2024
Weinand, Kathryn; Sakaue, Saori; Nathan, Aparna; Jonsson, Anna Helena; Zhang, Fan; Watts, Gerald F M; Suqri, Majd Al; Zhu, Zhu; ; Rao, Deepak A; Anolik, Jennifer H; Brenner, Michael B; Donlin, Laura T; Wei, Kevin; Raychaudhuri, Soumya
The chromatin landscape of pathogenic transcriptional cell states in rheumatoid arthritis Journal Article
In: Nat Commun, vol. 15, no. 1, pp. 4650, 2024, ISSN: 2041-1723.
@article{pmid38821936,
title = {The chromatin landscape of pathogenic transcriptional cell states in rheumatoid arthritis},
author = {Kathryn Weinand and Saori Sakaue and Aparna Nathan and Anna Helena Jonsson and Fan Zhang and Gerald F M Watts and Majd Al Suqri and Zhu Zhu and and Deepak A Rao and Jennifer H Anolik and Michael B Brenner and Laura T Donlin and Kevin Wei and Soumya Raychaudhuri},
doi = {10.1038/s41467-024-48620-7},
issn = {2041-1723},
year = {2024},
date = {2024-05-01},
journal = {Nat Commun},
volume = {15},
number = {1},
pages = {4650},
abstract = {Synovial tissue inflammation is a hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. Here, we examine genome-wide open chromatin at single-cell resolution in 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identify 24 chromatin classes and predict their associated transcription factors, including a CD8 + GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating with an RA tissue transcriptional atlas, we propose that these chromatin classes represent 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrate the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance, as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Synovial tissue inflammation is a hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. Here, we examine genome-wide open chromatin at single-cell resolution in 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identify 24 chromatin classes and predict their associated transcription factors, including a CD8 + GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating with an RA tissue transcriptional atlas, we propose that these chromatin classes represent 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrate the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance, as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.
Sakaue, Saori; Weinand, Kathryn; Isaac, Shakson; Dey, Kushal K; Jagadeesh, Karthik; Kanai, Masahiro; Watts, Gerald F M; Zhu, Zhu; ; Brenner, Michael B; McDavid, Andrew; Donlin, Laura T; Wei, Kevin; Price, Alkes L; Raychaudhuri, Soumya
Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles Journal Article
In: Nat Genet, vol. 56, no. 4, pp. 615–626, 2024, ISSN: 1546-1718.
@article{pmid38594305,
title = {Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles},
author = {Saori Sakaue and Kathryn Weinand and Shakson Isaac and Kushal K Dey and Karthik Jagadeesh and Masahiro Kanai and Gerald F M Watts and Zhu Zhu and and Michael B Brenner and Andrew McDavid and Laura T Donlin and Kevin Wei and Alkes L Price and Soumya Raychaudhuri},
doi = {10.1038/s41588-024-01682-1},
issn = {1546-1718},
year = {2024},
date = {2024-04-01},
journal = {Nat Genet},
volume = {56},
number = {4},
pages = {615--626},
abstract = {Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.
Lagattuta, Kaitlyn A; Park, Hannah L; Rumker, Laurie; Ishigaki, Kazuyoshi; Nathan, Aparna; Raychaudhuri, Soumya
The genetic basis of autoimmunity seen through the lens of T cell functional traits Journal Article
In: Nat Commun, vol. 15, no. 1, pp. 1204, 2024, ISSN: 2041-1723.
@article{pmid38331990,
title = {The genetic basis of autoimmunity seen through the lens of T cell functional traits},
author = {Kaitlyn A Lagattuta and Hannah L Park and Laurie Rumker and Kazuyoshi Ishigaki and Aparna Nathan and Soumya Raychaudhuri},
doi = {10.1038/s41467-024-45170-w},
issn = {2041-1723},
year = {2024},
date = {2024-02-01},
journal = {Nat Commun},
volume = {15},
number = {1},
pages = {1204},
abstract = {Autoimmune disease heritability is enriched in T cell-specific regulatory regions of the genome. Modern-day T cell datasets now enable association studies between single nucleotide polymorphisms (SNPs) and a myriad of molecular phenotypes, including chromatin accessibility, gene expression, transcriptional programs, T cell antigen receptor (TCR) amino acid usage, and cell state abundances. Such studies have identified hundreds of quantitative trait loci (QTLs) in T cells that colocalize with genetic risk for autoimmune disease. The key challenge facing immunologists today lies in synthesizing these results toward a unified understanding of the autoimmune T cell: which genes, cell states, and antigens drive tissue destruction?},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Autoimmune disease heritability is enriched in T cell-specific regulatory regions of the genome. Modern-day T cell datasets now enable association studies between single nucleotide polymorphisms (SNPs) and a myriad of molecular phenotypes, including chromatin accessibility, gene expression, transcriptional programs, T cell antigen receptor (TCR) amino acid usage, and cell state abundances. Such studies have identified hundreds of quantitative trait loci (QTLs) in T cells that colocalize with genetic risk for autoimmune disease. The key challenge facing immunologists today lies in synthesizing these results toward a unified understanding of the autoimmune T cell: which genes, cell states, and antigens drive tissue destruction?
Tegtmeyer, Matthew; Arora, Jatin; Asgari, Samira; Cimini, Beth A; Nadig, Ajay; Peirent, Emily; Liyanage, Dhara; Way, Gregory P; Weisbart, Erin; Nathan, Aparna; Amariuta, Tiffany; Eggan, Kevin; Haghighi, Marzieh; McCarroll, Steven A; O'Connor, Luke; Carpenter, Anne E; Singh, Shantanu; Nehme, Ralda; Raychaudhuri, Soumya
High-dimensional phenotyping to define the genetic basis of cellular morphology Journal Article
In: Nat Commun, vol. 15, no. 1, pp. 347, 2024, ISSN: 2041-1723.
@article{pmid38184653b,
title = {High-dimensional phenotyping to define the genetic basis of cellular morphology},
author = {Matthew Tegtmeyer and Jatin Arora and Samira Asgari and Beth A Cimini and Ajay Nadig and Emily Peirent and Dhara Liyanage and Gregory P Way and Erin Weisbart and Aparna Nathan and Tiffany Amariuta and Kevin Eggan and Marzieh Haghighi and Steven A McCarroll and Luke O'Connor and Anne E Carpenter and Shantanu Singh and Ralda Nehme and Soumya Raychaudhuri},
doi = {10.1038/s41467-023-44045-w},
issn = {2041-1723},
year = {2024},
date = {2024-01-01},
journal = {Nat Commun},
volume = {15},
number = {1},
pages = {347},
abstract = {The morphology of cells is dynamic and mediated by genetic and environmental factors. Characterizing how genetic variation impacts cell morphology can provide an important link between disease association and cellular function. Here, we combine genomic sequencing and high-content imaging approaches on iPSCs from 297 unique donors to investigate the relationship between genetic variants and cellular morphology to map what we term cell morphological quantitative trait loci (cmQTLs). We identify novel associations between rare protein altering variants in WASF2, TSPAN15, and PRLR with several morphological traits related to cell shape, nucleic granularity, and mitochondrial distribution. Knockdown of these genes by CRISPRi confirms their role in cell morphology. Analysis of common variants yields one significant association and nominate over 300 variants with suggestive evidence (P < 10) of association with one or more morphology traits. We then use these data to make predictions about sample size requirements for increasing discovery in cellular genetic studies. We conclude that, similar to molecular phenotypes, morphological profiling can yield insight about the function of genes and variants.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The morphology of cells is dynamic and mediated by genetic and environmental factors. Characterizing how genetic variation impacts cell morphology can provide an important link between disease association and cellular function. Here, we combine genomic sequencing and high-content imaging approaches on iPSCs from 297 unique donors to investigate the relationship between genetic variants and cellular morphology to map what we term cell morphological quantitative trait loci (cmQTLs). We identify novel associations between rare protein altering variants in WASF2, TSPAN15, and PRLR with several morphological traits related to cell shape, nucleic granularity, and mitochondrial distribution. Knockdown of these genes by CRISPRi confirms their role in cell morphology. Analysis of common variants yields one significant association and nominate over 300 variants with suggestive evidence (P < 10) of association with one or more morphology traits. We then use these data to make predictions about sample size requirements for increasing discovery in cellular genetic studies. We conclude that, similar to molecular phenotypes, morphological profiling can yield insight about the function of genes and variants.
2023
Kang, Joyce B; Shen, Amber Z; Gurajala, Saisriram; Nathan, Aparna; Rumker, Laurie; Aguiar, Vitor R C; Valencia, Cristian; Lagattuta, Kaitlyn A; Zhang, Fan; Jonsson, Anna Helena; Yazar, Seyhan; Alquicira-Hernandez, Jose; Khalili, Hamed; Ananthakrishnan, Ashwin N; Jagadeesh, Karthik; Dey, Kushal; ; Daly, Mark J; Xavier, Ramnik J; Donlin, Laura T; Anolik, Jennifer H; Powell, Joseph E; Rao, Deepak A; Brenner, Michael B; Gutierrez-Arcelus, Maria; Luo, Yang; Sakaue, Saori; Raychaudhuri, Soumya
Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution Journal Article
In: Nat Genet, vol. 55, no. 12, pp. 2255–2268, 2023, ISSN: 1546-1718.
@article{pmid38036787b,
title = {Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution},
author = {Joyce B Kang and Amber Z Shen and Saisriram Gurajala and Aparna Nathan and Laurie Rumker and Vitor R C Aguiar and Cristian Valencia and Kaitlyn A Lagattuta and Fan Zhang and Anna Helena Jonsson and Seyhan Yazar and Jose Alquicira-Hernandez and Hamed Khalili and Ashwin N Ananthakrishnan and Karthik Jagadeesh and Kushal Dey and and Mark J Daly and Ramnik J Xavier and Laura T Donlin and Jennifer H Anolik and Joseph E Powell and Deepak A Rao and Michael B Brenner and Maria Gutierrez-Arcelus and Yang Luo and Saori Sakaue and Soumya Raychaudhuri},
doi = {10.1038/s41588-023-01586-6},
issn = {1546-1718},
year = {2023},
date = {2023-12-01},
journal = {Nat Genet},
volume = {55},
number = {12},
pages = {2255--2268},
abstract = {The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.
Gupta, Anika; Weinand, Kathryn; Nathan, Aparna; Sakaue, Saori; Zhang, Martin Jinye; ; Donlin, Laura; Wei, Kevin; Price, Alkes L; Amariuta, Tiffany; Raychaudhuri, Soumya
Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability Journal Article
In: Nat Genet, vol. 55, no. 12, pp. 2200–2210, 2023, ISSN: 1546-1718.
@article{pmid38036783b,
title = {Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability},
author = {Anika Gupta and Kathryn Weinand and Aparna Nathan and Saori Sakaue and Martin Jinye Zhang and and Laura Donlin and Kevin Wei and Alkes L Price and Tiffany Amariuta and Soumya Raychaudhuri},
doi = {10.1038/s41588-023-01577-7},
issn = {1546-1718},
year = {2023},
date = {2023-12-01},
journal = {Nat Genet},
volume = {55},
number = {12},
pages = {2200--2210},
abstract = {In autoimmune diseases such as rheumatoid arthritis, the immune system attacks the body's own cells. Developing a precise understanding of the cell states where noncoding autoimmune risk variants impart causal mechanisms is critical to developing curative therapies. Here, to identify noncoding regions with accessible chromatin that associate with cell-state-defining gene expression patterns, we leveraged multimodal single-nucleus RNA and assay for transposase-accessible chromatin (ATAC) sequencing data across 28,674 cells from the inflamed synovial tissue of 12 donors. Specifically, we used a multivariate Poisson model to predict peak accessibility from single-nucleus RNA sequencing principal components. For 14 autoimmune diseases, we discovered that cell-state-dependent ('dynamic') chromatin accessibility peaks in immune cell types were enriched for heritability, compared with cell-state-invariant ('cs-invariant') peaks. These dynamic peaks marked regulatory elements associated with T peripheral helper, regulatory T, dendritic and STAT1CXCL10 myeloid cell states. We argue that dynamic regulatory elements can help identify precise cell states enriched for disease-critical genetic variation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In autoimmune diseases such as rheumatoid arthritis, the immune system attacks the body's own cells. Developing a precise understanding of the cell states where noncoding autoimmune risk variants impart causal mechanisms is critical to developing curative therapies. Here, to identify noncoding regions with accessible chromatin that associate with cell-state-defining gene expression patterns, we leveraged multimodal single-nucleus RNA and assay for transposase-accessible chromatin (ATAC) sequencing data across 28,674 cells from the inflamed synovial tissue of 12 donors. Specifically, we used a multivariate Poisson model to predict peak accessibility from single-nucleus RNA sequencing principal components. For 14 autoimmune diseases, we discovered that cell-state-dependent ('dynamic') chromatin accessibility peaks in immune cell types were enriched for heritability, compared with cell-state-invariant ('cs-invariant') peaks. These dynamic peaks marked regulatory elements associated with T peripheral helper, regulatory T, dendritic and STAT1CXCL10 myeloid cell states. We argue that dynamic regulatory elements can help identify precise cell states enriched for disease-critical genetic variation.
Rumker, Laurie; Sakaue, Saori; Reshef, Yakir; Kang, Joyce B; Yazar, Seyhan; Alquicira-Hernandez, Jose; Valencia, Cristian; Lagattuta, Kaitlyn A; Mah-Som, Annelise; Nathan, Aparna; Powell, Joseph E; Loh, Po-Ru; Raychaudhuri, Soumya
Identifying genetic variants that influence the abundance of cell states in single-cell data Miscellaneous
2023.
@misc{pmid38014313b,
title = {Identifying genetic variants that influence the abundance of cell states in single-cell data},
author = {Laurie Rumker and Saori Sakaue and Yakir Reshef and Joyce B Kang and Seyhan Yazar and Jose Alquicira-Hernandez and Cristian Valencia and Kaitlyn A Lagattuta and Annelise Mah-Som and Aparna Nathan and Joseph E Powell and Po-Ru Loh and Soumya Raychaudhuri},
doi = {10.1101/2023.11.13.566919},
year = {2023},
date = {2023-11-01},
journal = {bioRxiv},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Zhang, Fan; Jonsson, Anna Helena; Nathan, Aparna; Millard, Nghia; Curtis, Michelle; Xiao, Qian; Gutierrez-Arcelus, Maria; Apruzzese, William; Watts, Gerald F M; Weisenfeld, Dana; Nayar, Saba; Rangel-Moreno, Javier; Meednu, Nida; Marks, Kathryne E; Mantel, Ian; Kang, Joyce B; Rumker, Laurie; Mears, Joseph; Slowikowski, Kamil; Weinand, Kathryn; Orange, Dana E; Geraldino-Pardilla, Laura; Deane, Kevin D; Tabechian, Darren; Ceponis, Arnoldas; Firestein, Gary S; Maybury, Mark; Sahbudin, Ilfita; Ben-Artzi, Ami; Mandelin, Arthur M; Nerviani, Alessandra; Lewis, Myles J; Rivellese, Felice; Pitzalis, Costantino; Hughes, Laura B; Horowitz, Diane; DiCarlo, Edward; Gravallese, Ellen M; Boyce, Brendan F; ; Moreland, Larry W; Goodman, Susan M; Perlman, Harris; Holers, V Michael; Liao, Katherine P; Filer, Andrew; Bykerk, Vivian P; Wei, Kevin; Rao, Deepak A; Donlin, Laura T; Anolik, Jennifer H; Brenner, Michael B; Raychaudhuri, Soumya
Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes Journal Article
In: Nature, vol. 623, no. 7987, pp. 616–624, 2023, ISSN: 1476-4687.
@article{pmid37938773b,
title = {Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes},
author = {Fan Zhang and Anna Helena Jonsson and Aparna Nathan and Nghia Millard and Michelle Curtis and Qian Xiao and Maria Gutierrez-Arcelus and William Apruzzese and Gerald F M Watts and Dana Weisenfeld and Saba Nayar and Javier Rangel-Moreno and Nida Meednu and Kathryne E Marks and Ian Mantel and Joyce B Kang and Laurie Rumker and Joseph Mears and Kamil Slowikowski and Kathryn Weinand and Dana E Orange and Laura Geraldino-Pardilla and Kevin D Deane and Darren Tabechian and Arnoldas Ceponis and Gary S Firestein and Mark Maybury and Ilfita Sahbudin and Ami Ben-Artzi and Arthur M Mandelin and Alessandra Nerviani and Myles J Lewis and Felice Rivellese and Costantino Pitzalis and Laura B Hughes and Diane Horowitz and Edward DiCarlo and Ellen M Gravallese and Brendan F Boyce and and Larry W Moreland and Susan M Goodman and Harris Perlman and V Michael Holers and Katherine P Liao and Andrew Filer and Vivian P Bykerk and Kevin Wei and Deepak A Rao and Laura T Donlin and Jennifer H Anolik and Michael B Brenner and Soumya Raychaudhuri},
doi = {10.1038/s41586-023-06708-y},
issn = {1476-4687},
year = {2023},
date = {2023-11-01},
journal = {Nature},
volume = {623},
number = {7987},
pages = {616--624},
abstract = {Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments.
Xiao, Qian; Mears, Joseph; Nathan, Aparna; Ishigaki, Kazuyoshi; Baglaenko, Yuriy; Lim, Noha; Cooney, Laura A; Harris, Kristina M; Anderson, Mark S; Fox, David A; Smilek, Dawn E; Krueger, James G; Raychaudhuri, Soumya
Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin Journal Article
In: Nat Commun, vol. 14, no. 1, pp. 6268, 2023, ISSN: 2041-1723.
@article{pmid37805522b,
title = {Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin},
author = {Qian Xiao and Joseph Mears and Aparna Nathan and Kazuyoshi Ishigaki and Yuriy Baglaenko and Noha Lim and Laura A Cooney and Kristina M Harris and Mark S Anderson and David A Fox and Dawn E Smilek and James G Krueger and Soumya Raychaudhuri},
doi = {10.1038/s41467-023-41984-2},
issn = {2041-1723},
year = {2023},
date = {2023-10-01},
journal = {Nat Commun},
volume = {14},
number = {1},
pages = {6268},
abstract = {Psoriasis is a chronic, systemic inflammatory condition primarily affecting skin. While the role of the immune compartment (e.g., T cells) is well established, the changes in the skin compartment are more poorly understood. Using longitudinal skin biopsies (n = 375) from the "Psoriasis Treatment with Abatacept and Ustekinumab: A Study of Efficacy"(PAUSE) clinical trial (n = 101), we report 953 expression quantitative trait loci (eQTLs). Of those, 116 eQTLs have effect sizes that were modulated by local skin inflammation (eQTL interactions). By examining these eQTL genes (eGenes), we find that most are expressed in the skin tissue compartment, and a subset overlap with the NRF2 pathway. Indeed, the strongest eQTL interaction signal - rs1491377616-LCE3C - links a psoriasis risk locus with a gene specifically expressed in the epidermis. This eQTL study highlights the potential to use biospecimens from clinical trials to discover in vivo eQTL interactions with therapeutically relevant environmental variables.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Psoriasis is a chronic, systemic inflammatory condition primarily affecting skin. While the role of the immune compartment (e.g., T cells) is well established, the changes in the skin compartment are more poorly understood. Using longitudinal skin biopsies (n = 375) from the "Psoriasis Treatment with Abatacept and Ustekinumab: A Study of Efficacy"(PAUSE) clinical trial (n = 101), we report 953 expression quantitative trait loci (eQTLs). Of those, 116 eQTLs have effect sizes that were modulated by local skin inflammation (eQTL interactions). By examining these eQTL genes (eGenes), we find that most are expressed in the skin tissue compartment, and a subset overlap with the NRF2 pathway. Indeed, the strongest eQTL interaction signal - rs1491377616-LCE3C - links a psoriasis risk locus with a gene specifically expressed in the epidermis. This eQTL study highlights the potential to use biospecimens from clinical trials to discover in vivo eQTL interactions with therapeutically relevant environmental variables.
Sakaue, Saori; Gurajala, Saisriram; Curtis, Michelle; Luo, Yang; Choi, Wanson; Ishigaki, Kazuyoshi; Kang, Joyce B; Rumker, Laurie; Deutsch, Aaron J; Schönherr, Sebastian; Forer, Lukas; LeFaive, Jonathon; Fuchsberger, Christian; Han, Buhm; Lenz, Tobias L; de Bakker, Paul I W; Okada, Yukinori; Smith, Albert V; Raychaudhuri, Soumya
Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease Journal Article
In: Nat Protoc, vol. 18, no. 9, pp. 2625–2641, 2023, ISSN: 1750-2799.
@article{pmid37495751b,
title = {Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease},
author = {Saori Sakaue and Saisriram Gurajala and Michelle Curtis and Yang Luo and Wanson Choi and Kazuyoshi Ishigaki and Joyce B Kang and Laurie Rumker and Aaron J Deutsch and Sebastian Schönherr and Lukas Forer and Jonathon LeFaive and Christian Fuchsberger and Buhm Han and Tobias L Lenz and Paul I W de Bakker and Yukinori Okada and Albert V Smith and Soumya Raychaudhuri},
doi = {10.1038/s41596-023-00853-4},
issn = {1750-2799},
year = {2023},
date = {2023-09-01},
journal = {Nat Protoc},
volume = {18},
number = {9},
pages = {2625--2641},
abstract = {The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software ( https://github.com/immunogenomics/HLA_analyses_tutorial ). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software ( https://github.com/immunogenomics/HLA_analyses_tutorial ). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.
Lagattuta, Kaitlyn A; Nathan, Aparna; Rumker, Laurie; Birnbaum, Michael E; Raychaudhuri, Soumya
The T cell receptor sequence influences the likelihood of T cell memory formation Miscellaneous
2023.
@misc{pmid37502994b,
title = {The T cell receptor sequence influences the likelihood of T cell memory formation},
author = {Kaitlyn A Lagattuta and Aparna Nathan and Laurie Rumker and Michael E Birnbaum and Soumya Raychaudhuri},
doi = {10.1101/2023.07.20.549939},
year = {2023},
date = {2023-07-01},
journal = {bioRxiv},
abstract = {T cell differentiation depends on activation through the T cell receptor (TCR), whose amino acid sequence varies cell to cell. Particular TCR amino acid sequences nearly guarantee Mucosal-Associated Invariant T (MAIT) and Natural Killer T (NKT) cell fates. To comprehensively define how TCR amino acids affects all T cell fates, we analyze the paired αβTCR sequence and transcriptome of 819,772 single cells. We find that hydrophobic CDR3 residues promote regulatory T cell transcriptional states in both the CD8 and CD4 lineages. Most strikingly, we find a set of TCR sequence features, concentrated in CDR2α, that promotes positive selection in the thymus as well as transition from naïve to memory in the periphery. Even among T cells that recognize the same antigen, these TCR sequence features help to explain which T cells form immunological memory, which is essential for effective pathogen response.},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
T cell differentiation depends on activation through the T cell receptor (TCR), whose amino acid sequence varies cell to cell. Particular TCR amino acid sequences nearly guarantee Mucosal-Associated Invariant T (MAIT) and Natural Killer T (NKT) cell fates. To comprehensively define how TCR amino acids affects all T cell fates, we analyze the paired αβTCR sequence and transcriptome of 819,772 single cells. We find that hydrophobic CDR3 residues promote regulatory T cell transcriptional states in both the CD8 and CD4 lineages. Most strikingly, we find a set of TCR sequence features, concentrated in CDR2α, that promotes positive selection in the thymus as well as transition from naïve to memory in the periphery. Even among T cells that recognize the same antigen, these TCR sequence features help to explain which T cells form immunological memory, which is essential for effective pathogen response.
Weinand, Kathryn; Sakaue, Saori; Nathan, Aparna; Jonsson, Anna Helena; Zhang, Fan; Watts, Gerald F M; Zhu, Zhu; ; Rao, Deepak A; Anolik, Jennifer H; Brenner, Michael B; Donlin, Laura T; Wei, Kevin; Raychaudhuri, Soumya
The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis Miscellaneous
2023.
@misc{pmid37066336b,
title = {The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis},
author = {Kathryn Weinand and Saori Sakaue and Aparna Nathan and Anna Helena Jonsson and Fan Zhang and Gerald F M Watts and Zhu Zhu and and Deepak A Rao and Jennifer H Anolik and Michael B Brenner and Laura T Donlin and Kevin Wei and Soumya Raychaudhuri},
doi = {10.1101/2023.04.07.536026},
year = {2023},
date = {2023-04-01},
journal = {bioRxiv},
abstract = {Synovial tissue inflammation is the hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identified 24 chromatin classes and predicted their associated transcription factors, including a + + class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating an RA tissue transcriptional atlas, we found that the chromatin classes represented 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrated the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Synovial tissue inflammation is the hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identified 24 chromatin classes and predicted their associated transcription factors, including a + + class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating an RA tissue transcriptional atlas, we found that the chromatin classes represented 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrated the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.
Weinand, Kathryn; Sakaue, Saori; Nathan, Aparna; Jonsson, Anna Helena; Zhang, Fan; Watts, Gerald F M; Zhu, Zhu; ; Rao, Deepak A; Anolik, Jennifer H; Brenner, Michael B; Donlin, Laura T; Wei, Kevin; Raychaudhuri, Soumya
The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis Miscellaneous
2023.
@misc{pmid37066336,
title = {The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis},
author = {Kathryn Weinand and Saori Sakaue and Aparna Nathan and Anna Helena Jonsson and Fan Zhang and Gerald F M Watts and Zhu Zhu and and Deepak A Rao and Jennifer H Anolik and Michael B Brenner and Laura T Donlin and Kevin Wei and Soumya Raychaudhuri},
doi = {10.1101/2023.04.07.536026},
year = {2023},
date = {2023-04-01},
journal = {bioRxiv},
abstract = {Synovial tissue inflammation is the hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identified 24 chromatin classes and predicted their associated transcription factors, including a + + class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating an RA tissue transcriptional atlas, we found that the chromatin classes represented 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrated the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Synovial tissue inflammation is the hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. We measured genome-wide open chromatin at single cell resolution from 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identified 24 chromatin classes and predicted their associated transcription factors, including a + + class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating an RA tissue transcriptional atlas, we found that the chromatin classes represented 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrated the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.
2022
Ishigaki, Kazuyoshi; Sakaue, Saori; Terao, Chikashi; Luo, Yang; Sonehara, Kyuto; Yamaguchi, Kensuke; Amariuta, Tiffany; Too, Chun Lai; Laufer, Vincent A; Scott, Ian C; Viatte, Sebastien; Takahashi, Meiko; Ohmura, Koichiro; Murasawa, Akira; Hashimoto, Motomu; Ito, Hiromu; Hammoudeh, Mohammed; Emadi, Samar Al; Masri, Basel K; Halabi, Hussein; Badsha, Humeira; Uthman, Imad W; Wu, Xin; Lin, Li; Li, Ting; Plant, Darren; Barton, Anne; Orozco, Gisela; Verstappen, Suzanne M M; Bowes, John; MacGregor, Alexander J; Honda, Suguru; Koido, Masaru; Tomizuka, Kohei; Kamatani, Yoichiro; Tanaka, Hiroaki; Tanaka, Eiichi; Suzuki, Akari; Maeda, Yuichi; Yamamoto, Kenichi; Miyawaki, Satoru; Xie, Gang; Zhang, Jinyi; Amos, Christopher I; Keystone, Edward; Wolbink, Gertjan; van der Horst-Bruinsma, Irene; Cui, Jing; Liao, Katherine P; Carroll, Robert J; Lee, Hye-Soon; Bang, So-Young; Siminovitch, Katherine A; de Vries, Niek; Alfredsson, Lars; Rantapää-Dahlqvist, Solbritt; Karlson, Elizabeth W; Bae, Sang-Cheol; Kimberly, Robert P; Edberg, Jeffrey C; Mariette, Xavier; Huizinga, Tom; Dieudé, Philippe; Schneider, Matthias; Kerick, Martin; Denny, Joshua C; ; Matsuda, Koichi; Matsuo, Keitaro; Mimori, Tsuneyo; Matsuda, Fumihiko; Fujio, Keishi; Tanaka, Yoshiya; Kumanogoh, Atsushi; Traylor, Matthew; Lewis, Cathryn M; Eyre, Stephen; Xu, Huji; Saxena, Richa; Arayssi, Thurayya; Kochi, Yuta; Ikari, Katsunori; Harigai, Masayoshi; Gregersen, Peter K; Yamamoto, Kazuhiko; Bridges, S Louis; Padyukov, Leonid; Martin, Javier; Klareskog, Lars; Okada, Yukinori; Raychaudhuri, Soumya
Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis Journal Article
In: Nat Genet, vol. 54, no. 11, pp. 1640–1651, 2022, ISSN: 1546-1718.
@article{pmid36333501b,
title = {Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis},
author = {Kazuyoshi Ishigaki and Saori Sakaue and Chikashi Terao and Yang Luo and Kyuto Sonehara and Kensuke Yamaguchi and Tiffany Amariuta and Chun Lai Too and Vincent A Laufer and Ian C Scott and Sebastien Viatte and Meiko Takahashi and Koichiro Ohmura and Akira Murasawa and Motomu Hashimoto and Hiromu Ito and Mohammed Hammoudeh and Samar Al Emadi and Basel K Masri and Hussein Halabi and Humeira Badsha and Imad W Uthman and Xin Wu and Li Lin and Ting Li and Darren Plant and Anne Barton and Gisela Orozco and Suzanne M M Verstappen and John Bowes and Alexander J MacGregor and Suguru Honda and Masaru Koido and Kohei Tomizuka and Yoichiro Kamatani and Hiroaki Tanaka and Eiichi Tanaka and Akari Suzuki and Yuichi Maeda and Kenichi Yamamoto and Satoru Miyawaki and Gang Xie and Jinyi Zhang and Christopher I Amos and Edward Keystone and Gertjan Wolbink and Irene van der Horst-Bruinsma and Jing Cui and Katherine P Liao and Robert J Carroll and Hye-Soon Lee and So-Young Bang and Katherine A Siminovitch and Niek de Vries and Lars Alfredsson and Solbritt Rantapää-Dahlqvist and Elizabeth W Karlson and Sang-Cheol Bae and Robert P Kimberly and Jeffrey C Edberg and Xavier Mariette and Tom Huizinga and Philippe Dieudé and Matthias Schneider and Martin Kerick and Joshua C Denny and and Koichi Matsuda and Keitaro Matsuo and Tsuneyo Mimori and Fumihiko Matsuda and Keishi Fujio and Yoshiya Tanaka and Atsushi Kumanogoh and Matthew Traylor and Cathryn M Lewis and Stephen Eyre and Huji Xu and Richa Saxena and Thurayya Arayssi and Yuta Kochi and Katsunori Ikari and Masayoshi Harigai and Peter K Gregersen and Kazuhiko Yamamoto and S Louis Bridges and Leonid Padyukov and Javier Martin and Lars Klareskog and Yukinori Okada and Soumya Raychaudhuri},
doi = {10.1038/s41588-022-01213-w},
issn = {1546-1718},
year = {2022},
date = {2022-11-01},
journal = {Nat Genet},
volume = {54},
number = {11},
pages = {1640--1651},
abstract = {Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.
Korsunsky, Ilya; Wei, Kevin; Pohin, Mathilde; Kim, Edy Y; Barone, Francesca; Major, Triin; Taylor, Emily; Ravindran, Rahul; Kemble, Samuel; Watts, Gerald F M; Jonsson, A Helena; Jeong, Yunju; Athar, Humra; Windell, Dylan; Kang, Joyce B; Friedrich, Matthias; Turner, Jason; Nayar, Saba; Fisher, Benjamin A; Raza, Karim; Marshall, Jennifer L; Croft, Adam P; Tamura, Tomoyoshi; Sholl, Lynette M; Vivero, Marina; Rosas, Ivan O; Bowman, Simon J; Coles, Mark; Frei, Andreas P; Lassen, Kara; Filer, Andrew; Powrie, Fiona; Buckley, Christopher D; Brenner, Michael B; Raychaudhuri, Soumya
Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases Journal Article
In: Med, vol. 3, no. 7, pp. 481–518.e14, 2022, ISSN: 2666-6340.
@article{pmid35649411,
title = {Cross-tissue, single-cell stromal atlas identifies shared pathological fibroblast phenotypes in four chronic inflammatory diseases},
author = {Ilya Korsunsky and Kevin Wei and Mathilde Pohin and Edy Y Kim and Francesca Barone and Triin Major and Emily Taylor and Rahul Ravindran and Samuel Kemble and Gerald F M Watts and A Helena Jonsson and Yunju Jeong and Humra Athar and Dylan Windell and Joyce B Kang and Matthias Friedrich and Jason Turner and Saba Nayar and Benjamin A Fisher and Karim Raza and Jennifer L Marshall and Adam P Croft and Tomoyoshi Tamura and Lynette M Sholl and Marina Vivero and Ivan O Rosas and Simon J Bowman and Mark Coles and Andreas P Frei and Kara Lassen and Andrew Filer and Fiona Powrie and Christopher D Buckley and Michael B Brenner and Soumya Raychaudhuri},
doi = {10.1016/j.medj.2022.05.002},
issn = {2666-6340},
year = {2022},
date = {2022-07-01},
journal = {Med},
volume = {3},
number = {7},
pages = {481--518.e14},
abstract = {BACKGROUND: Pro-inflammatory fibroblasts are critical for pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjögren's syndrome and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited our understanding of which pathways are shared by multiple diseases.nnMETHODS: We profiled fibroblasts derived from inflamed and non-inflamed synovium, intestine, lungs, and salivary glands from affected individuals with single-cell RNA sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes.nnFINDINGS: Two shared clusters, CXCL10CCL19 immune-interacting and SPARCCOL3A1 vascular-interacting fibroblasts, were expanded in all inflamed tissues and mapped to dermal analogs in a public atopic dermatitis atlas. We confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation.nnCONCLUSIONS: This work represents a thorough investigation into fibroblasts across organ systems, individual donors, and disease states that reveals shared pathogenic activation states across four chronic inflammatory diseases.nnFUNDING: Grant from F. Hoffmann-La Roche (Roche) AG.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Pro-inflammatory fibroblasts are critical for pathogenesis in rheumatoid arthritis, inflammatory bowel disease, interstitial lung disease, and Sjögren's syndrome and represent a novel therapeutic target for chronic inflammatory disease. However, the heterogeneity of fibroblast phenotypes, exacerbated by the lack of a common cross-tissue taxonomy, has limited our understanding of which pathways are shared by multiple diseases.nnMETHODS: We profiled fibroblasts derived from inflamed and non-inflamed synovium, intestine, lungs, and salivary glands from affected individuals with single-cell RNA sequencing. We integrated all fibroblasts into a multi-tissue atlas to characterize shared and tissue-specific phenotypes.nnFINDINGS: Two shared clusters, CXCL10CCL19 immune-interacting and SPARCCOL3A1 vascular-interacting fibroblasts, were expanded in all inflamed tissues and mapped to dermal analogs in a public atopic dermatitis atlas. We confirmed these human pro-inflammatory fibroblasts in animal models of lung, joint, and intestinal inflammation.nnCONCLUSIONS: This work represents a thorough investigation into fibroblasts across organ systems, individual donors, and disease states that reveals shared pathogenic activation states across four chronic inflammatory diseases.nnFUNDING: Grant from F. Hoffmann-La Roche (Roche) AG.
Asgari, Samira; Luo, Yang; Huang, Chuan-Chin; Zhang, Zibiao; Calderon, Roger; Jimenez, Judith; Yataco, Rosa; Contreras, Carmen; Galea, Jerome T; Lecca, Leonid; Jones, David; Moody, D Branch; Murray, Megan B; Raychaudhuri, Soumya
Higher native Peruvian genetic ancestry proportion is associated with tuberculosis progression risk Journal Article
In: Cell Genom, vol. 2, no. 7, 2022, ISSN: 2666-979X.
@article{pmid35873671,
title = {Higher native Peruvian genetic ancestry proportion is associated with tuberculosis progression risk},
author = {Samira Asgari and Yang Luo and Chuan-Chin Huang and Zibiao Zhang and Roger Calderon and Judith Jimenez and Rosa Yataco and Carmen Contreras and Jerome T Galea and Leonid Lecca and David Jones and D Branch Moody and Megan B Murray and Soumya Raychaudhuri},
doi = {10.1016/j.xgen.2022.100151},
issn = {2666-979X},
year = {2022},
date = {2022-07-01},
journal = {Cell Genom},
volume = {2},
number = {7},
abstract = {We investigated whether ancestry-specific genetic factors affect tuberculosis (TB) progression risk in a cohort of admixed Peruvians. We genotyped 2,105 patients with TB and 1,320 household contacts (HHCs) who were infected with () but did not develop TB and inferred each individual's proportion of native Peruvian genetic ancestry. Our HHC study design and our data on potential confounders allowed us to demonstrate increased risk independent of socioeconomic factors. A 10% increase in individual-level native Peruvian genetic ancestry proportion corresponded to a 25% increased TB progression risk. This corresponds to a 3-fold increased risk for individuals in the highest decile of native Peruvian genetic ancestry versus the lowest decile, making native Peruvian genetic ancestry comparable in effect to clinical factors such as diabetes. Our results suggest that genetic ancestry is a major contributor to TB progression risk and highlight the value of including diverse populations in host genetic studies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We investigated whether ancestry-specific genetic factors affect tuberculosis (TB) progression risk in a cohort of admixed Peruvians. We genotyped 2,105 patients with TB and 1,320 household contacts (HHCs) who were infected with () but did not develop TB and inferred each individual's proportion of native Peruvian genetic ancestry. Our HHC study design and our data on potential confounders allowed us to demonstrate increased risk independent of socioeconomic factors. A 10% increase in individual-level native Peruvian genetic ancestry proportion corresponded to a 25% increased TB progression risk. This corresponds to a 3-fold increased risk for individuals in the highest decile of native Peruvian genetic ancestry versus the lowest decile, making native Peruvian genetic ancestry comparable in effect to clinical factors such as diabetes. Our results suggest that genetic ancestry is a major contributor to TB progression risk and highlight the value of including diverse populations in host genetic studies.
Nathan, Aparna; Asgari, Samira; Ishigaki, Kazuyoshi; Valencia, Cristian; Amariuta, Tiffany; Luo, Yang; Beynor, Jessica I; Baglaenko, Yuriy; Suliman, Sara; Price, Alkes L; Lecca, Leonid; Murray, Megan B; Moody, D Branch; Raychaudhuri, Soumya
Single-cell eQTL models reveal dynamic T cell state dependence of disease loci Journal Article
In: Nature, vol. 606, no. 7912, pp. 120–128, 2022, ISSN: 1476-4687.
@article{pmid35545678,
title = {Single-cell eQTL models reveal dynamic T cell state dependence of disease loci},
author = {Aparna Nathan and Samira Asgari and Kazuyoshi Ishigaki and Cristian Valencia and Tiffany Amariuta and Yang Luo and Jessica I Beynor and Yuriy Baglaenko and Sara Suliman and Alkes L Price and Leonid Lecca and Megan B Murray and D Branch Moody and Soumya Raychaudhuri},
doi = {10.1038/s41586-022-04713-1},
issn = {1476-4687},
year = {2022},
date = {2022-06-01},
journal = {Nature},
volume = {606},
number = {7912},
pages = {120--128},
abstract = {Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by differences in gene regulation across fluid functional cell states within cell types. These states-for example, neurotransmitter-driven programs in astrocytes or perivascular fibroblast differentiation-are obscured in eQTL studies that aggregate cells. Here we modelled eQTLs at single-cell resolution in one complex cell type: memory T cells. Using more than 500,000 unstimulated memory T cells from 259 Peruvian individuals, we show that around one-third of 6,511 cis-eQTLs had effects that were mediated by continuous multimodally defined cell states, such as cytotoxicity and regulatory capacity. In some loci, independent eQTL variants had opposing cell-state relationships. Autoimmune variants were enriched in cell-state-dependent eQTLs, including risk variants for rheumatoid arthritis near ORMDL3 and CTLA4; this indicates that cell-state context is crucial to understanding potential eQTL pathogenicity. Moreover, continuous cell states explained more variation in eQTLs than did conventional discrete categories, such as CD4 versus CD8, suggesting that modelling eQTLs and cell states at single-cell resolution can expand insight into gene regulation in functionally heterogeneous cell types.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Non-coding genetic variants may cause disease by modulating gene expression. However, identifying these expression quantitative trait loci (eQTLs) is complicated by differences in gene regulation across fluid functional cell states within cell types. These states-for example, neurotransmitter-driven programs in astrocytes or perivascular fibroblast differentiation-are obscured in eQTL studies that aggregate cells. Here we modelled eQTLs at single-cell resolution in one complex cell type: memory T cells. Using more than 500,000 unstimulated memory T cells from 259 Peruvian individuals, we show that around one-third of 6,511 cis-eQTLs had effects that were mediated by continuous multimodally defined cell states, such as cytotoxicity and regulatory capacity. In some loci, independent eQTL variants had opposing cell-state relationships. Autoimmune variants were enriched in cell-state-dependent eQTLs, including risk variants for rheumatoid arthritis near ORMDL3 and CTLA4; this indicates that cell-state context is crucial to understanding potential eQTL pathogenicity. Moreover, continuous cell states explained more variation in eQTLs than did conventional discrete categories, such as CD4 versus CD8, suggesting that modelling eQTLs and cell states at single-cell resolution can expand insight into gene regulation in functionally heterogeneous cell types.
Fava, Andrea; Rao, Deepak A; Mohan, Chandra; Zhang, Ting; Rosenberg, Avi; Fenaroli, Paride; Belmont, H Michael; Izmirly, Peter; Clancy, Robert; Trujillo, Jose Monroy; Fine, Derek; Arazi, Arnon; Berthier, Celine C; Davidson, Anne; James, Judith A; Diamond, Betty; Hacohen, Nir; Wofsy, David; Raychaudhuri, Soumya; Apruzzese, William; ; Buyon, Jill; Petri, Michelle
Urine Proteomics and Renal Single-Cell Transcriptomics Implicate Interleukin-16 in Lupus Nephritis Journal Article
In: Arthritis Rheumatol, vol. 74, no. 5, pp. 829–839, 2022, ISSN: 2326-5205.
@article{pmid34783463,
title = {Urine Proteomics and Renal Single-Cell Transcriptomics Implicate Interleukin-16 in Lupus Nephritis},
author = {Andrea Fava and Deepak A Rao and Chandra Mohan and Ting Zhang and Avi Rosenberg and Paride Fenaroli and H Michael Belmont and Peter Izmirly and Robert Clancy and Jose Monroy Trujillo and Derek Fine and Arnon Arazi and Celine C Berthier and Anne Davidson and Judith A James and Betty Diamond and Nir Hacohen and David Wofsy and Soumya Raychaudhuri and William Apruzzese and and Jill Buyon and Michelle Petri},
doi = {10.1002/art.42023},
issn = {2326-5205},
year = {2022},
date = {2022-05-01},
journal = {Arthritis Rheumatol},
volume = {74},
number = {5},
pages = {829--839},
abstract = {OBJECTIVE: Current lupus nephritis (LN) treatments are effective in only 30% of patients, emphasizing the need for novel therapeutic strategies. We undertook this study to develop mechanistic hypotheses and explore novel biomarkers by analyzing the longitudinal urinary proteomic profiles in LN patients undergoing treatment.nnMETHODS: We quantified 1,000 urinary proteins in 30 patients with LN at the time of the diagnostic renal biopsy and after 3, 6, and 12 months. The proteins and molecular pathways detected in the urine proteome were then analyzed with respect to baseline clinical features and longitudinal trajectories. The intrarenal expression of candidate biomarkers was evaluated using single-cell transcriptomics of renal biopsy sections from LN patients.nnRESULTS: Our analysis revealed multiple biologic pathways, including chemotaxis, neutrophil activation, platelet degranulation, and extracellular matrix organization, which could be noninvasively quantified and monitored in the urine. We identified 237 urinary biomarkers associated with LN, as compared to controls without systemic lupus erythematosus. Interleukin-16 (IL-16), CD163, and transforming growth factor β mirrored intrarenal nephritis activity. Response to treatment was paralleled by a reduction in urinary IL-16, a CD4 ligand with proinflammatory and chemotactic properties. Single-cell RNA sequencing independently demonstrated that IL16 is the second most expressed cytokine by most infiltrating immune cells in LN kidneys. IL-16-producing cells were found at key sites of kidney injury.nnCONCLUSION: Urine proteomics may profoundly change the diagnosis and management of LN by noninvasively monitoring active intrarenal biologic pathways. These findings implicate IL-16 in LN pathogenesis, designating it as a potentially treatable target and biomarker.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVE: Current lupus nephritis (LN) treatments are effective in only 30% of patients, emphasizing the need for novel therapeutic strategies. We undertook this study to develop mechanistic hypotheses and explore novel biomarkers by analyzing the longitudinal urinary proteomic profiles in LN patients undergoing treatment.nnMETHODS: We quantified 1,000 urinary proteins in 30 patients with LN at the time of the diagnostic renal biopsy and after 3, 6, and 12 months. The proteins and molecular pathways detected in the urine proteome were then analyzed with respect to baseline clinical features and longitudinal trajectories. The intrarenal expression of candidate biomarkers was evaluated using single-cell transcriptomics of renal biopsy sections from LN patients.nnRESULTS: Our analysis revealed multiple biologic pathways, including chemotaxis, neutrophil activation, platelet degranulation, and extracellular matrix organization, which could be noninvasively quantified and monitored in the urine. We identified 237 urinary biomarkers associated with LN, as compared to controls without systemic lupus erythematosus. Interleukin-16 (IL-16), CD163, and transforming growth factor β mirrored intrarenal nephritis activity. Response to treatment was paralleled by a reduction in urinary IL-16, a CD4 ligand with proinflammatory and chemotactic properties. Single-cell RNA sequencing independently demonstrated that IL16 is the second most expressed cytokine by most infiltrating immune cells in LN kidneys. IL-16-producing cells were found at key sites of kidney injury.nnCONCLUSION: Urine proteomics may profoundly change the diagnosis and management of LN by noninvasively monitoring active intrarenal biologic pathways. These findings implicate IL-16 in LN pathogenesis, designating it as a potentially treatable target and biomarker.
Mysore, Vijayashree; Tahir, Suhail; Furuhashi, Kazuhiro; Arora, Jatin; Rosetti, Florencia; Cullere, Xavier; Yazbeck, Pascal; Sekulic, Miroslav; Lemieux, Madeleine E; Raychaudhuri, Soumya; Horwitz, Bruce H; Mayadas, Tanya N
Monocytes transition to macrophages within the inflamed vasculature via monocyte CCR2 and endothelial TNFR2 Journal Article
In: J Exp Med, vol. 219, no. 5, 2022, ISSN: 1540-9538.
@article{pmid35404389,
title = {Monocytes transition to macrophages within the inflamed vasculature via monocyte CCR2 and endothelial TNFR2},
author = {Vijayashree Mysore and Suhail Tahir and Kazuhiro Furuhashi and Jatin Arora and Florencia Rosetti and Xavier Cullere and Pascal Yazbeck and Miroslav Sekulic and Madeleine E Lemieux and Soumya Raychaudhuri and Bruce H Horwitz and Tanya N Mayadas},
doi = {10.1084/jem.20210562},
issn = {1540-9538},
year = {2022},
date = {2022-05-01},
journal = {J Exp Med},
volume = {219},
number = {5},
abstract = {Monocytes undergo phenotypic and functional changes in response to inflammatory cues, but the molecular signals that drive different monocyte states remain largely undefined. We show that monocytes acquire macrophage markers upon glomerulonephritis and may be derived from CCR2+CX3CR1+ double-positive monocytes, which are preferentially recruited, dwell within glomerular capillaries, and acquire proinflammatory characteristics in the nephritic kidney. Mechanistically, the transition to immature macrophages begins within the vasculature and relies on CCR2 in circulating cells and TNFR2 in parenchymal cells, findings that are recapitulated in vitro with monocytes cocultured with TNF-TNFR2-activated endothelial cells generating CCR2 ligands. Single-cell RNA sequencing of cocultures defines a CCR2-dependent monocyte differentiation path associated with the acquisition of immune effector functions and generation of CCR2 ligands. Immature macrophages are detected in the urine of lupus nephritis patients, and their frequency correlates with clinical disease. In conclusion, CCR2-dependent functional specialization of monocytes into macrophages begins within the TNF-TNFR2-activated vasculature and may establish a CCR2-based autocrine, feed-forward loop that amplifies renal inflammation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Monocytes undergo phenotypic and functional changes in response to inflammatory cues, but the molecular signals that drive different monocyte states remain largely undefined. We show that monocytes acquire macrophage markers upon glomerulonephritis and may be derived from CCR2+CX3CR1+ double-positive monocytes, which are preferentially recruited, dwell within glomerular capillaries, and acquire proinflammatory characteristics in the nephritic kidney. Mechanistically, the transition to immature macrophages begins within the vasculature and relies on CCR2 in circulating cells and TNFR2 in parenchymal cells, findings that are recapitulated in vitro with monocytes cocultured with TNF-TNFR2-activated endothelial cells generating CCR2 ligands. Single-cell RNA sequencing of cocultures defines a CCR2-dependent monocyte differentiation path associated with the acquisition of immune effector functions and generation of CCR2 ligands. Immature macrophages are detected in the urine of lupus nephritis patients, and their frequency correlates with clinical disease. In conclusion, CCR2-dependent functional specialization of monocytes into macrophages begins within the TNF-TNFR2-activated vasculature and may establish a CCR2-based autocrine, feed-forward loop that amplifies renal inflammation.
Ishigaki, Kazuyoshi; Lagattuta, Kaitlyn A; Luo, Yang; James, Eddie A; Buckner, Jane H; Raychaudhuri, Soumya
HLA autoimmune risk alleles restrict the hypervariable region of T cell receptors Journal Article
In: Nat Genet, vol. 54, no. 4, pp. 393–402, 2022, ISSN: 1546-1718.
@article{pmid35332318,
title = {HLA autoimmune risk alleles restrict the hypervariable region of T cell receptors},
author = {Kazuyoshi Ishigaki and Kaitlyn A Lagattuta and Yang Luo and Eddie A James and Jane H Buckner and Soumya Raychaudhuri},
doi = {10.1038/s41588-022-01032-z},
issn = {1546-1718},
year = {2022},
date = {2022-04-01},
journal = {Nat Genet},
volume = {54},
number = {4},
pages = {393--402},
abstract = {Polymorphisms in the human leukocyte antigen (HLA) genes strongly influence autoimmune disease risk. HLA risk alleles may influence thymic selection to increase the frequency of T cell receptors (TCRs) reactive to autoantigens (central hypothesis). However, research in human autoimmunity has provided little evidence supporting the central hypothesis. Here we investigated the influence of HLA alleles on TCR composition at the highly diverse complementarity determining region 3 (CDR3), which confers antigen recognition. We observed unexpectedly strong HLA-CDR3 associations. The strongest association was found at HLA-DRB1 amino acid position 13, the position that mediates genetic risk for multiple autoimmune diseases. We identified multiple CDR3 amino acid features enriched by HLA risk alleles. Moreover, the CDR3 features promoted by the HLA risk alleles are more enriched in candidate pathogenic TCRs than control TCRs (for example, citrullinated epitope-specific TCRs in patients with rheumatoid arthritis). Together, these results provide genetic evidence supporting the central hypothesis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Polymorphisms in the human leukocyte antigen (HLA) genes strongly influence autoimmune disease risk. HLA risk alleles may influence thymic selection to increase the frequency of T cell receptors (TCRs) reactive to autoantigens (central hypothesis). However, research in human autoimmunity has provided little evidence supporting the central hypothesis. Here we investigated the influence of HLA alleles on TCR composition at the highly diverse complementarity determining region 3 (CDR3), which confers antigen recognition. We observed unexpectedly strong HLA-CDR3 associations. The strongest association was found at HLA-DRB1 amino acid position 13, the position that mediates genetic risk for multiple autoimmune diseases. We identified multiple CDR3 amino acid features enriched by HLA risk alleles. Moreover, the CDR3 features promoted by the HLA risk alleles are more enriched in candidate pathogenic TCRs than control TCRs (for example, citrullinated epitope-specific TCRs in patients with rheumatoid arthritis). Together, these results provide genetic evidence supporting the central hypothesis.
Guan, Steven; Mehta, Bella; Slater, David; Thompson, James R; DiCarlo, Edward; Pannellini, Tania; Pearce-Fisher, Diyu; Zhang, Fan; Raychaudhuri, Soumya; Hale, Caryn; Jiang, Caroline S; Goodman, Susan; Orange, Dana E
Rheumatoid Arthritis Synovial Inflammation Quantification Using Computer Vision Journal Article
In: ACR Open Rheumatol, vol. 4, no. 4, pp. 322–331, 2022, ISSN: 2578-5745.
@article{pmid35014221,
title = {Rheumatoid Arthritis Synovial Inflammation Quantification Using Computer Vision},
author = {Steven Guan and Bella Mehta and David Slater and James R Thompson and Edward DiCarlo and Tania Pannellini and Diyu Pearce-Fisher and Fan Zhang and Soumya Raychaudhuri and Caryn Hale and Caroline S Jiang and Susan Goodman and Dana E Orange},
doi = {10.1002/acr2.11381},
issn = {2578-5745},
year = {2022},
date = {2022-04-01},
journal = {ACR Open Rheumatol},
volume = {4},
number = {4},
pages = {322--331},
abstract = {OBJECTIVE: We quantified inflammatory burden in rheumatoid arthritis (RA) synovial tissue by using computer vision to automate the process of counting individual nuclei in hematoxylin and eosin images.nnMETHODS: We adapted and applied computer vision algorithms to quantify nuclei density (count of nuclei per unit area of tissue) on synovial tissue from arthroplasty samples. A pathologist validated algorithm results by labeling nuclei in synovial images that were mislabeled or missed by the algorithm. Nuclei density was compared with other measures of RA inflammation such as semiquantitative histology scores, gene-expression data, and clinical measures of disease activity.nnRESULTS: The algorithm detected a median of 112,657 (range 8,160-821,717) nuclei per synovial sample. Based on pathologist-validated results, the sensitivity and specificity of the algorithm was 97% and 100%, respectively. The mean nuclei density calculated by the algorithm was significantly higher (P < 0.05) in synovium with increased histology scores for lymphocytic inflammation, plasma cells, and lining hyperplasia. Analysis of RNA sequencing identified 915 significantly differentially expressed genes in correlation with nuclei density (false discovery rate is less than 0.05). Mean nuclei density was significantly higher (P < 0.05) in patients with elevated levels of C-reactive protein, erythrocyte sedimentation rate, rheumatoid factor, and cyclized citrullinated protein antibody.nnCONCLUSION: Nuclei density is a robust measurement of inflammatory burden in RA and correlates with multiple orthogonal measurements of inflammation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVE: We quantified inflammatory burden in rheumatoid arthritis (RA) synovial tissue by using computer vision to automate the process of counting individual nuclei in hematoxylin and eosin images.nnMETHODS: We adapted and applied computer vision algorithms to quantify nuclei density (count of nuclei per unit area of tissue) on synovial tissue from arthroplasty samples. A pathologist validated algorithm results by labeling nuclei in synovial images that were mislabeled or missed by the algorithm. Nuclei density was compared with other measures of RA inflammation such as semiquantitative histology scores, gene-expression data, and clinical measures of disease activity.nnRESULTS: The algorithm detected a median of 112,657 (range 8,160-821,717) nuclei per synovial sample. Based on pathologist-validated results, the sensitivity and specificity of the algorithm was 97% and 100%, respectively. The mean nuclei density calculated by the algorithm was significantly higher (P < 0.05) in synovium with increased histology scores for lymphocytic inflammation, plasma cells, and lining hyperplasia. Analysis of RNA sequencing identified 915 significantly differentially expressed genes in correlation with nuclei density (false discovery rate is less than 0.05). Mean nuclei density was significantly higher (P < 0.05) in patients with elevated levels of C-reactive protein, erythrocyte sedimentation rate, rheumatoid factor, and cyclized citrullinated protein antibody.nnCONCLUSION: Nuclei density is a robust measurement of inflammatory burden in RA and correlates with multiple orthogonal measurements of inflammation.
Maurits, Marc P; Korsunsky, Ilya; Raychaudhuri, Soumya; Murphy, Shawn N; Smoller, Jordan W; Weiss, Scott T; Huizinga, Thomas W J; Reinders, Marcel J T; Karlson, Elizabeth W; van den Akker, Erik B; Knevel, Rachel
In: J Am Med Inform Assoc, vol. 29, no. 5, pp. 761–769, 2022, ISSN: 1527-974X.
@article{pmid35139533,
title = {A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history},
author = {Marc P Maurits and Ilya Korsunsky and Soumya Raychaudhuri and Shawn N Murphy and Jordan W Smoller and Scott T Weiss and Thomas W J Huizinga and Marcel J T Reinders and Elizabeth W Karlson and Erik B van den Akker and Rachel Knevel},
doi = {10.1093/jamia/ocac008},
issn = {1527-974X},
year = {2022},
date = {2022-04-01},
journal = {J Am Med Inform Assoc},
volume = {29},
number = {5},
pages = {761--769},
abstract = {OBJECTIVE: To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects.nnMATERIAL AND METHODS: We used 1872 billing codes in EHRs of 102 880 patients from 12 healthcare systems. Using tools borrowed from single-cell omics, we mitigated center-specific batch effects and performed clustering to identify patients with highly similar medical history patterns across the various centers. Our visualization method (PheSpec) depicts the phenotypic profile of clusters, applies a novel filtering of noninformative codes (Ranked Scope Pervasion), and indicates the most distinguishing features.nnRESULTS: We observed 114 clinically meaningful profiles, for example, linking prostate hyperplasia with cancer and diabetes with cardiovascular problems and grouping pediatric developmental disorders. Our framework identified disease subsets, exemplified by 6 "other headache" clusters, where phenotypic profiles suggested different underlying mechanisms: migraine, convulsion, injury, eye problems, joint pain, and pituitary gland disorders. Phenotypic patterns replicated well, with high correlations of ≥0.75 to an average of 6 (2-8) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles.nnDISCUSSION: Costly clinical research ventures should be based on solid hypotheses. We repurpose methods from single-cell omics to build these hypotheses from observational EHR data, distilling useful information from complex data.nnCONCLUSION: We establish a generalizable pipeline for the identification and replication of clinically meaningful (sub)phenotypes from widely available high-dimensional billing codes. This approach overcomes datatype problems and produces comprehensive visualizations of validation-ready phenotypes.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
OBJECTIVE: To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects.nnMATERIAL AND METHODS: We used 1872 billing codes in EHRs of 102 880 patients from 12 healthcare systems. Using tools borrowed from single-cell omics, we mitigated center-specific batch effects and performed clustering to identify patients with highly similar medical history patterns across the various centers. Our visualization method (PheSpec) depicts the phenotypic profile of clusters, applies a novel filtering of noninformative codes (Ranked Scope Pervasion), and indicates the most distinguishing features.nnRESULTS: We observed 114 clinically meaningful profiles, for example, linking prostate hyperplasia with cancer and diabetes with cardiovascular problems and grouping pediatric developmental disorders. Our framework identified disease subsets, exemplified by 6 "other headache" clusters, where phenotypic profiles suggested different underlying mechanisms: migraine, convulsion, injury, eye problems, joint pain, and pituitary gland disorders. Phenotypic patterns replicated well, with high correlations of ≥0.75 to an average of 6 (2-8) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles.nnDISCUSSION: Costly clinical research ventures should be based on solid hypotheses. We repurpose methods from single-cell omics to build these hypotheses from observational EHR data, distilling useful information from complex data.nnCONCLUSION: We establish a generalizable pipeline for the identification and replication of clinically meaningful (sub)phenotypes from widely available high-dimensional billing codes. This approach overcomes datatype problems and produces comprehensive visualizations of validation-ready phenotypes.
Lagattuta, Kaitlyn A; Kang, Joyce B; Nathan, Aparna; Pauken, Kristen E; Jonsson, Anna Helena; Rao, Deepak A; Sharpe, Arlene H; Ishigaki, Kazuyoshi; Raychaudhuri, Soumya
Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate Journal Article
In: Nat Immunol, vol. 23, no. 3, pp. 446–457, 2022, ISSN: 1529-2916.
@article{pmid35177831,
title = {Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate},
author = {Kaitlyn A Lagattuta and Joyce B Kang and Aparna Nathan and Kristen E Pauken and Anna Helena Jonsson and Deepak A Rao and Arlene H Sharpe and Kazuyoshi Ishigaki and Soumya Raychaudhuri},
doi = {10.1038/s41590-022-01129-x},
issn = {1529-2916},
year = {2022},
date = {2022-03-01},
journal = {Nat Immunol},
volume = {23},
number = {3},
pages = {446--457},
abstract = {T cells acquire a regulatory phenotype when their T cell antigen receptors (TCRs) experience an intermediate- to high-affinity interaction with a self-peptide presented via the major histocompatibility complex (MHC). Using TCRβ sequences from flow-sorted human cells, we identified TCR features that promote regulatory T cell (T) fate. From these results, we developed a scoring system to quantify TCR-intrinsic regulatory potential (TiRP). When applied to the tumor microenvironment, TiRP scoring helped to explain why only some T cell clones maintained the conventional T cell (T) phenotype through expansion. To elucidate drivers of these predictive TCR features, we then examined the two elements of the T TCR ligand separately: the self-peptide and the human MHC class II molecule. These analyses revealed that hydrophobicity in the third complementarity-determining region (CDR3β) of the TCR promotes reactivity to self-peptides, while TCR variable gene (TRBV gene) usage shapes the TCR's general propensity for human MHC class II-restricted activation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
T cells acquire a regulatory phenotype when their T cell antigen receptors (TCRs) experience an intermediate- to high-affinity interaction with a self-peptide presented via the major histocompatibility complex (MHC). Using TCRβ sequences from flow-sorted human cells, we identified TCR features that promote regulatory T cell (T) fate. From these results, we developed a scoring system to quantify TCR-intrinsic regulatory potential (TiRP). When applied to the tumor microenvironment, TiRP scoring helped to explain why only some T cell clones maintained the conventional T cell (T) phenotype through expansion. To elucidate drivers of these predictive TCR features, we then examined the two elements of the T TCR ligand separately: the self-peptide and the human MHC class II molecule. These analyses revealed that hydrophobicity in the third complementarity-determining region (CDR3β) of the TCR promotes reactivity to self-peptides, while TCR variable gene (TRBV gene) usage shapes the TCR's general propensity for human MHC class II-restricted activation.
Pauken, Kristen E; Lagattuta, Kaitlyn A; Lu, Benjamin Y; Lucca, Liliana E; Daud, Adil I; Hafler, David A; Kluger, Harriet M; Raychaudhuri, Soumya; Sharpe, Arlene H
TCR-sequencing in cancer and autoimmunity: barcodes and beyond Journal Article
In: Trends Immunol, vol. 43, no. 3, pp. 180–194, 2022, ISSN: 1471-4981.
@article{pmid35090787,
title = {TCR-sequencing in cancer and autoimmunity: barcodes and beyond},
author = {Kristen E Pauken and Kaitlyn A Lagattuta and Benjamin Y Lu and Liliana E Lucca and Adil I Daud and David A Hafler and Harriet M Kluger and Soumya Raychaudhuri and Arlene H Sharpe},
doi = {10.1016/j.it.2022.01.002},
issn = {1471-4981},
year = {2022},
date = {2022-03-01},
journal = {Trends Immunol},
volume = {43},
number = {3},
pages = {180--194},
abstract = {The T cell receptor (TCR) endows T cells with antigen specificity and is central to nearly all aspects of T cell function. Each naïve T cell has a unique TCR sequence that is stably maintained during cell division. In this way, the TCR serves as a molecular barcode that tracks processes such as migration, differentiation, and proliferation of T cells. Recent technological advances have enabled sequencing of the TCR from single cells alongside deep molecular phenotypes on an unprecedented scale. In this review, we discuss strengths and limitations of TCR sequences as molecular barcodes and their application to study immune responses following Programmed Death-1 (PD-1) blockade in cancer. Additionally, we consider applications of TCR data beyond use as a barcode.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The T cell receptor (TCR) endows T cells with antigen specificity and is central to nearly all aspects of T cell function. Each naïve T cell has a unique TCR sequence that is stably maintained during cell division. In this way, the TCR serves as a molecular barcode that tracks processes such as migration, differentiation, and proliferation of T cells. Recent technological advances have enabled sequencing of the TCR from single cells alongside deep molecular phenotypes on an unprecedented scale. In this review, we discuss strengths and limitations of TCR sequences as molecular barcodes and their application to study immune responses following Programmed Death-1 (PD-1) blockade in cancer. Additionally, we consider applications of TCR data beyond use as a barcode.
Reshef, Yakir A; Rumker, Laurie; Kang, Joyce B; Nathan, Aparna; Korsunsky, Ilya; Asgari, Samira; Murray, Megan B; Moody, D Branch; Raychaudhuri, Soumya
Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics Journal Article
In: Nat Biotechnol, vol. 40, no. 3, pp. 355–363, 2022, ISSN: 1546-1696.
@article{pmid34675423,
title = {Co-varying neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics},
author = {Yakir A Reshef and Laurie Rumker and Joyce B Kang and Aparna Nathan and Ilya Korsunsky and Samira Asgari and Megan B Murray and D Branch Moody and Soumya Raychaudhuri},
doi = {10.1038/s41587-021-01066-4},
issn = {1546-1696},
year = {2022},
date = {2022-03-01},
journal = {Nat Biotechnol},
volume = {40},
number = {3},
pages = {355--363},
abstract = {As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes, such as clinical phenotypes. Current statistical approaches typically map cells to clusters and then assess differences in cluster abundance. Here we present co-varying neighborhood analysis (CNA), an unbiased method to identify associated cell populations with greater flexibility than cluster-based approaches. CNA characterizes dominant axes of variation across samples by identifying groups of small regions in transcriptional space-termed neighborhoods-that co-vary in abundance across samples, suggesting shared function or regulation. CNA performs statistical testing for associations between any sample-level attribute and the abundances of these co-varying neighborhood groups. Simulations show that CNA enables more sensitive and accurate identification of disease-associated cell states than a cluster-based approach. When applied to published datasets, CNA captures a Notch activation signature in rheumatoid arthritis, identifies monocyte populations expanded in sepsis and identifies a novel T cell population associated with progression to active tuberculosis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As single-cell datasets grow in sample size, there is a critical need to characterize cell states that vary across samples and associate with sample attributes, such as clinical phenotypes. Current statistical approaches typically map cells to clusters and then assess differences in cluster abundance. Here we present co-varying neighborhood analysis (CNA), an unbiased method to identify associated cell populations with greater flexibility than cluster-based approaches. CNA characterizes dominant axes of variation across samples by identifying groups of small regions in transcriptional space-termed neighborhoods-that co-vary in abundance across samples, suggesting shared function or regulation. CNA performs statistical testing for associations between any sample-level attribute and the abundances of these co-varying neighborhood groups. Simulations show that CNA enables more sensitive and accurate identification of disease-associated cell states than a cluster-based approach. When applied to published datasets, CNA captures a Notch activation signature in rheumatoid arthritis, identifies monocyte populations expanded in sepsis and identifies a novel T cell population associated with progression to active tuberculosis.
Lopez, Begoña G C; Kohale, Ishwar N; Du, Ziming; Korsunsky, Ilya; Abdelmoula, Walid M; Dai, Yang; Stopka, Sylwia A; Gaglia, Giorgio; Randall, Elizabeth C; Regan, Michael S; Basu, Sankha S; Clark, Amanda R; Marin, Bianca-Maria; Mladek, Ann C; Burgenske, Danielle M; Agar, Jeffrey N; Supko, Jeffrey G; Grossman, Stuart A; Nabors, Louis B; Raychaudhuri, Soumya; Ligon, Keith L; Wen, Patrick Y; Alexander, Brian; Lee, Eudocia Q; Santagata, Sandro; Sarkaria, Jann; White, Forest M; Agar, Nathalie Y R
Multimodal platform for assessing drug distribution and response in clinical trials Journal Article
In: Neuro Oncol, vol. 24, no. 1, pp. 64–77, 2022, ISSN: 1523-5866.
@article{pmid34383057,
title = {Multimodal platform for assessing drug distribution and response in clinical trials},
author = {Begoña G C Lopez and Ishwar N Kohale and Ziming Du and Ilya Korsunsky and Walid M Abdelmoula and Yang Dai and Sylwia A Stopka and Giorgio Gaglia and Elizabeth C Randall and Michael S Regan and Sankha S Basu and Amanda R Clark and Bianca-Maria Marin and Ann C Mladek and Danielle M Burgenske and Jeffrey N Agar and Jeffrey G Supko and Stuart A Grossman and Louis B Nabors and Soumya Raychaudhuri and Keith L Ligon and Patrick Y Wen and Brian Alexander and Eudocia Q Lee and Sandro Santagata and Jann Sarkaria and Forest M White and Nathalie Y R Agar},
doi = {10.1093/neuonc/noab197},
issn = {1523-5866},
year = {2022},
date = {2022-01-01},
journal = {Neuro Oncol},
volume = {24},
number = {1},
pages = {64--77},
abstract = {BACKGROUND: Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy.nnMETHODS: Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial.nnRESULTS: PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient's response to adavosertib.nnCONCLUSIONS: The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
BACKGROUND: Response to targeted therapy varies between patients for largely unknown reasons. Here, we developed and applied an integrative platform using mass spectrometry imaging (MSI), phosphoproteomics, and multiplexed tissue imaging for mapping drug distribution, target engagement, and adaptive response to gain insights into heterogeneous response to therapy.nnMETHODS: Patient-derived xenograft (PDX) lines of glioblastoma were treated with adavosertib, a Wee1 inhibitor, and tissue drug distribution was measured with MALDI-MSI. Phosphoproteomics was measured in the same tumors to identify biomarkers of drug target engagement and cellular adaptive response. Multiplexed tissue imaging was performed on sister sections to evaluate spatial co-localization of drug and cellular response. The integrated platform was then applied on clinical specimens from glioblastoma patients enrolled in the phase 1 clinical trial.nnRESULTS: PDX tumors exposed to different doses of adavosertib revealed intra- and inter-tumoral heterogeneity of drug distribution and integration of the heterogeneous drug distribution with phosphoproteomics and multiplexed tissue imaging revealed new markers of molecular response to adavosertib. Analysis of paired clinical specimens from patients enrolled in the phase 1 clinical trial informed the translational potential of the identified biomarkers in studying patient's response to adavosertib.nnCONCLUSIONS: The multimodal platform identified a signature of drug efficacy and patient-specific adaptive responses applicable to preclinical and clinical drug development. The information generated by the approach may inform mechanisms of success and failure in future early phase clinical trials, providing information for optimizing clinical trial design and guiding future application into clinical practice.
2021
Kang, Joyce B.; Nathan, Aparna; Weinand, Kathryn; Zhang, Fan; Millard, Nghia; Rumker, Laurie; Moody, D. Branch; Korsunsky, Ilya; Raychaudhuri, Soumya
Efficient and precise single-cell reference atlas mapping with Symphony Journal Article
In: Nat Commun, vol. 12, no. 1, 2021, ISSN: 2041-1723.
@article{Kang2021,
title = {Efficient and precise single-cell reference atlas mapping with Symphony},
author = {Joyce B. Kang and Aparna Nathan and Kathryn Weinand and Fan Zhang and Nghia Millard and Laurie Rumker and D. Branch Moody and Ilya Korsunsky and Soumya Raychaudhuri},
doi = {10.1038/s41467-021-25957-x},
issn = {2041-1723},
year = {2021},
date = {2021-12-00},
journal = {Nat Commun},
volume = {12},
number = {1},
publisher = {Springer Science and Business Media LLC},
abstract = {Abstract Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony (https://github.com/immunogenomics/symphony ), an algorithm for building large-scale, integrated reference atlases in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony in multiple real-world datasets, including (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Kang, Joyce B.; Nathan, Aparna; Weinand, Kathryn; Zhang, Fan; Millard, Nghia; Rumker, Laurie; Moody, D. Branch; Korsunsky, Ilya; Raychaudhuri, Soumya
Efficient and precise single-cell reference atlas mapping with Symphony Journal Article
In: Nat Commun, vol. 12, no. 1, 2021, ISSN: 2041-1723.
@article{Kang2021b,
title = {Efficient and precise single-cell reference atlas mapping with Symphony},
author = {Joyce B. Kang and Aparna Nathan and Kathryn Weinand and Fan Zhang and Nghia Millard and Laurie Rumker and D. Branch Moody and Ilya Korsunsky and Soumya Raychaudhuri},
doi = {10.1038/s41467-021-25957-x},
issn = {2041-1723},
year = {2021},
date = {2021-12-00},
journal = {Nat Commun},
volume = {12},
number = {1},
publisher = {Springer Science and Business Media LLC},
abstract = {Abstract Recent advances in single-cell technologies and integration algorithms make it possible to construct comprehensive reference atlases encompassing many donors, studies, disease states, and sequencing platforms. Much like mapping sequencing reads to a reference genome, it is essential to be able to map query cells onto complex, multimillion-cell reference atlases to rapidly identify relevant cell states and phenotypes. We present Symphony (https://github.com/immunogenomics/symphony ), an algorithm for building large-scale, integrated reference atlases in a convenient, portable format that enables efficient query mapping within seconds. Symphony localizes query cells within a stable low-dimensional reference embedding, facilitating reproducible downstream transfer of reference-defined annotations to the query. We demonstrate the power of Symphony in multiple real-world datasets, including (1) mapping a multi-donor, multi-species query to predict pancreatic cell types, (2) localizing query cells along a developmental trajectory of fetal liver hematopoiesis, and (3) inferring surface protein expression with a multimodal CITE-seq atlas of memory T cells. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Choi, Wanson; Luo, Yang; Raychaudhuri, Soumya; Han, Buhm
HATK: HLA analysis toolkit Journal Article
In: vol. 37, no. 3, pp. 416–418, 2021, ISSN: 1367-4811.
@article{Choi2020,
title = {HATK: HLA analysis toolkit},
author = {Wanson Choi and Yang Luo and Soumya Raychaudhuri and Buhm Han},
editor = {Alfonso Valencia},
doi = {10.1093/bioinformatics/btaa684},
issn = {1367-4811},
year = {2021},
date = {2021-04-20},
volume = {37},
number = {3},
pages = {416--418},
publisher = {Oxford University Press (OUP)},
abstract = {Abstract
Summary
Fine-mapping human leukocyte antigen (HLA) genes involved in disease susceptibility to individual alleles or amino acid residues has been challenging. Using information regarding HLA alleles obtained from HLA typing, HLA imputation or HLA inference, our software expands the alleles to amino acid sequences using the most recent IMGT/HLA database and prepares a dataset suitable for fine-mapping analysis. Our software also provides useful functionalities, such as various association tests, visualization tools and nomenclature conversion.
Availability and implementation
https://github.com/WansonChoi/HATK.
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Choi, Wanson; Luo, Yang; Raychaudhuri, Soumya; Han, Buhm
HATK: HLA analysis toolkit Journal Article
In: vol. 37, no. 3, pp. 416–418, 2021, ISSN: 1367-4811.
@article{Choi2020b,
title = {HATK: HLA analysis toolkit},
author = {Wanson Choi and Yang Luo and Soumya Raychaudhuri and Buhm Han},
editor = {Alfonso Valencia},
doi = {10.1093/bioinformatics/btaa684},
issn = {1367-4811},
year = {2021},
date = {2021-04-20},
volume = {37},
number = {3},
pages = {416--418},
publisher = {Oxford University Press (OUP)},
abstract = {Abstract
Summary
Fine-mapping human leukocyte antigen (HLA) genes involved in disease susceptibility to individual alleles or amino acid residues has been challenging. Using information regarding HLA alleles obtained from HLA typing, HLA imputation or HLA inference, our software expands the alleles to amino acid sequences using the most recent IMGT/HLA database and prepares a dataset suitable for fine-mapping analysis. Our software also provides useful functionalities, such as various association tests, visualization tools and nomenclature conversion.
Availability and implementation
https://github.com/WansonChoi/HATK.
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Shoop-Worrall, Stephanie J W; Hyrich, Kimme L; Wedderburn, Lucy R; Thomson, Wendy; Geifman, Nophar; Baildam, Eileen; Barnes, Michael; Beresford, Michael W; Carlsson, Emil; Chieng, Alice; Ciurtin, Coziana; Cleary, Gavin; Davidson, Joyce; Dekaj, Fatjon; Dews, Sally-Anne; Dick, Andrew; Diogo, Gil Reynolds; Duerr, Teresa; Fairlie, Joanna; Foster, Helen; Gritzfeld, Jenna F; Ioannou, Yiannis; Jebson, Beth; Kartawinata, Melissa; Kent, Toby; Kimonyo, Aline; Lawson-Tovey, Saskia; Lin, Wei-Yu; Martin, Paul; McErlane, Flora; Merali, Fatema; Morris, Andrew; Neale, Helen; Neisen, Jessica; Ng, Sandra; Ralph, Elizabeth; Ramanan, Athimalaipet V; Raychaudhuri, Soumya; Robinson, Emily; Smith, Samantha; Sumner, Emma; Tarasek, Damian; Wallace, Chris; Wanstall, Zoe; Yarwood, Annie
In: The Lancet Rheumatology, vol. 3, no. 2, pp. e111–e121, 2021, ISSN: 2665-9913.
@article{Shoop-Worrall2021,
title = {Patient-reported wellbeing and clinical disease measures over time captured by multivariate trajectories of disease activity in individuals with juvenile idiopathic arthritis in the UK: a multicentre prospective longitudinal study},
author = {Stephanie J W Shoop-Worrall and Kimme L Hyrich and Lucy R Wedderburn and Wendy Thomson and Nophar Geifman and Eileen Baildam and Michael Barnes and Michael W Beresford and Emil Carlsson and Alice Chieng and Coziana Ciurtin and Gavin Cleary and Joyce Davidson and Fatjon Dekaj and Sally-Anne Dews and Andrew Dick and Gil Reynolds Diogo and Teresa Duerr and Joanna Fairlie and Helen Foster and Jenna F Gritzfeld and Yiannis Ioannou and Beth Jebson and Melissa Kartawinata and Toby Kent and Aline Kimonyo and Saskia Lawson-Tovey and Wei-Yu Lin and Paul Martin and Flora McErlane and Fatema Merali and Andrew Morris and Helen Neale and Jessica Neisen and Sandra Ng and Elizabeth Ralph and Athimalaipet V Ramanan and Soumya Raychaudhuri and Emily Robinson and Samantha Smith and Emma Sumner and Damian Tarasek and Chris Wallace and Zoe Wanstall and Annie Yarwood},
doi = {10.1016/s2665-9913(20)30269-1},
issn = {2665-9913},
year = {2021},
date = {2021-02-00},
journal = {The Lancet Rheumatology},
volume = {3},
number = {2},
pages = {e111--e121},
publisher = {Elsevier BV},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Shoop-Worrall, Stephanie J W; Hyrich, Kimme L; Wedderburn, Lucy R; Thomson, Wendy; Geifman, Nophar; Baildam, Eileen; Barnes, Michael; Beresford, Michael W; Carlsson, Emil; Chieng, Alice; Ciurtin, Coziana; Cleary, Gavin; Davidson, Joyce; Dekaj, Fatjon; Dews, Sally-Anne; Dick, Andrew; Diogo, Gil Reynolds; Duerr, Teresa; Fairlie, Joanna; Foster, Helen; Gritzfeld, Jenna F; Ioannou, Yiannis; Jebson, Beth; Kartawinata, Melissa; Kent, Toby; Kimonyo, Aline; Lawson-Tovey, Saskia; Lin, Wei-Yu; Martin, Paul; McErlane, Flora; Merali, Fatema; Morris, Andrew; Neale, Helen; Neisen, Jessica; Ng, Sandra; Ralph, Elizabeth; Ramanan, Athimalaipet V; Raychaudhuri, Soumya; Robinson, Emily; Smith, Samantha; Sumner, Emma; Tarasek, Damian; Wallace, Chris; Wanstall, Zoe; Yarwood, Annie
In: The Lancet Rheumatology, vol. 3, no. 2, pp. e111–e121, 2021, ISSN: 2665-9913.
@article{Shoop-Worrall2021b,
title = {Patient-reported wellbeing and clinical disease measures over time captured by multivariate trajectories of disease activity in individuals with juvenile idiopathic arthritis in the UK: a multicentre prospective longitudinal study},
author = {Stephanie J W Shoop-Worrall and Kimme L Hyrich and Lucy R Wedderburn and Wendy Thomson and Nophar Geifman and Eileen Baildam and Michael Barnes and Michael W Beresford and Emil Carlsson and Alice Chieng and Coziana Ciurtin and Gavin Cleary and Joyce Davidson and Fatjon Dekaj and Sally-Anne Dews and Andrew Dick and Gil Reynolds Diogo and Teresa Duerr and Joanna Fairlie and Helen Foster and Jenna F Gritzfeld and Yiannis Ioannou and Beth Jebson and Melissa Kartawinata and Toby Kent and Aline Kimonyo and Saskia Lawson-Tovey and Wei-Yu Lin and Paul Martin and Flora McErlane and Fatema Merali and Andrew Morris and Helen Neale and Jessica Neisen and Sandra Ng and Elizabeth Ralph and Athimalaipet V Ramanan and Soumya Raychaudhuri and Emily Robinson and Samantha Smith and Emma Sumner and Damian Tarasek and Chris Wallace and Zoe Wanstall and Annie Yarwood},
doi = {10.1016/s2665-9913(20)30269-1},
issn = {2665-9913},
year = {2021},
date = {2021-02-00},
journal = {The Lancet Rheumatology},
volume = {3},
number = {2},
pages = {e111--e121},
publisher = {Elsevier BV},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Bonfá, Eloisa; Gossec, Laure; Isenberg, David A; Li, Zhanguo; Raychaudhuri, Soumya
How COVID-19 is changing rheumatology clinical practice Journal Article
In: Nat Rev Rheumatol, vol. 17, no. 1, pp. 11–15, 2021, ISSN: 1759-4804.
@article{pmid33139947,
title = {How COVID-19 is changing rheumatology clinical practice},
author = {Eloisa Bonfá and Laure Gossec and David A Isenberg and Zhanguo Li and Soumya Raychaudhuri},
doi = {10.1038/s41584-020-00527-5},
issn = {1759-4804},
year = {2021},
date = {2021-01-01},
journal = {Nat Rev Rheumatol},
volume = {17},
number = {1},
pages = {11--15},
abstract = {The emergence of COVID-19 in early 2020 led to unprecedented changes to rheumatology clinical practice worldwide, including the closure of research laboratories, the restructuring of hospitals and the rapid transition to virtual care. As governments sought to slow and contain the spread of the disease, rheumatologists were presented with the difficult task of managing risks, to their patients as well as to themselves, while learning and implementing new systems for remote health care. Consequently, the COVID-19 pandemic led to a transformation in health infrastructures and telemedicine that could become powerful tools for rheumatologists, despite having some limitations. In this Viewpoint, five experts from different regions discuss their experiences of the pandemic, including the most challenging aspects of this unexpected transition, the advantages and limitations of virtual visits, and potential opportunities going forward.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The emergence of COVID-19 in early 2020 led to unprecedented changes to rheumatology clinical practice worldwide, including the closure of research laboratories, the restructuring of hospitals and the rapid transition to virtual care. As governments sought to slow and contain the spread of the disease, rheumatologists were presented with the difficult task of managing risks, to their patients as well as to themselves, while learning and implementing new systems for remote health care. Consequently, the COVID-19 pandemic led to a transformation in health infrastructures and telemedicine that could become powerful tools for rheumatologists, despite having some limitations. In this Viewpoint, five experts from different regions discuss their experiences of the pandemic, including the most challenging aspects of this unexpected transition, the advantages and limitations of virtual visits, and potential opportunities going forward.
Khan, Atlas; Shang, Ning; Petukhova, Lynn; Zhang, Jun; Shen, Yufeng; Hebbring, Scott J.; Moncrieffe, Halima; Kottyan, Leah C.; Namjou-Khales, Bahram; Knevel, Rachel; Raychaudhuri, Soumya; Karlson, Elizabeth W.; Harley, John B.; Stanaway, Ian B.; Crosslin, David; Denny, Joshua C.; Elkind, Mitchell S. V.; Gharavi, Ali G.; Hripcsak, George; Weng, Chunhua; Kiryluk, Krzysztof
Medical Records-Based Genetic Studies of the Complement System Journal Article
In: JASN, vol. 32, no. 8, pp. 2031–2047, 2021, ISSN: 1533-3450.
@article{Khan2021,
title = {Medical Records-Based Genetic Studies of the Complement System},
author = {Atlas Khan and Ning Shang and Lynn Petukhova and Jun Zhang and Yufeng Shen and Scott J. Hebbring and Halima Moncrieffe and Leah C. Kottyan and Bahram Namjou-Khales and Rachel Knevel and Soumya Raychaudhuri and Elizabeth W. Karlson and John B. Harley and Ian B. Stanaway and David Crosslin and Joshua C. Denny and Mitchell S.V. Elkind and Ali G. Gharavi and George Hripcsak and Chunhua Weng and Krzysztof Kiryluk},
doi = {10.1681/asn.2020091371},
issn = {1533-3450},
year = {2021},
date = {2021-00-00},
journal = {JASN},
volume = {32},
number = {8},
pages = {2031--2047},
publisher = {Ovid Technologies (Wolters Kluwer Health)},
abstract = {
Significance Statement
The complement pathway represents one of the critical arms of the innate immune system. We combined genome-wide and phenome-wide association studies using medical records data for C3 and C4 levels to discover common genetic variants controlling systemic complement activation. Three genome-wide significant loci had large effects on complement levels. These loci encode three critical complement genes: CFH , C3 , and C4 . We performed detailed functional annotations of the significant loci, including multiallelic copy number variant analysis of the C4 locus to define two structural genomic variants with large effects on C4 levels. Blood C4 levels were strongly correlated with the copy number of C4A and C4B genes. Lastly, using genome-wide genetic correlations and electronic health records–based phenome-wide association studies in 102,138 participants, we catalogued a spectrum of human diseases genetically related to systemic complement activation, including inflammatory, autoimmune, cardiometabolic, and kidney diseases.
Background
Genetic variants in complement genes have been associated with a wide range of human disease states, but well-powered genetic association studies of complement activation have not been performed in large multiethnic cohorts.
Methods
We performed medical records–based genome-wide and phenome-wide association studies for plasma C3 and C4 levels among participants of the Electronic Medical Records and Genomics (eMERGE) network.
Results
In a GWAS for C3 levels in 3949 individuals, we detected two genome-wide significant loci: chr.1q31.3 (CFH locus; rs3753396-A; β =0.20; 95% CI, 0.14 to 0.25; P =1.52x10-11 ) and chr.19p13.3 (C3 locus; rs11569470-G; β =0.19; 95% CI, 0.13 to 0.24; P =1.29x10-8 ). These two loci explained approximately 2% of variance in C3 levels. GWAS for C4 levels involved 3998 individuals and revealed a genome-wide significant locus at chr.6p21.32 (C4 locus; rs3135353-C; β =0.40; 95% CI, 0.34 to 0.45; P =4.58x10-35 ). This locus explained approximately 13% of variance in C4 levels. The multiallelic copy number variant analysis defined two structural genomic C4 variants with large effect on blood C4 levels: C4-BS (β =−0.36; 95% CI, −0.42 to −0.30; P =2.98x10-22 ) and C4-AL-BS (β =0.25; 95% CI, 0.21 to 0.29; P =8.11x10-23 ). Overall, C4 levels were strongly correlated with copy numbers of C4A and C4B genes. In comprehensive phenome-wide association studies involving 102,138 eMERGE participants, we cataloged a full spectrum of autoimmune, cardiometabolic, and kidney diseases genetically related to systemic complement activation.
Conclusions
We discovered genetic determinants of plasma C3 and C4 levels using eMERGE genomic data linked to electronic medical records. Genetic variants regulating C3 and C4 levels have large effects and multiple clinical correlations across the spectrum of complement-related diseases in humans.
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2020
Cui, Jing; Raychaudhuri, Soumya; Karlson, Elizabeth W.; Speyer, Cameron; Malspeis, Susan; Guan, Hongshu; Sparks, Jeffrey A.; Ni, Hongru; Liu, Xinyi; Stevens, Emma; Williams, Jessica N.; Davenport, Emma E.; Knevel, Rachel; Costenbader, Karen H.
Interactions Between Genome‐Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus Journal Article
In: Arthritis & Rheumatology, vol. 72, no. 11, pp. 1863–1871, 2020, ISSN: 2326-5205.
@article{Cui2020,
title = {Interactions Between Genome‐Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus},
author = {Jing Cui and Soumya Raychaudhuri and Elizabeth W. Karlson and Cameron Speyer and Susan Malspeis and Hongshu Guan and Jeffrey A. Sparks and Hongru Ni and Xinyi Liu and Emma Stevens and Jessica N. Williams and Emma E. Davenport and Rachel Knevel and Karen H. Costenbader},
doi = {10.1002/art.41414},
issn = {2326-5205},
year = {2020},
date = {2020-11-00},
journal = {Arthritis & Rheumatology},
volume = {72},
number = {11},
pages = {1863--1871},
publisher = {Wiley},
abstract = {Objective To identify interactions between genetic factors and current or recent smoking in relation to risk of developing systemic lupus erythematosus (SLE). Methods For the study, 673 patients with SLE (diagnosed according to the American College of Rheumatology 1997 updated classification criteria) were matched by age, sex, and race (first 3 genetic principal components) to 3,272 control subjects without a history of connective tissue disease. Smoking status was classified as current smoking/having recently quit smoking within 4 years before diagnosis (or matched index date for controls) versus distant past/never smoking. In total, 86 single‐nucleotide polymorphisms and 10 classic HLA alleles previously associated with SLE were included in a weighted genetic risk score (wGRS), with scores dichotomized as either low or high based on the median value in control subjects (low wGRS being defined as less than or equal to the control median; high wGRS being defined as greater than the control median). Conditional logistic regression models were used to estimate both the risk of SLE and risk of anti–double‐stranded DNA autoantibody–positive (dsDNA+) SLE. Additive interactions were assessed using the attributable proportion (AP) due to interaction, and multiplicative interactions were assessed using a chi‐square test (with 1 degree of freedom) for the wGRS and for individual risk alleles. Separate repeated analyses were carried out among subjects of European ancestry only. Results The mean ± SD age of the SLE patients at the time of diagnosis was 36.4 ± 15.3 years. Among the 673 SLE patients included, 92.3% were female and 59.3% were dsDNA+. Ethnic distributions were as follows: 75.6% of European ancestry, 4.5% of Asian ancestry, 11.7% of African ancestry, and 8.2% classified as other ancestry. A high wGRS (odds ratio [OR] 2.0, P = 1.0 × 10−51 versus low wGRS) and a status of current/recent smoking (OR 1.5, P = 0.0003 versus distant past/never smoking) were strongly associated with SLE risk, with significant additive interaction (AP 0.33, P = 0.0012), and associations with the risk of anti‐dsDNA+ SLE were even stronger. No significant multiplicative interactions with the total wGRS (P = 0.58) or with the HLA ‐only wGRS (P = 0.06) were found. Findings were similar in analyses restricted to only subjects of European ancestry. Conclusion The strong additive interaction between an updated SLE genetic risk score and current/recent smoking suggests that smoking may influence specific genes in the pathogenesis of SLE.
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cui, Jing; Raychaudhuri, Soumya; Karlson, Elizabeth W.; Speyer, Cameron; Malspeis, Susan; Guan, Hongshu; Sparks, Jeffrey A.; Ni, Hongru; Liu, Xinyi; Stevens, Emma; Williams, Jessica N.; Davenport, Emma E.; Knevel, Rachel; Costenbader, Karen H.
Interactions Between Genome‐Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus Journal Article
In: Arthritis & Rheumatology, vol. 72, no. 11, pp. 1863–1871, 2020, ISSN: 2326-5205.
@article{Cui2020b,
title = {Interactions Between Genome‐Wide Genetic Factors and Smoking Influencing Risk of Systemic Lupus Erythematosus},
author = {Jing Cui and Soumya Raychaudhuri and Elizabeth W. Karlson and Cameron Speyer and Susan Malspeis and Hongshu Guan and Jeffrey A. Sparks and Hongru Ni and Xinyi Liu and Emma Stevens and Jessica N. Williams and Emma E. Davenport and Rachel Knevel and Karen H. Costenbader},
doi = {10.1002/art.41414},
issn = {2326-5205},
year = {2020},
date = {2020-11-00},
journal = {Arthritis & Rheumatology},
volume = {72},
number = {11},
pages = {1863--1871},
publisher = {Wiley},
abstract = {Objective To identify interactions between genetic factors and current or recent smoking in relation to risk of developing systemic lupus erythematosus (SLE). Methods For the study, 673 patients with SLE (diagnosed according to the American College of Rheumatology 1997 updated classification criteria) were matched by age, sex, and race (first 3 genetic principal components) to 3,272 control subjects without a history of connective tissue disease. Smoking status was classified as current smoking/having recently quit smoking within 4 years before diagnosis (or matched index date for controls) versus distant past/never smoking. In total, 86 single‐nucleotide polymorphisms and 10 classic HLA alleles previously associated with SLE were included in a weighted genetic risk score (wGRS), with scores dichotomized as either low or high based on the median value in control subjects (low wGRS being defined as less than or equal to the control median; high wGRS being defined as greater than the control median). Conditional logistic regression models were used to estimate both the risk of SLE and risk of anti–double‐stranded DNA autoantibody–positive (dsDNA+) SLE. Additive interactions were assessed using the attributable proportion (AP) due to interaction, and multiplicative interactions were assessed using a chi‐square test (with 1 degree of freedom) for the wGRS and for individual risk alleles. Separate repeated analyses were carried out among subjects of European ancestry only. Results The mean ± SD age of the SLE patients at the time of diagnosis was 36.4 ± 15.3 years. Among the 673 SLE patients included, 92.3% were female and 59.3% were dsDNA+. Ethnic distributions were as follows: 75.6% of European ancestry, 4.5% of Asian ancestry, 11.7% of African ancestry, and 8.2% classified as other ancestry. A high wGRS (odds ratio [OR] 2.0, P = 1.0 × 10−51 versus low wGRS) and a status of current/recent smoking (OR 1.5, P = 0.0003 versus distant past/never smoking) were strongly associated with SLE risk, with significant additive interaction (AP 0.33, P = 0.0012), and associations with the risk of anti‐dsDNA+ SLE were even stronger. No significant multiplicative interactions with the total wGRS (P = 0.58) or with the HLA ‐only wGRS (P = 0.06) were found. Findings were similar in analyses restricted to only subjects of European ancestry. Conclusion The strong additive interaction between an updated SLE genetic risk score and current/recent smoking suggests that smoking may influence specific genes in the pathogenesis of SLE.
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Krebs, Kristi; Bovijn, Jonas; Zheng, Neil; Lepamets, Maarja; Censin, Jenny C; Jürgenson, Tuuli; Särg, Dage; Abner, Erik; Laisk, Triin; Luo, Yang; Skotte, Line; Geller, Frank; Feenstra, Bjarke; Wang, Wei; Auton, Adam; ; Raychaudhuri, Soumya; Esko, Tõnu; Metspalu, Andres; Laur, Sven; Roden, Dan M; Wei, Wei-Qi; Holmes, Michael V; Lindgren, Cecilia M; Phillips, Elizabeth J; Mägi, Reedik; Milani, Lili; Fadista, João
Genome-wide Study Identifies Association between HLA-B55:01 and Self-Reported Penicillin Allergy Journal Article
In: Am J Hum Genet, vol. 107, no. 4, pp. 612–621, 2020, ISSN: 1537-6605.
@article{pmid32888428,
title = {Genome-wide Study Identifies Association between HLA-B55:01 and Self-Reported Penicillin Allergy},
author = {Kristi Krebs and Jonas Bovijn and Neil Zheng and Maarja Lepamets and Jenny C Censin and Tuuli Jürgenson and Dage Särg and Erik Abner and Triin Laisk and Yang Luo and Line Skotte and Frank Geller and Bjarke Feenstra and Wei Wang and Adam Auton and and Soumya Raychaudhuri and Tõnu Esko and Andres Metspalu and Sven Laur and Dan M Roden and Wei-Qi Wei and Michael V Holmes and Cecilia M Lindgren and Elizabeth J Phillips and Reedik Mägi and Lili Milani and João Fadista},
doi = {10.1016/j.ajhg.2020.08.008},
issn = {1537-6605},
year = {2020},
date = {2020-10-01},
journal = {Am J Hum Genet},
volume = {107},
number = {4},
pages = {612--621},
abstract = {Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center's BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe's research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B55:01 allele (OR 1.41 95% CI 1.33-1.49, p value 2.04 × 10) and confirmed by independent replication in 23andMe's research cohort (OR 1.30 95% CI 1.25-1.34, p value 1.00 × 10). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center's BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe's research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B55:01 allele (OR 1.41 95% CI 1.33-1.49, p value 2.04 × 10) and confirmed by independent replication in 23andMe's research cohort (OR 1.30 95% CI 1.25-1.34, p value 1.00 × 10). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.
Orange, Dana E.; Yao, Vicky; Sawicka, Kirsty; Fak, John; Frank, Mayu O.; Parveen, Salina; Blachere, Nathalie E.; Hale, Caryn; Zhang, Fan; Raychaudhuri, Soumya; Troyanskaya, Olga G.; Darnell, Robert B.
RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares Journal Article
In: N Engl J Med, vol. 383, no. 3, pp. 218–228, 2020, ISSN: 1533-4406.
@article{Orange2020,
title = {RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares},
author = {Dana E. Orange and Vicky Yao and Kirsty Sawicka and John Fak and Mayu O. Frank and Salina Parveen and Nathalie E. Blachere and Caryn Hale and Fan Zhang and Soumya Raychaudhuri and Olga G. Troyanskaya and Robert B. Darnell},
doi = {10.1056/nejmoa2004114},
issn = {1533-4406},
year = {2020},
date = {2020-07-16},
journal = {N Engl J Med},
volume = {383},
number = {3},
pages = {218--228},
publisher = {Massachusetts Medical Society},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Orange, Dana E.; Yao, Vicky; Sawicka, Kirsty; Fak, John; Frank, Mayu O.; Parveen, Salina; Blachere, Nathalie E.; Hale, Caryn; Zhang, Fan; Raychaudhuri, Soumya; Troyanskaya, Olga G.; Darnell, Robert B.
RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares Journal Article
In: N Engl J Med, vol. 383, no. 3, pp. 218–228, 2020, ISSN: 1533-4406.
@article{Orange2020b,
title = {RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares},
author = {Dana E. Orange and Vicky Yao and Kirsty Sawicka and John Fak and Mayu O. Frank and Salina Parveen and Nathalie E. Blachere and Caryn Hale and Fan Zhang and Soumya Raychaudhuri and Olga G. Troyanskaya and Robert B. Darnell},
doi = {10.1056/nejmoa2004114},
issn = {1533-4406},
year = {2020},
date = {2020-07-16},
journal = {N Engl J Med},
volume = {383},
number = {3},
pages = {218--228},
publisher = {Massachusetts Medical Society},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Svensson, Mattias N. D.; Zoccheddu, Martina; Yang, Shen; Nygaard, Gyrid; Secchi, Christian; Doody, Karen M.; Slowikowski, Kamil; Mizoguchi, Fumitaka; Humby, Frances; Hands, Rebecca; Santelli, Eugenio; Sacchetti, Cristiano; Wakabayashi, Kuninobu; Wu, Dennis J.; Barback, Christopher; Ai, Rizi; Wang, Wei; Sims, Gary P.; Mydel, Piotr; Kasama, Tsuyoshi; Boyle, David L.; Galimi, Francesco; Vera, David; Tremblay, Michel L.; Raychaudhuri, Soumya; Brenner, Michael B.; Firestein, Gary S.; Pitzalis, Costantino; Ekwall, Anna-Karin H.; Stanford, Stephanie M.; Bottini, Nunzio
Synoviocyte-targeted therapy synergizes with TNF inhibition in arthritis reversal Journal Article
In: Sci. Adv., vol. 6, no. 26, 2020, ISSN: 2375-2548.
@article{Svensson2020,
title = {Synoviocyte-targeted therapy synergizes with TNF inhibition in arthritis reversal},
author = {Mattias N. D. Svensson and Martina Zoccheddu and Shen Yang and Gyrid Nygaard and Christian Secchi and Karen M. Doody and Kamil Slowikowski and Fumitaka Mizoguchi and Frances Humby and Rebecca Hands and Eugenio Santelli and Cristiano Sacchetti and Kuninobu Wakabayashi and Dennis J. Wu and Christopher Barback and Rizi Ai and Wei Wang and Gary P. Sims and Piotr Mydel and Tsuyoshi Kasama and David L. Boyle and Francesco Galimi and David Vera and Michel L. Tremblay and Soumya Raychaudhuri and Michael B. Brenner and Gary S. Firestein and Costantino Pitzalis and Anna-Karin H. Ekwall and Stephanie M. Stanford and Nunzio Bottini},
doi = {10.1126/sciadv.aba4353},
issn = {2375-2548},
year = {2020},
date = {2020-06-26},
journal = {Sci. Adv.},
volume = {6},
number = {26},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {PTPRS-targeted FLS-directed therapy synergizes with TNF inhibition in therapy of arthritis. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Knevel, Rachel; le Cessie, Saskia; Terao, Chikashi C.; Slowikowski, Kamil; Cui, Jing; Huizinga, Tom W. J.; Costenbader, Karen H.; Liao, Katherine P.; Karlson, Elizabeth W.; Raychaudhuri, Soumya
Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis Journal Article
In: Sci. Transl. Med., vol. 12, no. 545, 2020, ISSN: 1946-6242.
@article{Knevel2020,
title = {Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis},
author = {Rachel Knevel and Saskia le Cessie and Chikashi C. Terao and Kamil Slowikowski and Jing Cui and Tom W. J. Huizinga and Karen H. Costenbader and Katherine P. Liao and Elizabeth W. Karlson and Soumya Raychaudhuri},
doi = {10.1126/scitranslmed.aay1548},
issn = {1946-6242},
year = {2020},
date = {2020-05-27},
journal = {Sci. Transl. Med.},
volume = {12},
number = {545},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {A genetic risk tool could be used at the first clinical visit of patients with inflammatory arthritis to increase diagnostic efficacy. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Knevel, Rachel; le Cessie, Saskia; Terao, Chikashi C.; Slowikowski, Kamil; Cui, Jing; Huizinga, Tom W. J.; Costenbader, Karen H.; Liao, Katherine P.; Karlson, Elizabeth W.; Raychaudhuri, Soumya
Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis Journal Article
In: Sci. Transl. Med., vol. 12, no. 545, 2020, ISSN: 1946-6242.
@article{Knevel2020b,
title = {Using genetics to prioritize diagnoses for rheumatology outpatients with inflammatory arthritis},
author = {Rachel Knevel and Saskia le Cessie and Chikashi C. Terao and Kamil Slowikowski and Jing Cui and Tom W. J. Huizinga and Karen H. Costenbader and Katherine P. Liao and Elizabeth W. Karlson and Soumya Raychaudhuri},
doi = {10.1126/scitranslmed.aay1548},
issn = {1946-6242},
year = {2020},
date = {2020-05-27},
journal = {Sci. Transl. Med.},
volume = {12},
number = {545},
publisher = {American Association for the Advancement of Science (AAAS)},
abstract = {A genetic risk tool could be used at the first clinical visit of patients with inflammatory arthritis to increase diagnostic efficacy. },
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Huizinga, Tom WJ; Holers, V Michael; Anolik, Jennifer; Brenner, Michael B; Buckley, Christopher Dominic; Bykerk, Vivian; Connolly, Sean E; Deane, Kevin D; Guo, Jianping; Hodge, Martin; Hoffmann, Steve; Nestle, Frank; Pitzalis, Costantino; Raychaudhuri, Soumya; Yamamoto, Kazuhiko; Li, Zhanguo; Klareskog, Lars
Disruptive innovation in rheumatology: new networks of global public–private partnerships are needed to take advantage of scientific progress Journal Article
In: Ann Rheum Dis, vol. 79, no. 5, pp. 553–555, 2020, ISSN: 1468-2060.
@article{Huizinga2020,
title = {Disruptive innovation in rheumatology: new networks of global public–private partnerships are needed to take advantage of scientific progress},
author = {Tom WJ Huizinga and V Michael Holers and Jennifer Anolik and Michael B Brenner and Christopher Dominic Buckley and Vivian Bykerk and Sean E Connolly and Kevin D Deane and Jianping Guo and Martin Hodge and Steve Hoffmann and Frank Nestle and Costantino Pitzalis and Soumya Raychaudhuri and Kazuhiko Yamamoto and Zhanguo Li and Lars Klareskog},
doi = {10.1136/annrheumdis-2019-216846},
issn = {1468-2060},
year = {2020},
date = {2020-05-00},
journal = {Ann Rheum Dis},
volume = {79},
number = {5},
pages = {553--555},
publisher = {BMJ},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Huizinga, Tom WJ; Holers, V Michael; Anolik, Jennifer; Brenner, Michael B; Buckley, Christopher Dominic; Bykerk, Vivian; Connolly, Sean E; Deane, Kevin D; Guo, Jianping; Hodge, Martin; Hoffmann, Steve; Nestle, Frank; Pitzalis, Costantino; Raychaudhuri, Soumya; Yamamoto, Kazuhiko; Li, Zhanguo; Klareskog, Lars
Disruptive innovation in rheumatology: new networks of global public–private partnerships are needed to take advantage of scientific progress Journal Article
In: Ann Rheum Dis, vol. 79, no. 5, pp. 553–555, 2020, ISSN: 1468-2060.
@article{Huizinga2020b,
title = {Disruptive innovation in rheumatology: new networks of global public–private partnerships are needed to take advantage of scientific progress},
author = {Tom WJ Huizinga and V Michael Holers and Jennifer Anolik and Michael B Brenner and Christopher Dominic Buckley and Vivian Bykerk and Sean E Connolly and Kevin D Deane and Jianping Guo and Martin Hodge and Steve Hoffmann and Frank Nestle and Costantino Pitzalis and Soumya Raychaudhuri and Kazuhiko Yamamoto and Zhanguo Li and Lars Klareskog},
doi = {10.1136/annrheumdis-2019-216846},
issn = {1468-2060},
year = {2020},
date = {2020-05-00},
journal = {Ann Rheum Dis},
volume = {79},
number = {5},
pages = {553--555},
publisher = {BMJ},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Slowikowski, Kamil; Nguyen, Hung N.; Noss, Erika H.; Simmons, Daimon P.; Mizoguchi, Fumitaka; Watts, Gerald F. M.; Gurish, Michael F.; Brenner, Michael B.; Raychaudhuri, Soumya
CUX1 and IκBζ (NFKBIZ) mediate the synergistic inflammatory response to TNF and IL-17A in stromal fibroblasts Journal Article
In: Proc. Natl. Acad. Sci. U.S.A., vol. 117, no. 10, pp. 5532–5541, 2020, ISSN: 1091-6490.
@article{Slowikowski2020,
title = {CUX1 and IκBζ (NFKBIZ) mediate the synergistic inflammatory response to TNF and IL-17A in stromal fibroblasts},
author = {Kamil Slowikowski and Hung N. Nguyen and Erika H. Noss and Daimon P. Simmons and Fumitaka Mizoguchi and Gerald F. M. Watts and Michael F. Gurish and Michael B. Brenner and Soumya Raychaudhuri},
doi = {10.1073/pnas.1912702117},
issn = {1091-6490},
year = {2020},
date = {2020-03-10},
journal = {Proc. Natl. Acad. Sci. U.S.A.},
volume = {117},
number = {10},
pages = {5532--5541},
publisher = {Proceedings of the National Academy of Sciences},
abstract = {
The role of stromal fibroblasts in chronic inflammation is unfolding. In rheumatoid arthritis, leukocyte-derived cytokines TNF and IL-17A work together, activating fibroblasts to become a dominant source of the hallmark cytokine IL-6. However, IL-17A alone has minimal effect on fibroblasts. To identify key mediators of the synergistic response to TNF and IL-17A in human synovial fibroblasts, we performed time series, dose–response, and gene-silencing transcriptomics experiments. Here we show that in combination with TNF, IL-17A selectively induces a specific set of genes mediated by factors including cut-like homeobox 1 (CUX1) and IκBζ (NFKBIZ). In the promoters of
CXCL1
,
CXCL2
, and
CXCL3
, we found a putative CUX1–NF-κB binding motif not found elsewhere in the genome. CUX1 and NF-κB p65 mediate transcription of these genes independent of LIFR, STAT3, STAT4, and ELF3. Transcription of
NFKBIZ
, encoding the atypical IκB factor IκBζ, is IL-17A dose-dependent, and IκBζ only mediates the transcriptional response to TNF and IL-17A, but not to TNF alone. In fibroblasts, IL-17A response depends on CUX1 and IκBζ to engage the NF-κB complex to produce chemoattractants for neutrophil and monocyte recruitment.
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The role of stromal fibroblasts in chronic inflammation is unfolding. In rheumatoid arthritis, leukocyte-derived cytokines TNF and IL-17A work together, activating fibroblasts to become a dominant source of the hallmark cytokine IL-6. However, IL-17A alone has minimal effect on fibroblasts. To identify key mediators of the synergistic response to TNF and IL-17A in human synovial fibroblasts, we performed time series, dose–response, and gene-silencing transcriptomics experiments. Here we show that in combination with TNF, IL-17A selectively induces a specific set of genes mediated by factors including cut-like homeobox 1 (CUX1) and IκBζ (NFKBIZ). In the promoters of
,
, and
, we found a putative CUX1–NF-κB binding motif not found elsewhere in the genome. CUX1 and NF-κB p65 mediate transcription of these genes independent of LIFR, STAT3, STAT4, and ELF3. Transcription of
, encoding the atypical IκB factor IκBζ, is IL-17A dose-dependent, and IκBζ only mediates the transcriptional response to TNF and IL-17A, but not to TNF alone. In fibroblasts, IL-17A response depends on CUX1 and IκBζ to engage the NF-κB complex to produce chemoattractants for neutrophil and monocyte recruitment.
Slowikowski, Kamil; Nguyen, Hung N.; Noss, Erika H.; Simmons, Daimon P.; Mizoguchi, Fumitaka; Watts, Gerald F. M.; Gurish, Michael F.; Brenner, Michael B.; Raychaudhuri, Soumya
CUX1 and IκBζ (NFKBIZ) mediate the synergistic inflammatory response to TNF and IL-17A in stromal fibroblasts Journal Article
In: Proc. Natl. Acad. Sci. U.S.A., vol. 117, no. 10, pp. 5532–5541, 2020, ISSN: 1091-6490.
@article{Slowikowski2020b,
title = {CUX1 and IκBζ (NFKBIZ) mediate the synergistic inflammatory response to TNF and IL-17A in stromal fibroblasts},
author = {Kamil Slowikowski and Hung N. Nguyen and Erika H. Noss and Daimon P. Simmons and Fumitaka Mizoguchi and Gerald F. M. Watts and Michael F. Gurish and Michael B. Brenner and Soumya Raychaudhuri},
doi = {10.1073/pnas.1912702117},
issn = {1091-6490},
year = {2020},
date = {2020-03-10},
journal = {Proc. Natl. Acad. Sci. U.S.A.},
volume = {117},
number = {10},
pages = {5532--5541},
publisher = {Proceedings of the National Academy of Sciences},
abstract = {
The role of stromal fibroblasts in chronic inflammation is unfolding. In rheumatoid arthritis, leukocyte-derived cytokines TNF and IL-17A work together, activating fibroblasts to become a dominant source of the hallmark cytokine IL-6. However, IL-17A alone has minimal effect on fibroblasts. To identify key mediators of the synergistic response to TNF and IL-17A in human synovial fibroblasts, we performed time series, dose–response, and gene-silencing transcriptomics experiments. Here we show that in combination with TNF, IL-17A selectively induces a specific set of genes mediated by factors including cut-like homeobox 1 (CUX1) and IκBζ (NFKBIZ). In the promoters of
CXCL1
,
CXCL2
, and
CXCL3
, we found a putative CUX1–NF-κB binding motif not found elsewhere in the genome. CUX1 and NF-κB p65 mediate transcription of these genes independent of LIFR, STAT3, STAT4, and ELF3. Transcription of
NFKBIZ
, encoding the atypical IκB factor IκBζ, is IL-17A dose-dependent, and IκBζ only mediates the transcriptional response to TNF and IL-17A, but not to TNF alone. In fibroblasts, IL-17A response depends on CUX1 and IκBζ to engage the NF-κB complex to produce chemoattractants for neutrophil and monocyte recruitment.
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The role of stromal fibroblasts in chronic inflammation is unfolding. In rheumatoid arthritis, leukocyte-derived cytokines TNF and IL-17A work together, activating fibroblasts to become a dominant source of the hallmark cytokine IL-6. However, IL-17A alone has minimal effect on fibroblasts. To identify key mediators of the synergistic response to TNF and IL-17A in human synovial fibroblasts, we performed time series, dose–response, and gene-silencing transcriptomics experiments. Here we show that in combination with TNF, IL-17A selectively induces a specific set of genes mediated by factors including cut-like homeobox 1 (CUX1) and IκBζ (NFKBIZ). In the promoters of
,
, and
, we found a putative CUX1–NF-κB binding motif not found elsewhere in the genome. CUX1 and NF-κB p65 mediate transcription of these genes independent of LIFR, STAT3, STAT4, and ELF3. Transcription of
, encoding the atypical IκB factor IκBζ, is IL-17A dose-dependent, and IκBζ only mediates the transcriptional response to TNF and IL-17A, but not to TNF alone. In fibroblasts, IL-17A response depends on CUX1 and IκBζ to engage the NF-κB complex to produce chemoattractants for neutrophil and monocyte recruitment.
Amariuta, Tiffany; Luo, Yang; Knevel, Rachel; Okada, Yukinori; Raychaudhuri, Soumya
Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis Journal Article
In: Immunol Rev, vol. 294, no. 1, pp. 188–204, 2020, ISSN: 1600-065X.
@article{pmid31782165,
title = {Advances in genetics toward identifying pathogenic cell states of rheumatoid arthritis},
author = {Tiffany Amariuta and Yang Luo and Rachel Knevel and Yukinori Okada and Soumya Raychaudhuri},
doi = {10.1111/imr.12827},
issn = {1600-065X},
year = {2020},
date = {2020-03-01},
journal = {Immunol Rev},
volume = {294},
number = {1},
pages = {188--204},
abstract = {Rheumatoid arthritis (RA) risk has a large genetic component (~60%) that is still not fully understood. This has hampered the design of effective treatments that could promise lifelong remission. RA is a polygenic disease with 106 known genome-wide significant associated loci and thousands of small effect causal variants. Our current understanding of RA risk has suggested cell-type-specific contexts for causal variants, implicating CD4 + effector memory T cells, as well as monocytes, B cells and stromal fibroblasts. While these cellular states and categories are still mechanistically broad, future studies may identify causal cell subpopulations. These efforts are propelled by advances in single cell profiling. Identification of causal cell subpopulations may accelerate therapeutic intervention to achieve lifelong remission.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Rheumatoid arthritis (RA) risk has a large genetic component (~60%) that is still not fully understood. This has hampered the design of effective treatments that could promise lifelong remission. RA is a polygenic disease with 106 known genome-wide significant associated loci and thousands of small effect causal variants. Our current understanding of RA risk has suggested cell-type-specific contexts for causal variants, implicating CD4 + effector memory T cells, as well as monocytes, B cells and stromal fibroblasts. While these cellular states and categories are still mechanistically broad, future studies may identify causal cell subpopulations. These efforts are propelled by advances in single cell profiling. Identification of causal cell subpopulations may accelerate therapeutic intervention to achieve lifelong remission.
2019
Korsunsky, Ilya; Millard, Nghia; Fan, Jean; Slowikowski, Kamil; Zhang, Fan; Wei, Kevin; Baglaenko, Yuriy; Brenner, Michael; Loh, Po-Ru; Raychaudhuri, Soumya
Fast, sensitive and accurate integration of single-cell data with Harmony Journal Article
In: Nat Methods, vol. 16, no. 12, pp. 1289–1296, 2019, ISSN: 1548-7105.
@article{pmid31740819,
title = {Fast, sensitive and accurate integration of single-cell data with Harmony},
author = {Ilya Korsunsky and Nghia Millard and Jean Fan and Kamil Slowikowski and Fan Zhang and Kevin Wei and Yuriy Baglaenko and Michael Brenner and Po-Ru Loh and Soumya Raychaudhuri},
doi = {10.1038/s41592-019-0619-0},
issn = {1548-7105},
year = {2019},
date = {2019-12-01},
journal = {Nat Methods},
volume = {16},
number = {12},
pages = {1289--1296},
abstract = {The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony (https://github.com/immunogenomics/harmony), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~10 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The emerging diversity of single-cell RNA-seq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies, because biological and technical differences are interspersed. We present Harmony (https://github.com/immunogenomics/harmony), an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms while requiring fewer computational resources. Harmony enables the integration of ~10 cells on a personal computer. We apply Harmony to peripheral blood mononuclear cells from datasets with large experimental differences, five studies of pancreatic islet cells, mouse embryogenesis datasets and the integration of scRNA-seq with spatial transcriptomics data.
Kim, Samuel S; Dai, Chengzhen; Hormozdiari, Farhad; van de Geijn, Bryce; Gazal, Steven; Park, Yongjin; O'Connor, Luke; Amariuta, Tiffany; Loh, Po-Ru; Finucane, Hilary; Raychaudhuri, Soumya; Price, Alkes L
Genes with High Network Connectivity Are Enriched for Disease Heritability Miscellaneous
2019, ISSN: 1537-6605.
@misc{pmid31809749,
title = {Genes with High Network Connectivity Are Enriched for Disease Heritability},
author = {Samuel S Kim and Chengzhen Dai and Farhad Hormozdiari and Bryce van de Geijn and Steven Gazal and Yongjin Park and Luke O'Connor and Tiffany Amariuta and Po-Ru Loh and Hilary Finucane and Soumya Raychaudhuri and Alkes L Price},
doi = {10.1016/j.ajhg.2019.11.009},
issn = {1537-6605},
year = {2019},
date = {2019-12-01},
journal = {Am J Hum Genet},
volume = {105},
number = {6},
pages = {1302},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Nathan, Aparna; Baglaenko, Yuriy; Fonseka, Chamith Y; Beynor, Jessica I; Raychaudhuri, Soumya
Multimodal single-cell approaches shed light on T cell heterogeneity Journal Article
In: Curr Opin Immunol, vol. 61, pp. 17–25, 2019, ISSN: 1879-0372.
@article{pmid31430664,
title = {Multimodal single-cell approaches shed light on T cell heterogeneity},
author = {Aparna Nathan and Yuriy Baglaenko and Chamith Y Fonseka and Jessica I Beynor and Soumya Raychaudhuri},
doi = {10.1016/j.coi.2019.07.002},
issn = {1879-0372},
year = {2019},
date = {2019-12-01},
journal = {Curr Opin Immunol},
volume = {61},
pages = {17--25},
abstract = {Single-cell methods have revolutionized the study of T cell biology by enabling the identification and characterization of individual cells. This has led to a deeper understanding of T cell heterogeneity by generating functionally relevant measurements - like gene expression, surface markers, chromatin accessibility, T cell receptor sequences - in individual cells. While these methods are independently valuable, they can be augmented when applied jointly, either on separate cells from the same sample or on the same cells. Multimodal approaches are already being deployed to characterize T cells in diverse disease contexts and demonstrate the value of having multiple insights into a cell's function. But, these data sets pose new statistical challenges for integration and joint analysis.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Single-cell methods have revolutionized the study of T cell biology by enabling the identification and characterization of individual cells. This has led to a deeper understanding of T cell heterogeneity by generating functionally relevant measurements - like gene expression, surface markers, chromatin accessibility, T cell receptor sequences - in individual cells. While these methods are independently valuable, they can be augmented when applied jointly, either on separate cells from the same sample or on the same cells. Multimodal approaches are already being deployed to characterize T cells in diverse disease contexts and demonstrate the value of having multiple insights into a cell's function. But, these data sets pose new statistical challenges for integration and joint analysis.