Biomarker Of Biological Aging Research Articles

Through the Lens of Age: Using Dog Photographs to Uncover Welfare and Stress

This study evaluated the potential of using dogs’ apparent age, judged from photographs, as a non-invasive tool for assessing their welfare. Traditional welfare assessment methods often rely on behavioral and physiological indicators, which can be resource-intensive and invasive. This research explored whether apparent age, a measure used in humans to predict health and longevity, can also serve as an indicator of welfare in dogs by investigating its association with relative telomere length (RTL), a biomarker of biological aging. Photographs of 60 domestic dogs were evaluated by canine specialists and general volunteers via the citizen science platform Zooniverse. Participants estimated the age of 20 dogs from three different age categories: young (0–2 years), adult (2–5 years), and senior (6+ years). The accuracy of these predictions was compared to the dogs’ chronological ages and RTLs. Generalized linear models were used to assess factors influencing prediction accuracy, including the dogs’ age, sex, and origin. Results indicated that both specialists and volunteers reliably estimated the age of senior dogs, with no significant differences in accuracy between groups. Dogs with accurate apparent age estimates had RTLs matching their chronological age, while those with premature aging signs had shorter RTLs. This suggests apparent age could be a practical, non-invasive welfare assessment tool, offering a potentially accessible method for new welfare assessment protocols.

Aging drives a program of DNA methylation decay in plant organs.

How organisms age is a question with broad implications for human health. In mammals, DNA methylation is a biomarker for biological age, which may predict age more accurately than date of birth. However, limitations in mammalian models make it difficult to identify mechanisms underpinning age-related DNA methylation changes. Here, we show that the short-lived model plant Arabidopsis thaliana exhibits a loss of epigenetic integrity during aging, causing heterochromatin DNA methylation decay and the expression of transposable elements. We show that the rate of epigenetic aging can be manipulated by extending or curtailing lifespan, and that shoot apical meristems are protected from this aging process. We demonstrate that a program of transcriptional repression suppresses DNA methylation maintenance pathways during aging, and that mutants of this mechanism display a complete absence of epigenetic decay. This presents a new paradigm in which a gene regulatory program sets the rate of epigenomic information loss during aging.

Integrating aging biomarkers and immune function to predict kidney health: insights from the future of families and child wellbeing study.

Biomarkers of biological aging predict health outcomes more accurately than chronological age. This study examines the relationship between aging biomarkers, immune function, and kidney health using the Future of Families and Child Wellbeing Study Biomarker Dataset. Using Wave 5 (year 9) and Wave 6 (year 15), we examined biomarker data from a total of 4898 individuals. The panel of aging biomarkers, comprised of epigenetic clocks (GrimAge, Horvath), immune function markers (CD8 + T cells, plasmablasts), and metabolic indicators (GDF-15, leptin), was evaluated in depth. We used principal component analysis (PCA) and K-means clustering for subtype identification. A random forest regressor was employed to predict kidney function using Cystatin C levels, and the importance of features was assessed. Three clusters with unique biological age and immune function profiles were identified. Cluster 1 had younger biological age markers. In Cluster 2, both GrimAge and GDF-15 levels were significantly increased, indicating an elevated risk for age-related diseases. According to predictive modeling, GrimAge, Pack Years, and immune function markers had the strongest influence on Cystatin C levels (R2 = 0.856). The incorporation of immune aging markers enhanced the predictive power, emphasizing the importance of immunosenescence in renal health. Aging biomarkers and immune function significantly impact kidney health prediction. The study results call for the utilization of extensive biomarker tests for individualized elderly care and early recognition of kidney deterioration. Clinical practice can be improved by incorporating biological age assessments for the prevention and management of age-related diseases.

Shorter Telomere Length is Associated with Food Insecurity in Older People: A Cross-Sectional Study.

Telomere length has been investigated as a biomarker of biological aging and is associated with several diseases, lifestyle, and socioeconomic factors. This study aimed to verify whether food insecurity is associated with shorter telomere length in older people. This is a cross-sectional study carried out in a municipality in the interior of Brazil, with a sample of 440 older people from the community. For telomere length analysis, a blood sample was obtained from each participant, followed by real-time qPCR, and sociodemographic and health information was collected through interviews. Food security/insecurity was measured using the reduced version of the Brazilian Food Insecurity Scale. Descriptive analysis and multiple logistic regression were performed to analyze the factors associated with shorter telomere length, adopting a significance level of 5%. We found that food insecurity was significantly associated with shorter telomere length, regardless of age group, skin color, tabagism, physical activity, milk and dairy consumption, living arrangement, and basic activities of daily life. The findings show the importance of ensuring full access to adequate nutrition for the older population, who are physiologically and socially vulnerable.

8553 GDF-15 Levels In Patients With Prostate Cancer On Androgen Deprivation Therapy

Abstract Disclosure: S.D. Jaramillo-Quiroz: Other; Self; VAPSHCS: Director Fund Research Fellowship/UW Abrass Family Fellowship Fund. CDMRP (PC170059).. L. Caeiro: None. L.J. Anderson: None. J.M. Garcia: None. Growth Differentiation Factor 15 (GDF-15) is a stress-induced cytokine known to induce anorexia and cachexia and a biomarker of biological aging, mitochondrial dysfunction, and worse hand grip strength and poor survival in different settings. Also, GDF-15 has pleiotropic functions at all stages of tumorigenicity and is suggested as a marker to differentiate BPH from PCa. Androgen Deprivation Therapy (ADT) is the standard treatment for advanced prostate cancer (PCa), but it also decreases muscle mass and function and Quality of life (QOL). The role and effects of GDF-15 in prostate cancer patients undergoing ADT are not well characterized and was explored in this longitudinal, 6-month, observational study that recruited men with (PCa) starting ADT (n=60, mean age 69). Body composition [dual energy X-ray absorptiometry (DEXA), body weight history], physical performance [handgrip strength (HGS), 6-minute walk test (6MWT), energy expenditure (indirect calorimetry and actigraphy)], were assessed before, at 3 and 6 months after starting ADT. QoL was assessed by the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC-QLQ-C30). GDF-15 was measured by ELISA. Mean differences performed with standard error of the mean, repeated measures ANOVA and Tukey’s Post Hoc test. Correlations were assessed by Spearman’s. After 6 months of ADT, fat mass was increased (mean difference: 1.14 ±0.38, p=0.0029), and lean muscle mass (mean difference: -1.214 ± 0.38, p=0.005), appendicular lean mass (ALM, mean difference: -0.879 ± 0.19, p=<0.0001). HGS (mean difference: -2.927 ± 0.59, p=<0.0001), and VO2 max decreased (mean difference -3.31 ± 0.83, p=0.0007). Baseline GDF-15 (mean 1456.59 ± 1022.80) was correlated with the changes in weight (r: -0.38, p=0.01), BMI (r: -0.33, p=0.01), ALM (r: -0.29, p=0.04), and fatigue (r: -0.38, p=0.004). As shown, baseline GDF-15 was inversely correlated with changes in weight, appendicular lean mass, and fatigue in subjects undergoing ADT, highlighting the possibility of its role as a biomarker and therapeutic target of body composition and patient-reported outcomes in this setting. Presentation: 6/1/2024

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

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

Development, characterization, and replication of proteomic aging clocks: Analysis of 2 population-based cohorts.

Biological age may be estimated by proteomic aging clocks (PACs). Previous published PACs were constructed either in smaller studies or mainly in white individuals, and they used proteomic measures from only one-time point. In this study, we created de novo PACs and compared their performance to published PACs at 2 different time points in the Atherosclerosis Risk in Communities (ARIC) study of white and black participants (around 75% white and 25% black). A total of 4,712 plasma proteins were measured using SomaScan in blood samples collected in 1990 to 1992 from 11,761 midlife participants (aged 46 to 70 years) and in 2011 to 2013 from 5,183 late-life participants (aged 66 to 90 years). The de novo ARIC PACs were constructed by training them against chronological age using elastic net regression in two-thirds of healthy participants in midlife and late life and validated in the remaining one-third of healthy participants at the corresponding time point. We also computed 3 published PACs. We estimated age acceleration for each PAC as residuals after regressing each PAC on chronological age. We also calculated the change in age acceleration from midlife to late life. We examined the associations of age acceleration and change in age acceleration with mortality through 2019 from all-cause, cardiovascular disease (CVD), cancer, and lower respiratory disease (LRD) using Cox proportional hazards regression in participants (irrespective of health) after excluding the training set. The model was adjusted for chronological age, smoking, body mass index (BMI), and other confounders. We externally validated the midlife PAC using the Multi-Ethnic Study of Atherosclerosis (MESA) Exam 1 data. The ARIC PACs had a slightly stronger correlation with chronological age than published PACs in healthy participants at each time point. Associations with mortality were similar for the ARIC PACs and published PACs. For late-life and midlife age acceleration for the ARIC PACs, respectively, hazard ratios (HRs) per 1 standard deviation were 1.65 and 1.38 (both p < 0.001) for all-cause mortality, 1.37 and 1.20 (both p < 0.001) for CVD mortality, 1.21 (p = 0.028) and 1.04 (p = 0.280) for cancer mortality, and 1.68 and 1.36 (both p < 0.001) for LRD mortality. For the change in age acceleration, HRs for all-cause, CVD, and LRD mortality were comparable to the HRs for late-life age acceleration. The association between the change in age acceleration and cancer mortality was not significant. The external validation of the midlife PAC in MESA showed significant associations with mortality, as observed for midlife participants in ARIC. The main limitation is that our PACs were constructed in midlife and late-life participants. It is unknown whether these PACs could be applied to young individuals. In this longitudinal study, we found that the ARIC PACs and published PACs were similarly associated with an increased risk of mortality. These findings suggested that PACs show promise as biomarkers of biological age. PACs may be serve as tools to predict mortality and evaluate the effect of anti-aging lifestyle and therapeutic interventions.

Animal Models Relevant for Geroscience: Current Trends and Future Perspectives in Biomarkers, and Measures of Biological Aging.

For centuries, aging was considered inevitable and immutable. Geroscience provides the conceptual framework to shift this focus toward a new view that regards aging as an active biological process, and the biological age of an individual as a modifiable entity. Significant steps forward have been made toward the identification of biomarkers for and measures of biological age, yet knowledge gaps in geroscience are still numerous. Animal models of aging are the focus of this perspective, which discusses how experimental design can be optimized to inform and refine the development of translationally relevant measures and biomarkers of biological age. We provide recommendations to the field, including: the design of longitudinal studies in which subjects are deeply phenotyped via repeated multilevel behavioral/social/molecular assays; the need to consider sociobehavioral variables relevant for the species studied; and finally, the importance of assessing age of onset, severity of pathologies, and age-at-death. We highlight approaches to integrate biomarkers and measures of functional impairment using machine learning approaches designed to estimate biological age as well as to predict future health declines and mortality. We expect that advances in animal models of aging will be crucial for the future of translational geroscience but also for the next chapter of medicine.

A retinal biomarker of biological age based on composite clinical phenotypic information

A retinal biomarker of biological age based on composite clinical phenotypic information

ScEpiAge: an age predictor highlighting single-cell ageing heterogeneity in mouse blood

Ageing is the accumulation of changes and decline of function of organisms over time. The concept and biomarkers of biological age have been established, notably DNA methylation-based clocks. The emergence of single-cell DNA methylation profiling methods opens the possibility of studying the biological age of individual cells. Here, we generate a large single-cell DNA methylation and transcriptome dataset from mouse peripheral blood samples, spanning a broad range of ages. The number of genes expressed increases with age, but gene-specific changes are small. We next develop scEpiAge, a single-cell DNA methylation age predictor, which can accurately predict age in (very sparse) publicly available datasets, and also in single cells. DNA methylation age distribution is wider than technically expected, indicating epigenetic age heterogeneity and functional differences. Our work provides a foundation for single-cell and sparse data epigenetic age predictors, validates their functionality and highlights epigenetic heterogeneity during ageing.

DNA methylation-estimated phenotypes, telomere length and risk of ischemic stroke: epigenetic age acceleration of screening and a Mendelian randomization study.

Aging is a complex biological process that may be accelerated in certain pathological conditions. DNA methylation age (DNAmAge) has emerged as a biomarker for biological age, which can differ from chronological age. This research peels back the layers of the relationship between fast-forward aging and ischemic stroke, poking and prodding the potential two-way causal influences between stroke and biological aging indicators. We analyzed a cohort of ischemic stroke patients, comparing DNAmAge with chronological age to measure age acceleration. We assessed variations in age acceleration among stroke subtypes and between sexes. Using Mendelian randomization, we examined the causal links between stroke, aging biomarkers like telomere length, and age acceleration's effect on stroke risk. Our investigation reveals a pronounced association between ischemic stroke and age acceleration, most notably in patients with cardioembolic strokes, who exhibited a striking median difference of 9 years between DNAmAge and chronological age. Furthermore, age acceleration differed significantly across stroke subtypes and was higher in women than in men. In terms of causality, MR analysis indicated a modest negative effect of stroke on telomere length, but no causal effect of age phenotypes on stroke or its subtypes. However, some indication of a potential causal effect of ischemic stroke on PhenoAge acceleration was observed. The study provides insight into the relationship between DNAmAge and ischemic stroke, particularly cardioembolic stroke, and suggests possible gender differences. These insights carry profound clinical significance and set stage for future investigations into the entwined pathways of stroke and accelerated aging.

Association Between Adverse Early Life Factors and Telomere Length in Middle and Late Life.

Telomere length (TL) has been acknowledged as biomarker of biological aging. Numerous investigations have examined associations between individual early life factors and leukocyte TL; however, the findings were far from consistent. We evaluated the relationship between individual and combined early life factors and leukocytes TL in middle and late life using data from the UK Biobank. The early life factors (eg, maternal smoking, breastfeeding, birth weight, and comparative body size and height to peers at age 10) were measured. The regression coefficients (β) and 95% confidence interval (CI) were applied to assess the link of the early life factors and TL in adulthood. Flexible parametric survival models incorporated age to calculate the relationship between early life factors and life expectancy. Exposure to maternal smoking, lack of breastfeeding, low birth weight, and shorter height compared to peers at age 10 were identified to be associated with shorter TL in middle and older age according to the large population-based study with 197 504 participants. Individuals who experienced more than 3 adverse early life factors had the shortest TL in middle and late life (β = -0.053; 95% CI = -0.069 to -0.038; p < .0001), as well as an average of 0.54 years of life loss at the age of 45 and 0.49 years of life loss at the age of 60, compared to those who were not exposed to any early life risk factors. Early life factors including maternal smoking, non-breastfed, low birth weight, and shorter height compared to peers at age 10 were associated with shorter TL in later life. In addition, an increased number of the aforementioned factors was associated with a greater likelihood of shorter TL in adulthood, as well as a reduced life expectancy.

The Impact of HIV and Parasite Single Infection and Coinfection on Telomere Length: A Systematic Review.

HIV and parasite infections accelerate biological aging, resulting in immune senescence, apoptosis and cellular damage. Telomere length is considered to be one of the most effective biomarkers of biological aging. HIV and parasite infection have been reported to shorten telomere length in the host. This systematic review aimed to highlight work that explored the influence of HIV and parasite single infections and coinfection on telomere length. Using specific keywords related to the topic of interest, an electronic search of several online databases (Google Scholar, Web of Science, Scopus, Science Direct and PubMed) was conducted to extract eligible articles. The association between HIV infection or parasite infection and telomere length and the association between HIV and parasite coinfection and telomere length were assessed independently. The studies reported were mostly conducted in the European countries. Of the 42 eligible research articles reviewed, HIV and parasite single infections were independently associated with telomere length shortening. Some studies found no association between antiretroviral therapy (ART) and telomere length shortening, while others found an association between ART and telomere length shortening. No studies reported on the association between HIV and parasite coinfection and telomere length. HIV and parasite infections independently accelerate telomere length shortening and biological aging. It is possible that coinfection with HIV and parasites may further accelerate telomere length shortening; however, this is a neglected field of research with no reported studies to date.

Lifestyle factors and metabolomic aging biomarkers: Meta-analysis of cross-sectional and longitudinal associations in three prospective cohorts

Biological age uses biophysiological information to capture a person’s age-related risk of adverse outcomes. MetaboAge and MetaboHealth are metabolomics-based biomarkers of biological age trained on chronological age and mortality risk, respectively. Lifestyle factors contribute to the extent chronological and biological age differ. The association of lifestyle factors with MetaboAge and MetaboHealth, potential sex differences in these associations, and MetaboAge’s and MetaboHealth’s sensitivity to lifestyle changes have not been studied yet.Linear regression analyses and mixed-effect models were used to examine the cross-sectional and longitudinal associations of scaled lifestyle factors with scaled MetaboAge and MetaboHealth in 24,332 middle-aged participants from the Doetinchem Cohort Study, Rotterdam Study, and UK Biobank. Random-effect meta-analyses were performed across cohorts. Repeated metabolomics measurements had a ten-year interval in the Doetinchem Cohort Study and a five-year interval in the UK Biobank.In the first study incorporating longitudinal information on MetaboAge and MetaboHealth, we demonstrate associations between current smoking, sleeping ≥8 hours/day, higher BMI, and larger waist circumference were associated with higher MetaboHealth, the latter two also with higher MetaboAge. Furthermore, adhering to the dietary and physical activity guidelines were inversely associated with MetaboHealth. Lastly, we observed sex differences in the associations between alcohol use and MetaboHealth.

Association between telomere length and cognitive function among cognitively unimpaired individuals at risk of Alzheimer’s disease

IntroductionLeukocyte telomere length (LTL) is an objective biomarker of biological aging, and it is proposed to play a crucial role in Alzheimer's disease (AD) risk. We aimed at evaluating the cross-sectional association between LTL and cognitive performance in middle-aged cognitively unimpaired individuals at increased risk of AD. MethodsA total of 1520 participants from the ALFA cohort were included. Relative telomere length was measured in leukocytes through qPCR. LTL was residualized against age and sex, and associations with cognitive performance were assessed in short and long groups based on residualized LTL (rLTL). Interactions with sex and genetic risk of AD were tested. ResultsNon-linear associations were found between LTL and episodic memory (EM). Better EM was associated with longer rLTL among women in the short rLTL group. DiscussionResults suggest a potential role of telomeres in the cognitive aging process with sex-specific patterns.

Genomic Frequencies of Dynamic DNA Sequences and Mammalian Lifespan.

Dynamic DNA sequences (i.e. sequences capable of forming hairpins, G-quadruplexes, i-motifs, and triple helices) can cause replication stress and associated mutations. One example of such a sequence occurs in the RACK7 gene in human DNA. Since this sequence forms i-motif structures at neutral pH that cause replication stress and result in spontaneous deletions in prostate cancer cells, our initial aim was to determine its potential utility as a biomarker of prostate cancer. We cloned and sequenced the region in RACK7 where i-motif deletions often occur in DNA obtained from eight individuals. Expressed prostatic secretions were obtained from three individuals with a positive biopsy for prostate cancer and two with individuals with a negative biopsy for prostate cancer. Peripheral blood specimens were obtained from two control healthy bone marrow donors and a marrow specimen was obtained from a third healthy marrow donor. Follow-up computer searches of the genomes of 74 mammalian species available at the NCBI ftp site or frequencies of 6 dynamic sequences known to produce mutations or replication stress using a program written in Mathematica were subsequently performed. Deletions were found in RACK7 in specimens from both older normal adults, as well as specimens from older patients with cancer, but not in the youngest normal adult. The deletions appeared to show a weak trend to increasing frequency with patient age. This suggested that endogenous mutations associated with dynamic sequences might accumulate during aging and might serve as biomarkers of biological age rather than direct biomarkers of cancer. To test that hypothesis, we asked whether or not the genomic frequencies of several dynamic sequences known to produce replication stress or mutations in human DNA were inversely correlated with maximum lifespan in mammals. Our results confirm this correlation for six dynamic sequences in 74 mammalian genomes studied, thereby suggesting that spontaneously induced replication stress and mutations linked to dynamic sequence frequency may limit lifespan by limiting genome stability.

Accelerated epigenetic age is associated with whole-brain functional connectivity and impaired cognitive performance in older adults

While chronological age is a strong predictor for health-related risk factors, it is an incomplete metric that fails to fully characterize the unique aging process of individuals with different genetic makeup, neurodevelopment, and environmental experiences. Recent advances in epigenomic array technologies have made it possible to generate DNA methylation-based biomarkers of biological aging, which may be useful in predicting a myriad of cognitive abilities and functional brain network organization across older individuals. It is currently unclear which cognitive domains are negatively correlated with epigenetic age above and beyond chronological age, and it is unknown if functional brain organization is an important mechanism for explaining these associations. In this study, individuals with accelerated epigenetic age (i.e. AgeAccelGrim) performed worse on tasks that spanned a wide variety of cognitive faculties including both fluid and crystallized intelligence (N = 103, average age = 68.98 years, 73 females, 30 males). Additionally, fMRI connectome-based predictive models suggested a mediating mechanism of functional connectivity on epigenetic age acceleration-cognition associations primarily in medial temporal lobe and limbic structures. This research highlights the important role of epigenetic aging processes on the development and maintenance of healthy cognitive capacities and function of the aging brain.

Associations among NMR-measured inflammatory and metabolic biomarkers and accelerated aging in cardiac catheterization patients.

Research into aging has grown substantially with the creation of molecular biomarkers of biological age that can be used to determine age acceleration. Concurrently, nuclear magnetic resonance (NMR) assessment of biomarkers of inflammation and metabolism provides researchers with new ways to examine intermediate risk factors for chronic disease. We used data from a cardiac catheterization cohort to examine associations between biomarkers of cardiometabolic health and accelerated aging assessed using both gene expression (Transcriptomic Age) and DNA methylation (Hannum Age, GrimAge, Horvath Age, and Phenotypic Age). Linear regression models were used to associate accelerated aging with each outcome (cardiometabolic health biomarkers) while adjusting for chronological age, sex, race, and neighborhood socioeconomic status. Our study shows a robust association between GlycA and GrimAge (5.71, 95% CI = 4.36, 7.05, P = 7.94 × 10-16), Hannum Age (1.81, 95% CI = 0.65, 2.98, P = 2.30 × 10-3), and Phenotypic Age (2.88, 95% CI = 1.91, 3.87, P = 1.21 × 10-8). We also saw inverse associations between apolipoprotein A-1 and aging biomarkers. These associations provide insight into the relationship between aging and cardiometabolic health that may be informative for vulnerable populations.

Non-neurological factors associated with serum neurofilament levels in the United States population.

To model interdependencies of serum neurofilament light chain (sNfL), a clinically useful biomarker of axonal injury in neurological diseases, with demographic, anthropometric, physiological, and disease biomarkers in the United States population. sNfL and 80 biomarkers were obtained from the National Health and Nutrition Examination Survey (n = 2071, age: 20-75 years). Body habitus and composition, electrolytes, blood cell, metabolic, liver, and kidney function biomarkers, and common diseases were assessed with weighted regression adjusted for age, sex, and race/ethnicity. Salient biomarkers were modeled with ensemble learning; a Bayesian network structure was obtained for interdependencies. Age was strongly associated with sNfL. sNfL levels were 13% higher in men versus women. Mexican Americans had 18.5% lower sNfL versus Non-Hispanic Whites. sNfL was similar in pregnant versus nonpregnant women. Lymphocyte, and neutrophil numbers, and phosphorus, and chloride levels were associated with sNfL. Multiple liver function (e.g., albumin and gamma-glutamyltransferase), renal function (e.g., creatinine and urea), and carbohydrate/lipid metabolism markers (e.g., glucose and triglycerides) were associated with sNfL. A 50% greater creatinine was associated with 26.8% greater sNfL. Diabetes, kidney disease, congestive heart failure, and stroke were associated with sNfL. The ensemble learning algorithm predicted high sNfL outliers with 5.06%-9.16% test error. Bayesian network modeling indicated sNfL had neighbor dependencies with age, creatinine, albumin, and chloride. sNfL is associated with age, kidney and liver function, diabetes, blood cell subsets, and electrolytes. sNfL may be a useful biomarker for biological age of the whole body and major organ systems including the brain.

Fasting-mimicking diet causes hepatic and blood markers changes indicating reduced biological age and disease risk

In mice, periodic cycles of a fasting mimicking diet (FMD) protect normal cells while killing damaged cells including cancer and autoimmune cells, reduce inflammation, promote multi-system regeneration, and extend longevity. Here, we performed secondary and exploratory analysis of blood samples from a randomized clinical trial (NCT02158897) and show that 3 FMD cycles in adult study participants are associated with reduced insulin resistance and other pre-diabetes markers, lower hepatic fat (as determined by magnetic resonance imaging) and increased lymphoid to myeloid ratio: an indicator of immune system age. Based on a validated measure of biological age predictive of morbidity and mortality, 3 FMD cycles were associated with a decrease of 2.5 years in median biological age, independent of weight loss. Nearly identical findings resulted from a second clinical study (NCT04150159). Together these results provide initial support for beneficial effects of the FMD on multiple cardiometabolic risk factors and biomarkers of biological age.