Ageing is one of the principal risk factors for many chronic diseases. However, there is considerable between-person variation in the rate of ageing and individual differences in their susceptibility ...to disease and death. Epigenetic mechanisms may play a role in human ageing, and DNA methylation age biomarkers may be good predictors of age-related diseases and mortality risk. The aims of this systematic review were to identify and synthesise the evidence for an association between peripherally measured DNA methylation age and longevity, age-related disease, and mortality risk.
A systematic search was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Using relevant search terms, MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsychINFO databases were searched to identify articles meeting the inclusion criteria. Studies were assessed for bias using Joanna Briggs Institute critical appraisal checklists. Data was extracted from studies measuring age acceleration as a predictor of age-related diseases, mortality or longevity, and the findings for similar outcomes compared. Using Review Manager 5.3 software, two meta-analyses (one per epigenetic clock) were conducted on studies measuring all-cause mortality.
Twenty-three relevant articles were identified, including a total of 41,607 participants. Four studies focused on ageing and longevity, 11 on age-related disease (cancer, cardiovascular disease, and dementia), and 11 on mortality. There was some, although inconsistent, evidence for an association between increased DNA methylation age and risk of disease. Meta-analyses indicated that each 5-year increase in DNA methylation age was associated an 8 to 15% increased risk of mortality.
Due to the small number of studies and heterogeneity in study design and outcomes, the association between DNA methylation age and age-related disease and longevity is inconclusive. Increased epigenetic age was associated with mortality risk, but positive publication bias needs to be considered. Further research is needed to determine the extent to which DNA methylation age can be used as a clinical biomarker.
Abstract
Background
Brain age is a biomarker that predicts chronological age using neuroimaging features. Deviations of this predicted age from chronological age is considered a sign of age-related ...brain changes, or commonly referred to as brain ageing. The aim of this systematic review is to identify and synthesize the evidence for an association between lifestyle, health factors and diseases in adult populations, with brain ageing.
Methods
This systematic review was undertaken in accordance with the PRISMA guidelines. A systematic search of Embase and Medline was conducted to identify relevant articles using search terms relating to the prediction of age from neuroimaging data or brain ageing. The tables of two recent review papers on brain ageing were also examined to identify additional articles. Studies were limited to adult humans (aged 18 years and above), from clinical or general populations. Exposures and study design of all types were also considered eligible.
Results
A systematic search identified 52 studies, which examined brain ageing in clinical and community dwelling adults (mean age between 21 to 78 years, ~ 37% were female). Most research came from studies of individuals diagnosed with schizophrenia or Alzheimer’s disease, or healthy populations that were assessed cognitively. From these studies, psychiatric and neurologic diseases were most commonly associated with accelerated brain ageing, though not all studies drew the same conclusions. Evidence for all other exposures is nascent, and relatively inconsistent. Heterogenous methodologies, or methods of outcome ascertainment, were partly accountable.
Conclusion
This systematic review summarised the current evidence for an association between genetic, lifestyle, health, or diseases and brain ageing. Overall there is good evidence to suggest schizophrenia and Alzheimer’s disease are associated with accelerated brain ageing. Evidence for all other exposures was mixed or limited. This was mostly due to a lack of independent replication, and inconsistency across studies that were primarily cross sectional in nature. Future research efforts should focus on replicating current findings, using prospective datasets.
Trial registration
A copy of the review protocol can be accessed through PROSPERO, registration number
CRD42020142817
.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Dementia can result from a number of distinct diseases with differing etiology and pathophysiology. Even within the same disease, there is considerable phenotypic heterogeneity with varying symptoms ...and disease trajectories. Dementia diagnosis is thus very complex, time-consuming, and expensive and can only be made definitively post-mortem with histopathological confirmation. These inherent difficulties combined with the overlap of some symptoms and even neuropathological features, present a challenging problem for research in the field. This has likely hampered progress in epidemiological studies of risk factors and preventative interventions, as well as genetic and biomarker research. Resource limitations in large epidemiologically studies mean that limited diagnostic criteria are often used, which can result in phenotypically heterogeneous disease states being grouped together, potentially resulting in misclassification bias. When biomarkers are identified for etiologically heterogeneous diseases, they will have low specificity for any utility in clinical practice, even if their sensitivity is high. We highlight several challenges in in the field which must be addressed for the success of future genetic and biomarker studies, and may be key to the development of the most effective treatments. As a step toward achieving this goal, defining the dementia as a biological construct based on the presence of specific pathological features, rather than clinical symptoms, will enable more precise predictive models. It has the potential to lead to the discovery of novel genetic variants, as well as the identification of individuals at heightened risk of the disease, even prior to the appearance of clinical symptoms.
Posttraumatic Stress Disorder (PTSD) could potentially increase the risk of mortality, and there is a need for a meta-analysis to quantify this association. This study aims to determine the extent to ...which PTSD is a predictor of mortality.
EMBASE, MEDLINE, and PsycINFO were searched systematically on 12th February 2020, with updated searches conducted in July 2021, and December 2022 (PROSPERO CRD42019142971). Studies involving community-dwelling participants with a diagnosis of PTSD or PTSD symptoms, and a comparator group of individuals without PTSD, and which assessed mortality risk, were included. A random-effects meta-analysis was conducted on studies reporting Odds Ratio (OR), Hazard Ratio (HR), and Risk Ratio (RR), and subgroup analysis was also performed by age, sex, type of trauma experienced, PTSD diagnosis, and cause of death.
A total of 30 eligible studies of mostly good methodological quality were identified, with a total of more than 2.1 million participants with PTSD. The majority of studies involved male-dominated, veteran populations. PTSD was associated with a 47% (95% CI: 1.06-2.04) greater risk of mortality across six studies that reported OR/RR, and a 32% increased risk across 18 studies which reported time to death (HR: 1.32, 95% CI: 1.10-1.59). There was very high study heterogeneity (I
> 94%) and this was not explained by the prespecified subgroup analysis.
PTSD is associated with increased mortality risk, however further research is required amongst civilians, involving women, and in individuals from underdeveloped countries.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Females live longer than males, and there are sex disparities in physical health and disease incidence. However, sex differences in biological aging have not been consistently reported and may differ ...depending on the measure used. This study aimed to determine the correlations between epigenetic age acceleration (AA), and other markers of biological aging, separately in males and females. We additionally explored the extent to which these AA measures differed according to socioeconomic characteristics, clinical markers, and diseases. Epigenetic clocks (HorvathAge, HannumAge, PhenoAge, GrimAge, GrimAge2, and DunedinPACE) were estimated in blood from 560 relatively healthy Australians aged ≥ 70 years (females, 50.7%) enrolled in the ASPREE study. A system-wide deficit accumulation frailty index (FI) composed of 67 health-related measures was generated. Brain age and subsequently brain-predicted age difference (brain-PAD) were estimated from neuroimaging. Females had significantly reduced AA than males, but higher FI, and there was no difference in brain-PAD. FI had the strongest correlation with DunedinPACE (range
r
: 0.21 to 0.24 in both sexes). Brain-PAD was not correlated with any biological aging measures. Significant correlations between AA and sociodemographic characteristics and health markers were more commonly found in females (e.g., for DunedinPACE and systolic blood pressure
r
= 0.2,
p
< 0.001) than in males. GrimAA and Grim2AA were significantly associated with obesity and depression in females, while in males, hypertension, diabetes, and chronic kidney disease were associated with these clocks, as well as DunedinPACE. Our findings highlight the importance of considering sex differences when investigating the link between biological age and clinical measures.
Neuroimaging-based 'brain age' can identify individuals with 'advanced' or 'resilient' brain aging. Brain-predicted age difference (brain-PAD) is predictive of cognitive and physical health outcomes. ...However, it is unknown how individual health and lifestyle factors may modify the relationship between brain-PAD and future cognitive or functional performance. We aimed to identify health-related subgroups of older individuals with resilient or advanced brain-PAD, and determine if membership in these subgroups is differentially associated with changes in cognition and frailty over three to five years.
Brain-PAD was predicted from T1-weighted images acquired from 326 community-dwelling older adults (73.8 ± 3.6 years, 42.3% female), recruited from the larger ASPREE (ASPirin in Reducing Events in the Elderly) trial. Participants were grouped as having resilient (n=159) or advanced (n=167) brain-PAD, and latent class analysis (LCA) was performed using a set of cognitive, lifestyle, and health measures. We examined associations of class membership with longitudinal change in cognitive function and frailty deficit accumulation index (FI) using linear mixed models adjusted for age, sex and education.
Subgroups of resilient and advanced brain aging were comparable in all characteristics before LCA. Two typically similar latent classes were identified for both subgroups of brain agers: class 1 were characterized by low prevalence of obesity and better physical health and class 2 by poor cardiometabolic, physical and cognitive health. Among resilient brain agers, class 1 was associated with a decrease in cognition, and class 2 with an increase over 5 years, though was a small effect that was equivalent to a 0.04 standard deviation difference per year. No significant class distinctions were evident with FI. For advanced brain agers, there was no evidence of an association between class membership and changes in cognition or FI.
These results demonstrate that the relationship between brain age and cognitive trajectories may be influenced by other health-related factors. In particular, people with age-resilient brains had different trajectories of cognitive change depending on their cognitive and physical health status at baseline. Future predictive models of aging outcomes will likely be aided by considering the mediating or synergistic influence of multiple lifestyle and health indices alongside brain age.
Abstract
DNA methylation (DNAm) algorithms of biological age provide a robust estimate of an individual’s chronological age and can predict their risk of age-related disease and mortality. This study ...reviewed the evidence that environmental, lifestyle and health factors are associated with the Horvath and Hannum epigenetic clocks. A systematic search identified 61 studies. Chronological age was correlated with DNAm age in blood (median .83, range .13–.99). In a meta-analysis body mass index (BMI) was associated with increased DNAm age (Hannum β: 0.07, 95% CI 0.04 to 0.10; Horvath β: 0.06, 95% CI 0.02 to 0.10), but there was no association with smoking (Hannum β: 0.12, 95% CI −0.50 to 0.73; Horvath β:0.18, 95% CI −0.10 to 0.46). DNAm age was positively associated with frailty (three studies, n = 3,093), and education was negatively associated with the Hannum estimate of DNAm age specifically (four studies, n = 13,955). For most other exposures, findings were too inconsistent to draw conclusions. In conclusion, BMI was positively associated with biological aging measured using DNAm, with some evidence that frailty also increased aging. More research is needed to provide conclusive evidence regarding other exposures. This field of research has the potential to provide further insights into how to promote slower biological aging and ultimately prolong healthy life.
•Neighborhood disadvantage negatively associated with BDNF IV methylation.•BDNF methylation negatively associated with prefrontal cortical thickness.•Neighborhood disadvantage not directly associated ...with thicker cortex.•But an indirect association found via decreasing BDNF IV methylation.
Prior research indicates that socioeconomic disadvantage is associated with prefrontal cortical (PFC) development in childhood and adolescence, however the mechanisms of this link are unclear. This study investigated whether DNA methylation of the brain-derived neurotrophic factor (BDNF, which plays a key role in synaptic plasticity), mediated the association between neighborhood disadvantage and thickness of the PFC in adolescents. Neighborhood disadvantage was measured in 33 adolescents aged 12–13 years using the Socio-Economic Indexes for Areas. Buccal swabs, collected during mid-adolescence (aged 16–18 years), enabled BDNF DNA methylation of the widely studied exon IV promoter region to be measured. Cortical thickness was assessed during late-adolescence (aged 18–20 years) via T1-weighted magnetic resonance imaging (MRI). A significant negative association between disadvantage and BDNF DNA methylation at a specific site of the exon IV promoter was identified. Lower levels of methylation were also significantly associated with greater thickness of the lateral orbitofrontal cortex (lOFC), and right medial OFC. Lower levels of DNA methylation at this site also mediated associations between higher disadvantage and thinner bilateral lOFC thickness. These novel findings give insight into a potential biological mechanism that could further our understanding as to why brain development is affected by varying environmental exposures.
BACKGROUNDThe neurocognitive effect of statins in older adults remain uncertain. OBJECTIVESThe aim of this study was to investigate the associations of statin use with cognitive decline and incident ...dementia among older adults. METHODSThis analysis included 18,846 participants ≥65 years of age in a randomized trial of aspirin, who had no prior cardiovascular events, major physical disability, or dementia initially and were followed for 4.7 years. Outcome measures included incident dementia and its subclassifications (probable Alzheimer's disease, mixed presentations); mild cognitive impairment (MCI) and its subclassifications (MCI consistent with Alzheimer's disease, other MCI); and changes in domain-specific cognition, including global cognition, memory, language and executive function, psychomotor speed, and the composite of these domains. Associations of baseline statin use versus nonuse with dementia and MCI outcomes were examined using Cox proportional hazards models and with cognitive change using linear mixed-effects models, adjusting for potential confounders. The impact of statin lipophilicity on these associations was further examined, and effect modifiers were identified. RESULTSStatin use versus nonuse was not associated with dementia, MCI, or their subclassifications or with changes in cognitive function scores over time (p > 0.05 for all). No differences were found in any outcomes between hydrophilic and lipophilic statin users. Baseline neurocognitive ability was an effect modifier for the associations of statins with dementia (p for interaction < 0.001) and memory change (p for interaction = 0.02). CONCLUSIONSIn adults ≥65 years of age, statin therapy was not associated with incident dementia, MCI, or declines in individual cognition domains. These findings await confirmation from ongoing randomized trials.
A recent study reported for the first time, that DNA methylation of the KITLG gene mediates the association between childhood trauma and cortisol stress reactivity. Our study aimed to provide the ...first independent replication of these findings. ESPRIT is a prospective study of community-dwelling participants (age ≥ 65), randomly selected from the electoral rolls of the Montpellier district, in France. Clinical depression was assessed using the Mini-International Neuropsychiatric Interview (MINI, French version 5.00), and the Centre for Epidemiological Studies Depression Scale (CES-D). Experiences of childhood adversity were ascertained via a 25-item questionnaire. Morning, evening, and diurnal salivary cortisol was measured under basal and stress conditions and determined using direct radioimmunoassay analysis. DNA methylation of the KITLG gene was quantified in whole blood using the SEQUENOM MassARRAY EpiTYPER platform. A significant negative association was observed between KITLG DNA methylation and both morning cortisol (β = −1.846 ± 0.666, p = .007) and diurnal cortisol (area under curve AUC) (β = −19.429 ± 8.868, p = .031) under a stress condition. However, only the former association was significant after correcting for multiple testing. Further, this association remained after adjusting for age, sex, and depression status. No significant association was observed between childhood trauma and KITLG DNA methylation in this older population. This study provides support for an association between KITLG methylation and stress cortisol levels, suggesting that DNA methylation of this gene may play a role in the longer term regulation of the stress system.
Lay summary
The significant negative association between KITLG DNA methylation and morning cortisol, measured under a stressful condition, suggests that individuals with higher KITLG methylation will secrete lower levels of cortisol whilst under stress.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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