Author
Niek de Vries
Other affiliations: Academic Medical Center, VU University Amsterdam, GlaxoSmithKline
Bio: Niek de Vries is an academic researcher from University of Amsterdam. The author has contributed to research in topics: Rheumatoid arthritis & Medicine. The author has an hindex of 29, co-authored 66 publications receiving 7140 citations. Previous affiliations of Niek de Vries include Academic Medical Center & VU University Amsterdam.
Topics: Rheumatoid arthritis, Medicine, Arthritis, T-cell receptor, T cell
Papers published on a yearly basis
Papers
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Broad Institute1, Harvard University2, Monash University3, Kyoto University4, Genentech5, Vanderbilt University6, New York University7, NewYork–Presbyterian Hospital8, Second Military Medical University9, University of Queensland10, University of Toronto11, University of Groningen12, University of Tartu13, Beijing Jiaotong University14, Icahn School of Medicine at Mount Sinai15, Radboud University Nijmegen16, Medisch Spectrum Twente17, Leiden University18, University of Paris19, French Institute of Health and Medical Research20, University of Alabama at Birmingham21, University of Cambridge22, University of Amsterdam23, GlaxoSmithKline24, Hanyang University25, Spanish National Research Council26, Complutense University of Madrid27, Umeå University28, Boston University29, Council on Education for Public Health30, McGill University31, University of Manchester32, National Health Service33, University of Pittsburgh34, University of California, San Francisco35, Karolinska Institutet36, North Shore-LIJ Health System37, University of Chicago38, University of Tokyo39
TL;DR: A genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries provides empirical evidence that the genetics of RA can provide important information for drug discovery, and sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis.
Abstract: A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
1,910 citations
Brigham and Women's Hospital1, Harvard University2, Massachusetts Institute of Technology3, National Institutes of Health4, University of Toronto5, University of Manchester6, Celera Corporation7, Leiden University8, Karolinska Institutet9, University of Texas at Austin10, Radboud University Nijmegen Medical Centre11, University of California, San Francisco12, VU University Amsterdam13, University of Leeds14, University of Oxford15, University of Aberdeen16, The Feinstein Institute for Medical Research17, Karolinska University Hospital18, University of Groningen19, University of California, Davis20, King's College21, University of Amsterdam22, University of Sheffield23, Hoffmann-La Roche24, University Health Network25, North Shore-LIJ Health System26, Broad Institute27
TL;DR: Seven new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 × 10−8) in an analysis of all 41,282 samples, and an additional 11 SNPs replicated at P < 0.05, suggesting that most represent genuine rhearatoid arthritisrisk alleles.
Abstract: To identify new genetic risk factors for rheumatoid arthritis, we conducted a genome-wide association study meta-analysis of 5,539 autoantibody-positive individuals with rheumatoid arthritis (cases) and 20,169 controls of European descent, followed by replication in an independent set of 6,768 rheumatoid arthritis cases and 8,806 controls. Of 34 SNPs selected for replication, 7 new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 x 10(-8)) in an analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5 and PXK. We also refined associations at two established rheumatoid arthritis risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed rheumatoid arthritis risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P < 0.05, many of which are validated autoimmune risk alleles, suggesting that most represent genuine rheumatoid arthritis risk alleles.
1,277 citations
TL;DR: Investigation of the contribution of microRNA-146a, identified in the pilot expression profiling step, to the pathogenesis of systemic lupus erythematosus revealed a negative regulator of innate immunity, which provides potential novel strategies for therapeutic intervention.
Abstract: Objective
MicroRNA have recently been identified as regulators that modulate target gene expression and are involved in shaping the immune response. This study was undertaken to investigate the contribution of microRNA-146a (miR-146a), which was identified in the pilot expression profiling step, to the pathogenesis of systemic lupus erythematosus (SLE).
Methods
TaqMan microRNA assays of peripheral blood leukocytes were used for comparison of expression levels of microRNA between SLE patients and controls. Transfection and stimulation of cultured cells were conducted to determine the biologic function of miR-146a. Bioinformatics prediction and validation by reporter gene assay and Western blotting were performed to identify miR-146a targets.
Results
Profiling of 156 miRNA in SLE patients revealed the differential expression of multiple microRNA, including miR-146a, a negative regulator of innate immunity. Further analysis showed that underexpression of miR-146a negatively correlated with clinical disease activity and with interferon (IFN) scores in patients with SLE. Of note, overexpression of miR-146a reduced, while inhibition of endogenous miR-146a increased, the induction of type I IFNs in peripheral blood mononuclear cells (PBMCs). Furthermore, miR-146a directly repressed the transactivation downstream of type I IFN. At the molecular level, miR-146a could target IFN regulatory factor 5 and STAT-1. More importantly, introduction of miR-146a into the patients' PBMCs alleviated the coordinate activation of the type I IFN pathway.
Conclusion
The microRNA miR-146a is a negative regulator of the IFN pathway. Underexpression of miR-146a contributes to alterations in the type I IFN pathway in lupus patients by targeting the key signaling proteins. The findings provide potential novel strategies for therapeutic intervention.
701 citations
Massachusetts Institute of Technology1, Brigham and Women's Hospital2, Harvard University3, National Institutes of Health4, North Shore-LIJ Health System5, Karolinska Institutet6, Leiden University7, Celera Corporation8, King's College London9, University of Amsterdam10, VU University Amsterdam11, University of California, San Francisco12, University of Texas MD Anderson Cancer Center13, University of California, Davis14, University of Manchester15, Agency for Science, Technology and Research16
TL;DR: To identify rheumatoid arthritis risk loci in European populations, a meta-analysis of two published genome-wide association studies totaling 3,393 cases and 12,462 controls identified a common variant at the CD40 gene locus and identified evidence of association at four additional gene loci.
Abstract: To identify rheumatoid arthritis risk loci in European populations, we conducted a meta-analysis of two published genome-wide association (GWA) studies totaling 3,393 cases and 12,462 controls We genotyped 31 top-ranked SNPs not previously associated with rheumatoid arthritis in an independent replication of 3,929 autoantibody-positive rheumatoid arthritis cases and 5,807 matched controls from eight separate collections We identified a common variant at the CD40 gene locus (rs4810485, P = 00032 replication, P = 82 x 10(-9) overall, OR = 087) Along with other associations near TRAF1 (refs 2,3) and TNFAIP3 (refs 4,5), this implies a central role for the CD40 signaling pathway in rheumatoid arthritis pathogenesis We also identified association at the CCL21 gene locus (rs2812378, P = 000097 replication, P = 28 x 10(-7) overall), a gene involved in lymphocyte trafficking Finally, we identified evidence of association at four additional gene loci: MMEL1-TNFRSF14 (rs3890745, P = 00035 replication, P = 11 x 10(-7) overall), CDK6 (rs42041, P = 0010 replication, P = 40 x 10(-6) overall), PRKCQ (rs4750316, P = 00078 replication, P = 44 x 10(-6) overall), and KIF5A-PIP4K2C (rs1678542, P = 00026 replication, P = 88 x 10(-8) overall)
538 citations
TL;DR: This first genome scan in RA Caucasian families revealed 14 candidate regions, one of which was supported further by the study of a second set of families, and could account for 16% of the genetic component of RA.
Abstract: Rheumatoid arthritis (RA), the most common autoimmune disease, is associated in families with other autoimmune diseases, including insulin-dependent diabetes mellitus (IDDM). Its genetic component has been suggested by familial aggregation (λs = 5), twin studies, and segregation analysis. HLA, which is the only susceptibility locus known, has been estimated to account for one-third of this component. The aim of this paper was to identify new RA loci. A genome scan was performed with 114 European Caucasian RA sib pairs from 97 nuclear families. Linkage was significant only for HLA (P < 2.5⋅10−5) and nominal for 19 markers in 14 other regions (P < 0.05). Four of the loci implicated in IDDM potentially overlap with these regions: the putative IDDM6, IDDM9, IDDM13, and DXS998 loci. The first two of these candidate regions, defined in the RA genome scan by the markers D18S68-D18S61-D18S469 (18q22–23) and D3S1267 (3q13), respectively, were studied in 194 additional RA sib pairs from 164 nuclear families. Support for linkage to chromosome 3 only was extended significantly (P = 0.002). The analysis of all 261 families provided a linkage evidence of P = 0.001 and suggested an interaction between this putative RA locus and HLA. This locus could account for 16% of the genetic component of RA. Candidate genes include those coding for CD80 and CD86, molecules involved in antigen-specific T cell recognition. In conclusion, this first genome scan in RA Caucasian families revealed 14 candidate regions, one of which was supported further by the study of a second set of families.
509 citations
Cited by
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Massachusetts Institute of Technology1, Broad Institute2, University of California, Los Angeles3, University of British Columbia4, Baylor College of Medicine5, Howard Hughes Medical Institute6, University of Washington7, Ludwig Institute for Cancer Research8, University of California, San Francisco9, University of Connecticut10, University of Zagreb11, University of Texas at Austin12, Washington University in St. Louis13, University of Queensland14, Harvard University15, Cold Spring Harbor Laboratory16, University of Southern California17, University of California, Santa Cruz18, Simon Fraser University19, Morgridge Institute for Research20, University of Texas at Dallas21, National Institutes of Health22
TL;DR: It is shown that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
5,037 citations
01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
4,409 citations
TL;DR: The increased understanding of the immune mechanisms of rheumatoid arthritis has led to the development of a considerable number of new therapeutic agents that alter the natural history of the disease and reduce mortality.
Abstract: The increased understanding of the immune mechanisms of rheumatoid arthritis has led to the development of a considerable number of new therapeutic agents that alter the natural history of the disease and reduce mortality.
3,975 citations
TL;DR: It is found that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size, and the LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control.
Abstract: Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.
3,708 citations
TL;DR: This work introduces a technique—cross-trait LD Score regression—for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap, and uses this method to estimate 276 genetic correlations among 24 traits.
Abstract: Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual-level genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique-cross-trait LD Score regression-for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity, and educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.
2,993 citations