Genetic and epigenetic fine mapping of causal autoimmune disease variants

Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated the...

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Published in	Nature (London) Vol. 518; no. 7539; pp. 337 - 343
Main Authors	Farh, Kyle Kai-How, Marson, Alexander, Zhu, Jiang, Kleinewietfeld, Markus, Housley, William J., Beik, Samantha, Shoresh, Noam, Whitton, Holly, Ryan, Russell J. H., Shishkin, Alexander A., Hatan, Meital, Carrasco-Alfonso, Marlene J., Mayer, Dita, Luckey, C. John, Patsopoulos, Nikolaos A., De Jager, Philip L., Kuchroo, Vijay K., Epstein, Charles B., Daly, Mark J., Hafler, David A., Bernstein, Bradley E.
Format	Journal Article
Language	English
Published	London Nature Publishing Group UK 19.02.2015 Nature Publishing Group
Subjects	13 13/31 45 45/15 45/43 45/91 631/208/212/177 Autoimmune diseases Autoimmune Diseases - genetics Autoimmune Diseases - immunology Autoimmune Diseases - pathology Base Sequence Causes of Chromatin - genetics Chromosome mapping Consensus Sequence - genetics Cytokines Disease Enhancer Elements, Genetic - genetics Epigenesis, Genetic - genetics Epigenetic inheritance Epigenetics Epigenomics Gene expression Gene loci Genetic aspects Genome-wide association studies Genome-Wide Association Study Haplotypes Humanities and Social Sciences Humans Immune system Methods multidisciplinary Mutation Nucleotide Motifs Organ Specificity Polymorphism, Single Nucleotide - genetics Science Studies T-Lymphocytes - immunology T-Lymphocytes - metabolism Transcription factors Transcription Factors - metabolism
Online Access	Get full text
ISSN	0028-0836 1476-4687 1476-4687
DOI	10.1038/nature13835

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Abstract	Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis -regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4 + T-cell subsets, regulatory T cells, CD8 + T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10–20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models. Genome-wide association studies combined with data from epigenomic maps for immune cells have been used to fine-map causal variants for 21 autoimmune diseases; disease risk tends to be linked to single nucleotide polymorphisms in cell-type-specific enhancers, often in regions adjacent to transcription factor binding motifs. Gene variation in autoimmune diseases Hundreds of risk loci for autoimmunity have been identified previously in genome-wide association studies (GWASs), but the implicated loci comprise multiple variants in linkage disequilibrium and rarely alter protein-coding sequence, which complicates their interpretation. This study adopts a new approach for fine mapping causal genetic variants for 21 autoimmune diseases, applying a novel algorithm to GWAS-based loci and integrating genotypic data with epigenomic maps for specialized immune cells. The results implicate a very specific subset of enhancers involved in T-cell stimulation as causal determinants of autoimmune diseases.
AbstractList	Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4+ T-cell subsets, regulatory T-cells, CD8+ T-cells, B-cells, and monocytes. We find that ~90% of causal variants are noncoding, with ~60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10–20% directly alter recognizable transcription factor binding motifs. Rather, most noncoding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models. Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4(+) T-cell subsets, regulatory T cells, CD8(+) T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10-20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models.Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4(+) T-cell subsets, regulatory T cells, CD8(+) T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10-20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models. Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4^sup +^T- cell subsets, regulatory T cells, CD8^sup +^T cells, B cells, and monocytes. We find that ~90% of causal variants are non-coding, with 60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10-20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models. Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated [CD4.sup.+] T-cell subsets, regulatory T cells, [CD8.sup.+] T cells, Bcells, and monocytes. We find that ~90% of causal variants are non-coding, with ~60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10- 20% directly alter recognizable transcription factor binding motifs. Rather, mostnon-codingriskvariants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models. Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis -regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4 + T-cell subsets, regulatory T cells, CD8 + T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10–20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models. Genome-wide association studies combined with data from epigenomic maps for immune cells have been used to fine-map causal variants for 21 autoimmune diseases; disease risk tends to be linked to single nucleotide polymorphisms in cell-type-specific enhancers, often in regions adjacent to transcription factor binding motifs. Gene variation in autoimmune diseases Hundreds of risk loci for autoimmunity have been identified previously in genome-wide association studies (GWASs), but the implicated loci comprise multiple variants in linkage disequilibrium and rarely alter protein-coding sequence, which complicates their interpretation. This study adopts a new approach for fine mapping causal genetic variants for 21 autoimmune diseases, applying a novel algorithm to GWAS-based loci and integrating genotypic data with epigenomic maps for specialized immune cells. The results implicate a very specific subset of enhancers involved in T-cell stimulation as causal determinants of autoimmune diseases. Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4(+) T-cell subsets, regulatory T cells, CD8(+) T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10-20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models.
Audience	Academic
Author	Housley, William J. Whitton, Holly Kleinewietfeld, Markus Marson, Alexander Carrasco-Alfonso, Marlene J. Luckey, C. John Daly, Mark J. Hatan, Meital Epstein, Charles B. Beik, Samantha Shoresh, Noam Mayer, Dita Patsopoulos, Nikolaos A. Bernstein, Bradley E. Farh, Kyle Kai-How Shishkin, Alexander A. Kuchroo, Vijay K. Zhu, Jiang Ryan, Russell J. H. Hafler, David A. De Jager, Philip L.
AuthorAffiliation	3 Diabetes Center and Division of Infectious Diseases, Department of Medicine, University of California, San Francisco, CA 94143, USA 10 Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA 9 California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, USA 4 Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA 6 Center for Systems Biology and Center for Cancer Research, Massachusetts General Hospital, Boston, MA 02114, USA 12 Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02142, USA 5 Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA 8 Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT 06511, USA 13 Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02142, USA 2 Analytical and Translational Genetics Unit, Massachusetts Gener
AuthorAffiliation_xml	– name: 1 Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA – name: 6 Center for Systems Biology and Center for Cancer Research, Massachusetts General Hospital, Boston, MA 02114, USA – name: 8 Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT 06511, USA – name: 12 Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02142, USA – name: 13 Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02142, USA – name: 10 Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA – name: 11 Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Department of Neurology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02142, USA – name: 3 Diabetes Center and Division of Infectious Diseases, Department of Medicine, University of California, San Francisco, CA 94143, USA – name: 9 California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, USA – name: 5 Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA – name: 2 Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA – name: 4 Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
Author_xml	– sequence: 1 givenname: Kyle Kai-How surname: Farh fullname: Farh, Kyle Kai-How organization: Broad Institute of MIT and Harvard, Analytical and Translational Genetics Unit, Massachusetts General Hospital – sequence: 2 givenname: Alexander surname: Marson fullname: Marson, Alexander email: alexander.marson@ucsf.edu organization: Diabetes Center and Division of Infectious Diseases, Department of Medicine, University of California – sequence: 3 givenname: Jiang surname: Zhu fullname: Zhu, Jiang organization: Broad Institute of MIT and Harvard, Howard Hughes Medical Institute, Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Center for Systems Biology and Center for Cancer Research, Massachusetts General Hospital – sequence: 4 givenname: Markus surname: Kleinewietfeld fullname: Kleinewietfeld, Markus organization: Broad Institute of MIT and Harvard, Departments of Neurology and Immunobiology, Yale School of Medicine, Present address: Translational Immunology, Medical Faculty Carl Gustav Carus, TU Dresden, 01307 Dresden, Germany – sequence: 5 givenname: William J. surname: Housley fullname: Housley, William J. organization: Departments of Neurology and Immunobiology, Yale School of Medicine – sequence: 6 givenname: Samantha surname: Beik fullname: Beik, Samantha organization: Broad Institute of MIT and Harvard – sequence: 7 givenname: Noam surname: Shoresh fullname: Shoresh, Noam organization: Broad Institute of MIT and Harvard – sequence: 8 givenname: Holly surname: Whitton fullname: Whitton, Holly organization: Broad Institute of MIT and Harvard – sequence: 9 givenname: Russell J. H. surname: Ryan fullname: Ryan, Russell J. H. organization: Broad Institute of MIT and Harvard, Department of Pathology, Massachusetts General Hospital and Harvard Medical School – sequence: 10 givenname: Alexander A. surname: Shishkin fullname: Shishkin, Alexander A. organization: Broad Institute of MIT and Harvard, California Institute of Technology, 1200 E California Boulevard – sequence: 11 givenname: Meital surname: Hatan fullname: Hatan, Meital organization: Broad Institute of MIT and Harvard – sequence: 12 givenname: Marlene J. surname: Carrasco-Alfonso fullname: Carrasco-Alfonso, Marlene J. organization: Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School – sequence: 13 givenname: Dita surname: Mayer fullname: Mayer, Dita organization: Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School – sequence: 14 givenname: C. John surname: Luckey fullname: Luckey, C. John organization: Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School – sequence: 15 givenname: Nikolaos A. surname: Patsopoulos fullname: Patsopoulos, Nikolaos A. organization: Broad Institute of MIT and Harvard, Department of Neurology, Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Brigham and Women’s Hospital and Harvard Medical School, Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School – sequence: 16 givenname: Philip L. surname: De Jager fullname: De Jager, Philip L. organization: Broad Institute of MIT and Harvard, Department of Neurology, Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Brigham and Women’s Hospital and Harvard Medical School, Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School – sequence: 17 givenname: Vijay K. surname: Kuchroo fullname: Kuchroo, Vijay K. organization: Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School – sequence: 18 givenname: Charles B. surname: Epstein fullname: Epstein, Charles B. organization: Broad Institute of MIT and Harvard – sequence: 19 givenname: Mark J. surname: Daly fullname: Daly, Mark J. organization: Broad Institute of MIT and Harvard, Analytical and Translational Genetics Unit, Massachusetts General Hospital – sequence: 20 givenname: David A. surname: Hafler fullname: Hafler, David A. organization: Broad Institute of MIT and Harvard, Departments of Neurology and Immunobiology, Yale School of Medicine – sequence: 21 givenname: Bradley E. surname: Bernstein fullname: Bernstein, Bradley E. organization: Broad Institute of MIT and Harvard, Howard Hughes Medical Institute, Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Center for Systems Biology and Center for Cancer Research, Massachusetts General Hospital
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/25363779$$D View this record in MEDLINE/PubMed
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Copyright	Springer Nature Limited 2014 COPYRIGHT 2015 Nature Publishing Group Copyright Nature Publishing Group Feb 19, 2015
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Present Address: Translational Immunology, Medical Faculty Carl Gustav Carus, TU Dresden, 01307 Dresden, Germany Equal Contribution
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Snippet	Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here...
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SubjectTerms	13 13/31 45 45/15 45/43 45/91 631/208/212/177 Autoimmune diseases Autoimmune Diseases - genetics Autoimmune Diseases - immunology Autoimmune Diseases - pathology Base Sequence Causes of Chromatin - genetics Chromosome mapping Consensus Sequence - genetics Cytokines Disease Enhancer Elements, Genetic - genetics Epigenesis, Genetic - genetics Epigenetic inheritance Epigenetics Epigenomics Gene expression Gene loci Genetic aspects Genome-wide association studies Genome-Wide Association Study Haplotypes Humanities and Social Sciences Humans Immune system Methods multidisciplinary Mutation Nucleotide Motifs Organ Specificity Polymorphism, Single Nucleotide - genetics Science Studies T-Lymphocytes - immunology T-Lymphocytes - metabolism Transcription factors Transcription Factors - metabolism
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Title	Genetic and epigenetic fine mapping of causal autoimmune disease variants
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