843 results found
Abelson S, Collord G, Ng SWK, et al., 2018, Prediction of acute myeloid leukaemia risk in healthy individuals., Nature
The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure1. The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion2,3. However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH)4-8. Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention.
Allione A, Pardini B, Viberti C, et al., 2018, The prognostic value of basal DNA damage level in peripheral blood lymphocytes of patients affected by bladder cancer, UROLOGIC ONCOLOGY-SEMINARS AND ORIGINAL INVESTIGATIONS, Vol: 36, ISSN: 1078-1439
Andersen ZJ, Pedersen M, Weinmayr G, et al., 2018, Long-term exposure to ambient air pollution and incidence of brain tumor: the European Study of Cohorts for Air Pollution Effects (ESCAPE), NEURO-ONCOLOGY, Vol: 20, Pages: 420-432, ISSN: 1522-8517
Assi N, Gunter MJ, Thomas DC, et al., 2018, Metabolic signature of healthy lifestyle and its relation with risk of hepatocellular carcinoma in a large European cohort., Am J Clin Nutr
Background: Studies using metabolomic data have identified metabolites from several compound classes that are associated with disease-related lifestyle factors. Objective: In this study, we identified metabolic signatures reflecting lifestyle patterns and related them to the risk of hepatocellular carcinoma (HCC) in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Design: Within a nested case-control study of 147 incident HCC cases and 147 matched controls, partial least squares (PLS) analysis related 7 modified healthy lifestyle index (HLI) variables (diet, BMI, physical activity, lifetime alcohol, smoking, diabetes, and hepatitis) to 132 targeted serum-measured metabolites and a liver function score. The association between the resulting PLS scores and HCC risk was examined in multivariable conditional logistic regression models, where ORs and 95% CIs were computed. Results: The lifestyle component's PLS score was negatively associated with lifetime alcohol, BMI, smoking, and diabetes, and positively associated with physical activity. Its metabolic counterpart was positively related to the metabolites sphingomyelin (SM) (OH) C14:1, C16:1, and C22:2, and negatively related to glutamate, hexoses, and the diacyl-phosphatidylcholine PC aaC32:1. The lifestyle and metabolomics components were inversely associated with HCC risk, with the ORs for a 1-SD increase in scores equal to 0.53 (95% CI: 0.38, 0.74) and 0.28 (0.18, 0.43), and the associated AUCs equal to 0.64 (0.57, 0.70) and 0.74 (0.69, 0.80), respectively. Conclusions: This study identified a metabolic signature reflecting a healthy lifestyle pattern which was inversely associated with HCC risk. The metabolic profile displayed a stronger association with HCC than did the modified HLI derived from questionnaire data. Measuring a specific panel of metabolites may identify strata of the population at higher risk for HCC and can add substantial discrimination compared with questionnaire
Assi N, Thomas DC, Leitzmann M, et al., 2018, Are Metabolic Signatures Mediating the Relationship between Lifestyle Factors and Hepatocellular Carcinoma Risk? Results from a Nested Case-Control Study in EPIC, CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, Vol: 27, Pages: 531-540, ISSN: 1055-9965
Campanella G, Gunter MJ, Polidoro S, et al., 2018, Epigenome-wide association study of adiposity and future risk of obesity-related diseases., Int J Obes (Lond)
BACKGROUND: Obesity is an established risk factor for several common chronic diseases such as breast and colorectal cancer, metabolic and cardiovascular diseases; however, the biological basis for these relationships is not fully understood. To explore the association of obesity with these conditions, we investigated peripheral blood leucocyte (PBL) DNA methylation markers for adiposity and their contribution to risk of incident breast and colorectal cancer and myocardial infarction. METHODS: DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population. RESULTS: We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P = 9.07×10-8 to 3.27×10-18) and lower transcriptional activity of the full-length isoform of ABCG1 (P = 6.00×10-7), higher triglyceride levels (P = 5.37×10-9) and higher triglycerides-to-HDL cholesterol ratio (P = 1.03×10-10). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P < 1.6×10-3) and one intergenic locus on chromosome 1 was inversely associated with myocardial infarcti
Castagne R, Gares V, Karimi M, et al., 2018, Allostatic load and subsequent all-cause mortality: which biological markers drive the relationship? Findings from a UK birth cohort, EUROPEAN JOURNAL OF EPIDEMIOLOGY, Vol: 33, Pages: 441-458, ISSN: 0393-2990
Courtin E, Muennig P, Verma N, et al., 2018, Conditional Cash Transfers And Health Of Low-Income Families In The US: Evaluating The Family Rewards Experiment, HEALTH AFFAIRS, Vol: 37, Pages: 438-446, ISSN: 0278-2715
Demetriou CA, Degli Esposti D, Fedinick KP, et al., 2018, Filling the gap between chemical carcinogenesis and the hallmarks of cancer: A temporal perspective, EUROPEAN JOURNAL OF CLINICAL INVESTIGATION, Vol: 48, ISSN: 0014-2972
Dossus L, Franceschi S, Biessy C, et al., 2018, Adipokines and inflammation markers and risk of differentiated thyroid carcinoma: The EPIC study, INTERNATIONAL JOURNAL OF CANCER, Vol: 142, Pages: 1332-1342, ISSN: 0020-7136
Dugue P-A, Bassett JK, Joo JE, et al., 2018, Association of DNA Methylation-Based Biological Age With Health Risk Factors and Overall and Cause-Specific Mortality, AMERICAN JOURNAL OF EPIDEMIOLOGY, Vol: 187, Pages: 529-538, ISSN: 0002-9262
Espin-Perez A, Font-Ribera L, van Veldhoven K, et al., 2018, Blood transcriptional and microRNA responses to short-term exposure to disinfection by-products in a swimming pool, ENVIRONMENT INTERNATIONAL, Vol: 110, Pages: 42-50, ISSN: 0160-4120
Espín-Pérez A, Krauskopf J, Chadeau-Hyam M, et al., 2018, Short-term transcriptome and microRNAs responses to exposure to different air pollutants in two population studies., Environ Pollut, Vol: 242, Pages: 182-190
Diesel vehicle emissions are the major source of genotoxic compounds in ambient air from urban areas. These pollutants are linked to risks of cardiovascular diseases, lung cancer, respiratory infections and adverse neurological effects. Biological events associated with exposure to some air pollutants are widely unknown but applying omics techniques may help to identify the molecular processes that link exposure to disease risk. Most data on health risks are related to long-term exposure, so the aim of this study is to investigate the impact of short-term exposure (two hours) to air pollutants on the blood transcriptome and microRNA expression levels. We analyzed transcriptomics and microRNA expression using microarray technology on blood samples from volunteers participating in studies in London, the Oxford Street cohort, and, in Barcelona, the TAPAS cohort. Personal exposure levels measurements of particulate matter (PM10, PM2.5), ultrafine particles (UFPC), nitrogen oxides (NO2, NO and NOx), black carbon (BC) and carbon oxides (CO and CO2) were registered for each volunteer. Associations between air pollutant levels and gene/microRNA expression were evaluated using multivariate normal models (MVN). MVN-models identified compound-specific expression of blood cell genes and microRNAs associated with air pollution despite the low exposure levels, the short exposure periods and the relatively small-sized cohorts. Hsa-miR-197-3p, hsa-miR-29a-3p, hsa-miR-15a-5p, hsa-miR-16-5p and hsa-miR-92a-3p are found significantly expressed in association with exposures. These microRNAs target also relevant transcripts, indicating their potential relevance in the research of omics-biomarkers responding to air pollution. Furthermore, these microRNAs are also known to be associated with diseases previously linked to air pollution exposure including several cancers such lung cancer and Alzheimer's disease. In conclusion, we identified in this study promising compound-specific mRN
Ferrero G, Cordero F, Tarallo S, et al., 2018, Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy individuals: description of the diverse and most represented species, ONCOTARGET, Vol: 9, Pages: 3097-3111, ISSN: 1949-2553
Fiorito G, Vlaanderen J, Polidoro S, et al., 2018, Oxidative stress and inflammation mediate the effect of air pollution on cardio- and cerebrovascular disease: A prospective study in nonsmokers, ENVIRONMENTAL AND MOLECULAR MUTAGENESIS, Vol: 59, Pages: 234-246, ISSN: 0893-6692
Gulliver J, Morley D, Dunster C, et al., 2018, Land use regression models for the oxidative potential of fine particles (PM2.5) in five European areas, ENVIRONMENTAL RESEARCH, Vol: 160, Pages: 247-255, ISSN: 0013-9351
Herceg Z, Ghantous A, Wild CP, et al., 2018, Roadmap for investigating epigenome deregulation and environmental origins of cancer, INTERNATIONAL JOURNAL OF CANCER, Vol: 142, Pages: 874-882, ISSN: 0020-7136
Integrative Analysis of Lung Cancer Etiology and Risk INTEGRAL Consortium for Early Detection of Lung Cancer, Guida F, Sun N, et al., 2018, Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins., JAMA Oncol
Importance: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. Objective: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. Design, Setting, and Participants: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). Main Outcomes and Measures: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). Results: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity
Jain P, Vineis P, Liquet B, et al., 2018, A multivariate approach to investigate the combined biological effects of multiple exposures., J Epidemiol Community Health, Vol: 72, Pages: 564-571
Epidemiological studies provide evidence that environmental exposures may affect health through complex mixtures. Formal investigation of the effect of exposure mixtures is usually achieved by modelling interactions, which relies on strong assumptions relating to the identity and the number of the exposures involved in such interactions, and on the order and parametric form of these interactions. These hypotheses become difficult to formulate and justify in an exposome context, where influential exposures are numerous and heterogeneous. To capture both the complexity of the exposome and its possibly pleiotropic effects, models handling multivariate predictors and responses, such as partial least squares (PLS) algorithms, can prove useful. As an illustrative example, we applied PLS models to data from a study investigating the inflammatory response (blood concentration of 13 immune markers) to the exposure to four disinfection by-products (one brominated and three chlorinated compounds), while swimming in a pool. To accommodate the multiple observations per participant (n=60; before and after the swim), we adopted a multilevel extension of PLS algorithms, including sparse PLS models shrinking loadings coefficients of unimportant predictors (exposures) and/or responses (protein levels). Despite the strong correlation among co-occurring exposures, our approach identified a subset of exposures (n=3/4) affecting the exhaled levels of 8 (out of 13) immune markers. PLS algorithms can easily scale to high-dimensional exposures and responses, and prove useful for exposome research to identify sparse sets of exposures jointly affecting a set of (selected) biological markers. Our descriptive work may guide these extensions for higher dimensional data.
Jeong A, Fiorito G, Keski-Rahkonen P, et al., 2018, Perturbation of metabolic pathways mediates the association of air pollutants with asthma and cardiovascular diseases., Environ Int, Vol: 119, Pages: 334-345
BACKGROUND: Epidemiologic evidence indicates common risk factors, including air pollution exposure, for respiratory and cardiovascular diseases, suggesting the involvement of common altered molecular pathways. OBJECTIVES: The goal was to find intermediate metabolites or metabolic pathways that could be associated with both air pollutants and health outcomes ("meeting-in-the-middle"), thus shedding light on mechanisms and reinforcing causality. METHODS: We applied a statistical approach named 'meet-in-the-middle' to untargeted metabolomics in two independent case-control studies nested in cohorts on adult-onset asthma (AOA) and cardio-cerebrovascular diseases (CCVD). We compared the results to identify both common and disease-specific altered metabolic pathways. RESULTS: A novel finding was a strong association of AOA with ultrafine particles (UFP; odds ratio 1.80 [1.26, 2.55] per increase by 5000 particles/cm3). Further, we have identified several metabolic pathways that potentially mediate the effect of air pollution on health outcomes. Among those, perturbation of Linoleate metabolism pathway was associated with air pollution exposure, AOA and CCVD. CONCLUSIONS: Our results suggest common pathway perturbations may occur as a consequence of chronic exposure to air pollution leading to increased risk for both AOA and CCVD.
Krauskopf J, Caiment F, van Veldhoven K, et al., 2018, The human circulating miRNome reflects multiple organ disease risks in association with short-term exposure to traffic-related air pollution, ENVIRONMENT INTERNATIONAL, Vol: 113, Pages: 26-34, ISSN: 0160-4120
Liu S, Grigoryan H, Edmands WMB, et al., 2018, Cys34 Adductomes Differ between Patients with Chronic Lung or Heart Disease and Healthy Controls in Central London, ENVIRONMENTAL SCIENCE & TECHNOLOGY, Vol: 52, Pages: 2307-2313, ISSN: 0013-936X
Mackenbach JP, Valverde JR, Artnik B, et al., 2018, Trends in health inequalities in 27 European countries, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 115, Pages: 6440-6445, ISSN: 0027-8424
Murphy N, Achaintre D, Zamora-Ros R, et al., 2018, A prospective evaluation of plasma polyphenol levels and colon cancer risk., Int J Cancer
Polyphenols have been shown to exert biological activity in experimental models of colon cancer; however, human data linking specific polyphenols to colon cancer is limited. We assessed the relationship between pre-diagnostic plasma polyphenols and colon cancer risk in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition study. Using high pressure liquid chromatography coupled to tandem mass spectrometry, we measured concentrations of 35 polyphenols in plasma from 809 incident colon cancer cases and 809 matched controls. We used multivariable adjusted conditional logistic regression models that included established colon cancer risk factors. The false discovery rate (qvalues ) was computed to control for multiple comparisons. All statistical tests were two-sided. After false discovery rate correction and in continuous log2 -transformed multivariable models, equol (odds ratio [OR] per log2 -value, 0.86, 95% confidence interval [95% CI] = 0.79-0.93; qvalue = 0.01) and homovanillic acid (OR per log2 -value, 1.46, 95% CI = 1.16-1.84; qvalue = 0.02) were associated with colon cancer risk. Comparing extreme fifths, equol concentrations were inversely associated with colon cancer risk (OR = 0.61, 95% CI = 0.41-0.91, ptrend = 0.003), while homovanillic acid concentrations were positively associated with colon cancer development (OR = 1.72, 95% CI = 1.17-2.53, ptrend < 0.0001). No heterogeneity for these associations was observed by sex and across other colon cancer risk factors. The remaining polyphenols were not associated with colon cancer risk. Higher equol concentrations were associated with lower risk, and higher homovanillic acid concentrations were associated with greater risk of colon cancer. These findings support a potential role for specific polyphenols in colon tumorigene
Nagel G, Stafoggia M, Pedersen M, et al., 2018, Air pollution and incidence of cancers of the stomach and the upper aerodigestive tract in the European Study of Cohorts for Air Pollution Effects (ESCAPE)., Int J Cancer
Air pollution has been classified as carcinogenic to humans. However, to date little is known about the relevance for cancers of the stomach and upper aerodigestive tract (UADT). We investigated the association of long-term exposure to ambient air pollution with incidence of gastric and UADT cancer in 11 European cohorts. Air pollution exposure was assigned by land-use regression models for particulate matter (PM) below 10 µm (PM10 ), below 2.5 µm (PM2.5 ), between 2.5 and 10 µm (PMcoarse ), PM2.5 absorbance and nitrogen oxides (NO2 and NOX ) as well as approximated by traffic indicators. Cox regression models with adjustment for potential confounders were used for cohort-specific analyses. Combined estimates were determined with random effects meta-analyses. During average follow-up of 14.1 years of 305 551 individuals, 744 incident cases of gastric cancer and 933 of UADT cancer occurred. The hazard ratio for an increase of 5 µg/m3 of PM2.5 was 1.38 (95%-CI 0.99;1.92) for gastric and 1.05 (95%-CI 0.62;1.77) for UADT cancers. No associations were found for any of the other exposures considered. Adjustment for additional confounders and restriction to study participants with stable addresses did not influence markedly the effect estimate for PM2.5 and gastric cancer. Higher estimated risks of gastric cancer associated with PM2.5 was found in men (HR 1.98 (1.30;3.01)) as compared to women (HR 0.85 (0.5;1.45)). This large multicentre cohort study shows an association between long-term exposure to PM2.5 and gastric cancer, but not UADT cancers, suggesting that air pollution may contribute to gastric cancer risk. This article is protected by copyright. All rights reserved.
Pardini B, Cordero F, Naccarati A, et al., 2018, microRNA profiles in urine by next-generation sequencing can stratify bladder cancer subtypes., Oncotarget, Vol: 9, Pages: 20658-20669
Bladder cancer (BC) is the most frequent malignancy of the urinary tract with a high incidence in men and smokers. Currently, there are no non-invasive markers useful for BC diagnosis and subtypes classification that could overcome invasive procedures such as cystoscopy. Dysregulated miRNA profiles have been associated with numerous cancers, including BC. Cell-free miRNAs are abundantly present in a variety of biofluids including urine and make them promising candidates in cancer biomarker discovery. In the present study, the identification of miRNA fingerprints associated with different BC status was performed by next-generation sequencing on urine samples from 66 BC and 48 controls. Three signatures based on dysregulated miRNAs have been identified by regression models, assessing the power to discriminate different BC subtypes. Altered miRNAs according to invasiveness and grade were validated by qPCR on 112 cases and 65 controls (among which 46 cases and 16 controls were an independent group of subjects while the rest were replica samples). The area under the curve (AUC) computed including three miRNAs (miR-30a-5p, let-7c-5p and miR-486-5p) altered in all BC subtypes showed a significantly increased accuracy in the discrimination of cases and controls (AUC model = 0.70; p-value = 0.01). In conclusions, the non-invasive detection in urine of a selected number of miRNAs altered in different BC subtypes could lead to an accurate early diagnosis of cancer and stratification of patients.
Pedersen M, Stafoggia M, Weinmayr G, et al., 2018, Is There an Association Between Ambient Air Pollution and Bladder Cancer Incidence? Analysis of 15 European Cohorts., Eur Urol Focus, Vol: 4, Pages: 113-120
BACKGROUND: Ambient air pollution contains low concentrations of carcinogens implicated in the etiology of urinary bladder cancer (BC). Little is known about whether exposure to air pollution influences BC in the general population. OBJECTIVE: To evaluate the association between long-term exposure to ambient air pollution and BC incidence. DESIGN, SETTING, AND PARTICIPANTS: We obtained data from 15 population-based cohorts enrolled between 1985 and 2005 in eight European countries (N=303431; mean follow-up 14.1 yr). We estimated exposure to nitrogen oxides (NO2 and NOx), particulate matter (PM) with diameter <10μm (PM10), <2.5μm (PM2.5), between 2.5 and 10μm (PM2.5-10), PM2.5absorbance (soot), elemental constituents of PM, organic carbon, and traffic density at baseline home addresses using standardized land-use regression models from the European Study of Cohorts for Air Pollution Effects project. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We used Cox proportional-hazards models with adjustment for potential confounders for cohort-specific analyses and meta-analyses to estimate summary hazard ratios (HRs) for BC incidence. RESULTS AND LIMITATIONS: During follow-up, 943 incident BC cases were diagnosed. In the meta-analysis, none of the exposures were associated with BC risk. The summary HRs associated with a 10-μg/m3 increase in NO2 and 5-μg/m3 increase in PM2.5 were 0.98 (95% confidence interval [CI] 0.89-1.08) and 0.86 (95% CI 0.63-1.18), respectively. Limitations include the lack of information about lifetime exposure. CONCLUSIONS: There was no evidence of an association between exposure to outdoor air pollution levels at place of residence and risk of BC. PATIENT SUMMARY: We assessed the link between outdoor air pollution at place of residence and bladder cancer using the largest study population to date and extensive assessment of exposure and comprehensive data on personal risk factors such as smoking. We found no association between
Perrier F, Novoloaca A, Ambatipudi S, et al., 2018, Identifying and correcting epigenetics measurements for systematic sources of variation, CLINICAL EPIGENETICS, Vol: 10, ISSN: 1868-7083
Petrovic D, de Mestral C, Bochud M, et al., 2018, The contribution of health behaviors to socioeconomic inequalities in health: A systematic review, PREVENTIVE MEDICINE, Vol: 113, Pages: 15-31, ISSN: 0091-7435
Plusquin M, Chadeau-Hyam M, Ghantous A, et al., 2018, DNA Methylome Marks of Exposure to Particulate Matter at Three Time Points in Early Life, ENVIRONMENTAL SCIENCE & TECHNOLOGY, Vol: 52, Pages: 5427-5437, ISSN: 0013-936X
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