Fatigue, muscle fatigability, and the Hallmarks of Aging: a narrative review.

Depression and biological aging: Unexpected vulnerability in relatively advantaged social risk profile group.

Activating the vagus nerve-adrenal anti-inflammatory axis to delay aging: A randomized controlled trial protocol.

Clock-like mutational signatures: Linking ageing to endogenous cancer risk.

DNA methylation changes are reliable biomarkers of aging, but the driving mechanisms remain poorly understood. Here we present SCARLET (Stem Cells and Age-ReLated Epigenetic Trajectories), a parsimonious mathematical model that describes how methylation changes in blood arise and propagate through hematopoietic stem cell divisions. Using a large human cohort, we demonstrate that seemingly distinct age-related methylation patterns can be explained by a unifying mechanistic model. We show that SCARLET captures known drivers of epigenetic aging, with accelerated individuals showing reduced ratios of stem cell pool size to division rate (N/s). Applying SCARLET to methylation data from 11 mammalian species reveals that N/s scales with maximum lifespan, suggesting that evolutionary adjustments to stem cell dynamics, rather than epigenetic maintenance efficiency, drive the previously observed relationship between methylation rates and lifespan. Our findings provide a quantitative framework for understanding epigenetic aging and suggest that stem cell dynamics may be a key driver of aging across mammals.

ProtFI, an efficient frailty-trained proteomics-based biomarker of aging, robustly predicts age-related decline.

Geroscience needs biomarkers that capture the progressive decline of integrated biological systems with age. Physical capacity, a direct manifestation of systemic integrity, is a core pillar of biological aging but is typically assessed through discrete clinical tests. Speech production, a complex motor act requiring coordinated respiratory, laryngeal, and articulatory control, shares fundamental physiological pathways with global physical function and may therefore serve as an accessible digital biomarker of aging. In a longitudinal cohort of 464 community-dwelling older adults (mean age 79.6 ± 8.7years), we tested the hypothesis that changes in speech track specific changes in physical capacity. Participants underwent a 3-month adapted physical activity (APA) program. At baseline (T0) and post-intervention (T1), we performed a battery of ten objective physical tests (strength, power, endurance, gait, balance, flexibility, mobility, appendicular lean mass, fatigue) and recorded spontaneous speech during emotional autobiographical recall. Multi-layered acoustic, temporal, and linguistic features were automatically extracted. The longitudinal association was analyzed via Spearman correlations and univariate linear mixed-effects models. The APA intervention induced significant improvements in key physical domains, including mobility, gait speed, handgrip strength, and balance (all p < 0.01). These gains were specifically correlated with concurrent changes in speech features (|ρ| = 0.11-0.22). For instance, greater lower-limb strength correlated with reduced vocal shimmer and lexical diversity, while improved flexibility was associated with a lower spectral centroid and zero-crossing rate, indicating smoother phonation. Linear mixed models confirmed significant within-individual coupling between trajectories of physical function and speech dynamics. Emotional context systematically modulated these associations, revealing different speech-stress signatures under cognitive-affective load. This study provides novel longitudinal evidence that speech is a dynamic digital biomarker of domain-specific physical capacity, reflecting underlying functional integrity. The domain-specific speech-physical coupling suggests that speech analysis can serve as a novel, integrative tool for remote monitoring of aging trajectories and the functional efficacy of interventions targeting the age-related physiological decline.

Nicotinamide adenine dinucleotide (NAD+) levels in blood and tissues are widely proposed to decline with age, yet evidence in human blood is inconsistent. Using a rigorously validated ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry system that accounts for real-world analytical variability, we quantify NAD+ across seven independent human cohorts. We find that whole-blood NAD+ levels remain remarkably stable with age and across lifestyle interventions, but change in response to nicotinamide riboside supplementation, as expected. Our results challenge the utility of blood NAD+ levels as a biomarker of ageing or lifestyle factors.

DNA methylation (DNAm)-based epigenetic clocks are emerging biomarkers of biological aging and have been linked to cognitive decline and dementia, but their relationship with blood-based neurodegenerative biomarkers remains understudied in low- and middle-income countries (LMIC). Using the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD), we examined whether epigenetic aging was associated with levels and changes in neurodegenerative biomarkers among adults aged ≥60 years. Seven epigenetic clocks were derived from DNAm data and related to plasma levels of glial fibrillary acidic protein (GFAP), neurofilament light (NfL), phosphorylated tau 181 (pTau181), total tau, Amyloid-β (Aβ)42, Aβ40 and Aβ42/Aβ40 measured at two time points. Baseline accelerated epigenetic aging was associated with higher levels of neurodegenerative biomarkers, including pTau181, GFAP, and NfL, with more consistent associations with increases in GFAP and NfL for morbidity- and mortality-trained clocks. These findings support the utility of epigenetic clocks as scalable tools for identifying risk of neurodegeneration in LMIC settings.

Diet is a modifiable lifestyle factor that may modify biological aging. However, its relationship with biomarkers of biological aging is scarce or divergent. Thus, we aimed to investigate the association between dietary patterns and epigenetic and inflammatory age acceleration. In this cross-sectional study with 764 adults (62% female; 20-100 years), participants in the INSPIRE-T observational cohort (France), we used linear regression models to associate dietary patterns (data-driven and as adherence scores to well-established diets) with biological age acceleration estimated by using epigenetic clocks (Horvath's, Hannum's, PhenoAge, and GrimAge) and the inflammatory clock (iAge). We further explored the moderating effect of sex and age groups (20-44, 45-64, ≥65), and the mediating role of body fat, measured by DXA. Here, we show that a 10-point increase in the Dietary Approaches to Stop Hypertension diet (DASH) score is associated with a 1.7-year lower PhenoAge acceleration, with 23% of this association being explained by android fat. Every one-unit increase in the "Plant-based" dietary pattern scores is marginally associated with 1.1-year lower PhenoAge acceleration, with total body fat accounting for 26% of this association. In the latter, the association seems more robust in older males. No consistent associations are observed for other dietary patterns, Horvath's and Hannum's clock, GrimAge, or iAge. Greater scores in aDASH and "Plant-based" dietary patterns are associated with lower epigenetic age acceleration through reduced body fat, with a partial moderating role of sex and age.

Adolescent-onset schizophrenia (AOS) is characterized by severe cognitive impairment. Insulin-like growth factor binding protein-7 (IGFBP-7), a biomarker of vascular aging and neuroinflammation, and hepatocyte growth factor (HGF), involved in neurodevelopment, have been linked to cognitive decline, but their roles in AOS remain unexplored. This case-control study enrolled 91 first-episode drug-naïve AOS patients and 40 healthy controls. Clinical symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and its five-factor model, and cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). AOS patients exhibited significantly lower serum IGFBP-7 levels compared to healthy controls (10.15 ± 3.62 vs. 11.75 ± 3.41 ng/mL, t = -2.377, P = 0.019), while HGF levels showed no significant difference (P > 0.05). IGFBP-7 levels were negatively correlated with PANSS cognitive factor scores (r = -0.308, P = 0.003) and positively correlated with RBANS total scores (r = 0.353, P = 0.001). IGFBP-7 was independently associated with RBANS total score (β = 0.284, P = 0.002) after controlling for confounding factors. Sex (β = 0.467, t = 5.325, P < 0.001) was identified as a confounder but did not moderate the IGFBP-7-cognition relationship (P > 0.05). Modified Poisson regression revealed that low IGFBP-7 levels independently predicted AOS risk (RR = 1.298, 95% CI: 1.037-1.624, P = 0.023), with attributable fractions of 23.0% in exposed individuals and 12.7% in the overall population. Decreased serum IGFBP-7 levels are associated with cognitive impairment in AOS and represent a significant risk factor, suggesting IGFBP-7 as a potential biomarker for cognitive dysfunction in AOS.

BackgroundThe gut microbiota adapts to and shapes the host’s metabolic state through affecting circulating metabolites and consequent gene regulatory networks, resulting in systemic influences in diverse organs via connections such as the gut–liver axis. Numerous variables such as diet, age, and host genetics modulate the composition of the gut microbiome, but their interactions and specific associative and mechanistic links to host molecular phenotypes remain incompletely unannotated. Integrated multi-omics approaches in genetically diverse populations offer an opportunity to dissect these interactions and identify predictive microbial signatures for host phenotypes, such as body weight and molecular associations with gene expression pathways in gut and liver.ResultsWe sequenced, aligned, and integrated the cecal metagenome, metatranscriptome, and host transcriptome from 232 mice across 175 distinct cohorts according to a low-fat chow diet (CD) or a high-fat diet (HF), four adult ages (between roughly 180 to 730 days of age), and 43 distinct genotypes (inbred BXD strains). Genetics and diet exerted the strongest influence on microbiota abundance and activity, followed by age. HF feeding significantly reduced diversity across all ages and all genotypes, altering > 300 species. Machine learning models based on microbial profiles reliably predicted body weight within dietary group (AUC = 0.84 for CD, 0.79 for HF) and chronological age (AUC = 0.84), with model performance of age prediction rising to 0.95 when integrating top microbial features with liver proteomics. Network analyses of expression data revealed links between genes, pathways, and specific microbes, including a negative association between cecal Ido1 expression and short-chain fatty acid (SCFA)-producing Lachnospiraceae, suggesting dietary fat may modulate host tryptophan metabolism through microbiota shifts.ConclusionsWhole metagenome and metatranscriptome sequencing approaches have massively expanded the landscape of microbiome analysis compared to earlier short-read 16S analyses. The resulting datasets quantify hundreds of uniquely identifiable microbes, which can be used to create sets of highly predictive microbial biomarkers for aging and obesity. When trained on controlled mouse populations, these results demonstrate that microbiome profiling can achieve high predictive capacity (AUC = 0.95 with multi-omics integration) for complex readouts such as age and body weight (AUC = 0.84), even considering genetic and dietary variation, establishing a framework for biomarker development. While at present many bacteria are still functionally unannotated at the species level, multi-omics approaches — including gene expression from the host tissues — provide insights into the functional associations of specific taxa in the microbiome.Video Supplementary InformationThe online version contains supplementary material available at 10.1186/s40168-026-02369-x.

Modern humans now routinely survive to advanced ages, in far greater proportions than ancestral populations, and thus experience the consequences of molecular pathways optimized for youth yet still active in old age. Natural selection weakens over the course of adulthood, creating a selection 'shadow' in which deleterious late-acting mutations accumulate and alleles with early-life benefits persist despite late-life costs. An evolutionary lens helps us to understand puzzling patterns - from conserved longevity pathways spanning the tree of life to a 100-fold variation in maximum lifespan across vertebrates - and explains why age-related diseases share genetic architectures. Advances in comparative genomics, large-scale human genetic studies and multi-omics ageing biomarkers now enable rigorous testing of evolutionary predictions. This Review integrates evolutionary genetics with molecular mechanisms to clarify why ageing evolves, how it varies across species and individuals, and how these insights can guide healthspan extension.

Assessing differences in epigenetic aging markers between sexual or gender minority and straight cisgender adults using the Coronary Artery Risk Development in Young Adults cohort.

Ergothioneine as a potential geroprotector: Targeting molecular hallmarks of ageing and age-related diseases.

Although plasma pTau181 has been shown to accurately discriminate patients with Alzheimer's disease from healthy older adults, there are few studies of plasma biomarkers among middle-aged populations. Given the potential utility of plasma AD biomarkers such as pTau181 in screening for disease risk, examining pTau181 in a middle-aged cohort without AD is important for future implementation. The objectives of this studywere to characterise plasma pTau181 in a middle-aged birth cohort aged 45years and to investigate associations with early indicators of dementia risk. Participants were members of the Dunedin Multidisciplinary Health and Development Study, a longitudinal study of 1037 people born in New Zealand in 1972-1973. Plasma pTau181, self-reported cognitive concerns, MRI-based brain structure, and DunedinPACE (an epigenetic biomarker of biological ageing) were measured at age 45; cognition was measured in childhood and age 45. Plasma pTau181 concentrations at age 45 (n = 854, 49% female) were associated with self-reported cognitive concerns (β = 0.09, p = .008); however, no significant associations were observed with objective cognitive decline, worse structural brain integrity, or biological ageing. Higher plasma pTau181 was associated with self-reported cognitive concerns at age 45, but not objective AD-related measures. The association of plasma pTau181 and self-reported cognitive concerns in this cohort suggests that AD pathology may begin to accumulate by age 45 and may be associated with subtle changes in cognition that are not at objectively measurable levels.

Among older adults with early breast cancer, the risk of chemotoxicity can vary widely despite similar chronological age. Here, we evaluated whether epigenetic indicators of biological age can stratify the risk of chemotoxicity in this population. In a prospective study of 394 women age > 65 with stage I-III breast cancer treated with neo/adjuvant chemotherapy, we analyzed peripheral blood DNA methylation patterns to estimate epigenetic age acceleration (EAA) before chemotherapy. We tested five epigenetic clocks. The primary endpoint was grade 2+ chemotoxicity (yes/no, yes defined as any grade 2+ toxicity attributed to chemotherapy). Using multivariable logistic regression, we examined the association between EAA and grade 2+ chemotoxicity, adjusting for demographic, clinical, and geriatric covariates. We also evaluated the relationship between EAA and individual grade 2+ toxicities. The median (range) pre-treatment chronological age was 70years (65-85); 65% had stage II/III disease; 38% received anthracycline; and 75% received G-CSF prophylaxis. A total of 334 (84.8%) participants experienced a grade 2+ toxicity. After multivariable adjustment, there was no significant association between measures of EAA and grade 2+ chemotoxicity. For individual toxicities, EAA by GrimAge was associated with increased risk for infection without neutropenia, and EAA by DunedinPACE was associated with increased risk for diarrhea. In this cohort of older adults with early breast cancer, there was no significant association between pre-treatment EAA and overall grade 2+ chemotoxicity. Further research is needed to examine whether blood-based biomarkers of aging may identify older adults at high risk of chemotoxicity. NCT01472094, Hurria Older PatiEnts (HOPE) with Breast Cancer Study.

The Role of Phospho-ubiquitin in Mitochondrial Health and Diseases.

Aging is a complex biological process uniquely shaped in women by hormonal transitions, particularly across the menopause transition. While chronological age alone fails to capture individual health variability, emerging molecular biomarkers offer tools to quantify biological aging and understand mechanisms underlying age-related decline. This review synthesizes the current landscape of aging biomarkers, including senescence-associated secretory phenotype factors, epigenetic clocks, clonal hematopoiesis of indeterminate potential, and telomere length, with a particular emphasis on their relevance to menopause. This narrative review synthesizes human studies, translational research, and foundational basic science identified through PubMed searches through June 2025, examining aging biomarkers in general populations, among women in the menopause transition, and in relation to vasomotor symptoms and hormone therapy. Evidence demonstrates that changes in biological aging biomarkers are observed across multiple molecular systems during midlife, including the menopause transition, reflecting broader age-related biological remodeling. Postmenopausal status, particularly following early or surgical menopause, has been associated with biological aging phenotypes, including elevated senescence-associated secretory phenotype factors, epigenetic age acceleration, clonal hematopoiesis, and shorter leukocyte telomere length, likely reflecting a combination of chronological aging, hormonal changes, and individual biological vulnerability. While severe vasomotor symptoms have been linked to higher epigenetic age, hormone therapy may favorably influence certain senescence markers and biological age discrepancy. Despite these advances, significant limitations constrain clinical translation, as current biomarkers capture overlapping biological processes and lack validated thresholds to define biological aging, especially in women. Future research requires large, longitudinal studies across diverse populations to establish clinically meaningful thresholds and sex-specific calibration. Advancing precision health strategies for women requires a better understanding of how reproductive and hormonal factors modify biomarker trajectories to improve risk prediction and to facilitate the development of targeted interventions for age-related diseases.

Advancing age, the APOEɛ4 allele, and female sex are the top nonmodifiable risk factors for Alzheimer's disease (AD). Female-specific experiences, such as parity and hormone therapy (HT) affect aging biomarkers such as metabolism and immune signaling, and may affect AD risk. Estradiol (E2), a component of many HTs, affects cognition and brain health in aging females although studies suggest the effects can vary depending on parity, genotype, and metabolic status which may account for some of the inconsistencies in the literature. We hypothesized that prior parity influences brain and metabolic health, including response to E2, depending on APOE genotype. Middle-aged female (10 month) wildtype (WT) or humanized (h) APOEɛ4 expressing rats, with different reproductive experience (nulliparous or primiparous) were fed a Western (WD) or standard diet (SD) for 2 months. In the second month, rats were given E2 or vehicle (oil) injections daily. Fear associative learning, plasma metabolic hormones, hippocampal inflammatory cytokine expression, and neuroplasticity (neurogenesis, synaptic protein) were assessed. Females fed a WD gained weight and displayed metabolic dysregulation, regardless of genotype. E2 treatment reduced WD-induced weight gain and reduced metabolic hormones, with stronger effects in WT rats. E2 treatment increased dorsal hippocampal inflammatory cytokine expression selectively in primiparous hAPOEɛ4 females fed a WD. Previous parity increased neurogenesis and reduced certain cytokine expression in the hippocampus of middle-aged WT rats under a SD. Both E2 treatment and previous parity decreased dorsal neurogenesis in hippocampus of hAPOEɛ4 rats. In hAPOEɛ4 females, higher weight was associated with reduced contextual fear memory, an effect driven by primiparous females. In the cued fear conditioning task, hAPOEɛ4 females displayed better cued fear memory than WT, however, WD exposure reduced cued fear memory only in this group. Together, this indicates that diet and weight gain may be more detrimental to associative memory in hAPOEɛ4 females and that E2 treatment has more favourable outcomes in WT rats. Previous parity alters how females respond to E2 and metabolic stress in midlife. Primiparous hAPOEɛ4 females were especially vulnerable to the effects of WD and E2, exhibiting more inflammation, impaired memory, and reduced weight-loss. These findings highlight the importance of considering parity and genotype when evaluating midlife metabolic and cognitive risk.