Human Lifespan Research Articles

Mendelian randomization analyses support causal relationships between gut microbiome and longevity.

Gut microbiome plays a significant role in longevity, and dysbiosis is indeed one of the hallmarks of aging. However, the causal relationship between gut microbiota and human longevity or aging remains elusive. Our study assessed the causal relationships between gut microbiome and longevity using Mendelian Randomization (MR). Summary statistics for the gut microbiome were obtained from four genome-wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340), Dutch Microbiome Project (N = 7738), German individuals (N = 8956), and Finland individuals (N = 5959). Summary statistics for Longevity were obtained from Five GWAS meta-analysis, including Human healthspan (N = 300,447), Longevity (N = 36,745), Lifespans (N = 1,012,240), Parental longevity (N = 389,166), and Frailty (one of the primary aging-linked physiological hallmarks, N = 175,226). Our findings reveal several noteworthy associations, including a negative correlation between Bacteroides massiliensis and longevity, whereas the genus Subdoligranulum and Alistipes, as well as species Alistipes senegalensis and Alistipes shahii, exhibited positive associations with specific longevity traits. Moreover, the microbial pathway of coenzyme A biosynthesis I, pyruvate fermentation to acetate and lactate II, and pentose phosphate pathway exhibited positive associations with two or more traits linked to longevity. Conversely, the TCA cycle VIII (helicobacter) pathway consistently demonstrated a negative correlation with lifespan and parental longevity. Our findings of this MR study indicated many significant associations between gut microbiome and longevity. These microbial taxa and pathways may potentially play a protective role in promoting longevity or have a suppressive effect on lifespan.

A High-Stability Pressure-Sensitive Implantable Memristor for Pulmonary Hypertension Monitoring.

Pulmonary hypertension (PH) significantly affects the quality of life and lifespan of humans and has promoted the development of flexible implantable electronic devices for PH diagnosis and prevention. Traditional implantable devices based on the von Neumann architecture face insurmountable challenges in processing large amounts of biological data due to computational bottlenecks. Memristors, with integrated in-memory sensing and computing capabilities, can effectively eliminate computational bottlenecks and become one of the most promising products in implantable devices for health monitoring. Here, a memristor with the Ag/MnO2/BaTiO3/FTO structure is implemented and implanted into Sprague‒Dawley (SD) rats. With polydimethylsiloxane (PDMS) packaging, the device can be continuously worked in vivo for up to four weeks, demonstrating excellent stability and biocompatibility. Furthermore, a memristive sensor array is designed for pulmonary artery blood pressure monitoring based on the pressure-responsive characteristics of the as-prepared memristive device. The front-end memristive sensor array can collect and feedback pressure signal, while noise reduction is achieved through memristive logic circuits, and ultimately the memristor neural network processes and classifies the information. Therefore, this work demonstrates the potential of implantable memristors for pulmonary artery pressure monitoring and provides new inspiration for the design of efficient, real-time, and reliable implantable pressure monitoring devices in medical health monitoring.

Abstract 4115690: COL4A1-related Vascular Disease Displays Strikingly Different Penetrance, Onset, and Expressivity in Literature versus Biobank-Derived Cases

Monogenic cardiovascular diseases present throughout the human lifespan with varying symptoms. For most, our understanding of their penetrance, onset, and expressivity is derived from published case reports. The extent to which these literature-derived cases capture the full allelic and phenotypic spectrum is unknown, particularly since the literature is biased towards severe presentations. To illustrate, we investigated the penetrance (i.e. the presence of at least one symptom), onset, and phenotypic expressivity of a rare genetic disease linked to hemorrhagic stroke and other complications: COL4A1 -related vascular disease (COL4A1VD, or Gould Syndrome). We performed a systematic review of COL4A1VD cases reported in the biomedical literature ( N =459), normalizing their genetic variants and symptoms to controlled terminologies. We then investigated the phenotypic expression among COL4A1VD pathogenic variant carriers isolated from two population-scale biobanks (the UK Biobank and All of Us Research Program; combined N =714,246), identifying 178 subjects (prevalence: 0.025%) that should be at high risk for COL4A1VD-related symptoms. Based on the literature, the penetrance of COL4A1VD is approximately 92% (95% CI: 90%-95%), with each case expressing 4.3 symptoms on average. Neurologic complications were the most common finding, observed in 85% of symptomatic patients. Alternatively, the biobank-derived cohort displayed an overall enrichment for disease-related symptoms (COL4A1 pathogenic carriers are more likely to have increased symptom burden compared to non-carrier controls; P<0.005), but the penetrance of the variants was substantially reduced (34%; 95% CI: 26%-41%). In addition, this cohort expressed fewer symptoms on average (0.8 per carrier), with renal complications being far more common (78% of symptomatic biobank patients vs 22% of literature-derived cases; P < 0.001). Finally, the apparent age-of-onset was much later for the biobank-derived cohort (57-years vs 5-years for the literature cases). Most of these differences reflect the distinct ascertainment of these two COL4A1VD cohorts, but they also highlight our incomplete understanding of the true penetrance, expressivity, and onset for this rare disease. These results have important implications for COL4A1VD-related genetic counseling and surveillance, and they highlight a need for new methods that formally integrate the rare disease knowledge captured from these distinct data sources.

Digital Doppelgängers and Lifespan Extension: What Matters?

There is an ongoing debate about the ethics of research on lifespan extension: roughly, using medical technologies to extend biological human lives beyond the current “natural” limit of about 120 years. At the same time, there is an exploding interest in the use of artificial intelligence (AI) to create “digital twins” of persons, for example by fine-tuning large language models on data specific to particular individuals. In this paper, we consider whether digital twins (or digital doppelgängers, as we refer to them) could be a path toward a kind of life extension—or more precisely, a kind of person extension—that does not rely on biological continuity. We discuss relevant accounts of consciousness and personal identity and argue that digital doppelgängers may at least help us achieve some of the aims or ostensible goods of person-span extension, even if they may not count as literal extensions of our personhood on dominant philosophical accounts. We also consider relational accounts of personhood and discuss how digital doppelgängers may be able to extend personhood in a relational sense, or at least secure some of the goods associated with relevant relationships. We conclude by suggesting that a research program to investigate such issues is relevant to ongoing debates about the ethics of extending the human lifespan.

TAKE AN OLD DRUG AND STAY YOUNG? METFORMIN AS AN ANTI-AGING MEDICATION – A LITERATURE REVIEW.

AIMS: Metformin is the main drug used in the treatment of type 2 diabetes mellitus, and the most widely prescribed oral antihyperglycemic medication. Its mechanism of action is still not completely understood and research into new uses for the compound is still ongoing, with one possible novel application of the medication being to combat aging on both the cellular and the macroscopic level. The aim of the study is to evaluate the current state of knowledge on metformin’s potential as a lifespan-extending and anti-senescence drug, present evidence on the matter and assess possible lanes of further study into such effects. METHODS: The literature review was performed using Internet research paper databases (PubMed, Google Scholar, Medline), using articles available in English. RESULTS: Multiple papers suggest tentative support for the notion that metformin may contribute to slowing cellular senescence, as well as to extending the human lifespan. Theoretical knowledge exists that shows possible routes of action of metformin in this regard. CONCLUSIONS: There is ample evidence in the literature for metformin’s possible effects as an anti-aging drug. Numerous cellular pathways by which it could exert lifespan-extending effects have been elucidated, and in vivo studies on some non-human animals have shown a measurable decrease in their production of aging markers, as well as an increase in the lifespan. Studies on diabetic patients have also demonstrated a significant reduction in all-cause mortality in that particular group. However, there is a lack of data and a need for more research that would investigate metformin’s potential as a universal anti-senescence agent more directly. Two large-scale studies (MILES and TAME) in the area are currently underway.

Biologically informed machine learning modeling of immune cells to reveal physiological and pathological aging process

The immune system undergoes progressive functional remodeling from neonatal stages to old age. Therefore, understanding how aging shapes immune cell function is vital for precise treatment of patients at different life stages. Here, we constructed the first transcriptomic atlas of immune cells encompassing human lifespan, ranging from newborns to supercentenarians, and comprehensively examined gene expression signatures involving cell signaling, metabolism, differentiation, and functions in all cell types to investigate immune aging changes. By comparing immune cell composition among different age groups, HLA highly expressing NK cells and CD83 positive B cells were identified with high percentages exclusively in the teenager (Tg) group, whereas unknown_T cells were exclusively enriched in the supercentenarian (Sc) group. Notably, we found that the biological age (BA) of pediatric COVID-19 patients with multisystem inflammatory syndrome accelerated aging according to their chronological age (CA). Besides, we proved that inflammatory shift- myeloid abundance and signature correlate with the progression of complications in Kawasaki disease (KD). The shift- myeloid signature was also found to be associated with KD treatment resistance, and effective therapies improve treatment outcomes by reducing this signaling. Finally, based on those age-related immune cell compositions, we developed a novel BA prediction model PHARE (https://xiazlab.org/phare/), which can apply to both scRNA-seq and bulk RNA-seq data. Using this model, we found patients with coronary artery disease (CAD) also exhibit accelerated aging compared to healthy individuals. Overall, our study revealed changes in immune cell proportions and function associated with aging, both in health and disease, and provided a novel tool for successfully capturing features that accelerate or delay aging.

Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity.

The recent unprecedented progress in ageing research and drug discovery brings together fundamental research and clinical applications to advance the goal of promoting healthy longevity in the human population. We, from the gathering at the Aging Research and Drug Discovery Meeting in 2023, summarised the latest developments in healthspan biotechnology, with a particular emphasis on artificial intelligence (AI), biomarkers and clocks, geroscience, and clinical trials and interventions for healthy longevity. Moreover, we provide an overview of academic research and the biotech industry focused on targeting ageing as the root of age-related diseases to combat multimorbidity and extend healthspan. We propose that the integration of generative AI, cutting-edge biological technology, and longevity medicine is essential for extending the productive and healthy human lifespan.

LINE1 modulate human T cell function by regulating protein synthesis during the life span.

The molecular mechanisms responsible for the heightened reactivity of quiescent T cells in human early life remain largely elusive. Our previous research identified that quiescent adult naïve CD4+ T cells express LINE1 (long interspersed nuclear elements 1) spliced in previously unknown isoforms, and their down-regulation marks the transition to activation. Here, we unveil that neonatal naïve T cell quiescence is characterized by enhanced energy production and protein synthesis. This phenotype is associated with the absence of LINE1 expression attributed to tonic T cell receptor/mTOR complex 1 (mTORC1) signaling and (polypyrimidine tract-binding protein 1 (PTBP1)-mediated LINE1 splicing suppression. The absence of LINE1 expression primes these cells for rapid execution of the activation program by directly regulating protein synthesis. LINE1 expression progressively increases in childhood and adults, peaking in elderly individuals, and, by decreasing protein synthesis, contributes to immune senescence in aging. Our study proposes LINE1 as a critical player of human T cell function across the human life span.

Mapping epidermal and dermal cellular senescence in human skin aging.

Single-cell RNA sequencing and spatial transcriptomics enable unprecedented insight into cellular and molecular pathways implicated in human skin aging and regeneration. Senescent cells are individual cells that are irreversibly cell cycle arrested and can accumulate across the human lifespan due to cell-intrinsic and -extrinsic stressors. With an atlas of single-cell RNA-sequencing and spatial transcriptomics, epidermal and dermal senescence and its effects were investigated, with a focus on melanocytes and fibroblasts. Photoaging due to ultraviolet light exposure was associated with higher burdens of senescent cells, a sign of biological aging, compared to chronological aging. A skin-specific cellular senescence gene set, termed SenSkin™, was curated and confirmed to be elevated in the context of photoaging, chronological aging, and non-replicating CDKN1A+ (p21) cells. In the epidermis, senescent melanocytes were associated with elevated melanin synthesis, suggesting haphazard pigmentation, while in the dermis, senescent reticular dermal fibroblasts were associated with decreased collagen and elastic fiber synthesis. Spatial analysis revealed the tendency for senescent cells to cluster, particularly in photoaged skin. This work proposes a strategy for characterizing age-related skin dysfunction through the lens of cellular senescence and suggests a role for senescent epidermal cells (i.e., melanocytes) and senescent dermal cells (i.e., reticular dermal fibroblasts) in age-related skin sequelae.

Functional connectivity across the lifespan: a cross-sectional analysis of changes.

In the era of functional brain networks, our understanding of how they evolve across life in a healthy population remains limited. Here, we investigate functional connectivity across the human lifespan using magnetoencephalography in a cohort of 792 healthy individuals, categorized into young (13 to 30 yr), middle (31 to 54 yr), and late adulthood (55 to 80 yr). Employing corrected imaginary phase-locking value, we map the evolving landscapes of connectivity within delta, theta, alpha, beta, and gamma classical frequency bands among brain areas. Our findings reveal significant shifts in functional connectivity patterns across all frequency bands, with certain networks exhibiting increased connectivity and others decreased, dependent on the frequency band and specific age groups, showcasing the dynamic reorganization of neural networks as age increases. This detailed exploration provides, to our knowledge, the first all-encompassing view of how electrophysiological functional connectivity evolves at different life stages, offering new insights into the brain's adaptability and the intricate interplay of cognitive aging and network connectivity. This work not only contributes to the body of knowledge on cognitive aging and neurological health but also emphasizes the need for further research to develop targeted interventions for maintaining cognitive function in the aging population.

Forecasting Population in an Uncertain World: Approaches, New Uses, and Troubling Limitations

AbstractThe long human lifespan enables long run forecasts of population size and age distribution. New methods include biodemographic research on upper limits to life expectancy and incorporation of early experiences affecting later life mortality such as smoking, obesity, and childhood health shocks. Some fertility forecasts incorporate education and quantum‐tempo insights. Statistical time series and Bayesian methods generate probabilistic forecasts. Yet recent decades have brought surprising changes in the economy, natural environment, and vital rates. In these changing circumstances we need new methods and the increasing use of probabilistic models and Bayesian methods incorporating outside information. The increasing use of microsimulation combined with aggregate forecasting methods is a very promising development enabling more detailed and heterogeneous forecasts. Some new uses of stochastic forecasts are interesting in themselves. Probabilistic mortality forecasts are used in finance and insurance, and a new Longevity Swap industry has been built on them. Random sample paths used to generate stochastic population forecasts can stress‐test public pension designs for fiscal stability and intergenerational equity. Population forecasting a few decades ago was a dull backwater of demographic research, but now it is increasingly important and is full of intellectual and technical challenges.

A biological age based on common clinical markers predicts health trajectory and mortality risk in dogs.

Predicting aging trajectories through biomarkers of biological aging can guide interventions that optimize healthy lifespan in humans and companion animals. Differences in physiology, genetics, nutrition, and lifestyle limit the generalization of such biomarkers and may therefore require species-specific algorithms. Here, we compared correlations of standard clinical blood parameters with survival probability in humans with those of the two most common mammalian companion animals, cats and dogs, and highlighted universal and species-specific relationships. Based on this comparative analysis, we generated and validated an algorithm that predicts biological age in canines using a longitudinal dataset with health records, blood count, and clinical chemistry from 829 dogs spanning over 12years. Positive deviations of biological from chronological age (AgeDev) measured by this composite score significantly correlated with a decreased survival probability (hazard ratio = 1.75 per 1year of AgeDev, p = 3.7e - 06). Importantly, in nearly half of the dogs whose biological age was accelerated by more than 1year, none or only a single individual marker scored outside its respective reference range, suggesting practical applications for the detection of unfavorable health trajectories. Analyzing samples from a unique 14-year life-long diet restriction study, we show that restricted caloric intake lowers biological age, an effect that can be quantified at midlife years before a difference in survival is observed. Thus, a biological age clock based on clinical blood tests predicts the health trajectories of dogs for use in research and veterinary practice.

Melatonin, Melatonin Receptors and Sleep: Moving Beyond Traditional Views.

Sleep, constituting approximately one-third of the human lifespan, is a crucial physiological process essential for physical and mental well-being. Normal sleep consists of an orderly progression through wakefulness, non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep, all of which are tightly regulated. Melatonin, often referred to as the "hormone of sleep," plays a pivotal role as a regulator of the sleep/wake cycle and exerts its effects through high-affinity G-protein coupled receptors known as MT1 and MT2. Selective modulation of these receptors presents a promising therapeutic avenue for sleep disorders. This review examines research on the multifaceted role of melatonin in sleep regulation, focusing on selective ligands targeting MT1 and MT2 receptors, as well as studies involving MT1 and MT2 knockout mice. Contrary to common beliefs, growing evidence suggests that melatonin, through MT1 and MT2 receptors, might not only influence circadian aspects of sleep but likely, also modulate the homeostatic process of sleep and sleep architecture, or could be the molecule linking the homeostatic and circadian regulation of sleep. Furthermore, the distinct brain localization of MT1 and MT2 receptors, with MT1 receptors primarily regulating REM sleep and MT2 receptors regulating NREM sleep, is discussed. Collectively, sleep regulation extends beyond the circulating levels and circadian peak of melatonin; it also critically involves the expression, molecular activation, and regulatory functions of MT1 and MT2 receptors across various brain regions and nuclei involved in the regulation of sleep. This research underscores the importance of ongoing investigation into the selective roles of MT1 and MT2 receptors in sleep. Such research efforts are expected to pave the way for the development of targeted MT1 or MT2 receptors ligands, thereby optimizing therapeutic interventions for sleep disorders.

DRADTiP: Drug repurposing for aging disease through drug-target interaction prediction

MotivationThe greatest risk factor for many non-communicable diseases is aging. Studies on model organisms have demonstrated that genetic and chemical perturbation alterations can lengthen longevity and overall health. However, finding longevity-enhancing medications and their related targets is difficult. MethodIn this work, we designed a novel drug repurposing model by identifying the interaction between aging-related genes or targets and drugs similar to aging disease. Each disease is associated with certain specific genetic factors for the occurrence of that disease. The factors include gene expression, pathway, miRNA, and degree of genes in the protein-protein interaction network. In this paper, we aim to find the drugs that prolong the life span of humans with their aging-related targets using the above-mentioned factors. In addition, the contribution or importance of each factor may vary among drugs and targets. Therefore, we designed a novel multi-layer random walk-based network representation learning model including node and edge weight to learn the features of drugs and targets respectively. ResultThe performance of the proposed model is demonstrated using k-fold cross-validation (k = 5). This model achieved better performance with scores of 0.93 and 0.91 for precision and recall respectively. The drugs identified by the system are evaluated to be potential candidates for aging since the degree of interaction between the potential drugs and their gene sets are high. In addition, the genes that are interacting with drugs produce the same biological functions. Hence the life span of the human will be increased or prolonged.

Abstract B040: B cells facilitate lymph node colonization in pancreatic ductal adenocarcinoma

Abstract Pancreatic ductal adenocarcinoma (PDAC) carries a low survival rate. Several factors contribute to its dismal prognosis, including resistance to available therapies and high invasiveness. Lymph nodes act as an early systemic source of circulating malignant cells, allowing their dissemination to other organs early in disease progression. Lymphatic colonization is linked to worse prognosis, and a better understanding of mechanisms regulating lymph node metastasis is clinically needed. To study each step in the metastatic cascade to the lymph nodes, we have developed a mouse co-clinical model of resectable pancreatic cancer. This model mimics the frequency of human PDAC metastatic recurrence, on a similar time scale relative to the lifespans of mice and humans and allows us to investigate very early events in the metastatic cascade. In contrast to the established anti-tumor role of T cells, the role of B cells in cancer immunology is more complex. B cells are a predominant immune population in lymph nodes, but their role in relation to lymph node colonization has never been fully addressed. Using our model of PDAC spontaneous metastasis and a mouse model of B cell depletion, we showed that lymph node metastasis does not form in the absence of B cells. We demonstrated that B cells, but not secreted antibodies, are required for successful lymph node colonization. We also gained evidence that B cells are orchestrating a complex interplay between disseminated cancer cells and other immune cells in the draining lymph node. Particularly, T cells seem to be involved in preventing cancer cell from growing into macro-metastasis only in the absence of B cells. We are now investigating the mechanisms employed by B cells to facilitate this cellular network to facilitate lymph node colonization in PDAC. The ultimate outcome of our work will be the design of effective immune strategies to prevent and treat lymph node dissemination of such a deadly disease. Citation Format: Alice Bertocchi, Megan T Hoffman, Li Qiang, Massiel Morell, Lauren L Hsu, Michael L Dougan, Judith Agudo, Stephanie K Dougan. B cells facilitate lymph node colonization in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B040.

Retraction of: Lithium treatment extends human lifespan: findings from the UK Biobank.

Retraction of: Lithium treatment extends human lifespan: findings from the UK Biobank.

Phenotypes of Dialysis-Requiring Acute Kidney Injury and Associations with Mortality in a South American Population.

Acute kidney injury (AKI) is a complex syndrome typically classified into strict categories. Alternatively, it may be more accurate to consider it as an intermediate event between an initiating cause and its outcome. Therefore, we investigated the burden of clinical scenarios associated with dialysis-requiring AKI (AKI-D) using latent class analysis (LCA) and examined the etiological spectrum and clinical phenotypes across different life stages. We analyzed 17,158 AKI-D patients from 170 medical facilities in Rio de Janeiro, Brazil (2002-2012). Utilizing survival curves and mixed-effects Cox regression for survival estimation, LCA classified patients based on clinical characteristics and outcomes, focusing on etiological variation over the human lifespan. The median age was 75 (IQR 59-83). Infections were the most common cause (44.2%), particularly community-acquired pneumonia (23.8%). Cardiovascular issues, especially ischemic heart disease (9.0%) and acute heart failure (8.1%), were also significant. LCA identified four distinct patient classes with varying clinical and outcome profiles. Class 1 patients were younger (median age 66), predominantly male, with lower ICU admission and higher rates of community-acquired AKI (60.8%). They had the lowest mortality (39.5%) and highest recovery rates. Class 2 had intermediate mortality (67.4%) and the highest comorbidity burden (mean Charlson score: 3.39). Classes 3 and 4 had the highest mortality (82.8% and 78.6%), requiring more mechanical ventilation and vasopressor use. Class 3 had a high prevalence of sepsis (92.7%) with lower comorbidities, while Class 4 had high chronic heart disease (76.3%) and perfusion factors (79.4%). Despite high mortality, Class 3 recovered better than Class 2 and 4. Survival analyses revealed diverse outcomes across etiological groups, with liver-related conditions being the most severe. This study highlights the complexity of AKI and the utility of LCA in revealing its clinical heterogeneity. It underscores distinct etiological trends across ages, suggesting future research should integrate clinical profiles with advanced diagnostics to understand AKI's clinical and molecular phenotypes throughout life.

Social Isolation as a Precursor to Academic Downturn and Vice Versa

Research in the fields of social science and public health indicates the vital role of social interaction and relationships in promoting mental well-being across the entire human lifespan and education is no exception. Academics ,with its power of inquiring about the universe’s hymn to the patterns of subatomic beings , go beyond the confines of textbooks, Academics can be comprehended as a banyan tree with ever growing branches. Each branch has nuances , differentiating it in the most miniscule ways. As leaves sprout out of innumerable nodes , it ingeniously represents the evolving nature of academics. Wherein each discovery or invention creates a ripple effect in academics. While I have only experienced the finance and business side of academics , The surrealness of penetrating the boundaries of education stays alive in me. For approximately 3 years , I have dedicated time and effort into dissecting my patterns of studying , results , and conducting research - primary and secondary- between Isolation and its effect on academics and learning experiences. Although the relation may seem one dimensional , it delves deeper into the studies of psychology and academics. This project has been intellectually stimulating for me. Furthermore , this research explains the effects of social isolation and how it profoundly impacts learning.

The Role of Molecular and Cellular Aging Pathways on Age-Related Hearing Loss.

Aging, a complex process marked by molecular and cellular changes, inevitably influences tissue and organ homeostasis and leads to an increased onset or progression of many chronic diseases and conditions, one of which is age-related hearing loss (ARHL). ARHL, known as presbycusis, is characterized by the gradual and irreversible decline in auditory sensitivity, accompanied by the loss of auditory sensory cells and neurons, and the decline in auditory processing abilities associated with aging. The extended human lifespan achieved by modern medicine simultaneously exposes a rising prevalence of age-related conditions, with ARHL being one of the most significant. While our understanding of the molecular basis for aging has increased over the past three decades, a further understanding of the interrelationship between the key pathways controlling the aging process and the development of ARHL is needed to identify novel targets for the treatment of AHRL. The dysregulation of molecular pathways (AMPK, mTOR, insulin/IGF-1, and sirtuins) and cellular pathways (senescence, autophagy, and oxidative stress) have been shown to contribute to ARHL. However, the mechanistic basis for these pathways in the initiation and progression of ARHL needs to be clarified. Therefore, understanding how longevity pathways are associated with ARHL will directly influence the development of therapeutic strategies to treat or prevent ARHL. This review explores our current understanding of the molecular and cellular mechanisms of aging and hearing loss and their potential to provide new approaches for early diagnosis, prevention, and treatment of ARHL.

Brain topology underlying executive functions across the lifespan: focus on the default mode network.

While traditional neuroimaging approaches to the study of executive functions (EFs) have typically employed task-evoked paradigms, resting state studies are gaining popularity as a tool for investigating inter-individual variability in the functional connectome and its relationship to cognitive performance outside of the scanner. Using resting state functional magnetic resonance imaging data from the Human Connectome Project Lifespan database, the present study capitalized on graph theory to chart cross-sectional variations in the intrinsic functional organization of the frontoparietal (FPN) and the default mode (DMN) networks in 500 healthy individuals (from 10 to 100 years of age), to investigate the neural underpinnings of EFs across the lifespan. Topological properties of both the FPN and DMN were associated with EF performance but not with a control task of picture naming, providing specificity in support for a tight link between neuro-functional and cognitive-behavioral efficiency within the EF domain. The topological organization of the DMN, however, appeared more sensitive to age-related changes relative to that of the FPN. The DMN matures earlier in life than the FPN and it ıs more susceptible to neurodegenerative changes. Because its activity is stronger in conditions of resting state, the DMN might be easier to measure in noncompliant populations and in those at the extremes of the life-span curve, namely very young or elder participants. Here, we argue that the study of its functional architecture in relation to higher order cognition across the lifespan might, thus, be of greater interest compared with what has been traditionally thought.