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.

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.

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.

Public involvement in research occurs when the public, patients, or research participants are actively contributing to the research process. Public involvement has been acknowledged as a key priority for prominent human genomics research initiatives in many different countries. However, to date, there has been no detailed analysis or review of the features, methods, and impacts of public involvement occurring in human genomics research projects worldwide. Here, we review the reported public involvement in 96 human genomics projects (initiatives), based on a database of initiatives hosted by the Global Alliance for Genomics and Health, according to information reported on public domain websites. To conduct the scoping review, we applied a structured categorization of criteria to all information extracted from the search. We found that only a third of all initiatives reported public involvement in any capacity (32/96, 33%). In those reporting public involvement, we found considerable variation in both the methods and tasks of involvement. Some noteworthy initiatives reported diverse and comprehensive ways of involving the public, occurring through different stages of the research project cycle. Three notable initiatives reported a total of eight distinct impacts as a result of involving people. Our findings suggest there would be intrinsic value in having more public involvement occur in human genomics research worldwide. We also suggest that more systematic ways of reporting and evaluating involvement would be highly beneficial, to help develop best practices.