A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events

Background: Recent evidence highlights the epidemiological value of blood DNA methylation (DNAm) as surrogate biomarker for exposure to risk factors for non-communicable diseases (NCD). DNAm surrogate of exposures predicts diseases and longevity better than self-reported or measured exposures in many cases. Consequently, disease prediction models based on blood DNAm surrogates may outperform current state-of-the-art prediction models. This study aims to develop novel DNAm surrogates for cardiovascular diseases (CVD) risk factors and develop a composite biomarker predictive of CVD risk. We compared the prediction performance of our newly developed risk score with the state-of-the-art DNAm risk scores for cardiovascular diseases, the ‘next-generation’ epigenetic clock DNAmGrimAge, and the prediction model based on traditional risk factors SCORE2. Results: Using data from the EPIC Italy cohort, we derived novel DNAm surrogates for BMI, blood pressure, fasting glucose and insulin, cholesterol, triglycerides, and coagulation biomarkers. We validated them in four independent data sets from Europe and the USA. Further, we derived a DNAmCVDscore predictive of the time-to-CVD event as a combination of several DNAm surrogates. ROC curve analyses show that DNAmCVDscore outperforms previously developed DNAm scores for CVD risk and SCORE2 for short-term CVD risk. Interestingly, the performance of DNAmGrimAge and DNAmCVDscore was comparable (slightly lower for DNAmGrimAge, although the differences were not statistically significant). Conclusions: We described novel DNAm surrogates for CVD risk factors useful for future molecular epidemiology research, and we described a blood DNAm-based composite biomarker, DNAmCVDscore, predictive of short-term cardiovascular events. Our results highlight the usefulness of DNAm surrogate biomarkers of risk factors in epigenetic epidemiology to identify high-risk populations. In addition, we provide further evidence on the effectiveness of prediction models based on DNAm surrogates and discuss methodological aspects for further improvements. Finally, our results encourage testing this approach for other NCD diseases by training and developing DNAm surrogates for disease-specific risk factors and exposures

A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events

Background. Recent evidence highlights the epidemiological value of blood DNA methylation (DNAm) as surrogate biomarker for exposure to risk factors for non-communicable diseases (NCD). DNAm surrogate of exposures predict diseases and longevity better than self-reported or measured exposures in many cases. Consequently, disease prediction models based on blood DNAm surrogates may outperform current state-of-art prediction models. This study aims to develop novel DNAm surrogates for cardiovascular diseases (CVD) risk factors and develop a composite biomarker predictive of CVD risk. We compared the prediction performance of our newly developed risk score with the state-of-art DNAm risk scores for cardiovascular diseases, the ‘next-generation’ epigenetic clock DNAmGrimAge, and the prediction model based on traditional risk factors SCORE2. Results. Using data from the EPIC Italy cohort, we derived novel DNAm surrogates for BMI, blood pressure, fasting glucose and insulin, cholesterol, triglycerides, and coagulation biomarkers. We validated them in four independent datasets from Europe and the US. Further, we derived a DNAmCVDscore predictive of the time-to-CVD event as a combination of several DNAm surrogates. ROC curve analyses show that DNAmCVDscore outperforms previously developed DNAm scores for CVD risk and SCORE2 for short-term CVD risk. Interestingly, the performance of DNAmGrimAge and DNAmCVDscore was comparable (slightly lower for DNAmGrimAge, although the differences were not statistically significant). Conclusions. We described novel DNAm surrogates for CVD risk factors useful for future molecular epidemiology research, and we described a blood DNAm-based composite biomarker, DNAmCVDscore, predictive of short-term cardiovascular events. Our results highlight the usefulness of DNAm surrogate biomarkers of risk factors in epigenetic epidemiology to identify high-risk populations. In addition, we provide further evidence on the effectiveness of prediction models based on DNAm surrogates and discuss methodological aspects for further improvements. Finally, our results encourage testing this approach for other NCD diseases by training and developing DNAm surrogates for disease-specific risk factors and exposures

Biomarkers of effect as determined in human biomonitoring studies on hexavalent chromium and cadmium in the period 2008–2020

This research was supported by funding from the European Union's Horizon 2020 research and innovation Programme under grant agreement No 733032 HBM4EU.A number of human biomonitoring (HBM) studies have presented data on exposure to hexavalent chromium [Cr (VI)] and cadmium (Cd), but comparatively few include results on effect biomarkers. The latter are needed to identify associations between exposure and adverse outcomes (AOs) in order to assess public health implications. To support improved derivation of EU regulation and policy making, it is of great importance to identify the most reliable effect biomarkers for these heavy metals that can be used in HBM studies. In the framework of the Human Biomonitoring for Europe (HBM4EU) initiative, our study aim was to identify effect biomarkers linking Cr(VI) and Cd exposure to selected AOs including cancer, immunotoxicity, oxidative stress, and omics/epigenetics. A comprehensive PubMed search identified recent HBM studies, in which effect biomarkers were examined. Validity and applicability of the markers in HBM studies are discussed. The most frequently analysed effect biomarkers regarding Cr(VI) exposure and its association with cancer were those indicating oxidative stress (e.g., 8-hydroxy-2 & rsquo;-deoxyguanosine (8-OHdG), malondialdehyde (MDA), glutathione (GSH)) and DNA or chromosomal damage (comet and micronucleus assays). With respect to Cd and to some extent Cr, 0-2-microglobulin (B2-MG) and N-acetyl-0-D-glucosaminidase (NAG) are well-established, sensitive, and the most common effect biomarkers to relate Cd or Cr exposure to renal tubular dysfunction. Neutrophil gelatinase-associated lipocalin (NGAL) and kidney injury molecule (KIM)-1 could serve as sensitive biomarkers of acute kidney injury in response to both metals, but need further investigation in HBM studies. Omics-based biomarkers, i.e., changes in the (epi-)genome, transcriptome, proteome, and metabolome associated with Cr and/or Cd exposure, are promising effect biomarkers, but more HBM data are needed to confirm their significance. The combination of established effect markers and omics biomarkers may represent the strongest approach, especially if based on knowledge of mechanistic principles. To this aim, also mechanistic data were collected to provide guidance on the use of more sensitive and specific effect biomarkers. This also led to the identification of knowledge gaps relevant to the direction of future research.European Commission 733032 HBM4E

Prediction models for endometrial cancer for the general population or symptomatic women: a systematic review

OBJECTIVE: To provide an overview of prediction models for the risk of developing endometrial cancer in women of the general population or for the presence of endometrial cancer in symptomatic women. METHODS: We systematically searched the Embase and Pubmed database until September 2017 for relevant publications. We included studies describing the development, the external validation, or the updating of a multivariable model for predicting endometrial cancer in the general population or symptomatic women. RESULTS: Out of 2756 references screened, 14 studies were included. We found two prediction models for developing endometrial cancer in the general population (risk models) and one extension. Eight studies described the development of models for symptomatic women (diagnostic models), one comparison of the performance of two diagnostic models and two external validation. Sample size varied from 60 (10 with cancer) to 201,811 (855 with cancer) women. The age of the women was included as a predictor in almost all models. The risk models included epidemiological variables related to the reproductive history of women, hormone use, BMI, and smoking history. The diagnostic models also included clinical predictors, such as endometrial thickness and recurrent bleeding. The concordance statistic (c), assessing the discriminative ability, varied from 0.68 to 0.77 in the risk models and from 0.73 to 0.957 in the diagnostic models. Methodological information was often limited, especially on the handling of missing data, and the selection of predictors. One risk model and four diagnostic models were externally validated. CONCLUSIONS: Only a few models have been developed to predict endometrial cancer in asymptomatic or symptomatic women. The usefulness of most models is unclear considering methodological shortcomings and lack of external validation. Future research should focus on external validation and extension with new predictors or biomarkers, such as genetic and epigenetic markers

The biology of inequalities in health: The LIFEPATH project

Socioeconomic differences in health have been consistently observed worldwide. Physical health deteriorates more rapidly with age among men and women with lower socioeconomic status (SES) than among those with higher SES. The biological processes underlying these differences are best understood by adopting a life course approach. In this paper we introduce the pan- European LIFEPATH project which uses multiple cohorts - including biomarker data - to investigate ageing as a phenomenon with two broad stages across life: build-up and decline. The ‘build-up’ stage, from conception and early intra-uterine life to late adolescence or early twenties, is characterised by rapid successions of developmentally and socially sensitive periods. The second stage, starting in early adulthood, is a period of ‘decline’ from maximum attained health to loss of function, overt disease and death. LIFEPATH adopts a study design that integrates social science and public health approaches with biology (including molecular epidemiology), using well-characterised population cohorts and omics measurements (particularly epigenomics). LIFEPATH includes information and biological samples from 17 cohorts, including several with extensive phenotyping and repeat biological samples, and a very large cohort (1 million individuals) without biological samples (WHIP, from Italy). The countries that are covered by the cohorts are France, Italy, Portugal, Ireland, UK, Finland, Switzerland and Australia. These cohorts are only a small proportion of all cohorts available in Europe, but we have chosen them for the combination of good measures of socioeconomic status, risk factors for non-communicable diseases (NCDs) and biomarkers already measured (or availability of blood samples for further testing). The majority of cohorts include ‘hard’ outcomes (diabetes, cancer, Cardiovascular Disease (CVD), total mortality), and the extensively phenotyped cohorts also include several measurements of the functional components of healthy ageing, including frailty, impaired vision, cognitive function, renal and brain function, osteoporosis, sleep disturbances and mental health. All age groups are represented with two birth cohorts, one cohort of adolescents and several cohorts encompassing young adults (age 18 and above). Furthermore, there is a strong representation of elderly subjects in seven cohorts. The specific objectives of the project are: (a) to show that healthy ageing is an achievable goal for society; (b) to improve the understanding of the mechanisms through which healthy ageing pathways diverge by SES, by investigating life course biological pathways using omic technologies; (c) to examine the consequences of the current economic recession on health and the biology of ageing (and the consequent increase in social inequalities); (d) to provide updated, relevant and innovative evidence for healthy ageing policies (particularly ‘health in all policies’) using both observational studies and an experimental approach based on a reanalysis of data from a ‘conditional cash transfer’ randomised experiment in New York and new data collected as part of an earned income tax credit randomised experiment in Atlanta and New York. To achieve these objectives, data are used from three categories of studies: 1. national census-based followup data to obtain mortality by socioeconomic status; 2. cohorts with intense phenotyping and repeat biological samples; 3. large cohorts with biological samples. With these objectives and methodologies, LIFEPATH seeks to provide updated, relevant and innovative evidence to underpin future policies and strategies for the promotion of healthy ageing, targeted disease prevention and clinical interventions that address the issue of social disparities in ageing and the social determinants of health. The present paper describes the design and some initial results of LIFEPATH as an example of the integration of social and biological sciences to provide evidence for public health policies

Toxicological profile for n-nitrosodimethylamine (NDMA)

VERSION HISTORYDate DescriptionApril 2023 Final toxicological profile releasedJanuary 2022 Draft for public comment toxicological profile releasedDecember 1989 Final toxicological profile releasedhttps://www.atsdr.cdc.gov/ToxProfiles/tp141.pd

Current and future approaches to screening for endometrial cancer

Due largely to the rise in obesity and prolonged life expectancy, endometrial cancer (EC) rates have increased by 56% since the early 90s. Women at high risk (Lynch Syndrome) have a 12–47% lifetime risk of developing EC and professional societies recommend annual surveillance using transvaginal ultrasound (TVS) and endometrial biopsy (outpatients hysteroscopy) from the age of 30–35 years with hysterectomy from the age of 40 years. In women at low risk, screening is not currently advocated. The emerging data from Genome Wide Association studies (GWAS) in combination with epidemiological data may refine risk stratification in the future. In addition to screening, preventative approaches such as intrauterine progesterone may help reduce disease burden in those identified at ‘higher risk’

Leveraging Epidemiology to Improve Risk Assessment.

The field of environmental public health is at an important crossroad. Our current biomonitoring efforts document widespread exposure to a host of chemicals for which toxicity information is lacking. At the same time, advances in the fields of genomics, proteomics, metabolomics, genetics and epigenetics are yielding volumes of data at a rapid pace. Our ability to detect chemicals in biological and environmental media has far outpaced our ability to interpret their health relevance, and as a result, the environmental risk paradigm, in its current state, is antiquated and ill-equipped to make the best use of these new data. In light of new scientific developments and the pressing need to characterize the public health burdens of chemicals, it is imperative to reinvigorate the use of environmental epidemiology in chemical risk assessment. Two case studies of chemical assessments from the Environmental Protection Agency Integrated Risk Information System database are presented to illustrate opportunities where epidemiologic data could have been used in place of experimental animal data in dose-response assessment, or where different approaches, techniques, or studies could have been employed to better utilize existing epidemiologic evidence. Based on the case studies and what can be learned from recent scientific advances and improved approaches to utilizing human data for dose-response estimation, recommendations are provided for the disciplines of epidemiology and risk assessment for enhancing the role of epidemiologic data in hazard identification and dose-response assessment