Paradoxical downregulation of HLA-A expression by IFNγ associated with schizophrenia and noncoding genes

Predicting Pseudogene-miRNA Associations Based on Feature Fusion and Graph Auto-Encoder

Pseudogenes were originally regarded as non-functional components scattered in the genome during evolution. Recent studies have shown that pseudogenes can be transcribed into long non-coding RNA and play a key role at multiple functional levels in different physiological and pathological processes. microRNAs (miRNAs) are a type of non-coding RNA, which plays important regulatory roles in cells. Numerous studies have shown that pseudogenes and miRNAs have interactions and form a ceRNA network with mRNA to regulate biological processes and involve diseases. Exploring the associations of pseudogenes and miRNAs will facilitate the clinical diagnosis of some diseases. Here, we propose a prediction model PMGAE (Pseudogene–MiRNA association prediction based on the Graph Auto-Encoder), which incorporates feature fusion, graph auto-encoder (GAE), and eXtreme Gradient Boosting (XGBoost). First, we calculated three types of similarities including Jaccard similarity, cosine similarity, and Pearson similarity between nodes based on the biological characteristics of pseudogenes and miRNAs. Subsequently, we fused the above similarities to construct a similarity profile as the initial representation features for nodes. Then, we aggregated the similarity profiles and associations of nodes to obtain the low-dimensional representation vector of nodes through a GAE. In the last step, we fed these representation vectors into an XGBoost classifier to predict new pseudogene–miRNA associations (PMAs). The results of five-fold cross validation show that PMGAE achieves a mean AUC of 0.8634 and mean AUPR of 0.8966. Case studies further substantiated the reliability of PMGAE for mining PMAs and the study of endogenous RNA networks in relation to diseases.

Function of multiple sclerosis-protective HLA class I alleles revealed by genome-wide protein-quantitative trait loci mapping of interferon signalling

Interferons (IFNs) are cytokines that are central to the host defence against viruses and other microorganisms. If not properly regulated, IFNs may contribute to the pathogenesis of inflammatory autoimmune, or infectious diseases. To identify genetic polymorphisms regulating the IFN system we performed an unbiased genome-wide protein-quantitative trait loci (pQTL) mapping of cell-type specific type I and type II IFN receptor levels and their responses in immune cells from 303 healthy individuals. Seven genome-wide significant (p < 5.0E-8) pQTLs were identified. Two independent SNPs that tagged the multiple sclerosis (MS)-protective HLA class I alleles A*02/A*68 and B*44, respectively, were associated with increased levels of IFNAR2 in B and T cells, with the most prominent effect in IgD^–CD27⁺ memory B cells. The increased IFNAR2 levels in B cells were replicated in cells from an independent set of healthy individuals and in MS patients. Despite increased IFNAR2 levels, B and T cells carrying the MS-protective alleles displayed a reduced response to type I IFN stimulation. Expression and methylation-QTL analysis demonstrated increased mRNA expression of the pseudogene HLA-J in B cells carrying the MS-protective class I alleles, possibly driven via methylation-dependent transcriptional regulation. Together these data suggest that the MS-protective effects of HLA class I alleles are unrelated to their antigen-presenting function, and propose a previously unappreciated function of type I IFN signalling in B and T cells in MS immune-pathogenesis.

Genetic association studies have been very successful in identifying disease-associated single nucleotide polymorphisms (SNPs), but it has been challenging to define the molecular mechanisms underlying these associations. As interferons (IFNs) have a central role in the immune system, we hypothesized that some of the SNPs associated to immune-mediated diseases would affect the IFN system. By combining genetic data with characterization of interferon receptor levels and their responses on the protein level in immune cells from 303 genotyped healthy individuals, we show that two SNPs tagging the HLA class I alleles A*02/A*68 and B*44 are associated with a decreased response to type I IFN stimulation in B cells and T cells. Notably, both HLA-A*02 and HLA-B*44 confer protection from developing multiple sclerosis (MS), which is a chronic inflammatory neurologic disease. In addition to suggesting a pathogenic role of enhanced type I interferon signalling in B cells and T cells in MS, our data emphasize the fact that genetic associations in the HLA locus can affect functions not directly associated to antigen presentation, which conceptually may be important for other diseases genetically associated to the HLA locus.

Blood transcriptomic comparison of individuals with and without autism spectrum disorder: A combined-samples mega-analysis

Blood-based microarray studies comparing individuals affected with autism spectrum disorder (ASD) and typically developing individuals help characterize differences in circulating immune cell functions and offer potential biomarker signal. We sought to combine the subject-level data from previously published studies by mega-analysis to increase the statistical power. We identified studies that compared ex vivo blood or lymphocytes from ASD-affected individuals and unrelated comparison subjects using Affymetrix or Illumina array platforms. Raw microarray data and clinical meta-data were obtained from seven studies, totaling 626 affected and 447 comparison subjects. Microarray data were processed using uniform methods. Covariate-controlled mixed-effect linear models were used to identify gene transcripts and co-expression network modules that were significantly associated with diagnostic status. Permutation-based gene-set analysis was used to identify functionally related sets of genes that were over- and under-expressed among ASD samples. Our results were consistent with diminished interferon-, EGF-, PDGF-, PI3K-AKT-mTOR-, and RAS-MAPK-signaling cascades, and increased ribosomal translation and NK-cell related activity in ASD. We explored evidence for sex-differences in the ASD-related transcriptomic signature. We also demonstrated that machine-learning classifiers using blood transcriptome data perform with moderate accuracy when data are combined across studies. Comparing our results with those from blood-based studies of protein biomarkers (e.g., cytokines and trophic factors), we propose that ASD may feature decoupling between certain circulating signaling proteins (higher in ASD samples) and the transcriptional cascades which they typically elicit within circulating immune cells (lower in ASD samples). These findings provide insight into ASD-related transcriptional differences in circulating immune cells. © 2016 Wiley Periodicals, Inc.

Epigenetics in Schizophrenia: A Pilot Study of Global DNA Methylation in Different Brain Regions Associated with Higher Cognitive Functions

Attempts to discover genes that are involved in the pathogenesis of major psychiatric disorders have been frustrating and often fruitless. Concern is building about the need to understand the complex ways in which nature and nurture interact to produce mental illness. We analyze the epigenome in several brain regions from schizophrenic patients with severe cognitive impairment using high-resolution (450K) DNA methylation array. We identified 139 differentially methylated CpG sites included in known and novel candidate genes sequences as well as in and intergenic sequences which functions remain unknown. We found that altered DNA methylation is not restricted to a particular region, but includes others such as CpG shelves and gene bodies, indicating the presence of different DNA methylation signatures depending on the brain area analyzed. Our findings suggest that epimutations are not relatables between different tissues or even between tissues' regions, highlighting the need to adequately study brain samples to obtain reliable data concerning the epigenetics of schizophrenia.

Expression of classical HLA class I molecules: regulation and clinical impacts: Julia Bodmer Award Review 2015

Human leukocyte antigen (HLA) class I genes are ubiquitously expressed, but in a tissue specific-manner. Their expression is primarily regulated at the transcriptional level and can be modulated both positively and negatively by different stimuli. Advances in sequencing technologies led to the identification of new regulatory variants located in the untranslated regions (UTRs), which could influence the expression. After a brief description of the mechanisms underlying the transcriptional regulation of HLA class I genes expression, we will review how the expression levels of HLA class I genes could affect biological and pathological processes. Then, we will discuss on the differential expression of HLA class I genes according to the locus, allele and UTR polymorphisms and its clinical impact. This interesting field of study led to a new dimension of HLA typing, going beyond a qualitative aspect.

The spatio-temporal expression of MHC class I molecules during human hippocampal formation development

In the immune system, the major histocompatibility complex (MHC) class I molecules mediate both the innate and adaptive immune responses in vertebrates. There has been a dogma that the central nervous system (CNS) is immune privileged and healthy neurons do not express MHC class I molecules. However, recent studies have indicated that the expression and non-immunobiologic roles of MHC class I in mammalian CNS. But data referring to humans are scarce. In this study we report the expression and cellular localization of MHC class I in the human fetal, early postnatal and adult hippocampal formation. The expression of MHC class I was very low in the hippocampus at 20 (gestational weeks) GW and slowly increased at 27-33 GW. The gradually increased expression in the somata of some granular cells in dentate gyrus (DG) was observed at 30-33 GW. Whereas, a rapid increase in MHC class I molecules expression was found in the subiculum and it reached high levels at 31-33 GW and maintained at postnatal 55 days. No expression of MHC class I was found in hippocampal formation in adult. MHC class I heavy chain and β2 microglobulin (β2M) showed similar expression in some cells of the hippocampal formation at 30-33 GW. Moreover, MHC class I molecules were mainly expressed in neurons and most MHC class I-expressing neurons were glutamatergic. The temporal and spatial patterns of MHC class I expression appeared to follow gradients of pyramidal neurons maturation in the subiculum at prenatal stages and suggested that MHC class I molecules are likely to regulate neuron maturation. This article is part of a Special Issue entitled Priority to Publish.