Over the past decade, epigenetic clocks have emerged as powerful machine learning tools, not only to estimate chronological and biological age but also to assess the efficacy of anti-ageing, cellular rejuvenation and disease-preventive interventions. However, many computational and statistical challenges remain that limit our understanding, interpretation and application of epigenetic clocks. Here, we review these computational challenges, focusing on interpretation, cell-type heterogeneity and emerging single-cell methods, aiming to provide guidelines for the rigorous construction of interpretable epigenetic clocks at cell-type and single-cell resolution.

Down syndrome (DS) is a genetic disorder that leads to intellectual disability and accelerated aging, increasing the risk of Alzheimer's disease (AD). The pathophysiology of AD and DS is multifactorial, involving amyloid precursor protein overexpression, neuroinflammation, and oxidative stress. This study investigates kynurenine pathway metabolites in elderly individuals with DS (with/without cognitive decline), AD, and cognitively healthy controls to clarify their roles in these pathogeneses.

A cross-sectional study was conducted involving DS, AD, and healthy participants. Plasma levels of tryptophan, kynurenine, 3-hydroxykynurenine, anthranilic acid, 3-hydroxyanthranilic acid, and quinolinic acid were analyzed by Liquid Chromatography coupled with Tandem Mass spectrometry (LC-MS/MS) methodology.

Elevated kynurenine and other neuroprotective metabolites were found in DS individuals without cognitive decline, while significant differences in neurotoxic metabolites were observed between groups.

Our findings suggest a link between kynurenine pathway dysregulation and cognitive decline, indicating alterations in DS and AD.

There are altered kynurenine pathway metabolites in Down syndrome and Alzheimer's disease. Elevated neuroprotective metabolites are found in Down syndrome without cognitive decline. Significant differences in neurotoxic metabolites among study groups were analyzed. There is a potential link between kynurenine pathway dysregulation and cognitive decline. The study provides insights into metabolic changes in aging and neurodegeneration.

Human-rodent chimeric brain models serve as a unique platform for investigating the pathophysiology of human cells within a living brain environment. These models are established by transplanting human tissue- or human pluripotent stem cell (hPSC)-derived macroglial, microglial, or neuronal lineage cells, as well as cerebral organoids, into the brains of host animals. This approach has opened new avenues for exploring human brain development, disease mechanisms, and regenerative processes. Here, we highlight recent advancements in using chimeric models to study human neural development, aging, and disease. Additionally, we explore the potential applications of these models for studying human glial cell-replacement therapies, studying in vivo human glial-to-neuron reprogramming, and harnessing single-cell omics and advanced functional assays to uncover detailed insights into human neurobiology. Finally, we discuss strategies to enhance the precision and translational relevance of these models, expanding their impact in stem cell and neuroscience research.

Down syndrome (DS), caused by trisomy of chromosome 21 (HSA21), is a complex condition associated with neurodevelopmental impairments and accelerated brain aging, often culminating in early-onset Alzheimer's disease (AD). Central to this accelerated aging is mitochondrial imbalance, characterized by disrupted energy metabolism, increased oxidative stress, impaired dynamics, and defective quality control mechanisms like mitophagy. These abnormalities exacerbate neuronal vulnerability, driving cognitive decline and neurodegeneration. This review examines the genetic and biochemical underpinnings of mitochondrial dysfunction in DS, with a focus on the role of HSA21-encoded genes. We also highlight how mitochondrial dysfunction, amplified by oxidative stress and HSA21 gene dosage effects, converges with cellular senescence and neuroinflammation to accelerate Alzheimer-like pathology and brain aging in DS. Finally, we discuss emerging therapeutic strategies targeting mitochondrial pathways, which hold promise for mitigating neurodegenerative phenotypes and improving outcomes in DS.

An increasing body of evidence indicates altered DNA methylation in Parkinson's disease, yet the reproducibility and utility of such methylation changes are largely unexplored. We aimed to further elucidate the role of dysregulated DNA methylation in Parkinson's disease and to evaluate the biomarker potential of methylation-based profiling.

We conducted an epigenome-wide association study (EWAS) in whole blood, including 280 Parkinson's disease and 279 control participants from Oslo, Norway. Next, we took advantage of data from the Parkinson's Progression Markers Initiative (PPMI) and a previously published EWAS to conduct a whole blood EWAS meta-analysis in Parkinson's disease, incorporating results from a total of 3068 participants. Finally, we generated multiple methylation-based scores for each Oslo and PPMI participant and tested their association with disease status, individually and in a joint multiscore model.

In EWAS meta-analysis, we confirm SLC7A11 hypermethylation and nominate a novel differentially methylated CpG near LPIN1. A joint multiscore model incorporating polygenic risk and methylation-based estimates of epigenetic Parkinson's disease risk, smoking, and leukocyte proportions differentiated patients from control participants with an area under the receiver-operator curve of 0.82 in the Oslo cohort and 0.65 in PPMI.

Our results highlight the power of DNA methylation profiling to capture multiple aspects of disease risk, indicating a biomarker potential for precision medicine in neurodegenerative disorders. The reproducibility of specific differentially methylated CpGs across data sets was limited but may improve if future studies are designed to account for disease stage and incorporate environmental exposure data.

Individuals with Down syndrome (DS) are highly susceptible to Alzheimer's disease (AD). The integration of genomics, transcriptomics, epigenomics, proteomics, and metabolomics enables unprecedented understanding of DS-AD, offering a detailed picture of this complex issue. The vast -omics data also present challenges that reflect the complexity of genetic information flow. These studies nonetheless reveal critical mechanisms behind AD risk, including unique observations in DS that differ from those seen in the general population and familial dominant AD. In addition, the correlations between the AD polygenic risk score and proteins related to female infertility and autoimmune thyroiditis corroborate clinical observations. Metabolomic data reveal disrupted metabolic networks, offering prospects for a dynamic score to create specialized nutritional interventions. By adopting a multidimensional perspective with integrated reductionism, the evolving landscape presents an opportunity to identify promising directions for developing precision strategies to mitigate the impact of AD in the DS population. HIGHLIGHTS: Individuals with Down syndrome (DS) are highly susceptible to Alzheimer's disease (AD). DS-AD is characterized by its polygenic nature, extending beyond chromosome 21 with significant contributions from various chromosomes. DS-AD also presents unique features that differ from those observed in the general population and familial dominant AD. Our review consolidates key findings from genomics, transcriptomics, epigenomics, proteomics, and metabolomics, providing a comprehensive view of the molecular mechanisms underlying DS-AD. We highlight promising research directions to further elucidate the pathogenesis of DS-AD.

BRG1 deficiency in patients with lung adenocarcinoma that has metastasized to the brain, termed BRG1-deficient brain metastasis lung adenocarcinoma, is an uncommon event. Prior to this study, these patients had not undergone extensive molecular and (epi)genetic analysis. We report a comprehensive clinical, histopathologic, and molecular assessment of 9 BRG1-deficient brain metastasis lung adenocarcinoma cohort (BRG1-deficient BM cohort) in comparison with a 16 BRG1-retained brain metastasis lung adenocarcinoma cohort (BRG1-retained BM cohort). Patients with BRG1-deficient BM exhibited a significantly increased risk of mortality. Molecular analysis revealed a high prevalence of mutations in SMARCA4 and TP53 genes within this group. DNA methylation molecular diagnostics showed a high rate of genomic instability and a markedly lower DNA methylation age in these patients. Functional enrichment analysis of differentially methylated genes suggested that hypomethylation genes were primarily associated with the negative regulation of neuron differentiation, G protein-coupled receptor signaling pathways, and cell differentiation. Conversely, hypermethylation was linked to the regulation of small GTPase mediated signal transduction, Rho protein signal transduction, DNA damage response, and apoptotic processes. This study investigated a rare subgroup of lung adenocarcinoma patients with brain metastasis characterized by BRG1 deficiency and a poor prognosis. Our study not only provides a comprehensive multi-omic data resource but also provides valuable biological insights into patients. The findings may serve as a valuable reference for the future pathological diagnosis of BRG1-deficient brain metastasis in lung adenocarcinoma patients.

The purpose of this study was to (1) perform the first analysis of bone-derived DNA methylation, (2) compare DNA methylation clocks derived from bone with those derived from whole blood, and (3) establish a relationship between DNA methylation age and 1-year mortality within the geriatric hip fracture population.

Patients ≥65 years old who presented to a Level-I trauma center with a hip fracture were prospectively enrolled from 2020 to 2021. Preoperative whole blood and intraoperative bone samples were collected. Following DNA extraction, RRBS (reduced representation bisulfite sequencing) libraries for methylation clock analysis were prepared. Sequencing data were analyzed using computational algorithms previously described by Horvath et al. to build a regression model of methylation (biological) age for each tissue type. Student t tests were used to analyze differences (Δ) in methylation age versus chronological age. Correlation between blood and bone methylation ages was expressed using the Pearson R coefficient.

Blood and bone samples were collected from 47 patients. DNA extraction, sequencing, and methylation analysis were performed on 24 specimens from 12 subjects. Mean age at presentation was 85.4 ± 8.65 years. There was no difference in DNA extraction yield between the blood and bone samples (p = 0.935). The mean follow-up duration was 12.4 ± 4.3 months. The mortality cohort (4 patients, 33%) showed a mean ΔAgeBone of 18.33 ± 6.47 years and mean ΔAgeBlood of 16.93 ± 4.02 years. In comparison, the survival cohort showed a significantly lower mean ΔAgeBone and ΔAgeBlood (7.86 ± 6.7 and 7.31 ± 7.71 years; p = 0.026 and 0.039, respectively). Bone-derived methylation age was strongly correlated with blood-derived methylation age (R = 0.81; p = 0.0016).

Bone-derived DNA methylation clocks were found to be both feasible and strongly correlated with those derived from whole blood within a geriatric hip fracture population. Mortality was independently associated with the DNA methylation age, and that age was approximately 17 years greater than chronological age in the mortality cohort. The results of the present study suggest that prevention of advanced DNA methylation may play a key role in decreasing mortality following hip fracture.

Prognostic Level I . See Instructions for Authors for a complete description of levels of evidence.

This study introduces EpiAgePublic, a new method to estimate biological age using only three specific sites on the gene ELOVL2, known for its connection to aging. Unlike traditional methods that require complex and extensive data, our model uses a simpler approach that is well-suited for next-generation sequencing technology, which is a more advanced method of analyzing DNA methylation. This new model overcomes some of the common challenges found in older methods, such as errors due to sample quality and processing variations. We tested EpiAgePublic with a large and varied group of over 4,600 people to ensure its accuracy. It performed on par with, and sometimes better than, more complicated models that use much more data for age estimation. We examined its effectiveness in understanding how factors like HIV infection and stress affect aging, confirming its usefulness in real-world clinical settings. Our results prove that our simple yet effective model, EpiAgePublic, can capture the subtle signs of aging with high accuracy. We also used this model in a study involving patients with Alzheimer's Disease, demonstrating the practical benefits of next-generation sequencing in making precise age-related assessments. This study lays the groundwork for future research on aging mechanisms and assessing how different interventions might impact the aging process using this clock.

The mitotic inheritability of DNA methylation as an epigenetic marker in higher-order eukaryotes has been established for >40 years. The DNA methylome and mitotic division interplay is now considered bidirectional and highly intertwined. Various epigenetic writers, erasers, and modulators shape the perceived replicative methylation dynamics. This Review surveys the principles and complexity of mitotic transmission of DNA methylation, emphasizing the awareness of mitotic aging in analyzing DNA methylation dynamics in development and disease. We reviewed how DNA methylation changes alter mitotic proliferation capacity, implicating age-related diseases like cancer. We link replicative epimutation to stem cell dysfunction, inflammatory response, cancer risks, and epigenetic clocks, discussing the causative role of DNA methylation in health and disease.

Down syndrome (DS), a genetic condition caused by trisomy 21 (T21), manifests various neurological symptoms, including intellectual disability, early neurodegeneration, and early-onset dementia. N-glycosylation is a protein modification that plays a critical role in numerous neurobiological processes and whose dysregulation is associated with a range of neurological disorders. However, whether N-glycosylation of neural glycoproteins is affected in DS has not been studied. To better understand how T21 affects N-glycosylation during neural differentiation, we utilized an isogenic in vitro induced pluripotent stem cell (iPSC) model of T21 in which both T21 and euploid disomic karyotype (D21) clones were obtained from a single individual with mosaic DS. We comprehensively characterized and compared the total N-glycomes of iPSCs and their neural stem cell (NSC) derivatives. N-glycomics analysis of whole cell lysates was performed using liquid chromatography coupled with tandem mass spectrometry to determine N-glycan structures. Our results show that neural differentiation of iPSCs to NSCs is characterized by an increase in the abundance of complex N-glycans at the expense of minimally processed mannosidic N-glycans. Moreover, we found differences in N-glycosylation patterns between D21 and T21 cells. Notably, the abundance of pseudohybrid N-glycans was significantly higher in T21 cells which also exhibited a significantly lower abundance of a specific hybrid monoantennary fucosylated N-glycan (H6N3F1). Overall, our data define the total N-glycome of both D21 and T21 iPSCs and NSCs and show that T21 already impacts N-glycosylation patterns in the stem cell state in a manner consistent with aberrantly premature neural differentiation of T21 cells.

DNA methylation (DNAm)-based marker of aging, referred to as 'epigenetic age' or 'DNAm age' is a highly accurate multi-tissue biomarker for aging, associated with age-related disease risk, including cancer. Breast cancer (BC), an age-associated disease, is associated with older DNAm age and epigenetic age acceleration (age accel) at tissue levels. But this raises a question on the predictability of DNAm age/age accel in BC development, emphasizing the importance of studying DNAm age in pre-diagnostic peripheral blood (PB) in BC etiology and prevention.

We included postmenopausal women from the largest study cohort and prospectively investigated BC development with their pre-diagnostic DNAm in PB leukocytes (PBLs). We estimated Horvath's pan-tissue DNAm age and investigated whether DNAm age/age accel highly correlates with risk for developing subtype-specific BC and to what degree the risk is modified by hormones and lifestyle factors.

DNAm age in PBLs was tightly correlated with age in this age range, and older DNAm age and epigenetic age accel were significantly associated with risk for developing overall BC and luminal subtypes. Of note, in women with bilateral oophorectomy before natural menopause experiencing shorter lifetime estrogen exposure than those with natural menopause, epigenetic age accel substantially influenced BC development, independent of obesity status and exogeneous estrogen use.

Our findings contribute to better understanding of biologic aging processes that mediate BC carcinogenesis, detecting a non-invasive epigenetic aging marker that better reflects BC development, and ultimately identifying the elderly with high risk who can benefit from epigenetically targeted preventive interventions.

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

Since the mid-1970s, increasingly innovative methods to detect DNA methylation provided detailed information about its distribution, functions, and dynamics. As a result, new concepts were formulated and older ones were revised, transforming our understanding of the associated biology and catalyzing unprecedented advances in biomedical research, drug development, anthropology, and evolutionary biology. In this review, we discuss a few of the most notable advances, which are intimately intertwined with the study of DNA methylation, with a particular emphasis on the past three decades. Examples of these strides include elucidating the intricacies of 5-methylcytosine (5-mC) oxidation, which are at the core of the reversibility of this epigenetic modification; the three-dimensional structural characterization of eukaryotic DNA methyltransferases, which offered insights into the mechanisms that explain several disease-associated mutations; a more in-depth understanding of DNA methylation in development and disease; the possibility to learn about the biology of extinct species; the development of epigenetic clocks and their use to interrogate aging and disease; and the emergence of epigenetic biomarkers and therapies.

The emergence of epigenetic predictors was a pivotal moment in geroscience, propelling the measurement and concept of biological aging into a quantitative era; however, while current epigenetic clocks show strong predictive power, they are data-driven in nature and are not based on the underlying biological mechanisms driving methylation dynamics. We show that predictions of these clocks are susceptible to several confounding non-age-related phenomena that make interpretation of these estimates and associations difficult. To address these limitations, we developed a probabilistic model describing methylation transitions at the cellular level. Our approach reveals two measurable components, acceleration and bias, which directly reflect perturbations of the underlying cellular dynamics. Acceleration is the proportional increase in the speed of methylation transitions across CpG sites, whereas bias corresponds to global changes in methylation levels. Using data from 15,900 participants from the Generation Scotland study, we develop a robust inference framework and show that these are two distinct processes confounding current epigenetic predictors. Our results show improved associations of acceleration and bias with physiological traits known to impact healthy aging, such as smoking and alcohol consumption, respectively. Furthermore, a genome-wide association study of epigenetic age acceleration identified seven genomic loci.

Down syndrome is the most frequently occurring genetic condition, with a substantial escalation in risk associated with advanced maternal age. The syndrome is characterized by a diverse range of phenotypes, affecting to some extent all levels of organization, and its progeroid nature - early manifestation of aspects of the senile phenotype. Despite extensive investigations, many aspects and mechanisms of the disease remain unexplored. The current review aims to provide an overview of the main causes and manifestations of Down syndrome, while also examining the phenomenon of accelerated aging and exploring potential therapeutic strategies.

The one-carbon metabolism pathway is involved in critical human cellular functions such as cell proliferation, mitochondrial respiration, and epigenetic regulation. In the homocysteine-methionine cycle S-adenosyl-methionine (SAM) and S-adenosyl-homocysteine (SAH) are synthetized, and their levels are finely regulated to ensure proper functioning of key enzymes which control cellular growth and differentiation. Here we review the main biological mechanisms involving SAM and SAH and the known related human diseases. It was recently demonstrated that SAM and SAH levels are altered in plasma of subjects with trisomy 21 (T21) but how this metabolic dysregulation influences the clinical manifestation of T21 phenotype has not been previously described. This review aims at providing an overview of the biological mechanisms which are altered in response to changes in the levels of SAM and SAH observed in DS.

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

Down syndrome (DS) is characterized by lowered immune competence and premature aging. We previously showed decreased antibody response following SARS-CoV-2 vaccination in adults with DS. IgG1 Fc glycosylation patterns are known to affect the effector function of IgG and are associated with aging. Here, we compare total and anti-spike (S) IgG1 glycosylation patterns following SARS-CoV-2 vaccination in DS and healthy controls (HC). Total and anti-Spike IgG1 Fc N-glycan glycoprofiles were measured in non-exposed adults with DS and controls before and after SARS-CoV-2 vaccination by liquid chromatography-mass spectrometry (LC-MS) of Fc glycopeptides. We recruited N = 44 patients and N = 40 controls. We confirmed IgG glycosylation patterns associated with aging in HC and showed premature aging in DS. In DS, we found decreased galactosylation (50.2% vs. 59.0%) and sialylation (6.7% vs. 8.5%) as well as increased fucosylation (97.0% vs. 94.6%) of total IgG. Both cohorts showed similar bisecting GlcNAc of total and anti-S IgG1 with age. In contrast, anti-S IgG1 of DS and HC showed highly comparable glycosylation profiles 28 days post vaccination. The IgG1 glycoprofile in DS exhibits strong premature aging. The combination of an early decrease in IgG1 Fc galactosylation and sialylation and increase in fucosylation is predicted to reduce complement activity and decrease FcγRIII binding and subsequent activation, respectively. The altered glycosylation patterns, combined with decreased antibody concentrations, help us understand the susceptibility to severe infections in DS. The effect of premature aging highlights the need for individuals with DS to receive tailored vaccines and/or vaccination schedules.

Down syndrome (DS) stands as the prevalent genetic cause of intellectual disability, yet comprehensive understanding of its cellular and molecular underpinnings remains limited. In this study, we explore the cellular landscape of the hippocampus in a DS mouse model, the Ts65Dn, through single-nuclei transcriptional profiling. Our findings demonstrate that trisomy manifests as a highly specific modification of the transcriptome within distinct cell types. Remarkably, we observed a significant shift in the transcriptomic profile of granule cells in the dentate gyrus (DG) associated with trisomy. We identified the downregulation of a specific small nucleolar RNA host gene, Snhg11, as the primary driver behind this observed shift in the trisomic DG. Notably, reduced levels of Snhg11 in this region were also observed in a distinct DS mouse model, the Dp(16)1Yey, as well as in human postmortem brain tissue, indicating its relevance in Down syndrome. To elucidate the function of this long non-coding RNA (lncRNA), we knocked down Snhg11 in the DG of wild-type mice. Intriguingly, this intervention alone was sufficient to impair synaptic plasticity and adult neurogenesis, resembling the cognitive phenotypes associated with trisomy in the hippocampus. Our study uncovers the functional role of Snhg11 in the DG and underscores the significance of this lncRNA in intellectual disability. Furthermore, our findings highlight the importance of DG in the memory deficits observed in Down syndrome.

As human life expectancy continues to rise, becoming a pressing global concern, it brings into focus the underlying mechanisms of aging. The increasing lifespan has led to a growing elderly population grappling with age-related diseases (ARDs), which strains healthcare systems and economies worldwide. While human senescence was once regarded as an immutable and inexorable phenomenon, impervious to interventions, the emerging field of geroscience now offers innovative approaches to aging, holding the promise of extending the period of healthspan in humans. Understanding the intricate links between aging and pathologies is essential in addressing the challenges presented by aging populations. A substantial body of evidence indicates shared mechanisms and pathways contributing to the development and progression of various ARDs. Consequently, novel interventions targeting the intrinsic mechanisms of aging have the potential to delay the onset of diverse pathological conditions, thereby extending healthspan. In this narrative review, we discuss the most promising methods and interventions aimed at modulating aging, which harbor the potential to mitigate ARDs in the future. We also outline the complexity of senescence and review recent empirical evidence to identify rational strategies for promoting healthy aging.

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.

Down syndrome (DS) is a segmental progeroid genetic disorder associated with multi-systemic precocious aging phenotypes, which are particularly evident in the immune and nervous systems. Accordingly, people with DS show an increased biological age as measured by epigenetic clocks. The Ts65Dn trisomic mouse, which harbors extra-numerary copies of chromosome 21 (Hsa21)-syntenic regions, was shown to recapitulate several progeroid features of DS, but no biomarkers of age have been applied to it so far. In this pilot study, we used a mouse-specific epigenetic clock to measure the epigenetic age of hippocampi from Ts65Dn and euploid mice at 20 weeks. Ts65Dn mice showed an increased epigenetic age in comparison with controls, and the observed changes in DNA methylation partially recapitulated those observed in hippocampi from people with DS. Collectively, our results support the use of the Ts65Dn model to decipher the molecular mechanisms underlying the progeroid DS phenotypes.

Epigenetic ageing in a human context, has been used to better understand the relationship between age and factors such as lifestyle and genetics. In an ecological setting, it has been used to predict the age of individual animals for wildlife management. Despite the importance of epigenetic ageing in a range of research fields, the assays to measure epigenetic ageing are either expensive on a large scale or complex. In this study, we aimed to improve the efficiency and sequencing quality of an existing epigenetic ageing assay for the Australian Lungfish (Neoceratodus forsteri). We used an enzyme-based alternative to bisulfite conversion to reduce DNA fragmentation and evaluated its performance relative to bisulfite conversion. We found the sequencing quality to be 12% higher with the enzymatic alternative compared to bisulfite treatment (p-value < 0.01). This new enzymatic based approach, although currently double the cost of bisulfite treatment can increases the throughput and sequencing quality. We envisage this assay setup being adopted increasingly as the scope and scale of epigenetic ageing research continues to grow.

We develop blood test-based aging clocks and examine how these clocks reflect high-volume sports activity.

We use blood tests and body metrics data of 421 Hungarian athletes and 283 age-matched controls (mean age, 24.1 and 23.9 yr, respectively), the latter selected from a group of healthy Caucasians of the National Health and Nutrition Examination Survey (NHANES) to represent the general population ( n = 11,412). We train two age prediction models (i.e., aging clocks) using the NHANES dataset: the first model relies on blood test parameters only, whereas the second one additionally incorporates body measurements and sex.

We find lower age acceleration among athletes compared with the age-matched controls with a median value of -1.7 and 1.4 yr, P < 0.0001. BMI is positively associated with age acceleration among the age-matched controls ( r = 0.17, P < 0.01) and the unrestricted NHANES population ( r = 0.11, P < 0.001). We find no association between BMI and age acceleration within the athlete dataset. Instead, age acceleration is positively associated with body fat percentage ( r = 0.21, P < 0.05) and negatively associated with skeletal muscle mass (Pearson r = -0.18, P < 0.05) among athletes. The most important blood test features in age predictions were serum ferritin, mean cell volume, blood urea nitrogen, and albumin levels.

We develop and apply blood test-based aging clocks to adult athletes and healthy controls. The data suggest that high-volume sports activity is associated with slowed biological aging. Here, we propose an alternative, promising application of routine blood tests.

DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.

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.

To identify potent DNA methylation candidates that could predict response to temozolomide (TMZ) in glioblastomas (GBMs) that do not have glioma-CpGs island methylator phenotype (G-CIMP) but have an unmethylated promoter of O-6-methylguanine-DNA methyltransferase (unMGMT).

The discovery-validation approach was planned incorporating a series of G-CIMP-/unMGMT GBM cohorts with DNA methylation microarray data and clinical information, to construct multi-CpG prediction models. Different bioinformatic and experimental analyses were performed for biological exploration.

By analyzing discovery sets with radiotherapy (RT) plus TMZ versus RT alone, we identified a panel of 64 TMZ efficacy-related CpGs, from which a 10-CpG risk signature was further constructed. Both the 64-CpG panel and the 10-CpG risk signature were validated showing significant correlations with overall survival of G-CIMP-/unMGMT GBMs when treated with RT/TMZ, rather than RT alone. The 10-CpG risk signature was further observed for aiding TMZ choice by distinguishing differential outcomes to RT/TMZ versus RT within each risk subgroup. Functional studies on GPR81, the gene harboring one of the 10 CpGs, indicated its distinct impacts on TMZ resistance in GBM cells, which may be dependent on the status of MGMT expression.

The 64 TMZ efficacy-related CpGs and in particular the 10-CpG risk signature may serve as promising predictive biomarker candidates for guiding optimal usage of TMZ in G-CIMP-/unMGMT GBMs.

Over 200,000 individuals in the United States alone live with Down Syndrome (DS), the most common genetic disorder associated with intellectual disability. DS has a constellation of features across the body, including dysregulation of the immune system. Individuals with DS have both a higher frequency of autoimmunity and more severe infections than the general population, highlighting the importance of understanding the immune system in this population. Individuals with DS present with dysregulation of both the innate and adaptive immune systems. Elevated cytokine levels, increased type I and type II IFN signaling, a shift toward memory phenotypes in T cells, and a decrease in the size of the B-cell compartment are observed in individuals with DS, which contribute to both autoinflammation and severe infections. Herein, we discuss the current knowledge of the immune system in individuals with Down Syndrome as well as ideas of necessary further investigations to decipher the mechanisms by which trisomy 21 leads to immune dysregulation, with the ultimate goal of identifying clinical targets to improve treatment.

Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.

Characterise the circumstances associated with death during admission of adults with Down syndrome (DS) and to identify predictors of mortality.

Observational study based on data on all emergent admissions of adults with DS to hospitals of the Spanish National Health System between 1997 and 2014. We analysed epidemiological and clinical variables.

We analysed admissions of 11,594 adults with DS, mean age 47 years. 1715 patients died (15%), being the highest mortality (35%) in individuals aged 50-59. A past medical history of cerebrovascular disease (aOR 2.95 [2.30-3.77]) or cancer (aOR 2.79 [2.07-3.75]), gross aspiration's admission (aOR 2.59 [2.20-3.04]), immobility (aOR 2.31 [1.46-3-62]), and readmission within 30 days (aOR 2.43 [2.06-2.86]) were identified as predictors of mortality.

Adults with DS have a high in-hospital mortality rate. The main predictors of death were cerebrovascular disease, cancer, early readmission, and conditions commonly associated with advanced dementia.

Reis, AL, Deus, LA, Neves, RVP, Corrêa, HL Reis, TL, Aguiar, LS Honorato, FS, Barbosa, JMS, Araújo, TB, Palmeira, TRC, Simões, HG, Prestes, J, Sousa, CV, Ide, BN, and Rosa, TdS. Exercise-induced transient oxidative stress is mitigated in Down syndrome: insights about redox balance and muscle strength. J Strength Cond Res 38(3): e125-e34, 2024-This study aimed to evaluate the acute effects of a session of resistance exercise (RE) performed with elastic tubes on the redox balance and inflammatory profile in individuals with Down syndrome (DS). Subjects ( n = 23) were allocated into 2 groups: individuals with DS (DS; n = 11) and individuals without DS (WDS; n = 12), who performed an acute RE session. Diagnostic assessment included medical history, anthropometric measures (body height, body mass, body mass index, and body composition assessment), biological collections, muscle strength assessments (handgrip and maximal voluntary isometric contraction tests), and exercises. The redox balance and inflammatory profile were assessed in urine and saliva samples before and after an acute RE session. There were no differences between WDS and DS groups for body composition ( p > 0.05). The DS group presented higher values pre and post an acute RE session with elastic tubes for oxidative and proinflammatory markers compared with WDS ( p < 0.05). Uric acid values increased from pre-acute RE session to post-acute RE session for WDS ( p < 0.0001). No differences were identified within groups for the delta analysis ( p > 0.05). Inverse correlations were found between total force and F2-isoprostane, 8OHdG, uric acid, allantoin, IL-6, TNF-α, and the TNF-α:IL-10 ratio. A positive correlation was found between IL-10 and total force. The DS group presented increased peak force in the knee extension and elbow flexion exercises (∼25 and 12%, respectively) but decreases in handgrip strength of ∼7%. The WDS group showed higher peak force values for knee extension, elbow flexion, and handgrip (∼16, 10, and 14%, respectively). The DS group had lower transient elevation of oxidative stress after an acute RE session compared with WDS. Oxidative stress and inflammation responses of DS to an acute RE session with elastic tubes may be insufficient to induce health adaptations for the same relative load compared with WDS.

Individuals with Down syndrome (DS) are born with and develop many health-related complications. The purpose of this study was to determine the longitudinal functional fitness profile of adults with DS.

The functional fitness of adults with DS was tested twice, 12 years apart. Sixty-six adults with DS were tested for body mass, stature and 10 functional fitness tests. Data were categorised according to gender and age-specific categories.

Static balance, shoulder flexibility, trunk strength and aerobic capacity deteriorated significantly with medium to large effect sizes for both DS men and women (most age categories). For women, dynamic balance deteriorated significantly, and for men, leg- and upper body-strength deteriorated significantly.

Practitioners working in the field of adapted physical activity should take cognisance of the functional fitness ageing profile of adults with DS and timeously develop habitual physical activity interventions to reduce the effect of accelerated ageing experienced by this population.

In many studies of human diseases, multiple omics datasets are measured. Typically, these omics datasets are studied one by one with the disease, thus the relationship between omics is overlooked. Modeling the joint part of multiple omics and its association to the outcome disease will provide insights into the complex molecular base of the disease. Several dimension reduction methods which jointly model multiple omics and two-stage approaches that model the omics and outcome in separate steps are available. Holistic one-stage models for both omics and outcome are lacking. In this article, we propose a novel one-stage method that jointly models an outcome variable with omics. We establish the model identifiability and develop EM algorithms to obtain maximum likelihood estimators of the parameters for normally and Bernoulli distributed outcomes. Test statistics are proposed to infer the association between the outcome and omics, and their asymptotic distributions are derived. Extensive simulation studies are conducted to evaluate the proposed model. The method is illustrated by modeling Down syndrome as outcome and methylation and glycomics as omics datasets. Here we show that our model provides more insight by jointly considering methylation and glycomics.

Young blood plasma is known to confer beneficial effects on various organs in mice and rats. However, it was not known whether plasma from young adult pigs rejuvenates old rat tissues at the epigenetic level; whether it alters the epigenetic clock, which is a highly accurate molecular biomarker of aging. To address this question, we developed and validated six different epigenetic clocks for rat tissues that are based on DNA methylation values derived from n = 613 tissue samples. As indicated by their respective names, the rat pan-tissue clock can be applied to DNA methylation profiles from all rat tissues, while the rat brain, liver, and blood clocks apply to the corresponding tissue types. We also developed two epigenetic clocks that apply to both human and rat tissues by adding n = 1366 human tissue samples to the training data. We employed these six rat clocks to investigate the rejuvenation effects of a porcine plasma fraction treatment in different rat tissues. The treatment more than halved the epigenetic ages of blood, heart, and liver tissue. A less pronounced, but statistically significant, rejuvenation effect could be observed in the hypothalamus. The treatment was accompanied by progressive improvement in the function of these organs as ascertained through numerous biochemical/physiological biomarkers, behavioral responses encompassing cognitive functions. An immunoglobulin G (IgG) N-glycosylation pattern shift from pro- to anti-inflammatory also indicated reversal of glycan aging. Overall, this study demonstrates that a young porcine plasma-derived treatment markedly reverses aging in rats according to epigenetic clocks, IgG glycans, and other biomarkers of aging.