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Background: The aim of the EU-funded HERA (health and environment research agenda) project is to set priorities for the future European research agenda in the environment, climate and health nexus. We report results from a European researcher’s perspective and identify research areas that have been inadequately investigated to date. Methods: An online survey was completed by European researchers to assess, evaluate and visualise research gaps. These research gaps were identified for 21 predefined areas within 3 main categories: i) classical environment and health paradigm; ii) problem or sector-based research areas and approaches and iii) holistic research areas and concepts. All research gaps were then evaluated by expert groups with the pre-defined criteria and systematically summarized. For areas identified within the survey as under-reported, additional input was sought from a range of key selected experts. The EU project database Cordis was utilized to verify that these areas were under-researched. Results: Between May and July 2019, 318 respondents from 38 countries reported 624 research gaps. The main areas for attention identified were: urban environments; chemicals; and climate change, (combined n = 313 gaps). Biodiversity loss and health; transport, mobility, sustainable solutions and health; energy transition and health; waste and the circular economy and health; ethics and philosophy and health were areas that were acknowledged as under-researched (combined n = 27 gaps). These under-researched areas were identified as having certain commonalities, they: i) mostly fell in the category “problem or sector based approaches“; ii) they are essential for developing and implementing solutions; and iii) require trans-disciplinary and cross-sectoral collaboration. Conclusions: Currently attention is given to topical and highly researched areas in environmental health. In contrast, this paper identifies key topics and approaches that are under-researched, yet, are critical for the implementation of the EU Green Deal, related strategies and action plans, and require further investigation and investment. The findings reveal the imperative to foster solutions-oriented, trans-disciplinary and participatory research and its implementation through changes in research funding and research structures.

BackgroundIn this study we investigated the prevalence of undiagnosed impaired glucose tolerance and type-2-diabetes (T2D) among patients with acute myocardial infarction (AMI) and prospectively analyzed whether these patients have a higher long-term mortality.MethodsThe analysis was based on 2,317 AMI patients aged 25–84 years from the population-based Myocardial Infarction Registry Augsburg, recruited between 2009 and 2014 and followed-up until 2019 (median follow-up time 6.5 years [IQR: 4.9–8.1]). AMI patients with a diagnosis of diabetes were divided into a high (>7.0%) and a low HbA1c group (≤7.0%) according to HbA1c values at admission. The remaining patients (without known diabetes) were grouped into normal ( 6.5% HR: 1.34 [0.77–2.31]). A linear regression model including the variables admission serum glucose, BMI, age, sex and type of infarction (STEMI, NSTEMI) showed only poor prediction of HbA1c values (R2: 11.08%).ConclusionA fairly high number of AMI patients without known diabetes have elevated HbA1c values. Though we could not prove a higher risk of premature mortality in these patients, early detection and adequate therapy might lead to reduced diabetes-associated complications and improve long-term outcomes.

To assess whether anthropometric measures (body mass index [BMI], waist-hip ratio [WHR], and estimated fat mass [EFM]) are independently associated with major adverse cardiovascular events (MACE), and to assess their added prognostic value compared with serum total-cholesterol. The study population comprised 109,509 individuals (53% men) from the MORGAM-Project, aged 19–97 years, without established cardiovascular disease, and not on antihypertensive treatment. While BMI was reported in all, WHR and EFM were reported in ∼52,000 participants. Prognostic importance of anthropometric measurements and total-cholesterol was evaluated using adjusted Cox proportional-hazards regression, logistic regression, area under the receiver-operating-characteristic curve (AUCROC), and net reclassification improvement (NRI). The primary endpoint was MACE, a composite of stroke, myocardial infarction, or death from coronary heart disease. Age interacted significantly with anthropometric measures and total-cholesterol on MACE (P ≤ 0.003), and therefore age-stratified analyses (

Abstract Background The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study. Results Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant’s gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5. Conclusions The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies. Video abstract

Abstract Prior studies examined association between short-term mortality and certain changes in the admission ECG in acute myocardial infarction (AMI). Nevertheless, little is known about possible differences between patients with diabetes and without diabetes in this regard. So the aim of the study was to investigate the association between 28-day case fatality according to certain ECG changes comparing AMI cases with and without diabetes from the general population. From 2000 until 2017 a total of 9756 AMI cases was prospectively recorded in the study Area of Augsburg, Germany. Each case was assigned to one of the following groups according to admission ECG: ‘ST-elevation’, ‘ST-depression’, ‘only T-negativity’, ‘predominantly bundle branch block’, ‘unspecific changes’ and ‘normal ECG’ (the last two were put together for regression analyses). Multivariable adjusted logistic regression models were calculated to compare 28-day case-fatality between the ECG groups for the total sample and separately for diabetes and non-diabetes cases. For the non-diabetes group, the parsimonious logistic regression model revealed significantly better 28-day-outcome for the ‘normal ECG / unspecific changes’ group (OR: 0.47 [0.29–0.76]) compared to the reference group (STEMI). Contrary, in AMI cases with diabetes the category ‘normal ECG / unspecific changes’ was not significantly associated with lower short-term mortality (OR: 0.87 [0.49–1.54]). Neither of the other ECG groups was significantly associated with 28-day-mortality in the parsimonious logistic regression models. Consequently, the absence of AMI-typical changes in the admission ECG predicts favorable short-term mortality only in non-diabetic cases, but not so in patients with diabetes.

Abstract Background Neurofilament light chain (NfL) is a cytoskeletal protein component whose release into blood is indicative of neuronal damage. Tau is a microtubule-associated protein in neurons and strongly associated with overall brain degeneration. NfL and tau levels are associated with mortality in different neurological diseases, but studies in the general population are missing. We investigated whether NfL and tau serum levels could serve as prognostic markers for overall mortality in elderly individuals without pre-defined neurological conditions. Further, we investigated the cross-sectional associations between NfL, tau, neuropsychological functioning, and brain structures. Methods In 1997, 385 inhabitants of Augsburg who were aged 65 years and older were included in the Memory and Morbidity in Augsburg Elderly (MEMO) study. They participated in a face-to-face medical interview including neuropsychological tests and magnetic resonance imaging (MRI) of the brain. NfL and tau were measured from non-fasting blood samples using highly sensitive single molecule array assays. To assess the prognostic accuracy of the biomarkers, concordance statistics based on the predicted 5-year survival probabilities were calculated for different Cox regression models. Associations between the biomarkers and the neuropsychological test scores or brain structures were investigated using linear or logistic regression. Results NfL (HR 1.27, 95% CI [1.14–1.42]) and tau (1.20 [1.07–1.35]) serum levels were independently associated with all-cause mortality. NfL, but not tau, increased the prognostic accuracy when added to a model containing sociodemographic characteristics (concordance statistic 0.684 [0.612–0.755] vs. 0.663 [0.593–0.733]), but not when added to a model containing sociodemographic characteristics and brain atrophy or neuropsychological test scores. NfL serum levels were cross-sectionally associated with neuropsychological test scores and brain structures. Conclusions The association between NfL serum levels and brain atrophy and neuropsychological performance in individuals without overt neurological disease is similar to that seen in patients with neurodegenerative diseases. These findings support the concept of a continuum of physiological aging and incipient, subclinical pathology, and manifest disease. NfL, but not tau, serum levels might serve as a prognostic marker for all-cause mortality if no other clinical information is available.

Blood circulating proteins reflect biological processes, thus providing insight into complex traits. Here the authors study the relationship between 1000 plasma proteins and body mass index (BMI), highlighting widespread proteome changes and causal relationships between BMI and specific proteins.

Abstract Background The association of longitudinal trajectories of cardiovascular risk factors with cardiovascular magnetic resonance (CMR)-measures of cardiac structure and function in the community is not well known. Therefore we aimed to relate risk factor levels from different examination cycles to CMR-measures of the left ventricle (LV) and right ventricle in a population-based cohort. Methods We assessed conventional cardiovascular disease risk factors in 349 participants (143 women; aged 25–59 years) at three examination cycles (Exam 1 [baseline], at Exam 2 [7-years follow-up] and at Exam 3 [14-years follow-up]) of the KORA S4 cohort and related single-point measurements of individual risk factors and longitudinal trajectories of these risk factors to various CMR-measures obtained at Exam 3. Results High levels of diastolic blood pressure, waist circumference, and LDL-cholesterol at the individual exams were associated with worse cardiac function and structure. Trajectory clusters representing higher levels of the individual risk factors were associated with worse cardiac function and structure compared to low risk trajectory clusters of individual risk factors. Multivariable (combining different risk factors) trajectory clusters were associated with different cardiac parameters in a graded fashion (e.g. decrease of LV stroke volume for middle risk cluster β = − 4.91 ml/m2, 95% CI − 7.89; − 1.94, p

Abstract Calcium plays an essential role in physiology of the cardiovascular system. Aberrations from normal serum calcium levels are known to be associated with several cardiovascular diseases. Its possible role as a predictor for long-term mortality after acute myocardial infarction (AMI) is still uncertain. In this study, a total of 3732 patients (aged 25–74 years) with incident AMI surviving at least 28 days after AMI was included. The median follow-up time was 6.0 years. Admission total serum calcium levels were divided into quartiles. The Kaplan–Meier-Curve suggested a division of the follow up time in two different time periods. So, Cox regression models were calculated to assess association between admission serum calcium levels and all-cause long-term mortality with two observation periods: 28–2500 days and > 2500 days. The final model was adjusted for various comorbidities, clinical characteristics, in-hospital treatment and medication. The third quartile (normal-high Calcium levels) served as the reference group. The fully adjusted Cox-regression model shows significantly higher mortality risk for low serum calcium (quartile 1) within the timeframe 28–2500 days after the event (OR 1.53 [1.19–1.98]). The other groups did not differ significantly from each other. In the later observation period (from 2500 days until death or censoring) no more significant differences were seen between the four calcium quartiles. In summary, low serum calcium is an independent predictor of adverse outcome in the first 2500 days (about 7 years) after AMI. On later points in time this effect attenuates, so that no more significant differences can be observed.

Abstract To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we used a data-driven machine-learning approach. We analysed two independent cohorts (KORA and SHIP). WMH volumes were derived from cMRI-images (FLAIR). 90 (KORA) and 34 (SHIP) potential determinants of WMH including measures of diabetes, blood-pressure, medication-intake, sociodemographics, life-style factors, somatic/depressive-symptoms and sleep were collected. Elastic net regression was used to identify relevant predictor covariates associated with WMH volume. The ten most frequently selected variables in KORA were subsequently examined for robustness in SHIP. The final KORA sample consisted of 370 participants (58% male; age 55.7 ± 9.1 years), the SHIP sample comprised 854 participants (38% male; age 53.9 ± 9.3 years). The most often selected and highly replicable parameters associated with WMH volume were in descending order age, hypertension, components of the social environment (i.e. widowed, living alone) and prediabetes. A systematic machine-learning based analysis of two independent, population-based cohorts showed, that besides age and hypertension, prediabetes and components of the social environment might play important roles in the development of WMH. Our results enable personal risk assessment for the development of WMH and inform prevention strategies tailored to the individual patient.

Obesity plays an important role in the development of insulin resistance and diabetes, but the molecular mechanism that links obesity and diabetes is still not completely understood. Here, we used 146 targeted metabolomic profiles from the German KORA FF4 cohort consisting of 1715 participants and associated them with obesity and type 2 diabetes. In the basic model, 83 and 51 metabolites were significantly associated with body mass index (BMI) and T2D, respectively. Those metabolites are branched-chain amino acids, acylcarnitines, lysophospholipids, or phosphatidylcholines. In the full model, 42 and 3 metabolites were significantly associated with BMI and T2D, respectively, and replicate findings in the previous studies. Sobel mediation testing suggests that the effect of BMI on T2D might be mediated via lipids such as sphingomyelin (SM) C16:1, SM C18:1 and diacylphosphatidylcholine (PC aa) C38:3. Moreover, mendelian randomization suggests a causal relationship that BMI causes the change of SM C16:1 and PC aa C38:3, and the change of SM C16:1, SM C18:1, and PC aa C38:3 contribute to T2D incident. Biological pathway analysis in combination with genetics and mice experiments indicate that downregulation of sphingolipid or upregulation of phosphatidylcholine metabolism is a causal factor in early-stage T2D pathophysiology. Our findings indicate that metabolites like SM C16:1, SM C18:1, and PC aa C38:3 mediate the effect of BMI on T2D and elucidate their role in obesity related T2D pathologies.

Ambient air temperature and temperature variability are supposed to influence blood pressure (BP); however, findings are inconsistent. We examined the effects of short-term changes in ambient temperature and temperature variability on systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP) in a repeated-measures study. Repeated BP measurements were available for 3184 participants from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999–2001) and two follow-up examinations (2006–08 and 2013–14). Daily meteorological data were obtained from fixed measurement stations including air temperature and diurnal temperature range (DTR). We used confounder-adjusted additive mixed models to examine immediate (same-day, lag 0), delayed (lag 1 to lag 4), and cumulative (up to lag 0–13) exposure effects. Decreases in air temperature were associated with increases in SBP, DBP, and MAP, while we observed no effects for PP at all. For example, a 1 °C decrease in the 14-day moving average (lag 0–13) mean air temperature was associated with a 0.54% [95% confidence interval [95%CI]: 0.41%;0.68%] increase in SBP. Furthermore, decreasing DTR was linked to increasing SBP, DBP, and MAP measures. In the sensitivity analyses, results were found to be robust. Examination of exposure–response functions according to season revealed, that associations for summer and winter can be considered linear, while we detected non-linear functions in spring and autumn. Furthermore, exposure–response functions also differed in the three different surveys. As BP levels influence the risk of cardiovascular mortality, our results show the importance of considering temperature and its variation as potential risk factors. As ongoing climate change affects temperature variability, it is important to understand how the body adapts to changing ambient temperatures.

Background: In contrast to studies in patients, an association between obesity and blood coagulation factors has not been established in the population. If confirmed it could become a target for primary prevention. Objective: To investigate the relationship between Body Mass Index (BMI) and waist circumference (WC) with plasma concentrations of antithrombin III, D-dimers, fibrinogen D, protein S, factor VIII, activated partial thromboplastin time (aPTT), quick value, and international normalized ratio (INR) in the general population. Materials and Methods: Participants of the Cooperative Health Research in the Region of Augsburg (KORA) S4 study who took part in the KORA Fit follow-up (2018–2019, aged 54–74 years) examination were eligible. Citrate plasma samples were collected in fasted participants. After the exclusion of participants with anticoagulative treatment, 776 participants (420 women and 356 men) with analytic data on hemostatic factors were included in the present analysis. Linear regression models were used to explore the association between BMI or WC with hemostatic markers, adjusted for sex, age, alcohol consumption, education, smoking status, and physical activity. In a second model, additional adjustments were made for the prevalence of stroke, hypertension, myocardial infarction, serum non-HDL cholesterol, and serum triglycerides. Results: In the multivariable models (with or without health conditions), significant positive associations with BMI were obtained for plasma concentrations of D-dimers, factor VIII, fibrinogen D, protein S, and quick value, while INR and antithrombin III were inversely associated. Similar to BMI, WC was significantly associated with all hemostatic factors, except for aPTT. Conclusion: In this population-based study, both increasing BMI and WC affect the blood coagulation system. Thus, modification of a prothrombotic coagulation profile emerged as a potential target for primary prevention in obese subjects.

Abstract Background Current evidence suggests that the information needs of people with diabetes mellitus differ across patient groups. With a view to being able to provide individualized information, this study aims to identify (i) the diabetes-related information needs of people with diabetes mellitus; (ii) different subgroups of people with specific information needs; and (iii) associated characteristics of the identified subgroups, such as sociodemographic characteristics, diabetes-related comorbidities, and well-being. Methods This cross-sectional study was based on data from 837 respondents with diabetes mellitus who participated in the population-based KORA (Cooperative Health Research in the Augsburg Region) Health Survey 2016 in Southern Germany (KORA GEFU 4 study) (45.6% female, mean age 71.1 years, 92.8% Type 2 diabetes). Diabetes-related information needs were assessed with a questionnaire asking about patients’ information needs concerning 11 diabetes-related topics, e.g. ‘long-term complications’ and ‘treatment/therapy’. Subgroups of people with different information needs and associated characteristics were identified using latent class analysis. Results We identified the following four classes of people with different information needs: ‘high needs on all topics’, ‘low needs on all topics’, ‘moderate needs with a focus on complications and diabetes in everyday life’, and ‘advanced needs with a focus on social and legal aspects and diabetes research’. The classes differed significantly in age, years of education, type of diabetes, diabetes duration, diabetes-related comorbidities, smoking behaviour, diabetes education, current level of information, and time preference. Conclusions Knowledge about different patient subgroups can be useful for tailored information campaigns or physician-patient interactions. Further research is needed to analyse health care needs in these groups, changes in information needs over the course of the disease, and prospective health outcomes.

Abstract Background High N-terminal pro-brain-type natriuretic peptide levels have been associated with a lower risk of type 2 diabetes mellitus (T2D). However, less is known about other cardiac stress biomarkers in this context. Here we evaluated the association of mid-regional pro-atrial natriuretic peptide (MR-proANP), C-terminal pro-arginine vasopressin (copeptin), C-terminal pro-endothelin-1 (CT-proET-1) and mid-regional pro-adrenomedullin (MR-proADM) with incident T2D and changes in glucose metabolism. Methods We performed a prospective cohort study using data from the population-based KORA F4/FF4 study. 1773 participants (52.3% women) with MR-proANP measurements and 960 (52.7% women) with copeptin, CT-proET-1 and MR-proADM measurements were included. We examined associations of circulating plasma levels of MR-proANP, copeptin, CT-proET-1 and MR-proADM with incident T2D, the combined endpoint of incident prediabetes/T2D and with fasting and 2 h-glucose, fasting insulin, HOMA-IR, HOMA-B and HbA1c at follow-up. Logistic and linear regression models adjusted for age, sex, waist circumference, height, hypertension, total/HDL cholesterol ratio, triglycerides, smoking, physical activity and parental history of diabetes were used to compute effect estimates. Results During a median follow-up time of 6.4 years (25th and 75th percentiles: 6.0 and 6.6, respectively), 119 out of the 1773 participants and 72 out of the 960 participants developed T2D. MR-proANP was inversely associated with incident T2D (odds ratio [95% confidence interval]: 0.75 [0.58; 0.96] per 1-SD increase of log MR-proANP). Copeptin was positively associated with incident prediabetes/T2D (1.29 [1.02; 1.63] per 1-SD increase of log copeptin). Elevated levels of CT-proET-1 were associated with increased HOMA-B at follow-up, while elevated MR-proADM levels were associated with increased fasting insulin, HOMA-IR and HOMA-B at follow-up. These associations were independent of previously described diabetes risk factors. Conclusions High plasma concentrations of MR-proANP contributed to a lower risk of incident T2D, whereas high plasma concentrations of copeptin were associated with an increased risk of incident prediabetes/T2D. Furthermore, high plasma concentrations of CT-proET-1 and MR-proADM were associated with increased insulin resistance. Our study provides evidence that biomarkers implicated in cardiac stress are associated with incident T2D and changes in glucose metabolism.

The Federal Ministry of Education and Research (BMBF) issued a call for a new nationwide research network on mental disorders, the German Center of Mental Health (DZPG). The Munich/Augsburg consortium was selected to participate as one of six partner sites with its concept “Precision in Mental Health (PriMe): Understanding, predicting, and preventing chronicity.” PriMe bundles interdisciplinary research from the Ludwig-Maximilians-University (LMU), Technical University of Munich (TUM), University of Augsburg (UniA), Helmholtz Center Munich (HMGU), and Max Planck Institute of Psychiatry (MPIP) and has a focus on schizophrenia (SZ), bipolar disorder (BPD), and major depressive disorder (MDD). PriMe takes a longitudinal perspective on these three disorders from the at-risk stage to the first-episode, relapsing, and chronic stages. These disorders pose a major health burden because in up to 50% of patients they cause untreatable residual symptoms, which lead to early social and vocational disability, comorbidities, and excess mortality. PriMe aims at reducing mortality on different levels, e.g., reducing death by psychiatric and somatic comorbidities, and will approach this goal by addressing interdisciplinary and cross-sector approaches across the lifespan. PriMe aims to add a precision medicine framework to the DZPG that will propel deeper understanding, more accurate prediction, and personalized prevention to prevent disease chronicity and mortality across mental illnesses. This framework is structured along the translational chain and will be used by PriMe to innovate the preventive and therapeutic management of SZ, BPD, and MDD from rural to urban areas and from patients in early disease stages to patients with long-term disease courses. Research will build on platforms that include one on model systems, one on the identification and validation of predictive markers, one on the development of novel multimodal treatments, one on the regulation and strengthening of the uptake and dissemination of personalized treatments, and finally one on testing of the clinical effectiveness, utility, and scalability of such personalized treatments. In accordance with the translational chain, PriMe’s expertise includes the ability to integrate understanding of bio-behavioral processes based on innovative models, to translate this knowledge into clinical practice and to promote user participation in mental health research and care.

BackgroundAlthough gene-expression (GE) and protein levels are typically strongly genetically regulated, their correlation is known to be low. Here we investigate this phenomenon by focusing on the genetic background of this correlation in order to understand the similarities and differences in the genetic regulation of these omics layers.Methods and resultsWe performed locus-wide association studies of 92 protein levels measured in whole blood for 2,014 samples of European ancestry and found that 66 are genetically regulated. Three female- and one male-specific effects were detected. We estimated the genetically regulated GE for all significant genes in 49 GTEx v8 tissues. A total of 7 proteins showed negative correlations with their respective GE across multiple tissues. Finally, we tested for causal links of GE on protein expression via Mendelian Randomization, and confirmed a negative causal effect of GE on protein level for five of these genes in a total of 63 gene-tissue pairs: BLMH, CASP3, CXCL16, IL6R, and SFTPD. For IL6R, we replicated the negative causal effect on coronary-artery disease (CAD), while its GE was positively linked to CAD.ConclusionWhile total GE and protein levels are only weakly correlated, we found high correlations between their genetically regulated components across multiple tissues. Of note, strong negative causal effects of tissue-specific GE on five protein levels were detected. Causal network analyses revealed that GE effects on CAD risks was in general mediated by protein levels.

Summary: Background: Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE). Methods: In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000–11; follow-up until 2011–17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM2·5), nitrogen dioxide (NO2), black carbon, and tropospheric warm-season ozone (O3) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis. Findings: We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM2·5, NO2, and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021–1·085) per 5 μg/m3 increment in PM2·5, 1·044 (1·019–1·069) per 10 μg/m3 NO2, and 1·039 (1·018–1·059) per 0·5 × 10−5/m black carbon. Associations with PM2·5, NO2, and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O3 was negatively associated with both non-accidental and cause-specific mortality. Associations were stronger at low concentrations: HRs for non-accidental mortality at concentrations lower than the WHO 2005 air quality guideline values for PM2·5 (10 μg/m3) and NO2 (40 μg/m3) were 1·078 (1·046–1·111) per 5 μg/m3 PM2·5 and 1·049 (1·024–1·075) per 10 μg/m3 NO2. Similarly, the association between black carbon and non-accidental mortality was highest at low concentrations, with a HR of 1·061 (1·032–1·092) for exposure lower than 1·5× 10−5/m, and 1·081 (0·966–1·210) for exposure lower than 1·0× 10−5/m. Interpretation: Long-term exposure to concentrations of PM2·5 and NO2 lower than current annual limit values was associated with non-accidental, cardiovascular, non-malignant respiratory, and lung cancer mortality in seven large European cohorts. Continuing research on the effects of low concentrations of air pollutants is expected to further inform the process of setting air quality standards in Europe and other global regions. Funding: Health Effects Institute.

Background and aimDespite its vasodilatory effect, adrenomedullin and its surrogate mid-regional pro-adrenomedullin (MR-proADM) have been found to be positively associated with all-cause and cardiovascular mortality. However, the underlying mechanisms thereof remain unclear and the associations were mostly shown in geriatric cohorts or in patients with chronic diseases. Therefore, we aimed to investigate the possible involvement of abdominal obesity, selected adipokines, and biomarkers of subclinical inflammation in the association of MR-proADM with mortality in a population based study cohort.MethodsProspective analysis of the KORA F4 study; median follow-up 9.1 (8.8-9.4) years. Complete data on MR-proADM and mortality was available for 1551 participants, aged 56.9±12.9 years (mean±SD). Correlation and regression analyses of MR-proADM with overall (BMI) and abdominal obesity (waist circumference), selected adipokines and biomarkers of subclinical inflammation. Cox proportional hazard models on the association of MR-proADM with all-cause and cardiovascular mortality with adjustment for cardiovascular risk factors and selected biomarkers in study subgroups (n = 603-1551).ResultsMR-proADM associated with all-cause (HR (95%CI): 2.37 (1.72-3.26) and 2.31 (1.67-3.20)) and cardiovascular mortality (4.28 (2.19-8.39) and 4.44 (2.25-8.76)) after adjustment for traditional cardiovascular risk factors including BMI or waist circumference, respectively. MR-proADM was further associated with four out of seven examined adipokines (leptin, retinol-binding protein-4, chemerin, and adiponectin) and with five out of eleven examined biomarkers of subclinical inflammation (high-sensitivity C-reactive protein, interleukin-6, myeloperoxidase, interleukin-22, and interleukin-1 receptor antagonist) after multivariable adjustment and correction for multiple testing. However, only IL-6 substantially attenuated the association of MR-proADM with all-cause mortality.ConclusionsWe found an association of MR-proADM with (abdominal) obesity, selected adipokines, and biomarkers of subclinical inflammation. However, the association of MR-proADM with mortality was independent of these parameters. Future studies should investigate the role of IL-6 and further characteristics of subclinical inflammation in the association between MR-proADM and all-cause mortality.

Protein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNA methylation (DNAm) signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample (Generation Scotland; n = 9537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 130 EpiScore-disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors, and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.

Abstract Background Bilirubin, a byproduct of hemoglobin breakdown and purported anti-oxidant, is thought to be cancer preventive. We conducted complementary serological and Mendelian randomization (MR) analyses to investigate whether alterations in circulating levels of bilirubin are associated with risk of colorectal cancer (CRC). We decided a priori to perform analyses separately in men and women based on suggestive evidence that associations may differ by sex. Methods In a case-control study nested in the European Prospective Investigation into Cancer and Nutrition (EPIC), pre-diagnostic unconjugated bilirubin (UCB, the main component of total bilirubin) concentrations were measured by high-performance liquid chromatography in plasma samples of 1386 CRC cases and their individually matched controls. Additionally, 115 single-nucleotide polymorphisms (SNPs) robustly associated (P

Abstract Background Advanced age-related macular degeneration (AMD) is a leading cause of blindness. While around half of the genetic contribution to advanced AMD has been uncovered, little is known about the genetic architecture of early AMD. Methods To identify genetic factors for early AMD, we conducted a genome-wide association study (GWAS) meta-analysis (14,034 cases, 91,214 controls, 11 sources of data including the International AMD Genomics Consortium, IAMDGC, and UK Biobank, UKBB). We ascertained early AMD via color fundus photographs by manual grading for 10 sources and via an automated machine learning approach for > 170,000 photographs from UKBB. We searched for early AMD loci via GWAS and via a candidate approach based on 14 previously suggested early AMD variants. Results Altogether, we identified 10 independent loci with statistical significance for early AMD: (i) 8 from our GWAS with genome-wide significance (P

Abstract Background The concentrations of the highly atherogenic lipoprotein(a) [Lp(a)] are mainly genetically determined by the LPA gene locus. However, up to 70% of the coding sequence is located in the complex so-called kringle IV type 2 (KIV-2) copy number variation, a region hardly accessible by common genotyping and sequencing technologies. Despite its size, little is known about genetic variants in this complex region. The R21X variant is a functional variant located in this region, but it has never been analyzed in large cohorts. Methods We typed R21X in 10,910 individuals from three European populations using a newly developed high-throughput allele-specific qPCR assay. R21X allelic location was determined by separating the LPA alleles using pulsed-field gel electrophoresis (PFGE) and typing them separately. Using GWAS data, we identified a proxy SNP located outside of the KIV-2. Linkage disequilibrium was determined both statistically and by long-range haplotyping using PFGE. Worldwide frequencies were determined by reanalyzing the sequencing data of the 1000 Genomes Project with a dedicated pipeline. Results R21X carriers (frequency 0.016–0.021) showed significantly lower mean Lp(a) concentrations (− 11.7 mg/dL [− 15.5; − 7.82], p = 3.39e−32). The variant is located mostly on medium-sized LPA alleles. In the 1000 Genome data, R21X mostly occurs in Europeans and South Asians, is absent in Africans, and shows varying frequencies in South American populations (0 to 0.022). Of note, the best proxy SNP was another LPA null mutation (rs41272114, D′ = 0.958, R 2 = 0.281). D′ was very high in all 1000G populations (0.986–0.996), although rs41272114 frequency varies considerably (0–0.182). Co-localization of both null mutations on the same allele was confirmed by PFGE-based long-range haplotyping. Conclusions We performed the largest epidemiological study on an LPA KIV-2 variant so far, showing that it is possible to assess LPA KIV-2 mutations on a large scale. Surprisingly, in all analyzed populations, R21X was located on the same haplotype as the splice mutation rs41272114, creating “double-null” LPA alleles. Despite being a nonsense variant, the R21X status does not provide additional information beyond the rs41272114 genotype. This has important implications for studies using LPA loss-of-function mutations as genetic instruments and emphasizes the complexity of LPA genetics.

Abstract Background Hypertension remains a significant modifiable risk factor for cardiovascular diseases and a major determinant of morbidity and mortality. We aimed to describe sex-stratified age-standardized estimates of prevalence, awareness, treatment and control of hypertension, and their associated factors in older adults. Methods The KORA-Age1 is a population-based cross-sectional survey carried out in 2008/2009 on individuals aged 65–94 years in Augsburg region, Germany. Blood pressure measurements were available for 1052 out of 1079 persons who participated in the physical examination. Factors associated with prevalence, awareness and control of hypertension were investigated by multivariable logistic regression. Results The overall prevalence of hypertension (≥140/90 mmHg) was 73.8% [95% confidence interval (CI), 69.3–77.9], representing 74.8% (95% CI, 68.4–80.2) in men and 73.5% (95% CI, 66.8–79.3) in women. Among those with hypertension, 80.2% (95% CI, 75.3–84.4) were aware of their hypertensive condition and 74.4% (95% CI, 69.2–79.1) were on treatment for hypertension. Among those aware of their hypertension status, 92.8% (95% CI, 88.8–95.6) were on treatment and 53.7% (95% CI, 47.0–60.1) had their blood pressure controlled. Hypertension was more frequent in individuals who were older, obese, or had diabetes. Higher education attainment or presence of comorbidities was associated with higher level of hypertension awareness. Individuals taking three antihypertensive drug classes were more likely to have controlled hypertension compared with those taking one antihypertensive drug class, odds ratio (OR), 1.85 (95% CI, 1.14–2.99). Conclusion Our findings identified high prevalence of hypertension and relevant health gaps on awareness, treatment and suboptimal control of hypertension in older adults in Germany. Screening for hypertension should especially target older adults with low educational attainment and ‘healthy’ elderly with less contact to physicians.

On the electrocardiogram, the PR interval reflects conduction from the atria to ventricles and also serves as risk indicator of cardiovascular morbidity and mortality. Here, the authors perform genome-wide meta-analyses for PR interval in multiple ancestries and identify 141 previously unreported genetic loci.

Objective: Sex hormone-binding globulin (SHBG) and androgens have been associated with mortality in women and men, but controversy still exists. Our objective was to investigate associations of SHBG and androgens with all-cause a nd cause-specific mortality in men and women. Design: 1006 men and 709 peri- and postmenopausal women (age range: 45–82 years) from the German population-based KORA F4 cohort study were followed-up for a median of 8.7 years. Methods: SHBG was measured with an immunoassay, total testosterone (TT) and dihydrotestosterone (DHT) with mass-spectrometry in serum samples and we calculated free testosterone (cFT). To assess associations between SHBG and androgen levels and mortality, we calculated hazard ratios (HRs) with 95% CIs using Cox proportional-hazards models. Results: In the cohort, 128 men (12.7%) and 70 women (9.9%) died. In women, we observed positive associations of SHBG with all-cause (HR: 1.54, 95% CI: 1.16–2.04) and with other disease-related mortality (HR: 1.86, 95% CI: 1.08–3.20) and for DHT with all-cause mortality (HR: 1.32, 95% CI: 1.00–1.73). In men, we found a positive association of SHBG (HR: 1.24 95% CI: 1.00–1.54) and inverse associations of TT (HR: 0.87, 95% CI: 0.77–0.97) and cFT (HR: 0.84, 95% CI: 0.73–0.97) with all-cause mortality. No other associations were found for cause-specific mortality. Conclusions: Higher SHBG levels were associated with increased risk of all-cause mortality in men and women. Lower TT and cFT levels in men and higher DHT levels in women were associated with increased risk of all-cause mortality. Future, well-powered population-based studies should further investigate cause-specific mortality risk.

Abstract Background Biomarkers may contribute to our understanding of the pathophysiology of various diseases. Type 2 diabetes (T2D) and coronary heart disease (CHD) share many clinical and lifestyle risk factors and several biomarkers are associated with both diseases. The current analysis aims to assess the relevance of biomarkers combined to pathway groups for the development of T2D and CHD in the same cohort. Methods Forty-seven serum biomarkers were measured in the MONICA/KORA case-cohort study using clinical chemistry assays and ultrasensitive molecular counting technology. The T2D (CHD) analyses included 689 (568) incident cases and 1850 (2004) non-cases from three population-based surveys. At baseline, the study participants were 35–74 years old. The median follow-up was 14 years. We computed Cox regression models for each biomarker, adjusted for age, sex, and survey. Additionally, we assigned the biomarkers to 19 etiological pathways based on information from literature. One age-, sex-, and survey-controlled average variable was built for each pathway. We used the R2 PM coefficient of determination to assess the explained disease risk. Results The associations of many biomarkers, such as several cytokines or the iron marker soluble transferrin receptor (sTfR), were similar in strength for T2D and CHD, but we also observed important differences. Lipoprotein (a) (Lp(a)) and N-terminal pro B-type natriuretic peptide (NT-proBNP) even demonstrated opposite effect directions. All pathway variables together explained 49% of the T2D risk and 21% of the CHD risk. The insulin-like growth factor binding protein 2 (IGFBP-2, IGF/IGFBP system pathway) best explained the T2D risk (about 9% explained risk, independent of all other pathway variables). For CHD, the myocardial-injury- and lipid-related-pathways were most important and both explained about 4% of the CHD risk. Conclusions The biomarker-derived pathway variables explained a higher proportion of the T2D risk compared to CHD. The ranking of the pathways differed between the two diseases, with the IGF/IGFBP-system-pathway being most strongly associated with T2D and the myocardial-injury- and lipid-related-pathways with CHD. Our results help to better understand the pathophysiology of the two diseases, with the ultimate goal of pointing out targets for lifestyle intervention and drug development to ideally prevent both T2D and CHD development.

Abstract Background Highly walkable neighbourhoods may increase transport-related and leisure-time physical activity and thus decrease the risk for obesity and obesity-related diseases, such as type 2 diabetes (T2D). Methods We investigated the association between walkability and prevalent/incident T2D in a pooled sample from five German cohorts. Three walkability measures were assigned to participant’s addresses: number of transit stations, points of interest, and impedance (restrictions to walking due to absence of intersections and physical barriers) within 640 m. We estimated associations between walkability and prevalent/incident T2D with modified Poisson regressions and adjusted for education, sex, age at baseline, and cohort. Results Of the baseline 16,008 participants, 1256 participants had prevalent T2D. Participants free from T2D at baseline were followed over a mean of 9.2 years (SD: 3.5, minimum: 1.6, maximum: 14.8 years). Of these, 1032 participants developed T2D. The three walkability measures were not associated with T2D. The estimates pointed toward a zero effect or were within 7% relative risk increase per 1 standard deviation with 95% confidence intervals including 1. Conclusion In the studied German settings, walkability differences might not explain differences in T2D.

DNA methylation is associated with complex traits and the expression of genes and proteins. Here, Zaghlool et al. perform epigenome-wide association studies for 1,123 plasma proteins, replicate obtained protein (p)QTMs in an independent cohort and find overlap of pQTMs with expression QTMs and previously reported disease associations.

Sleep duration is associated with an adverse lipid profile. Here, the authors perform genome-wide gene-by-sleep interaction analysis and find 49 previously unreported lipid loci when considering short or long total sleep time.

Abstract Background Mortality attributable to heart failure remains high. The prevalence of heart failure in patients with diabetes mellitus ranges from 19 to 26%. It is estimated that up to 21.1 million adults in the United States have diagnosed diabetes mellitus and around 80.8 million have impaired fasting glucose. We investigated the associations of fasting glucose (FG) and fasting insulin (FI), the homeostasis model assessment-insulin resistance index (HOMA-IR) and 2-h postload glucose (2HG) and insulin (2HI) with parameters of left ventricular geometry and function and arterial stiffness determined by magnetic resonance imaging in individuals without diagnosed type 2 diabetes. Methods Cross-sectional analyses of 1001 individuals (453 women, 45.3%), aged 21 to 80 years, from two independent population-based studies, the Study of Health in Pomerania (SHIP-TREND-0) and KORA FF4 Study. FG, FI, HOMA-IR, 2HG and 2HI, as well as glucose tolerance categories, were analyzed for associations with heart and arterial parameters using multivariable-adjusted linear regression models. Results In total, 390 individuals (39%) had prediabetes (isolated impaired fasting glucose, isolated glucose tolerance or both), and 49 (4.9%) were found to have unknown type 2 diabetes. In the multivariable-adjusted analysis, positive linear associations of FG, FI, HOMA-IR, 2HG and 2HI with arterial stiffness index and left ventricular wall-thickness and concentricity and inverse linear associations with left ventricular end-diastolic volume were observed. A 1 mmol/l higher FG was associated with a 1.18 ml/m2.7 (1.80 to 0.57; p

Objective: Metabolic syndrome and obesity are risk factors for chronic kidney disease. However, early kidney alterations may escape diagnosis in these conditions due to glomerular hyperfiltration. Uromodulin, a glycoprotein exclusively synthesized in tubular cells of the thick ascending limb of Henle´s loop, is a novel t issue-specific biomarker for kidney function. In contrast to the commonly used markers creatinine and cystatin C, serum uromodulin does not primarily depend on glomerular filtrat ion. We hypothesized that serum uromodulin is a marker for metabolic syndrome and related components. Design: The analyses included 1088 participants of the population-based KORA F4 study aged 62–81 years. Metabolic syndrome was present in 554 participants. After a mean follow-up time of 6.5 years, 621 participants were reevaluated, of which 92 had developed incident metabolic syndrome. Methods: The association of serum uromodulin with metabolic syndrome and its components were assessed using multivariable logistic regression models. Results: Serum uromodulin was inversely associated with metabolic syndrome after adjustment for sex, age, estimated glomerular filtration rate, p hysical activity, smoking, alcohol consumption and high-sensitivity C-reactive protein (OR 0.65; 95% CI 0.56–0.76 per standard deviation uromodulin; P < 0.001). Serum uromodulin was inversely associated with all single components of metabolic syndrome. However, serum uromodulin was not associated with new-onset metabolic syndrome after the follow-up period of 6.5 ± 0.3 years (OR 1.18; 95% CI 0.86–1.60). Conclusions: Serum uromodulin is independently associated with prevalent, but not with incident metabolic syndrome. Low serum uromodulin may indicate a decreased renal reserve in the metabolic syndrome.

The aim of this study was to compare characteristics of incident acute myocardial infarction (AMI) and first and second time reinfarctions in terms of sociodemographic characteristics, comorbidities, symptoms, treatment, clinical characteristics, medication and outcome. A further aim was to identify predictors for an increased risk of hospitalized reinfarction. Between 2000 and 2017, a total of 13,276 AMI cases were recorded by a population-based registry in the area of Augsburg, Germany, and were included in this study (11,871 incident events, 1217 cases of first-time reinfarction and 202 cases of second-time reinfarction). Median follow-up time was 5.3 years. For differences in baseline characteristics, Chi-square tests and analysis of variance (ANOVA) were calculated. To determine factors that are associated with an increased risk of hospitalized reinfarction COX regression models were fitted. Myocardial reinfarctions differ from incident events in some major characteristics such as the frequency of comorbidities, laboratory values, ECG presentation and therapy, but not regarding 28-day mortality. Moreover, typical comorbidities and risk factors (diabetes, hypertension, hyperlipidemia, smoking, impaired renal function) are associated with an increased risk of hospitalized reinfarction. Conversely, STEMI ECG, being married, German nationality and bypass surgery are predictors for a lower risk of hospitalized reinfarction. Incident AMI and reinfarction are distinctly different in many characteristics, which physicians should have in mind when treating patients with prior AMI. Typical comorbidities are risk factors for hospitalized reinfarction. This underlines the importance of comprehensive treatment of these comorbidities including education of patients and encouragement towards lifestyle adjustments.

Several studies have implied a role of magnesium in the development of cardiovascular disease (CVD). Thus, magnesium might serve as a potential risk marker for early CVD. Therefore, we investigated the association of serum magnesium and dietary magnesium intake with markers of subclinical CVD in a population-based study. We used cross-sectional data from the sub-study of the Cooperative Health Research in the Region of Augsburg (KORA-FF4). Markers of subclinical CVD, namely, left and right ventricular structure and function and carotid plaque and carotid wall thickness, were derived by magnetic resonance imaging (MRI). Multivariable-adjusted regression models were applied to assess the relationship between serum and dietary magnesium and MRI-derived subclinical CVD markers. Among 396 included participants (mean age: 56.3 ± 9.2 years; 57.8% male), 181 (45.7%) had low serum magnesium levels (p-value = 0.5). Serum magnesium was significantly associated with presence of carotid plaque (OR 1.62, p-value 0.033). Dietary magnesium was associated with higher left ventricular end-systolic and end-diastolic volume (0.04 mL/m2, 0.06 mL/m2; p-value 0.011, 0.013, respectively), and also with a decrease in left ventricular remodeling index and mean diastolic wall thickness (−0.001 g/mL/m2, −0.002 mm/m2; p-value 0.004, 0.029, respectively). In summary, there was no consistent association of serum and dietary magnesium with imaging markers of subclinical CVD.

Metabolite identification in non-targeted NMR-based metabolomics remains a challenge. While many peaks of frequently occurring metabolites are assigned, there is a high number of unknowns in high-resolution NMR spectra, hampering biological conclusions for biomarker analysis. Here, we use a cluster analysis approach to guide peak assignment via statistical correlations, which gives important information on possible structural and/or biological correlations from the NMR spectrum. Unknown peaks that cluster in close proximity to known peaks form hypotheses for their metabolite identities, thus, facilitating metabolite annotation. Subsequently, metabolite identification based on a database search, 2D NMR analysis and standard spiking is performed, whereas without a hypothesis, a full structural elucidation approach would be required. The approach allows a higher identification yield in NMR spectra, especially once pathway-related subclusters are identified.

Introduction As white matter hyperintensities (WMHs) of the brain are associated with an increased risk of stroke, cognitive decline, and depression, elucidating the associated risk factors is important. In addition to age and hypertension, pre-diabetes and diabetes may play important roles in the development of WMHs. Previous studies have, however, shown conflicting results. We aimed to investigate the effect of diabetes status and quantitative markers of glucose metabolism on WMH volume in a population-based cohort without prior cardiovascular disease.Research design and methods 400 participants underwent 3 T MRI. WMHs were manually segmented on 3D fluid-attenuated inversion recovery images. An oral glucose tolerance test (OGTT) was administered to all participants not previously diagnosed with diabetes to assess 2-hour serum glucose concentrations. Fasting glucose concentrations and glycated hemoglobin (HbA1c) levels were measured. Zero-inflated negative binomial regression analyses of WMH volume and measures of glycemic status were performed while controlling for cardiovascular risk factors and multiple testing.Results The final study population comprised 388 participants (57% male; age 56.3±9.2 years; n=98 with pre-diabetes, n=51 with diabetes). Higher WMH volume was associated with pre-diabetes (p=0.001) and diabetes (p=0.026) compared with normoglycemic control participants after adjustment for cardiovascular risk factors. 2-hour serum glucose (p

To improve ambient air quality during the 2008 Summer Olympic and Paralympic Games, the Chinese Government and Beijing’s municipal government implemented comprehensive emission control policies in Beijing and its neighboring regions before and during this period. The goal of this study was to investigate the association between particulate air pollution and cause-specific respiratory mortality before, during and after the period of the Olympic Games. Further, we wanted to assess whether changes in pollutant concentrations were linked to changes in respiratory mortality. We obtained daily data on mortality due to respiratory diseases (coded as J00-J99 according to the International Classification of Diseases and Related Health Problems 10th revision [ICD10]) and pneumonia (ICD10: J12–18), meteorology, particulate matter less than 10 µm or 2.5 μm in diameter (PM10, PM2.5) and particle number size distribution from official monitoring networks and sites located on the Peking University campus between May 20 and December 1, 2008. We assessed the effects of particulate air pollution on daily respiratory mortality using confounder-adjusted Quasi-Poisson regression models. Furthermore, we estimated air pollution effects for three periods—before (May 20 to July 20, 2008), during (August 1 to September 20, 2008) and after (October 1 to December 1, 2008)—by including interaction terms in the models. We found associations between different particle metrics and respiratory and pneumonia mortality, with more pronounced effects in smaller particle size ranges. For example, an interquartile range increase of 7,958 particles/cm3 in ultrafine particles (particles

Management of radiological incidental findings (IF) is of rising importance; however, psychosocial implications of IF reporting remain unclear. We compared long-term psychosocial effects between individuals who underwent whole-body magnetic resonance imaging (MRI) with and without reported IF, and individuals who did not undergo imaging. We used a longitudinal population-based cohort from Western Europe. Longitudinal analysis included three examinations (exam 1, 6 years prior to MRI; exam 2, MRI; exam 3, 4 years after MRI). Psychosocial outcomes included PHQ-9 (Patient Health Questionnaire), DEEX (Depression and Exhaustion Scale), PSS-10 (Perceived Stress Scale) and a Somatization Scale. Univariate analyses and adjusted linear mixed models were calculated. Among 855 included individuals, 25% (n = 212) underwent MRI and 6% (n = 50) had at least one reported IF. Compared to MRI participants, non-participants had a higher psychosocial burden indicated by PHQ-9 in exam 1 (3.3 ± 3.3 vs. 2.5 ± 2.3) and DEEX (8.6 ± 4.7 vs. 7.7 ± 4.4), Somatization Scale (5.9 ± 4.3 vs. 4.8 ± 3.8) and PSS-10 (14.7 ± 5.7 vs. 13.7 ± 5.3, all p < 0.05) in exam 3. MRI participation without IF reporting was significantly associated with lower values of DEEX, PHQ-9 and Somatization Scale. There were no significant differences at the three timepoints between MRI participants with and without IF. In conclusion, individuals who voluntarily participated in whole-body MRI had less psychosocial burden and imaging and IF reporting were not associated with adverse long-term psychosocial consequences. However, due to the study design we cannot conclude that the MRI exam itself represented a beneficial intervention causing improvement in mental health scores.

The aim of metabotyping is to categorize individuals into metabolically similar groups. Earlier studies that explored metabotyping used numerous parameters, which made it less transferable to apply. Therefore, this study aimed to identify metabotypes based on a set of standard laboratory parameters that are regularly determined in clinical practice. K-means cluster analysis was used to group 3001 adults from the KORA F4 cohort into three clusters. We identified the clustering parameters through variable importance methods, without including any specific disease endpoint. Several unique combinations of selected parameters were used to create different metabotype models. Metabotype models were then described and evaluated, based on various metabolic parameters and on the incidence of cardiometabolic diseases. As a result, two optimal models were identified: a model composed of five parameters, which were fasting glucose, HDLc, non-HDLc, uric acid, and BMI (the metabolic disease model) for clustering; and a model that included four parameters, which were fasting glucose, HDLc, non-HDLc, and triglycerides (the cardiovascular disease model). These identified metabotypes are based on a few common parameters that are measured in everyday clinical practice. These metabotypes are cost-effective, and can be easily applied on a large scale in order to identify specific risk groups that can benefit most from measures to prevent cardiometabolic diseases, such as dietary recommendations and lifestyle interventions.

Bile acids, neutral sterols, and the gut microbiome are intricately intertwined and each affects human health and metabolism. However, much is still unknown about this relationship. This analysis included 1280 participants of the KORA FF4 study. Fecal metabolites (primary and secondary bile acids, plant and animal sterols) were analyzed using a metabolomics approach. Dirichlet regression models were used to evaluate associations between the metabolites and twenty microbial subgroups that were previously identified using latent Dirichlet allocation. Significant associations were identified between 12 of 17 primary and secondary bile acids and several of the microbial subgroups. Three subgroups showed largely positive significant associations with bile acids, and six subgroups showed mostly inverse associations with fecal bile acids. We identified a trend where microbial subgroups that were previously associated with “healthy” factors were here inversely associated with fecal bile acid levels. Conversely, subgroups that were previously associated with “unhealthy” factors were positively associated with fecal bile acid levels. These results indicate that further research is necessary regarding bile acids and microbiota composition, particularly in relation to metabolic health.

Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.

Associations between diet and DNA methylation may vary among subjects with different metabolic states, which can be captured by clustering populations in metabolically homogenous subgroups, called metabotypes. Our aim was to examine the relationship between habitual consumption of various food groups and DNA methylation as well as to test for effect modification by metabotype. A cross-sectional analysis of participants (median age 58 years) of the population-based prospective KORA FF4 study, habitual dietary intake was modeled based on repeated 24-h diet recalls and a food frequency questionnaire. DNA methylation was measured using the Infinium MethylationEPIC BeadChip providing data on >850,000 sites in this epigenome-wide association study (EWAS). Three metabotype clusters were identified using four standard clinical parameters and BMI. Regression models were used to associate diet and DNA methylation, and to test for effect modification. Few significant signals were identified in the basic analysis while many significant signals were observed in models including food group-metabotype interaction terms. Most findings refer to interactions of food intake with metabotype 3, which is the metabotype with the most unfavorable metabolic profile. This research highlights the importance of the metabolic characteristics of subjects when identifying associations between diet and white blood cell DNA methylation in EWAS.