Background DNA methylation changes with age. Chronological age predictors built from DNA methylation are termed ‘epigenetic clocks’. The deviation of predicted age from the actual age (‘age acceleration residual’, AAR) has been reported to be associated with death. However, it is currently unclear how a better prediction of chronological age affects such association. Methods In this study, we build multiple predictors based on training DNA methylation samples selected from 13,661 samples (13,402 from blood and 259 from saliva). We use the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936) to examine whether the association between AAR (from these predictors) and death is affected by (1) improving prediction accuracy of an age predictor as its training sample size increases (from 335 to 12,710) and (2) additionally correcting for confounders (i.e., cellular compositions). In addition, we investigated the performance of our predictor in non-blood tissues. Results We found that in principle, a near-perfect age predictor could be developed when the training sample size is sufficiently large. The association between AAR and mortality attenuates as prediction accuracy increases. AAR from our best predictor (based on Elastic Net, https://github.com/qzhang314/DNAm-based-age-predictor ) exhibits no association with mortality in both LBC1921 (hazard ratio = 1.08, 95% CI 0.91–1.27) and LBC1936 (hazard ratio = 1.00, 95% CI 0.79–1.28). Predictors based on small sample size are prone to confounding by cellular compositions relative to those from large sample size. We observed comparable performance of our predictor in non-blood tissues with a multi-tissue-based predictor. Conclusions This study indicates that the epigenetic clock can be improved by increasing the training sample size and that its association with mortality attenuates with increased prediction of chronological age. Electronic supplementary material The online version of this article (10.1186/s13073-019-0667-1) contains supplementary material, which is available to authorized users.
OBJECTIVERecent studies have drawn attention to the adverse effects of ambient air pollutants such as particulate matter 2.5 (PM2.5) on human health. We evaluated the association between PM2.5 exposure and diabetes prevalence in the U.S. and explored factors that may influence this relationship.RESEARCH DESIGN AND METHODSThe relationship between PM2.5 levels and diagnosed diabetes prevalence in the U.S. was assessed by multivariate regression models at the county level using data obtained from both the Centers for Disease Control and Prevention (CDC) and U.S. Environmental Protection Agency (EPA) for years 2004 and 2005. Covariates including obesity rates, population density, ethnicity, income, education, and health insurance were collected from the U.S. Census Bureau and the CDC.RESULTSDiabetes prevalence increases with increasing PM2.5 concentrations, with a 1% increase in diabetes prevalence seen with a 10 μg/m3 increase in PM2.5 exposure (2004: β = 0.77 [95% CI 0.39–1.25], P < 0.001; 2005: β = 0.81 [0.48–1.07], P < 0.001). This finding was confirmed for each study year in both univariate and multivariate models. The relationship remained consistent and significant when different estimates of PM2.5 exposure were used. Even for counties within guidelines for EPA PM2.5 exposure limits, those with the highest exposure showed a >20% increase in diabetes prevalence compared with that for those with the lowest levels of PM2.5, an association that persisted after controlling for diabetes risk factors.CONCLUSIONSOur results suggest PM2.5 may contribute to increased diabetes prevalence in the adult U.S. population. These findings add to the growing evidence that air pollution is a risk factor for diabetes.
There is a need for objective imaging markers of Parkinson's disease status and progression. Positron emission tomography and single photon emission computed tomography studies have suggested patterns of abnormal cerebral perfusion in Parkinson's disease as potential functional biomarkers. This study aimed to identify an arterial spin labelling magnetic resonance-derived perfusion network as an accessible, non-invasive alternative. We used pseudo-continuous arterial spin labelling to measure cerebral grey matter perfusion in 61 subjects with Parkinson's disease with a range of motor and cognitive impairment, including patients with dementia and 29 age- and sex-matched controls. Principal component analysis was used to derive a Parkinson's disease-related perfusion network via logistic regression. Region of interest analysis of absolute perfusion values revealed that the Parkinson's disease pattern was characterized by decreased perfusion in posterior parieto-occipital cortex, precuneus and cuneus, and middle frontal gyri compared with healthy controls. Perfusion was preserved in globus pallidus, putamen, anterior cingulate and post- and pre-central gyri. Both motor and cognitive statuses were significant factors related to network score. A network approach, supported by arterial spin labelling-derived absolute perfusion values may provide a readily accessible neuroimaging method to characterize and track progression of both motor and cognitive status in Parkinson's disease.
BackgroundEnterotoxigenic Bacteroides fragilis (ETBF) is a toxin-producing bacteria thought to possibly promote colorectal carcinogenesis by modulating the mucosal immune response and inducing epithelial cell changes. Here, we aim to examine the association of colonic mucosal colonization with ETBF and the presence of a range of lesions on the colonic neoplastic spectrum.MethodsMucosal tissue from up to four different colonic sites was obtained from a consecutive series of 150 patients referred for colonoscopy. The presence and relative abundance of the B. fragilis toxin gene (bft) in each tissue sample was determined using quantitative PCR, and associations with clinicopathological characteristics were analysed.FindingsWe found a high concordance of ETBF between different colonic sites (86%). Univariate analysis showed statistically significant associations between ETBF positivity and the presence of low-grade dysplasia (LGD), tubular adenomas (TA), and serrated polyps (P-values of 0.007, 0.027, and 0.007, respectively). A higher relative abundance of ETBF was significantly associated with LGD and TA (P-values of < 0.0001 and 0.025, respectively). Increased ETBF positivity and abundance was also associated with left-sided biopsies, compared to those from the right side of the colon.ConclusionOur results showing association of ETBF positivity and increased abundance with early-stage carcinogenic lesions underlines its importance in the development of colorectal cancer, and we suggest that detection of ETBF may be a potential marker of early colorectal carcinogenesis.
BackgroundPseudomonas aeruginosa infections are associated with progressive life threatening decline of lung function in cystic fibrosis sufferers. Growth of Ps. aeruginosa releases a "grape-like" odour that has been identified as the microbial volatile organic compound 2-aminoacetophenone (2-AA).MethodsWe investigated 2-AA for its specificity to Ps. aeruginosa and its suitability as a potential breath biomarker of colonisation or infection by Solid Phase Micro Extraction and Gas Chromatography-Mass Spectrometry (GC/MS).ResultsCultures of 20 clinical strains of Ps. aeruginosa but not other respiratory pathogens had high concentrations of 2-AA in the head space of in vitro cultures when analysed by GC/MS. 2-AA was stable for 6 hours in deactivated glass sampling bulbs but was not stable in Tedlar® bags. Optimisation of GC/MS allowed detection levels of 2-AA to low pico mol/mol range in breath. The 2-AA was detected in a significantly higher proportion of subjects colonised with Ps. aeruginosa 15/16 (93.7%) than both the healthy controls 5/17 (29%) (p < 0.0002) and CF patients not colonised with Ps. aeruginosa 4/13(30.7%) (p < 0.001). The sensitivity and specificity of the 2-AA breath test compared to isolation of Ps. aeruginosa in sputum and/or BALF was 93.8% (95% CI, 67-99) and 69.2% (95% CI, 38-89) respectively. The peak integration values for 2-AA analysis in the breath samples were significantly higher in Ps. aeruginosa colonised subjects (median 242, range 0-1243) than the healthy controls (median 0, range 0-161; p < 0.001) and CF subjects not colonised with Ps. aeruginosa (median 0, range 0-287; p < 0.003)ConclusionsOur results report 2-AA as a promising breath biomarker for the detection of Ps. aeruginosa infections in the cystic fibrosis lung.
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