Dataset Information

Circulating levels of inflammatory markers and DNA methylation, an analysis of repeated samples from a population based cohort.

ABSTRACT: DNA methylation in blood may adapt to conditions affecting our health, such as inflammation, and multiple studies have identified differential DNA methylation related to smoking, obesity and various diseases. The purpose of this study was to evaluate previously reported, and explore possible new, associations between levels of inflammatory markers and DNA methylation in blood. We used a well-characterized study population consisting of 127 individuals, all of whom were participants in the population-based Västerbotten Intervention Programme cohort and had provided two blood samples, ten years apart. Levels of CRP and 160 other proteins were measured in plasma, and DNA methylation levels (assessed using the 850K Illumina Infinium MethylationEPIC BeadChip) were measured in white blood cell DNA. Associations between CpG methylation and protein levels were estimated using linear mixed models. In the study we were able to confirm the direction for 85 of 102 previously reported protein-methylation associations. Depicting associations in a network allowed us to identify CpG sites with associations to multiple proteins, and ten CpG sites were each associated with three or more inflammatory markers. Furthermore, two genetic regions included nine additional unreported CpG sites that may represent trans-acting methylation sites. Our study supports a complex interaction between DNA methylation and circulating proteins involved in the inflammatory response. The notion of trans-acting methylation sites affecting, or being affected by, the expression of genes on completely different chromosomes should be taken into account when interpreting results from epigenome-wide association studies.

SUBMITTER: Myte R

PROVIDER: S-EPMC6557598 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Circulating levels of inflammatory markers and DNA methylation, an analysis of repeated samples from a population based cohort.

Myte Robin R Sundkvist Anneli A Van Guelpen Bethany B Harlid Sophia S

Epigenetics 20190429 7

DNA methylation in blood may adapt to conditions affecting our health, such as inflammation, and multiple studies have identified differential DNA methylation related to smoking, obesity and various diseases. The purpose of this study was to evaluate previously reported, and explore possible new, associations between levels of inflammatory markers and DNA methylation in blood. We used a well-characterized study population consisting of 127 individuals, all of whom were participants in the popula ...[more]

PMID: 31033411

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Project description:BackgroundDetection of cancer and identification of tumor origin at an early stage improve the survival and prognosis of patients. Herein, we proposed a plasma cfDNA-based approach called TOTEM to detect and trace the cancer signal origin (CSO) through methylation markers.MethodsWe performed enzymatic conversion-based targeted methylation sequencing on plasma cfDNA samples collected from a clinical cohort of 500 healthy controls and 733 cancer patients with seven types of cancer (breast, colorectum, esophagus, stomach, liver, lung, and pancreas) and randomly divided these samples into a training cohort and a testing cohort. An independent validation cohort of 143 healthy controls, 79 liver cancer patients and 100 stomach cancer patients were recruited to validate the generalizability of our approach.ResultsA total of 57 multi-cancer diagnostic markers and 873 CSO markers were selected for model development. The binary diagnostic model achieved an area under the curve (AUC) of 0.907, 0.908 and 0.868 in the training, testing and independent validation cohorts, respectively. With a training specificity of 98%, the specificities in the testing and independent validation cohorts were 100% and 98.6%, respectively. Overall sensitivity across all cancer stages was 65.5%, 67.3% and 55.9% in the training, testing and independent validation cohorts, respectively. Early-stage (I and II) sensitivity was 50.3% and 45.7% in the training and testing cohorts, respectively. For cancer patients correctly identified by the binary classifier, the top 1 and top 2 CSO accuracies were 77.7% and 86.5% in the testing cohort (n = 148) and 76.0% and 84.0% in the independent validation cohort (n = 100). Notably, performance was maintained with only 21 diagnostic and 214 CSO markers, achieving a training AUC of 0.865, a testing AUC of 0.866, and an integrated top 2 accuracy of 83.1% in the testing cohort.ConclusionsTOTEM demonstrates promising potential for accurate multi-cancer detection and localization by profiling plasma methylation markers. The real-world clinical performance of our approach needs to be investigated in a much larger prospective cohort.

Dataset Information

Circulating levels of inflammatory markers and DNA methylation, an analysis of repeated samples from a population based cohort.

Publications

Circulating levels of inflammatory markers and DNA methylation, an analysis of repeated samples from a population based cohort.

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