Search

The diagnosis of primary sclerosing cholangitis (PSC) is difficult due to the lack of sensitive and specific biomarkers, as is the early diagnosis of cholangiocarcinoma (CC), a complication of PSC. The aim of this study was to identify specific serum miRNAs as diagnostic biomarkers for PSC and CC. The levels of 667 miRNAs were evaluated in 90 human serum samples (30 PSC, 30 CC and 30 control subjects) to identify disease-associated candidate miRNAs (discovery phase). The deregulated miRNAs were validated in an independent cohort of 140 samples [40 PSC, 40 CC, 20 primary biliary cirrhosis (PBC) and 40 controls]. Receiver operating characteristic (ROC) curves were established and only miRNAs with an area under the curve (AUC) > 0·70 were considered useful as biomarkers. In the discovery phase we identified the following: 21 miRNAs expressed differentially in PSC, 33 in CC and 26 in both in comparison to control subjects as well as 24 miRNAs expressed differentially between PSC and CC. After the validation phase, miR-200c was found to be expressed differentially in PSC versus controls, whereas miR-483-5p and miR-194 showed deregulated expression in CC compared with controls. We also demonstrate a difference in the expression of miR-222 and miR-483-5p in CC versus PSC. Combination of these specific miRNAs further improved the specificity and accuracy of diagnosis. This study provides a basis for the use of miRNAs as biomarkers for the diagnosis of PSC and CC. [ABSTRACT FROM AUTHOR]

The environmental contaminant dibutyl phthalate (DBP) is reported to be hepatotoxic, but the underlying molecular pathways and pathological processes remain unclear. Here we used RNA-sequencing to characterize persistent hepatic transcriptional effects one week after the conclusion of five weeks oral exposure to 10 mg/kg/day or 100 mg/kg/day DBP in adult male mice. The exploratory transcriptome analysis demonstrated five differentially expressed genes (DEGs) in the 10 mg/kg/day group and 13 in the 100 mg/kg/day group. Gene Set Enrichment Analysis (GSEA), which identifies affected biological pathways rather than focusing solely on individual genes, revealed nine significantly enriched Reactome pathways shared by both DBP treatment groups. Additionally, we found 54 upregulated and one downregulated Reactome pathways in the 10 mg/kg/day DBP group, and 29 upregulated and 13 downregulated pathways in the 100 mg/kg/day DBP group. DBP exposure disrupted several key biological processes, including protein translation, protein folding, apoptosis, Hedgehog signaling, degradation of extracellular matrix and alterations in the energy/lipid metabolism. Subsequent liver tissue analysis confirmed that DBP exposure induced tissue disorganization, oxidative stress, lipid accumulation, increased TNF-α, ATP and glucokinase levels, and affected key metabolic proteins, predominantly in a dose-response manner. Overall, the results show that DBP can cause hepatic stress and damage and suggest a potential role for DBP in the development of non-alcoholic fatty liver disease, the most prevalent liver disease worldwide., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

We explored opportunities for personalized and predictive health care by collecting serial clinical measurements, health surveys, genomics, proteomics, autoantibodies, metabolomics, and gut microbiome data from 96 individuals who participated in a data-driven health coaching program over a 16-month period with continuous digital monitoring of activity and sleep. We generated a resource of >20,000 biological samples from this study and a compendium of >53 million primary data points for 558,032 distinct features. Multiomics factor analysis revealed distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet, and hormonal effects. For example, ethinyl estradiol, a common oral contraceptive, produced characteristic molecular and physiological effects, including increased levels of inflammation and impact on thyroid, cortisol levels, and pulse, that were distinct from other sources of variability observed in our study. In total, this work illustrates the value of combining deep molecular and digital monitoring of human health. A record of this paper's transparent peer review process is included in the supplemental information., Competing Interests: Declaration of interests O.K. received research funding from Vinnova for collaboration between Astra Zeneca, Takeda, Pelago, and Labcyte. O.K. is also a board member and a co-founder of Medisapiens and Sartar Therapeutics and has received a royalty on patents licensed by Vysis-Abbot. R.S. is currently employed at Crown CRO., (Copyright © 2021. Published by Elsevier Inc.)

Multi-omics approaches use a diversity of high-throughput technologies to profile the different molecular layers of living cells. Ideally, the integration of this information should result in comprehensive systems models of cellular physiology and regulation. However, most multi-omics projects still include a limited number of molecular assays and there have been very few multi-omic studies that evaluate dynamic processes such as cellular growth, development and adaptation. Hence, we lack formal analysis methods and comprehensive multi-omics datasets that can be leveraged to develop true multi-layered models for dynamic cellular systems. Here we present the STATegra multi-omics dataset that combines measurements from up to 10 different omics technologies applied to the same biological system, namely the well-studied mouse pre-B-cell differentiation. STATegra includes high-throughput measurements of chromatin structure, gene expression, proteomics and metabolomics, and it is complemented with single-cell data. To our knowledge, the STATegra collection is the most diverse multi-omics dataset describing a dynamic biological system.

We introduce and develop a method that demonstrates that the algorithmic information content of a system can be used as a steering handle in the dynamical phase space, thus affording an avenue for controlling and reprogramming systems. The method consists of applying a series of controlled interventions to a networked system while estimating how the algorithmic information content is affected. We demonstrate the method by reconstructing the phase space and their generative rules of some discrete dynamical systems (cellular automata) serving as controlled case studies. Next, the model-based interventional or causal calculus is evaluated and validated using (1) a huge large set of small graphs, (2) a number of larger networks with different topologies, and finally (3) biological networks derived from a widely studied and validated genetic network (E. coli) as well as on a significant number of differentiating (Th17) and differentiated human cells from a curated biological network data., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Aim: Accumulating evidence links epigenetic age to diseases and age-related conditions, but little is known about its association with multiple sclerosis (MS). Materials & methods: We estimated epigenetic age acceleration measures using DNA methylation from blood or sorted cells of MS patients and controls. Results: In blood, sex (p = 4.39E-05) and MS (p = 2.99E-03) explained the variation in age acceleration, and isolated blood cell types showed different epigenetic age. Intrinsic epigenetic age acceleration and extrinsic epigenetic age acceleration were only associated with sex (p = 2.52E-03 and p = 1.58E-04, respectively), while PhenoAge Acceleration displayed positive association with MS (p = 3.40E-02). Conclusion: Different age acceleration measures are distinctly influenced by phenotypic factors, and they might measure separate pathophysiological aspects of MS. Data deposition: DNA methylation data can be accessed at Gene Expression Omnibus database under accession number GSE35069, GSE43976, GSE106648, GSE130029, GSE130030.

The human leukocyte antigen (HLA) haplotype DRB1*15:01 is the major risk factor for multiple sclerosis (MS). Here, we find that DRB1*15:01 is hypomethylated and predominantly expressed in monocytes among carriers of DRB1*15:01. A differentially methylated region (DMR) encompassing HLA-DRB1 exon 2 is particularly affected and displays methylation-sensitive regulatory properties in vitro. Causal inference and Mendelian randomization provide evidence that HLA variants mediate risk for MS via changes in the HLA-DRB1 DMR that modify HLA-DRB1 expression. Meta-analysis of 14,259 cases and 171,347 controls confirms that these variants confer risk from DRB1*15:01 and also identifies a protective variant (rs9267649, p < 3.32 × 10 -8 , odds ratio = 0.86) after conditioning for all MS-associated variants in the region. rs9267649 is associated with increased DNA methylation at the HLA-DRB1 DMR and reduced expression of HLA-DRB1, suggesting a modulation of the DRB1*15:01 effect. Our integrative approach provides insights into the molecular mechanisms of MS susceptibility and suggests putative therapeutic strategies targeting a methylation-mediated regulation of the major risk gene.

Background: Regulatory T cells (Tregs) expressing the transcription factor FOXP3 are crucial mediators of self-tolerance, preventing autoimmune diseases but possibly hampering tumor rejection. Clinical manipulation of Tregs is of great interest, and first-in-man trials of Treg transfer have achieved promising outcomes. Yet, the mechanisms governing induced Treg (iTreg) differentiation and the regulation of FOXP3 are incompletely understood., Results: To gain a comprehensive and unbiased molecular understanding of FOXP3 induction, we performed time-series RNA sequencing (RNA-Seq) and proteomics profiling on the same samples during human iTreg differentiation. To enable the broad analysis of universal FOXP3-inducing pathways, we used five differentiation protocols in parallel. Integrative analysis of the transcriptome and proteome confirmed involvement of specific molecular processes, as well as overlap of a novel iTreg subnetwork with known Treg regulators and autoimmunity-associated genes. Importantly, we propose 37 novel molecules putatively involved in iTreg differentiation. Their relevance was validated by a targeted shRNA screen confirming a functional role in FOXP3 induction, discriminant analyses classifying iTregs accordingly, and comparable expression in an independent novel iTreg RNA-Seq dataset., Conclusion: The data generated by this novel approach facilitates understanding of the molecular mechanisms underlying iTreg generation as well as of the concomitant changes in the transcriptome and proteome. Our results provide a reference map exploitable for future discovery of markers and drug candidates governing control of Tregs, which has important implications for the treatment of cancer, autoimmune, and inflammatory diseases.

Background: Chronic obstructive pulmonary disease (COPD) patients often show skeletal muscle dysfunction that has a prominent negative impact on prognosis. The study aims to further explore underlying mechanisms of skeletal muscle dysfunction as a characteristic systemic effect of COPD, potentially modifiable with preventive interventions (i.e. muscle training). The research analyzes network module associated pathways and evaluates the findings using independent measurements., Methods: We characterized the transcriptionally active network modules of interacting proteins in the vastus lateralis of COPD patients (n = 15, FEV 1 46 ± 12% pred, age 68 ± 7 years) and healthy sedentary controls (n = 12, age 65 ± 9  years), at rest and after an 8-week endurance training program. Network modules were functionally evaluated using experimental data derived from the same study groups., Results: At baseline, we identified four COPD specific network modules indicating abnormalities in creatinine metabolism, calcium homeostasis, oxidative stress and inflammatory responses, showing statistically significant associations with exercise capacity (VO 2 peak, Watts peak, BODE index and blood lactate levels) (P < 0.05 each), but not with lung function (FEV 1 ). Training-induced network modules displayed marked differences between COPD and controls. Healthy subjects specific training adaptations were significantly associated with cell bioenergetics (P < 0.05) which, in turn, showed strong relationships with training-induced plasma metabolomic changes; whereas, effects of training in COPD were constrained to muscle remodeling., Conclusion: In summary, altered muscle bioenergetics appears as the most striking finding, potentially driving other abnormal skeletal muscle responses. Trial registration The study was based on a retrospectively registered trial (May 2017), ClinicalTrials.gov identifier: NCT03169270.

Cigarette smoking is an established environmental risk factor for Multiple Sclerosis (MS), a chronic inflammatory and neurodegenerative disease, although a mechanistic basis remains largely unknown. We aimed at investigating how smoking affects blood DNA methylation in MS patients, by assaying genome-wide DNA methylation and comparing smokers, former smokers and never smokers in two Swedish cohorts, differing for known MS risk factors. Smoking affects DNA methylation genome-wide significantly, an exposure-response relationship exists and the time since smoking cessation affects methylation levels. The results also show that the changes were larger in the cohort bearing the major genetic risk factors for MS (female sex and HLA risk haplotypes). Furthermore, CpG sites mapping to genes with known genetic or functional role in the disease are differentially methylated by smoking. Modeling of the methylation levels for a CpG site in the AHRR gene indicates that MS modifies the effect of smoking on methylation changes, by significantly interacting with the effect of smoking load. Alongside, we report that the gene expression of AHRR increased in MS patients after smoking. Our results suggest that epigenetic modifications may reveal the link between a modifiable risk factor and the pathogenetic mechanisms.

Regulatory T cells (Tregs) control key events of immune tolerance, primarily by suppression of effector T cells. We previously revealed that Tregs rapidly suppress T cell receptor (TCR)-induced calcium store depletion in conventional CD4 + CD25 - T cells (Tcons) independently of IP 3 levels, consequently inhibiting NFAT signaling and effector cytokine expression. Here, we study Treg suppression mechanisms through unbiased phosphoproteomics of primary human Tcons upon TCR stimulation and Treg-mediated suppression, respectively. Tregs induced a state of overall decreased phosphorylation as opposed to TCR stimulation. We discovered novel phosphosites (T595&#95;S597) in the DEF6 (SLAT) protein that were phosphorylated upon TCR stimulation and conversely dephosphorylated upon coculture with Tregs. Mutation of these DEF6 phosphosites abrogated interaction of DEF6 with the IP 3 receptor and affected NFAT activation and cytokine transcription in primary Tcons. This novel mechanism and phosphoproteomics data resource may aid in modifying sensitivity of Tcons to Treg-mediated suppression in autoimmune disease or cancer.

Multiple sclerosis (MS) is a chronic inflammatory and demyelinating disease of the central nervous system. MS likely results from a complex interplay between predisposing causal gene variants (the strongest influence coming from HLA class II locus) and environmental risk factors such as smoking, infectious mononucleosis, and lack of sun exposure/vitamin D. However, little is known about the mechanisms underlying MS development and progression. Moreover, the clinical heterogeneity and variable response to treatment represent additional challenges to a comprehensive understanding and efficient treatment of disease. Epigenetic processes, such as DNA methylation and histone posttranslational modifications, integrate influences from the genes and the environment to regulate gene expression accordingly. Studying epigenetic modifications, which are stable and reversible, may provide an alternative approach to better understand and manage disease. We here aim to review findings from epigenetic studies in MS and further discuss the challenges and clinical opportunities arising from epigenetic research, many of which apply to other diseases with similar complex etiology. A growing body of evidence supports a role of epigenetic processes in the mechanisms underlying immune pathogenesis and nervous system dysfunction in MS. However, disparities between studies shed light on the need to consider possible confounders and methodological limitations for a better interpretation of the data. Nevertheless, translational use of epigenetics might offer new opportunities in epigenetic-based diagnostics and therapeutic tools for a personalized care of MS patients., (Copyright © 2017 the American Physiological Society.)

Arsenic, a carcinogen with immunotoxic effects, is a common contaminant of drinking water and certain food worldwide. We hypothesized that chronic arsenic exposure alters gene expression, potentially by altering DNA methylation of genes encoding central components of the immune system. We therefore analyzed the transcriptomes (by RNA sequencing) and methylomes (by target-enrichment next-generation sequencing) of primary CD4-positive T cells from matched groups of four women each in the Argentinean Andes, with fivefold differences in urinary arsenic concentrations (median concentrations of urinary arsenic in the lower- and high-arsenic groups: 65 and 276 μg/l, respectively). Arsenic exposure was associated with genome-wide alterations of gene expression; principal component analysis indicated that the exposure explained 53% of the variance in gene expression among the top variable genes and 19% of 28,351 genes were differentially expressed (false discovery rate <0.05) between the exposure groups. Key genes regulating the immune system, such as tumor necrosis factor alpha and interferon gamma, as well as genes related to the NF-kappa-beta complex, were significantly downregulated in the high-arsenic group. Arsenic exposure was associated with genome-wide DNA methylation; the high-arsenic group had 3% points higher genome-wide full methylation (>80% methylation) than the lower-arsenic group. Differentially methylated regions that were hyper-methylated in the high-arsenic group showed enrichment for immune-related gene ontologies that constitute the basic functions of CD4-positive T cells, such as isotype switching and lymphocyte activation and differentiation. In conclusion, chronic arsenic exposure from drinking water was related to changes in the transcriptome and methylome of CD4-positive T cells, both genome wide and in specific genes, supporting the hypothesis that arsenic causes immunotoxicity by interfering with gene expression and regulation.

Azacitidine (Aza) is first-line treatment for patients with high-risk myelodysplastic syndromes (MDS), although its precise mechanism of action is unknown. We performed the first study to globally evaluate the epigenetic effects of Aza on MDS bone marrow progenitor cells assessing gene expression (RNA seq), DNA methylation (Illumina 450k) and the histone modifications H3K18ac and H3K9me3 (ChIP seq). Aza induced a general increase in gene expression with 924 significantly upregulated genes but this increase showed no correlation with changes in DNA methylation or H3K18ac, and only a weak association with changes in H3K9me3. Interestingly, we observed activation of transcripts containing 15 endogenous retroviruses (ERVs) confirming previous cell line studies. DNA methylation decreased moderately in 99% of all genes, with a median β-value reduction of 0.018; the most pronounced effects seen in heterochromatin. Aza-induced hypomethylation correlated significantly with change in H3K9me3. The pattern of H3K18ac and H3K9me3 displayed large differences between patients and healthy controls without any consistent pattern induced by Aza. We conclude that the marked induction of gene expression only partly could be explained by epigenetic changes, and propose that activation of ERVs may contribute to the clinical effects of Aza in MDS.

Objective: Members of the transient receptor potential (TRP) channels are involved in mediating the electrical excitability and stimulus-secretion coupling in the pancreatic β-cells. The expression and the relative abundance of different TRP channels in the human β-cells are unknown. The objective of this study was to examine the expression of the TRP channels and their relative abundance in the human β-cell., Methods: RNA sequencing data obtained from human islets, fluorescence-activated cell sorting-purified human β-cell and human pancreatic acinar cells were analyzed. Gene counts and fragments per kilobase per million mapped reads were obtained., Results: Among the TRPC family only the TRPC1 was expressed in the human β-cell. TRPV1 channels were not expressed in the human β-cells. Among the TRPM family, TRPM4, TRPM7, TRPM2, and TRPM3 were expressed in the human β-cell. Of the remaining TRP channels, TRPP2, TRPML1, and TRPML3 were expressed in these cells., Conclusions: By analyzing the RNA sequencing data, we have detected for the first time the TRP channels that are expressed in the purified human β-cells, in comparison to the other relevant pancreatic cell types. Our study provides an opportunity to focus on these TRP channels for a better understanding of the electrophysiology and stimulus-secretion coupling in these cells.

The high-throughput analysis of microRNAs (miRNAs) circulating within the blood of healthy and diseased individuals is an active area of biomarker research. Whereas quantitative real-time reverse transcription polymerase chain reaction (qPCR)-based methods are widely used, it is yet unresolved how the data should be normalized. Here, we show that a combination of different algorithms results in the identification of candidate reference miRNAs that can be exploited as normalizers, in both discovery and validation phases. Using the methodology considered here, we identify normalizers that are able to reduce nonbiological variation in the data and we present several case studies, to illustrate the relevance in the context of physiological or pathological scenarios. In conclusion, the discovery of stable reference miRNAs from high-throughput studies allows appropriate normalization of focused qPCR assays., (© The Author 2015. Published by Oxford University Press.)

Regular endurance exercise training induces beneficial functional and health effects in human skeletal muscle. The putative contribution to the training response of the epigenome as a mediator between genes and environment has not been clarified. Here we investigated the contribution of DNA methylation and associated transcriptomic changes in a well-controlled human intervention study. Training effects were mirrored by significant alterations in DNA methylation and gene expression in regions with a homogeneous muscle energetics and remodeling ontology. Moreover, a signature of DNA methylation and gene expression separated the samples based on training and gender. Differential DNA methylation was predominantly observed in enhancers, gene bodies and intergenic regions and less in CpG islands or promoters. We identified transcriptional regulator binding motifs of MRF, MEF2 and ETS proteins in the proximity of the changing sites. A transcriptional network analysis revealed modules harboring distinct ontologies and, interestingly, the overall direction of the changes of methylation within each module was inversely correlated to expression changes. In conclusion, we show that highly consistent and associated modifications in methylation and expression, concordant with observed health-enhancing phenotypic adaptations, are induced by a physiological stimulus.

Background and Hypothesis: Chronic Obstructive Pulmonary Disease (COPD) patients are characterized by heterogeneous clinical manifestations and patterns of disease progression. Two major factors that can be used to identify COPD subtypes are muscle dysfunction/wasting and co-morbidity patterns. We hypothesized that COPD heterogeneity is in part the result of complex interactions between several genes and pathways. We explored the possibility of using a Systems Medicine approach to identify such pathways, as well as to generate predictive computational models that may be used in clinic practice., Objective and Method: Our overarching goal is to generate clinically applicable predictive models that characterize COPD heterogeneity through a Systems Medicine approach. To this end we have developed a general framework, consisting of three steps/objectives: (1) feature identification, (2) model generation and statistical validation, and (3) application and validation of the predictive models in the clinical scenario. We used muscle dysfunction and co-morbidity as test cases for this framework., Results: In the study of muscle wasting we identified relevant features (genes) by a network analysis and generated predictive models that integrate mechanistic and probabilistic models. This allowed us to characterize muscle wasting as a general de-regulation of pathway interactions. In the co-morbidity analysis we identified relevant features (genes/pathways) by the integration of gene-disease and disease-disease associations. We further present a detailed characterization of co-morbidities in COPD patients that was implemented into a predictive model. In both use cases we were able to achieve predictive modeling but we also identified several key challenges, the most pressing being the validation and implementation into actual clinical practice., Conclusions: The results confirm the potential of the Systems Medicine approach to study complex diseases and generate clinically relevant predictive models. Our study also highlights important obstacles and bottlenecks for such approaches (e.g. data availability and normalization of frameworks among others) and suggests specific proposals to overcome them.

Background and Aims: The PNPLA3 I148M sequence variant favors hepatic lipid accumulation and confers susceptibility to hepatic fibrosis and hepatocellular carcinoma. The aim of this study was to estimate the effect size of homozygosity for the PNPLA3 I148M variant (148M/M) on the fibrosis progression rate (FPR) and the interaction with age at infection in chronic hepatitis C (CHC)., Methods: FPR was estimated in a prospective cohort of 247 CHC patients without alcohol intake and diabetes, with careful estimation of age at infection and determination of fibrosis stage by Ishak score., Results: Older age at infection was the strongest determinant of FPR (p<0.0001). PNPLA3 148M/M was associated with faster FPR in individuals infected at older age (above the median, 21 years; -0.64±0.2, n = 8 vs. -0.95±0.3, n = 166 log10 FPR respectively; p = 0.001; confirmed for lower age thresholds, p<0.05), but not in those infected at younger age (p = ns). The negative impact of PNPLA3 148M/M on fibrosis progression was more marked in subjects at risk of altered hepatic lipid metabolism (those with grade 2-3 steatosis, genotype 3, and overweight; p<0.05). At multivariate analysis, PNPLA3 148M/M was associated with FPR (incremental effect 0.08±0.03 log10 fibrosis unit per year; p = 0.022), independently of several confounders, and there was a significant interaction between 148M/M and older age at infection (p = 0.025). The association between 148M/M and FPR remained significant even after adjustment for steatosis severity (p = 0.032)., Conclusions: We observed an interaction between homozygosity for the PNPLA3 I148M variant and age at infection in determining fibrosis progression in CHC patients.

Activated lymphocytes release nano-sized vesicles (exosomes) containing microRNAs that can be monitored in the bloodstream. We asked whether elicitation of immune responses is followed by release of lymphocyte-specific microRNAs. We found that, upon activation in vitro, human and mouse lymphocytes down-modulate intracellular miR-150 and accumulate it in exosomes. In vivo, miR-150 levels increased significantly in serum of humans immunized with flu vaccines and in mice immunized with ovalbumin, and this increase correlated with elevation of antibody titers. Immunization of immune-deficient mice, lacking MHCII, resulted neither in antibody production nor in elevation of circulating miR-150. This study provides proof of concept that serum microRNAs can be detected, with minimally invasive procedure, as biomarkers of vaccination and more in general of adaptive immune responses. Furthermore, the prompt reduction of intracellular level of miR-150, a key regulator of mRNAs critical for lymphocyte differentiation and functions, linked to its release in the external milieu suggests that the selective extracellular disposal of microRNAs can be a rapid way to regulate gene expression during lymphocyte activation.

The proper identification of differentially methylated CpGs is central in most epigenetic studies. The Illumina HumanMethylation450 BeadChip is widely used to quantify DNA methylation; nevertheless, the design of an appropriate analysis pipeline faces severe challenges due to the convolution of biological and technical variability and the presence of a signal bias between Infinium I and II probe design types. Despite recent attempts to investigate how to analyze DNA methylation data with such an array design, it has not been possible to perform a comprehensive comparison between different bioinformatics pipelines due to the lack of appropriate data sets having both large sample size and sufficient number of technical replicates. Here we perform such a comparative analysis, targeting the problems of reducing the technical variability, eliminating the probe design bias and reducing the batch effect by exploiting two unpublished data sets, which included technical replicates and were profiled for DNA methylation either on peripheral blood, monocytes or muscle biopsies. We evaluated the performance of different analysis pipelines and demonstrated that: (1) it is critical to correct for the probe design type, since the amplitude of the measured methylation change depends on the underlying chemistry; (2) the effect of different normalization schemes is mixed, and the most effective method in our hands were quantile normalization and Beta Mixture Quantile dilation (BMIQ); (3) it is beneficial to correct for batch effects. In conclusion, our comparative analysis using a comprehensive data set suggests an efficient pipeline for proper identification of differentially methylated CpGs using the Illumina 450K arrays.

Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs., Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform., Availability: BMIQ is freely available from http://code.google.com/p/bmiq/., Contact: a.teschendorff@ucl.ac.uk, Supplementary Information: Supplementary data are available at Bioinformatics online.

Autoimmune hepatitis (AIH) is an unresolving inflammation of the liver of unknown cause. Diagnosis requires the exclusion of other conditions and the presence of characteristic features such as specific autoantibodies. Presently, these autoantibodies have relatively low sensitivity and specificity and are identified via immunostaining of cells or tissues; therefore, there is a diagnostic need for better and easy-to-assess markers. To identify new AIH-specific autoantigens, we developed a protein microarray comprising 1626 human recombinant proteins, selected in silico for being secreted or membrane associated. We screened sera from AIH patients on this microarray and compared the reactivity with that of sera from healthy donors and patients with chronic viral hepatitis C. We identified six human proteins that are specifically recognized by AIH sera. Serum reactivity to a combination of four of these autoantigens allows identification of AIH patients with high sensitivity (82%) and specificity (92%). Of the six autoantigens, the interleukin-4 (IL4) receptor fibronectin type III domain of the IL4 receptor (CD124), which is expressed on the surface of both lymphocytes and hepatocytes, showed the highest individual sensitivity and specificity for AIH. Remarkably, patients' sera inhibited STAT6 phosphorylation induced by IL4 binding to CD124, demonstrating that these autoantibodies are functional and suggesting that IL4 neutralization has a pathogenetic role in AIH.

Unlabelled: Polymorphisms in the interleukin-28B (IL28B) region are associated with spontaneous and treatment-induced viral clearance in hepatitis C virus (HCV) infection. Nevertheless, it is unknown whether genetic variation at the IL28B locus influences the natural history of chronic HCV infection. Thus, we asked whether an association between IL28B polymorphisms and liver fibrosis progression existed. We studied 247 consecutive patients with chronic HCV, an accurate estimate of the date of infection, and a liver biopsy performed before any treatment. No patient had a history of alcohol abuse or coinfection with other viruses. We assessed the role of rs8099917 and rs12979860 polymorphisms and the effect of host and environmental factors on fibrosis progression. Blood transfusion (75%) was the main modality of infection. Median age at infection was 21 years, and median interval between infection and liver biopsy was 25 years. One hundred twenty-nine patients (52%) were infected by HCV-1, 74 (30%) by HCV-2, 34 (14%) by HCV-3, and 10 (4%) by HCV-4. Bridging fibrosis/cirrhosis (Ishak ≥ 4) was detected in 24% of patients. Age at infection had a marked effect on fibrosis progression by both a linear model and Cox proportional-hazard regression (P < 2E-16). A 12.1% increase in the hazard of advanced fibrosis was estimated for each additional year at infection, suggesting that this was the major explanatory variable in this cohort. Male gender (P < 0.05), HCV genotype 3 (P < 0.001) and steatosis (P < 0.05) were also associated with faster fibrosis progression. Conversely, the two IL28B polymorphisms had no impact on fibrosis progression., Conclusion: In HCV patients with a known date of infection, IL28B genotype was not associated with fibrosis progression rate or with the risk of developing advanced liver fibrosis., (Copyright © 2011 American Association for the Study of Liver Diseases.)

MicroRNAs are small noncoding RNAs that regulate gene expression post-transcriptionally. Here we applied microRNA profiling to 17 human lymphocyte subsets to identify microRNA signatures that were distinct among various subsets and different from those of mouse lymphocytes. One of the signature microRNAs of naive CD4+ T cells, miR-125b, regulated the expression of genes encoding molecules involved in T cell differentiation, including IFNG, IL2RB, IL10RA and PRDM1. The expression of synthetic miR-125b and lentiviral vectors encoding the precursor to miR-125b in naive lymphocytes inhibited differentiation to effector cells. Our data provide an 'atlas' of microRNA expression in human lymphocytes, define subset-specific signatures and their target genes and indicate that the naive state of T cells is enforced by microRNA.