Daniele Biasci

Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn's disease

For most immune-mediated diseases, the main determinant of patient well-being is not the diagnosis itself but instead the course that the disease takes over time (prognosis). Prognosis may vary substantially between patients for reasons that are poorly understood. Familial studies support a genetic contribution to prognosis, but little evidence has been found for a proposed association between prognosis and the burden of susceptibility variants. To better characterize how genetic variation influences disease prognosis, we performed a within-cases genome-wide association study in two cohorts of patients with Crohns disease. We identified four genome-wide significant loci, none of which showed any association with disease susceptibility. Conversely, the aggregated effect of all 170 disease susceptibility loci was not associated with disease prognosis. Together, these data suggest that the genetic contribution to prognosis in Crohns disease is largely independent of the contribution to disease susceptibility and point to a biology of prognosis that could provide new therapeutic opportunities.

Molecular and functional definition of the developing human striatum

The complexity of the human brain derives from the intricate interplay of molecular instructions during development. Here we systematically investigated gene expression changes in the prenatal human striatum and cerebral cortex during development from post-conception weeks 2 to 20. We identified tissue-specific gene coexpression networks, differentially expressed genes and a minimal set of bimodal genes, including those encoding transcription factors, that distinguished striatal from neocortical identities. Unexpected differences from mouse striatal development were discovered. We monitored 36 determinants at the protein level, revealing regional domains of expression and their refinement, during striatal development. We electrophysiologically profiled human striatal neurons differentiated in vitro and determined their refined molecular and functional properties. These results provide a resource and opportunity to gain global understanding of how transcriptional and functional processes converge to specify human striatal and neocortical neurons during development.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation

BackgroundAlthough numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study.ResultsUsing a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this “gold-standard” comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues.ConclusionsMicroarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Characterization of the Rx1‐dependent transcriptome during early retinal development

Background: The transcription factor Rx1, also known as Rax, controls key properties of retinal precursors including migration behavior, proliferation, and maintenance of multipotency. However, Rx1 effector genes are largely unknown. Results: To identify genes controlled by Rx1 in early retinal precursors, we compared the transcriptome of Xenopus embryos overexpressing Rx1 to that of embryos in which Rx1 was knocked‐down. In particular, we selected 52 genes coherently regulated, i.e., actived in Rx1 gain of function and repressed in Rx1 loss of function experiments, or vice versa. RT‐qPCR and in situ hybridization confirmed the trend of regulation predicted by microarray data for the selected genes. Most of the genes upregulated by Rx1 are coexpressed with this transcription factor, while downregulated genes are either not expressed or expressed at very low levels in the early developing retina. Putative direct Rx1 target genes, activated by GR‐Rx1 in the absence of protein synthesis, include Ephrin B1 and Sh2d3c, an interactor of ephrinB1 receptor, which represent candidate novel effectors for the migration promoting activity of Rx1. Conclusions: This study identifies previously undescribed Rx1 regulated genes mainly involved in transcription regulation, cell migration/adhesion, and cell proliferation that contribute to delineate the molecular mechanisms underlying Rx1 activities. Developmental Dynamics 243:1352–1361, 2014.

A DNA transposon-based approach to functional screening in neural stem cells

We describe the use of DNA transposons as tools for carrying out functional screenings in murine embryonic stem (ES) cell-derived neural stem (NS) cells. NS cells are a new type of stem cells featuring radial glial properties, that undergoes symmetric cell division for an indefinite number of passages, expanding as a monolayer. In this model, the previously unreported Sleeping Beauty transposase M3A achieves an optimal blend of clone generation efficiency and low redundancy of integrations per clone, compared to the SB100X Sleeping Beauty variant and to the piggyBac transposon. The technology described here makes it possible to randomly trap genes in the NS cell genome and modify their expression or tag them with fluorescent markers and selectable genes, allowing recombinant cells to be isolated and expanded clonally. This approach will facilitate the identification of novel determinants of stem cell biology and neural cell fate specification in NS cells.

Brief Report: Rx1 Defines Retinal Precursor Identity by Repressing Alternative Fates Through the Activation of TLE2 and Hes4

The molecular mechanisms underlying the acquisition of retinal precursor identity are scarcely defined. Although the homeobox gene Rx1 (also known as Rax) plays a major role in specifying retinal precursors and maintaining their multipotent state, the involved mechanisms remain to be largely deciphered. Here, following a highthroughput screen for genes regulated by Rx1, we found that this transcription factor specifies the fate of retinal progenitors by repressing genes normally activated in adjacent ectodermal territories. Unexpectedly, we also observed that Rx1, mainly through the activation of the transcriptional repressors TLE2 and Hes4, is necessary and sufficient to inhibit endomesodermal gene expression in retinal precursors of the eye field. In particular, Rx1 knockdown leads retinogenic blastomeres to adopt an endomesodermal fate, indicating a previously undescribed function for Rx1 in preventing the expression of endomesoderm determinants known to inhibit retinal fate. Altogether these data suggest that an essential requirement to establish a retinal precursor identity is the active inhibition of pathways leading to alternative fates. Stem Cells 2013;31:2842–2847

Loss of function NFKB1 variants are the most common monogenic cause of CVID in Europeans.

This study was supported by The National Institute for Health Research England (grant number RG65966), and by the Center of Immunodeficiencies Amsterdam (CIDA). JET is supported by an MRC Clinician Scientist Fellowship (MR/L006197/1). AJT is supported by both the Wellcome Trust (104807/Z/14/Z) and by the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. EO receives personal fees from CSL Behring and MSD.

OC-044 Profile trial: predicting outcomes for crohn’s disease using a molecular biomarker

Introduction The course of Crohn’s disease (CD) varies substantially between affected individuals, but reliable prognostic markers are not available in clinical practice. This hinders disease management because patients with aggressive disease will be undertreated by conventional “step-up” therapy, while those with indolent disease would be exposed to the risks of unnecessary immunosuppression of a “top-down” approach. Previously, we have described a transcriptional signature that is detectable within peripheral blood CD8 T cells at diagnosis and which correlates with subsequent disease course. To translate this work to the bedside and overcome the technical challenges of separating cell populations, we sought to develop a whole blood qPCR-based biomarker that can re-capitulate the CD8 subgroups without the need for cell separation. Here we describe the development and validation of this biomarker and the upcoming biomarker-stratified trial that will test whether it can deliver personalised medicine in CD. Method From a training cohort of 69 newly diagnosed IBD patients, we simultaneously obtained a whole blood PAXgene RNA tube and peripheral blood CD8 T cell sample. Gene expression in both samples was measured by microarray. After confirming that the CD8 transcriptional signature was detectable and correlated with prognosis, we used machine learning to identify a transcriptional classifier in whole blood gene expression data that would re-capitulate the CD8 transcriptional subgroups. Model selection was performed using Bayesian Information Criterion and the genes identified were subsequently tested by qPCR and optimised to produce an 18 gene qPCR assay. Results Independent validation of this biomarker was established using a second, independent cohort of 85 newly diagnosed patients with CD from 4 sites around the United Kingdom. This validated the biomarker and confirmed that the subgroups it identified had significantly different disease courses (analogous to those observed with the CD8 T cell subgroups). The hazard ratio for time to treatment escalation in this validation cohort was 3.52 (1.84–6.76, 95% confidence intervals, p=0.0002). We now propose to conduct the first ever biomarker-stratified trial in any inflammatory disease to determine whether this biomarker can deliver personalised medicine in CD. Conclusion We have developed, optimised and validated a whole blood qPCR classifier that is able to predict disease course from diagnosis in IBD patients. This represents a major step towards personalised therapy in IBD, and we will soon investigate whether this could make personalised medicine a reality in CD. Disclosure of Interest None Declared