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Background and aims:Infliximab is an effective treatment for ulcerative colitis with over 60% of patients responding to treatment and up to 30% reaching remission. The mechanism of resistance to anti-tumour necrosis factor α (anti-TNFα) is unknown. This study used colonic mucosal gene expression to provide a predictive response signature for infliximab treatment in ulcerative colitis.Methods:Two cohorts of patients who received their first treatment with infliximab for refractory ulcerative colitis were studied. Response to infliximab was defined as endoscopic and histological healing. Total RNA from pre-treatment colonic mucosal biopsies was analysed with Affymetrix Human Genome U133 Plus 2.0 Arrays. Quantitative RT-PCR was used to confirm microarray data.Results:For predicting response to infliximab treatment, pre-treatment colonic mucosal expression profiles were compared for responders and non-responders. Comparative analysis identified 179 differentially expressed probe sets in cohort A and 361 in cohort B with an overlap of 74 probe sets, representing 53 known genes, between both analyses. Comparative analysis of both cohorts combined, yielded 212 differentially expressed probe sets. The top five differentially expressed genes in a combined analysis of both cohorts were osteoprotegerin, stanniocalcin-1, prostaglandin-endoperoxide synthase 2, interleukin 13 receptor alpha 2 and interleukin 11. All proteins encoded by these genes are involved in the adaptive immune response. These markers separated responders from non-responders with 95% sensitivity and 85% specificity.Conclusion:Gene array studies of ulcerative colitis mucosal biopsies identified predictive panels of genes for (non-)response to infliximab. Further study of the pathways involved should allow a better understanding of the mechanisms of resistance to infliximab therapy in ulcerative colitis.ClinicalTrials.gov number, NCT00639821.

Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems.

Human rhinovirus infections cause colds and trigger exacerbations of lower airway diseases. To define changes in gene expression profiles during in vivo rhinovirus infections. Nasal epithelial scrapings were obtained before and during experimental rhinovirus infection, and gene expression was evaluated by microarray. Naturally acquired rhinovirus infections, cultured human epithelial cells, and short interfering RNA knockdown were used to further evaluate the role of viperin in rhinovirus infections. Symptom scores and viral titers were measured in subjects inoculated with rhinovirus or sham control, and changes in gene expression were assessed 8 and 48 hours after inoculation. Real-time reverse transcription-polymerase chain reaction for viperin and rhinoviruses was used in naturally acquired infections, and viperin mRNA levels and viral titers were measured in cultured cells. Rhinovirus-induced changes in gene expression were not observed 8 hours after viral infection, but 11,887 gene transcripts were significantly altered in scrapings obtained 2 days postinoculation. Major groups of up-regulated genes included chemokines, signaling molecules, interferon-responsive genes, and antivirals. Viperin expression was further examined and also was increased in naturally acquired rhinovirus infections, as well as in cultured human epithelial cells infected with intact, but not replication-deficient, rhinovirus. Knockdown of viperin with short interfering RNA increased rhinovirus replication in infected epithelial cells. Rhinovirus infection significantly alters the expression of many genes associated with the immune response, including chemokines and antivirals. The data obtained provide insights into the host response to rhinovirus infection and identify potential novel targets for further evaluation.

Genome-wide association studies with SNP markers are expected to allow identification of genes that underlie complex disorders. Hundreds of thousands of SNP markers will be required for comprehensive genome-wide association studies. The development of microarray-based methods for SNP genotyping on this scale remains a demanding task, despite many recent advances in technology for the production of high-density microarrays. A key technical obstacle is the PCR amplification step, which is required to reduce the complexity of and gain sufficient sensitivity for genotyping SNPs in large, diploid genomes. The multiplexing level that can be achieved in PCR does not match that of current microarray-based methods, making PCR the limiting step in the assays. Highly multiplexed microarray systems for SNP genotyping have recently been developed by combining well-known reaction principles for DNA amplification and SNP genotyping in clever ways. These new methods offer the potential of genome-wide SNP mapping of genes involved in complex diseases in the foreseeable future, provided that issues related to selection of the optimal SNP markers, sample throughput and the cost of the assays can be addressed.

Background China is the birthplace of the deer family and the country with the most abundant deer resources. However, at present, China’s deer industry faces the problem that pure sika deer and hybrid deer cannot be easily distinguished. Therefore, the development of a SNP identification chip is urgently required. Results In this study, 250 sika deer, 206 red deer, 23 first-generation hybrid deer (F1), 20 s-generation hybrid deer (F2), and 20 third-generation hybrid deer (F3) were resequenced. Using the chromosome-level sika deer genome as the reference sequence, mutation detection was performed on all individuals, and a total of 130,306,923 SNP loci were generated. After quality control filtering was performed, the remaining 31,140,900 loci were confirmed. From molecular-level and morphological analyses, the sika deer reference population and the red deer reference population were established. The Fst values of all SNPs in the two reference populations were calculated. According to customized algorithms and strict screening principles, 1000 red deer-specific SNP sites were finally selected for chip design, and 63 hybrid individuals were determined to contain red deer-specific SNP loci. The results showed that the gene content of red deer gradually decreased in subsequent hybrid generations, and this decrease roughly conformed to the law of statistical genetics. Reaction probes were designed according to the screening sites. All candidate sites met the requirements of the Illumina chip scoring system. The average score was 0.99, and the MAF was in the range of 0.3277 to 0.3621. Furthermore, 266 deer (125 sika deer, 39 red deer, 56 F1, 29 F2,17 F3) were randomly selected for 1 K SNP chip verification. The results showed that among the 1000 SNP sites, 995 probes were synthesized, 4 of which could not be typed, while 973 loci were polymorphic. PCA, random forest and ADMIXTURE results showed that the 1 K sika deer SNP chip was able to clearly distinguish sika deer, red deer, and hybrid deer and that this 1 K SNP chip technology may provide technical support for the protection and utilization of pure sika deer species resources. Conclusion We successfully developed a low-density identification chip that can quickly and accurately distinguish sika deer from their hybrid offspring, thereby providing technical support for the protection and utilization of pure sika deer germplasm resources.

Background Prenatal inflammation has been proposed as an important mediating factor in several adverse pregnancy outcomes. C-reactive protein (CRP) is an inflammatory cytokine easily measured in blood. It has clinical value due to its reliability as a biomarker for systemic inflammation and can indicate cellular injury and disease severity. Elevated levels of CRP in adulthood are associated with alterations in DNA methylation. However, no studies have prospectively investigated the relationship between maternal CRP levels and newborn DNA methylation measured by microarray in cord blood with reasonable epigenome-wide coverage. Importantly, the timing of inflammation exposure during pregnancy may also result in different effects. Thus, our objective was to evaluate this prospective association of CRP levels measured during multiple periods of pregnancy and in cord blood at delivery which was available in one cohort (i.e., Effects of Aspirin in Gestation and Reproduction trial), and also to conduct a meta-analysis with available data at one point in pregnancy from three other cohorts from the Pregnancy And Childhood Epigenetics consortium (PACE). Secondarily, the impact of maternal randomization to low dose aspirin prior to pregnancy on methylation was assessed. Results Maternal CRP levels were not associated with newborn DNA methylation regardless of gestational age of measurement (i.e., CRP at approximately 8, 20, and 36 weeks among 358 newborns in EAGeR). There also was no association in the meta-analyses (all p > 0.5) with a larger sample size ( n = 1603) from all participating PACE cohorts with available CRP data from first trimester (< 18 weeks gestation). Randomization to aspirin was not associated with DNA methylation. On the other hand, newborn CRP levels were significantly associated with DNA methylation in the EAGeR trial, with 33 CpGs identified (FDR corrected p < 0.05) when both CRP and methylation were measured at the same time point in cord blood. The top 7 CpGs most strongly associated with CRP resided in inflammation and vascular-related genes. Conclusions Maternal CRP levels measured during each trimester were not associated with cord blood DNA methylation. Rather, DNA methylation was associated with CRP levels measured in cord blood, particularly in gene regions predominately associated with angiogenic and inflammatory pathways. Trial registration Clinicaltrials.gov, NCT00467363 , Registered April 30, 2007, http://www.clinicaltrials.gov/ct2/show/NCT00467363

MicroRNAs are short, 18- to 25-nt sequences of noncoding, single-stranded RNA that function as regulatory molecules and participate in a series of vital processes including early development, cell proliferation, cell differentiation, apoptosis, substance metabolism and the pathogenesis of human diseases. This study compared the microRNA profiles of patients with systemic scleroderma (SSc) and healthy control individuals to investigate the pathogenesis of SSc. Skin tissue was isolated from three patients with SSc and three healthy controls. miRNA microarray chip analysis identified 24 miRNAs that were differentially expressed in patients with SSc and 6 microRNAs that may be correlated with the pathogenesis of SSc. The results of the microarray analysis were confirmed using real-time PCR. This work suggests that miRNAs may be potential diagnosis biomarkers and are likely to be involved in the pathogenesis of SSc.

Developmental disorders (DD), including autism spectrum disorder (ASD) and intellectual disability (ID), are a common group of clinical manifestations caused by a variety of genetic abnormalities. Genetic testing, including chromosomal microarray (CMA), plays an important role in diagnosing these conditions, but CMA can be limited by incomplete coverage of genetic abnormalities and lack of guidance for conditions rarely seen by treating physicians. We conducted a longitudinal, randomized controlled trial investigating the impact of a higher resolution 2.8 million (MM) probe-CMA test on the quality of care delivered by practicing general pediatricians and specialists. To overcome the twin problems of finding an adequate sample size of multiple rare conditions and under/incorrect diagnoses, we used standardized simulated patients known as CPVs. Physicians, randomized into control and intervention groups, cared for the CPV pediatric patients with DD/ASD/ID. Care responses were scored against evidence-based criteria. In round one, participants could order diagnostic tests including existing CMA tests. In round two, intervention physicians could order the 2.8MM probe-CMA test. Outcome measures included overall quality of care and quality of the diagnosis and treatment plan. Physicians ordering CMA testing had 5.43% (p<0.001) higher overall quality scores than those who did not. Intervention physicians ordering the 2.8MM probe-CMA test had 7.20% (p<0.001) higher overall quality scores. Use of the 2.8MM probe-CMA test led to a 10.9% (p<0.001) improvement in the diagnosis and treatment score. Introduction of the 2.8MM probe-CMA test led to significant improvements in condition-specific interventions including an 8.3% (p = 0.04) improvement in evaluation and therapy for gross motor delays caused by Hunter syndrome, a 27.5% (p = 0.03) increase in early cognitive intervention for FOXG1-related disorder, and an 18.2% (p<0.001) improvement in referrals to child neurology for Dravet syndrome. Physician use of the 2.8MM probe-CMA test significantly improves overall quality as well as diagnosis and treatment quality for simulated cases of pediatric DD/ASD/ID patients, and delivers additional clinical utility over existing CMA tests.

Different technologies, such as quantitative real-time PCR or microarrays, have been developed to measure microRNA (miRNA) expression levels. Quantification of miRNA transcripts implicates data normalization using endogenous and exogenous reference genes for data correction. However, there is no consensus about an optimal normalization strategy. The choice of a reference gene remains problematic and can have a serious impact on the actual available transcript levels and, consequently, on the biological interpretation of data. In this review article we discuss the reliability of the use of small RNAs, commonly reported in the literature as miRNA expression normalizers, and compare different strategies used for data normalization. A workflow strategy is proposed for normalization of miRNA expression data in an attempt to provide a basis for the establishment of a global standard procedure that will allow comparison across studies.

Batch effects can lead to incorrect biological conclusions but are not widely considered. The authors show that batch effects are relevant to a range of high-throughput 'omics' data sets and are crucial to address. They also explain how batch effects can be mitigated. High-throughput technologies are widely used, for example to assay genetic variants, gene and protein expression, and epigenetic modifications. One often overlooked complication with such studies is batch effects, which occur because measurements are affected by laboratory conditions, reagent lots and personnel differences. This becomes a major problem when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. Using both published studies and our own analyses, we argue that batch effects (as well as other technical and biological artefacts) are widespread and critical to address. We review experimental and computational approaches for doing so.