Epigenetic biomarkers of ageing are predictive of mortality risk in a longitudinal clinical cohort of individuals diagnosed with oropharyngeal cancer

Background: Epigenetic clocks are biomarkers of ageing derived from DNA methylation levels at a subset of CpG sites. The difference between age predicted by these clocks and chronological age, termed “epigenetic age acceleration”, has been shown to predict age-related disease and mortality. We aimed to assess the prognostic value of epigenetic age acceleration and a DNA methylation-based mortality risk score with all-cause mortality in a prospective clinical cohort of individuals with head and neck cancer: Head and Neck 5000. We investigated two markers of intrinsic epigenetic age acceleration (IEAAHorvath and IEAAHannum), one marker of extrinsic epigenetic age acceleration (EEAA), one optimised to predict physiological dysregulation (AgeAccelPheno), one optimised to predict lifespan (AgeAccelGrim) and a DNA methylation-based predictor of mortality (ZhangScore). Cox regression models were first used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for associations of epigenetic age acceleration with all-cause mortality in people with oropharyngeal cancer (n = 408; 105 deaths). The added prognostic value of epigenetic markers compared to a clinical model including age, sex, TNM stage and HPV status was then evaluated. Results: IEAAHannum and AgeAccelGrim were associated with mortality risk after adjustment for clinical and lifestyle factors (HRs per standard deviation [SD] increase in age acceleration = 1.30 [95% CI 1.07, 1.57; p = 0.007] and 1.40 [95% CI 1.06, 1.83; p = 0.016], respectively). There was weak evidence that the addition of AgeAccelGrim to the clinical model improved 3-year mortality prediction (area under the receiver operating characteristic curve: 0.80 vs. 0.77; p value for difference = 0.069). Conclusion: In the setting of a large, clinical cohort of individuals with head and neck cancer, our study demonstrates the potential of epigenetic markers of ageing to enhance survival prediction in people with oropharyngeal cancer, beyond established prognostic factors. Our findings have potential uses in both clinical and non-clinical contexts: to aid treatment planning and improve patient stratification

Dual-energy X-ray absorptiometry derived knee shape may provide a useful imaging biomarker for predicting total knee replacement:Findings from a study of 37,843 people in UK Biobank

Objective: We aimed to create an imaging biomarker for knee shape using knee dual-energy x-ray absorptiometry (DXA) scans and investigate its potential association with subsequent total knee replacement (TKR), independently of radiographic features of knee osteoarthritis and established risk factors. Methods: Using a 129-point statistical shape model, knee shape (expressed as a B-score) and minimum joint space width (mJSW) of the medial joint compartment (binarized as above or below the first quartile) were derived. Osteophytes were manually graded in a subset of images and an overall score was assigned. Cox proportional hazards models were used to examine the associations of B-score, mJSW and osteophyte score with TKR risk, adjusting for age, sex, height and weight. Results: The analysis included 37,843 individuals (mean age 63.7 years). In adjusted models, B-score was associated with TKR: each unit increase in B-score, reflecting one standard deviation from the mean healthy shape, corresponded to a hazard ratio (HR) of 2.25 (2.08, 2.43), while a lower mJSW had a HR of 2.28 (1.88, 2.77). Among the 6,719 images scored for osteophytes, mJSW was replaced by osteophyte score in the most strongly predictive model for TKR. In ROC analyses, a model combining B-score, osteophyte score, and demographics outperformed a model including demographics alone (AUC=0.87 vs 0.73). Conclusions: Using statistical shape modelling, we derived a DXA-based imaging biomarker for knee shape that was associated with kOA progression. When combined with osteophytes and demographic data, this biomarker may help identify individuals at high risk of TKR, facilitating targeted interventions. <br/

Epigenetic prediction of complex traits and mortality in a cohort of individuals with oropharyngeal cancer

Background DNA methylation (DNAm) variation is an established predictor for several traits. In the context of oropharyngeal cancer (OPC), where 5-year survival is ~ 65%, DNA methylation may act as a prognostic biomarker. We examined the accuracy of DNA methylation biomarkers of 4 complex exposure traits (alcohol consumption, body mass index [BMI], educational attainment and smoking status) in predicting all-cause mortality in people with OPC. Results DNAm predictors of alcohol consumption, BMI, educational attainment and smoking status were applied to 364 individuals with OPC in the Head and Neck 5000 cohort (HN5000; 19.6% of total OPC cases in the study), followed up for median 3.9 years; inter-quartile range (IQR) 3.3 to 5.2 years (time-to-event—death or censor). The proportion of phenotypic variance explained in each trait was as follows: 16.5% for alcohol consumption, 22.7% for BMI, 0.4% for educational attainment and 51.1% for smoking. We then assessed the relationship between each DNAm predictor and all-cause mortality using Cox proportional-hazard regression analysis. DNAm prediction of smoking was most consistently associated with mortality risk (hazard ratio [HR], 1.38 per standard deviation (SD) increase in smoking DNAm score; 95% confidence interval [CI] 1.04 to 1.83; P 0.025, in a model adjusted for demographic, lifestyle, health and biological variables). Finally, we examined the accuracy of each DNAm predictor of mortality. DNAm predictors explained similar levels of variance in mortality to self-reported phenotypes. Receiver operator characteristic (ROC) curves for the DNAm predictors showed a moderate discrimination of alcohol consumption (area under the curve [AUC] 0.63), BMI (AUC 0.61) and smoking (AUC 0.70) when predicting mortality. The DNAm predictor for education showed poor discrimination (AUC 0.57). Z tests comparing AUCs between self-reported phenotype ROC curves and DNAm score ROC curves did not show evidence for difference between the two (alcohol consumption P 0.41, BMI P 0.62, educational attainment P 0.49, smoking P 0.19). Conclusions In the context of a clinical cohort of individuals with OPC, DNAm predictors for smoking, alcohol consumption, educational attainment and BMI exhibit similar predictive values for all-cause mortality compared to self-reported data. These findings may have translational utility in prognostic model development, particularly where phenotypic data are not available

Dual-energy X-ray absorptiometry derived knee shape may provide a useful imaging biomarker for predicting total knee replacement: findings from a study of 37,843 people in UK Biobank.

Objective We developed a novel imaging biomarker derived from knee dual-energy x-ray absorptiometry (DXA) to predict subsequent total knee replacement (TKR). The biomarker is based on knee shape, determined through statistical shape modelling. It was developed and evaluated using data and scans from the UK Biobank cohort.Methods Using a 129-point statistical shape model (SSM), knee shape (B-score) and minimum joint space width (mJSW) of the medial joint compartment (binarized as above or below the first quartile) were derived. Osteophytes were manually graded in a subset of DXA images. Cox proportional hazards models were used to examine the associations of B-score, mJSW and osteophyte score with the risk of TKR, adjusted for age, sex, height and weight.Results The analysis included 37,843 individuals (mean 63.7 years). In adjusted models, B-score and mJSW were associated with TKR: a standard deviation increase in B-score was associated with a hazard ratio (HR) of 2.32 (2.13, 2.54), and a lower mJSW with a HR of 2.21 (1.76, 2.76). In the 6,719 images scored for osteophytes, mJSW was replaced by osteophyte score in the most strongly predictive model for TKR. In subsequent ROC analyses, a model combining B-score, osteophyte score, and demographic variables had superior discrimination (AUC=0.87) in predicting TKR at five years compared with a model with demographic variables alone (AUC=0.73).Conclusions An imaging biomarker derived from knee DXA scans reflecting knee shape and osteophytes, in conjunction with demographic factors, could help identify those at high risk of TKR, in whom preventative strategies should be targeted

Investigating the effects of lycopene and green tea on the metabolome of men at risk of prostate cancer:the ProDiet randomised controlled trial

Abstract Lycopene and green tea consumption have been observationally associated with reduced prostate cancer risk, but the underlying mechanisms have not been fully elucidated. We investigated the effect of factorial randomisation to a 6‐month lycopene and green tea dietary advice or supplementation intervention on 159 serum metabolite measures in 128 men with raised PSA levels (but prostate cancer‐free), analysed by intention‐to‐treat. The causal effects of metabolites modified by the intervention on prostate cancer risk were then assessed by Mendelian randomisation, using summary statistics from 44,825 prostate cancer cases and 27,904 controls. The systemic effects of lycopene and green tea supplementation on serum metabolic profile were comparable to the effects of the respective dietary advice interventions (R² = 0.65 and 0.76 for lycopene and green tea respectively). Metabolites which were altered in response to lycopene supplementation were acetate [β (standard deviation difference vs. placebo): 0.69; 95% CI = 0.24, 1.15; p = 0.003], valine (β: −0.62; −1.03, −0.02; p = 0.004), pyruvate (β: −0.56; −0.95, −0.16; p = 0.006) and docosahexaenoic acid (β: −0.50; −085, −0.14; p = 0.006). Valine and diacylglycerol were lower in the lycopene dietary advice group (β: −0.65; −1.04, −0.26; p = 0.001 and β: −0.59; −1.01, −0.18; p = 0.006). A genetically instrumented SD increase in pyruvate increased the odds of prostate cancer by 1.29 (1.03, 1.62; p = 0.027). An intervention to increase lycopene intake altered the serum metabolome of men at risk of prostate cancer. Lycopene lowered levels of pyruvate, which our Mendelian randomisation analysis suggests may be causally related to reduced prostate cancer risk