24 research outputs found

    KIM-1 as a blood-based marker for early detection of kidney cancer: a prospective nested case-control study

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    Purpose: Renal cell carcinoma (RCC) has the potential for cure with surgery when diagnosed at an early stage. Kidney injury molecule-1 (KIM-1) has been shown to be elevated in the plasma of RCC patients. We aimed to test whether plasma KIM-1 could represent a means of detecting RCC prior to clinical diagnosis. Experimental Design: KIM-1 concentrations were measured in pre-diagnostic plasma from 190 RCC cases and 190 controls nested within a population-based prospective cohort study. Cases had entered the cohort up to five years before diagnosis, and controls were matched on cases for date of birth, date at blood donation, sex, and country. We applied conditional logistic regression and flexible parametric survival models to evaluate the association between plasma KIM-1 concentrations and RCC risk and survival. Results: The incidence rate ratio (IRR) of RCC for a doubling in KIM-1 concentration was 1.71 (95% confidence interval [CI]: 1.44-2.03, p-value = 4.1x10-23), corresponding to an IRR of 63.3 (95% CI: 16.2-246.9) comparing the 80th to the 20th percentile of the KIM-1 distribution in this sample. Compared with a risk model including known risk factors of RCC (age, sex, country, body mass index and tobacco smoking status), a risk model additionally including KIM-1 substantially improved discrimination between cases and controls (area under the receiver operating characteristic curve of 0.8 compared to 0.7). High plasma KIM-1 concentrations were also associated with poorer survival (p=0.0053). Conclusions: Plasma KIM-1 concentrations could predict RCC incidence up to 5 years prior to diagnosis and were associated with poorer survival

    Bedmap2: improved ice bed, surface and thickness datasets for Antarctica

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    We present Bedmap2, a new suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60° S. We derived these products using data from a variety of sources, including many substantial surveys completed since the original Bedmap compilation (Bedmap1) in 2001. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1. In most parts of Antarctica the subglacial landscape is visible in much greater detail than was previously available and the improved data-coverage has in many areas revealed the full scale of mountain ranges, valleys, basins and troughs, only fragments of which were previously indicated in local surveys. The derived statistics for Bedmap2 show that the volume of ice contained in the Antarctic ice sheet (27 million km3) and its potential contribution to sea-level rise (58 m) are similar to those of Bedmap1, but the mean thickness of the ice sheet is 4.6% greater, the mean depth of the bed beneath the grounded ice sheet is 72 m lower and the area of ice sheet grounded on bed below sea level is increased by 10%. The Bedmap2 compilation highlights several areas beneath the ice sheet where the bed elevation is substantially lower than the deepest bed indicated by Bedmap1. These products, along with grids of data coverage and uncertainty, provide new opportunities for detailed modelling of the past and future evolution of the Antarctic ice sheets

    Bedmap2: improved ice bed, surface and thickness datasets for Antarctica

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    We present Bedmap2, a new suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60 S. We derived these products using data from a variety of sources, including many substantial surveys completed since the original Bedmap compilation (Bedmap1) in 2001. In particular, the Bedmap2 ice thickness grid is made from 25 million measurements, over two orders of magnitude more than were used in Bedmap1. In most parts of Antarctica the subglacial landscape is visible in much greater detail than was previously available and the improved datacoverage has in many areas revealed the full scale of mountain ranges, valleys, basins and troughs, only fragments of which were previously indicated in local surveys. The derived statistics for Bedmap2 show that the volume of ice contained in the Antarctic ice sheet (27 million km3) and its potential contribution to sea-level rise (58 m) are similar to those of Bedmap1, but the mean thickness of the ice sheet is 4.6% greater, the mean depth of the bed beneath the grounded ice sheet is 72m lower and the area of ice sheet grounded on bed below sea level is increased by 10 %. The Bedmap2 compilation highlights several areas beneath the ice sheet where the bed elevation is substantially lower than the deepest bed indicated by Bedmap1. These products, along with grids of data coverage and uncertainty, provide new opportunities for detailed modelling of the past and future evolution of the Antarctic ice sheets

    Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: A multi-cohort analysis

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    Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life. We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries. The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect. Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity

    Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: A multi-cohort analysis

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    Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life.We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries.The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect.Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity

    Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis

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    Background: Epidemiological and experimental evidence has linked chronic inflammation to cancer aetiology. It is unclear whether associations for specific inflammatory biomarkers are causal or due to bias. In order to examine whether altered genetically predicted concentration of circulating cytokines are associated with cancer development, we performed a two-sample Mendelian randomisation (MR) analysis.Methods: Up to 31,112 individuals of European descent were included in genome-wide association study (GWAS) meta-analyses of 47 circulating cytokines. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene (cis), were used as instrumental variables. Inverse-variance weighted MR was used as the primary analysis, and the MR assumptions were evaluated in sensitivity and colocalization analyses and a false discovery rate (FDR) correction for multiple comparisons was applied. Corresponding germline GWAS summary data for five cancer outcomes (breast, endometrial, lung, ovarian, and prostate), and their subtypes were selected from the largest cancer-specific GWASs available (cases ranging from 12,906 for endometrial to 133,384 for breast cancer).Results: There was evidence of inverse associations of macrophage migration inhibitory factor with breast cancer (OR per SD = 0.88, 95% CI 0.83 to 0.94), interleukin-1 receptor antagonist with endometrial cancer (0.86, 0.80 to 0.93), interleukin-18 with lung cancer (0.87, 0.81 to 0.93), and beta-chemokine-RANTES with ovarian cancer (0.70, 0.57 to 0.85) and positive associations of monokine induced by gamma interferon with endometrial cancer (3.73, 1.86 to 7.47) and cutaneous T-cell attracting chemokine with lung cancer (1.51, 1.22 to 1.87). These associations were similar in sensitivity analyses and supported in colocalization analyses.Conclusions: Our study adds to current knowledge on the role of specific inflammatory biomarker pathways in cancer aetiology. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for cancer prevention.</p

    Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: A multi-cohort analysis

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    Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life. We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries. The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect. Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity

    Antarctic Bedmap data: Findable, Accessible, Interoperable, and Reusable (FAIR) sharing of 60 years of ice bed, surface, and thickness data

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    One of the key components of this research has been the mapping of Antarctic bed topography and ice thickness parameters that are crucial for modelling ice flow and hence for predicting future ice loss and the ensuing sea level rise. Supported by the Scientific Committee on Antarctic Research (SCAR), the Bedmap3 Action Group aims not only to produce new gridded maps of ice thickness and bed topography for the international scientific community, but also to standardize and make available all the geophysical survey data points used in producing the Bedmap gridded products. Here, we document the survey data used in the latest iteration, Bedmap3, incorporating and adding to all of the datasets previously used for Bedmap1 and Bedmap2, including ice bed, surface and thickness point data from all Antarctic geophysical campaigns since the 1950s. More specifically, we describe the processes used to standardize and make these and future surveys and gridded datasets accessible under the Findable, Accessible, Interoperable, and Reusable (FAIR) data principles. With the goals of making the gridding process reproducible and allowing scientists to re-use the data freely for their own analysis, we introduce the new SCAR Bedmap Data Portal (https://bedmap.scar.org, last access: 1 March 2023) created to provide unprecedented open access to these important datasets through a web-map interface. We believe that this data release will be a valuable asset to Antarctic research and will greatly extend the life cycle of the data held within it. Data are available from the UK Polar Data Centre: https://data.bas.ac.uk (last access: 5 May 2023​​​​​​​). See the Data availability section for the complete list of datasets.</p

    Producing the ideal fascist landscape:nature, materiality and the cinematic representation of land reclamation in the Pontine Marshes

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    BACKGROUND: DNA methylation changes in peripheral blood have recently been identified in relation to lung cancer risk. Some of these changes have been suggested to mediate part of the effect of smoking on lung cancer. However, limitations with conventional mediation analyses mean that the causal nature of these methylation changes has yet to be fully elucidated. METHODS: We first performed a meta-analysis of four epigenome-wide association studies (EWAS) of lung cancer (918 cases, 918 controls). Next, we conducted a two-sample Mendelian randomization analysis, using genetic instruments for methylation at CpG sites identified in the EWAS meta-analysis, and 29&nbsp;863 cases and 55&nbsp;586 controls from the TRICL-ILCCO lung cancer consortium, to appraise the possible causal role of methylation at these sites on lung cancer. RESULTS: Sixteen CpG sites were identified from the EWAS meta-analysis [false discovery rate (FDR) &lt; 0.05], for 14 of which we could identify genetic instruments. Mendelian randomization provided little evidence that DNA methylation in peripheral blood at the 14 CpG sites plays a causal role in lung cancer development (FDR &gt; 0.05), including for cg05575921-AHRR where methylation is strongly associated with both smoke exposure and lung cancer risk. CONCLUSIONS: The results contrast with previous observational and mediation analysis, which have made strong claims regarding the causal role of DNA methylation. Thus, previous suggestions of a mediating role of methylation at sites identified in peripheral blood, such as cg05575921-AHRR, could be unfounded. However, this study does not preclude the possibility that differential DNA methylation at other sites is causally involved in lung cancer development, especially within lung tissue

    Stochastic epigenetic mutations are associated with risk of breast cancer, lung cancer, and mature b-cell neoplasms

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    Background: Age-related epigenetic dysregulations are associated with several diseases, including cancer. The number of stochastic epigenetic mutations (SEM) has been suggested as a biomarker of life-course accumulation of exposure-related DNA damage; however, the predictive role of SEMs in cancer has seldom been investigated. Methods: A SEM, at a given CpG site, was defined as an extreme outlier of DNA methylation value distribution across individuals. We investigated the association of the total number of SEMs with the risk of eight cancers in 4,497 case-control pairs nested in three prospective cohorts. Furthermore, we investigated whether SEMs were randomly distributed across the genome or enriched in functional genomic regions. Results: In the three-study meta-analysis, the estimated ORs per one-unit increase in log(SEM) from logistic regression models adjusted for age and cancer risk factors were 1.25; 95% confidence interval (CI), 1.11-1.41 for breast cancer, and 1.23; 95% CI, 1.07-1.42 for lung cancer. In the Melbourne Collaborative Cohort Study, the OR for mature B-cell neoplasm was 1.46; 95% CI, 1.25-1.71. Enrichment analyses indicated that SEMs frequently occur in silenced genomic regions and in transcription factor binding sites regulated by EZH2 and SUZ12 (P &lt; 0.0001 and P ¼ 0.0005, respectively): two components of the polycomb repressive complex 2 (PCR2). Finally, we showed that PCR2-specific SEMs are generally more stable over time compared with SEMs occurring in the whole genome. Conclusions: The number of SEMs is associated with a higher risk of different cancers in prediagnostic blood samples. Impact: We identified a candidate biomarker for cancer early detection, and we described a carcinogenesis mechanism involving PCR2 complex proteins worthy of further investigations.The authors are very thankful to Dr. Akram Ghantous (IARC, Lyon, France) for the methylation analyses of PEM-Turin study, produced within the Exposomics EC FP7 grant (grant agreement no. 308610, to P. Vineis). The results here are, in part, based upon data generated by TCGA research network: https://www.cancer.gov/tcga. The EPIC Italy component of this research was supported by European Commission grant no. 633666, awarded to P. Vineis, and by the AIRC grant (Progetto IG 2013 N.14410, to C. Sacerdote) for part of the DNA methylation experiments. The Melbourne Collaborative Cohort Study (MCCS) cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS component of the work was funded by the Australian National Health and Medical Research Council, including grants 1106016 (to G.G. Giles); 1011618 (to L. Baglietto); 1026892 (to M.C. Southey); 1027505 (to D.R. English); 1050198 and 1087683 (to A.M. Hodge); 1088405 (to R.L. Milne); and 1043616, 209057, 396414, and 1074383 (to G.G. Giles). Cases and their vital status were ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database. The NOWAC component of the work was supported by the European Research Council Advanced Researcher grant, 2008: Transcriptomics in cancer research (grant no. ERC-2008-AdG, to E. Lund)
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