Telomere Length in a South African Population Co-Infected with HIV and Helminths.

Biological ageing refers to the gradual decrease in physiological functions, resulting in immune senescence, cellular damage and apoptosis. Telomere length is a biomarker of biological ageing. Limited studies have associated shorter telomere length with HIV and parasite single infections, with no studies reporting the association of HIV and parasite co-infection with telomere length. The study aimed to investigate whether telomere length shortening is accelerated in a South African population co-infected with HIV and helminths compared to participants singly infected with either HIV or helminths. Additionally, telomere length data were compared with participants' biochemical and full blood count parameters. A total of 200 participants were in groups of uninfected control, HIV single infection, helminth single infection and HIV and helminth co-infection groups. Relative telomere length (RTL) was determined using Real-Time PCR and associated with biochemical and full blood count parameters using multivariate regression analysis models that were adjusted for confounders. The uninfected control group was used as a reference group. The uninfected control group had the highest mean RTL (1.21 ± 0.53) while the HIV-infected (0.96 ± 0.42) and co-infected (0.93 ± 0.41) groups had similar RTLs, and lastly, the helminth-infected group (0.83 ± 0.33) had the lowest RTL (p = 0.0002). When compared to the uninfected control group, a significant association between RTL and biochemical parameters, including blood iron (ß = -0.48), ferritin (ß = -0.48), transferrin saturation (ß = -0.57), transferrin (ß = -0.57), phosphate (ß = -0.47), vitamin A (ß = -0.49) and C-reactive protein (ß = -0.52) were noted in the co-infected group (p < 0.05). In addition, a significant association between RTL and full blood count, including (ß = -0.47), haematocrit (ß = -0.46), mean corpuscular volume (ß = -0.47), lymphocytes (ß = -0.45), mean corpuscular haemoglobin concentration (ß = -0.45), red cell distribution width (ß = -0.47), monocytes (ß = -0.45), eosinophils (ß = -0.45), basophils (ß = -0.44) and transferrin saturation (ß = -0.57) were also noted in the co-infected group (p < 0.05). Accelerated biological ageing, as indicated by telomere length shortening, is associated with HIV and helminth co-infections.

Biological aging mediates the associations of metabolic score for insulin resistance with all-cause and cardiovascular disease mortality among US adults: A nationwide cohort study.

AIM: To investigate the associations of metabolic score for insulin resistance (METS-IR) with all-cause and cardiovascular disease (CVD)-specific mortality and the potential mediating role of biological ageing. METHODS: A cohort of 19 204 participants from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 was recruited for this study. Cox regression models, restricted cubic splines, and Kaplan-Meier survival curves were used to determine the relationships of METS-IR with all-cause and CVD-specific mortality. Mediation analyses were performed to explore the possible intermediary role of biological ageing markers, including phenotypic age (PhenoAge) and biological age (BioAge). RESULTS: During a median follow-up of 9.17 years, we observed 2818 deaths, of which 875 were CVD-specific. Multivariable Cox regression showed that the highest METS-IR level (Q4) was associated with increased all-cause (hazard ratio [HR] 1.38, 95% confidence interval [CI] 1.14-1.67) and CVD mortality (HR 1.52, 95% CI 1.10-2.12) compared with the Q1 level. Restricted cubic splines showed a nonlinear relationship between METS-IR and all-cause mortality. Only METS-IR above the threshold (41.02 µg/L) was positively correlated with all-cause death. METS-IR had a linear positive relationship with CVD mortality. In mediation analyses, we found that PhenoAge mediated 51.32% (p < 0.001) and 41.77% (p < 0.001) of the association between METS-IR and all-cause and CVD-specific mortality, respectively. For BioAge, the mediating proportions of PhenoAge were 21.33% (p < 0.001) and 15.88% (p < 0.001), respectively. CONCLUSIONS: This study highlights the detrimental effects of insulin resistance, as measured by METS-IR, on all-cause and CVD mortality. Moreover, it underscores the role of biological ageing in mediating these associations, emphasizing the need for interventions targeting both insulin resistance and ageing processes to mitigate mortality risks in metabolic disorders.

Advanced biological ageing predicts future risk for neurological diagnoses and clinical examination findings.

Age is a dominant risk factor for some of the most common neurological diseases. Biological ageing encompasses interindividual variation in the rate of ageing and can be calculated from clinical biomarkers or DNA methylation data amongst other approaches. Here, we tested the hypothesis that a biological age greater than one's chronological age affects the risk of future neurological diagnosis and the development of abnormal signs on clinical examination. We analysed data from the Swedish Adoption/Twin Study of Aging (SATSA): a cohort with 3175 assessments of 802 individuals followed-up over several decades. Six measures of biological ageing were generated: two physiological ages (created from bedside clinical measurements and standard blood tests) and four blood methylation age measures. Their effects on future stroke, dementia or Parkinson's disease diagnosis, or development of abnormal clinical signs, were determined using survival analysis, with and without stratification by twin pairs. Older physiological ages were associated with ischaemic stroke risk; for example one standard deviation advancement in baseline PhenoAgePhys or KDMAgePhys residual increased future ischaemic stroke risk by 29.2% [hazard ratio (HR): 1.29, 95% confidence interval (CI) 1.06-1.58, P = 0.012] and 42.9% (HR 1.43, CI 1.18-1.73, P = 3.1 × 10-4), respectively. In contrast, older methylation ages were more predictive of future dementia risk, which was increased by 29.7% (HR 1.30, CI 1.07-1.57, P = 0.007) per standard deviation advancement in HorvathAgeMeth. Older physiological ages were also positively associated with future development of abnormal patellar or pupillary reflexes, and the loss of normal gait. Measures of biological ageing can predict clinically relevant pathology of the nervous system independent of chronological age. This may help to explain variability in disease risk between individuals of the same age and strengthens the case for trials of geroprotective interventions for people with neurological disorders.

Identifying the relation between food groups and biological ageing: a data-driven approach.

BACKGROUND: Heterogeneity in ageing rates drives the need for research into lifestyle secrets of successful agers. Biological age, predicted by epigenetic clocks, has been shown to be a more reliable measure of ageing than chronological age. Dietary habits are known to affect the ageing process. However, much remains to be learnt about specific dietary habits that may directly affect the biological process of ageing. OBJECTIVE: To identify food groups that are directly related to biological ageing, using Copula Graphical Models. METHODS: We performed a preregistered analysis of 3,990 postmenopausal women from the Women's Health Initiative, based in North America. Biological age acceleration was calculated by the epigenetic clock PhenoAge using whole-blood DNA methylation. Copula Graphical Modelling, a powerful data-driven exploratory tool, was used to examine relations between food groups and biological ageing whilst adjusting for an extensive amount of confounders. Two food group-age acceleration networks were established: one based on the MyPyramid food grouping system and another based on item-level food group data. RESULTS: Intake of eggs, organ meat, sausages, cheese, legumes, starchy vegetables, added sugar and lunch meat was associated with biological age acceleration, whereas intake of peaches/nectarines/plums, poultry, nuts, discretionary oil and solid fat was associated with decelerated ageing. CONCLUSION: We identified several associations between specific food groups and biological ageing. These findings pave the way for subsequent studies to ascertain causality and magnitude of these relationships, thereby improving the understanding of biological mechanisms underlying the interplay between food groups and biological ageing.

Association between biological ageing and periodontitis: Evidence from a cross-sectional survey and multi-omics Mendelian randomization analysis.

AIM: To investigate the relationship and potential causality between biological ageing and periodontitis. MATERIALS AND METHODS: We obtained the National Health and Nutrition Examination Survey (NHANES) and genome-wide association study (GWAS) summary statistics as well as single-cell sequencing data. Multivariate regression analysis based on cross-sectional data, Mendelian randomization (MR) and multi-omics integration analysis were employed to explore the causal association and potential molecular mechanisms between biological ageing and periodontitis. Additionally, two-step MR mediation analysis explored the risk factors in biological ageing-mediated periodontitis. RESULTS: We analysed data from 3189 participants in the NHANES data and found that higher biological age was associated with increased risk of periodontitis. MR analyses revealed causal associations between biological age measures and periodontitis risk. Frailty (odds ratio [OR] = 2.08, 95% confidence interval [CI]: 1.04-4.18, p = .039) and GrimAge acceleration (OR = 1.16, 95% CI: 1.01-1.32, p = .033) were causally associated with periodontitis risk, and these results were validated in a large-scale meta-periodontitis GWAS dataset. Additionally, the risk effects of body mass index, waist circumference and lifetime smoking on periodontitis were partially mediated by frailty and GrimAge acceleration. CONCLUSIONS: Evidence from cross-sectional survey and MR analysis suggests that biological ageing increases the risk of periodontitis. Additionally, improving the associated risk factors can help prevent both ageing and periodontitis.

Association between life's essential 8 and biological ageing among US adults.

BACKGROUND: Biological ageing is tightly linked to cardiovascular disease (CVD). We aimed to investigate the relationship between Life's Essential 8 (LE8), a currently updated measure of cardiovascular health (CVH), and biological ageing. METHODS: This cross-sectional study selected adults ≥ 20 years of age from the 2005-2010 National Health and Nutrition Examination Survey. LE8 scores (range 0-100) were obtained from measurements based on American Heart Association definitions, divided into health behavior and health factor scores. Biological ageing was assessed by different methods including phenotypic age, phenotypic age acceleration (PhenoAgeAccel), biological age and biological age acceleration (BioAgeAccel). Correlations were analyzed by weighted linear regression and restricted cubic spline models. RESULTS: Of the 11,729 participants included, the mean age was 47.41 ± 0.36 years and 5983 (51.01%) were female. The mean phenotypic and biological ages were 42.96 ± 0.41 and 46.75 ± 0.39 years, respectively, and the mean LE8 score was 67.71 ± 0.35. After adjusting for potential confounders, higher LE8 scores were associated with lower phenotypic age, biological age, PhenoAgeAccel, and BioAgeAccel, with nonlinear dose-response relationships. Negative associations were also found between health behavior and health factor scores and biological ageing, and were stronger for health factors. In health factor-specific analyses, the ß negativity was greater for blood glucose and blood pressure. The inverse correlations of LE8 scores with phenotypic age and biological age in the stratified analyses remained solid across strata. CONCLUSIONS: LE8 and its subscale scores were strongly negatively related to biological ageing. Encouraging optimal CVH levels may be advantageous in preventing and slowing down ageing.

Investigating three ways of measuring the intrinsic capacity domain of vitality: nutritional status, handgrip strength and ageing biomarkers.

BACKGROUND: Vitality is conceptually considered as the underlying capacity influencing other intrinsic capacity (IC) domains and being related to nutrition, physiological reserve and biological ageing. However, there is no consensus on its operationalisation. OBJECTIVE: To investigate the structure and magnitude of the association of vitality with other IC domains and functional difficulties using three operational definitions of vitality. METHODS: We included 1,389 older adults from the Multidomain Alzheimer Preventive Trial with data on Mini Nutritional Assessment (MNA), handgrip strength and plasma biomarkers (comprising inflammatory and mitochondrial markers). Using path analysis, we examined the effects of vitality on difficulties in basic and instrumental activities of daily living (ADL and IADL) exerted directly and indirectly through the mediation of other IC domains: cognition, locomotion, psychological, vision and hearing. We further explored the longitudinal association of vitality with IC domains, ADL and IADL over 4 years using linear mixed-effect regression. RESULTS: We observed significant indirect effects of vitality on IADL, mainly through cognitive, locomotor and psychological domains, regardless of the vitality measurement. Participants with higher vitality had fewer IADL difficulties at follow-up (MNA score: ß [95% CI] = -0.020 [-0.037, -0.003]; handgrip strength: -0.011 [-0.023, 0.000]; plasma biomarker-based index: -0.015 [-0.028, -0.002]). Vitality assessed with the plasma biomarker-based index predicted improved locomotion over time. CONCLUSION: Vitality was associated with disability primarily through the mediation of other IC domains. The three indicators examined are acceptable measurements of vitality; biomarkers might be more suitable for the early detection of locomotion decline.

Biological ageing and the risk of decreased handgrip strength among community-dwelling older adult Indians: a cross-sectional study.

BACKGROUND: Evidence from the literature demonstrates that the risk of decreased handgrip strength is associated with various health issues, particularly in older persons. To make judgments regarding their general health condition that are well-informed for longevity, it is crucial to assess the risk level of decreased handgrip strength among community-dwelling older adult Indians. However, no study has examined the relationship between biological aging and the risk of decreased handgrip strength in Indian men and women aged 60 and older. The goal of the current study was to fill this gap in the literature. METHODS: In this cross-sectional study, we included 31,464 (15,098 men and 16,366 women) community-dwelling older adult Indians aged 60 years and older using data from the Longitudinal Aging Study in India (LASI). The LASI is the world's most extensive and India's first multidisciplinary, internationally harmonized, longitudinal aging study. It has enrolled 72,250 individuals aged 45 and above across all 28 states and 8 union territories of India. Secondary analysis of biological ageing was performed by stratifying for age groups (60-64, 65-69, 70-74, 75-79, 80-84, and 85 + years) for both genders. The dominant right and nondominant left handgrip strength was assessed using the portable Smedley's Hand Dynamometer. All individuals had a dominant right hand. The adjusted logistic regression analysis assessed the association between biological ageing and the risk of decreased handgrip strength for both genders. RESULTS: Compared to those between the ages of 60-64, those at age 65 and those aged 85 and above had 1-fold and 12-fold odds of decreasing handgrip strength, respectively. Men 85 years or older had a 12-fold higher chance than women in the same age group of having decreased handgrip strength. CONCLUSIONS: The results indicate that community-dwelling older adult Indians aged 65 years and older are significantly associated with a higher risk of decreased handgrip strength, especially among older men. The results of this study can help assess and implement handgrip strength measurement in medicine for older Indians as part of regular admission assessment, particularly for older men.

Single- and combined-phthalate exposures are associated with biological ageing among adults.

BACKGROUND: Previous research has emphasized the effects of lifestyle and genetics on ageing. However, the association between exposure to phthalates, which are extensively used in cosmetics and personal care products, and ageing is still unclear. METHOD: Data for 4711 subjects from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2010 were incorporated in the present study. The acceleration of the Klemera-Doubal method-biological age (KDM-BA) and phenotypic Age (PhenoAge) were measured by the composite of 13 biomarkers. Multiple-linear and weighted-quantile sum (WQS) regression models were constructed to explore the relationships of single- and combined-phthalate exposures, as indicated by urinary phthalate metabolites, with KDM-BA and PhenoAge. A generalized additive model (GAM) was fitted to explore the potential nonlinear relationships among the above variables. RESULTS: Except for mono-(carboxynonyl), all urinary phthalate metabolites were associated with biological ageing, with correlation coefficients ranging from 0.241 to 0.526; however, mono-ethyl presented a negative correlation. The WQS models revealed mixed effects of combined urinary phthalate metabolites on ageing, with a 0.22-year ((95 % CI) 0.09, 0.32) increase in KDM-BA acceleration and a 0.27-year ((95 % CI) 0.13, 0.37) increase in PhenoAge acceleration for each decile increase in urinary phthalate metabolites. Moreover, MCPP, MEOHP, and MBzP seemed to be the top three phthalates in terms of biological ageing, with weights of 33.3 % and 32.2 %, 29.2 % and 17.2 %, and 21.5 % and 30.1 % in KDM-BA and PhenoAge acceleration, respectively. CONCLUSION: Single-phthalate exposure was mostly associated with the ageing process, and combined-phthalate exposure presented mixed effects on biological ageing, emphasizing phthalate exposure as a significant risk factor for ageing.

A healthy lifestyle is positively associated with mental health and well-being and core markers in ageing.

BACKGROUND: Studies often evaluate mental health and well-being in association with individual health behaviours although evaluating multiple health behaviours that co-occur in real life may reveal important insights into the overall association. Also, the underlying pathways of how lifestyle might affect our health are still under debate. Here, we studied the mediation of different health behaviours or lifestyle factors on mental health and its effect on core markers of ageing: telomere length (TL) and mitochondrial DNA content (mtDNAc). METHODS: In this study, 6054 adults from the 2018 Belgian Health Interview Survey (BHIS) were included. Mental health and well-being outcomes included psychological and severe psychological distress, vitality, life satisfaction, self-perceived health, depressive and generalised anxiety disorder and suicidal ideation. A lifestyle score integrating diet, physical activity, smoking status, alcohol consumption and BMI was created and validated. On a subset of 739 participants, leucocyte TL and mtDNAc were assessed using qPCR. Generalised linear mixed models were used while adjusting for a priori chosen covariates. RESULTS: The average age (SD) of the study population was 49.9 (17.5) years, and 48.8% were men. A one-point increment in the lifestyle score was associated with lower odds (ranging from 0.56 to 0.74) for all studied mental health outcomes and with a 1.74% (95% CI: 0.11, 3.40%) longer TL and 4.07% (95% CI: 2.01, 6.17%) higher mtDNAc. Psychological distress and suicidal ideation were associated with a lower mtDNAc of - 4.62% (95% CI: - 8.85, - 0.20%) and - 7.83% (95% CI: - 14.77, - 0.34%), respectively. No associations were found between mental health and TL. CONCLUSIONS: In this large-scale study, we showed the positive association between a healthy lifestyle and both biological ageing and different dimensions of mental health and well-being. We also indicated that living a healthy lifestyle contributes to more favourable biological ageing.

Exploring domains, clinical implications and environmental associations of a deep learning marker of biological ageing.

Deep Neural Networks (DNN) have been recently developed for the estimation of Biological Age (BA), the hypothetical underlying age of an organism, which can differ from its chronological age (CA). Although promising, these population-specific algorithms warrant further characterization and validation, since their biological, clinical and environmental correlates remain largely unexplored. Here, an accurate DNN was trained to compute BA based on 36 circulating biomarkers in an Italian population (N = 23,858; age ≥ 35 years; 51.7% women). This estimate was heavily influenced by markers of metabolic, heart, kidney and liver function. The resulting Δage (BA-CA) significantly predicted mortality and hospitalization risk for all and specific causes. Slowed biological aging (Δage < 0) was associated with higher physical and mental wellbeing, healthy lifestyles (e.g. adherence to Mediterranean diet) and higher socioeconomic status (educational attainment, household income and occupational status), while accelerated aging (Δage > 0) was associated with smoking and obesity. Together, lifestyles and socioeconomic variables explained ~48% of the total variance in Δage, potentially suggesting the existence of a genetic basis. These findings validate blood-based biological aging as a marker of public health in adult Italians and provide a robust body of knowledge on its biological architecture, clinical implications and potential environmental influences.

Serum markers of biological ageing provide long-term prediction of life expectancy-a longitudinal analysis in middle-aged and older German adults.

BACKGROUND: lifestyle behaviours and chronic co-morbidities are leading risk factors for premature mortality and collectively predict wide variability in individual life expectancy (LE). We investigated whether a pre-selected panel of five serum markers of biological ageing could improve predicting the long-term mortality risk and LE in middle-aged and older women and men. METHODS: we conducted a case-cohort study (n = 5,789 among which there were 2,571 deaths) within the European Prospective Investigation into Cancer-Heidelberg cohort, a population cohort of middle-aged and older individuals, followed over a median duration of 18 years. Gompertz models were used to compute multi-adjusted associations of growth differentiation factor-15, N-terminal pro-brain natriuretic peptide, glycated haemoglobin A1c, C-reactive protein and cystatin-C with mortality risk. Areas under estimated Gompertz survival curves were used to estimate the LE of individuals using a model with lifestyle-related risk factors only (smoking history, body mass index, waist circumference, alcohol, physical inactivity, diabetes and hypertension), or with lifestyle factors plus the ageing-related markers. RESULTS: a model including only lifestyle-related factors predicted a LE difference of 16.8 [95% confidence interval: 15.9; 19.1] years in men and 9.87 [9.20; 13.1] years in women aged ≥60 years by comparing individuals in the highest versus the lowest quintiles of estimated mortality risk. Including the ageing-related biomarkers in the model increased these differences up to 22.7 [22.3; 26.9] years in men and 14.00 [12.9; 18.2] years in women. CONCLUSIONS: serum markers of ageing are potentially strong predictors for long-term mortality risk in a general population sample of older and middle-aged individuals and may help to identify individuals at higher risk of premature death, who could benefit from interventions to prevent further ageing-related health declines.

Geriatric medicine learning objectives and entrustable professional activities in undergraduate medical curricula: a scoping review.

BACKGROUND: entrustable professional activities (EPAs) have become an important component of competency-based medical education. The aim of this study is to evaluate how geriatric medicine learning objectives are addressed by undergraduate medical curricula including EPAs. METHODS: we performed a scoping review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines to identify undergraduate medical curricula that include EPAs. A content analysis was conducted to examine how these curricula address the care of older individuals. In addition, we mapped the curricula to 19 geriatric medicine learning objectives identified from the European curriculum of undergraduate medical education. RESULTS: we found nine curricula, each containing between 4 and 16 core EPAs. In the sections describing the EPAs, three of the nine curricula specify that all core EPAs apply to all age groups including older patients, whereas the remaining six curricula either only refer to older patients in selected EPAs or not at all. Mapping revealed that some geriatric medicine learning objectives are covered by most curricula (e.g. medication use, multidisciplinary team work), whereas others are lacking in the majority (e.g. normal ageing, geriatric assessment, cognitive assessment, nutrition assessment, decision-making capacity assessment, long-term care). Three curricula cover most geriatric learning objectives by using a matrix aligning EPAs with geriatric competencies. CONCLUSIONS: geriatric learning objectives continue to be missing from undergraduate medical curricula, also from those adopting the novel approach of EPAs. However, this review also identified some curricula that might serve as models for how geriatric learning objectives can be successfully covered within future EPA frameworks.

Brain age prediction: A comparison between machine learning models using region- and voxel-based morphometric data.

Brain morphology varies across the ageing trajectory and the prediction of a person's age using brain features can aid the detection of abnormalities in the ageing process. Existing studies on such "brain age prediction" vary widely in terms of their methods and type of data, so at present the most accurate and generalisable methodological approach is unclear. Therefore, we used the UK Biobank data set (N = 10,824, age range 47-73) to compare the performance of the machine learning models support vector regression, relevance vector regression and Gaussian process regression on whole-brain region-based or voxel-based structural magnetic resonance imaging data with or without dimensionality reduction through principal component analysis. Performance was assessed in the validation set through cross-validation as well as an independent test set. The models achieved mean absolute errors between 3.7 and 4.7 years, with those trained on voxel-level data with principal component analysis performing best. Overall, we observed little difference in performance between models trained on the same data type, indicating that the type of input data had greater impact on performance than model choice. All code is provided online in the hope that this will aid future research.

Sex-specific effects of experimental ectoparasite infestation on telomere length in great tit nestlings.

Telomere length is a biomarker of biological ageing and lifespan in various vertebrate taxa. Evidence is accumulating that telomeres shorten more rapidly when an individual is exposed to environmental stressors. Parasites are potent selective agents that can cause physiological stress directly or indirectly through the activation of the host's immune system. Yet to date, empirical evidence for a role of parasites in telomere dynamics in natural populations is limited. Here, we show experimentally that exposure to ectoparasitic hen fleas (Ceratophyllus gallinae) during growth results in shorter telomeres in female, but not male, great tit (Parus major) nestlings. Females had longer telomeres than males when growing up in experimentally deparasitized nests but, likely because of the sex-specific effects of ectoparasitism on telomere length, this sexual dimorphism was absent in birds growing up in experimentally infested nests. Our results provide the first experimental evidence for a role of ectoparasitism in telomere dynamics in a natural vertebrate population, and suggest that the costs of infection manifest in sex-specific ways.

A 6-year prospective clinical cohort study on the bidirectional association between frailty and depressive disorder.

INTRODUCTION: Depressive disorder has been conceptualised as a condition of accelerated biological ageing. We operationalised a frailty index (FI) as marker for biological ageing aimed to explore the bidirectional, longitudinal association between frailty and either depressive symptoms or depressive disorder. METHODS: A cohort study with 6-year follow-up including 377 older (≥60 years) outpatients with a DSM-IV-defined depressive disorder and 132 never-depressed controls. Site visits at baseline, 2 and 6-year follow-up were conducted and included the CIDI 2.0 to assess depressive disorder and relevant covariates. Depressive symptom severity and mortality were assessed every 6 months by mail and telephone. A 41-item FI was operationalised and validated against the 6-year morality rate by Cox regression (HRFI  = 1.04 [95% CI: 1.02-1.06]). RESULTS: Cox regression showed that a higher FI was associated with a lower chance of remission among depressed patients (HRFI  = 0.98 [95% CI: 0.97-0.99]). Nonetheless, this latter effect disappeared after adjustment for baseline depressive symptom severity. Linear mixed models showed that the FI increased over time in the whole sample (B[SE] = 0.94 (0.12), p < .001) with a differential impact of depressive symptom severity and depressive disorder. Higher baseline depressive symptom severity was associated with an attenuated and depressive disorder with an accelerated increase of the FI over time. CONCLUSIONS: The sum score of depression rating scales is likely confounded by frailty. Depressive disorder, according to DSM-IV criteria, is associated with accelerated biological ageing. This argues for the development of multidisciplinary geriatric care models incorporating frailty to improve the overall outcome of late-life depression.

Early-breeding females experience greater telomere loss.

Annual reproductive success is often highest in individuals that initiate breeding early, yet relatively few individuals start breeding during this apparently optimal time. This suggests that individuals, particularly females who ultimately dictate when offspring are born, incur costs by initiating reproduction early in the season. We hypothesized that increases in the ageing rate of somatic cells may be one such cost. Telomeres, the repetitive DNA sequences on the ends of chromosomes, may be good proxies of biological wear and tear as they shorten with age and in response to stress. Using historical data from a long-term study population of dark-eyed juncos (Junco hyemalis), we found that telomere loss between years was greater in earlier breeding females, regardless of chronological age. There was no relationship between telomere loss and the annual number of eggs laid or chicks that reached independence. However, telomere loss was greater when temperatures were cooler, and cooler temperatures generally occur early in the season. This suggests that environmental conditions could be the primary cause of accelerated telomere loss in early breeders.

Healthy lifestyles reduce suPAR and mortality in a Danish general population study.

BACKGROUND: The plasma level of the inflammatory biomarker soluble urokinase plasminogen activator receptor (suPAR) is a strong predictor of disease development and premature mortality in the general population. Unhealthy lifestyle habits such as smoking or unhealthy eating is known to elevate the suPAR level. We aimed to investigate whether change in lifestyle habits impact on the suPAR level, and whether the resultant levels are associated with mortality. RESULTS: Paired suPAR measurements from baseline- and the 5-year visit of the population-based Inter99 study were compared with the habits of diet, smoking, alcohol consumption, and physical activity. Paired suPAR measurements for 3225 individuals were analyzed by linear regression, adjusted for demographics and lifestyle habits. Compared to individuals with a healthy lifestyle, an unhealthy diet, low physical activity, and daily smoking were associated with a 5.9, 12.8, and 17.6% higher 5-year suPAR, respectively. During 6.1 years of follow-up after the 5-year visit, 1.6% of those with a low suPAR (mean 2.93 ng/ml) died compared with 3.8% of individuals with a high suPAR (mean 4.73 ng/ml), P <  0.001. In Cox regression analysis, adjusted for demographics and lifestyle, the hazard ratio for mortality per 5-year suPAR doubling was 2.03 (95% CI: 1.22-3.37). CONCLUSION: Lifestyle has a considerable impact on suPAR levels; the combination of unhealthy habits was associated with 44% higher 5-year suPAR values and the 5-year suPAR was a strong predictor of mortality. We propose suPAR as a candidate biomarker for lifestyle changes as well as the subsequent risk of mortality.

Genomic signatures of adaptation to wine biological ageing conditions in biofilm-forming flor yeasts.

The molecular and evolutionary processes underlying fungal domestication remain largely unknown despite the importance of fungi to bioindustry and for comparative adaptation genomics in eukaryotes. Wine fermentation and biological ageing are performed by strains of S. cerevisiae with, respectively, pelagic fermentative growth on glucose and biofilm aerobic growth utilizing ethanol. Here, we use environmental samples of wine and flor yeasts to investigate the genomic basis of yeast adaptation to contrasted anthropogenic environments. Phylogenetic inference and population structure analysis based on single nucleotide polymorphisms revealed a group of flor yeasts separated from wine yeasts. A combination of methods revealed several highly differentiated regions between wine and flor yeasts, and analyses using codon-substitution models for detecting molecular adaptation identified sites under positive selection in the high-affinity transporter gene ZRT1. The cross-population composite likelihood ratio revealed selective sweeps at three regions, including in the hexose transporter gene HXT7, the yapsin gene YPS6 and the membrane protein coding gene MTS27. Our analyses also revealed that the biological ageing environment has led to the accumulation of numerous mutations in proteins from several networks, including Flo11 regulation and divalent metal transport. Together, our findings suggest that the tuning of FLO11 expression and zinc transport networks are a distinctive feature of the genetic changes underlying the domestication of flor yeasts. Our study highlights the multiplicity of genomic changes underlying yeast adaptation to man-made habitats and reveals that flor/wine yeast lineage can serve as a useful model for studying the genomics of adaptive divergence.

Chemotherapy-induced acceleration of DNA methylation-based biological age in breast cancer.

Breast cancer is the most common cancer diagnosed in women and is often treated with chemotherapy. Although previous studies have demonstrated increasing biological age in patients who receive chemotherapy, evaluation of this association with DNA methylation-based markers of biological ageing may provide novel insight into the role of chemotherapy on the ageing process. We therefore sought to investigate the association between chemotherapy and markers of biological ageing as estimated from DNA methylation in women with breast cancer. DNA methylation profiling was performed on peripheral blood collected from 18 patients before and after the first cycle of chemotherapy using the Infinium HumanMethylation450 BeadChip. Six markers of biological age acceleration were estimated from DNA methylation levels. Multiple linear regression analyses were performed to evaluate the association between each metric of biological age acceleration and chemotherapy. After adjusting for chronological age and race, intrinsic epigenetic age acceleration (p = 0.041), extrinsic epigenetic age acceleration (p = 0.050), PhenoAge acceleration (p = 0.001), GrimAge acceleration (p < 0.001), and DunedinPACE (p = 0.006) were significantly higher and telomere length (p = 0.027) was significantly lower following the first cycle of chemotherapy compared to before treatment initiation. These results demonstrate greater biological ageing as estimated from DNA methylation following chemotherapy in women with breast cancer. Our findings illustrate that cytotoxic therapies may modulate the ageing process among breast cancer patients and may also have implications for age-related health conditions in cancer survivors.