Few cases or peri-implant peripheral giant cell lesions (PGCL) have been reported in the literature. The aim of this study was to report 13 new cases of peri-implant PGCL and compare the expression of smooth muscle actin, Bcl-2 protein, GLUT-1, CD68, osteoprotegerin, receptor activator of nuclear factor kappa-B, Ki-67 and CD34 in these cases with PGCL and central giant cell lesions (CGCL). Clinical data were retrieved from the laboratory records and histological analysis was performed using HE-stained slides. Immunohistochemical reactions for the above mentioned antibodies were performed and digitally scored.p=0.033 for CD68 and p<.0001 for Bcl-2). Microvessel density was higher in conventional peripheral than in central and peri-implant PGCL (p=0.002). Proliferative index of the mononuclear cells showed no statistically significant differences comparing the three groups but it was higher in peri-implant PGCL. Peri-implant PGCL mostly affected the posterior mandible of adult females. CD68 and Bcl-2 expressions were higher in conventional PGCL and CGCL than in peri-implant PGCL ( The current study demonstrated that peri-implant PGCL is more common in the posterior mandible of adult females. There were some differences in microvessel density, proliferative activity and expression of CD68 and Bcl-2 among conventional PGCL, peri-implant and CGCL. Further studies are encouraged to better understand these early findings. Key words:Giant cell lesion, giant cell granuloma, peripheral, dental implants, immunohistochemistry. Peripheral giant cell lesions (PGCL) are relatively common proliferative growths that affect mainly the lower posterior gingiva and edentulous areas of the alveolar mucosa . It is wAlmost all PGCL are associated with teeth or arise in edentulous areas of the alveolar mucosa, but there are also some few reported cases of peri-implant PGCL . ConventPiracicaba Dental School, University of Campinas .The sample consisted of 36 specimens retrieved from the files of the Oral Pathology Laboratory, School of Dentistry, State University of Rio de Janeiro, Brazil and from the Oral & Maxillofacial Pathology Laboratory, University of the Basque Country/EHU, Leioa, Spain. After analysis of the integrity of the specimen and its representativeness, the cases were selected and grouped in CGCL (n=10), conventional PGCL (n=13) and peri-implant PGCL (n=13). Clinical, radiological and gross specimen data from each case were obtained from the laboratory registries and histological features were described after analysis of five-µm HE-stained sections. This study was approved by the Institutional Board Review of the Immunohistochemical (IHC) reactions were performed using 3-µm sections deparaffinized in xylene and hydrated in graded series of alcohol. Antigen retrieval was performed with a citric acid solution (pH 6.0)  or EDTA/Tris solution  and pressure cooker. The activity of the endogenous peroxidase was blocked with one 15-minute bath of 10% hydrogen peroxide. The sections were incubated for 2 hours with the primary antibodies against α-SMA , Bcl-2 , Glut-1 , CD68 , OPG , RANK , CD34  and Ki-67 . After that, the sections were incubated with the super-sensitive non-biotin based IHC visualization system . Diaminobenzidine tetrahydrochloride  was used as chromogen and was followed by counterstaining with Carazzi’s hematoxylin.Pixel Count v9 (Aperio Technologies Inc.) algorithm classified staining in negative, weak-positive, medium-positive and strong-positive; five distinct medium-power fields were evaluated for each case. The final score of each marker for each lesion was calculated as the sum of the percentage of each category multiplied by their intensity scores using the following formula: [tumor score = (percentage weak × 1) + (percentage moderate × 2) + (percentage strong × 3)]. The results ranged from 100 to 300, which was in agreement with previous study from our group . For α-SMA, Bcl-2, Glut-1, CD68, OPG and RANK, the Positive p ≤ 0.05) for all analyses.Statistical Package for Social Sciences (SPSS) software version 22  was used for statistical analysis. Normality was analyzed with the Kolmogorov-Smirnov test. Kruskal-Wallis test was applied to compare the means from all scores, cellular proliferative index and microvessel density. Data were also examined through the Pearson correlation test. The level of significance was considered 5%  and mean age of the patients was 57.5 years (ranging from 29 to 73 years old). Ten cases affected the mandible (77%) and 70% of the cases were located in the posterior region. Clinical aspect of the lesions was described as a reddish/purplish growth in 62% of the cases and most cases presented less than 15 mm in size in its greater diameter. Clinical diagnosis included mostly pyogenic granuloma (in 10 cases) and PGCL was suspected in only two cases. Clinical and demographical characteristics comparing the three groups are shown in CGCL and peri-implant PGCL demonstrated a predilection for females while conventional PGCL were more common in males. Mean age of the patients affected by PGCL was higher than the mean age of the CGCL-affected patients. All three groups were more common in the mandible and most PGCL were smaller than the CGCL .All lesions showed a similar histological pattern. Conventional and peri-implant PGCL were mostly covered by a keratinized stratified squamous epithelium, with a higher frequency of ulceration in peri-implant PGCL. The lamina propria was composed by a loose connective tissue and the deeper parts of the stroma showed a proliferation of multinucleated giant cells interspersed by a component of ovoid and spindled shaped mesenchymal cells and numerous small blood vessels. In CGCL, a spindle cell proliferation was also present and multinucleated giant cells were observed in direct contact with bone trabeculae. Multiple areas of hemorrhage and presence of hemosiderin were also common in CGCL Fig. . Mean nuThe IHC features showed that α-SMA was expressed in blood vessels and myofibroblasts in all groups. Bcl-2 demonstrated a variable expression in mononuclear cells and multinucleated giant cells. Several cases showed a weak expression of Bcl-2 in multinucleated giant cells. Ulcerated conventional and peri-implant PGCL showed a higher number of inflammatory cells positive for Bcl-2 close to areas of ulceration. Glut-1 was expressed in the cytoplasm of few multinucleated giant cells in all groups and surface epithelium in conventional and peri-implant PGCL. CD68 was expressed mainly in the cytoplasm of the multinucleated giant cells and some disperse mononuclear cells. RANK and OPG demonstrated a cytoplasmic expression in fusiform and mononuclear cells, and some giant cells were also strongly positive for both markers. CGCL presented higher expression of RANK than conventional and peri-implant PGCL, while OPG was more expressed in peri-implant PGCL than in conventional PGCL and CGCL. CD34 was expressed mainly in the endothelial cells of large and small vessels and occasionally in dispersed fusiform cells, compatible with fibroblasts/myofibroblasts.Fig. The proliferative index of the mononuclear ovoid/spindled mesenchymal cells, assessed by Ki-67-positive nuclei was 5.33%, 5.24% and 6.49% for CGCL, conventional PGCL and peri-implant PGCL, respectively  and ulcerated was 10.53% (3/13 cases). Regarding the peri-implant PGCL the values were 18.31% for non-ulcerated lesions (3/13 cases) and 23.75% for ulcerated lesions (10/13 cases).Mean scores from the digital analysis for all studied markers are shown in Fig. P=0.033 for CD68 and P<0.0001 for Bcl-2). Microvessel density was higher in conventional PGCL than in CGCL and peri-implant PGCL (P=0.002). The α-SMA, Glut-1, RANK and OPG scores demonstrated a similar expression in the three groups, without any statistically significant differences. Correlation tests demonstrated a positive correlation between microvessel density and the expression of CD68  and OPG .CD68 and Bcl-2 scores were higher in conventional PGCL and CGCL than in peri-implant PGCL (Most studies have demonstrated that oral mucosal and gnathic giant cell lesions show a similar histological pattern and are considered reactive entities, although they sometimes present a local aggressive clinical course -5. They et al. in 2003 (There are less than 30 cases of peri-implant PGCL reported in the English-language literature since its first description by Hirshberg  in 2003 -25. Apar in 2003 -25. This in 2003 ,22,23. B in 2003 ,5,18. ItThe present results showed that both the mean number of multinucleated giant cells per high-power field and the proportion of ovoid/spindled mononuclear mesenchymal cells to multinucleated giant cells were similar for CGCL, conventional PGCL and peri-implant PGCL. One previous study showed, however, a significantly lower number of giant cells and a lower density of mesenchymal cells in peri-implant PGCL in comparison with conventional PGCL . It is pCD68 is a transmembrane glycoprotein widely used as a specific marker of cells of the monocyte-macrophage lineage, such as monocytes, histiocytes and osteoclasts. We observed a higher CD68 expression score in CGCL and conventional PGCL than in peri-implant PGCL. Conventional PGCL demonstrated a higher CD68 expression score in comparison with CGCL, although not statistically significant, in accordance with previous results , so osteMacrophages are potent angiogenic stimulators by producing several angiogenic factors and our results showed a positive correlation between the expression of CD68 and microvessel density. Conventional PGCL showed both a higher microvessel density and a higher score of CD68-positive cells than peri-implant PGCL; one explanation for these findings could be that conventional PGCL is exposed to continuous local irritative factors from the periodontal ligament or local trauma, showing an increase in the number of blood vessels and, consequently, a higher microvessel density. Higher microvessel density has been also associated with a more aggressive phenotype of CGCL , but we Several components of the B-cell lymphoma family, particularly Bcl-2, have been involved in the apoptotic pathway, acting as positive or negative regulators of this process . It is wRANK pathway is directly involved in the dynamics of osteoclastogenesis, playing an important role in osteoclast proliferation, activation and apoptosis . On the Expression of α-SMA was similar in the three groups suggesting that the presence of cells with myofibroblastic phenotype is constant in GCL and is not dependent on origin and relationship to periodontal ligament. Glut-1 is a molecule involved in the basal glucose uptake and, consequently, plays an important role in the cellular metabolism, energy production and intracellular glucose concentration levels . Its expComparison of the proliferative index of the mononuclear cells from the three groups showed no statistically significant differences. However, the proliferative index was higher in peri-implant PGCL than in conventional PGCL and CGCL. The higher proliferative index of the peri-implant PGCL could be associated with the higher frequency of ulceration of the surface epithelium seen in this group and seems to be not associated with apoptotic pathways. Peri-implant PGCL have demonstrated higher intralesional and epithelial proliferative index in comparison with conventional PGCL and CGCL, together with lower expression of Bcl-2 compared with the other lesions.In conclusion, the results of the current study showed that peri-implant PGCL are more common in the posterior mandible of adult females. We have also demonstrated some differences in microvessel density, proliferative activity and expression of CD68 and Bcl-2 among conventional PGCL, peri-implant PGCL and CGCL. Although this series is the largest reported up to now, the present study has some limitations in data interpretation such as the limited number of cases and the difficulties in obtaining information on follow-up, limiting the discussion about biological behavior of peri-implant PGCL. Further studies with larger series with follow-up and inclusion of additional histogenetic markers are encouraged to better understand these early findings.


Overall hazard ratio for progression-free survival was 0.58 , with significant heterogeneity and publication bias, and unbiased estimate was significant . Overall hazard ratio for overall survival was 0.51 , and this estimate was not likely confounded by heterogeneity or publication bias. Subgroup and meta-regression analyses suggested that hypertension grade of controls, sample size, age and gender were possible causes of heterogeneity. Taken together, our findings indicate that bevacizumab-induced hypertension can predict progress-free survival and overall survival in patients with metastatic colorectal cancer, whereas its prediction for objective response rate was nonsignificant.We tested the hypothesis that bevacizumab-induced hypertension may be a useful predictor for objective response rate, progression-free and overall survival in patients with metastatic colorectal cancer via a comprehensive meta-analysis. Search process, article selection and data extraction were independently performed by two investigators. Statistical analyses were conducted using the STATA/SE software. Fourteen independent studies and 2292 study subjects were synthesized. Overall relative risk of objective response rate for bevacizumab-induced hypertension was 2.03 (95% confidence interval [CI]: 1.18-3.48,  Colorectal cancer is the third most common cancer in the world, and its global burden is projected to be increased by 60% to over 2.2 million new cases and 11 million deaths by 2030 . It is eBevacizumab, a humanized anti-vascular endothelial growth factor (VEGF) monoclonal antibody, is increasingly recognized as standard of care for the treatment of metastatic colorectal cancer in a first-line setting, with reasonable biological implications ,11. HoweIn total, 632 articles were identified after searching the medical literature, as well as the reference lists of retrieved major articles and reviewers. Of them, only 13 articles including 14 independent studies and 2292 study subjects were qualified for the final analysis -15,18-26The baseline characteristics of 14 qualified studies published from 2009 to 2016 are listed in p=0.01), whereas this risk was clouded by the significance of between-study heterogeneity (I2: 77.1%).As shown in p<0.001) and was not impacted by heterogeneity (I2: 0.0%), with the effect estimate over twice as much as that in studies with hypertension grade 0 in controls . Moreover, no significance was detected after dividing studies using the median cutoff value of total sample size at 77, in spite of divergent difference in risk estimates. In univariate meta-regression analysis, gender was identified as a significant source of heterogeneity for overall response rate (p=0.037).Heterogeneity sources were explored using both subgroup analysis and meta-regression analysis. In subgroup analysis, bevacizumab dose, sample size and hypertension grade of controls may account for the presence of significant heterogeneity based on significant differences in stratified relative risk . For exap=0.047). Analysis of incorporating the three missing studies showed that the unbiased relative risk of response rate was 1.55, which did not deviate significantly from 1 . Further cumulative meta-analysis indicated a stable trend in the risk estimates of objective response rate for bevacizumab-induced hypertension, as presented in Publication bias was evaluated using both filled funnel plots  and Eggep<0.001), with significant heterogeneity (I2: 74.7%)  .I2: 0.0%). In meta-regression analysis, age and gender were identified as significant confounders for the prediction of bevacizumab-induced hypertension for progression-free survival .Subgroup analysis showed that hypertension grade of controls and sample size may confound the prediction of bevacizumab-induced hypertension in patients with metastatic colorectal cancer based on the differences in hazard ratio between subgroups . The risp=0.001). After adjusting for the five missing studies, the hazard ratio of progression-free survival was still significant . In cumulative meta-analysis, a stable trend in risk estimates was noted for progression-free survival , and this estimate was not likely confounded by heterogeneity (I2: 23.1%), as presented in p<0.001) and with total sample size over the median cutoff value of total sample size at 84 . Meta-regression analysis showed that age and gender might be other causes of heterogeneity .The pooled hazard ratio for overall survival of bevacizumab-induced hypertension was 0.51 . Risk estimates were stabilized in cumulative meta-analysis, as shown in No missing study was reported by filled funnel plot in Finally, trial sequential analysis was employed to minimize random errors for objective response rate, progression-free survival and overall survival, respectively . The thrThe aim of this present study was to update the results of two previous meta-analyses ,17 by inIt is widely recognized that VEGF is a key mediator of angiogenesis and an effective biological target for patients with metastatic colorectal cancer, and its overexpression can accelerate tumor progression and metastatic spread of colorectal cancer ,28. AlsoPreviously, two meta-analyses examined the validity of using hypertension to predict response rate and survival of patients with metastatic colorectal cancer, and both studies consistently demonstrated that bevacizumab-induced hypertension was associated with significant improvement in objective response rate, progression-free survival and overall survival ,17. DiffBesides objective response rate, we have assessed the association of bevacizumab-induced hypertension with two survival outcomes. Consistent with the results of two previous studies, our findings consolidated the prognostic contribution of bevacizumab-induced hypertension to both progression-free survival and overall survival. However, extending the results of the two studies, we found that sample size and hypertension grade of controls, as well as age and gender, may be possible causes of between-study heterogeneity. In particular, after grouping studies per the median cutoff point of total sample size, the prediction of bevacizumab-induced hypertension for survival outcomes was more obvious when analysis was restricted to the large studies, indicating the robustness of our findings. In fact, the difference between progression-free survival and overall survival is whether the incorporation of patients who get worse. Just because of this difference, another aspect worth noting was that risk magnitude of overall survival was more obvious in studies with hypertension grade 0 of controls than studies with hypertension grade 1/2, whereas this situation was slightly reversed for that of progression-free survival. In other words, the protective effect of bevacizumab indexed by overall survival was more obvious for a lower grade of hypertension, whereas that by progression-free survival was more obvious for a higher grade of hypertension. Generally, the probability of tumor aggressiveness is higher during early treatment of bevacizumab for metastatic colorectal cancer than the late treatment. A higher grade of bevacizumab-induced hypertension may surrogate a longer treatment period. So the findings of this study further demonstrated the usefulness of using hypertension to signal bevacizumab treatment in metastatic colorectal cancer. Moreover, it is not surprising to notice that the prediction of bevacizumab-induced hypertension for survival outcomes was age- and gender-dependent. As evidenced, aging-related methylation can influence the gene expression of key control genes in colorectal cancer and adenoma , and horSome limitations deserve special considerations for this meta-analysis. Firstly, only articles published in the English language were identified and the exclusion of gray literature from this meta-analysis can lead to the exaggerated estimates of intervention effectiveness . SecondlTaken together, through a comprehensive analysis of 14 independent studies and 2292 study subjects, our findings indicate that bevacizumab-induced hypertension can predict progress-free survival and overall survival in patients with metastatic colorectal cancer, whereas its prediction for objective response rate was nonsignificant. Meanwhile, several issues from this meta-analysis remain to be clarified, and yet other areas warrant further investigation. If the usefulness of bevacizumab-induced hypertension were successfully validated in the future, it will be clinically important to administrate bevacizumab agents to patients with metastatic colorectal cancer who are more likely to benefit from the treatment.The conduct of this meta-analysis was consistent with the guidelines in the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement .A systematic literature search was conducted in the following electronic bibliographic databases: PubMed (Medline), EMBASE (Excerpta Medica dataBASE) and Web of Science . Search strategy was expressed in the Boolean style, that is,  and (“cancer” or “tumor” or “tumour” or “carcinoma” or “neoplasm”) and (“bevacizumab” or “avastin”) and (“hypertension” or “blood pressure”). The literature search was completed on February 17, 2018. The reference lists of two previous meta-analyses ,17 and rArticles were retained for analysis pending the simultaneous satisfaction of following criteria: (i) metastatic colorectal cancer patients receiving bevacizumab treatment were grouped according to the presence or severity of hypertension determined by the Common Terminology Criteria for Adverse Events (CTC AE); (ii) information on objective response rate or its associated odds ratio, or hazard ratio for progression-free survival or overall survival, or survival curves was available for extraction or inference; (iii) articles were written in the English language. Meanwhile, conference abstract, case report or case series, review or meta-analysis, basic medical research and phase I clinical trial were not included in this study.Two investigators (Chun-Jing Zhang and Shu-Ying Zhang) of this present study independently assessed the eligibility of all potential articles according to above criteria. A third investigator (Hai-Tao Yu) solved the disagreements, if exist, from literature screening.The following variables were extracted from each eligible article: the first author’s surname, published year, country where study was conducted, CTC AE version, combined chemotherapy, bevacizumab dose, age, gender, metastatic position of metastatic colorectal cancer, objective response rate, progression-free survival, overall survival, odds ratio (95% CI) and hazard ratio (95% CI). Survival rate was used to estimate progression-free survival or overall survival from survival curves in case of no available risk estimates by aid of the Engauge Digitizer software Release 4.0.Data extraction was independently completed by two investigators (Chun-Jing Zhang and Shu-Ying Zhang) of the present study, and a third investigator (Hai-Tao Yu) checked table entries for accuracy by referring to original context.According to a previous publication , trial sOdds ratio and its 95% CI for objective response rate, as well as hazard ratio and its 95% CI for progression-free survival or overall survival were calculated between metastatic colorectal cancer patients with and without bevacizumab-induced hypertension.From a statistical standpoint, in the absence of between-study heterogeneity, effect estimates based on the fixed-effects model and the random-effects model are exactly the same, whereas in the presence of heterogeneity, effect estimates are more reliable based on the random-effects model, relative to the fixed-effects model. Thus, in this meta-analysis, random-effects model using the DerSimonian & Laird method ,41 was uI2) on the basis of the Cochrane Q-test. Heterogeneity is reported to be low if I2 ranges from 0% to 25%, moderate from 25% to 75% and high from 75% to 100% [Between-study heterogeneity was quantified using the inconsistency index ( to 100% .Regardless of the magnitude of heterogeneity, subgroup analysis and meta-regression analysis were conducted to assess the impact of categorical and continuous study variables on the overall heterogeneity.The presence of publication bias, the bias resulting from the possibly unpublished studies due to the negative results or extreme deviations from previous results, was visually appraised by filled funnel plots. The statistical evidence of publication bias was assessed by the Egger’s test, a weighted regression test that can help justify the asymmetry of funnel plots. In case of evident publication bias, a trim and fill method was employed to derive an unbiased estimate after considering potentially missing studies. In addition, to evaluate whether later studies impacted previous studies, a cumulative meta-analysis was conducted accordingly.Above statistical analyses were completed using the STATA/SE software Release 11.2.Supplementary File


Smoking-DNAm scores were positively associated with self-reported smoking status  and smoking pack years . Higher smoking DNAm scores were associated with variables related to poorer cognitive function, structural brain integrity, physical health, and psychosocial health. Compared with phenotypic smoking, the methylation marker provided stronger associations with all of the cognitive function scores, especially visuospatial ability  and processing speed ; inflammatory markers ; dietary patterns  and traditional diet ; stroke ; mortality , and at age 73; with MRI volumetric measures . Additionally, education was the most important life-course predictor of lifetime smoking tested. Our results suggest that a smoking-associated methylation biomarker typically explains a greater proportion of the variance in some smoking-related morbidities in older adults, than phenotypic measures of smoking exposure, with some of the accounted-for variance being independent of phenotypic smoking status.Recent advances in genome-wide DNA methylation (DNAm) profiling for smoking behaviour have given rise to a new, molecular biomarker of smoking exposure. It is unclear whether a smoking-associated DNAm (epigenetic) score has predictive value for ageing-related health outcomes which is independent of contributions from self-reported (phenotypic) smoking measures. Blood DNA methylation levels were measured in 895 adults aged 70 years in the Lothian Birth Cohort 1936 (LBC1936) study using the Illumina 450K assay. A DNA methylation score based on 230 CpGs was used as a proxy for smoking exposure. Associations between smoking variables and health outcomes at age 70 were modelled using general linear modelling (ANCOVA) and logistic regression. Additional analyses of smoking with brain MRI measures at age 73 ( Understanding the mechanisms by which smoking predisposes individuals to chronic disease is crucial for the provision of therapeutic targets4, yet they are not well understood. Differential DNA methylation (DNAm) has been proposed as one possible partial explanation, which also could mean that these changes could act as a biomarker of smoking exposure. The possible attraction of a DNAm-based marker for smoking exposure lies in part with the limitations of other ways of quantifying smoking exposure. Analyses are usually dependent on self-report data, such as smoking status and pack years, which are prone to underestimation and reporting biases5. Cotinine, a metabolite of nicotine, is a widely used biomarker, but due to a half-life of around 15–20 h, it reflects only short-term exposure to smoke6.Smoking is an exposure with broad and well-characterised adverse health effects. Smoking-associated death and disability remains a major global public health problem7 and cancer8. Although these studies show a trend for more cardiovascular events and cancer in active smokers, they have failed to find a significant dose-dependent correlation between risk, and the number of cigarettes smoked or the pack-years of exposure. This suggests that phenotypic measures of smoking are unable to capture the relevant smoking-related variance  that relates to disease risk. These limitations underline the need for an objective measure of smoking exposure for precise classification in epidemiological studies. A better biomarker of smoking could also increase the effectiveness of interventions.Whether there is a direct dose-dependent association between smoking exposure and disease is debatable, as some studies have shown a non-linear relation with diseases such as coronary heart disease9. DNAm is an epigenetic modification of the DNA molecule without altering the DNA sequence itself10. Epigenetic modifications are increasingly recognised as key mechanisms involved in response to environmental stimuli11, such as smoking, and in smoking-induced disease onset17. Smoking is robustly associated with highly specific DNAm changes at specific loci across the genome (occurring mainly at CpG—cytosine-phosphate-guanine—sites), which not only clearly distinguish between current and never smokers, but may also reflect the cumulative amount smoked, and time since quitting in former smokers21. In the majority of loci, smoking induces hypomethylation (loss of methylation)24. Recent evidence suggests that smoking-related DNAm changes occur after prolonged exposure to smoke (5–9 years for heavy smokers and 15–19 years for lighter smokers) and that these dose-dependent changes are reversible following cessation19.Smoking contributes to disease development and progression through genetic and epigenetic mechanisms31. Differentially methylated loci with respect to smoking are related to clinical outcomes. Robust associations have been demonstrated between smoking-methylation signatures and major diseases including asthma32, COPD33, and lung cancer34, and markers of physical health, including lung function and periodontal disease28. Decreased methylation levels in the aryl hydrocarbon receptor repressor (AHRR) gene was found in the lung tissue of current smokers compared with non-smokers35. Smoking associated DNAm has also been shown to predict mortality across several studies, including a Scottish sample36, in coronary heart disease patients37, and in the ESTHER study in which a smoking-related DNAm score based on two CpGs (cg05575921 and cg06126421) showed strong associations with all-cause, cardiovascular, and cancer mortality38.Advances in epigenome-wide profiling of DNAm patterns associated with smoking have given rise to a new molecular biomarker or ‘epigenetic signature’ (epigenetic patterns detected in blood) of lifetime smoking exposure, with the potential to improve the prediction of smoking-related risks38. Although several studies have examined smoking-related DNAm in relation to a specific outcome such as mortality22, see refs. 31, comparisons of the predictive value of epigenetic versus phenotypic smoking measures has never been performed simultaneously in the same sample, and for a range of health outcomes.One previous study examined the relationships between self-reported smoking, serum cotinine and smoking-associated DNAm, and found that the smoking measures were correlated, and that the methylation marker was superior in measuring long-term smoking exposure based on its ability to discriminate between former smokers and never smokers with high accuracyHere, we extend previous work by examining associations between smoking-associated changes in DNA methylation (smoking-DNAm scores), phenotypic smoking measures (current smoking status and pack years of smoking), and a comprehensive range of smoking-related health outcomes. We, (1) determine the proportion of variance the epigenetic and phenotypic predictors explain in their outcomes, (2) examine whether the smoking methylation marker accounts for variance in these outcome variables independently of the standard phenotypic smoking measures, and, (3) examine the life-course predictors of epigenetic and phenotypic smoking. The sample is a narrow-age cohort of older adults aged ~70 years at baseline, for whom there are extensive phenotypic data.41. Most participants had previously taken part in the Scottish Mental Survey of 1947 (SMS194742) at about age 11 years (from which we derived an age 11 IQ score), and subsequently traced and recruited to the study almost 60 years later, at approximately 70 years of age. Briefly, individuals born in 1936, who were living in the Lothian area of Scotland, were contacted by Lothian Health Board on behalf of the investigators and invited to take part in the study. In total, 1091 men and women were recruited at Wave 1  with further follow-up waves at ages 73 (n = 866), 76 (n = 697), 79 (n = 550) and 82 (ongoing). Extensive phenotypic data have been collected, including blood biomarkers, cognitive testing, neuroimaging, and psychosocial, lifestyle, genetic, and health measures. All participants provided written informed consent before testing. The LBC1936 study was approved by the Multi-Centre Research Ethics Committee for Scotland (MREC/01/0/56) and the Lothian Research Ethics Committee (LREC/2003/2/29 for Wave 1 and 07/MRE00/58 for Waves 2–5).Participants were from the Lothian Birth Cohort 1936 (LBC1936), a group of relatively heathy community-dwelling subjects in their seventies, enrolled in a longitudinal study of cognitive and brain ageing conducted in ScotlandMost of data for the present study come from Wave 1 (age 70). Structural brain imaging was undertaken three years later for 700 participants at Wave 2 (age 73). Here, a total of 895 individuals had smoking-DNAm data at age 70, and of the 895, 532 had MRI data at age 73. Following quality control which removed instances in which aberrant surfaces or segmentation errors were removed, additional analyses of cortical thickness were run for 521 participants.n = 1091) assessment by trained research nurses using standard procedures, at the Wellcome Trust Clinical Research Facility Genetics Core at the Western General Hospital, Edinburgh. Of the 1091 LBC1936 participants, 1005 who had previously passed GWAS quality control were selected for methylation typing. Of these, 920 passed DNAm quality control. Due to missingness of measured cell counts (n = 14) and missing phenotype data (n = 11), this number dropped to the 895 that were included in the current analyses. DNAm typing was measured at 485,512 CpG sites using the Illumina Human Methylation450 Bead Chip . Full details of sample preparation and methylation typing have been reported previously43. Briefly, after background correction, probes were removed if they were poorly detected (P > 0.01) in >5% of samples or of low quality . Samples were removed if they had a low call rate (P < 0.01 for <95% of probes), a poor match between genotype and SNP control probes, or incorrect DNAm-predicted sex.Blood samples were obtained at the time of Wave 1 baseline  were created19. As pack years are positively coded, a higher methylation score indicates more smoking.A LASSO regression was performed to predict pack years of smoking on 3444 participants  from the Generation Scotland studySelf-report smoking status  and smoking behaviour  were ascertained at age 70 during a baseline interview. Pack years were calculated as the average number of cigarettes per day times years as a smoker, divided by 20, with zero assigned to never smokers. Pack years expresses lifelong exposure to cigarettes. Cotinine data were not available in the LBC1936.44.Sociodemographic measures were education , deprivation score at age 11 , and adult occupational social class 45. MHT scores were corrected for age in days at time of testing and converted to standard IQ type scores, where mean = 100 and SD = 15. This is a general mental test comprising 71 items, mostly verbal reasoning, but also some numerical, spatial, and other items. Cognitive function measures at age 70 were age 70 IQ (the same test taken at age 11), the Mini-Mental State Examination46, and four latent scores representing: Visuospatial ability; Processing Speed; Memory; and Crystallised abilities. Visuospatial ability consisted of two subtests from the Wechsler Adult Intelligence Scale, 3rd UK Edition (WAIS-IIIUK47): Matrix Reasoning and Block Design. It also included the Spatial Span (Forward and Backward) subtest from the Wechsler Memory Scale, 3rd UK Edition (WMS-IIIUK48). Processing Speed was measured using two tests from the WAIS-IIIUK (Symbol Search and Digit-Symbol Substitution), Four-Choice Reaction time49, and Inspection Time , and the measure we used was the total number of correct responses50. Memory was measured using two subtests from the WMS-IIIUK , and the Digit Span Backward subtest of the WAIS-IIIUK. Crystallised Ability was measured by two tests that involved the participant reading aloud a list of irregular words: the National Adult Reading Test (NART51), and the Wechsler Test of Adult Reading (WTAR52). We also included a test of phonemic verbal fluency, using the letters C, F, and L53.Cognitive ability from childhood (age 11 IQ) was derived from scores on the Moray House Test no.12 (MHT), a validated test of general intelligence, obtained for the SMS194754. Briefly, a 1.5 T GE Signa HDx clinical scanner  was used to collect structural T1-, T2-, T2*-, and fluid attenuated inversion recovery-weighted images. Total brain volume (TBV), grey matter volume (GMV), white matter hyperintensity volume (WMHV), and normal-appearing white matter volume (NAWMV), are used in the present study. Measures were adjusted for intracranial volume (ICV) to control for head size. In addition, regional brain cortical thickness data were measured using FreeSurfer v5.1. Cortical thickness denotes the closest distance from the brain’s grey-white matter boundary to the grey-CSF boundary at each of 327,684 vertices. The sample lag between baseline assessment and MRI assessment was relatively small. That the phenotypic and epigenetic smoking variables were measured at the same time is more important for the purposes of comparison, i.e. the increased noise in the signal introduced by sampling lag is likely to be constant, and therefore unlikely to affect the relative differences in their magnitude.Brain structural MRI was first performed 3-years after baseline (when participants were ~age 73 years. Brain MRI acquisition and processing has been reported previously2). All measures were taken at time of assessment by trained nurses.Physical function measures were: lung function (forced expiratory volume in one second FEV1) based on the highest score from three tests using a Micro Medical Spriometer); grip strength (based on the highest reading from the right hand using a North Coast Hydraulic Hand Dynamometer (JAMAR); walking speed ; and body mass index (BMI) derived from height and weight ; inflammation (C-reactive protein (CRP), fibrinogen), and glycaemic status (glycated haemoglobin (HbA1c)). Serum cholesterol (mmol/L) was measured via non-fasting blood and analysed within 24 h in serum stored at 4 °C using an enzymatic Quinoneimine dye method measuring at 500 nm. The CRP (mg/L) assay was performed using a dry-slide immuno-rate method on OrthoFusion 5.1 F.S analysers . The fibrinogen (g/L) assay was performed using an automated Clauss assay .55), and the WHOQoL .Psychosocial measures were the HADS . Dietary pattern scores were obtained previously via principal components analysis of all FFQ items (see ref. 58), and include: Mediterranean-style diet; Health-aware diet; Traditional diet; Sweet-foods diet.Health behaviour data, including alcohol intake (units/week) and dietary intake (dietary pattern scores), were derived from responses to a food frequency questionnaire (FFQBinary variables relating to self-reported disease history include: cardiovascular disease (CVD); hypertension; diabetes; hypercholesterolaemia; and stroke. Deaths during follow-up (between 2004 and 2018) were identified by record linkage and coded as yes/no.59. General linear modelling (ANCOVA) was used to investigate the associations between smoking measures (smoking-DNAm and phenotypic) and continuous outcome variables. An additive model included both smoking status and smoking-DNAm together. Logistic regression was used to investigate the associations between smoking and binary health variables (disease/no disease), namely: CVD; hypertension; high cholesterol; stroke; and, diabetes. The relationship between each smoking exposure and all-cause mortality was assessed using Cox proportional hazards models. We note that smoking-phenotypic associations with brain cortical thickness have been previously reported in this sample60 and are shown here for comparison with DNAm-smoking associations.The majority of the data used in the current study were collected at baseline (age ~70 years). MRI was performed age 73. Three-year stability in imaging markers in this cohort has been previously ascertainedTo examine the associations between life-course predictors of smoking in later life, we entered four life-course measures  into models, simultaneously, with smoking status (using logistic regression) and smoking-DNAm . We ran a series of path models within a structural equation modelling framework to assess the degree to which early-life factors (age 11 IQ and childhood deprivation) contributed to phenotypic and epigenetic smoking measures in later life, and whether their associations were mediated via years of education and adult SES-occupation. Specifically, we modelled the contributions of both childhood deprivation and childhood intelligence on education and adult SES, with the variables in a life-course order, and allowing a residual correlation between these two early-life factors. Contributions of all four predictors were modelled on smoking category and DNAm-smoking; that is, we fitted two models, one for each separate smoking outcome. The numerical values in the models’ results are standardised path coefficients, which may be treated like standardised partial beta weights.p-values were corrected for multiple comparisons using the false discovery rate (FDR) with an FDR corrected p-value ≤ 0.024 considered significant. We report partial-eta squared (ηp2) effect sizes for ANCOVA models (to derive % variance explained) and R2, and odds ratios (OR) and 95% confidence intervals (95% CI) for logistic regression models. We report hazard ratios for associations between smoking and mortality using Cox proportional hazards regression. Most analyses were carried out using SPSS version 22. The brain cortical thickness linear regression analyses were conducted using the SurfStat toolbox (http://www.math.mcgill.ca/keith/surfstat) for Matrix Laboratory R2018a . The path analyses were implemented using structural equation modelling which was conducted using ‘lavaan’ in R version 3.5.061.All models were adjusted for age (exact age in days at time of testing) and sex. Height was included as an additional covariate in the models for FEV1, grip strength, and walking speed. All r = 0.69 (P < 0.001). There was a significant association between DNAm and self-reported smoking status  = 764.03, P < 0.001, ɳ2 = 0.63). Thus, 63% of the variance in smoking-DNAm scores can be explained by phenotypic smoking status. The smoking DNAm values (mean ± sd) for never smokers was 3.08 ± 0.35, for former smokers was 3.71 ± 0.68, and for current smokers was 5.48 ± 0.74.Higher scores on the smoking-DNAm marker were strongly associated with higher self-reported smoking exposure. The Spearman correlation between DNAm scores and smoking pack years was n = 895) by current smoking status. Of the total sample, 418 (47%) were self-reported never smokers, 375 (42%) were former smokers, and 102 (11%) were current smokers. The mean age of participants was 69.5 years (sd 0.8). Never smokers were more likely to be female and, compared with ever smokers, consumed less alcohol, had a higher childhood IQ and more education, and had fewer cases of CVD, and diabetes. Average pack years (cumulative smoking exposure) of current smokers was 45.0 and former smokers was 27.5. Current smokers had the highest prevalence of stroke and the lowest physical activity. Former smokers had the highest prevalence of CVD and diabetes, the highest BMI, alcohol consumption, and were most physically active. Over 14 years of follow-up, there were 224 (25%) deaths from 895 participants; 51% of current smokers at baseline had died, compared to 27% of former smokers and 17% of never smokers.Table Table Figure Higher smoking-DNAm scores were associated with markers of poorer physical function and health: lower lung function FEV1 (1.3%); slower 6-m walk time (1.4%); higher BMI (0.7%); higher triglycerides (1.7%); higher CRP (2.1%) and fibrinogen (3.0%). DNAm was not associated with grip strength, total cholesterol, HDL cholesterol, or HbA1c. Higher smoking-DNAm scores were associated with lower psychosocial health , and with poorer dietary patterns . DNAm was also associated with lower quality of life on all of the domains tested; following correction for multiple testing, DNAm remained significantly associated with the WHOQoL Physical and Environment domains, accounting for 1.75 and 2.4% in these outcomes, respectively.P = 0.006) and hypercholesterolaemia . Using Cox’s proportional hazards models, we observed a higher all-cause mortality risk . A positive association with mortality risk  has previously been shown in the LBC1936, over a slightly shorter (12 year) follow-up period36. Here, we showed that smoking-DNAm accounts for a proportion of the variance in stroke and mortality outcomes, which is independent of phenotypic smoking status.Table Compared with the phenotypic smoking measures epigenetic smoking accounted for a greater proportion of the variance for many of the significant smoking-health associations , and for higher pack years . Higher pack years was associated with hypercholesterolaemia  (see Table P = 0.012). Associations of phenotypic smoking with CVD became non-significant following correction for multiple testing. Higher mortality risk over 14 years of follow-up was associated with higher pack years of smoking . Compared with never smokers, we found a higher mortality risk in former smokers , and current smokers .Compared with smoking-DNAm scores, the phenotypic smoking measures were generally stronger predictors of the psychosocial measures. We report higher effect sizes for phenotypic smoking and HADS-Depression score and all four quality of life subdomains of the WHOQOL). Both phenotypic smoking variables were associated with a higher prevalence of stroke , and epigenetic score simultaneously in order to examine whether the R2 was better than in the single predictor models. In none of the models were both predictors significantly associated with an outcome variable. For ten of the additive models, the smoking epigenetic score remained a significant predictor of health outcome measures even after smoking status was included. We report % variance accounted for in the outcome measure. These measures included processing speed (1.0%), crystallised ability (0.7%), structural brain MRI markers (range 1.2% to 2.1%), lung function FEV1 (3.0%), fibrinogen concentrations (0.9%), healthy diet pattern (1.5%) and traditional diet pattern (1.6%) , and all-cause mortality risk  .Phenotypic smoking category remained a significant predictor, after DNAm smoking was included in the additive models, for BMI (2.5%), all of the WHOQoL measures (range 1.3–1.8%), alcohol intake (1.1%), physical activity (1.1%), and diabetes, for ex-smokers only, , with the exception of adult SES, which was significant only for current smoking .Table Finally, path models were fit, using SEM, for each of the smoking outcome measures in order to examine the strength of associations between the life-course predictors and lifetime smoking behaviour, and to test whether any early-life associations were mediated via education and adult occupational status. The path diagrams are presented in Fig. Using genome-wide DNAm values from the Illumina 450 K platform, we created a DNm biomarker of smoking and examined its ability to predict multiple smoking-associated adverse health outcomes in a healthy ageing cohort, the LBC1936. We found that higher smoking-DNAm scores were cross-sectionally associated with poorer cognitive function, physical function, psychosocial health, blood biomarkers of health, diet, and with markers of structural brain health measured at follow-up. Our analyses also showed that epigenetic signatures of smoking were associated with stroke, hypercholesterolaemia, and with a higher mortality rate after 14 years. The novel findings in the current study are, firstly, the epigenetic biomarker of smoking explained a greater proportion of the variance in many smoking-related morbidities than phenotypic smoking. The largest effect sizes for the methylation marker were observed for measures of cognitive function, structural brain integrity, lung function (FEV1), systemic inflammation, and mortality. Secondly, by combining the methylation predictor and self-reported smoking predictor in an additive model, we demonstrated that some of the accounted-for variance was independent of phenotypic smoking status. These findings support the predictive utility of a smoking-associated DNAm score compared with more traditionally used markers of smoking exposure for assessing smoking-related health risks. To our knowledge, this is the first study to compare the predictive capabilities of smoking-DNAm scores and conventional phenotypic self-report measures of smoking exposure, over a wide range of health-related outcomes, and in the same sample.62. These data likely result in an underestimation of true effects25. Methylation derived scores reflect the cumulative physiological effects of smoking, compared with cotinine—an already present serological marker of smoking—which exclusively measures short-term exposure. Research into the distribution of methylation changes by time since smoking cessation, found that for many CpGs, methylation levels reverted back to levels of never smokers, but for some CpGs, hypo- and hypermethylation were still present 30–40 years after quitting63. Given the age of LBC1936 participants, most of whom were in their eighth decade at time of testing, smoking DNAm is a more informative and sensitive biomarker of lifetime smoking. As such, this objective, blood-based biomarker is more desirable for accurate evaluation and stratification of smoking-related disease risk, and has the potential to validate self-reports of smoking behaviour. Of prime importance is that, even in cohorts which have not collected phenotypic data on smoking, a DNAm-based measure can be used as a proxy for smoking exposure.Quantification of smoking behaviour in epidemiologic studies, for the purposes of assessing smoking-attributable risk, is typically derived from questionnaire-based metrics of current and past smoking. Pack years is the most commonly used measure of smoking intensity. However, self-reported smoking data are hampered by recall bias, and as a socially undesirable behaviour, they are subject to under-reporting64 and our results suggest that this biomarker may improve the ability to capture the deleterious effects of smoking exposure across major ageing-related domains of cognitive function, and provide valuable clues to disease pathways. The authors are unaware of any previous research to examine the link between smoking-associated DNAm and risk of cognitive decline but note that the precise regulation of DNAm is essential for normal cognitive function66. DNAm changes have been linked with the pathophysiology of brain ageing, Alzheimer’s Disease and other types of dementia67.In the current study, which benefits from a comprehensive assessment of cognitive function, the methylation-based biomarker of smoking better predicted deficiencies in visuospatial function and processing speed than either phenotypic measure (self-reported smoking status or pack years). Smoking is a well-established risk factor for cognitive decline68, cortical thinning60 (using the present sample), white matter hyperintensities69, reduced GMV70, and atrophy71. In a large UK Biobank study, pack years of smoking was related to a range of brain MRI measures including higher WMH volume, lower global and regional GMV, poorer white matter microstructure and lower subcortical volumes72. These structural MRI measures have been linked to an increased risk for dementia73. Differential brain structural measures, such as we observed here with higher DNAm, including lower overall brain volume, smaller GMV, reduced white matter integrity, increased WMHV, and greater cortical thinning, could indicate an effect of chronic nicotine exposure on pathological brain changes74. However, smoking-associated DNAm accounted for around double the proportion of variance in some of these brain volume measures compared with pack years, suggesting that a dose-response effect of lifetime nicotine exposure is less likely to be a cause, and rather, that DNAm better captures the neurological impact of chronic smoking.We also observed that the epigenetic smoking score was a better predictor of decreased structural brain integrity in older age than the phenotypic markers of smoking. The strength of the associations between DNAm and brain MRI indices—accounting for between 3 and 5% of the variance in structural deficits such as reduced white matter integrity and cortical thinning—were striking given the time lag in measurement between baseline and MRI assessment. Moreover, that the smoking DNAm predictor explained variance in brain health independently of phenotypic smoking (in the additive model) may suggest that the methylation signatures are capturing additional effects of smoking which have neurobiological consequences. Previous neuroimaging studies have demonstrated widespread structural brain abnormalities in cigarette smokers, including ventricular enlargement77. In addition to cognitive and brain health, we also observed that smoking DNAm was a strong predictor of inflammatory marker concentrations, hypercholesterolaemia, stroke, and with all-cause mortality after 14 years.A number of novel smoking-DNAm biomarkers have been identified in recent years, using epigenome-wide association studies, which have been shown to be highly predictive for smoking-related health outcomes such as cancer and mortality78. Smokers have higher levels of CRP and Interleukin-6 (IL-6), but less is known about how epigenetic variation such as DNAm, correlates with chronic inflammation concentrations. Ligthart et al.79 performed a meta-analysis of EWAS of CRP and reported strong correlations with 58 methylation sites, and other studies report similar findings with other serum cytokines including IL-6 and tumour necrosis factor (TNF)80. Smoking-associated DNAm changes have previously been found in genes involved in inflammatory networks81 but the link between the epigenetic impact of smoking and inflammatory marker concentrations has not yet been evaluated in population studies. Given the crucial functions that inflammation has in brain ageing, neurodegeneration, and disease, it is important to discern whether smoking is driving the inflammatory response or whether this association is confounded by chronic disease.We found that the smoking epigenetic score explained 2–3% of the variation in circulating CRP and fibrinogen. Smoking has a systemic impact and induces the release of pro-inflammatory markers82. In the current study, all three smoking measures were associated with a history of stroke, and the risk of stroke among those still smoking into their seventies, was over three times that of lifelong non-smokers, and in those with higher smoking DNA-methylation values. In the LBC1936 sample, neither epigenetic smoking nor phenotypic smoking variables were significant predictors of cardiovascular disease, a well-established health effect of prolonged smoking exposure. This in contrast with many previous studies which report associations between differential DNAm with smoking exposure, and various coronary artery diseases76.Cigarette smokers are three to four times more likely to have a stroke83, and differential methylation associated with smoking has been suggested as a potential mechanism. Zhang et al. reported clear dose-response relationships between smoking-related DNAm and mortality30, and in a further study, developed a biomarker strongly associated with all-cause mortality, cardiovascular, and cancer mortality31. Our results strongly support an increased risk of early death with smoking-associated DNm , and we showed that current smokers had a fourfold increase in risk of death compared with lifelong non-smokers. Over half the current smokers at baseline (age 70) had died by follow-up approximately 14 years later, compared with 27% of ex-smokers, and 17% of never smokers. Smoking is associated with other unhealthy behaviours86, and lifestyle factors are associated with poorer health and mortality87. Here, we also observed significantly poorer dietary habits in those with higher smoking-DNAm values. To a lesser extent, poorer psychosocial health was observed in those with higher DNAm values in terms of lower quality of life associated with one’s physical health and environment.On average, smokers die 13–14 years earlier than do non-smokers92. Early-life exposures (including those associated with SES) during sensitive periods may be stored in cells through epigenetic modifications that can be sustained for decades94. It is plausible that the accumulation of environmental exposures across the lifespan, contributes to epigenetic change with age. An alternative explanation could be that early-life factors, including low childhood IQ/high deprivation, leads to increased smoking uptake. Smoking is a strongly social-patterned risk factor; it is more prevalent among those with lower incomes and its association with economic, occupational and educational levels is well documented95. In epidemiological studies, it is often unclear whether the observed associations are true associations between epigenetic smoking signatures and poor health, or whether the associations are influenced by the socioeconomic path of an individual across the life-course, i.e., the result of poorer people ageing faster than more affluent people due to the unhealthy environments to which they are exposed96.Interestingly, the epigenetic signatures of smoking at age 70 were associated with factors from early life, such as childhood deprivation, childhood cognitive function, and educational level. Furthermore, we showed that the variance explained by these childhood factors in smoking behaviour, were independent of phenotypic smoking. Previous studies have suggested that environmental influences including adversity in childhood have been linked with stable DNAm differences that persist into adulthood97. However, the causal pathways between education and smoking are complex and subject to confounding from social networks, risk preferences and other factors. In addition, the initiation of regular smoking generally occurs before the completion of education. On the other hand, support for educational gradients in smoking come from those who argue that more schooling leads to the acquisition of important skills and resources that impact health management98.It is important to understand the life-course influences on such an important health-related variable as smoking, and we rarely have so many relevant, well-measured variables in one sample, across most of the human life-course. The LBC1936 study is relatively rare in having a direct measure of IQ from youth, multiple childhood deprivation data, education, and adult SES, especially in combination with both self-reported smoking and epigenetic smoking data. As far as the authors are aware, there have been no studies to date which have examined both childhood and adult SES influences, on smoking DNAm patterns. The results of the current study suggest that individual differences in smoking behaviour in later life, are best explained by education level rather than other life-course predictors. This finding supports previous studies that suggest education is the SES indicator that shows the greatest disparity in smoking outcomesThe key strengths of our study include the use of a wide  array of traits examined in relation to smoking in a large single, narrow-age cohort study with DNAm. Given the age of participants, the DNAm score for smoking was based on many years of exposure, and is likely to be a more sensitive marker than in younger cohorts. Future analyses of longitudinal changes in smoking-DNAm in the LBC1936 are possible given that the study is ongoing. In terms of limitations, we must consider the causative versus correlative role of DNAm with respect to its relationship with age. It may be that the common changes in age-related epigenetic mechanisms across individuals are important contributors to the ageing process, rather than a consequence. Cotinine data were not available for this cohort, and therefore we were unable to compare the predictive capability of smoking DNAm with another smoking biomarker, or to validate self-reports of non-smoking. However, a single measure of cotinine concentrations is insufficient to reclassify participants into smoking categories given that it measures recent smoking only (previous 15–20 h), and LBC1936 participants (many of whom did not smoke daily) who refrained from smoking on the day of assessment or the day before, would have misleading data. Finally, the cross-sectional nature of the majority of our analyses limits our ability to make causal inferences and to study the time course of smoking effects. To that end, future studies with longitudinal data would be desirable to extend these findings in the current sample, and in other datasets, may partially explain the variable susceptibility to the health effects of cigarette smoking.Our study supports the potential utility of a smoking DNAm score, derived from genome-wide data, as a biomarker of lifetime smoking exposure, and for contributing toward the prediction of important ageing-related health outcomes in later life. In particular, the smoking methylation biomarker better predicted poorer cognitive function and brain structural integrity, chronic inflammation, stroke and mortality in later life, compared with much-used phenotypic measures of smoking. It may help to identify novel health impacts, improve adjustment for smoking in research studies, and shed light on the molecular mechanisms by which smoking predisposes to chronic mental and physical disease, and less good brain and cognitive health. In terms of clinical impacts, a methylation marker holds promise for better risk prediction in precision medicine. A useful implication of the present study is that it suggests that one may obtain an indication of smoking exposure and its implications even in studies which have not collected smoking data.


High-precision radiotherapy has been established as a valid and effective treatment option in patients with pituitary adenomas. We report on outcome after fractionated stereotactic radiotherapy (FSRT) in correlation with patient-reported outcomes (PROs). We analyzed 69 patients treated between 2000 and 2019. FSRT was delivered with a median total dose of 54 Gy (single fraction: 1.8 Gy). PRO questionnaires were sent to 28 patients. Median overall survival was 17.2 years; mean local control was 15.6 years (median not reached). Median follow-up was 5.8 years. Twenty (71%) patients participated in the PRO assessment. Physicians reported symptoms grade ≥3 in 6 cases (9%). Of all, 35 (51%) patients suffered from hypopituitarism at baseline, and during follow-up, new or progressive hypopituitarism was observed in 11 cases (16%). Patients reported 10 cases of severe side effects. Most of these symptoms were already graded as CTCAE (Common Terminology Criteria for Adverse Events) grade 2 by a physician in a previous follow-up exam. PROs are an essential measure and only correlate to a certain extent with the physician-reported outcomes. For high-precision radiotherapy of pituitary adenomas, they confirm excellent overall outcomes and low toxicity. In the future, the integration of PROs paired with high-end treatment will further improve outcomes. Pituitary adenomas are benign neoplasms of the anterior pituitary gland. These lesions account for approximately 10–15% of all intracranial neoplasms  and are Generally, treatment of pituitary adenomas is intricate and depends on the size, anatomical extension, secreting or non-secreting nature, as well as patient performance status and patient’s preference. Since the incidence of pituitary adenomas is comparably low, patients should be assigned to specialized centers offering advanced neurosurgery, experienced endocrinology, as well as advanced radiotherapy (RT) expertise ,9,10,11.The pharmacological approach is another cornerstone in the management of functioning adenomas: Dopamine antagonists such as cabergoline or bromocriptine have anti-tumor effects and are first-line treatments for prolactinomas, and somatostatin analogons like octreotide are applied for somatotroph adenomas secondary to surgery or RT with persistently elevated hormone levels . Other dStereotactic radiosurgery (SRS) or fractionated stereotactic radiotherapy (FSRT) have been established as a valid and highly effective treatment option in patients with pituitary adenomas. The concern of long-term side effects has been the main argument against early RT; however, since SRS and FSRT are available in increasing specialized centers, long-term data are becoming available, demonstrating excellent outcomes ,17,18,19Indication for RT is generally seen for tumor progression if surgical resection is not feasible or has been performed several times, followed by tumor recurrence. Additionally, partial resection can be an indication for RT, especially if the tumor remnant is progressive. In hormone-secreting adenomas, RT is indicated for persistent hormonal secretion even after macroscopic total resection. High-precision RT offers the benefit of high local dose deposition and sparing of healthy tissue. Excellent results have been reported with SRS for smaller lesions, and with FSRT for larger and complex lesions ,20,21. VTo date, all clinical results reported include toxicity but not patient-reported outcomes (PRO), which are becoming more and more relevant since modern documentation methods and advanced communication with patients via online tools such as app-based and web-based become available ,29,30,31The present study aims to analyze overall survival (OS) and local control (LC) after high precision photon RT, as well as long-term toxicity rates after treatment. It is one of the first studies reporting outcomes in correlation with PRO up to 17 years after treatment, and therefore complements the existing literature with novel data.We analyzed 69 patients with pituitary adenoma consecutively treated between 2000 and 2019 at the Department of Radiation Oncology at the Klinikum rechts der Isar, Munich. Exclusion criteria were early termination of treatment or re-irradiation due to local recurrence. Patient data were collected prospectively and documented in the institutional database. For patient characteristics, see The local ethics committee of the Medical Faculty of the Technical University Munich (TUM) approved the study, vote number 407/19 S (NOSY Study).All patients were resected at least once during their treatment period. Primary radiotherapy was delivered postoperatively in an additive setting in 12 (17%) cases, and the other 57 (83%) were treated due to recurrent tumor growth. Treatment planning was performed using a stereotactic treatment setup with a thermoplastic mask system  by robotic ExacTrac positioning . An advanced radiation oncologist delineated gross tumor volume (GTV) on contrast-enhanced computed tomography (CT) and fused T1-weighted magnetic resonance imaging MRI. The clinical target volume (CTV) resulted from the GTV with an additional margin of 1–2 mm. Another 1–2 mm were added for the planning target volume (PTV). We performed a linear accelerator-based high-precision fractionated stereotactic radiotherapy (FSRT) with a median total dose of 54 Gy (range: 45–54 Gy) to the 95%-isodose level in single fractions of 1.8 Gy. Patients were treated five times a week, with daily image-guidance (IGRT).Clinical neurological assessment, including contrast-enhanced MRI, was scheduled initially 4–6 weeks after treatment. Patients were monitored every 3–6 months in the first year and then annually in the years thereafter, or earlier in case of new symptoms or recurrent tumor on follow-up imaging. Toxicity before and after RT was rated according to the Common Terminology Criteria for Adverse Events .As pituitary adenomas are benign, patients tend to get lost to follow-up as they feel healthy and have no more symptoms. We established a PRO assessment via mail to gain long-term information ,28. At tLocal failure was defined as re-growth of the original tumor confirmed on MRI by a senior neuroradiologist. Salvage treatment was re-resection or re-irradiation based on interdisciplinary consent in the neurooncology board. Statistical calculations were performed using SPSS Statistics v25 . We calculated OS from the end of treatment until death or last follow-up, and LC from the end of treatment until the date of local failure or until death or last follow-up. Outcome analyses were based on the Kaplan–Meier and Cox regression methods.p = 0.962, LC: p = 0.576) or RT type . None of the patients developed a histopathological change to malignant pituitary disease after irradiation.At the time of analysis, 16 (23%) patients were deceased. Reasons for death were not evaluated. Median OSwas 17.2 years : 9.0–25.4). Local failure was reported in 6 (9%) cases and resulted in a mean LC of 15.6 years , see Median follow-up was 5.8 years (range: 0.1–17.4 years). We contacted 28 patients for PRO assessment, of which 20 (71%) participated via mail. The median time between treatment and PRO was 13.3 years (range: 5.3–17.4 years).PRO data are listed separately and not included in the physician-reported toxicity. Long-term evaluation of high-precision RT as FSRT demonstrates excellent local control; treatment outcome is well tolerated by all patients, which is in part due to very low side effects. PROs confirm convincing long-term outcomes and low side effects. For the first time, this analysis reports PROs for high-precision RT of patients with pituitary lesions.Generally, interdisciplinary discussion of patients with pituitary tumors is necessary. While neurosurgical resection remains to be the mainstay of treatment, outcome data from stereotactic radiotherapy delivered as SRS or FSRT convincingly and reproducibly show excellent outcomes in terms of local control and toxicity.In the present study, we found a 5-year and 10-year LC of 92% and 87%, respectively, which is in accordance with previously published data. While the 5-year local control after FSRT is between 90% and 95%, few groups have reported on long-term outcome. The study reported by Weber and colleagues published 27 patients treated with either adjuvant or radical, with a median follow-up of six years; local control rates were >95% at five years . Sun et In our analyses, we did not find a correlation with hormone functioning and LC or OS. However, Langsenlehner et al. showed inferior local control of non-secreting adenomas . The reaIn a group of 92 patients, improved quality of life (QOL) was reported by 24%, and stabilization of QOL was noted by 68% of all patients . The samWhile FSRT offers the radiobiological benefits of fractionation, several experienced centers argue for radiosurgery in pituitary adenomas. Stereotactic Radiosurgery (SRS) can be delivered either with specialized machines such as the gamma knife or cyberknife system, or with dedicated linear accelerators. Overall, the GKS technology offers the most precise dose deposition with the best sparing of healthy tissue. In a retrospective analysis from three large Korean centers, long-term data of GKS on local control and acromegaly were reported by Kong et al. . The stuIn the present analyses of long-term toxicity, vision loss and visual deficits were the most reported symptoms by both physicians and patients. Physicians reported 27 cases of grade 1/2 symptoms and 5 cases of grade 3. Accordingly, patients reported optic symptoms in 14 cases graded from mild to severe. Considering the close anatomical relation of pituitary tumors to the visual apparatus, including the optic nerves and chiasm, special attention must be given to dose to those organs at risk (OARs). Dose-response modeling has shown that the Dmax should be limited to 12 Gy in 1 fraction based on QUANTEC data , while oDocumentation of long-term side effects remains a challenge, and objective assessment may not correlate with patient-centered assessment. Therefore, PROs are becoming continuously more important in follow-up care due to increasing evidence that tight connection with patients, integration of PRO into care plans, as well as the use of electronic devices such as apps improves outcomes. Recently, Denis et al.  showed iAs with all retrospective analyses, the main problem is heterogeneous and incomplete data. PRO data are also a relevant supplement that leads to greater completeness of data and should not be seen as an alternative. PRO is especially useful in cancer entities were long-term results are of interest and patients are lost to follow-up. In our analysis, the median time between treatment and PRO was 13.3 years. Hence, PRO is an easily applicable tool for long-term follow-up, generating valuable data on QOL and late effects years after RT for pituitary adenomas. In this study, 20 of 28 patients (71%) participated in PRO, implying a fairly high response rate partially many years after treatment. This reflects the favorable course of the disease and long-term preservation of good health of patients with pituitary adenomas treated with RT.The interpretation of PRO data is still difficult. In our study, we saw several symptoms graded as severe by the patients. However, this is not comparable to a CTCAE severe symptom grade 3. The translation of patient-reported and physician-reported symptoms is an existing limitation also in this study . As showVision loss and visual deficits are a severe complication in the treatment of pituitary adenomas, which is luckily a very rare phenomenon in the era of high precision medicine. However, depending on the size of the lesion, pretreatment damage, and other patient-related factors, some visual decline can be possible. In the PRO assessment, we observed six patients who newly reported mild-to-moderate deficits; however, no objective data on eye-sight and visual field were included in the PRO documentation. Any patient reporting on sight deficits should be taken seriously and must be seen by an ophthalmologist, and/or cranial MRI must be performed to rule out a recurrent tumor or other medical conditions. Therefore, the identification of such symptoms early by PRO will help reverse or stop the deterioration of tumor or treatment complications and help identify tumor recurrences very early when symptoms begin to develop. Further long-term symptoms only reported by PRO were cognitive disorders and dizziness. This might be due to the increasing age of patients and not caused by RT treatment. However, prospective studies must be implemented to provide evidence. There is an increasing effort to establish a PRO-CTCAE classification by the National Cancer Institute (NCI) to improve symptom comparison ,44. The The integration of digital information available from computed tomography (CT) and/or MRI may also enable prediction of treatment outcome, identification of early responders, or predictors of treatment failure. Fan et al.  demonstrPROs are an essential measure and only correlate to a certain extent with the physician-reported outcomes. For high-precision RT of pituitary lesions, they confirm excellent overall survival, low recurrence rates, and toxicity. PRO will help to foster patient–physician connection and will lead to early detection of side effects or tumor recurrences when symptoms and/or changes in QOL, patient lifestyle, resilience, and stamina are observed more promptly. In the future, standardized integration of PRO paired with high-end treatment will further improve outcomes and enhance patient care in modern radiation oncology.


Phase-rectified signal averaging (PRSA) was often applied to assess the cardiac vagal modulation. Despite its broad use, this method suffers from the confounding effects of anomalous variants of sinus rhythm. This study aimed to improve the original PRSA method in deceleration capacity (DC) quantification.DCref) was calculated by excluding from non-vagally mediated abnormal variants of sinus rhythms. Holter recordings from 202 healthy subjects and 51 patients with end-stage renal disease (ESRD) have been used for validity. The DCref was compared to original DC (DCorg) by the area under receiver operating characteristic curve.The refined deceleration capacity (DCs calculated from 24-h, 2-h, and 30-min Holter recordings are significantly lower in patients with ESRD than those in the healthy group. In receiver operating characteristic curve analysis, the DCref provides better performance than the DCorg in distinguishing between the patients with ESRD and healthy control subjects. Furthermore, the refined PRSA technique enhances the low frequency and attenuates high frequency components for spectral analysis in ESRD patients.Experimental results demonstrate that the original and refined DCref appears to reduce the influence of non-vagally mediated abnormal variants of sinus rhythm and highlighting the pathological influence. DCref, especially assessed from short-term electrocardiography recordings, may be complementary to existing autonomic function assessment, risk stratification, and efficacy prediction strategies.The  The autonomic nervous system (ANS) plays an essential and important role in maintaining homeostasis for the body’s internal environment via two opposing branches: the sympathetic system and the parasympathetic/vagal system , 2. AutoPhase-rectified signal averaging (PRSA) was introduced to identify subtle short-term repeated patterns for characterizing the complex non-linear, non-stationary and quasi-periodic signals . When apref), by excluding from non-vagally mediated abnormal variants of sinus rhythms in heartbeat interval time series to counteract the shortcoming. This approach is expected to be more accurate than original PRSA in assessing cardiac vagal modulation. Experimental data including long-term electrocardiography (ECG) recordings were obtained from healthy and end-stage renal disease (ESRD) subjects. ESRD is characterized by altered cardiac autonomic function, reflecting as vagal modulation damage and sympathetic nerve overactivity [DCorg) and DCref quantified from different ECG-regimens in healthy subjects and patients with ESRD is utilized to demonstrate the performance of the two approaches over real clinical data.The purpose of this study is to develop and investigate a refined version of PRSA to quantify DC, represented as refined deceleration capacity , For given ECG recordings, the time series of heartbeat intervals, mentclass2pt{minimA t if Eq.  is satis2L are identified around each deceleration-related anchor. The refined PRSA signal is obtained by averaging over all segments, which are aligned and centered at deceleration-related anchors. The refined DC (DCref) is quantified according to Eq. (After the identification of deceleration-related anchor points and inflection points are selected according to Eqs.  and 5),,5), resphttp://thew-project.org/databases.htm). In addition to ECG data, automated beat annotations are available after reviewing and adjudicating manually in both databases. All human data was obtained retrospectively from completed, Institutional-Review-Board-approved clinical research studies with subject de-identification. These trials complied with the Declaration of Helsinki and all subjects signed informed consent documents.We employed two long-term (24-h) ECG ambulatory databases which are made available via the University of Rochester Telemetric and Holter ECG Warehouse (THEW) archives  comprises 24-h Holter recordings from 202 ostensibly healthy subjects . Subjects had (1) no overt cardiovascular disease or history of cardiovascular disorders; (2) no reported medications, (3) a normal physical examination, (4) a 12-lead ECG showing sinus rhythm with normal waveforms . The ECG signals were recorded at a sampling frequency of 200 Hz. Overall, we analyzed data from 191 healthy adult subjects by excluding from 11 subjects with poor ECG quality. The ESRD database (THEW identification: E-HOL-03-0202-016) comprises 48-h Holter recordings with a sampling frequency of 1000 Hz from 51 ESRD patients with high risk for cardiac arrhythmias and sudden cardiac death . ESRD subjects confirmed the history of hypertension or diabetes requiring treatment enrolled in the study. Exclusion criteria included a history of chronic atrial fibrillation, with class I antiarrhythmic, pacemaker, implantable cardioverter defibrillator device, cardiac resynchronization therapy device, female subject of childbearing potential not using medically prescribed contraceptive measures and subject unable to cooperate with the protocol due to dementia, psychological, or other related reason.For our analysis, all 24-h Holter recordings were analyzed automatically and annotated files were then carefully inspected and corrected by technicians for extracting the RR intervals. Furthermore, any RR-interval that exhibited more than 20% change from the previous RR-interval were excluded, as they were likely to be related to premature beats, artifacts and measurement noise . 2-h andDCorg and DCref using Spearman’s correlation test. In order to compare the ability of DCorg indices and DCref to differentiate the ESRD patients from the healthy control subjects, receiver operating characteristic curve (ROC) was constructed from the sensitivity and specificity after leave-one-out cross-validation of the continuous variables to assess the goodness of fit of each model. The area under the ROC curve (AUCs) gave an estimate of the overall discriminate ability. All statistical analyses were performed using SPSS version 20 software package . All the p values were adjusted using the false discovery rate (FDR) method and a value of p < 0.05 was considered to indicate statistical significance.Data were presented as the mean ± standard deviation (SD) for continuous variables. Gaussian distribution and homogeneity of variance tests were applied to determine the distribution and homoscedasticity of sample data. Because of the non-normal distribution and heterogeneity of variance of some sample data, a Mann–Whitney U test was applied to compare DCs between groups . Correlation analysis was perfomed between L for both the original and refined PRSA methods is set to 64. Similar patterns of the original and refined PRSA curves were observed for both long-term (24-h) and short-term (2-h and 30-min) ECG recordings. The heartbeat interval oscillations in the refined PRSA curves extracted from different length of ECG recordings are enhanced, especially around the deceleration-related anchor points. Different levels of the heartbeat intervals obtained by the original and refined PRSA methods can also be observed. As the length of the analyzed ECG signal is shortened, the difference between original and refined PRSA signals is also reduced.Demographic data and clinical factors of ESRD patients and healthy control subjects are presented in Table The averages of the normalized spectra obtained with the original and refined PRSA signal in the group of 51 patients with ESRD are depicted in Fig. DCref values were significantly higher than DCorg for all 24-h , 2-h and 30-min  ECG segments. Furthermore, the Pearson’s correlation coefficients between the DCorg and DCref for 24-h, 2-h and 30-min ECG recordings were 0.980, 0.983 and 0.981 , respectively.DCs calculated based on original and refined PRSA methods with different criteria of anchor point selection for the healthy control subjects and the ESRD group are given in Table DCorg and DCref compared to healthy control subjects for the analyzed three lengths of ECG episodes . In ROC curve analysis, The areas under the curve (AUC) of DCorg and DCref were 0.945 vs. 0.944, 0.960 vs. 0.969, and 0.967 vs. 0.971 for 24-h, 2-h and 30-min ECG recordings, respectively (Table DCref from long-term (24-h) ECG recordings was comparable to that of DCorg while the AUCs of DCref from short-term (2-h and 30-min) ECG recordings were slightly higher than those of DCorg. In addition, the maximum of Youden’s index of long-term (24-h) DCref was higher than that of short-term (2-h and 30-min) DCorg. DCref from 2-h ECG recordings, providing the highest value of Youden’s index, had the best discrimination power of all calculated DCs. The best cutoff value of DCref from 2-h ECG episodes for distinguishing ESRD from healthy subjects was 8.26 ms, with a sensitivity of 90.1%, specificity of 94.1%.ESRD patients substantially had significantly lower DCs were calculated through proposed refined and original PRSA methods from different length of ECG recordings and were tested their predictive value in healthy subjects and patients with ESRD. The present findings demonstrate that the refined PRSA technique better reflects the periodic components in heartbeat intervals and enhances the HF and LF components for spectral analysis. DCref, with significantly higher values compared to DCorg, was significantly lower for ESRD group than that with healthy group. This phenomenon was observed for the analysis of 24-h, as well as 2-h and 30-min ECG recordings. Furthermore, the DCref quantified from different length of ECG episodes outperformed corresponding DCorg in separating healthy subjects from patients with ESRD. Among them, DCref obtained through 2-h ECG recordings have the best discrimination ability.In the present study, a refined method was presented for the quantification of deceleration capacity of heart rate. DCref in the present study is the use of stricter criteria for the selection of the deceleration-related anchor points. This allows a smaller number of legal vagally-mediated anchor points to participate in the quantification, thereby improving the accuracy of cardiac vagal modulation assessment.HRV analysis is a non-invasive, simple and effective method for assessing the sympathovagal balance of ANS and is used to predict the risk to many cardiovascular diseases and neurological disorders , 22, 23.sgn and BBDC, which can discriminate more efficiently healthy young and elderly subjects than the original PRSA method [Theoretically, DC index could reflect the cardiac vagal modulation on heart rate , 31, 32.A method . HoweverA method . AccordiDCref in the present study was able to improve the classification of healthy subjects from ESRD patients compared to DCorg. In addition to showing the higher AUC values (except for 24-h ECG recordings) among all methods tested, the DCref also showed higher Youden’s index, thus featuring better discrimination power. Most importantly, DCref from 2-h ECG recordings had the best discrimination power of all calculated DCs. Similar with a recent study [DCref, especially from 2-h ECG recordings may be a more useful and better index for autonomic bedside risk stratification that as complementary to traditional HRV measures and clinical factors.It has been observed that an imbalance between cardiac vagal and sympathetic modulation occurs and that a sympathetic activation is an early event in the pathophysiology of ESRD , 39. In nt study , our finDCref is not particularly obvious. Second, only three ECG-regimes, the 24-h, 2-h and 30-min ECG recordings were used to quantify DCs. More ECG-regimens should be used to determine the optimal ECG length for DCref quantification, which could be performed in everyday clinical practice. Third, the proposed DCref was verified by separating healthy subjects from ESRD patients. Since the original PRSA method was developed as a prognostic tool for risk stratification, particularly mortality in post-myocardial infarction patients. Further studies are warranted to demonstrate advantages of DCref in autonomic risk stratification.Several limitations are present in this study. First, the sample size is small for ESRD group. The ESRD patients enrolled after strictly screening through enrollment exclusion and criteria was most likely to be in a similar autonomic dysfunction, leading to the advantage of DCref), which excludes from non-vagally mediated inflection points, provides an accurate assessment of cardiac vagal modulation. Furthermore, DCref also provides a better distinction between healthy subjects and patients with ESRD compared with DCorg. DCref derived from 2-h ECG recordings, which have the best discrimination ability, might be complementary to existing autonomic function assessment, risk stratification, and efficacy prediction techniques for clinical use.The refined deceleration capacity index (