Breakdown of multiple sclerosis genetics to identify an integrated disease network and potential variant mechanisms

Genetics of multiple sclerosis (MS) are highly polygenic with few insights into mechanistic associations with pathology. In this study, we assessed MS genetics through linkage disequilibrium and missense variant interpretation to yield a MS gene network. This network of 96 genes was taken through pathway analysis, tissue expression profiles, single cell expression segregation, expression quantitative trait loci (eQTLs), genome annotations, transcription factor (TF) binding profiles, structural genome looping, and overlap with additional associated genetic traits. This work revealed immune system dysfunction, nerve cell myelination, energetic control, transcriptional regulation, and variants that overlap multiple autoimmune disorders. Tissue-specific expression and eQTLs of MS genes implicate multiple immune cell types including macrophages, neutrophils, and T cells, while the genes in neural cell types enrich for oligodendrocyte and myelin sheath biology. There are eQTLs in linkage with lead MS variants in 25 genes including the multitissue eQTL, rs9271640, for HLA-DRB1/ DRB5. Using multiple functional genomic databases, we identified noncoding variants that disrupt TF binding for GABPA, CTCF, EGR1, YY1, SPI1, CLOCK, ARNTL, BACH1, and GFI1. Overall, this paper suggests multiple genetic mechanisms for MS associated variants while highlighting the importance of a systems biology and network approach when elucidating intersections of the immune and nervous system.

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Progress and challenge for computational quantification of tissue immune cells

Briefings in Bioinformatics ◽

10.1093/bib/bbaa358 ◽

2021 ◽

Author(s):

Ziyi Chen ◽

Aiping Wu

Keyword(s):

Immune Cells ◽

Computational Models ◽

Immune Cell ◽

Expression Profiles ◽

Cell Types ◽

Tissue Expression ◽

The Body ◽

Advantages And Disadvantages ◽

Benchmark Datasets ◽

The Impact

Abstract Tissue immune cells have long been recognized as important regulators for the maintenance of balance in the body system. Quantification of the abundance of different immune cells will provide enhanced understanding of the correlation between immune cells and normal or abnormal situations. Currently, computational methods to predict tissue immune cell compositions from bulk transcriptomes have been largely developed. Therefore, summarizing the advantages and disadvantages is appropriate. In addition, an examination of the challenges and possible solutions for these computational models will assist the development of this field. The common hypothesis of these models is that the expression of signature genes for immune cell types might represent the proportion of immune cells that contribute to the tissue transcriptome. In general, we grouped all reported tools into three groups, including reference-free, reference-based scoring and reference-based deconvolution methods. In this review, a summary of all the currently reported computational immune cell quantification tools and their applications, limitations, and perspectives are presented. Furthermore, some critical problems are found that have limited the performance and application of these models, including inadequate immune cell type, the collinearity problem, the impact of the tissue environment on the immune cell expression level, and the deficiency of standard datasets for model validation. To address these issues, tissue specific training datasets that include all known immune cells, a hierarchical computational framework, and benchmark datasets including both tissue expression profiles and the abundances of all the immune cells are proposed to further promote the development of this field.

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484 Bioturing browser: interactively explore public single cell sequencing data

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0484 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A520-A520

Author(s):

Son Pham ◽

Tri Le ◽

Tan Phan ◽

Minh Pham ◽

Huy Nguyen ◽

...

Keyword(s):

Single Cell ◽

Immune Cell ◽

Expression Profiles ◽

Meta Analysis ◽

Cell Types ◽

Sequencing Data ◽

Single Cell Sequencing ◽

Data Formats ◽

Cancer Types ◽

Cell Data

BackgroundSingle-cell sequencing technology has opened an unprecedented ability to interrogate cancer. It reveals significant insights into the intratumoral heterogeneity, metastasis, therapeutic resistance, which facilitates target discovery and validation in cancer treatment. With rapid advancements in throughput and strategies, a particular immuno-oncology study can produce multi-omics profiles for several thousands of individual cells. This overflow of single-cell data poses formidable challenges, including standardizing data formats across studies, performing reanalysis for individual datasets and meta-analysis.MethodsN/AResultsWe present BioTuring Browser, an interactive platform for accessing and reanalyzing published single-cell omics data. The platform is currently hosting a curated database of more than 10 million cells from 247 projects, covering more than 120 immune cell types and subtypes, and 15 different cancer types. All data are processed and annotated with standardized labels of cell types, diseases, therapeutic responses, etc. to be instantly accessed and explored in a uniform visualization and analytics interface. Based on this massive curated database, BioTuring Browser supports searching similar expression profiles, querying a target across datasets and automatic cell type annotation. The platform supports single-cell RNA-seq, CITE-seq and TCR-seq data. BioTuring Browser is now available for download at www.bioturing.com.ConclusionsN/A

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Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

eLife ◽

10.7554/elife.26476 ◽

2017 ◽

Vol 6 ◽

Cited By ~ 107

Author(s):

Julien Racle ◽

Kaat de Jonge ◽

Petra Baumgaertner ◽

Daniel E Speiser ◽

David Gfeller

Keyword(s):

Gene Expression ◽

Gene Expression Data ◽

Immune Cell ◽

Expression Profiles ◽

Cell Types ◽

Response To Therapy ◽

Expression Data ◽

Cell Type ◽

Tumor Gene Expression ◽

Tumor Gene

Immune cells infiltrating tumors can have important impact on tumor progression and response to therapy. We present an efficient algorithm to simultaneously estimate the fraction of cancer and immune cell types from bulk tumor gene expression data. Our method integrates novel gene expression profiles from each major non-malignant cell type found in tumors, renormalization based on cell-type-specific mRNA content, and the ability to consider uncharacterized and possibly highly variable cell types. Feasibility is demonstrated by validation with flow cytometry, immunohistochemistry and single-cell RNA-Seq analyses of human melanoma and colorectal tumor specimens. Altogether, our work not only improves accuracy but also broadens the scope of absolute cell fraction predictions from tumor gene expression data, and provides a unique novel experimental benchmark for immunogenomics analyses in cancer research (http://epic.gfellerlab.org).

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KVα1 channels in murine arterioles: differential cellular expression and regulation of diameter

AJP Heart and Circulatory Physiology ◽

10.1152/ajpheart.2001.281.3.h1057 ◽

2001 ◽

Vol 281 (3) ◽

pp. H1057-H1065 ◽

Cited By ~ 39

Author(s):

A. Cheong ◽

A. M. Dedman ◽

S. Z. Xu ◽

D. J. Beech

Keyword(s):

Smooth Muscle ◽

Smooth Muscle Cells ◽

Expression Profiles ◽

Second Messengers ◽

Expression Patterns ◽

Muscle Cells ◽

Cell Types ◽

Specific Expression ◽

Major Function ◽

Cellular Expression

The primary objectives of this study were to reveal cell-specific expression patterns and functions of voltage-gated K+ channel (KVα1) subunits in precapillary arterioles of the murine cerebral circulation. KVα1 were detected using peptide-specific antibodies in immunofluorescence and Western blotting assays. KV1.2 was localized almost exclusively to endothelial cells, whereas KV1.5 was discretely localized to the nerves and nerve terminals that innervate the arterioles. KV1.5 also localized specifically to arteriolar nerves in human pial membrane. KV1.5 was notable for its absence from smooth muscle cells. KV1.3, KV1.4, and KV1.6 were localized to endothelial and smooth muscle cells, although KV1.4 had a low expression level. KV1.1 was not expressed. Therefore, we show that different cell types of pial arterioles have distinct physiological expression profiles of KVα1, conferring the possibility of differential modulation by extracellular and second messengers. Furthermore, we show recombinant agitoxin-2 and margatoxin are potent vasoconstrictors, suggesting that KVα1 subunits have a major function in determining arteriolar resistance to blood flow.

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Combining evidence from four immune cell types identifies DNA methylation patterns that implicate functionally distinct pathways during Multiple Sclerosis progression

EBioMedicine ◽

10.1016/j.ebiom.2019.04.042 ◽

2019 ◽

Vol 43 ◽

pp. 411-423 ◽

Cited By ~ 7

Author(s):

Ewoud Ewing ◽

Lara Kular ◽

Sunjay J. Fernandes ◽

Nestoras Karathanasis ◽

Vincenzo Lagani ◽

...

Keyword(s):

Multiple Sclerosis ◽

Dna Methylation ◽

Immune Cell ◽

Cell Types ◽

Combining Evidence ◽

Methylation Patterns

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The gene coding for secreted phosphoprotein1/osteopontin is the most overexpressed gene in cholangiocarcinoma—detected by oligonucleotide arrays and LightCycler analysis

Journal of Clinical Oncology ◽

10.1200/jco.2006.24.18_suppl.10036 ◽

2006 ◽

Vol 24 (18_suppl) ◽

pp. 10036-10036

Author(s):

H. G. Hass ◽

J. Jobst ◽

O. Nehls ◽

A. Frilling ◽

J. T. Hartmann ◽

...

Keyword(s):

Cell Function ◽

Immune Cell ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Cell Types ◽

Cell Phenotype ◽

Oligonucleotide Arrays ◽

Surface Receptors ◽

Malignant Liver ◽

And Control

10036 Background: Cholangiocarcinomas (CCC) are the second most common primary hepatic malignancy with a still poor prognosis and arise from biliary epithelia or cholangiocytes. Until now, less is known about the molecular pathways leeding to CCC. Methods: Oligonucleotide arrays were used to analyze gene expression profiles of 8 intrahepatic CCCs. After isolation of tRNA and transcription into cDNA, biotin-labelled cRNA probes were hybridized to GeneArrays (Affymetrix U 133A) containing probes of more than 22.000 genes/ESTs. For two-dimensional cluster analysis we used special software programs (Genexplore, GeneSpring). Dysregulated genes were determined by presence in more than 70% and a 2-fold change in relation to the corresponding non-malignant liver tissue. Lightcycler analysis were performed to validate the expression datas of dysregulated genes. Results: A total of 694 dysregulated genes (330 up-/364 down-regulated, compared with corresponding non-malignant tissue) were detected. As the gene with the highest and most consistent upregulation we were able to identify osteopontin (OPN) with an average 5-fold overexpression in all CCC tissues. OPN is an acidic phosphoprotein that is secreted by osteoblasts, macrophages and many other cell types and binds to a variety of cell surface receptors (integrins/CD44). OPN is multifunctional, with activities in cell migration, regulation of bone metabolism, immune cell function and control of tumor cell phenotype. Elevated OPN levels were seen in different tumors but until now no data exist about the expression in CCCs. As one possible interaction in human carcinogenesis, OPN has recently been shown to be a novel substrate for some MMPs, which play an importand role in tumor invasion and metastasis. Conclusions: This is the first report about an overexpression of OPN in CCC and our data indicate an important role in cholangiocarcinogenesis. Further studies are needed to illucidate the moleculargenetic mechanisms of OPN interactions in CCC. No significant financial relationships to disclose.

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Paired Immunoglobulin-like Type 2 Receptor Alpha G78R variant alters ligand binding and confers protection to Alzheimer’s disease

10.1101/325936 ◽

2018 ◽

Author(s):

Nisha Rathore ◽

Sree Ranjani Ramani ◽

Homer Pantua ◽

Jian Payandeh ◽

Tushar Bhangale ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Immune Cell ◽

Disease Risk ◽

Missense Variant ◽

Cell Types ◽

Glycoprotein B ◽

Receptor Alpha ◽

Hsv 1

AbstractPaired Immunoglobulin-like Type 2 Receptor Alpha (PILRA) is a cell surface inhibitory receptor that recognizes specific O-glycosylated proteins and is expressed on various innate immune cell types including microglia. We show here that a common missense variant (G78R, rs1859788) of PILRA is the likely causal allele for the confirmed Alzheimer’s disease risk locus at 7q21 (rs1476679). The G78R variant alters the interaction of residues essential for sialic acid engagement, resulting in >50% reduced binding for several PILRA ligands including a novel ligand, complement component 4A, and herpes simplex virus 1 (HSV-1) glycoprotein B. PILRA is an entry receptor for HSV-1 via glycoprotein B, and macrophages derived from R78 homozygous donors showed significantly decreased levels of HSV-1 infection at several multiplicities of infection compared to homozygous G78 macrophages. We propose that PILRA G78R protects individuals from Alzheimer’s disease risk via reduced inhibitory signaling in microglia and reduced microglial infection during HSV-1 recurrence.

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Unraveling patterns of disrupted gene expression across a complex tissue

10.1101/2021.07.08.451646 ◽

2021 ◽

Author(s):

Kelsie E Hunnicutt ◽

Jeffrey M Good ◽

Erica L Larson

Keyword(s):

Gene Expression ◽

Evolutionary Biology ◽

Large Scale ◽

Expression Profiles ◽

Cell Types ◽

Tissue Expression ◽

Network Evolution ◽

F1 Hybrids ◽

Cellular Composition ◽

Mus Musculus Musculus

Whole tissue RNASeq is the standard approach for studying gene expression divergence in evolutionary biology and provides a snapshot of the comprehensive transcriptome for a given tissue. However, whole tissues consist of diverse cell types differing in expression profiles, and the cellular composition of these tissues can evolve across species. Here, we investigate the effects of different cellular composition on whole tissue expression profiles. We compared gene expression from whole testes and enriched spermatogenesis populations in two species of house mice, Mus musculus musculus and M. m. domesticus, and their sterile and fertile F1 hybrids, which differ in both cellular composition and regulatory dynamics. We found that cellular composition differences skewed expression profiles and differential gene expression in whole testes samples. Importantly, both approaches were able to detect large-scale patterns such as disrupted X chromosome expression although whole testes sampling resulted in decreased power to detect differentially expressed genes. We encourage researchers to account for histology in RNASeq and consider methods that reduce sample complexity whenever feasible. Ultimately, we show that differences in cellular composition between tissues can modify expression profiles, potentially altering inferred gene ontological processes, insights into gene network evolution, and processes governing gene expression evolution.

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Heterozygous transcriptional and nonsense decay signatures in blood outgrowth endothelial cells from patients with hereditary haemorrhagic telangiectasia

10.1101/2021.12.05.471269 ◽

2021 ◽

Author(s):

Maria E Bernabeu-Herrero ◽

Dilip Patel ◽

Adrianna Bielowka ◽

Sindu Srikaran ◽

Patricia Chaves Guerrero ◽

...

Keyword(s):

Endothelial Cells ◽

Protein Production ◽

Transforming Growth Factor ◽

Expression Profiles ◽

Transforming Growth Factor Β ◽

Premature Termination Codon ◽

Cell Types ◽

Tissue Expression ◽

Additional Stress ◽

Hereditary Haemorrhagic Telangiectasia

ABSTRACTIn order to identify cellular phenotypes resulting from nonsense (gain of stop/premature termination codon) variants, we devised a framework of analytic methods that minimised confounder contributions, and applied to blood outgrowth endothelial cells (BOECs) derived from controls and patients with heterozygous nonsense variants in ACVRL1, ENG or SMAD4 causing hereditary haemorrhagic telangiectasia (HHT). Following validation of 48 pre-selected genes by single cell qRT-PCR, discovery RNASeq ranked HHT-differential alignments of 16,807 Ensembl transcripts. Consistent gene ontology (GO) processes enriched compared to randomly-selected gene lists included bone morphogenetic protein, transforming growth factor-β and angiogenesis GO processes already implicated in HHT, further validating methodologies. Additional terms/genes including for endoplasmic reticulum stress could be attributed to a generic process of inefficient nonsense mediated decay (NMD). NMD efficiency ranged from 78-92% (mean 87%) in different BOEC cultures, with misprocessed mutant protein production confirmed by pulse chase experiments. Genes in HHT-specific and generic nonsense decay (ND) lists displayed differing expression profiles in normal endothelial cells exposed to an additional stress of exogenous 10μmol/L iron which acutely upregulates multiple mRNAs: Despite differing donors and endothelial cell types, >50% of iron-induced variability could be explained by the magnitude of transcript downregulation in HHT BOECs with less efficient NMD. The Genotype Tissue Expression (GTEx) Project indicated ND list genes were usually most highly expressed in non-endothelial tissues. However, across 5 major tissues, although 18/486 nonsense and frameshift variants in highly expressed genes were captured in GTEx, none were sufficiently prevalent to obtain genome-wide significant p values for expression quantitative trait loci (GnomAD allele frequencies <0.0005). In conclusion, RNASeq analytics of rare genotype-selected, patient-derived endothelial cells facilitated identification of natural disease-specific and more generic transcriptional signatures. Future studies should evaluate wider relevance and whether injury from external agents is augmented in cells with already high burdens of defective protein production.

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Single-cell RNA sequencing reveals micro-evolution of the stickleback immune system

10.1101/2021.12.20.473470 ◽

2021 ◽

Author(s):

Lauren E Fuess ◽

Daniel I Bolnick

Keyword(s):

Immune System ◽

Single Cell ◽

Immune Cells ◽

Gasterosteus Aculeatus ◽

Immune Cell ◽

Expression Profiles ◽

Cell Types ◽

Model Systems ◽

System Structure ◽

Ecological Processes

Pathogenic infection is an important driver of many ecological processes. Furthermore, variability in immune function is an important driver of differential infection outcomes. New evidence would suggest that immune variation extends to broad cellular structure of immune systems. However, variability at such broad levels is traditionally difficult to detect in non-model systems. Here we leverage single cell transcriptomic approaches to document signatures of microevolution of immune system structure in a natural system, the three-spined stickleback (Gasterosteus aculeatus). We sampled nine adult fish from three populations with variability in resistance to a cestode parasite, Schistocephalus solidus, to create the first comprehensive immune cell atlas for G. aculeatus. Eight major immune cell types, corresponding to major vertebrate immune cells, were identified. We were also able to document significant variation in both abundance and expression profiles of the individual immune cell types, among the three populations of fish. This variability may contribute to observed variability in parasite susceptibility. Finally, we demonstrate that identified cell type markers can be used to reinterpret traditional transcriptomic data. Combined our study demonstrates the power of single cell sequencing to not only document evolutionary phenomena (i.e. microevolution of immune cells), but also increase the power of traditional transcriptomic datasets.

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