrafish, mice, and humans, we here perform a RNA interference (RNAi) screen in C. elegans to discover evolutionarily conserved TFs impacting aging. We identify a basic helix-loop-helix TF, named HLH-2 in nematodes (Tcf3/E2A in mammals), to exert a pronounced lifespan-extending effect in C. elegans upon impairment. We further show that its impairment impacts cellular energy metabolism, increases parameters of healthy aging, and extends nematodal lifespan in a ROS-dependent manner. We then identify arginine kinases, orthologues of mammalian creatine kinases, as a target of HLH-2 transcriptional regulation, serving to mediate the healthspan-promoting effects observed upon impairment of hlh-2 expression. Consistently, HLH-2 is shown to epistatically interact with core components of known lifespan-regulating pathways, i.e. AAK-2/AMPK and LET-363/mTOR, as well as the aging-related TFs SKN-1/Nrf2 and HSF-1. Lastly, single-nucelotide polymorphisms (SNPs) in Tcf3/E2A are associated with exceptional longevity in humans. Together, these findings demonstrate that HLH-2 regulates energy metabolism via arginine kinases and thereby affects the aging phenotype dependent on ROS-signaling and established canonical effectors.

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A C. elegans RNAi screen identifies conserved aging-related transcription factors.

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Impairment of transcription factor hlh-2 has the most pronounced effect on lifespan.

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C. elegans HLH-2 affects cellular energy homeostasis and redox signaling.

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HLH-2 modulates arginine kinase to interact with downstream longevity pathways.

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Polymorphisms (SNPs) in the hlh-2 orthologue Tcf3/E2A are linked to human longevity.

Molecular therapies delaying cardiovascular aging: disease- or health-oriented approaches

Regenerative medicine is a new therapeutic modality that aims to mend tissue damage by encouraging the reconstitution of physiological integrity. It represents an advancement over conventional therapies that allow reducing the damage but result in disease chronicization. Age-related decline in spontaneous capacity of repair, especially in organs like the heart that have very limited proliferative capacity, contributes in reducing the benefit of conventional therapy. ncRNAs are emerging as key epigenetic regulators of cardiovascular regeneration. Inhibition or replacement of miRNAs may offer reparative solutions to cardiovascular disease. The first part of this review article is devoted to illustrating novel therapies emerging from research on miRNAs. In the second part, we develop new therapeutic concepts emerging from genetics of longevity. Prolonged survival, as in supercentenarians, denotes an exceptional capacity to repair and cope with risk factors and diseases. These characteristics are shared with offspring, suggesting that the regenerative phenotype is heritable. New evidence indicates that genetic traits responsible for prolongation of health span in humans can be passed to and benefit the outcomes of animal models of cardiovascular disease. Genetic studies have also focused on determinants of accelerated senescence and related druggable targets. Evolutionary genetics assessing the genetic basis of adaptation and comparing successful and unsuccessful genetic changes in response to selection within populations represent a powerful basis to develop novel therapies aiming to prolong cardiovascular and whole organism health.

Computational tools for geroscience

The rapid progress of the past three decades has led the geroscience field near a point where human interventions in aging are plausible. Advances across scientific areas, such as high throughput "-omics" approaches, have led to an exponentially increasing quantity of data available for biogerontologists. To best translate the lifespan and healthspan extending interventions discovered by basic scientists into preventative medicine, it is imperative that the current data are comprehensively utilized to generate testable hypotheses about translational interventions. Building a translational pipeline for geroscience will require both systematic efforts to identify interventions that extend healthspan across taxa and diagnostics that can identify patients who may benefit from interventions prior to the onset of an age-related morbidity. Databases and computational tools that organize and analyze both the wealth of information available on basic biogerontology research and clinical data on aging populations will be critical in developing such a pipeline. Here, we review the current landscape of databases and computational resources available for translational aging research. We discuss key platforms and tools available for aging research, with a focus on how each tool can be used in concert with hypothesis driven experiments to move closer to human interventions in aging.

Dynamic transcriptome profiling in DNA damage-induced cellular senescence and transient cell-cycle arrest

Cellular senescence is an irreversible cell cycle arrest process associated with aging and senescence-related diseases. DNA damage is an extensive feature of cellular senescence and aging. Different levels of DNA damage could lead to cellular senescence or transient cell-cycle arrest, but the genetic regulatory mechanisms determining cell fate are still not clear. In this work, high-resolution time course analysis of gene expression in DNA damage-induced cellular senescence and transient cell-cycle arrest was used to explore the transcriptomic differences between different cell fates after DNA damage response and to investigate the key regulatory factors affecting senescent cell fates. Pathways such as the cell cycle, DNA repair and cholesterol metabolism showed characteristic differential response. A number of key transcription factors were predicted to regulating cell cycle and DNA repair. Our study provides genome-wide insights into the molecular-level mechanisms of senescent cell fate decisions after DNA damage response.

Human Ageing Genomic Resources: new and updated databases

In spite of a growing body of research and data, human ageing remains a poorly understood process. Over 10 years ago we developed the Human Ageing Genomic Resources (HAGR), a collection of databases and tools for studying the biology and genetics of ageing. Here, we present HAGR’s main functionalities, highlighting new additions and improvements. HAGR consists of six core databases: (i) the GenAge database of ageing-related genes, in turn composed of a dataset of >300 human ageing-related genes and a dataset with >2000 genes associated with ageing or longevity in model organisms; (ii) the AnAge database of animal ageing and longevity, featuring >4000 species; (iii) the GenDR database with >200 genes associated with the life-extending effects of dietary restriction; (iv) the LongevityMap database of human genetic association studies of longevity with >500 entries; (v) the DrugAge database with >400 ageing or longevity-associated drugs or compounds; (vi) the CellAge database with >200 genes associated with cell senescence. All our databases are manually curated by experts and regularly updated to ensure a high quality data. Cross-links across our databases and to external resources help researchers locate and integrate relevant information. HAGR is freely available online (http://genomics.senescence.info/).

Biomedical and genetic characteristics of the Ryukyuans: demographic history, diseases and physical and physiological traits

Context: The Ryukyu Islands stretch across a southwestern area of the Japanese Archipelago. Because of their unique geographical and historical backgrounds, Ryukyuans have their own genetic and phenotypic characteristics, which have been disclosed in previous anthropological and biomedical studies. Objective: The history, peopling and biomedical and genetic characteristics of Ryukyuans are reviewed and future research directions are discussed. Conclusion: Morphological and genetic studies have suggested the complex demographic history of Ryukyuans and their relationships with other Asian populations. Knowledge of population formation processes is important to understand the distribution of pathogens. In viral infectious diseases, some strains that may be associated with disease symptoms are specific to Ryukyuans. Dramatic changes in diet have played an important role among Ryukyuans in terms of increases in lifestyle-related diseases and mortality risks. To achieve a better understanding of pathogenic disease factors, further integration of findings regarding the genetic and biomedical characteristics of the Ryukyuans is needed.

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.

Artificial intelligence for aging and longevity research: Recent advances and perspectives

The applications of modern artificial intelligence (AI) algorithms within the field of aging research offer tremendous opportunities. Aging is an almost universal unifying feature possessed by all living organisms, tissues, and cells. Modern deep learning techniques used to develop age predictors offer new possibilities for formerly incompatible dynamic and static data types. AI biomarkers of aging enable a holistic view of biological processes and allow for novel methods for building causal models-extracting the most important features and identifying biological targets and mechanisms. Recent developments in generative adversarial networks (GANs) and reinforcement learning (RL) permit the generation of diverse synthetic molecular and patient data, identification of novel biological targets, and generation of novel molecular compounds with desired properties and geroprotectors. These novel techniques can be combined into a unified, seamless end-to-end biomarker development, target identification, drug discovery and real world evidence pipeline that may help accelerate and improve pharmaceutical research and development practices. Modern AI is therefore expected to contribute to the credibility and prominence of longevity biotechnology in the healthcare and pharmaceutical industry, and to the convergence of countless areas of research.

Facing up to the global challenges of ageing

Longer human lives have led to a global burden of late-life disease. However, some older people experience little ill health, a trait that should be extended to the general population. Interventions into lifestyle, including increased exercise and reduction in food intake and obesity, can help to maintain healthspan. Altered gut microbiota, removal of senescent cells, blood factors obtained from young individuals and drugs can all improve late-life health in animals. Application to humans will require better biomarkers of disease risk and responses to interventions, closer alignment of work in animals and humans, and increased use of electronic health records, biobank resources and cohort studies.

Genomic Approach to Understand the Association of DNA Repair with Longevity and Healthy Aging Using Genomic Databases of Oldest-Old Population

Aged population is increasing worldwide due to the aging process that is inevitable. Accordingly, longevity and healthy aging have been spotlighted to promote social contribution of aged population. Many studies in the past few decades have reported the process of aging and longevity, emphasizing the importance of maintaining genomic stability in exceptionally long-lived population. Underlying reason of longevity remains unclear due to its complexity involving multiple factors. With advances in sequencing technology and human genome-associated approaches, studies based on population-based genomic studies are increasing. In this review, we summarize recent longevity and healthy aging studies of human population focusing on DNA repair as a major factor in maintaining genome integrity. To keep pace with recent growth in genomic research, aging- and longevity-associated genomic databases are also briefly introduced. To suggest novel approaches to investigate longevity-associated genetic variants related to DNA repair using genomic databases, gene set analysis was conducted, focusing on DNA repair- and longevity-associated genes. Their biological networks were additionally analyzed to grasp major factors containing genetic variants of human longevity and healthy aging in DNA repair mechanisms. In summary, this review emphasizes DNA repair activity in human longevity and suggests approach to conduct DNA repair-associated genomic study on human healthy aging.

Involvement of SPATA31 copy number variable genes in human lifespan

The SPATA31 (alias FAM75A) gene family belongs to the core duplicon families that are thought to have contributed significantly to hominoid evolution. It is also among the gene families with the strongest signal of positive selection in hominoids. It has acquired new protein domains in the primate lineage and a previous study has suggested that the gene family has expanded its function into UV response and DNA repair. Here we show that over-expression of SPATA31A1 in fibroblast cells leads to premature senescence due to interference with aging-related transcription pathways. We show that there are considerable copy number differences for this gene family in human populations and we ask whether this could influence mutation rates and longevity in humans. We find no evidence for an influence on germline mutation rates, but an analysis of long-lived individuals (> 96 years) shows that they carry significantly fewer SPATA31 copies in their genomes than younger individuals in a control group. We propose that the evolution of SPATA31 copy number is an example for antagonistic pleiotropy by providing a fitness benefit during the reproductive phase of life, but negatively influencing the overall life span.

Identification of new genetic variants of HLA-DQB1 associated with human longevity and lipid homeostasis-a cross-sectional study in a Chinese population

Healthy longevity has been an unremitting pursuit of human, but its genetic and the environment causes are still unclear. As longevity population is a good healthy aging model for understanding how the body begin aging and the process of aging, and plasma lipids metabolism and balance is a very important to life maintain and physiologic functional turnover. It is important to explore how the effect of genetic variants associated long-life individuals on lipids metabolism and balance. Therefore, we developed a comparative study based population which contains 2816 longevity and 2819 control. Through whole-exome sequencing and sanger sequencing genotypes, we identified four new single nucleotide polymorphisms of HLA-DQB1(major histocompatibility complex, class II, DQ beta 1), rs41542812 rs1049107 rs1049100 rs3891176(P_range=0.048-2.811×10⁻⁸ for allele frequencies), associated with longevity in Chinese Longevity Cohort. Further, by analysis of the longevity-variants linked to blood lipids, we identified HLA-DQB1 rs1049107, T-carriers (P_HDL=0.006, OR: 11.277; P_TG=9.095×10⁻⁷, OR: 0.025; P_LDL/HDL=0.047, OR: 1.901) and HLA-DQB1 rs1049100, T-carriers (P_TG=1.799×10-6, OR: 0.028) associated with lipid homeostasis in long lived individuals. Our finding showed that longevity and lipid homeostasis were associated with HLA-DQB1 and suggested that immune gene variants could act on both new function of maintaining the homeostasis and anti-aging in longevity.

Systematic analysis of the gerontome reveals links between aging and age-related diseases

In model organisms, over 2,000 genes have been shown to modulate aging, the collection of which we call the ‘gerontome’. Although some individual aging-related genes have been the subject of intense scrutiny, their analysis as a whole has been limited. In particular, the genetic interaction of aging and age-related pathologies remain a subject of debate. In this work, we perform a systematic analysis of the gerontome across species, including human aging-related genes. First, by classifying aging-related genes as pro- or anti-longevity, we define distinct pathways and genes that modulate aging in different ways. Our subsequent comparison of aging-related genes with age-related disease genes reveals species-specific effects with strong overlaps between aging and age-related diseases in mice, yet surprisingly few overlaps in lower model organisms. We discover that genetic links between aging and age-related diseases are due to a small fraction of aging-related genes which also tend to have a high network connectivity. Other insights from our systematic analysis include assessing how using datasets with genes more or less studied than average may result in biases, showing that age-related disease genes have faster molecular evolution rates and predicting new aging-related drugs based on drug-gene interaction data. Overall, this is the largest systems-level analysis of the genetics of aging to date and the first to discriminate anti- and pro-longevity genes, revealing new insights on aging-related genes as a whole and their interactions with age-related diseases.

FOXO3 and Exceptional Longevity: Insights From Hydra to Humans

Aging is a complex, multifactorial process with significant plasticity. While several biological pathways appear to influence aging, few genes have been identified that are both evolutionarily conserved and have a strong impact on aging and age-related phenotypes. The FoxO3 gene (FOXO3), and its homologs in model organisms, appears especially important, forming a key gene in the insulin/insulin-like growth factor-signaling pathway, and influencing life span across diverse species. We highlight some of the key findings that are associated with FoxO3 protein, its gene and homologs in relation to lifespan in different species, and the insights these findings might provide about the molecular, cellular, and physiological processes that modulate aging and longevity in humans.

Predicting age by mining electronic medical records with deep learning characterizes differences between chronological and physiological age

Determining the discrepancy between chronological and physiological age of patients is central to preventative and personalized care. Electronic medical records (EMR) provide rich information about the patient physiological state, but it is unclear whether such information can be predictive of chronological age. Here we present a deep learning model that uses vital signs and lab tests contained within the EMR of Mount Sinai Health System (MSHS) to predict chronological age. The model is trained on 377,686 EMR from patients of ages 18-85 years old. The discrepancy between the predicted and real chronological age is then used as a proxy to estimate physiological age. Overall, the model can predict the chronological age of patients with a standard deviation error of ∼7 years. The ages of the youngest and oldest patients were more accurately predicted, while patients of ages ranging between 40 and 60 years were the least accurately predicted. Patients with the largest discrepancy between their physiological and chronological age were further inspected. The patients predicted to be significantly older than their chronological age have higher systolic blood pressure, higher cholesterol, damaged liver, and anemia. In contrast, patients predicted to be younger than their chronological age have lower blood pressure and shorter stature among other indicators; both groups display lower weight than the population average. Using information from ∼10,000 patients from the entire cohort who have been also profiled with SNP arrays, genome-wide association study (GWAS) uncovers several novel genetic variants associated with aging. In particular, significant variants were mapped to genes known to be associated with inflammation, hypertension, lipid metabolism, height, and increased lifespan in mice. Several genes with missense mutations were identified as novel candidate aging genes. In conclusion, we demonstrate how EMR data can be used to assess overall health via a scale that is based on deviation from the patient's predicted chronological age.

Identification of polymorphisms in cancer patients that differentially affect survival with age

The World Health Organization predicts that the proportion of the world's population over 60 will almost double from 12% to 22% between 2015 and 2050. Ageing is the biggest risk factor for cancer, which is a leading cause of deaths worldwide. Unfortunately, research describing how genetic variants affect cancer progression commonly neglects to account for the ageing process. Herein is the first systematic analysis that combines a large longitudinal data set with a targeted candidate gene approach to examine the effect of genetic variation on survival as a function of age in cancer patients. Survival was significantly decreased in individuals with heterozygote or rare homozygote (i.e. variant) genotypes compared to those with a common homozygote genotype (i.e. wild type) for two single nucleotide polymorphisms (rs11574358 and rs4147918), one gene (SIRT3) and one pathway (FoxO signalling) in an age-dependent manner. All identified genes and pathways have previously been associated with ageing and cancer. These observations demonstrate that there are ageing-related genetic elements that differentially affect mortality in cancer patients in an age-dependent manner. Understanding the genetic determinants affecting prognosis differently with age will be invaluable to develop age-specific prognostic biomarkers and personalized therapies that may improve clinical outcomes for older individuals.

Deciphering hallmark processes of aging from interaction networks

BACKGROUND

Aging is broadly considered to be a dynamic process that accumulates unfavourable structural and functional changes in a time dependent fashion, leading to a progressive loss of physiological integrity of an organism, which eventually leads to age-related diseases and finally to death.

SCOPE OF REVIEW

The majority of aging-related studies are based on reductionist approaches, focusing on single genes/proteins or on individual pathways without considering possible interactions between them. Over the last few decades, several such genes/proteins were independently analysed and linked to a role that is affecting the longevity of an organism. However, an isolated analysis on genes and proteins largely fails to explain the mechanistic insight of a complex phenotype due to the involvement and integration of multiple factors.

MAJOR CONCLUSIONS

Technological advance makes it possible to generate high-throughput temporal and spatial data that provide an opportunity to use computer-based methods. These techniques allow us to go beyond reductionist approaches to analyse large-scale networks that provide deeper understanding of the processes that drive aging.

GENERAL SIGNIFICANCE

In this review, we focus on systems biology approaches, based on network inference methods to understand the dynamics of hallmark processes leading to aging phenotypes. We also describe computational methods for the interpretation and identification of important molecular hubs involved in the mechanistic linkage between aging related processes. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang.

Systems-level analysis of human aging genes shed new light on mechanisms of aging

Although studies over the last decades have firmly connected a number of genes and molecular pathways to aging, the aging process as a whole still remains poorly understood. To gain novel insights into the mechanisms underlying aging, instead of considering aging genes individually, we studied their characteristics at the systems level in the context of biological networks. We calculated a comprehensive set of network characteristics for human aging-related genes from the GenAge database. By comparing them with other functional groups of genes, we identified a robust group of aging-specific network characteristics. To find the structural basis and the molecular mechanisms underlying this aging-related network specificity, we also analyzed protein domain interactions and gene expression patterns across different tissues. Our study revealed that aging genes not only tend to be network hubs, playing important roles in communication among different functional modules or pathways, but also are more likely to physically interact and be co-expressed with essential genes. The high expression of aging genes across a large number of tissue types also points to a high level of connectivity among aging genes. Unexpectedly, contrary to the depletion of interactions among hub genes in biological networks, we observed close interactions among aging hubs, which renders the aging subnetworks vulnerable to random attacks and thus may contribute to the aging process. Comparison across species reveals the evolution process of the aging subnetwork. As the organisms become more complex, the complexity of its aging mechanisms increases and their aging hub genes are more functionally connected.