Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients

Despite advancements in genetic studies, it is difficult to understand and characterize the functional relevance of disease-associated genetic variants, especially in the context of a complex multifactorial disease such as multiple sclerosis (MS). As a large proportion of expression quantitative trait loci (eQTLs) are context-specific, we performed RNA-Seq in peripheral blood mononuclear cells from MS patients (n = 145) to identify eQTLs in regions centered on 109 MS risk single nucleotide polymorphisms and 7 associated human leukocyte antigen variants. We identified 77 statistically significant eQTL associations, including pseudogenes and non-coding RNAs. Thirty-eight out of 40 testable eQTL effects were colocalized with the disease association signal. As many eQTLs are tissue specific, we aimed to detail their significance in different cell types. Approximately 70% of the eQTLs were replicated and characterized in at least one major peripheral blood mononuclear cell-derived cell type. Furthermore, 40% of eQTLs were found to be more pronounced in MS patients compared with non-inflammatory neurological diseases patients. In addition, we found two single nucleotide polymorphisms to be significantly associated with the proportions of three different cell types. Mapping to enhancer histone marks and predicted transcription factor binding sites added additional functional evidence for eight eQTL regions. As an example, we found that rs71624119, shared with three other autoimmune diseases and located in a primed enhancer (H3K4me1) with potential binding for STAT transcription factors, significantly associates with ANKRD55 expression. This study provides many novel and validated targets for future functional characterization of MS and other diseases.

[1]  D. Bennett,et al.  Altered NEP2 expression and activity in mild cognitive impairment and Alzheimer's disease. , 2012, Journal of Alzheimer's disease : JAD.

[2]  N. Olson,et al.  Dendritic Cell-Associated Lectin-1: A Novel Dendritic Cell-Associated, C-Type Lectin-Like Molecule Enhances T Cell Secretion of IL-41 , 2002, The Journal of Immunology.

[3]  A. Minagar Related B cell clones populate the meninges and parenchyma of patients with multiple sclerosis , 2011 .

[4]  Andrew D. Johnson,et al.  SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap , 2008, Bioinform..

[5]  S. Harding,et al.  Expansion and preferential activation of the CD14+CD16+ monocyte subset during multiple sclerosis , 2014, Immunology and cell biology.

[6]  Calliope A. Dendrou,et al.  Class II HLA interactions modulate genetic risk for multiple sclerosis , 2015, Nature Genetics.

[7]  Pedro G. Ferreira,et al.  Transcriptome and genome sequencing uncovers functional variation in humans , 2013, Nature.

[8]  Simon C. Potter,et al.  Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis , 2011, Nature.

[9]  Paul Theodor Pyl,et al.  HTSeq—a Python framework to work with high-throughput sequencing data , 2014, bioRxiv.

[10]  A. Lin,et al.  AHI-1 interacts with BCR-ABL and modulates BCR-ABL transforming activity and imatinib response of CML stem/progenitor cells , 2008, The Journal of experimental medicine.

[11]  Davide Heller,et al.  STRING v10: protein–protein interaction networks, integrated over the tree of life , 2014, Nucleic Acids Res..

[12]  C. Wallace,et al.  Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics , 2013, PLoS genetics.

[13]  Data production leads,et al.  An integrated encyclopedia of DNA elements in the human genome , 2012 .

[14]  J. Schwartz,et al.  Neprilysin II: A putative novel metalloprotease and its isoforms in CNS and testis. , 2000, Biochemical and biophysical research communications.

[15]  Michael Q. Zhang,et al.  Integrative analysis of 111 reference human epigenomes , 2015, Nature.

[16]  B. Stranger,et al.  Regulation of Gene Expression in Autoimmune Disease Loci and the Genetic Basis of Proliferation in CD4+ Effector Memory T Cells , 2014, PLoS genetics.

[17]  J. Salamero,et al.  Homozygous human TAP peptide transporter mutation in HLA class I deficiency. , 1994, Science.

[18]  Thomas R. Gingeras,et al.  STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..

[19]  Y. Kong,et al.  Mapping a dynamic innate immunity protein interaction network regulating type I interferon production. , 2011, Immunity.

[20]  Hongbo Hu,et al.  Otud7b controls noncanonical NF-κB activation via deubiquitination of TRAF3 , 2013, Nature.

[21]  María M. Abad-Grau,et al.  Multiple Sclerosis Risk Variant HLA-DRB1*1501 Associates with High Expression of DRB1 Gene in Different Human Populations , 2012, PloS one.

[22]  S. Beck,et al.  Second proteasome-related gene in the human MHC class II region , 1991, Nature.

[23]  Wieslawa I. Mentzen,et al.  Genetic Variants Regulating Immune Cell Levels in Health and Disease , 2013, Cell.

[24]  A. Traboulsee,et al.  Ocrelizumab versus Interferon Beta‐1a in Relapsing Multiple Sclerosis , 2017, The New England journal of medicine.

[25]  Daphne Koller,et al.  Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes , 2014, Science.

[26]  H. Ullum,et al.  The Multiple Sclerosis Genomic Map: Role of peripheral immune cells and resident microglia in susceptibility , 2017, bioRxiv.

[27]  F. Sharp,et al.  Genome wide differences of gene expression associated with HLA-DRB1 genotype in multiple sclerosis: A pilot study , 2013, Journal of Neuroimmunology.

[28]  J. Lozano,et al.  MERTK as negative regulator of human T cell activation , 2015, Journal of leukocyte biology.

[29]  X. Montalban,et al.  Novel Insights into the Multiple Sclerosis Risk Gene ANKRD55 , 2016, The Journal of Immunology.

[30]  R. Andrews,et al.  Innate Immune Activity Conditions the Effect of Regulatory Variants upon Monocyte Gene Expression , 2014, Science.

[31]  Kenny Q. Ye,et al.  An integrated map of genetic variation from 1,092 human genomes , 2012, Nature.

[32]  M. Daly,et al.  Genetic and Epigenetic Fine-Mapping of Causal Autoimmune Disease Variants , 2014, Nature.

[33]  H. Link,et al.  Review: cytokines and the pathogenesis of multiple sclerosis , 1996, Journal of neuroscience research.

[34]  A. Compston,et al.  Recommended diagnostic criteria for multiple sclerosis: Guidelines from the international panel on the diagnosis of multiple sclerosis , 2001, Annals of neurology.

[35]  C. Watson,et al.  The Effect of Single Nucleotide Polymorphisms from Genome Wide Association Studies in Multiple Sclerosis on Gene Expression , 2010, PloS one.

[36]  T. Olsson,et al.  Genetic and Environmental Risk Factors for Multiple Sclerosis—A Role for Interaction Analysis , 2014 .

[37]  D. Cox,et al.  B cell exchange across the blood-brain barrier in multiple sclerosis. , 2012, The Journal of clinical investigation.

[38]  Shane J. Neph,et al.  Systematic Localization of Common Disease-Associated Variation in Regulatory DNA , 2012, Science.

[39]  Jan Hillert,et al.  Gene expression profiling in multiple sclerosis: A disease of the central nervous system, but with relapses triggered in the periphery? , 2010, Neurobiology of Disease.

[40]  P. Pandolfi,et al.  A coding-independent function of gene and pseudogene mRNAs regulates tumour biology , 2010, Nature.

[41]  M. Pirinen,et al.  Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis , 2013, Nature Genetics.

[42]  Ash A. Alizadeh,et al.  Robust enumeration of cell subsets from tissue expression profiles , 2015, Nature Methods.

[43]  W. Huber,et al.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.

[44]  Alexander T. Dilthey,et al.  Multi-Population Classical HLA Type Imputation , 2013, PLoS Comput. Biol..

[45]  A. López de Munain,et al.  HLA-DRB1*15:01 and multiple sclerosis: a female association? , 2012, Multiple sclerosis.

[46]  A. Dejean,et al.  A Role for VAV1 in Experimental Autoimmune Encephalomyelitis and Multiple Sclerosis , 2009, Science Translational Medicine.

[47]  Manolis Kellis,et al.  Large-scale epigenome imputation improves data quality and disease variant enrichment , 2015, Nature Biotechnology.

[48]  K. Hansen,et al.  Removing technical variability in RNA-seq data using conditional quantile normalization , 2012, Biostatistics.

[49]  Robert Tibshirani,et al.  Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data , 2013, Statistical methods in medical research.

[50]  T. Mak,et al.  Activation of noncanonical NF-κB requires coordinated assembly of a regulatory complex of the adaptors cIAP1, cIAP2, TRAF2, TRAF3 and the kinase NIK , 2008, Nature Immunology.

[51]  P. Sørensen,et al.  Cellular sources of dysregulated cytokines in relapsing-remitting multiple sclerosis , 2012, Journal of Neuroinflammation.

[52]  Eurie L. Hong,et al.  Annotation of functional variation in personal genomes using RegulomeDB , 2012, Genome research.

[53]  K. Morris,et al.  A pseudogene long noncoding RNA network regulates PTEN transcription and translation in human cells , 2013, Nature Structural &Molecular Biology.

[54]  G. Casari,et al.  A physical and functional map of the human TNF-alpha/NF-kappa B signal transduction pathway. , 2004, Nature cell biology.

[55]  M. Duddy,et al.  Analyses of all matrix metalloproteinase members in leukocytes emphasize monocytes as major inflammatory mediators in multiple sclerosis. , 2003, Brain : a journal of neurology.

[56]  Manolis Kellis,et al.  Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers , 2015, Nature Genetics.

[57]  Oliver H. Tam,et al.  Pseudogene-derived small interfering RNAs regulate gene expression in mouse oocytes , 2008, Nature.

[58]  Per Eriksson,et al.  Association of Genetic Risk Variants With Expression of Proximal Genes Identifies Novel Susceptibility Genes for Cardiovascular Disease , 2010, Circulation. Cardiovascular genetics.

[59]  Martin Renqiang Min,et al.  An integrated encyclopedia of DNA elements in the human genome , 2012 .

[60]  M. Lupien,et al.  Combinatorial effects of multiple enhancer variants in linkage disequilibrium dictate levels of gene expression to confer susceptibility to common traits , 2014, Genome research.

[61]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[62]  M. Bottai,et al.  Modest familial risks for multiple sclerosis: a registry-based study of the population of Sweden , 2014, Brain : a journal of neurology.

[63]  H. Kayserili,et al.  Mutations in the AHI1 gene, encoding jouberin, cause Joubert syndrome with cortical polymicrogyria. , 2004, American journal of human genetics.

[64]  F. Vannberg,et al.  GENETICS OF GENE EXPRESSION IN PRIMARY IMMUNE CELLS IDENTIFIES CELL-SPECIFIC MASTER REGULATORS AND ROLES OF HLA ALLELES , 2012, Nature Genetics.

[65]  Giulio Superti-Furga,et al.  A physical and functional map of the human TNF-α/NF-κB signal transduction pathway , 2004, Nature Cell Biology.