<i>AHRR </i>(cg05575921) methylation extent of leukocyte DNA and lung cancer survival

<div><p>Background</p><p>Prior studies have shown that <i>AHRR</i> (cg05575921) hypomethylation may be a marker of smoking, lung cancer risk and potentially lung cancer survival (in some lung cancer subtypes). It is unknown if <i>AHRR</i> (cg05575921) hypomethylation is associated with reduced survival among lung cancer patients.</p><p>Methods</p><p>In bisulfite treated leukocyte DNA from 465 lung cancer patients from the Copenhagen prospective lung cancer study, we measured <i>AHRR</i> (cg05575921) methylation. 380 died during max follow-up of 4.4 years. Cox proportional hazard models were used to analyze survival as a function of <i>AHRR</i> (cg05575921) methylation.</p><p>Results</p><p>We observed the expected inverse correlation between cumulative smoking and <i>AHRR</i> methylation, as methylation (%) decreased (Coefficient -0.03; 95% confidence interval, -0.04- -0.02, p = 8.6x10^-15) for every pack-year. Cumulative smoking > 60 pack-years was associated with reduced survival (hazard ratio and 95% confidence interval 1.48; 1.05–2.09), however, <i>AHRR</i> (cg05575921) methylation was not associated with survival when adjusted for sex, body mass index, smoking status, ethnicity, performance status, TNM Classification, and histology type of lung cancer.</p><p>Conclusion</p><p><i>AHRR</i> (cg05575921) methylation is linked to smoking but does not provide independent prognostic information in lung cancer patients.</p></div

Self-Reported Health as Predictor of Allostatic Load and All-Cause Mortality: Findings From the Lolland-Falster Health Study

Objectives: The aim was to determine the association between self-reported health (SRH), allostatic load (AL) and mortality.Methods: Data derived from the Lolland-Falster Health Study undertaken in Denmark from 2016–2020 (n = 14,104). Median follow-up time for death was 4.6 years where 456 participants died. SRH was assessed with a single question and AL by an index of ten biomarkers. Multinomial regression analysis were used to examine the association between SRH and AL, and Cox regression to explore the association between SRH, AL and mortality.Results: The risk of high AL increased by decreasing level of SRH. The ratio of relative risk (RRR) of having medium vs. low AL was 1.58 (1.11–2.23) in women reporting poor/very poor SRH as compared with very good SRH. For men it was 1.84 (1.20–2.81). For high vs. low AL, the RRR was 2.43 (1.66–3.56) in women and 2.96 (1.87–4.70) in men. The hazard ratio (HR) for all-cause mortality increased by decreasing SRH. For poor/very poor vs. very good SRH, the HR was 6.31 (2.84–13.99) in women and 3.92 (2.12–7.25) in men.Conclusion: Single-item SRH was able to predict risk of high AL and all-cause mortality

Tumor suppressor p53 Arg72Pro polymorphism and longevity, cancer survival, and risk of cancer in the general population

p53 is an important tumor suppressor, normally preventing cancer development via apoptosis. A genomic Arg72Pro substitution in the p53 protein has important influence on cell death via apoptosis, which could be beneficial. We therefore tested the hypotheses that this polymorphism influences longevity, survival after a cancer diagnosis, and risk of cancer in the general population. We examined a cohort of 9,219 participants ages 20–95 from the Danish general population with 100% follow-up. The overall 12-yr survival was increased in p53 Arg/Pro heterozygotes with 3% (P = 0.003) and in Pro/Pro homozygotes with 6% (P = 0.002) versus Arg/Arg homozygotes, corresponding to an increase in median survival of 3 yr for Pro/Pro versus Arg/Arg homozygotes. We also demonstrated an increased survival after the development of cancer, or even after the development of other life-threatening diseases, for Pro/Pro versus Arg/Arg homozygotes. The Arg72Pro substitution did not associate with decreased risk of cancer. In conclusion, in this large cohort from the general population, we show that a well-known functional single nucleotide polymorphism in the tumor suppressor p53 protein leads to increased longevity, but not to decreased risk of cancer. The increased longevity may be due to increased survival after a diagnosis of cancer or other life-threatening diseases

Physical activity and risk of instant and 28-day case-fatality in myocardial infarction

BackgroundWhile physical activity reduces risk of developing myocardial infarction (MI), it is unknown whether a history of physical activity is also protective of fatal arrhythmia and case-fatality in patients who have suffered an acute MI.Methods104,801 individuals included in 2003-2014 in the Copenhagen General Population Study (CGPS), a prospective population-based study with self-reported leisure time physical activity (LTPA) in three categories measured at baseline, were followed until 2014 through national registries. The 1,517 individuals who suffered a first time MI during follow-up constituted the study population. Outcomes were fatal MI, defined as date of death same as date of MI (including out-of-hospital deaths) and 28-day fatality. Through multivariable analyses the association between baseline LTPA and outcomes were assessed adjusted for CVD risk factors.ResultsOf 1,517 MI events, 117 (7.7%) were fatal and another 79 (5.6%) lead to death within 28 days. Median time from baseline to MI was 3.6 years (IQR 1.7-5.8). LTPA was associated with lower risk of fatal MI with odds ratios of 0.40 (95% CI: 0.22-0.73) for light and 0.41 (0.22-0.76) for moderate/high LTPA after multivariable adjustment with sedentary LTPA as reference. Age, alcohol-intake, education and smoking were identified as other predictors for fatal MI. We found no association between LTPA and 28-day case fatality.ConclusionsAmong individuals with MI, those that have engaged in any light or moderate physical activity were more likely to survive their MI. Results are consistent with effect of exercise preconditioning on risk of fatal arrhythmia

Development and validation of a model to predict incident chronic liver disease in the general population: the CLivD score

BACKGROUND & AIMS: Current screening strategies for chronic liver disease focus on detection of subclinical advanced liver fibrosis but cannot identify persons at high future risk for severe liver disease. Our aim was to develop and validate a risk prediction model for incident chronic liver disease in the general population based on widely available factors. METHODS: Multivariable Cox regression analyses were used to develop prediction models for liver-related outcomes with and without laboratory measures (Modellab and Modelnon-lab) in 25,760 individuals aged 40-70 years. Their data were sourced from the Finnish population-based health examination surveys FINRISK 1992-2012 and Health 2000 (derivation cohort). The models were externally validated in the Whitehall II (n = 5058) and Copenhagen City Heart Study (CCHS) (n = 3049) cohorts. RESULTS: The absolute rate of incident liver outcomes per 100,000 person-years ranged from 53 to 144. The final prediction model included age, sex, alcohol use (drinks/week), waist-hip ratio, diabetes, and smoking, and Modellab also included gamma-glutamyltransferase values. Internally-validated Wolbers' C-statistics were 0.77 for Modellab and 0.75 for Modelnon-lab, while apparent 15-year AUCs were 0.84 (95% CI 0.75-0.93) and 0.82 (95% CI 0.74-0.91). The models identified a small proportion (10% absolute 15-year risk for liver events. Of all liver events, only 10% occurred in participants in the lowest risk category. In the validation cohorts, 15-year AUCs were 0.78 (Modellab) and 0.65 (Modelnon-lab) in the CCHS cohort, and 0.78 (Modelnon-lab) in the Whitehall II cohort. CONCLUSIONS: Based on widely available risk factors, this Chronic Liver Disease (CLivD) score can be used to predict risk for future advanced liver disease in the general population. LAY SUMMARY: Liver disease often progresses silently without symptoms and thus the diagnosis is often delayed until severe complications occur and prognosis becomes poor. In order to identify individuals in the general population who have high risk of developing severe liver disease in the future, we developed and validated a Chronic liver disease (CLivD) risk prediction score, based on age, sex, alcohol use, waist-hip ratio, diabetes, smoking, with or without gamma-glutamyltransferase (GGT). The CLivD score can be used as part of health counseling, and for planning further liver investigations and follow-up

Development and validation of a model to predict incident chronic liver disease in the general population : The CLivD score

Background & Aims: Current screening strategies for chronic liver disease focus on detection of subclinical advanced liver fibrosis but cannot identify those at high future risk of severe liver disease. Our aim was to develop and validate a risk pre-diction model for incident chronic liver disease in the general population based on widely available factors. Methods: Multivariable Cox regression analyses were used to develop prediction models for liver-related outcomes with and without laboratory measures (Modellab and Modelnon-lab) in 25,760 individuals aged 40-70 years. Their data were sourced from the Finnish population-based health examination surveys FINRISK 1992-2012 and Health 2000 (derivation cohort). The models were externally validated in the Whitehall II (n = 5,058) and Copenhagen City Heart Study (CCHS) (n = 3,049) cohorts. Results: The absolute rate of incident liver outcomes per 100,000 person-years ranged from 53 to 144. The final prediction model included age, sex, alcohol use (drinks/week), waist-hip ratio, diabetes, and smoking, and Modellab also included gamma-glutamyltransferase values. Internally validated Wolbers' C -sta-tistics were 0.77 for Modellab and 0.75 for Modelnon-lab, while apparent 15-year AUCs were 0.84 (95% CI 0.75-0.93) and 0.82 (95% CI 0.74-0.91). The models identified a small proportion ( 10% absolute 15-year risk for liver events. Of all liver events, only 10% occurred in participants in the lowest risk category. In the validation cohorts, 15-year AUCs were 0.78 (Modellab) and 0.65 (Modelnon-lab) in the CCHS cohort, and 0.78 (Modelnon-lab) in the Whitehall II cohort. Conclusions: Based on widely available risk factors, the Chronic Liver Disease (CLivD) score can be used to predict risk of future advanced liver disease in the general population. Lay summary: Liver disease often progresses silently without symptoms and thus the diagnosis is often delayed until severe complications occur and prognosis becomes poor. In order to identify individuals in the general population who have a high risk of developing severe liver disease in the future, we developed and validated a Chronic Liver Disease (CLivD) risk prediction score, based on age, sex, alcohol use, waist-hip ratio, diabetes, and smoking, with or without measurement of the liver enzyme gamma-glutamyltransferase. The CLivD score can be used as part of health counseling, and for planning further liver investigations and follow-up. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of European Association for the Study of the Liver.Peer reviewe