Heterogeneous aging across multiple organ systems and prediction of chronic disease and mortality

James German and the Quest to Understand Human RECQ Helicase Deficiencies

James German's work to establish the natural history and cancer risk associated with Bloom syndrome (BS) has had a strong influence on the generation of scientists and clinicians working to understand other RECQ deficiencies and heritable cancer predisposition syndromes. I summarize work by us and others below, inspired by James German's precedents with BS, to understand and compare BS with the other heritable RECQ deficiency syndromes with a focus on Werner syndrome (WS). What we know, unanswered questions and new opportunities are discussed, as are potential ways to treat or modify WS-associated disease mechanisms and pathways.

Towards Healthy Longevity: Comprehensive Insights from Molecular Targets and Biomarkers to Biological Clocks

Aging is a complex and time-dependent decline in physiological function that affects most organisms, leading to increased risk of age-related diseases. Investigating the molecular underpinnings of aging is crucial to identify geroprotectors, precisely quantify biological age, and propose healthy longevity approaches. This review explores pathways that are currently being investigated as intervention targets and aging biomarkers spanning molecular, cellular, and systemic dimensions. Interventions that target these hallmarks may ameliorate the aging process, with some progressing to clinical trials. Biomarkers of these hallmarks are used to estimate biological aging and risk of aging-associated disease. Utilizing aging biomarkers, biological aging clocks can be constructed that predict a state of abnormal aging, age-related diseases, and increased mortality. Biological age estimation can therefore provide the basis for a fine-grained risk stratification by predicting all-cause mortality well ahead of the onset of specific diseases, thus offering a window for intervention. Yet, despite technological advancements, challenges persist due to individual variability and the dynamic nature of these biomarkers. Addressing this requires longitudinal studies for robust biomarker identification. Overall, utilizing the hallmarks of aging to discover new drug targets and develop new biomarkers opens new frontiers in medicine. Prospects involve multi-omics integration, machine learning, and personalized approaches for targeted interventions, promising a healthier aging population.

The Genetic Architecture of Biological Age in Nine Human Organ Systems

Understanding the genetic basis of biological aging in multi-organ systems is vital for elucidating age-related disease mechanisms and identifying therapeutic interventions. This study characterized the genetic architecture of the biological age gap (BAG) across nine human organ systems in 377,028 individuals of European ancestry from the UK Biobank. We discovered 393 genomic loci-BAG pairs (P-value<5×10-8) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary, and renal systems. We observed BAG-organ specificity and inter-organ connections. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system while exerting pleiotropic effects on traits linked to multiple organ systems. A gene-drug-disease network confirmed the involvement of the metabolic BAG-associated genes in drugs targeting various metabolic disorders. Genetic correlation analyses supported Cheverud's Conjecture1 - the genetic correlation between BAGs mirrors their phenotypic correlation. A causal network revealed potential causal effects linking chronic diseases (e.g., Alzheimer's disease), body weight, and sleep duration to the BAG of multiple organ systems. Our findings shed light on promising therapeutic interventions to enhance human organ health within a complex multi-organ network, including lifestyle modifications and potential drug repositioning strategies for treating chronic diseases. All results are publicly available at https://labs-laboratory.com/medicine.

Plasma proteomics in the UK Biobank reveals youthful brains and immune systems promote healthspan and longevity

Organ-derived plasma protein signatures derived from aptamer protein arrays track organ-specific aging, disease, and mortality in humans, but the robustness and clinical utility of these models and their biological underpinnings remain unknown. Here, we estimate biological age of 11 organs from 44,526 individuals in the UK Biobank using an antibody-based proteomics platform to model disease and mortality risk. Organ age estimates are associated with future onset of heart failure (heart age HR=1.83), chronic obstructive pulmonary disease (lung age HR=1.39), type II diabetes (kidney age HR=1.58), and Alzheimer's disease (brain age HR=1.81) and sensitive to lifestyle factors such as smoking and exercise, hormone replacement therapy, or supplements. Remarkably, the accrual of aged organs progressively increases mortality risk while a youthful brain and immune system are uniquely associated with disease-free longevity. These findings support the use of plasma proteins for monitoring organ health and the efficacy of drugs targeting organ aging disease.

Heterogeneous associations of multiplexed environmental factors and multidimensional aging metrics

Complicated associations between multiplexed environmental factors and aging are poorly understood. We manipulated aging using multidimensional metrics such as phenotypic age, brain age, and brain volumes in the UK Biobank. Weighted quantile sum regression was used to examine the relative individual contributions of multiplexed environmental factors to aging, and self-organizing maps (SOMs) were used to examine joint effects. Air pollution presented a relatively large contribution in most cases. We also found fair heterogeneities in which the same environmental factor contributed inconsistently to different aging metrics. Particulate matter contributed the most to variance in aging, while noise and green space showed considerable contribution to brain volumes. SOM identified five subpopulations with distinct environmental exposure patterns and the air pollution subpopulation had the worst aging status. This study reveals the heterogeneous associations of multiplexed environmental factors with multidimensional aging metrics and serves as a proof of concept when analyzing multifactors and multiple outcomes.

Tau Protein Accumulation Trajectory-Based Brain Age Prediction in the Alzheimer's Disease Continuum

Clinical cognitive advancement within the Alzheimer's disease (AD) continuum is intimately connected with sustained accumulation of tau protein pathology. The biological brain age and its gap show great potential for pathological risk and disease severity. In the present study, we applied multivariable linear support vector regression to train a normative brain age prediction model using tau brain images. We further assessed the predicted biological brain age and its gap for patients within the AD continuum. In the AD continuum, evaluated pathologic tau binding was found in the inferior temporal, parietal-temporal junction, precuneus/posterior cingulate, dorsal frontal, occipital, and inferior-medial temporal cortices. The biological brain age gaps of patients within the AD continuum were notably higher than those of the normal controls (p < 0.0001). Significant positive correlations were observed between the brain age gap and global tau protein accumulation levels for mild cognitive impairment (r = 0.726, p < 0.001), AD (r = 0.845, p < 0.001), and AD continuum (r = 0.797, p < 0.001). The pathologic tau-based age gap was significantly linked to neuropsychological scores. The proposed pathologic tau-based biological brain age model could track the tau protein accumulation trajectory of cognitive impairment and further provide a comprehensive quantification index for the tau accumulation risk.

Regenerative rehabilitation measures to restore tissue function after arsenic exposure

Environmental exposure of arsenic impairs the cardiometabolic profile, skeletal muscle health, and neurological function. Such declining tissue health is observed as early as in one's childhood, where the exposure is prevalent, thereby accelerating the effect of time's arrow. Despite the known deleterious effects of arsenic exposure, there is a paucity of specific treatment plans for restoring tissue function in exposed individuals. In this review, we propose to harness the untapped potential of existing regenerative rehabilitation programs, such as stem cell therapeutics with rehabilitation, acellular therapeutics, and artificial intelligence/robotics technologies, to address this critical gap in environmental toxicology. With regenerative rehabilitation techniques showing promise in other injury paradigms, fostering collaboration between these scientific realms offers an effective means of mitigating the detrimental effects of arsenic on tissue function.

Morphometric brain organization across the human lifespan reveals increased dispersion linked to cognitive performance

The human brain is organized as segregation and integration units and follows complex developmental trajectories throughout life. The cortical manifold provides a new means of studying the brain's organization in a multidimensional connectivity gradient space. However, how the brain's morphometric organization changes across the human lifespan remains unclear. Here, leveraging structural magnetic resonance imaging scans from 1,790 healthy individuals aged 8 to 89 years, we investigated age-related global, within- and between-network dispersions to reveal the segregation and integration of brain networks from 3D manifolds based on morphometric similarity network (MSN), combining multiple features conceptualized as a "fingerprint" of an individual's brain. Developmental trajectories of global dispersion unfolded along patterns of molecular brain organization, such as acetylcholine receptor. Communities were increasingly dispersed with age, reflecting more disassortative morphometric similarity profiles within a community. Increasing within-network dispersion of primary motor and association cortices mediated the influence of age on the cognitive flexibility of executive functions. We also found that the secondary sensory cortices were decreasingly dispersed with the rest of the cortices during aging, possibly indicating a shift of secondary sensory cortices across the human lifespan from an extreme to a more central position in 3D manifolds. Together, our results reveal the age-related segregation and integration of MSN from the perspective of a multidimensional gradient space, providing new insights into lifespan changes in multiple morphometric features of the brain, as well as the influence of such changes on cognitive performance.

Gut microbiota in centenarians: A potential metabolic and aging regulator in the study of extreme longevity

Centenarians, those aged 100 years or older, are considered the most successful biological aging model in humans. This population is commonly characterized by a low prevalence of chronic diseases, with favorable maintenance of functionality and independence, thus determining a health phenotype of successful aging. There are many factors usually associated with extreme longevity: genetics, lifestyles, diet, among others. However, it is most likely a multifactorial condition where protective factors contribute individually to some extent. The gut microbiota (GM) has emerged as a potential factor associated with the establishment of a favorable health phenotype that allows for extreme longevity, as seen in centenarians. To understand the possible impact generated by the GM, its changes, and the probable causes for successful aging, the aim of this review was to synthesize evidence on the role of the GM as a potential protective factor for achieving extreme longevity, using its relationship with centenarians.

A novel approach to quantifying individual's biological aging using Korea's national health screening program toward precision public health

Accurate prediction of biological age can inform public health measures to extend healthy lifespans and reduce chronic conditions. Multiple theoretical models and methods have been developed; however, their applicability and accuracy are still not extensive. Here, we report Differential Aging and Health Index (DAnHI), a novel measure of age deviation, developed using physical and serum biomarkers from four million individuals in Korea's National Health Screening Program. Participants were grouped into aging statuses (< 26 vs. ≥ 26, < 27 vs. ≥ 27, …, < 75 vs. ≥ 75 years) as response variables in a binary logistic regression model with thirteen biomarkers as independent variables. DAnHI for each individual was calculated as the weighted mean of their relative probabilities of being classified into each older age status, based on model ages ranging from 26 to 75. DAnHI in our large study population showed a steady increase with the increase in age and was positively associated with death after adjusting for chronological age. However, the effect size of DAnHI on the risk of death varied according to the age group and sex. The hazard ratio was highest in the 50-59-year age group and then decreased as the individuals aged. This study demonstrates that routine health check-up biomarkers can be integrated into a quantitative measure for predicting aging-related health status and death via appropriate statistical models and methodology. Our DAnHI-based results suggest that the same level of aging-related health status does not indicate the same degree of risk for death.

Targeting the epigenetically older individuals for geroprotective trials: the use of DNA methylation clocks

Chronological age is the most important risk factor for the incidence of age-related diseases. The pace of ageing determines the magnitude of that risk and can be expressed as biological age. Targeting fundamental pathways of human aging with geroprotectors has the potential to lower the biological age and therewith prolong the healthspan, the period of life one spends in good health. Target populations for geroprotective interventions should be chosen based on the ageing mechanisms being addressed and the expected effect of the geroprotector on the primary outcome. Biomarkers of ageing, such as DNA methylation age, can be used to select populations for geroprotective interventions and as a surrogate outcome. Here, the use of DNA methylation clocks for selecting target populations for geroprotective intervention is explored.

Chronological and Biological Aging in Amyotrophic Lateral Sclerosis and the Potential of Senolytic Therapies

Amyotrophic Lateral Sclerosis (ALS) is a group of sporadic and genetic neurodegenerative disorders that result in losses of upper and lower motor neurons. Treatment of ALS is limited, and survival is 2-5 years after disease onset. While ALS can occur in younger individuals, the risk significantly increases with advancing age. Notably, both sporadic and genetic forms of ALS share pathophysiological features overlapping hallmarks of aging including genome instability/DNA damage, mitochondrial dysfunction, inflammation, proteostasis, and cellular senescence. This review explores chronological and biological aging in the context of ALS onset and progression. Age-related muscle weakness and motor unit loss mirror aspects of ALS pathology and coincide with peak ALS incidence, suggesting a potential link between aging and disease development. Hallmarks of biological aging, including DNA damage, mitochondrial dysfunction, and cellular senescence, are implicated in both aging and ALS, offering insights into shared mechanisms underlying disease pathogenesis. Furthermore, senescence-associated secretory phenotype and senolytic treatments emerge as promising avenues for ALS intervention, with the potential to mitigate neuroinflammation and modify disease progression.

Rosa roxburghii Fruit Extracts Upregulate Telomerase Activity and Ameliorate Cell Replicative Senescence

Anti-aging functional foods benefit the elderly. Telomeres are chromosomal ends that maintain genome stability extended by telomerase catalytic subunit TERT. Due to the end-replication problem, telomeres shorten after each cell cycle without telomerase in most human cells, and eventually the cell enters the senescence stage. Natural products can attenuate the aging process by increasing telomerase activity, such as TA-65. However, TA-65 is expensive. Other Chinese natural products may achieve comparable effects. Here, we found that Rosa roxburghii fruit extracts effectively increase TERT expression and telomerase activity in cultured human mesenchymal stem cells. Both R. roxburghii fruit extracts obtained by freeze-drying and spray-drying increased the activity of telomerase. R. roxburghii fruit extracts were able to reduce reactive oxygen species levels, enhance superoxide dismutase activity, and reduce DNA damage caused by oxidative stress or radiation. R. roxburghii fruit extracts promoted cell proliferation, improved senescent cell morphology, delayed replicative cellular senescence, attenuated cell cycle suppressors, and alleviated the senescence-associated secretory phenotype. Transcriptome and metabolic profiling revealed that R. roxburghii fruit extracts promote DNA replication and telomere maintenance pathways and decrease triglyceride levels. Overall, we provide a theoretical basis for the application of R. roxburghii fruit as an anti-aging product.

The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression

Cross-sectional studies have demonstrated strong associations between physical frailty and depression. However, the evidence from prospective studies is limited. Here, we analyze data of 352,277 participants from UK Biobank with 12.25-year follow-up. Compared with non-frail individuals, pre-frail and frail individuals have increased risk for incident depression independent of many putative confounds. Altogether, pre-frail and frail individuals account for 20.58% and 13.16% of depression cases by population attributable fraction analyses. Higher risks are observed in males and individuals younger than 65 years than their counterparts. Mendelian randomization analyses support a potential causal effect of frailty on depression. Associations are also observed between inflammatory markers, brain volumes, and incident depression. Moreover, these regional brain volumes and three inflammatory markers-C-reactive protein, neutrophils, and leukocytes-significantly mediate associations between frailty and depression. Given the scarcity of curative treatment for depression and the high disease burden, identifying potential modifiable risk factors of depression, such as frailty, is needed.

Predicting exacerbation of renal function by DNA methylation clock and DNA damage of urinary shedding cells: a pilot study

Recent reports have shown the feasibility of measuring biological age from DNA methylation levels in blood cells from specific regions identified by machine learning, collectively known as the epigenetic clock or DNA methylation clock. While extensive research has explored the association of the DNA methylation clock with cardiovascular diseases, cancer, and Alzheimer's disease, its relationship with kidney diseases remains largely unexplored. In particular, it is unclear whether the DNA methylation clock could serve as a predictor of worsening kidney function. In this pilot study involving 20 subjects, we investigated the association between the DNA methylation clock and subsequent deterioration of renal function. Additionally, we noninvasively evaluated DNA damage in urinary shedding cells using a previously reported method to examine the correlation with the DNA methylation clock and worsening kidney function. Our findings revealed that patients with an accelerated DNA methylation clock exhibited increased DNA damage in urinary shedding cells, along with a higher rate of eGFR decline. Moreover, in cases of advanced CKD (G4-5), the DNA damage in urinary shedding cells was significantly increased, highlighting the interplay between elevated DNA damage and eGFR decline. This study suggests the potential role of the DNA methylation clock and urinary DNA damage as predictive markers for the progression of chronic kidney disease.

Interplay of Demographic Influences, Clinical Manifestations, and Longitudinal Profile of Laboratory Parameters in the Progression of SARS-CoV-2 Infection: Insights from the Saudi Population

Understanding the factors driving SARS-CoV-2 infection progression and severity is complex due to the dynamic nature of human physiology. Therefore, we aimed to explore the severity risk indicators of SARS-CoV-2 through demographic data, clinical manifestations, and the profile of laboratory parameters. The study included 175 patients either hospitalized at King Abdulaziz Medical City-Riyadh or placed in quarantine at designated hotels in Riyadh, Saudi Arabia, from June 2020 to April 2021. Hospitalized patients were followed up through the first week of admission. Demographic data, clinical presentations, and laboratory results were retrieved from electronic patient records. Our results revealed that older age (OR: 1.1, CI: [1.1-1.12]; p < 0.0001), male gender (OR: 2.26, CI: [1.0-5.1]; p = 0.047), and blood urea nitrogen level (OR: 2.56, CI: [1.07-6.12]; p = 0.034) were potential predictors of severity level. In conclusion, the study showed that apart from laboratory parameters, age and gender could potentially predict the severity of SARS-CoV-2 infection in the early stages. To our knowledge, this study is the first in Saudi Arabia to explore the longitudinal profile of laboratory parameters among risk factors, shedding light on SARS-CoV-2 infection progression parameters.

Imaging without barriers

Low-field magnetic resonance imaging can be engineered for widespread point-of-care diagnostics.

An integrated multi-omics analysis reveals osteokines involved in global regulation

Bone secretory proteins, termed osteokines, regulate bone metabolism and whole-body homeostasis. However, fundamental questions as to what the bona fide osteokines and their cellular sources are and how they are regulated remain unclear. In this study, we analyzed bone and extraskeletal tissues, osteoblast (OB) conditioned media, bone marrow supernatant (BMS), and serum, for basal osteokines and those responsive to aging and mechanical loading/unloading. We identified 375 candidate osteokines and their changes in response to aging and mechanical dynamics by integrating data from RNA-seq, scRNA-seq, and proteomic approaches. Furthermore, we analyzed their cellular sources in the bone and inter-organ communication facilitated by them (bone-brain, liver, and aorta). Notably, we discovered that senescent OBs secrete fatty-acid-binding protein 3 to propagate senescence toward vascular smooth muscle cells (VSMCs). Taken together, we identified previously unknown candidate osteokines and established a dynamic regulatory network among them, thus providing valuable resources to further investigate their systemic roles.

Aging in Heart Failure: Embracing Biology Over Chronology: JACC Family Series

Age is among the most potent risk factors for developing heart failure and is strongly associated with adverse outcomes. As the global population continues to age and the prevalence of heart failure rises, understanding the role of aging in the development and progression of this chronic disease is essential. Although chronologic age is on a fixed course, biological aging is more variable and potentially modifiable in patients with heart failure. This review describes the current knowledge on mechanisms of biological aging that contribute to the pathogenesis of heart failure. The discussion focuses on 3 hallmarks of aging-impaired proteostasis, mitochondrial dysfunction, and deregulated nutrient sensing-that are currently being targeted in therapeutic development for older adults with heart failure. In assessing existing and emerging therapeutic strategies, the review also enumerates the importance of incorporating geriatric conditions into the management of older adults with heart failure and in ongoing clinical trials.

Podocyte Ercc1 is indispensable for glomerular integrity

As life expectancy continues to increase, age-related kidney diseases are becoming more prevalent. Chronic kidney disease (CKD) is not only a consequence of aging but also a potential accelerator of aging process. Here we report the pivotal role of podocyte ERCC1, a DNA repair factor, in maintaining glomerular integrity and a potential effect on multiple organs. Podocyte-specific ERCC1-knockout mice developed severe proteinuria, glomerulosclerosis, and renal failure, accompanied by a significant increase in glomerular DNA single-strand breaks (SSBs) and double-strand breaks (DSBs). ERCC1 gene transfer experiment in the knockout mice attenuated proteinuria and glomerulosclerosis with reduced DNA damage. Notably, CD44+CD8+ memory T cells, indicative of T-cell senescence, were already elevated in the peripheral blood of knockout mice at 10 weeks old. Additionally, levels of senescence-associated secretory phenotype (SASP) factors were significantly increased in both the circulation and multiple organs of the knockout mice. In older mice and human patients, we observed an accumulation of DSBs and an even greater buildup of SSBs in glomeruli, despite no significant reduction in ERCC1 expression with age in mice. Collectively, our findings highlight the crucial role of ERCC1 in repairing podocyte DNA damage, with potential implications for inflammation in various organs.

Dissecting unique and common variance across body and brain health indicators using age prediction

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals.

Correlation among job-induced stress, overall well-being, and cardiovascular risk in Italian workers of logistics and distribution

Introduction

Work-related stress is an occupational risk that has been linked to the development of cardiovascular disease (CVD). While previous studies have explored this association in various work contexts, none have focused specifically on logistics and distribution personnel. These workers may be exposed to significant job stress, which potentially increases the risk of CVD.

Methods

In this study, we aimed to examine the relationship between work-related stress and cardiovascular risk in a sample of 413 healthy workers of a logistics and distribution company. To assess work-related stress and cardiovascular risk, we used the organisational well-being questionnaire proposed by the Italian National Anti-Corruption Authority, the Framingham Heart Study General Cardiovascular Disease (CVD) Risk Prediction Score and the WHO General Wellbeing Index (WHO-5).

Results

Our results revealed that individuals with low job support had a significantly higher CVD risk score and lower well-being index than those reporting high job support. Furthermore, workers with high-stress tasks showed higher well-being index scores than those with passive tasks. Approximately 58% of the subjects were classified as low CVD risk (CVD risk <10%), approximately 31% were classified as moderate risk (CVD risk between 10 and 20%) and 11% were considered high risk (CVD risk >20%). The overall median CVD risk for the population was moderate (6.9%), with individual scores ranging from 1 to 58%.

Discussion

Further analyses confirmed the protective effect of work support, also identifying physical inactivity, regular alcohol consumption and low educational level as factors contributing to an increased risk of CVD. Interestingly, factors such as job control and work support demonstrated a positive impact on psychological well-being. These results emphasise the importance of intervention strategies aimed at promoting health in the workplace. By addressing these combined factors, organisations can effectively reduce the risk of CVD and improve the general well-being of their workforce.

Contributions of mouse genetic strain background to age-related phenotypes in physically active HET3 mice

We assessed aging hallmarks in skin, muscle, and adipose in the genetically diverse HET3 mouse, and generated a broad dataset comparing these to individual animal diagnostic SNPs from the 4 founding inbred strains of the HET3 line. For middle- and old-aged HET3 mice, we provided running wheel exercise to ensure our observations were not purely representative of sedentary animals, but age-related phenotypes were not improved with running wheel activity. Adipose tissue fibrosis, peripheral neuropathy, and loss of neuromuscular junction integrity were consistent phenotypes in older-aged HET3 mice regardless of physical activity, but aspects of these phenotypes were moderated by the SNP% contributions of the founding strains for the HET3 line. Taken together, the genetic contribution of founder strain SNPs moderated age-related phenotypes in skin and muscle innervation and were dependent on biological sex and chronological age. However, there was not a single founder strain (BALB/cJ, C57BL/6J, C3H/HeJ, DBA/2J) that appeared to drive more protection or disease-risk across aging in this mouse line, but genetic diversity in general was more protective.

A blood biomarker of the pace of aging is associated with brain structure: replication across three cohorts

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3380; total N individuals=2322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, greater burden of white matter microlesions, and thinner cortex. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Organ-specific biological clocks: Ageotyping for personalized anti-aging medicine

Aging is a complex multidimensional, progressive remodeling process affecting multiple organ systems. While many studies have focused on studying aging across multiple organs, assessment of the contribution of individual organs to overall aging processes is a cutting-edge issue. An organ's biological age might influence the aging of other organs, revealing a multiorgan aging network. Recent data demonstrated a similar yet asynchronous inter-organs and inter-individuals progression of aging, thereby providing a foundation to track sources of declining health in old age. The integration of multiple omics with common clinical parameters through artificial intelligence has allowed the building of organ-specific aging clocks, which can predict the development of specific age-related diseases at high resolution. The peculiar individual aging-trajectory, referred to as ageotype, might provide a novel tool for a personalized anti-aging, preventive medicine. Here, we review data relative to biological aging clocks and omics-based data, suggesting different organ-specific aging rates. Additional research on longitudinal data, including young subjects and analyzing sex-related differences, should be encouraged to apply ageotyping analysis for preventive purposes in clinical practice.

BrainAGE, brain health, and mental disorders: A systematic review

The imaging-based method of brainAGE aims to characterize an individual's vulnerability to age-related brain changes. The present study systematically reviewed brainAGE findings in neuropsychiatric conditions and discussed the potential of brainAGE as a marker for biological age. A systematic PubMed search (from inception to March 6th, 2023) identified 273 articles. The 30 included studies compared brainAGE between neuropsychiatric and healthy groups (n≥50). We presented results qualitatively and adapted a bias risk assessment questionnaire. The imaging modalities, design, and input features varied considerably between studies. While the studies found higher brainAGE in neuropsychiatric conditions (11 mild cognitive impairment/ dementia, 11 schizophrenia spectrum/ other psychotic and bipolar disorder, six depression/ anxiety, two multiple groups), the associations with clinical characteristics were mixed. While brainAGE is sensitive to group differences, limitations include the lack of diverse training samples, multi-modal studies, and external validation. Only a few studies obtained longitudinal data, and all have used algorithms built solely to predict chronological age. These limitations impede the validity of brainAGE as a biological age marker.

A synergetic turn in cognitive neuroscience of brain diseases

Despite significant improvements in our understanding of brain diseases, many barriers remain. Cognitive neuroscience faces four major challenges: complex structure-function associations; disease phenotype heterogeneity; the lack of transdiagnostic models; and oversimplified cognitive approaches restricted to the laboratory. Here, we propose a synergetics framework that can help to perform the necessary dimensionality reduction of complex interactions between the brain, body, and environment. The key solutions include low-dimensional spatiotemporal hierarchies for brain-structure associations, whole-brain modeling to handle phenotype diversity, model integration of shared transdiagnostic pathophysiological pathways, and naturalistic frameworks balancing experimental control and ecological validity. Creating whole-brain models with reduced manifolds combined with ecological measures can improve our understanding of brain disease and help identify novel interventions. Synergetics provides an integrated framework for future progress in clinical and cognitive neuroscience, pushing the boundaries of brain health and disease toward more mature, naturalistic approaches.

The 'middle-aging' brain

Middle age has historically been an understudied period of life compared to older age, when cognitive and brain health decline are most pronounced, but the scope for intervention may be limited. However, recent research suggests that middle age could mark a shift in brain aging. We review emerging evidence on multiple levels of analysis indicating that midlife is a period defined by unique central and peripheral processes that shape future cognitive trajectories and brain health. Informed by recent developments in aging research and lifespan studies in humans and animal models, we highlight the utility of modeling non-linear changes in study samples with wide subject age ranges to distinguish life stage-specific processes from those acting linearly throughout the lifespan.

The genetic architecture of multimodal human brain age

The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG displayed the most pronounced heritability enrichment in genetic variants within conserved regions. Oligodendrocytes and astrocytes, but not neurons, exhibited notable heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several chronic diseases on brain aging, such as type 2 diabetes on GM-BAG and AD on WM-BAG. Our results provide insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at https://labs.loni.usc.edu/medicine .

Intrinsic capacity trajectories and socioeconomic inequalities in health: the contributions of wealth, education, gender, and ethnicity

BACKGROUND

Life-long health inequalities exert enduring impacts and are governed by social determinants crucial for achieving healthy aging. A fundamental aspect of healthy aging, intrinsic capacity, is the primary focus of this study. Our objective is to evaluate the social inequalities connected with the trajectories of intrinsic capacity, shedding light on the impacts of socioeconomic position, gender, and ethnicity.

METHODS

Our dynamic cohort study was rooted in three waves (2009, 2014, 2017) of the World Health Organization's Study on Global AGEing and Adult Health in Mexico. We incorporated a nationally representative sample comprising 2722 older Mexican adults aged 50 years and over. Baseline measurements of socioeconomic position, gender, and ethnicity acted as the exposure variables. We evaluated intrinsic capacity across five domains: cognition, psychological, sensory, vitality, and locomotion. The Relative Index of Inequality and Slope Index of Inequality were used to quantify socioeconomic disparities.

RESULTS

We discerned three distinct intrinsic capacity trajectories: steep decline, moderate decline, and slight increase. Significant disparities based on wealth, educational level, gender, and ethnicity were observed. Older adults with higher wealth and education typically exhibited a trajectory of moderate decrease or slight increase in intrinsic capacity. In stark contrast, women and indigenous individuals were more likely to experience a steeply declining trajectory.

CONCLUSIONS

These findings underscore the pressing need to address social determinants, minimize gender and ethnic discrimination to ensure equal access to resources and opportunities across the lifespan. It is imperative for policies and interventions to prioritize these social determinants in order to promote healthy aging and alleviate health disparities. This approach will ensure that specific demographic groups receive customized support to sustain their intrinsic capacity during their elder years.

Risk stratification for frailty, impairment and assessment of sleep disorders in community-dwelling older adults

BACKGROUND

Frailty is associated with an increased susceptibility to functional decline, impairment, hospitalization, and mortality among the older adults. However, the potential reversibility of frailty lies in identifying modifiable factors that could prevent, mitigate, or interrupt its progression. While there is a suggestion that sleep disorders may increase the risk of frailty and impairment, the risk stratification of this relationship remains inconclusive.

OBJECTIVE

Stratify the risk of frailty and impairment and investigate potential connections with sleep quality, excessive daytime sleepiness, and the risk of obstructive sleep apnea in older adults dwelling in the community.

METHODS

This was a quantitative cross-sectional investigation. Frailty risk and impairment were stratified using the Frail Non-disabled Questionnaire (for impairment) and the FRAIL Scale (for Frailty). The assessment of excessive daytime sleepiness, sleep quality, and the risk of obstructive sleep apnea involved the employment of the Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, and the STOP-BANG questionnaire, respectively.

RESULTS

A total of 109 older adults living in the urban area (86 %, p = 0.010), females (61 %; p = 0.030), median age 68 (64-75) years, with overweight (36 %, p < 0.010) and self-identified as belonging to other racial or ethnic categories (71 %, p < 0.010). According to the impairment assessment, 32 % of participants were classified as disable (p < 0.01). Conversely, as per the frailty evaluation, 33 % were pre-frail and 25 % were identified as frail. Additionally, a substantial proportion experienced poor sleep quality (80 %, p = 0.010), exhibited a moderate risk of obstructive sleep apnea (49 %, p < 0.010), and showed no signs of excessive daytime sleepiness (62 %, p < 0.010). There was a modest correlation between frailty and impairment with poor sleep quality (rho = 0.39; p < 0.001) and the risk of obstructive sleep apnea (rho = 0.26; p = 0.000). However, the was no significant relationship was observed between frailty and impairment and excessive daytime sleepiness (rho = 0.04; p = 0.660). Similarly, a modest correlation was observed between sleep quality (rho = 0.33; p < 0.001), the risk of obstructive sleep apnea (rho = 0.27; p = 0.001), and frailty. Conversely, no correlation was found with excessive daytime sleepiness (rho = 0.05; p = 0.590). Also, the poor sleep quality and the risk of obstructive sleep apnea explain 14 % of the risk of frailty in the population of community-dwelling older adults (r2 = 0.14; p = 0.04).

CONCLUSION

This study reveals a modest risk of frailty and impairment with sleep quality and the risk of obstructive sleep apnea, but not with excessive daytime sleepiness in community-dwelling older adults.

Prior-guided individualized thalamic parcellation based on local diffusion characteristics

Comprising numerous subnuclei, the thalamus intricately interconnects the cortex and subcortex, orchestrating various facets of brain functions. Extracting personalized parcellation patterns for these subnuclei is crucial, as different thalamic nuclei play varying roles in cognition and serve as therapeutic targets for neuromodulation. However, accurately delineating the thalamic nuclei boundary at the individual level is challenging due to intersubject variability. In this study, we proposed a prior-guided parcellation (PG-par) method to achieve robust individualized thalamic parcellation based on a central-boundary prior. We first constructed probabilistic atlas of thalamic nuclei using high-quality diffusion MRI datasets based on the local diffusion characteristics. Subsequently, high-probability voxels in the probabilistic atlas were utilized as prior guidance to train unique multiple classification models for each subject based on a multilayer perceptron. Finally, we employed the trained model to predict the parcellation labels for thalamic voxels and construct individualized thalamic parcellation. Through a test-retest assessment, the proposed prior-guided individualized thalamic parcellation exhibited excellent reproducibility and the capacity to detect individual variability. Compared with group atlas registration and individual clustering parcellation, the proposed PG-par demonstrated superior parcellation performance under different scanning protocols and clinic settings. Furthermore, the prior-guided individualized parcellation exhibited better correspondence with the histological staining atlas. The proposed prior-guided individualized thalamic parcellation method contributes to the personalized modeling of brain parcellation.

Consequences of heterogeneity in aging: parental age at death predicts midlife all-cause mortality and hospitalization in a Swedish national birth cohort

BACKGROUND

The processes that underlie aging may advance at different rates in different individuals and an advanced biological age, relative to the chronological age, is associated with increased risk of disease and death. Here we set out to quantify the extent to which heterogeneous aging shapes health outcomes in midlife by following a Swedish birth-cohort and using parental age at death as a proxy for biological age in the offspring.

METHODS

We followed a nationwide Swedish birth cohort (N = 89,688) between the ages of 39 and 66 years with respect to hospitalizations and death. Cox regressions were used to quantify the association, in the offspring, between parental age at death and all-cause mortality, as well as hospitalization for conditions belonging to the 10 most common ICD-10 chapters.

RESULTS

Longer parental lifespan was consistently associated with reduced risks of hospitalization and all-cause mortality. Differences in risk were mostly evident from before the age of 50 and persisted throughout the follow-up. Each additional decade of parental survival decreased the risk of offspring all-cause mortality by 22% and risks of hospitalizations by 9 to 20% across the 10 diseases categories considered. The number of deaths and hospitalizations attributable to having parents not living until old age were 1500 (22%) and 11,000 (11%) respectively.

CONCLUSIONS

Our findings highlight that increased parental lifespan is consistently associated with health benefits in the offspring across multiple outcomes and suggests that heterogeneous aging processes have clinical implications already in midlife.

Cellular reprogramming as a tool to model human aging in a dish

The design of human model systems is highly relevant to unveil the underlying mechanisms of aging and to provide insights on potential interventions to extend human health and life span. In this perspective, we explore the potential of 2D or 3D culture models comprising human induced pluripotent stem cells and transdifferentiated cells obtained from aged or age-related disorder-affected donors to enhance our understanding of human aging and to catalyze the discovery of anti-aging interventions.

Plasma proteins as potential biomarkers of aging of single tissue and cell type

Plasma proteins serve as biomarkers of aging and various age-related diseases. While a number of plasma proteins have been identified that increase or decrease with age, the interpretation of each protein is challenging. This is due to the nature of plasma, which is a mixture of factors secreted by many different tissues and cells. Therefore, the catalog of age-related proteins secreted by a single cell type in a single tissue would be useful for understanding tissue-specific aging patterns. In this study, the author addressed this challenge by integrative data mining of the Human Protein Atlas and the recently published result of large-scale aging proteomics research. Finally, we identified the 17 age-related proteins produced by a single tissue and a single cell type: MBL2 and HP in the liver (hepatocytes), SFTPC in the lung (type II alveolar cells), PRL and POMC in the pituitary (anterior cells), GCG, CUZD1 and CPA2 in the pancreas (pancreatic cells), MYBPC1 in skeletal muscle (myocytes), PTH in the parathyroid gland (glandular cells), LPO and AMY1A in the salivary gland (glandular cells), INSL3 in the male testis (Leydig cells), KLK3 and KLK4 in the male prostate (glandular cells), MPO and ACP5 in immune cells. This list of proteins would be potentially useful for understanding age-related changes in the plasma proteome and inter-tissue networks.

Validation of biomarkers of aging

The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.

A biomarker framework for liver aging: the Aging Biomarker Consortium consensus statement

In human aging, liver aging per se not only increases susceptibility to liver diseases but also increases vulnerability of other organs given its central role in regulating metabolism. Total liver function tends to be well maintained in the healthy elderly, so liver aging is generally difficult to identify early. In response to this critical challenge, the Aging Biomarker Consortium of China has formulated an expert consensus on biomarkers of liver aging by synthesizing the latest scientific literature, comprising insights from both scientists and clinicians. This consensus provides a comprehensive assessment of biomarkers associated with liver aging and presents a systematic framework to characterize these into three dimensions: functional, imaging, and humoral. For the functional domain, we highlight biomarkers associated with cholesterol metabolism and liver-related coagulation function. For the imaging domain, we note that hepatic steatosis and liver blood flow can serve as measurable biomarkers for liver aging. Finally, in the humoral domain, we pinpoint hepatokines and enzymatic alterations worthy of attention. The aim of this expert consensus is to establish a foundation for assessing the extent of liver aging and identify early signs of liver aging-related diseases, thereby improving liver health and the healthy life expectancy of the elderly population.

Extracellular vesicles set the stage for brain plasticity and recovery by multimodal signalling

Extracellular vesicles (EVs) are extremely versatile naturally occurring membrane particles that convey complex signals between cells. EVs of different cellular sources are capable of inducing striking therapeutic responses in neurological disease models. Differently from pharmacological compounds that act by modulating defined signalling pathways, EV-based therapeutics possess multiple abilities via a variety of effectors, thus allowing the modulation of complex disease processes that may have very potent effects on brain tissue recovery. When applied in vivo in experimental models of neurological diseases, EV-based therapeutics have revealed remarkable effects on immune responses, cell metabolism and neuronal plasticity. This multimodal modulation of neuroimmune networks by EVs profoundly influences disease processes in a highly synergistic and context-dependent way. Ultimately, the EV-mediated restoration of cellular functions helps to set the stage for neurological recovery. With this review we first outline the current understanding of the mechanisms of action of EVs, describing how EVs released from various cellular sources identify their cellular targets and convey signals to recipient cells. Then, mechanisms of action applicable to key neurological conditions such as stroke, multiple sclerosis and neurodegenerative diseases are presented. Pathways that deserve attention in specific disease contexts are discussed. We subsequently showcase considerations about EV biodistribution and delineate genetic engineering strategies aiming at enhancing brain uptake and signalling. By sketching a broad view of EV-orchestrated brain plasticity and recovery, we finally define possible future clinical EV applications and propose necessary information to be provided ahead of clinical trials. Our goal is to provide a steppingstone that can be used to critically discuss EVs as next generation therapeutics for brain diseases.

The Gompertz Law emerges naturally from the inter-dependencies between sub-components in complex organisms

Understanding and facilitating healthy aging has become a major goal in medical research and it is becoming increasingly acknowledged that there is a need for understanding the aging phenotype as a whole rather than focusing on individual factors. Here, we provide a universal explanation for the emergence of Gompertzian mortality patterns using a systems approach to describe aging in complex organisms that consist of many inter-dependent subsystems. Our model relates to the Sufficient-Component Cause Model, widely used within the field of epidemiology, and we show that including inter-dependencies between subsystems and modeling the temporal evolution of subsystem failure results in Gompertizan mortality on the population level. Our model also provides temporal trajectories of mortality-risk for the individual. These results may give insight into understanding how biological age evolves stochastically within the individual, and how this in turn leads to a natural heterogeneity of biological age in a population.

Human lifespan and sex-specific patterns of resilience to disease: a retrospective population-wide cohort study

BACKGROUND

Slower paces of aging are related to lower risk of developing diseases and premature death. Therefore, the greatest challenge of modern societies is to ensure that the increase in lifespan is accompanied by an increase in health span. To better understand the differences in human lifespan, new insight concerning the relationship between lifespan and the age of onset of diseases, and the ability to avoid them is needed. We aimed to comprehensively study, at a population-wide level, the sex-specific disease patterns associated with human lifespan.

METHODS

Observational data from the SIDIAP database of a cohort of 482,058 individuals that died in Catalonia (Spain) at ages over 50 years old between the 1st of January 2006 and the 30th of June 2022 were included. The time to the onset of the first disease in multiple organ systems, the prevalence of escapers, the percentage of life free of disease, and their relationship with lifespan were evaluated considering sex-specific traits.

RESULTS

In the study cohort, 50.4% of the participants were women and the mean lifespan was 83 years. The results show novel relationships between the age of onset of disease, health span, and lifespan. The key findings include: Firstly, the onset of both single and multisystem diseases is progressively delayed as lifespan increases. Secondly, the prevalence of escapers is lower in lifespans around life expectancy. Thirdly, the number of disease-free systems decreases until individuals reach lifespans around 87-88 years old, at which point it starts to increase. Furthermore, long-lived women are less susceptible to multisystem diseases. The associations between health span and lifespan are system-dependent, and disease onset and the percentage of life spent free of disease at the time of death contribute to explaining lifespan variability. Lastly, the study highlights significant system-specific disparities between women and men.

CONCLUSIONS

Health interventions focused on delaying aging and age-related diseases should be the most effective in increasing not only lifespan but also health span. The findings of this research highlight the relevance of Electronic Health Records in studying the aging process and open up new possibilities in age-related disease prevention that should assist primary care professionals in devising individualized care and treatment plans.

A deep learning model for brain age prediction using minimally preprocessed T1w images as input

Introduction

In the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We developed and validated a convolutional neural network (CNN)-based biological brain age prediction model that uses one T1w MRI preprocessing step when applying the model to external datasets to simplify implementation and increase accessibility in research settings. Our model only requires rigid image registration to the MNI space, which is an advantage compared to previous methods that require more preprocessing steps, such as feature extraction.

Methods

We used a multicohort dataset of cognitively healthy individuals (age range = 32.0-95.7 years) comprising 17,296 MRIs for training and evaluation. We compared our model using hold-out (CNN1) and cross-validation (CNN2-4) approaches. To verify generalisability, we used two external datasets with different populations and MRI scan characteristics to evaluate the model. To demonstrate its usability, we included the external dataset's images in the cross-validation training (CNN3). To ensure that our model used only the brain signal on the image, we also predicted brain age using skull-stripped images (CNN4).

Results

The trained models achieved a mean absolute error of 2.99, 2.67, 2.67, and 3.08 years for CNN1-4, respectively. The model's performance in the external dataset was in the typical range of mean absolute error (MAE) found in the literature for testing sets. Adding the external dataset to the training set (CNN3), overall, MAE is unaffected, but individual cohort MAE improves (5.63-2.25 years). Salience maps of predictions reveal that periventricular, temporal, and insular regions are the most important for age prediction.

Discussion

We provide indicators for using biological (predicted) brain age as a metric for age correction in neuroimaging studies as an alternative to the traditional chronological age. In conclusion, using different approaches, our CNN-based model showed good performance using one T1w brain MRI preprocessing step. The proposed CNN model is made publicly available for the research community to be easily implemented and used to study ageing and age-related disorders.

Stress, epigenetics, and aging: Unraveling the intricate crosstalk

Aging, as a complex process involving multiple cellular and molecular pathways, is known to be exacerbated by various stresses. Because responses to these stresses, such as oxidative stress and genotoxic stress, are known to interplay with the epigenome and thereby contribute to the development of age-related diseases, investigations into how such epigenetic mechanisms alter gene expression and maintenance of cellular homeostasis is an active research area. In this review, we highlight recent studies investigating the intricate relationship between stress and aging, including its underlying epigenetic basis; describe different types of stresses that originate from both internal and external stimuli; and discuss potential interventions aimed at alleviating stress and restoring epigenetic patterns to combat aging or age-related diseases. Additionally, we address the challenges currently limiting advancement in this burgeoning field.

Eternal Youth: A Comprehensive Exploration of Gene, Cellular, and Pharmacological Anti-Aging Strategies

The improvement of human living conditions has led to an increase in average life expectancy, creating a new social and medical problem-aging, which diminishes the overall quality of human life. The aging process of the body begins with the activation of effector signaling pathways of aging in cells, resulting in the loss of their normal functions and deleterious effects on the microenvironment. This, in turn, leads to chronic inflammation and similar transformations in neighboring cells. The cumulative retention of these senescent cells over a prolonged period results in the deterioration of tissues and organs, ultimately leading to a reduced quality of life and an elevated risk of mortality. Among the most promising methods for addressing aging and age-related illnesses are pharmacological, genetic, and cellular therapies. Elevating the activity of aging-suppressing genes, employing specific groups of native and genetically modified cells, and utilizing senolytic medications may offer the potential to delay aging and age-related ailments over the long term. This review explores strategies and advancements in the field of anti-aging therapies currently under investigation, with a particular emphasis on gene therapy involving adeno-associated vectors and cell-based therapeutic approaches.

Aging Hallmarks and Progression and Age-Related Diseases: A Landscape View of Research Advancement

Aging is a dynamic, time-dependent process that is characterized by a gradual accumulation of cell damage. Continual functional decline in the intrinsic ability of living organisms to accurately regulate homeostasis leads to increased susceptibility and vulnerability to diseases. Many efforts have been put forth to understand and prevent the effects of aging. Thus, the major cellular and molecular hallmarks of aging have been identified, and their relationships to age-related diseases and malfunctions have been explored. Here, we use data from the CAS Content Collection to analyze the publication landscape of recent aging-related research. We review the advances in knowledge and delineate trends in research advancements on aging factors and attributes across time and geography. We also review the current concepts related to the major aging hallmarks on the molecular, cellular, and organismic level, age-associated diseases, with attention to brain aging and brain health, as well as the major biochemical processes associated with aging. Major age-related diseases have been outlined, and their correlations with the major aging features and attributes are explored. We hope this review will be helpful for apprehending the current knowledge in the field of aging mechanisms and progression, in an effort to further solve the remaining challenges and fulfill its potential.

Brain structure ages-A new biomarker for multi-disease classification

Age is an important variable to describe the expected brain's anatomy status across the normal aging trajectory. The deviation from that normative aging trajectory may provide some insights into neurological diseases. In neuroimaging, predicted brain age is widely used to analyze different diseases. However, using only the brain age gap information (i.e., the difference between the chronological age and the estimated age) can be not enough informative for disease classification problems. In this paper, we propose to extend the notion of global brain age by estimating brain structure ages using structural magnetic resonance imaging. To this end, an ensemble of deep learning models is first used to estimate a 3D aging map (i.e., voxel-wise age estimation). Then, a 3D segmentation mask is used to obtain the final brain structure ages. This biomarker can be used in several situations. First, it enables to accurately estimate the brain age for the purpose of anomaly detection at the population level. In this situation, our approach outperforms several state-of-the-art methods. Second, brain structure ages can be used to compute the deviation from the normal aging process of each brain structure. This feature can be used in a multi-disease classification task for an accurate differential diagnosis at the subject level. Finally, the brain structure age deviations of individuals can be visualized, providing some insights about brain abnormality and helping clinicians in real medical contexts.

Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.

Epitranscriptome analysis of NAD-capped RNA by spike-in-based normalization and prediction of chronological age

Nicotinamide adenine dinucleotide (NAD) can be used as an initiating nucleotide in RNA transcription to produce NAD-capped RNA (NAD-RNA). RNA modification by NAD that links metabolite with expressed transcript is a poorly studied epitranscriptomic modification. Current NAD-RNA profiling methods involve multi-steps of chemo-enzymatic labeling and affinity-based enrichment, thus presenting a critical analytical challenge to remove unwanted variations, particularly batch effects. Here, we propose a computational framework, enONE, to remove unwanted variations. We demonstrate that designed spike-in RNA, together with modular normalization procedures and evaluation metrics, can mitigate technical noise, empowering quantitative and comparative assessment of NAD-RNA across different datasets. Using enONE and a human aging cohort, we reveal age-associated features of NAD-capping and further develop an accurate RNA-based aging clock that combines signatures from both transcriptome and NAD-modified epitranscriptome. enONE facilitates the discovery of NAD-RNA responsive to physiological changes, laying an important foundation for functional investigations into this modification.

Endothelial progenitor cells systemic administration alleviates multi-organ senescence by down-regulating USP7/p300 pathway in chronic obstructive pulmonary disease

BACKGROUND

Chronic obstructive pulmonary disease (COPD) has impacted approximately 390 million people worldwide and the morbidity is increasing every year. However, due to the poor treatment efficacy of COPD, exploring novel treatment has become the hotpot of study on COPD. Endothelial progenitor cells (EPCs) aging is a possible molecular way for COPD development. We aimed to explore the effector whether intravenous administration of EPCs has therapeutic effects in COPD mice.

METHODS

COPD mice model was induced by cigarette smoke exposure and EPCs were injected intravenously to investigate their effects on COPD mice. At day 127, heart, liver, spleen, lung and kidney tissues of mice were harvested. The histological effects of EPCs intervention on multiple organs of COPD mice were detected by morphology assay. Quantitative real-time PCR and Western blotting were used to detect the effect of EPCs intervention on the expression of multi-organ senescence-related indicators. And we explored the effect of EPCs systematically intervening on senescence-related USP7/p300 pathway.

RESULTS

Compared with COPD group, senescence-associated β-galactosidase activity was decreased, protein and mRNA expression of p16 was down-regulated, while protein and mRNA expression of cyclin D1 and TERT were up-regulated of multiple organs, including lung, heart, liver, spleen and kidney in COPD mice after EPCs system intervention. But the morphological alterations of the tissues described above in COPD mice failed to be reversed. Mechanistically, EPCs systemic administration inhibited the expression of mRNA and protein of USP7 and p300 in multiple organs of COPD mice, exerting therapeutic effects.

CONCLUSIONS

EPCs administration significantly inhibited the senescence of multiple organs in COPD mice via down-regulating USP7/p300 pathway, which presents a possibility of EPCs therapy for COPD.

[Cerebral Small Vessel Disease: Advances in Understanding its Pathophysiology]

Sporadic cerebral small vessel disease determines age- and vascular-risk-factor-related processes of the small brain vasculature. The underlying pathology develops in a stage-dependent manner - probably over decades - often already starting in midlife. Endothelial and pericyte activation precedes blood-brain barrier leaks, extracellular matrix remodeling and neuroinflammation, which ultimately result in bleeds, synaptic and neural dysfunction. Hemodynamic compromise of the small vessel walls promotes perivascular drainage failure and accumulation of neurotoxic waste products in the brain. Clinical diagnosis is mainly based on magnetic resonance imaging according to the Standards for Reporting Vascular Changes on Neuroimaging 2. Cerebral amyloid angiopathy is particularly stratified according to the Boston v2.0 criteria. Small vessel disease of the brain could be clinically silent, or manifested through a heterogeneous spectrum of diseases, where cognitive decline and stroke-related symptoms are the most common ones. Prevention and therapy are centered around vascular risk factor control, physically and cognitively enriched life style and, presumably, maintenance of a good sleep quality, which promotes sufficient perivascular drainage. Prevention of ischemic stroke through anticoagulation that carries at the same time an increased risk for large brain hemorrhages - particularly in the presence of disseminated cortical superficial siderosis - remains one of the main challenges. The cerebral small vessel disease field is rapidly evolving, focusing on the establishment of early disease stage imaging and biofluid biomarkers of neurovascular unit remodeling and the compromise of perivascular drainage. New prevention and therapy strategies will correspondingly center around the dedicated targeting of, e. g., cellular small vessel wall and perivascular tissue structures. Growing knowledge about brain microvasculature bridging neuroimmunological, neurovascular and neurodegenerative fields might lead to a rethink about apparently separate disease entities and the development of overarching concepts for a common line of prevention and treatment for several diseases.