Biological Age Acceleration Research Articles

Painful diabetic neuropathy is associated with accelerated epigenetic aging.

About one out of two diabetic patients develop diabetic neuropathy (DN), of these 20% experience neuropathic pain (NP) leading to individual, social, and health-economic burden. Risk factors for NP are largely unknown; however, premature aging was recently associated with several chronic pain disorders. DNA methylation-based biological age (DNAm) is associated with disease risk, morbidity, and mortality in different clinical settings. The purpose of this work was to study, for the first time, whether biological age is involved in pain development in a huge cohort of DN patients with neuropathy assessed by anatomopathological assay (99 painful (PDN), 132 painless (PLDN) patients, 84 controls (CTRL)). Six subsets of DNAm biomarkers were calculated to evaluate NP-associated changes in epigenetic aging, telomere shortening, blood cell count estimates, and plasma protein surrogates. We observed pain-related acceleration of epigenetic age (DNAmAgeHannum, DNAmGrimAgeBasedOnPredictedAge, DNAmAgeSkinBloodClock), pace of aging (DunedinPoAm), and shortening of telomeres between PDN and PLDN patients. PDN showed decreased predicted counts of B lymphocytes, naive and absolute CD8 T cells, and increased granulocyte counts. Several surrogates of plasma proteins were significantly different (GHR, MMP1, THBS2, PAPPA, TGF-α, GDF8, EDA, MPL, CCL21) in PDNs compared to PLDNs. These results provide the first evidence of an acceleration of biological aging in patients with painful compared to painless DN. This achievement has been possible thanks to the state of the art clinical phenotyping of the enrolled patients. Our findings indicate that the aging process may be directly involved in the PDN progression and in general health degeneration in the T2DM patients. Therefore, it is possible to hypothesize that the administration of effective antiaging drugs could slow down or even block the disease advancement.

Epigenetic age acceleration and methylation differences in IgG4-related cholangitis and primary sclerosing cholangitis

BackgroundIgG4-related cholangitis (IgG4-SC) and primary sclerosing cholangitis (PSC) are chronic fibro-inflammatory hepatobiliary conditions, with genetic, environmental, and immunologic risk factors, in which epigenetic alterations may provide insights into pathophysiology and novel biomarkers. This study is the first to assess methylation signatures in IgG4-SC.ResultsWhole blood DNA methylation profiling and genotyping was performed in 264 individuals; 47 with IgG4-SC, 65 with PSC, 64 with ulcerative colitis (UC), and 88 healthy controls. We identified 19 significant methylation differences between IgG4-SC and controls and 38 between PSC and controls. IgG4-SC and PSC shared 8 probes. Inflammatory genes (including CEP97, IFNAR1, TXK, HERC6, C5orf36, PYY, and MTRNR2L1) were predominantly involved in dysregulated methylation. Epigenetic age acceleration was observed in patients with IgG4-SC, but not in those with PSC or UC. meQTL analyses to identify genetic determinants of methylation revealed a strong human leucocyte antigen (HLA) signal in both PSC and IgG4-SC (HLA-DQB2, HLA-DPA1, HLA-F and HLA-DRA).ConclusionsWe identify novel epigenetic alterations in IgG4-SC and PSC, with biological age acceleration in IgG4-SC, providing insights into disease pathogenesis, and highlight the role of genetic variation especially within the HLA region in shaping the methylome.

Cell-type specific epigenetic clocks to quantify biological age at cell-type resolution.

The ability to accurately quantify biological age could help monitor and control healthy aging. Epigenetic clocks have emerged as promising tools for estimating biological age, yet they have been developed from heterogeneous bulk tissues, and are thus composites of two aging processes, one reflecting the change of cell-type composition with age and another reflecting the aging of individual cell-types. There is thus a need to dissect and quantify these two components of epigenetic clocks, and to develop epigenetic clocks that can yield biological age estimates at cell-type resolution. Here we demonstrate that in blood and brain, approximately 39% and 12% of an epigenetic clock's accuracy is driven by underlying shifts in lymphocyte and neuronal subsets, respectively. Using brain and liver tissue as prototypes, we build and validate neuron and hepatocyte specific DNA methylation clocks, and demonstrate that these cell-type specific clocks yield improved estimates of chronological age in the corresponding cell and tissue-types. We find that neuron and glia specific clocks display biological age acceleration in Alzheimer's Disease with the effect being strongest for glia in the temporal lobe. Moreover, CpGs from these clocks display a small but significant overlap with the causal DamAge-clock, mapping to key genes implicated in neurodegeneration. The hepatocyte clock is found accelerated in liver under various pathological conditions. In contrast, non-cell-type specific clocks do not display biological age-acceleration, or only do so marginally. In summary, this work highlights the importance of dissecting epigenetic clocks and quantifying biological age at cell-type resolution.

Inflammaging Markers in the Extremely Cold Climate: A Case Study of Yakutian Population.

Yakutia is one of the coldest permanently inhabited regions in the world, characterized by a subarctic climate with average January temperatures near -40 °C and the minimum below -60 °C. Recently, we demonstrated accelerated epigenetic aging of the Yakutian population in comparison to their Central Russian counterparts, residing in a considerably milder climate. In this paper, we analyzed these cohorts from the inflammaging perspective and addressed two hypotheses: a mismatch in the immunological profiles and accelerated inflammatory aging in Yakuts. We found that the levels of 17 cytokines displayed statistically significant differences in the mean values between the groups (with minimal p-value = 2.06 × 10-19), and 6 of them are among 10 SImAge markers. We demonstrated that five out of these six markers (PDGFB, CD40LG, VEGFA, PDGFA, and CXCL10) had higher mean levels in the Yakutian cohort, and therefore, due to their positive chronological age correlation, might indicate a trend toward accelerated inflammatory aging. At the same time, a statistically significant biological age acceleration difference between the two cohorts according to the inflammatory SImAge clock was not detected because they had similar levels of CXCL9, CCL22, and IL6, the top contributing biomarkers to SImAge. We introduced an explainable deep neural network to separate individual inflammatory profiles between the two groups, resulting in over 95% accuracy. The obtained results allow for hypothesizing the specificity of cytokine and chemokine profiles among people living in extremely cold climates, possibly reflecting the effects of long-term human (dis)adaptation to cold conditions related to inflammaging and the risk of developing a number of pathologies.

Associations of combined accelerated biological aging and genetic susceptibility with incidence of heart failure in a population-based cohort study.

The global aging population raises concerns about heart failure (HF), yet its association with accelerated biological age (BA) remains inadequately understood. We aimed to examine the longitudinal association between BA acceleration and incident HF risk, assess its modifying effect on genetic susceptibility, and how much BA acceleration mediates the impact of modifiable health behaviors on incident HF. We analyzed 274,608 UK Biobank participants without HF at baseline. Two BA accelerations (Biological Age Acceleration [BioAgeAccel] and Phenotypic Age Acceleration [PhenoAgeAccel]) were calculated by regressing clinical biomarker-based BA on chronological age, with higher values indicating accelerated aging. Health behavior scores were computed based on diet, physical activity, tobacco/nicotine, sleep, and BMI. Genetic risk scores (GRS) were calculated by 12 HF-associated loci. During a median follow-up of 13.5 years, 8915 HF cases were documented. Each standard deviation increase in BioAgeAccel and PhenoAgeAccel was associated with an increased incident HF risk, yielding HRs of 1.45 (95% CI, 1.42-1.48) and 1.42 (95% CI, 1.40-1.45), respectively. Participants with high GRS and highest quartile of BioAgeAccel had an HR of 2.69 (95% CI, 2.42-2.99), and for PhenoAgeAccel, an HR of 2.83 (95% CI, 2.52-3.18), compared to those with low GRS, and lowest quartile. Additive interactions were observed between GRS and BA accelerations. Health behaviors reduced HF risk, with 21.1% (95% CI, 19.5%-22.8%) mediated by decreased BioAgeAccel and 20.9% (95% CI, 19.5%-22.6%) by decreased PhenoAgeAccel. Accelerated BA is associated with an increased incident HF risk, with an additive effect when combined with genetic susceptibility. Maintaining health behaviors may help mitigate BA aging and reduce HF risk.

Biological Age Acceleration and Colonic Polyps in Persons under Age 50.

Epigenetic clocks can quantify DNA methylation by measuring the methylation levels at specific sites in the genome, which correlate with biological age (BA). Accelerated aging, where BA exceeds chronologic age, has been studied in relation to cancer development, but its utility in cancer prevention remains unclear. Accelerated aging holds promise as a tool to explain the increase in early-onset colorectal cancer (EOCRC). We investigate the association of accelerated aging and the presence of preneoplastic polyps (PNP) in the colon, defined as tubular adenomas and sessile serrated adenomas. In this study of persons under age 50 undergoing colonoscopy, we used peripheral blood samples to determine BA and age acceleration metrics. Age acceleration was determined by interrogating DNA methylation at specific CpG sites across the genome, which has been shown to correlate with age. We then conducted logistic regression analyses to evaluate the association between age acceleration and PNPs. In total, 51 patient samples were evaluated. We found that that the odds of harboring a PNP are 16% higher with 1 year of accelerated aging, as measured by GrimAge. However, the strongest risk factor for PNPs remained male sex. This represents one of the first studies to explore accelerated aging and PNP in patients under the age of 50. A risk-stratified approach to EOCRC screening would minimize unnecessary colonoscopies and minimize healthcare burden while addressing the increase in EOCRC. Our findings suggest that BA calculations with peripheral blood collections could be an important component of such a risk model. Prevention Relevance: Understanding the association of accelerated aging and colorectal PNPs presents an opportunity to develop a risk-stratified approach to colorectal cancer screening in young persons.

Associations between dietary carotenoid and biological age acceleration: insights from NHANES 2009-2018.

Carotenoids are naturally occurring pigments found in plants and certain microorganisms. Some carotenoids act as precursors to vitamin A, which is essential for various health aspects, including vision, immune function, and skin health. Carotenoids, including α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin, are known to reduce the risk of age-related diseases and promote healthy aging. This study examines the relationship between dietary carotenoid levels and biological age. This study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2009 to 2018, and 19,280 participants were included. The Phenotypic Age (PhenoAge) was used to measure biological age, and the Klemera-Doubal Method (KDM) was employed in sensitivity analyses. Biological age acceleration was determined by calculating the residuals of PhenoAge or KDM after regressing them against chronological age. Weighted multivariate linear and logistic regressions were conducted to examine the relationship between carotenoids and biological age acceleration. Additionally, restricted cubic spline regression, subgroup analysis, interaction analysis, and sensitivity analyses were employed for further examination. Both linear regression and logistic regression analyses indicated that participants with higher carotenoid intake exhibited lower rates of phenotypic age acceleration, with α-carotene, β-carotene, β-cryptoxanthin, lutein and zeaxanthin, and lycopene all demonstrating protective effects. Restricted cubic spline regression indicates non-linear associations between carotenoid levels and phenotypic age acceleration. Subgroup analyses revealed that younger participants, females, and individuals with hypertension or diabetes benefited more from higher carotenoid intake. Sensitivity analyses further confirmed the robustness of inverse relationship. The WQS analysis identifies β-carotene and β-cryptoxanthin as the most influential compounds. Higher dietary intake of carotenoids is associated with reduced biological age acceleration, underscoring their protective role against aging. Further longitudinal studies are needed to establish causal relationships and explore the underlying mechanisms of carotenoid benefits on aging.

Accelerated biological aging, healthy behaviors, and genetic susceptibility with incidence of stroke and its subtypes: A prospective cohort study.

Stroke risk increases with chronological age, but the relationship with biological age (BA) acceleration is poorly understood. We aimed to examine the association between BA acceleration and incident stroke and its subtypes, explore the modifying effects on genetic susceptibility, and assess how BA acceleration mediates the effect of behavior score. We studied 253,932 UK Biobank participants and computed two BA measures (Klemera-Doubal Method [KDM], Phenotypic Age [PhenoAge]), with BA acceleration calculated by regressing BA on chronological age. The polygenic risk score (PRS) was derived from 87 genetic loci. The behaviors score was based on diet, physical activity, tobacco/nicotine, sleep, and BMI. During a median follow-up of 13.6 years, 5460 strokes, 4337 ischemic stroke (IS), 951 intracerebral hemorrhage (ICH), and 553 subarachnoid hemorrhage (SAH) cases were documented. Adjusting for confounding factors, each standard deviation increase in BA acceleration was associated with higher stroke risk: for KDM-BA acceleration, stroke (HR = 1.28, 95% CI = 1.25-1.32), IS (1.32, 1.28-1.36), ICH (1.15, 1.08-1.23), and SAH (1.16, 1.07-1.27); for PhenoAge acceleration, stroke (1.22, 1.19-1.25), IS (1.26, 1.22-1.29), ICH (1.08, 1.02-1.16), and SAH (1.08, 1.00-1.18). Compared to participants with the lowest PRS and BA acceleration, those with the highest PRS and BA acceleration had the highest stroke risk (KDM-BA acceleration: 2.19, 1.85-2.59; PhenoAge acceleration: 2.03, 1.69-2.42). Additionally, there was an additive interaction between KDM-BA acceleration and PRS. The mediation proportion of BA acceleration in associations of behaviors score with incident stroke and its subtypes ranged from 15.84% to 33.08%. BA acceleration may raise stroke risk, especially in those with high genetic risk. Maintaining healthy behaviors may help mitigate this risk.

Association of early-life factors with biological age acceleration and the mediating effect of social environment risks in middle-aged and older adults.

Adverse early-life events influence the health with ageing throughout the life course. However, the effects of combined early-life risks on ageing acceleration in adults and the roles of social environment risks remain unknown. To investigate associations of maternal smoking, breastfeeding and birth weight with accelerated biological age (BA), and to explore genetic-predicted effect and mediating effect of social environment risks. Population-based prospective cohort. UK Biobank. 151773 participants. We used Klemera-Doubal BA (KDM-BA), PhenoAge and leukocyte telomere length (LTL) as BA biomarkers. Associations of early-life risk factors and score with BA acceleration were estimated using linear regression models. Genetic risk score (GRS) was calculated based on genetic variations for maternal smoking and birth weight. Polysocial risk scores (PsRS) for each BA were calculated by summing the number of dichotomised social environment factors significantly associated with each of the three BA biomarkers. Maternal smoking, non-breastfeeding and low birth weight were individually associated with BA acceleration. The early-life risk score was significantly associated with accelerated KDM-BA and PhenoAge and shorter LTL. The effects of GRS on accelerated BA were in the same direction. The BA-specific PsRS mediated the accelerated KDM-BA and PhenoAge and shorter LTL by 8.37%, 22.34% and 7.90%, respectively. Our findings demonstrated a dose-dependent association of combined early-life risks with accelerated BA in middle-aged and older adults, partially mediated by social environment risks. The findings highlight the importance of early identification and surveillance of high-risk individuals for ageing acceleration during adulthood.

Associations between ethylene oxide exposure and biological age acceleration: evidence from NHANES 2013-2016.

Population aging is a global concern, with the World Health Organization predicting that by 2030, one in six individuals worldwide will be 60 years or older. Ethylene oxide (EO) is a widely used industrial chemical with potential health risks, including associations with age-related diseases. This study investigates the relationship between EO exposure and biological age acceleration. Data from the National Health and Nutrition Examination Survey (NHANES) 2013-2016 were analyzed, including 3,155 participants after exclusions. Blood EO levels were measured using hemoglobin adducts (HbEO). Biological age acceleration was assessed using two methods: Phenotypic Age Acceleration (PhenoAgeAccel) and Klemera-Doubal Method Age Acceleration (KDM-AA). Linear and logistic regression models were applied, adjusting for various covariates, and restricted cubic spline (RCS) regression was used to explore non-linear associations. Higher EO exposure was significantly associated with increased PhenoAgeAccel and KDM-AA across all models. In the continuous model, substantial positive associations were observed (PhenoAgeAccel: β = 0.73, p < 0.001; KDM-AA: β = 0.66, p < 0.001) in Model 3. Quintile analysis indicated a trend of increasing biological age acceleration with higher EO exposure. RCS regression demonstrated a significant linear relationship between EO exposure and PhenoAgeAccel (p for non-linearity = 0.067), as well as with KDM-AA (p for non-linearity = 0.083). Subgroup and interaction analyses revealed significant modifying effects by factors such as body mass index, gender, diabetes status, and physical activity level. Our study demonstrates a significant association between EO exposure and accelerated biological aging. These findings highlight the need for further prospective and mechanistic studies to validate and explore this phenomenon.

Parental epigenetic age acceleration and risk of adverse birth outcomes: the Norwegian mother, father and child cohort study

BackgroundFew studies have examined associations between maternal epigenetic age acceleration and adverse birth outcomes, and none have investigated paternal epigenetic age acceleration. Our objective was to assess the associations of parental (both maternal and paternal) epigenetic age acceleration in relation to birth outcomes.MethodsParental epigenetic age was estimated using seven established epigenetic clocks in 2198 mothers and 2193 fathers from the Norwegian Mother, Father, and Child Cohort Study (MoBa). Individual epigenetic age acceleration was then calculated as residuals from linear regressions of estimates from the epigenetic clocks on chronological age. Further, linear regression was used to analyze differences in continuous outcomes (gestational length and standardized birthweight), while logistic regression was used for binary outcomes (preterm birth, post-term birth, small-for-gestational age [SGA], large-for-gestational age [LGA], and pre-eclampsia), adjusting for chronological age, parity, educational level, smoking, and BMI.ResultsIncreasing maternal, but not paternal, epigenetic age acceleration was associated with decreased gestational length for five out of six clocks, with adjusted estimates ranging from a mean 0.51-day decrease (95% CI − 1.00, − 0.02; p-value 0.043) for the Horvath clock to a 0.80-day decrease (95% CI − 1.29, − 0.31; p-value 0.002) for the Levine clock. An association with increasing maternal epigenetic age acceleration according to the DunedinPACE clock was also seen with greater standardized birthweight [mean difference 0.08 (95% CI 0.04, 0.12; p-value < 0.001]. These results were also reflected in an increased risk of spontaneous preterm birth and LGA. No associations were observed with post-term birth, SGA, or pre-eclampsia.ConclusionsMaternal, but not paternal, epigenetic age acceleration is associated with shorter pregnancies and an increased risk of spontaneous preterm birth. This may suggest that women’s biological age acceleration, including factors such as metabolic and physiologic state, is an additional risk factor for preterm delivery, beyond chronological age.

Epigenetic age and long-term cancer risk following a stroke

BackgroundThe association between increased cancer risk following a cerebrovascular event (CVE) has been previously reported. We hypothesize that biological age (B-age) acceleration is involved in this association. Our study aims to examine B-age as a novel contributing factor to cancer development post-CVE.MethodsFrom our prospective stroke registry (BasicMar), we selected 940 cases with epigenetic data. For this study, we specifically analyzed 648 of these patients who had available data, no prior history of cancer, and a minimum follow-up of 3 months. The primary outcome was cancer incidence. B-age was estimated using DNA methylation data derived from whole blood samples obtained within 24 h of stroke onset, employing various epigenetic clocks (including Hannum, Horvath, PhenoAge, ZhangBLUP, ZhangEN, and the mitotic epiTOC). Extrinsic epigenetic age acceleration (EEAA) was calculated as the residuals from the regression of B-age against chronological age (C-age). For epiTOC, the age-adjusted values were obtained by regressing out the effect of age from the raw epiTOC measurements. Estimated white cell counts were derived from DNA methylation data, and these cell fractions were used to compute the intrinsic epigenetic age acceleration (IEAA). Subsequently, we evaluated the independent association between EEAA, IEAA, and cancer incidence while controlling for potential confounding variables.ResultsAmong 648 patients with a median follow-up of 8.15 years, 83 (12.8%) developed cancer. Cox multivariable analyses indicated significant associations between Hannum, Zhang, and epiTOC EEAA and the risk of cancer after CVE. After adjusting for multiple testing and competing risks, EEAA measured by Hannum clock maintained an independent association with cancer risk. Specifically, for each year increase in Hannum’s EEAA, we observed a 6.0% increased incidence of cancer (HR 1.06 [1.02–1.10], p value = 0.002).ConclusionsOur findings suggest that epigenetic accelerated aging, as indicated by Hannum’s EEAA, may play a significant role in the increased cancer risk observed in CVE survivors.

Ultra-processed food consumption is associated with the acceleration of biological aging in the Moli-sani Study

BackgroundHealthy diets have been inversely associated with biological aging. However, the nutritional content is only one aspect of the overall food health potential, and more recently, increasing attention has been paid to nonnutrient food characteristics, such as food processing. ObjectivesTo examine the association of ultra-processed food (UPF) consumption with biological aging measured by circulating blood biomarkers. MethodsCross-sectional analyses were conducted on 22,495 participants enrolled in the Moli-sani Study (2005–2010, Italy). Food intake was assessed by a 188-item food frequency questionnaire. UPF was defined according to the Nova classification and calculated as the ratio (weight ratio; %) between UPF (g/d) and total food eaten (g/d). Diet quality was assessed by the Mediterranean Diet Score (MDS; ranging 0–9). A deep neural network approach based on 36 circulating biomarkers was used to compute biological age (BA), and the resulting difference (Δage = BA − chronological age)—an index of biological aging—was tested as dependent variable in multivariable linear regression analyses including known risk factors. ResultsThe mean Δage in this population was −0.70 (standard deviation ±7.70) years. In multivariable-adjusted analyses, higher intake of UPF was associated with accelerated Δage [β = 0.34 years; 95% confidence interval (CI): 0.08, 0.61 for the last fifth compared with the first). This association was not linear (P value for overall association <0.001; P value for nonlinearity = 0.049). Inclusion of the MDS into the model slightly attenuated this association by 9.1% (β = 0.31 years; 95% CI: 0.04, 0.59). ConclusionsA diet rich in UPF was associated with an acceleration of biological aging in a large sample of Italian adults. The poor nutritional composition of highly processed foods weakly accounted for this association, suggesting that biological aging could be adversely influenced by nonnutrient characteristics of these foods.

Associations of various healthy dietary patterns with biological age acceleration and the mediating role of gut microbiota: results from the China Multi-Ethnic Cohort study.

To investigate the associations between dietary patterns and biological ageing, identify the most recommended dietary pattern for ageing and explore the potential mediating role of gut microbiota in less-developed ethnic minority regions (LEMRs). This prospective cohort study included 8288 participants aged 30-79 years from the China Multi-Ethnic Cohort study. Anthropometric measurements and clinical biomarkers were utilised to construct biological age based on Klemera and Doubal's method (KDM-BA) and KDM-BA acceleration (KDM-AA). Dietary information was obtained through the baseline FFQ. Six dietary patterns were constructed: plant-based diet index, healthful plant-based diet index, unhealthful plant-based diet index, healthy diet score, Dietary Approaches to Stop Hypertension (DASH), and alternative Mediterranean diets. Follow-up adjusted for baseline analysis assessed the associations between dietary patterns and KDM-AA. Additionally, quantile G-computation identified significant beneficial and harmful food groups. In the subsample of 764 participants, we used causal mediation model to explore the mediating role of gut microbiota in these associations. The results showed that all dietary patterns were associated with KDM-AA, with DASH exhibiting the strongest negative association (β = -0·91, 95 % CI (-1·19, -0·63)). The component analyses revealed that beneficial food groups primarily included tea and soy products, whereas harmful groups mainly comprised salt and processed vegetables. In mediation analysis, the Synergistetes and Pyramidobacter possibly mediated the negative associations between plant-based diets and KDM-AA (5·61-9·19 %). Overall, healthy dietary patterns, especially DASH, are negatively associated with biological ageing in LEMRs, indicating that Synergistetes and Pyramidobacter may be potential mediators. Developing appropriate strategies may promote healthy ageing in LEMRs.

Association of night shift work and biological ageing: the mediating role of body mass index.

We aimed to examine whether current and lifetime night shift work is associated with accelerated biological ageing and the potential role of body mass index (BMI) in mediating the association. Data were sourced from the UK Biobank cohort. This study included participants who reported detailed information on their current work schedule and had complete data to calculate PhenoAge. The outcome of interest was biological ageing, measured by PhenoAge acceleration. Multivariable linear regression models were conducted to test the relationship between night shift work and biological ageing. Mediation analyses were performed. Of the 182064 participants included, the mean age was 52.6years, and 51.1% were male. After adjustment for chronological age and sex, compared with day workers, shift workers without night shift, irregular night shift workers and permanent night shift workers were associated with 0.59-, 0.87- and 1.30-year increase in biological ageing, respectively (P for trend <.001). Considering the lifetime work schedule, participants who worked night shifts >10years and participants who worked >8 night shifts each month showed increased biological age acceleration [>10years: β = 0.54, 95% confidence interval (CI) 0.29-0.79; >8 times/month: β = 0.29, 95% CI 0.07-0.50]. The mediation analysis showed that BMI mediated the associations between night shift work and biological age acceleration by 36%-53%. We showed that night shift work was associated with accelerated biological ageing. Our findings highlight the interventions on appropriate shift work schedules and weight management in night shift workers, which may slow the biological ageing process and ultimately reduce the burden of age-related diseases.

Healthful plant-based diets are negatively associated with the rate of biological aging: A national study based on US adults

Plant-based diets are recognized for their health benefits. However, evidence on the association between plant-based diet quality and aging in the US population is limited. This study aimed to investigate the association between different plant-based diet indices, phenotypic age acceleration (PhenoAgeAccel), and biological age acceleration (BioAgeAccel). We hypothesized that healthful plant-based diets would negatively affect PhenoAgeAccel and BioAgeAccel in US adults. The cross-sectional analysis included 22,363 participants, and information was obtained from the National Health and Nutrition Examination Survey database. The quality of plant-based diet was assessed using 3 indices: overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI). Phenotypic age (PA) and biological age (BA) was calculated based on a linear combination of chronological age and 12 multi-system clinical chemistry biomarkers in accordance with the previously established method. PhenoAgeAccel and BioAgeAccel are the residuals of the PA and BA. Weighted linear regression analyses were performed to evaluate the relationships between PDI, hPDI and uPDI, and PhenoAgeAccel and BioAgeAccel. After adjusting for all covariates, we observed that a 10-unit higher PDI score was associated with 0.80 years lower PhenoAgeAccel (β: -0.80, 95% confidence interval [CI]: -0.94, -0.67), and 1.91 years lower BioAgeAccel (β: -1.91, 95% CI: -2.42,-1.40). A 10-unit higher hPDI score was associated with 0.83 years lower PhenoAgeAccel (β: -0.83, 95% CI: -0.96, -0.70), and 1.76 years lower BioAgeAccel (β: -1.76, 95% CI: -2.18, -1.34). Conversely, a 10-unit higher uPDI score was associated with 0.77 years higher PhenoAgeAccel (β: 0.77, 95% CI: 0.66, 0.89) and 1.21 years higher BioAgeAccel (β: 1.21, 95% CI: 0.80, 1.62). These findings suggest that US adults may be able to slow the aging process by increasing adherence to a healthy plant-based diet.

Optimal lifestyle patterns for delaying ageing and reducing all-cause mortality: insights from the UK Biobank

BackgroundWith the rapid aging of the global population, identifying lifestyle patterns that effectively delay aging and reduce mortality risk is of paramount importance. This study utilizes the UK Biobank to analyze the associations of the Dietary Inflammatory Index, physical activity, and sleep on biological aging and all-cause mortality.MethodsA prospective cohort study was conducted using data from over half a million UK Biobank participants. Two datasets were created by subjective and objective measurements of physical activity: the Subjective Physical Activity (SPA) and Objective Physical Activity (OPA) datasets. Lifestyle patterns, including diet habits, exercise levels, and sleep quality, were assessed within these datasets. Biological aging was quantified using validated methods, including Homeostatic Dysregulation, Klemera-Doubal Method Biological Age, Phenotypic Age, and Telomere Length. All-cause mortality data were obtained from the National Health Service. Statistical analyses included weighted linear regression and Cox proportional hazard models, adjusted for a range of covariates.ResultsThe findings indicate that, in most cases, maintaining an anti-inflammatory diet, engaging in at least moderate physical activity, and ensuring healthy sleep conditions are associated with delayed physiological aging (Cohen’s d ranging from 0.274 to 0.633) and significantly reduced risk of all-cause mortality (HR-SPA: 0.690, 95% CI: 0.538, 0.884; HR-OPA: 0.493, 95% CI: 0.293, 0.828). These effects are particularly pronounced in individuals under 60 years of age and in women. However, it was observed that the level of physical activity recommended by the World Health Organization (600 MET-minutes/week) does not achieve the optimal effect in delaying biological aging. The best effect in decelerating biological aging was seen in the high-level physical activity group (≥ 3000 MET-minutes/week). The study also highlights the potential of biological age acceleration and telomere length as biomarkers for predicting the risk of mortality.ConclusionsChoosing healthy lifestyle patterns, especially an anti-inflammatory diet, at least moderate physical activity, and healthy sleep patterns, is crucial for delaying aging and reducing mortality risk. These findings support the development of targeted interventions to improve public health outcomes. Future research should focus on objective assessments of lifestyle to further validate these associations.

Evaluating the role of biological age in osteoporosis risk among middle-aged and older adults: A nationwide perspective

ObjectivesThis study aimed to investigate the association between biological age acceleration and osteoporosis (OP) risk in middle-aged and older adults using data from the National Health and Nutrition Examination Survey (NHANES). The research focused on analyzing the relationship between two biological aging metrics, Klemera-Doubal Method Age (KDMAge) and Phenotypic Age (PhenoAge), and OP risk. MethodsThe study analyzed data from NHANES, which included 6550 participants aged 50 and above from survey cycles 2005–2010 and 2017–2018. Linear and logistic regression were used to investigate the relationship between biological age acceleration (KDMAgeAccel and PhenoAgeAccel) and OP. Subgroup analysis was performed by age, gender and other factors. Multivariable Cox regression analysis yielded Hazard Ratios (HRs) relating biological age acceleration to mortality were evaluated. The study also considered the mediating roles of body mass index (BMI). ResultsKDMAgeAccel (odds ratio [OR] = 2.34, 95 % CI, 1.72–3.18) and PhenoAgeAccel (OR = 2.03, 95 % CI, 1.48–2.78) were significantly associated with increased OP risk and reduced bone mineral density (BMD). Specifically, higher KDMAgeAccel and PhenoAgeAccel were linked to higher OP prevalence and lower BMD at multiple sites. Subgroup analyses indicated that the association between accelerated biological age acceleration and OP risk was consistent across different demographics. Mediation analysis revealed that BMI partially mediated the relationship between accelerated biological age and OP, although other mechanisms are likely involved. Statistical analysis indicated that individuals with higher biological age metrics had increased mortality risk related to OP. ConclusionThe findings suggest that accelerated biological age is a robust predictor of OP risk and related mortality. KDMAgeAccel and PhenoAgeAccel could serve as valuable biomarkers for identifying individuals at high risk for OP, guiding preventive strategies.

Periodontitis prevalence and acceleration of biological aging: Insights from NHANES 2009-2014 and Mendelian randomization study.

This study aimed to investigate the association of periodontitis with biological aging and to assess potential causality using Mendelian randomization (MR). A cross-sectional study with 9558 participants from the National Health and Nutrition Examination Survey (2009-2014) was conducted. Age acceleration (BioAgeAccel and PhenoAgeAccel) was calculated from clinical biomarkers and their discrepancies with chronological age. Two-sample MR analysis was performed using data from a large-scale genome-wide association study and UK Biobank. Periodontitis was associated with increased biological aging, with 0.57-year (95% CI: 0.28-0.86, p < .001) increases in BioAgeAccel and 0.41-year (95% CI: 0.04-0.78, p = .034) increases in PhenoAgeAccel. Subgroup analysis found significantly stronger associations in males for BioAgeAccele (PINTERACTION = .006), and pronounced associations in young adults (pinteraction = .023), individuals with normal body mass index (pinteraction = .015), and current smokers (pinteraction = .016) for PehonAgeAccel. MR analysis did not provide strong evidence for a causal effect of periodontitis on biological aging (BioAgeAccel: IVW β = 0.008, 95% CI: -0.018 to 0.034, p = .553 and PhenoAgeAccel: IVW β = 0.016, 95% CI: -0.042 to 0.074, p = .585). This study identified the association of periodontitis and its severity with accelerated aging, suggesting periodontal health could be a possible method in personalized preventive and therapeutic strategies of biological aging.

Gerotherapeutics: Aging Mechanism-based Pharmaceutical and Behavioral Interventions to Reduce Cancer Racial and Ethnic Disparities.

The central premise of this article is that a portion of the established relationships between social determinants of health and racial/ethnic disparities in cancer morbidity and mortality are mediated through differences in rates of biological aging processes. We further posit that using knowledge about aging could enable discovery and testing of new mechanism-based pharmaceutical and behavioral interventions ("gerotherapeutics") to differentially improve the health of minoritized cancer survivors and reduce cancer disparities. These hypotheses are based on evidence that lifelong differences in adverse social determinants of health contribute to disparities in rates of biological aging ("social determinants of aging"), with minoritized groups having accelerated aging (ie, a steeper slope or trajectory of biological aging over time relative to chronological age) more often than non-minoritized groups. Acceleration of biological aging can increase the risk, age of onset, aggressivity and/or stage of many adult cancers. There are also documented negative feedback loops whereby the cellular damage caused by cancer and its therapies act as drivers of additional biological aging. Together, these dynamic intersectional forces can contribute to differences in cancer outcomes between minoritized vs non-minoritized survivor populations. We highlight key targetable biological aging mechanisms with potential applications to reducing cancer disparities and discuss methodological considerations for pre-clinical and clinical testing of the impact of gerotherapeutics on cancer outcomes in minoritized populations. Ultimately, the promise of reducing cancer disparities will require broad societal policy changes that address the structural causes of accelerated biological aging and ensure equitable access to all new cancer control paradigms.