Emerging Omics Approaches in Aging Research

Combination of the biomarkers for aging and cancer? - Challenges and current status

The proportion of patients diagnosed with cancer has been shown to rise with the increasing aging global population. Advanced age is a major risk factor for morbidity and mortality in older adults. As individuals experience varying health statuses, particularly with age, it poses a challenge for medical professionals in the cancer field to obtain standardized treatment outcomes. Hence, relying solely on chronological age and disease-related parameters is inadequate for clinical decision-making for elderly patients. With functional, multimorbidity-related, and psychosocial changes that occur with aging, oncologic diseases may develop and be treated differently from younger patients, leading to unique challenges in treatment efficacy and tolerance. To overcome this challenge, personalized therapy using biomarkers has emerged as a promising solution. Various categories of biomarkers, including inflammatory, hematological, metabolic, endocrine, and DNA modification-related indicators, may display features related to both cancer and aging, aiding in the development of innovative therapeutic approaches for patients with cancer in old age. Furthermore, physical functional measurements as non-molecular phenotypic biomarkers are being investigated for their potential complementary role in structured multidomain strategies to combat age-related diseases such as cancer. This review provides insight into the current developments, recent discoveries, and significant challenges in cancer and aging biomarkers, with a specific focus on their application in advanced age.

How is Big Data reshaping preclinical aging research?

The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.

The association between aging-related monocyte transcriptional networks and comorbidity burden: the Multi-Ethnic Study of Atherosclerosis (MESA)

Translating our knowledge of the biological aging from animal models to humans may give rise to novel approaches of targeting multiple aging-related diseases simultaneously and increasing health span. Here, for the first time, we use transcriptomic signatures of monocytes to identify biological aging pathways underlying multiple aging-related diseases in humans. The ordinal logistic regression was used to cross-sectionally investigate transcriptomics of the comorbidity index in 1264 community-based Multi-Ethnic Study of Atherosclerosis (MESA) adults, 47% Caucasian, 32% Hispanic, 21% African American, and 51% female, aged 55-94 years. The comorbidity index was defined as the number of prevalent aging-related diseases including cardiovascular disease, type-2 diabetes, hypertension, cancer, dementia, chronic kidney disease, chronic obstructive pulmonary disease, and hip fracture. We identified 708 gene transcripts associated with the comorbidity index (FDR < 0.05) after adjusting for age, sex, ethnicity, and study site. In a weighted gene co-expression network analysis, as postulated, aging-related declines in apoptosis/autophagy (OR = 1.21 per SD increment, p = 0.0006) and ribosome/mitochondrion (OR = 0.90 per SD increment, p = 0.05) were positively associated with the comorbidity index. After adjusting for multiple comparisons, we identified 10 comorbidity-associated modules (FDR < 0.05), including the module of apoptosis/autophagy. There were three inter-correlated modules of these 10 involved in the complement subcomponent C1q, Fc gamma receptor I, and Fc gamma receptor III of the immune system, respectively. Aging-related upregulation of these three modules was positively associated with the comorbidity index. The odds of comorbidity increased with more of these modules acting together in a dose-response fashion. In conclusion, transcriptomic analysis of human immune cells may identify biomarker panels indicative of comprehensive biological mechanisms, especially immune signaling pathways, contributing to health aging.

Brain and testicular metabonomics revealed the protective effects of Guilingji on senile sexual dysfunction rats

ETHNOPHARMACOLOGICAL RELEVANCE

Guilingji (GLJ), which has been used to treat male diseases in China for centuries, contains 28 Chinese herbs and was previously established as an effective treatment for male sexual dysfunction. However, its mechanism of action remains unclear.

AIM OF THE STUDY

To explore the efficacy and mechanism of action of GLJ in improving senile sexual dysfunction (SSD) in aging rats.

MATERIALS AND METHODS

An aging rat model of SSD was induced by the subcutaneous injection of d-galactose (300 mg⋅kg^-1) and used to analyse the effects of GLJ (different concentrations of 37.5, 75, and 150 mg⋅kg^-1) on the mating of aging rats. At the end of the 8th week, histopathological analysis of testicular tissues, assessment of the hypothalamic-pituitary-gonadal (HPG) axis hormone levels in serum or brain, and metabonomics analysis of the brain and testicular tissue with liquid chromatography-mass spectrometry was performed to explore the mechanism of action of GLJ.

RESULT

After treatment with GLJ, the mount and ejaculation latency levels were increased in the treatment group than those in model group (P < 0.05), moreover, the testicular morphology was improved. Gonadotropin-releasing hormone (GnRH) and luteinizing hormone (LH) levels in rats were also improved significant (P < 0.05) compared with those in the model group. Furthermore, the metabonomics results in the testicular and brain tissue showed that GLJ improved SSD by adjusting amino acid and lipid metabolism.

CONCLUSION

This study integrated the complementary metabolic profiles of the target tissues. GLJ might affect SSD rats by regulating amino acid and lipid metabolism and may modulate sensitivity to the signaling pathway in the HPG axis. This study provides an essential basis for the broad clinical application of GLJ.

Structured Long-Chain Omega-3 Fatty Acids for Improvement of Cognitive Function during Aging

Although the human lifespan has increased in the past century owing to advances in medicine and lifestyle, the human healthspan has not kept up the same pace, especially in brain aging. Consequently, the role of preventive health interventions has become a crucial strategy, in particular, the identification of nutritional compounds that could alleviate the deleterious effects of aging. Among nutrients to cope with aging in special cognitive decline, the long-chain omega-3 polyunsaturated fatty acids (ω-3 LCPUFAs) docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), have emerged as very promising ones. Due to their neuroinflammatory resolving effects, an increased status of DHA and EPA in the elderly has been linked to better cognitive function and a lower risk of dementia. However, the results from clinical studies do not show consistent evidence and intake recommendations for old adults are lacking. Recently, supplementation with structured forms of EPA and DHA, which can be derived natural forms or targeted structures, have proven enhanced bioavailability and powerful benefits. This review summarizes present and future perspectives of new structures of ω-3 LCPUFAs and the role of "omic" technologies combined with the use of high-throughput in vivo models to shed light on the relationships and underlying mechanisms between ω-3 LCPUFAs and healthy aging.

A Deep-Learning Proteomic-Scale Approach for Drug Design

Computational approaches have accelerated novel therapeutic discovery in recent decades. The Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multitarget therapeutic discovery, repurposing, and design aims to improve their efficacy and safety by employing a holistic approach that computes interaction signatures between every drug/compound and a large library of non-redundant protein structures corresponding to the human proteome fold space. These signatures are compared and analyzed to determine if a given drug/compound is efficacious and safe for a given indication/disease. In this study, we used a deep learning-based autoencoder to first reduce the dimensionality of CANDO-computed drug-proteome interaction signatures. We then employed a reduced conditional variational autoencoder to generate novel drug-like compounds when given a target encoded "objective" signature. Using this approach, we designed compounds to recreate the interaction signatures for twenty approved and experimental drugs and showed that 16/20 designed compounds were predicted to be significantly (p-value ≤ 0.05) more behaviorally similar relative to all corresponding controls, and 20/20 were predicted to be more behaviorally similar relative to a random control. We further observed that redesigns of objectives developed via rational drug design performed significantly better than those derived from natural sources (p-value ≤ 0.05), suggesting that the model learned an abstraction of rational drug design. We also show that the designed compounds are structurally diverse and synthetically feasible when compared to their respective objective drugs despite consistently high predicted behavioral similarity. Finally, we generated new designs that enhanced thirteen drugs/compounds associated with non-small cell lung cancer and anti-aging properties using their predicted proteomic interaction signatures. his study represents a significant step forward in automating holistic therapeutic design with machine learning, enabling the rapid generation of novel, effective, and safe drug leads for any indication.

Circulating Metabolomic Analysis following Cecal Ligation and Puncture in Young and Aged Mice Reveals Age-Associated Temporal Shifts in Nicotinamide and Histidine/Histamine Metabolic Pathways

INTRODUCTION

Aged individuals are at higher risk for morbidity and mortality following acute stressors than similarly stressed young people. Evaluation of age-associated metabolic changes could lead to the identification of specific therapeutic targets to improve outcomes from acute stressors, such as infections, in the elderly. We thus compared the plasma metabolomes of both young and old mice following cecal ligation and puncture (CLP), an accepted model of acute infection and stress.

METHODS

Young (9-17 wks) and aged (78-96 wks) male C57bl/6 mice were subjected to a retro-orbital bleed and two-week recovery prior to sham surgery (laparotomy alone) or CLP. Animals were sacrificed at 4 h, 8 h, or 12 h following intervention, and plasma was isolated from blood for subsequent analysis. Metabolomic analysis of samples were performed (Metabolon; Durham, NC).

RESULTS

Aged animals demonstrated greater intraprocedural mortality than young (30.2% vs. 17.4%, χ ² p = 0.0004), confirming enhanced frailty. Principal component analysis and partial-least squares discriminant analysis of 566 metabolites demonstrated distinct metabolomic shifts following sham surgery or CLP in both young and aged animals. Identification of metabolites of interest using a consensus statistical approach revealed that both the histidine/histamine pathway and the nicotinamide pathway have significant age-associated alterations following CLP.

CONCLUSIONS

The application of untargeted plasma metabolomics identified key pathways underpinning metabolomic responses to CLP in both young and aged animals. Ultimately, these data provide a robust foundation for future mechanistic studies that may assist in improving outcomes in frail patients in response to acute stressors such as infection, trauma, or surgery.

Lipid and metabolite correlation networks specific to clinical and biochemical covariate show differences associated with sexual dimorphism in a cohort of nonagenarians

This study defines and estimates the metabolite-lipidic component association networks constructed from an array of 20 metabolites and 114 lipids identified and quantified via NMR spectroscopy in the serum of a cohort of 355 Italian nonagenarians and ultra-nonagenarian. Metabolite-lipid association networks were built for men and women and related to an array of 101 clinical and biochemical parameters, including the presence of diseases, bio-humoral parameters, familiarity diseases, drugs treatments, and risk factors. Different connectivity patterns were observed in lipids, branched chains amino acids, alanine, and ketone bodies, suggesting their association with the sex-related and sex-clinical condition-related intrinsic metabolic changes. Furthermore, our results demonstrate, using a holistic system biology approach, that the characterization of metabolic structures and their dynamic inter-connections is a promising tool to shed light on the dimorphic pathophysiological mechanisms of aging at the molecular level.

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.

An update in toxicology of ageing

The field of ageing research has been rapidly advancing in recent decades and it had provided insight into the complexity of ageing phenomenon. However, as the organism-environment interaction appears to significantly affect the organismal pace of ageing, the systematic approach for gerontogenic risk assessment of environmental factors has yet to be established. This puts demand on development of effective biomarker of ageing, as a relevant tool to quantify effects of gerontogenic exposures, contingent on multidisciplinary research approach. Here we review the current knowledge regarding the main endogenous gerontogenic pathways involved in acceleration of ageing through environmental exposures. These include inflammatory and oxidative stress-triggered processes, dysregulation of maintenance of cellular anabolism and catabolism and loss of protein homeostasis. The most effective biomarkers showing specificity and relevancy to ageing phenotypes are summarized, as well. The crucial part of this review was dedicated to the comprehensive overview of environmental gerontogens including various types of radiation, certain types of pesticides, heavy metals, drugs and addictive substances, unhealthy dietary patterns, and sedentary life as well as psychosocial stress. The reported effects in vitro and in vivo of both recognized and potential gerontogens are described with respect to the up-to-date knowledge in geroscience. Finally, hormetic and ageing decelerating effects of environmental factors are briefly discussed, as well.

Potential reversal of epigenetic age using a diet and lifestyle intervention: a pilot randomized clinical trial

Manipulations to slow biological aging and extend healthspan are of interest given the societal and healthcare costs of our aging population. Herein we report on a randomized controlled clinical trial conducted among 43 healthy adult males between the ages of 50-72. The 8-week treatment program included diet, sleep, exercise and relaxation guidance, and supplemental probiotics and phytonutrients. The control group received no intervention. Genome-wide DNA methylation analysis was conducted on saliva samples using the Illumina Methylation Epic Array and DNAmAge was calculated using the online Horvath DNAmAge clock (2013). The diet and lifestyle treatment was associated with a 3.23 years decrease in DNAmAge compared with controls (p=0.018). DNAmAge of those in the treatment group decreased by an average 1.96 years by the end of the program compared to the same individuals at the beginning with a strong trend towards significance (p=0.066). Changes in blood biomarkers were significant for mean serum 5-methyltetrahydrofolate (+15%, p=0.004) and mean triglycerides (-25%, p=0.009). To our knowledge, this is the first randomized controlled study to suggest that specific diet and lifestyle interventions may reverse Horvath DNAmAge (2013) epigenetic aging in healthy adult males. Larger-scale and longer duration clinical trials are needed to confirm these findings, as well as investigation in other human populations.

New methodologies in ageing research

Ageing is arguably the most complex phenotype that occurs in humans. To understand and treat ageing as well as associated diseases, highly specialised technologies are emerging that reveal critical insight into the underlying mechanisms and provide new hope for previously untreated diseases. Herein, we describe the latest developments in cutting edge technologies applied across the field of ageing research. We cover emerging model organisms, high-throughput methodologies and machine-driven approaches. In all, this review will give you a glimpse of what will be pushing the field onwards and upwards.

MetaboAge DB: a repository of known ageing-related changes in the human metabolome

Accumulating metabolomics data is starting to become extremely useful in understanding the ageing process, by providing a snapshot into the metabolic state of tissues and organs, at different ages. Molecular studies of such metabolic variations during “normal” ageing can hence guide lifestyle changes and/or medical interventions aimed at improving healthspan and perhaps even lifespan. In this work, we present MetaboAge, a freely accessible database which hosts ageing-related metabolite changes, occurring in healthy individuals. Data is automatically filtered and then manually curated from scientific articles reporting statistically significant associations of human metabolite variations or correlations with ageing. Up to date, MetaboAge contains 408 metabolites annotated with their biological and chemical information, and more than 1515 ageing-related variations, graphically represented on the website grouped by validation methods, sex and age-groups. The MetaboAge database aims to continually structure the expanding information from the field of metabolomics in relation to ageing, thus making it more accessible for further research in gerontology.

Age and Gender Characteristics of the Infrared Spectra of Normal Human Saliva

The comparison of the characteristics of the infrared (IR) spectra of saliva of healthy volunteers was carried out based on gender and age. It is shown that statistically significant differences between male and female groups are observed for the absorption bands of proteins and lipids. At the same time, the absorbance of the bands assigned to proteins and nucleic acids is higher for males, whereas the absorbance of the bands assigned to lipids is higher in the group of females. It is established that the correlation relationships of the characteristics of the spectra and age are weakly expressed. Thus, when forming the criteria of the norm and pathology for saliva, it is necessary to take into account the gender of the subjects, while there are no strict requirements for taking into account age periodization. Nevertheless, the revealed patterns are valid only for the composition of the saliva of healthy volunteers, the extension of the results to groups of patients with various diseases, as well as other biological fluids, requires additional testing.

1H NMR-based metabolomics revealed the protective effects of Guilingji on the testicular dysfunction of aging rats

ETHNOPHARMACOLOGICAL RELEVANCE

Guilingji (GLJ), a famous and classical traditional Chinese medicine (TCM) prescription, has been used to extend the lifespan and improve the life qualities of the elderly for hundreds of years in China.

AIM OF THE STUDY

We aimed to explore the protective effects of GLJ on the testicular dysfunction of aging rats, as well as the regulating effects of GLJ on the metabolic disturbance and metabolite changes in natural aging rats.

MATERIALS AND METHODS

Forty 23-month-old rats were divided randomly into four groups, including the old control group and three groups of GLJ treatment at 37.5, 75, and 150 mg/kg doses, respectively. Additionally, 10 four-month rats were included as the youth control group. Testicular dysfunction was first evaluated by measuring the changes in the wet weights of the testicles, concentration of serum testosterone (T), and morphologic changes of the testis. Subsequently, an ¹H NMR-based metabolomics approach coupled with multivariate analysis, including partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied to monitor the metabolite changes.

RESULTS

Compared with the old control group, the wet weights of the testicles and T concentration were significantly increased, while the morphologic abnormality of testicular tissues was improved by a 4-week treatment course with GLJ. Furthermore, compared with the old control group, the urinary levels of alanine, pantothenate, phenylalanine, β-hydroxybutyrate and pyruvate were significantly decreased after a 4-week treatment course with GLJ. Additionally, we found that amino acid metabolism and pyruvate metabolism were significantly involved in the regulatory effect of GLJ.

CONCLUSIONS

The current findings provided, for the first time, sound evidence of the protective effects of GLJ on testicular dysfunction from both biochemical and metabolomics perspectives. The mechanisms of GLJ could be related to regulating amino acid metabolism and pyruvate metabolism. The current study lays an important foundation for further research and for the broad clinical application of GLJ.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.