Undulating changes in human plasma proteome profiles across the lifespan

Proteomics and Epidemiological Models of Human Aging

Human aging is associated with a decline of physical and cognitive function and high susceptibility to chronic diseases, which is influenced by genetics, epigenetics, environmental, and socio-economic status. In order to identify the factors that modulate the aging process, established measures of aging mechanisms are required, that are both robust and feasible in humans. It is also necessary to connect these measures to the phenotypes of aging and their functional consequences. In this review, we focus on how this has been addressed from an epidemiologic perspective using proteomics. The key aspects of epidemiological models of aging can be incorporated into proteomics and other omics which can provide critical detailed information on the molecular and biological processes that change with age, thus unveiling underlying mechanisms that drive multiple chronic conditions and frailty, and ideally facilitating the identification of new effective approaches for prevention and treatment.

Autoimmunomic Signatures of Aging and Age-Related Neurodegenerative Diseases Are Associated With Brain Function and Ribosomal Proteins

Biological aging is a complex process featured by declined function of cells and tissues, including those of the immune system. As a consequence, aging affects the expression and development of autoantibodies and autoreactive T cells, which can be seen in their sum as the autoimmunome of an individual. In this study we analyzed whether sets of autoimmune features are associated with specific phenotypes which form autoimmunomic signatures related to age and neurodegenerative diseases. The autoantibody profile data of healthy subjects and patients from the GEO database was used to explore autoimmunomic signatures of aging and three neurodegenerative diseases including Parkinson's disease (PD), Alzheimer disease (AD) and Multiple Sclerosis (MS). Our results demonstrate that the autoimmunomic signature of aging is featured by an undulated increase of IgG autoantibodies associated with learning and behavior and a consistent increase of IgG autoantibodies related to ribosome and translation, and the autoimmunomic signature of aging are also associated with age-related neurodegenerative diseases. Intriguingly, Differential Expression-Sliding Window Analysis (DE-SWAN) identified three waves of changes of autoantibodies during aging at an age of 30, 50, and 62 years, respectively. Furthermore, IgG autoantibodies, in particular those against ribosomal proteins, could be used as prediction markers for aging and age-related neurodegenerative diseases. Therefore, this study for the first time uncovers comprehensive autoimmunomic signatures for aging and age-related neurodegenerative diseases.

Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging

Introduction

Blood proteins are emerging as candidate biomarkers for Alzheimer's disease (AD). We systematically profiled the plasma proteome to identify novel AD blood biomarkers and develop a high‐performance, blood‐based test for AD.

Methods

We quantified 1160 plasma proteins in a Hong Kong Chinese cohort by high‐throughput proximity extension assay and validated the results in an independent cohort. In subgroup analyses, plasma biomarkers for amyloid, tau, phosphorylated tau, and neurodegeneration were used as endophenotypes of AD.

Results

We identified 429 proteins that were dysregulated in AD plasma. We selected 19 “hub proteins” representative of the AD plasma protein profile, which formed the basis of a scoring system that accurately classified clinical AD (area under the curve  = 0.9690–0.9816) and associated endophenotypes. Moreover, specific hub proteins exhibit disease stage‐dependent dysregulation, which can delineate AD stages.

Discussion

This study comprehensively profiled the AD plasma proteome and serves as a foundation for a high‐performance, blood‐based test for clinical AD screening and staging.

The secretome mouse provides a genetic platform to delineate tissue-specific in vivo secretion

At present, it remains difficult to deconvolute serum in order to identify the cell or tissue origin of a given circulating protein. Here, by exploiting the properties of proximity biotinylation, we describe a mouse model that enables the elucidation of the in vivo tissue-specific secretome. As an example, we demonstrate how we can readily identify in vivo endothelial-specific secretion as well as how this model allows for the characterization of muscle-derived serum proteins that either increase or decrease with exercise. This genetic platform should, therefore, be of wide utility in understanding normal and disease physiology and for the rational design of tissue-specific disease biomarkers.

Effect of longevity genetic variants on the molecular aging rate

We conducted a genome-wide association study of 1320 centenarians from the New England Centenarian Study (median age = 104 years) and 2899 unrelated controls using >9 M genetic variants imputed to the HRC panel of ~65,000 haplotypes. The genetic variants with the most significant associations were correlated to 4131 proteins that were profiled in the serum of a subset of 224 study participants using a SOMAscan array. The genetic associations were replicated in a genome-wide association study of 480 centenarians and ~800 controls of Ashkenazi Jewish descent. The proteomic associations were replicated in a proteomic scan of approximately 1000 Ashkenazi Jewish participants from a third cohort. The analysis replicated a protein signature associated with APOE genotypes and confirmed strong overexpression of BIRC2 (p < 5E-16) and under-expression of APOB in carriers of the APOE2 allele (p < 0.05). The analysis also discovered and replicated associations between longevity variants and slower changes of protein biomarkers of aging, including a novel protein signature of rs2184061 (CDKN2A/CDKN2B in chromosome 9) that suggests a genetic regulation of GDF15. The analyses showed that longevity variants correlate with proteome signatures that could be manipulated to discover healthy-aging targets.

The impact of donor sex and age on stored platelet metabolism and post-transfusion recovery

BACKGROUND

The impact of donor biology on blood component storability is increasingly appreciated as a determinant of the storage lesion and post-transfusion performances. Platelet metabolism is affected by age and it is critical to platelet responses to activating stimuli in an age-dependent manner. Sex has been previously highlighted as a contributing factor to the platelet proteomics lesion. However, little is known about the impact of donor sex and age on stored platelet metabolism and post-transfusion capacity to circulate.

MATERIALS AND METHODS

Apheresis platelets were donated via apheresis by 21 healthy volunteers (12 males and 9 females; ages 20 to 59). Metabolomics analyses were performed at day 0 and after 5 days of storage at 22+2 °C, along with autologous post-transfusion recovery and survival studies with ⁵¹Cr and ¹¹¹In.

RESULTS

Sex and age significantly impacted platelet metabolism at baseline and upon storage. Platelets from older, male donors were characterised by higher levels of Krebs cycle metabolites, pentose phosphate pathway intermediates and byproducts, deaminated purines and long chain fatty acids. These metabolites ranked amongst the top significant correlates to post-transfusion recoveries. Glutathione homeostasis and sphingosine 1-phosphate were the top positive correlates to long term survival, which was lower in platelets from older, male donors - without reaching statistical significance.

DISCUSSION

In this study we report that donor sex and age have a significant impact on platelet metabolism. Novel metabolic correlates to platelet post-transfusion performances (24 h recovery and long-term survival) were identified through high-resolution, stable isotope-labeled internal standard-assisted metabolomics approach.

Systems biology in cardiovascular disease: a multiomics approach

Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for analysing these data but must be applied with an understanding of the relevant biological and computational theories. Through applying these techniques to omics data, systems biology addresses the problems posed by the complex organization of biological processes. In this Review, we describe the techniques and sources of omics data, outline network theory, and highlight exemplars of novel approaches that combine gene regulatory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics techniques to provide new insights into cardiovascular disease. The use of systems approaches will become necessary to integrate data from more than one omic technique. Although understanding the interactions between different omics data requires increasingly complex concepts and methods, we argue that hypothesis-driven investigations and independent validation must still accompany these novel systems biology approaches to realize their full potential.

Large-scale plasma proteomic analysis identifies proteins and pathways associated with dementia risk

The plasma proteomic changes that precede the onset of dementia could yield insights into disease biology and highlight new biomarkers and avenues for intervention. We quantified 4,877 plasma proteins in nondemented older adults in the Atherosclerosis Risk in Communities cohort and performed a proteome-wide association study of dementia risk over five years (n = 4,110; 428 incident cases). Thirty-eight proteins were associated with incident dementia after Bonferroni correction. Of these, 16 were also associated with late-life dementia risk when measured in plasma collected nearly 20 years earlier, during mid-life. Two-sample Mendelian randomization causally implicated two dementia-associated proteins (SVEP1 and angiostatin) in Alzheimer's disease. SVEP1, an immunologically relevant cellular adhesion protein, was found to be part of larger dementia-associated protein networks, and circulating levels were associated with atrophy in brain regions vulnerable to Alzheimer's pathology. Pathway analyses for the broader set of dementia-associated proteins implicated immune, lipid, metabolic signaling and hemostasis pathways in dementia pathogenesis.

Pilot proteomic analysis of cerebrospinal fluid in Alzheimer's disease

Proteomic analysis of cerebrospinal fluid (CSF) holds great promise in understanding the progression of neurodegenerative diseases, including Alzheimer's disease (AD). As one of the primary reservoirs of neuronal biomolecules, CSF provides a window into the biochemical and cellular aspects of the neurological environment. CSF can be drawn from living participants allowing the potential alignment of clinical changes with these biochemical markers. Using cutting-edge mass spectrometry technologies, we perform a streamlined proteomic analysis of CSF. We quantify greater than 700 proteins across 10 pairs of age- and sex-matched participants in approximately one hour of analysis time each. Using the paired participant study structure, we identify a small group of biologically relevant proteins that show substantial changes in abundance between cognitive normal and AD participants, which were then analyzed at the peptide level using parallel reaction monitoring experiments. Our findings suggest the utility of fractionating a single sample and using matching to increase proteomic depth in cerebrospinal fluid, as well as the potential power of an expanded study.

The aging lung: Physiology, disease, and immunity

The population is aging at a rate never seen before in human history. As the number of elderly adults grows, it is imperative we expand our understanding of the underpinnings of aging biology. Human lungs are composed of a unique panoply of cell types that face ongoing chemical, mechanical, biological, immunological, and xenobiotic stress over a lifetime. Yet, we do not fully appreciate the mechanistic drivers of lung aging and why age increases the risk of parenchymal lung disease, fatal respiratory infection, and primary lung cancer. Here, we review the molecular and cellular aspects of lung aging, local stress response pathways, and how the aging process predisposes to the pathogenesis of pulmonary disease. We place these insights into context of the COVID-19 pandemic and discuss how innate and adaptive immunity within the lung is altered with age.

Noninvasive Analysis Using Data-Independent Acquisition Mass Spectrometry: New Epidermal Proteins That Reveal Sex Differences in the Aging Process

The development of mass spectrometry has provided a method with extremely high sensitivity and selectivity that can be used to identify protein biomarkers. Epidermal proteins, lipids, and cornified envelopes are involved in the formation of the skin epidermal barrier. The epidermal protein composition changes with age. Therefore, quantitative proteomic changes may be indicative of skin aging. We sought to utilize data-independent acquisition mass spectrometry for noninvasive analysis of epidermal proteins in healthy Chinese individuals of different age groups and sexes. In our study, we completed high-throughput protein detection, analyzed protein differences with MaxQuant software, and performed statistical analyses of the proteome. We obtained interesting findings regarding ceruloplasmin (CP), which exhibited significant differences and is involved in ferroptosis, a signaling pathway significantly associated with aging. There were also several proteins that differed between sexes in the younger group, but the sex differences disappeared with aging. These proteins, which were associated with both aging processes and sex differences, are involved in signaling pathways such as apoptosis, oxidative stress, and genomic stability and can serve as candidate biomarkers for sex differences during aging. Our approach for noninvasive detection of epidermal proteins and its application to accurately quantify protein expression can provide ideas for future epidermal proteomics studies.

Proteomics in aging research: A roadmap to clinical, translational research

The identification of plasma proteins that systematically change with age and, independent of chronological age, predict accelerated decline of health is an expanding area of research. Circulating proteins are ideal translational "omics" since they are final effectors of physiological pathways and because physicians are accustomed to use information of plasma proteins as biomarkers for diagnosis, prognosis, and tracking the effectiveness of treatments. Recent technological advancements, including mass spectrometry (MS)-based proteomics, multiplexed proteomic assay using modified aptamers (SOMAscan), and Proximity Extension Assay (PEA, O-Link), have allowed for the assessment of thousands of proteins in plasma or other biological matrices, which are potentially translatable into new clinical biomarkers and provide new clues about the mechanisms by which aging is associated with health deterioration and functional decline. We carried out a detailed literature search for proteomic studies performed in different matrices (plasma, serum, urine, saliva, tissues) and species using multiple platforms. Herein, we identified 232 proteins that were age-associated across studies. Enrichment analysis of the 232 age-associated proteins revealed metabolic pathways previously connected with biological aging both in animal models and in humans, most remarkably insulin-like growth factor (IGF) signaling, mitogen-activated protein kinases (MAPK), hypoxia-inducible factor 1 (HIF1), cytokine signaling, Forkhead Box O (FOXO) metabolic pathways, folate metabolism, advance glycation end products (AGE), and receptor AGE (RAGE) metabolic pathway. Information on these age-relevant proteins, likely expanded and validated in longitudinal studies and examined in mechanistic studies, will be essential for patient stratification and the development of new treatments aimed at improving health expectancy.

Longitudinal course of GDF15 levels before acute hospitalization and death in the general population

Growth differentiation 15 (GDF15) is a potential novel biomarker of biological aging. To separate the effects of chronological age and birth cohort from biological age, longitudinal studies investigating the associations of GDF15 levels with adverse health outcomes are needed. We investigated changes in GDF15 levels over 10 years in an age-stratified sample of the general population and their relation to the risk of acute hospitalization and death. Serum levels of GDF15 were measured three times in 5-year intervals in 2176 participants aged 30, 40, 50, or 60 years from the Danish population-based DAN-MONICA cohort. We assessed the association of single and repeated GDF15 measurements with the risk of non-traumatic acute hospitalizations. We tested whether changes in GDF15 levels over 10 years differed according to the frequency of hospitalizations within 2 years or survival within 20 years, after the last GDF15 measurement. The change in GDF15 levels over time was dependent on age and sex. Higher GDF15 levels and a greater increase in GDF15 levels were associated with an increased risk of acute hospitalization in adjusted Cox regression analyses. Participants with more frequent admissions within 2 years, and those who died within 20 years, after the last GDF15 measurement already had elevated GDF15 levels at baseline and experienced greater increases in GDF15 levels during the study. The change in GDF15 levels was associated with changes in C-reactive protein and biomarkers of kidney, liver, and cardiac function. Monitoring of GDF15 starting in middle-aged could be valuable for the prediction of adverse health outcomes.

Deep learning in systems medicine

Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features needed for a given task from high-dimensional, heterogeneous data, deep learning (DL) holds great promise in this endeavour. This review paper addresses the main developments of DL algorithms and a set of general topics where DL is decisive, namely, within the SM landscape. It discusses how DL can be applied to SM with an emphasis on the applications to predictive, preventive and precision medicine. Several key challenges have been highlighted including delivering clinical impact and improving interpretability. We used some prototypical examples to highlight the relevance and significance of the adoption of DL in SM, one of them is involving the creation of a model for personalized Parkinson's disease. The review offers valuable insights and informs the research in DL and SM.

Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics

Background

Clinical and epidemiological studies have suggested systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are comorbidities and common genetic etiologies can partly explain such coexistence. However, shared genetic determinations underlying the two diseases remain largely unknown.

Methods

Our analysis relied on summary statistics available from genome-wide association studies of SLE (N = 23,210) and RA (N = 58,284). We first evaluated the genetic correlation between RA and SLE through the linkage disequilibrium score regression (LDSC). Then, we performed a multiple-tissue eQTL (expression quantitative trait loci) weighted integrative analysis for each of the two diseases and aggregated association evidence across these tissues via the recently proposed harmonic mean P-value (HMP) combination strategy, which can produce a single well-calibrated P-value for correlated test statistics. Afterwards, we conducted the pleiotropy-informed association using conjunction conditional FDR (ccFDR) to identify potential pleiotropic genes associated with both RA and SLE.

Results

We found there existed a significant positive genetic correlation (r_g = 0.404, P = 6.01E-10) via LDSC between RA and SLE. Based on the multiple-tissue eQTL weighted integrative analysis and the HMP combination across various tissues, we discovered 14 potential pleiotropic genes by ccFDR, among which four were likely newly novel genes (i.e., INPP5B, OR5K2, RP11-2C24.5, and CTD-3105H18.4). The SNP effect sizes of these pleiotropic genes were typically positively dependent, with an average correlation of 0.579. Functionally, these genes were implicated in multiple auto-immune relevant pathways such as inositol phosphate metabolic process, membrane and glucagon signaling pathway.

Conclusion

This study reveals common genetic components between RA and SLE and provides candidate associated loci for understanding of molecular mechanism underlying the comorbidity of the two diseases.

Serum GDF15 Level Is Independent of Sarcopenia in Older Asian Adults

BACKGROUND

Growth differentiation factor 15 (GDF15), induced by tissue inflammation and mitochondrial stress, has received significant attention as a biomarker of mitochondrial dysfunction and has been implicated in various age-related diseases. However, the association between circulating GDF15 and sarcopenia-associated outcomes in older adults remains to be established.

AIM

To validate previous experimental data and to investigate the possible role of GDF15 in aging and muscle physiology in humans, this study examined serum GDF15 levels in relation to sarcopenia-related parameters in a cohort of older Asian adults.

METHODS

Muscle mass and muscle function-related parameters, such as grip strength, gait speed, chair stands, and short physical performance battery score were evaluated by experienced nurses in 125 geriatric participants with or without sarcopenia. Sarcopenia was diagnosed using the Asian-specific cutoff points. Serum GDF15 levels were measured using an enzyme immunoassay kit.

RESULTS

Serum GDF15 levels were not significantly different according to sarcopenia status, muscle mass, muscle strength, and physical performance and were not associated with the skeletal muscle index, grip strength, gait speed, time to complete 5 chair stands, and short physical performance battery score, regardless of adjustments for sex, age, and BMI.

CONCLUSIONS

These findings indicate that the definite role of GDF15 on muscle metabolism observed in animal models might not be evident in humans and that elevated GDF15 levels might not predict the risk for sarcopenia, at least in older Asian adults.

Aging biomarkers and the measurement of health and risk

Prevention of age-related disorders is increasingly in focus of health policies, and it is hoped that early intervention on processes of deterioration can promote healthier and longer lives. New opportunities to slow down the aging process are emerging with new fields such as personalized nutrition. Data-intensive research has the potential to improve the precision of existing risk factors, e.g., to replace coarse-grained markers such as blood cholesterol with more detailed multivariate biomarkers. In this paper, we follow an attempt to develop a new aging biomarker. The vision among the project consortium, comprising both research and industrial partners, is that the new biomarker will be predictive of a range of age-related conditions, which may be preventable through personalized nutrition. We combine philosophical analysis and ethnographic fieldwork to explore the possibilities and challenges of managing aging through bodily signs that are not straightforwardly linked to symptomatic disease. We document how the improvement of measurement brings about new conceptual challenges of demarcating healthy and unhealthy states. Moreover, we highlight that the reframing of aging as risk has social and ethical implications, as it is generative of normative notions of what constitutes successful aging and good citizenship.

Aging biomarkers and the measurement of health and risk

Prevention of age-related disorders is increasingly in focus of health policies, and it is hoped that early intervention on processes of deterioration can promote healthier and longer lives. New opportunities to slow down the aging process are emerging with new fields such as personalized nutrition. Data-intensive research has the potential to improve the precision of existing risk factors, e.g., to replace coarse-grained markers such as blood cholesterol with more detailed multivariate biomarkers. In this paper, we follow an attempt to develop a new aging biomarker. The vision among the project consortium, comprising both research and industrial partners, is that the new biomarker will be predictive of a range of age-related conditions, which may be preventable through personalized nutrition. We combine philosophical analysis and ethnographic fieldwork to explore the possibilities and challenges of managing aging through bodily signs that are not straightforwardly linked to symptomatic disease. We document how the improvement of measurement brings about new conceptual challenges of demarcating healthy and unhealthy states. Moreover, we highlight that the reframing of aging as risk has social and ethical implications, as it is generative of normative notions of what constitutes successful aging and good citizenship.

Unite to predict

Integrating the analysis of molecular data from different sources may improve our understanding of the effects of biological aging.

Molecular and phenotypic analysis of rodent models reveals conserved and species-specific modulators of human sarcopenia

Sarcopenia, the age-related loss of skeletal muscle mass and function, affects 5-13% of individuals aged over 60 years. While rodents are widely-used model organisms, which aspects of sarcopenia are recapitulated in different animal models is unknown. Here we generated a time series of phenotypic measurements and RNA sequencing data in mouse gastrocnemius muscle and analyzed them alongside analogous data from rats and humans. We found that rodents recapitulate mitochondrial changes observed in human sarcopenia, while inflammatory responses are conserved at pathway but not gene level. Perturbations in the extracellular matrix are shared by rats, while mice recapitulate changes in RNA processing and autophagy. We inferred transcription regulators of early and late transcriptome changes, which could be targeted therapeutically. Our study demonstrates that phenotypic measurements, such as muscle mass, are better indicators of muscle health than chronological age and should be considered when analyzing aging-related molecular data.

A neuronal blood marker is associated with mortality in old age

Neurofilament light chain (NfL) has emerged as a promising blood biomarker for the progression of various neurological diseases. NfL is a structural protein of nerve cells, and elevated NfL levels in blood are thought to mirror damage to the nervous system. We find that plasma NfL levels increase in humans with age (n = 122; 21-107 years of age) and correlate with changes in other plasma proteins linked to neural pathways. In centenarians (n = 135), plasma NfL levels are associated with mortality equally or better than previously described multi-item scales of cognitive or physical functioning, and this observation was replicated in an independent cohort of nonagenarians (n = 180). Plasma NfL levels also increase in aging mice (n = 114; 2-30 months of age), and dietary restriction, a paradigm that extends lifespan in mice, attenuates the age-related increase in plasma NfL levels. These observations suggest a contribution of nervous system functional deterioration to late-life mortality.

Cellular and Intercellular Homeostasis in Adipose Tissue with Mitochondria-Specific Stress

Paracrine interactions are imperative for the maintenance of adipose tissue intercellular homeostasis, and intracellular organelle dysfunction results in local and systemic alterations in metabolic homeostasis. It is currently accepted that mitochondrial proteotoxic stress activates the mitochondrial unfolded protein response (UPRmt) in vitro and in vivo. The induction of mitochondrial chaperones and proteases during the UPRmt is a key cell-autonomous mechanism of mitochondrial quality control. The UPRmt also affects systemic metabolism through the secretion of cell non-autonomous peptides and cytokines (hereafter, metabokines). Mitochondrial function in adipose tissue plays a pivotal role in whole-body metabolism and human diseases. Despite continuing interest in the role of the UPRmt and quality control pathways of mitochondria in energy metabolism, studies on the roles of the UPRmt and metabokines in white adipose tissue are relatively sparse. Here, we describe the role of the UPRmt in adipose tissue, including adipocytes and resident macrophages, and the interactive roles of cell non-autonomous metabokines, particularly growth differentiation factor 15, in local adipose cellular homeostasis and systemic energy metabolism.

Protein signatures of centenarians and their offspring suggest centenarians age slower than other humans

Using samples from the New England Centenarian Study (NECS), we sought to characterize the serum proteome of 77 centenarians, 82 centenarians' offspring, and 65 age-matched controls of the offspring (mean ages: 105, 80, and 79 years). We identified 1312 proteins that significantly differ between centenarians and their offspring and controls (FDR < 1%), and two different protein signatures that predict longer survival in centenarians and in younger people. By comparing the centenarian signature with 2 independent proteomic studies of aging, we replicated the association of 484 proteins of aging and we identified two serum protein signatures that are specific of extreme old age. The data suggest that centenarians acquire similar aging signatures as seen in younger cohorts that have short survival periods, suggesting that they do not escape normal aging markers, but rather acquire them much later than usual. For example, centenarian signatures are significantly enriched for senescence-associated secretory phenotypes, consistent with those seen with younger aged individuals, and from this finding, we provide a new list of serum proteins that can be used to measure cellular senescence. Protein co-expression network analysis suggests that a small number of biological drivers may regulate aging and extreme longevity, and that changes in gene regulation may be important to reach extreme old age. This centenarian study thus provides additional signatures that can be used to measure aging and provides specific circulating biomarkers of healthy aging and longevity, suggesting potential mechanisms that could help prolong health and support longevity.

Automated 16-Plex Plasma Proteomics with Real-Time Search and Ion Mobility Mass Spectrometry Enables Large-Scale Profiling in Naked Mole-Rats and Mice

Performing large-scale plasma proteome profiling is challenging due to limitations imposed by lengthy preparation and instrument time. We present a fully automated multiplexed proteome profiling platform (AutoMP3) using the Hamilton Vantage liquid handling robot capable of preparing hundreds to thousands of samples. To maximize protein depth in single-shot runs, we combined 16-plex Tandem Mass Tags (TMTpro) with high-field asymmetric waveform ion mobility spectrometry (FAIMS Pro) and real-time search (RTS). We quantified over 40 proteins/min/sample, doubling the previously published rates. We applied AutoMP3 to investigate the naked mole-rat plasma proteome both as a function of the circadian cycle and in response to ultraviolet (UV) treatment. In keeping with the lack of synchronized circadian rhythms in naked mole-rats, we find few circadian patterns in plasma proteins over the course of 48 h. Furthermore, we quantify many disparate changes between mice and naked mole-rats at both 48 h and one week after UV exposure. These species differences in plasma protein temporal responses could contribute to the pronounced cancer resistance observed in naked mole-rats. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD022891.

Cancer Treatment-Induced Accelerated Aging in Cancer Survivors: Biology and Assessment

Rapid improvements in cancer survival led to the realization that many modalities used to treat or control cancer may cause accelerated aging in cancer survivors. Clinically, "accelerated aging" phenotypes in cancer survivors include secondary cancers, frailty, chronic organ dysfunction, and cognitive impairment, all of which can impact long-term health and quality of life in cancer survivors. The treatment-induced accelerated aging in cancer survivors could be explained by telomere attrition, cellular senescence, stem cell exhaustion, DNA damage, and epigenetic alterations. Several aging clocks and biomarkers of aging have been proposed to be potentially useful in estimating biological age, which can provide specific information about how old an individual is biologically independent of chronological age. Measuring biological age in cancer survivors may be important for two reasons. First, it can better predict the risk of cancer treatment-related comorbidities than chronological age. Second, biological age may provide additional value in evaluating the effects of treatments and personalizing cancer therapies to maximize efficacy of treatment. A deeper understanding of treatment-induced accelerated aging in individuals with cancer may lead to novel strategies that reduce the accelerated aging and improve the quality of life in cancer survivors.

Fractional re-distribution among cell motility states during ageing

Ageing in humans is associated with the decreased capacity to regulate cell physiology. Cellular properties, such as cell morphology and mechanics, encode ageing information, and can therefore be used as robust biomarkers of ageing. Using a panel of dermal fibroblasts derived from healthy donors spanning a wide age range, we observe an age-associated decrease in cell motility. By taking advantage of the single-cell nature of our motility data, we classified cells based on spatial and activity patterns to define age-dependent motility states. We show that the age-dependent decrease in cell motility is not due to the reduced motility of all cells, but results from the fractional re-distribution among motility states. These findings highlight an important feature of ageing cells characterized by a reduction of cellular heterogeneity in older adults relative to post-adolescent/adults. Furthermore, these results point to a mechanistic framework of ageing, with potential applications in deciphering emergent ageing phenotypes and biomarker development.

Asynchronous, contagious and digital aging

Aging has largely been defined by analog measures of organ and organismal dysfunction. This has led to the characterization of aging processes at the molecular and cellular levels that underlie these gradual changes. However, current knowledge does not fully explain the growing body of data emerging from large epidemiological, systems biology, and single cell studies of entire organisms pointing to varied rates of aging between individuals (different functionality and lifespan), across lifespan (asynchronous aging), and within an organism at the tissue and organ levels (aging mosaicism). Here we consider these inhomogeneities in the broader context of the rate of aging and from the perspective of underlying cellular changes. These changes reflect genetic, environmental, and stochastic factors that cells integrate to adopt new homeostatic, albeit less functional, states, such as cellular senescence. In this sense, cellular aging can be viewed, at least in part, as a quantal process we refer to as "digital aging". Nevertheless, analog declines of tissue dysfunction and organ failure with age could be the sum of underlying digital events. Importantly, cellular aging, digital or otherwise, is not uniform across time or space within the organism or between organisms of the same species. Certain tissues may exhibit earliest signs of cellular aging, acting as drivers for organismal aging as signals from those driver cells within those tissues may accelerate the aging of other cells locally or even systemically. Advanced methodologies at the systems level and at the single cell level are likely to continue to refine our understanding to the processes of how cells and tissues age and how the integration of those processes leads to the complexities of individual, organismal aging.

Association of GDF15 With Inflammation and Physical Function During Aging and Recovery After Acute Hospitalization: A Longitudinal Study of Older Patients and Age-Matched Controls

Growth differentiation factor 15 (GDF15) is a stress-induced cytokine. Its plasma levels increase during aging and acute illness. In older Patients and age-matched Controls, we evaluated whether GDF15 levels (i) were associated with recovery after acute illness, and (ii) reflected different trajectories of aging and longitudinal changes in health measures. Fifty-two older Patients (≥65 years) were included upon admission to the emergency department (ED). At 30 days after discharge (time of matching), Patients were matched 1:1 on age and sex with Controls who had not been hospitalized within 2 years of inclusion. Both groups were followed up after 1 year. We assessed plasma levels of GDF15 and inflammatory biomarkers, frailty, nutritional status (mini nutritional assessment short-form), physical and cognitive function, and metabolic biomarkers. In Patients, elevated GDF15 levels at ED admission were associated with poorer resolution of inflammation (soluble urokinase plasminogen activator receptor [suPAR]), slowing of gait speed, and declining nutritional status between admission and 30-day follow-up. At time of matching, Patients were frailer and overall less healthy than age-matched Controls. GDF15 levels were significantly associated with participant group, on average Patients had almost 60% higher GDF15 than age-matched Controls, and this difference was partly mediated by reduced physical function. Increases in GDF15 levels between time of matching and 1-year follow-up were associated with increases in levels of interleukin-6 in Patients, and tumor necrosis factor-α and suPAR in age-matched Controls. In older adults, elevated GDF15 levels were associated with signs of accelerated aging and with poorer recovery after acute illness.

Methionine transsulfuration pathway is upregulated in long-lived humans

Available evidences point to methionine metabolism as a key target to study the molecular adaptive mechanisms underlying differences in longevity. The plasma methionine metabolic profile was determined using a LC-MS/MS platform to systematically define specific phenotypic patterns associated with genotypes of human extreme longevity (centenarians). Our findings demonstrate the presence of a specific plasma profile associated with human longevity characterized by an enhanced transsulfuration pathway and tricarboxylic acid (TCA) cycle intermediates, as well as a reduced content of specific amino acids. Furthermore, our work reveals that centenarians maintain a strongly correlated methionine metabolism, suggesting an improved network integrity, homeostasis and more tightly regulated metabolism. We have discovered a particular methionine signature related to the condition of extreme longevity, allowing the identification of potential mechanisms and biomarkers of healthy aging.

Association of a Serum Protein Signature With Rheumatoid Arthritis Development

OBJECTIVE

The pathophysiologic events that precede the onset of rheumatoid arthritis (RA) remain incompletely understood. This study was undertaken to identify changes in the serum proteome that precede the onset of RA, with the aim of providing new insights into the pathogenic mechanisms that lead to its development.

METHODS

In a cohort of first-degree relatives of Indigenous North American RA patients, the SomaScan proteomics platform was used to determine the levels of 1,307 proteins in multiple longitudinal serum samples from 17 individuals who were followed up prospectively to the time of disease onset. Proteomic signatures from this group of individuals (designated the progressor group) were compared to those in a group of individuals who were considered at risk of developing RA, stratified as either positive (n = 63) or negative (n = 47) for anti-citrullinated protein antibodies (ACPAs) (designated the at-risk group). Machine learning was used to identify a protein signature that could accurately classify those individuals at highest risk of future RA development.

RESULTS

A preclinical proteomic signature that differentiated RA progressors from at-risk individuals, irrespective of ACPA status, was identified (area under the curve 0.913, accuracy 91.2%). Importantly, the predictive preclinical proteomic signature was present not only in serum samples obtained close to the onset of RA, but also in serum samples obtained a median of 30.9 months prior to onset. Network analysis implicated the activation of Toll-like receptor 2 and production of tumor necrosis factor and interleukin-1 as key events that precede RA progression.

CONCLUSION

Alterations in the serum proteome in the preclinical phase of RA can emerge years prior to the onset of disease. Our findings suggest that the serum proteome provides a rich source of proteins serving both to classify at-risk individuals and to identify molecular pathways involved in the development of clinically detectable RA.

It's in Our Blood: A Glimpse of Personalized Medicine

Recent advances in protein profiling technology has facilitated simultaneous measurement of thousands of proteins in large population studies, exposing the depth and complexity of the plasma and serum proteomes. This revealed that proteins in circulation were organized into regulatory modules under genetic control and closely associated with current and future common diseases. Unlike networks in solid tissues, serum protein networks comprise members synthesized across different tissues of the body. Genetic analysis reveals that this cross-tissue regulation of the serum proteome participates in systemic homeostasis and mirrors the global disease state of individuals. Here, we discuss how application of this information in routine clinical evaluations may transform the future practice of medicine.

ARDD 2020: from aging mechanisms to interventions

Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead to novel discoveries to treat age-related diseases. The present review summarizes presentations from the 7th Annual Aging Research and Drug Discovery (ARDD) meeting, held online on the 1st to 4th of September 2020. The meeting covered topics related to new methodologies to study aging, knowledge about basic mechanisms of longevity, latest interventional strategies to target the aging process as well as discussions about the impact of aging research on society and economy. More than 2000 participants and 65 speakers joined the meeting and we already look forward to an even larger meeting next year. Please mark your calendars for the 8th ARDD meeting that is scheduled for the 31st of August to 3rd of September, 2021, at Columbia University, USA.

Decline in biological resilience as key manifestation of aging: Potential mechanisms and role in health and longevity

Decline in biological resilience (ability to recover) is a key manifestation of aging that contributes to increase in vulnerability to death with age eventually limiting longevity even in people without major chronic diseases. Understanding the mechanisms of this decline is essential for developing efficient anti-aging and pro-longevity interventions. In this paper we discuss: a) mechanisms of the decline in resilience with age, and aging components that contribute to this decline, including depletion of body reserves, imperfect repair mechanisms, and slowdown of physiological processes and responses with age; b) anti-aging interventions that may improve resilience or attenuate its decline; c) biomarkers of resilience available in human and experimental studies; and d) genetic factors that could influence resilience. There are open questions about optimal anti-aging interventions that would oppose the decline in resilience along with extending longevity limits. However, the area develops quickly, and prospects are exciting.

Identification of Potential Serum Protein Biomarkers and Pathways for Pancreatic Cancer Cachexia Using an Aptamer-Based Discovery Platform

Simple Summary

Patients with pancreatic cancer and other advanced cancers suffer from progressive weight loss that reduces treatment response and quality of life and increases treatment toxicity and mortality. Effective interventions to prevent such weight loss, known as cachexia, require molecular markers to diagnose, stage, and monitor cachexia. No such markers are currently validated or in clinical use. This study used a discovery platform to measure changes in plasma proteins in patients with pancreatic cancer compared with normal controls. We found proteins specific to pancreatic cancer and cancer stage, as well as proteins that correlate with cachexia. These include some previously known proteins along with novel ones and implicates both well-known and new molecular mechanisms. Thus, this study provides novel insights into the molecular processes underpinning cancer and cachexia and affords a basis for future validation studies in larger numbers of patients with pancreatic cancer and cachexia.

Abstract

Patients with pancreatic ductal adenocarcinoma (PDAC) suffer debilitating and deadly weight loss, known as cachexia. Development of therapies requires biomarkers to diagnose, and monitor cachexia; however, no such markers are in use. Via Somascan, we measured ~1300 plasma proteins in 30 patients with PDAC vs. 11 controls. We found 60 proteins specific to local PDAC, 46 to metastatic, and 67 to presence of >5% cancer weight loss (FC ≥ |1.5|, p ≤ 0.05). Six were common for cancer stage (Up: GDF15, TIMP1, IL1RL1; Down: CCL22, APP, CLEC1B). Four were common for local/cachexia (C1R, PRKCG, ELANE, SOST: all oppositely regulated) and four for metastatic/cachexia (SERPINA6, PDGFRA, PRSS2, PRSS1: all consistently changed), suggesting that stage and cachexia status might be molecularly separable. We found 71 proteins that correlated with cachexia severity via weight loss grade, weight loss, skeletal muscle index and radiodensity (r ≥ |0.50|, p ≤ 0.05), including some known cachexia mediators/markers (LEP, MSTN, ALB) as well as novel proteins (e.g., LYVE1, C7, F2). Pathway, correlation, and upstream regulator analyses identified known (e.g., IL6, proteosome, mitochondrial dysfunction) and novel (e.g., Wnt signaling, NK cells) mechanisms. Overall, this study affords a basis for validation and provides insights into the processes underpinning cancer cachexia.

Age-related DNA methylation changes are sex-specific: a comprehensive assessment

The existence of a sex gap in human health and longevity has been widely documented. Autosomal DNA methylation differences between males and females have been reported, but so far few studies have investigated if DNA methylation is differently affected by aging in males and females. We performed a meta-analysis of 4 large whole blood datasets, comparing 4 aspects of epigenetic age-dependent remodeling between the two sexes: differential methylation, variability, epimutations and entropy. We reported that a large fraction (43%) of sex-associated probes undergoes age-associated DNA methylation changes, and that a limited number of probes show age-by-sex interaction. We experimentally validated 2 regions mapping in FIGN and PRR4 genes and showed sex-specific deviations of their methylation patterns in models of decelerated (centenarians) and accelerated (Down syndrome) aging. While we did not find sex differences in the age-associated increase in epimutations and entropy, we showed that the number of probes having an age-related increase in methylation variability is 15 times higher in males compared to females. Our results can offer new epigenetic tools to study the interaction between aging and sex and can pave the way to the identification of molecular triggers of sex differences in longevity and age-related diseases prevalence.

Longitudinal profiling of the blood transcriptome in an African green monkey aging model

African green monkeys (AGMs, Chlorocebus aethiops) are Old World monkeys which are used as experimental models in biomedical research. Recent technological advances in next generation sequencing are useful for unraveling the genetic mechanisms underlying senescence, aging, and age-related disease. To elucidate the normal aging mechanisms in older age, the blood transcriptomes of nine healthy, aged AGMs (15‒23 years old), were analyzed over two years. We identified 910‒1399 accumulated differentially expressed genes (DEGs) in each individual, which increased with age. Aging-related DEGs were sorted across the three time points. A major proportion of the aging-related DEGs belonged to gene ontology (GO) categories involved in translation and rRNA metabolic processes. Next, we sorted common aging-related DEGs across three time points over two years. Common aging-related DEGs belonged to GO categories involved in translation, cellular component biogenesis, rRNA metabolic processes, cellular component organization, biogenesis, and RNA metabolic processes. Furthermore, we identified 29 candidate aging genes that were upregulated across the time series analysis. These candidate aging genes were linked to protein synthesis. This study describes a changing gene expression pattern in AGMs during aging using longitudinal transcriptome sequencing. The candidate aging genes identified here may be potential targets for the treatment of aging.

Multi-modal Single-Cell Analysis Reveals Brain Immune Landscape Plasticity during Aging and Gut Microbiota Dysbiosis

Phenotypic and functional plasticity of brain immune cells contribute to brain tissue homeostasis and disease. Immune cell plasticity is profoundly influenced by tissue microenvironment cues and systemic factors. Aging and gut microbiota dysbiosis that reshape brain immune cell plasticity and homeostasis has not been fully delineated. Using Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), we analyze compositional and transcriptional changes of the brain immune landscape in response to aging and gut dysbiosis. Discordance between canonical surface-marker-defined immune cell types and their transcriptomes suggest transcriptional plasticity among immune cells. Ly6C⁺ monocytes predominate a pro-inflammatory signature in the aged brain, while innate lymphoid cells (ILCs) shift toward an ILC2-like profile. Aging increases ILC-like cells expressing a T memory stemness (T_scm) signature, which is reduced through antibiotics-induced gut dysbiosis. Systemic changes due to aging and gut dysbiosis increase propensity for neuroinflammation, providing insights into gut dysbiosis in age-related neurological diseases.

Targeting Senescent Cells for a Healthier Aging: Challenges and Opportunities

Aging is a physiological decline in both structural homeostasis and functional integrity, progressively affecting organismal health. A major hallmark of aging is the accumulation of senescent cells, which have entered a state of irreversible cell cycle arrest after experiencing inherent or environmental stresses. Although cellular senescence is essential in several physiological events, it plays a detrimental role in a large array of age-related pathologies. Recent biomedical advances in specifically targeting senescent cells to improve healthy aging, or alternatively, postpone natural aging and age-related diseases, a strategy termed senotherapy, have attracted substantial interest in both scientific and medical communities. Challenges for aging research are highlighted and potential avenues that can be leveraged for therapeutic interventions to control aging and age-related disorders in the current era of precision medicine.

Can Serum Nitrosoproteome Predict Longevity of Aged Women?

Aging is characterized by increase in reactive oxygen (ROS) and nitrogen (RNS) species, key factors of cardiac failure and disuse-induced muscle atrophy. This study focused on serum nitroproteome as a trait of longevity by adopting two complementary gel-based techniques: two-dimensional differential in gel electrophoresis (2-D DIGE) and Nitro-DIGE coupled with mass spectrometry of albumin-depleted serum of aged (A, n = 15) and centenarian (C, n = 15) versus young females (Y, n = 15). Results indicate spots differently expressed in A and C compared to Y and spots changed in A vs. C. Nitro-DIGE revealed nitrosated protein spots in A and C compared to Y and spots changed in A vs. C only (p-value < 0.01). Nitro-proteoforms of alpha-1-antitripsin (SERPINA1), alpha-1-antichimotripsin (SERPINA3), ceruloplasmin (CP), 13 proteoforms of haptoglobin (HP), and inactive glycosyltransferase 25 family member 3 (CERCAM) increased in A vs. Y and C. Conversely, nitrosation levels decreased in C vs. Y and A, for immunoglobulin light chain 1 (IGLC1), serotransferrin (TF), transthyretin (TTR), and vitamin D-binding protein (VDBP). Immunoblottings of alcohol dehydrogenase 5/S-nitrosoglutathione reductase (ADH5/GSNOR) and thioredoxin reductase 1 (TRXR1) indicated lower levels of ADH5 in A vs. Y and C, whereas TRXR1 decreased in A and C in comparison to Y. In conclusion, the study identified putative markers in C of healthy aging and high levels of ADH5/GSNOR that can sustain the denitrosylase activity, promoting longevity.

Common diseases alter the physiological age-related blood microRNA profile

Aging is a key risk factor for chronic diseases of the elderly. MicroRNAs regulate post-transcriptional gene silencing through base-pair binding on their target mRNAs. We identified nonlinear changes in age-related microRNAs by analyzing whole blood from 1334 healthy individuals. We observed a larger influence of the age as compared to the sex and provide evidence for a shift to the 5' mature form of miRNAs in healthy aging. The addition of 3059 diseased patients uncovered pan-disease and disease-specific alterations in aging profiles. Disease biomarker sets for all diseases were different between young and old patients. Computational deconvolution of whole-blood miRNAs into blood cell types suggests that cell intrinsic gene expression changes may impart greater significance than cell abundance changes to the whole blood miRNA profile. Altogether, these data provide a foundation for understanding the relationship between healthy aging and disease, and for the development of age-specific disease biomarkers.

Plasma proteomic biomarker signature of age predicts health and life span

Older age is a strong shared risk factor for many chronic diseases, and there is increasing interest in identifying aging biomarkers. Here, a proteomic analysis of 1301 plasma proteins was conducted in 997 individuals between 21 and 102 years of age. We identified 651 proteins associated with age (506 over-represented, 145 underrepresented with age). Mediation analysis suggested a role for partial cis-epigenetic control of protein expression with age. Of the age-associated proteins, 33.5% and 45.3%, were associated with mortality and multimorbidity, respectively. There was enrichment of proteins associated with inflammation and extracellular matrix as well as senescence-associated secretory proteins. A 76-protein proteomic age signature predicted accumulation of chronic diseases and all-cause mortality. These data support the use of proteomic biomarkers to monitor aging trajectories and to identify individuals at higher risk of disease to be targeted for in depth diagnostic procedures and early interventions.

The potential for complex computational models of aging

The gradual accumulation of damage and dysregulation during the aging of living organisms can be quantified. Even so, the aging process is complex and has multiple interacting physiological scales - from the molecular to cellular to whole tissues. In the face of this complexity, we can significantly advance our understanding of aging with the use of computational models that simulate realistic individual trajectories of health as well as mortality. To do so, they must be systems-level models that incorporate interactions between measurable aspects of age-associated changes. To incorporate individual variability in the aging process, models must be stochastic. To be useful they should also be predictive, and so must be fit or parameterized by data from large populations of aging individuals. In this perspective, we outline where we have been, where we are, and where we hope to go with such computational models of aging. Our focus is on data-driven systems-level models, and on their great potential in aging research.

A Primer on Constructing Plasticity Phenotypes to Classify Experience-Dependent Development of the Visual Cortex

Many neural mechanisms regulate experience-dependent plasticity in the visual cortex (V1), and new techniques for quantifying large numbers of proteins or genes are transforming how plasticity is studied into the era of big data. With those large data sets comes the challenge of extracting biologically meaningful results about visual plasticity from data-driven analytical methods designed for high-dimensional data. In other areas of neuroscience, high-information content methodologies are revealing more subtle aspects of neural development and individual variations that give rise to a richer picture of brain disorders. We have developed an approach for studying V1 plasticity that takes advantage of the known functions of many synaptic proteins for regulating visual plasticity. We use that knowledge to rebrand protein measurements into plasticity features and combine those into a plasticity phenotype. Here, we provide a primer for analyzing experience-dependent plasticity in V1 using example R code to identify high-dimensional changes in a group of proteins. We describe using PCA to classify high-dimensional plasticity features and use them to construct a plasticity phenotype. In the examples, we show how to use this analytical framework to study and compare experience-dependent development and plasticity of V1 and apply the plasticity phenotype to translational research questions. We include an R package “PlasticityPhenotypes” that aggregates the coding packages and custom code written in RStudio to construct and analyze plasticity phenotypes.

Circulating plasma factors involved in rejuvenation

Aging is defined as a time-dependent functional decline that occurs in many physiological systems. This decline is the primary risk factor for prominent human pathologies such as cancer, metabolic disorders, cardiovascular disorders, and neurodegenerative diseases. Aging and age-related diseases have multiple causes. Parabiosis experiments, in which the circulatory systems of young and old mice were surgically joined, revealed that young plasma counteracts aging and rejuvenates organs in old mice, suggesting the existence of rejuvenating factors that become less abundant with aging. Diverse approaches have identified a large number of plasma proteins whose levels differ significantly between young and old mice, as well as numerous rejuvenating factors that reverse aged-related impairments in multiple tissues. These observations suggest that increasing the levels of key rejuvenating factors could promote restorative biological processes or inhibit pathological degeneration. Inspired by such findings, several companies have begun selling “young blood transfusions,” and others have tested young plasma as a treatment for Alzheimer’s disease. Here, we summarize the current findings regarding rejuvenating factors.

Impact of contact lens wear on NLRP3 gene expression: Implications for ocular frailty in middle-aged adults

The inflammatory process plays a crucial role in frailty syndrome, which can appear in middle age and is associated with a poor health outcome. Consequently, gerontologists recommend screening inflammatory biomarkers in middle-aged adults to detect frailty and, therefore, prevent chronic diseases and mortality. External factors could be a risk factor for frailty because they can generate and extend the inflammatory process. For these reasons, we analysed the effect of long-term contact lens wear on mRNA level of genes linked to inflammation (IL-6, NLRP3, NK1R, CD73, MUC16 and TRPV1 genes) in conjunctival cells of middle-aged individuals, by quantitative PCR. Middle-aged contact lens wearers presented a significant increase of NLRP3 and MUC16 mRNA level as well as a decrease of CD73 mRNA level, in comparison with non-contact lens wearers. Additionally, we checked for a potential correlation between these transcript levels and clinical changes of the participants' ocular surface. Unlike molecular analysis, clinical examination fails to detect inflammation in contact lens wearers. These data suggest that long-term contact lens wear could trigger an inflammatory response in middle age orchestrated by NLRP3 inflammasome and modulated by CD73 and MUC16 proteins. Further studies are needed to confirm our gene expression findings at the protein level as well as to investigate the potential role of long-term CL wear in the onset of ocular frailty.

Inflammaging in Endemic Areas for Infectious Diseases

Immunosenescence is marked by a systemic process named inflammaging along with a series of defects in the immunological activity that results in poor responses to infectious agents and to vaccination. Inflammaging, a state of low-grade chronic inflammation, usually leads to chronic inflammatory diseases and frailty in the elderly. However, some elderly escape from frailty and reach advanced age free of the consequences of inflammaging. This process has been called immunological remodeling, and it is the hallmark of healthy aging as described in the studies of centenarians in Italy. The biological markers of healthy aging are still a matter of debate, and the studies on the topic have focused on inflammatory versus remodeling processes and molecules. The sub-clinical inflammatory status associated with aging might be a deleterious event for populations living in countries where chronic infectious diseases are not prevalent. Nevertheless, in other parts of the world where they are, two possibilities may occur. Inflammatory responses may have a protective effect against these infectious agents. At the same time, the long-term consequences of protective immune responses during chronic infections may result in accelerated immunosenescence in these individuals. Therefore, the biological markers of healthy aging can vary according to environmental, cultural, and geographical settings that reflect worldwide, and in a non-biased, non-westernized perspective, the changes that we experience regarding our contacts with microorganisms and the outcomes of such contacts.