BackgroundMany different methods exist to adjust for variability in cell-type mixture proportions when analyzing DNA methylation studies. Here we present the result of an extensive simulation study, built on cell-separated DNA methylation profiles from Illumina Infinium 450K methylation data, to compare the performance of eight methods including the most commonly used approaches.ResultsWe designed a rich multi-layered simulation containing a set of probes with true associations with either binary or continuous phenotypes, confounding by cell type, variability in means and standard deviations for population parameters, additional variability at the level of an individual cell-type-specific sample, and variability in the mixture proportions across samples. Performance varied quite substantially across methods and simulations. In particular, the number of false positives was sometimes unrealistically high, indicating limited ability to discriminate the true signals from those appearing significant through confounding. Methods that filtered probes had consequently poor power. QQ plots of p values across all tested probes showed that adjustments did not always improve the distribution. The same methods were used to examine associations between smoking and methylation data from a case–control study of colorectal cancer, and we also explored the effect of cell-type adjustments on associations between rheumatoid arthritis cases and controls.ConclusionsWe recommend surrogate variable analysis for cell-type mixture adjustment since performance was stable under all our simulated scenarios.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0935-y) contains supplementary material, which is available to authorized users.

Background:This study explored state-related tendencies in DNA methylation in people with anorexia nervosa. Methods: We measured genome-wide DNA methylation in 75 women with active anorexia nervosa (active), 31 women showing stable remission of anorexia nervosa (remitted) and 41 women with no eating disorder (NED). We also obtained postintervention methylation data from 52 of the women from the active group. Results: Comparisons between members of the active and NED groups showed 58 differentially methylated sites (Q < 0.01) that corresponded to genes relevant to metabolic and nutritional status (lipid and glucose metabolism), psychiatric status (serotonin receptor activity) and immune function. Methylation levels in members of the remitted group differed from those in the active group on 265 probes that also involved sites associated with genes for serotonin and insulin activity, glucose metabolism and immunity. Intriguingly, the direction of methylation effects in remitted participants tended to be opposite to those seen in active participants. The chronicity of Illness correlated (usually inversely, at Q < 0.01) with methylation levels at 64 sites that mapped onto genes regu lating glutamate and serotonin activity, insulin function and epigenetic age. In contrast, body mass index increases coincided (at Q < 0.05) with generally increased methylation-level changes at 73 probes associated with lipid and glucose metabolism, immune and inflammatory processes, and olfaction. Limitations: Sample sizes were modest for this type of inquiry, and findings may have been subject to uncontrolled effects of medication and substance use. Conclusion: Findings point to the possibility of reversible epigenetic alterations in anorexia nervosa, and suggest that an adequate pathophysiological model would likely need to include psychiatric, metabolic and immune components.

Background: Many different methods exist to adjust for variability in cell-type

Motivation The human microbiota is the collection of microorganisms colonizing the human body, and plays an integral part in human health. A growing trend in microbiome analysis is to construct a network to estimate the co-occurrence patterns among taxa through precision matrices. Existing methods do not facilitate investigation into how these networks change with respect to covariates. Results We propose a new model called Microbiome Differential Network Estimation (MDiNE) to estimate network changes with respect to a binary covariate. The counts of individual taxa in the samples are modeled through a multinomial distribution whose probabilities depend on a latent Gaussian random variable. A sparse precision matrix over all the latent terms determines the co-occurrence network among taxa. The model fit is obtained and evaluated using Hamiltonian Monte Carlo methods. The performance of our model is evaluated through an extensive simulation study and is shown to outperform existing methods in terms of estimation of network parameters. We also demonstrate an application of the model to estimate changes in the intestinal microbial network topology with respect to Crohn’s disease. Availability and implementation MDiNE is implemented in a freely available R package: https://github.com/kevinmcgregor/mdine. Supplementary information Supplementary data are available at Bioinformatics online.

Objective Nearly 20%–29% of patients with colorectal cancer (CRC) succumb to liver or lung metastasis and there is a dire need for novel targets to improve the survival of patients with metastasis. The long isoform of the Carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1-L or CC1-L) is a key regulator of immune surveillance in primary CRC, but its role in metastasis remains largely unexplored. We have examined how CC1-L expression impacts on colon cancer liver metastasis. Design Murine MC38 transfected with CC1-L were evaluated in vitro for proliferation, migration and invasion, and for in vivo experimental liver metastasis. Using shRNA silencing or pharmacological inhibition, we delineated the role in liver metastasis of Chemokine (C-C motif) Ligand 2 (CCL2) and Signal Transducer and Activator of Transcription 3 (STAT3) downstream of CC1-L. We further assessed the clinical relevance of these findings in a cohort of patients with CRC. Results MC38-CC1-L-expressing cells exhibited significantly reduced in vivo liver metastasis and displayed decreased CCL2 chemokine secretion and reduced STAT3 activity. Down-modulation of CCL2 expression and pharmacological inhibition of STAT3 activity in MC38 cells led to reduced cell invasion capacity and decreased liver metastasis. The clinical relevance of our findings is illustrated by the fact that high CC1 expression in patients with CRC combined with some inflammation-regulated and STAT3-regulated genes correlate with improved 10-year survival. Conclusions CC1-L regulates inflammation and STAT3 signalling and contributes to the maintenance of a less-invasive CRC metastatic phenotype of poorly differentiated carcinomas.

Motivation:The human microbiota is the collection of microorganisms colonizing the human body, and plays an integral part in human health. A growing trend in microbiome analysis is to construct a network to estimate the co-occurrence patterns among taxa though precision matrices. Existing methods do not facilitate investigation into how these networks change with respect to covariates. Results:We propose a new model called Microbiome Differential Network Estimation (MDiNE) to estimate network changes with respect to a binary covariate. The counts of individual taxa in the samples are modelled through a multinomial distribution whose probabilities depend on a latent Gaussian random variable. A sparse precision matrix over all the latent terms determines the co-occurrence network among taxa.

The mechanisms linking chronic inflammation of the gut (IBD) and increased colorectal cancer susceptibility are poorly understood. IBD risk is influenced by genetic factors, including the IBD5 locus (human 5q31), that harbors the IRF1 gene. A cause-to-effect relationship between chronic inflammation and colorectal cancer, and a possible role of IRF1 were studied in Irf1-/- mice in a model of colitis-associated colorectal cancer (CA-CRC) induced by azoxymethane and dextran sulfate. Loss of Irf1 causes hyper-susceptibility to CA-CRC, with early onset and increased number of tumors leading to rapid lethality. Transcript profiling (RNA-seq) and immunostaining of colons shows heightened inflammation and enhanced enterocyte proliferation in Irf1−/− mutants, prior to appearance of tumors. Considerable infiltration of leukocytes is seen in Irf1−/− colons at this early stage, and is composed primarily of proinflammatory Gr1+ Cd11b+ myeloid cells and other granulocytes, as well as CD4+ lymphoid cells. Differential susceptibility to CA-CRC of Irf1−/− vs. B6 controls is fully transferable through hematopoietic cells as observed in bone marrow chimera studies. Transcript signatures seen in Irf1−/− mice in response to AOM/DSS are enriched in clinical specimens from patients with IBD and with colorectal cancer. In addition, IRF1 expression in the colon is significantly decreased in late stage colorectal cancer (stages 3, 4) and is associated with poorer prognosis. This suggests that partial or complete loss of IRF1 expression alters the type, number, and function of immune cells in situ during chronic inflammation, possibly via the creation of a tumor-promoting environment.

DNA methylation allows for the environmental regulation of gene expression and is believed to link environmental stressors to psychiatric disorder phenotypes, such as anorexia nervosa (AN). The oxytocin receptor (OXTR) gene is epigenetically regulated, and studies have shown associations between OXTR and social behaviours in various samples, including women with AN. The present study examined differential levels of methylation at various CG sites of the OXTR gene in 69 women with active AN (AN‐Active), 21 in whom AN was in remission (AN‐Rem) and 35 with no eating disorder (NED). Within each group, we explored the correlation between methylation and measures of social behaviour such as insecure attachment and social avoidance. Hypermethylation of a number of CG sites was seen in AN‐Active participants as compared with AN‐Rem and NED participants. In the AN‐Rem sample, methylation at CG27501759 was significantly positively correlated with insecure attachment (r = .614, p = .003, permutation Q = 0.008) and social avoidance (r = .588, p = .005, permutation Q = 0.0184). Our results highlight differential methylation of the OXTR gene among women with AN, those in remission from AN, and those who never had AN and provide some evidence of associations between OXTR methylation and social behaviour in women remitted from AN.