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Article ; Online: The genetic basis of autoimmunity seen through the lens of T cell functional traits.

Lagattuta, Kaitlyn A / Park, Hannah L / Rumker, Laurie / Ishigaki, Kazuyoshi / Nathan, Aparna / Raychaudhuri, Soumya

2024 Volume 15, Issue 1, Page(s) 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 ... ...

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?
MeSH term(s)	Humans ; T-Lymphocytes ; Autoimmunity/genetics ; Quantitative Trait Loci/genetics ; Phenotype ; Polymorphism, Single Nucleotide ; Receptors, Antigen, T-Cell/genetics ; Autoimmune Diseases/genetics ; Genome-Wide Association Study
Chemical Substances	Receptors, Antigen, T-Cell
Language	English
Publishing date	2024-02-08
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-024-45170-w
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Article: The T cell receptor sequence influences the likelihood of T cell memory formation.

Lagattuta, Kaitlyn A / Nathan, Aparna / Rumker, Laurie / Birnbaum, Michael E / Raychaudhuri, Soumya

bioRxiv : the preprint server for biology

2023

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 ... ...

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.
Language	English
Publishing date	2023-07-23
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.07.20.549939
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Article ; Online: Methods and Insights from Single-Cell Expression Quantitative Trait Loci.

Kang, Joyce B / Raveane, Alessandro / Nathan, Aparna / Soranzo, Nicole / Raychaudhuri, Soumya

Annual review of genomics and human genetics

2023 Volume 24, Page(s) 277–303

Abstract: Recent advancements in single-cell technologies have enabled expression quantitative trait locus (eQTL) analysis across many individuals at single-cell resolution. Compared with bulk RNA sequencing, which averages gene expression across cell types and ... ...

Abstract	Recent advancements in single-cell technologies have enabled expression quantitative trait locus (eQTL) analysis across many individuals at single-cell resolution. Compared with bulk RNA sequencing, which averages gene expression across cell types and cell states, single-cell assays capture the transcriptional states of individual cells, including fine-grained, transient, and difficult-to-isolate populations at unprecedented scale and resolution. Single-cell eQTL (sc-eQTL) mapping can identify context-dependent eQTLs that vary with cell states, including some that colocalize with disease variants identified in genome-wide association studies. By uncovering the precise contexts in which these eQTLs act, single-cell approaches can unveil previously hidden regulatory effects and pinpoint important cell states underlying molecular mechanisms of disease. Here, we present an overview of recently deployed experimental designs in sc-eQTL studies. In the process, we consider the influence of study design choices such as cohort, cell states, and ex vivo perturbations. We then discuss current methodologies, modeling approaches, and technical challenges as well as future opportunities and applications.
MeSH term(s)	Humans ; Quantitative Trait Loci ; Genome-Wide Association Study/methods ; Chromosome Mapping ; Research Design
Language	English
Publishing date	2023-05-17
Publishing country	United States
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	2037670-4
ISSN	1545-293X ; 1527-8204
ISSN (online)	1545-293X
ISSN	1527-8204
DOI	10.1146/annurev-genom-101422-100437
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Article ; Online: Single-cell genomics meets human genetics.

Cuomo, Anna S E / Nathan, Aparna / Raychaudhuri, Soumya / MacArthur, Daniel G / Powell, Joseph E

Nature reviews. Genetics

2023 Volume 24, Issue 8, Page(s) 535–549

Abstract: Single-cell genomic technologies are revealing the cellular composition, identities and states in tissues at unprecedented resolution. They have now scaled to the point that it is possible to query samples at the population level, across thousands of ... ...

Abstract	Single-cell genomic technologies are revealing the cellular composition, identities and states in tissues at unprecedented resolution. They have now scaled to the point that it is possible to query samples at the population level, across thousands of individuals. Combining single-cell information with genotype data at this scale provides opportunities to link genetic variation to the cellular processes underpinning key aspects of human biology and disease. This strategy has potential implications for disease diagnosis, risk prediction and development of therapeutic solutions. But, effectively integrating large-scale single-cell genomic data, genetic variation and additional phenotypic data will require advances in data generation and analysis methods. As single-cell genetics begins to emerge as a field in its own right, we review its current state and the challenges and opportunities ahead.
MeSH term(s)	Humans ; Genomics/methods ; Genome ; Genotype ; Human Genetics
Language	English
Publishing date	2023-04-21
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2035157-4
ISSN	1471-0064 ; 1471-0056
ISSN (online)	1471-0064
ISSN	1471-0056
DOI	10.1038/s41576-023-00599-5
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Article ; Online: Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin.

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

Nature communications

2023 Volume 14, Issue 1, Page(s) 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 ... ...

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.
MeSH term(s)	Humans ; Quantitative Trait Loci/genetics ; Skin/pathology ; Psoriasis/drug therapy ; Psoriasis/genetics ; Psoriasis/pathology ; Immunosuppression Therapy ; Biopsy ; Genome-Wide Association Study ; Polymorphism, Single Nucleotide
Language	English
Publishing date	2023-10-07
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-41984-2
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Article: The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis.

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

bioRxiv : the preprint server for biology

2023

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 ... ...

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
Language	English
Publishing date	2023-04-08
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.04.07.536026
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Article ; Online: Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability.

Gupta, Anika / Weinand, Kathryn / Nathan, Aparna / Sakaue, Saori / Zhang, Martin Jinye / Donlin, Laura / Wei, Kevin / Price, Alkes L / Amariuta, Tiffany / Raychaudhuri, Soumya

Nature genetics

2023 Volume 55, Issue 12, Page(s) 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 ... ...

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 STAT1
MeSH term(s)	Humans ; Chromatin/genetics ; Regulatory Sequences, Nucleic Acid/genetics ; Chromosomes ; Autoimmune Diseases/genetics ; Genome, Human
Chemical Substances	Chromatin
Language	English
Publishing date	2023-11-30
Publishing country	United States
Document type	Journal Article
ZDB-ID	1108734-1
ISSN	1546-1718 ; 1061-4036
ISSN (online)	1546-1718
ISSN	1061-4036
DOI	10.1038/s41588-023-01577-7
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Article: Identifying genetic variants that influence the abundance of cell states in single-cell data.

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

bioRxiv : the preprint server for biology

2023

Language	English
Publishing date	2023-11-15
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.11.13.566919
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Article ; Online: Maximizing statistical power to detect differentially abundant cell states with scPOST.

Millard, Nghia / Korsunsky, Ilya / Weinand, Kathryn / Fonseka, Chamith Y / Nathan, Aparna / Kang, Joyce B / Raychaudhuri, Soumya

Cell reports methods

2021 Volume 1, Issue 8

Abstract: To estimate a study design's power to detect differential abundance, we require a framework that simulates many multi-sample single-cell datasets. However, current simulation methods are challenging for large-scale power analyses because they are ... ...

Abstract	To estimate a study design's power to detect differential abundance, we require a framework that simulates many multi-sample single-cell datasets. However, current simulation methods are challenging for large-scale power analyses because they are computationally resource intensive and do not support easy simulation of multi-sample datasets. Current methods also lack modeling of important inter-sample variation, such as the variation in the frequency of cell states between samples that is observed in single-cell data. Thus, we developed single-cell POwer Simulation Tool (scPOST) to address these limitations and help investigators quickly simulate multi-sample single-cell datasets. Users may explore a range of effect sizes and study design choices (such as increasing the number of samples or cells per sample) to determine their effect on power, and thus choose the optimal study design for their planned experiments.
MeSH term(s)	Research Design ; Computer Simulation
Language	English
Publishing date	2021-11-22
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	2667-2375
ISSN (online)	2667-2375
DOI	10.1016/j.crmeth.2021.100120
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Article ; Online: IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 lungs and inflammatory diseases with tissue inflammation.

Zhang, Fan / Mears, Joseph R / Shakib, Lorien / Beynor, Jessica I / Shanaj, Sara / Korsunsky, Ilya / Nathan, Aparna / Donlin, Laura T / Raychaudhuri, Soumya

Genome medicine

2021 Volume 13, Issue 1, Page(s) 64

Abstract: Background: Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate ... ...

Abstract	Background: Immunosuppressive and anti-cytokine treatment may have a protective effect for patients with COVID-19. Understanding the immune cell states shared between COVID-19 and other inflammatory diseases with established therapies may help nominate immunomodulatory therapies. Methods: To identify cellular phenotypes that may be shared across tissues affected by disparate inflammatory diseases, we developed a meta-analysis and integration pipeline that models and removes the effects of technology, tissue of origin, and donor that confound cell-type identification. Using this approach, we integrated > 300,000 single-cell transcriptomic profiles from COVID-19-affected lungs and tissues from healthy subjects and patients with five inflammatory diseases: rheumatoid arthritis (RA), Crohn's disease (CD), ulcerative colitis (UC), systemic lupus erythematosus (SLE), and interstitial lung disease. We tested the association of shared immune states with severe/inflamed status compared to healthy control using mixed-effects modeling. To define environmental factors within these tissues that shape shared macrophage phenotypes, we stimulated human blood-derived macrophages with defined combinations of inflammatory factors, emphasizing in particular antiviral interferons IFN-beta (IFN-β) and IFN-gamma (IFN-γ), and pro-inflammatory cytokines such as TNF. Results: We built an immune cell reference consisting of > 300,000 single-cell profiles from 125 healthy or disease-affected donors from COVID-19 and five inflammatory diseases. We observed a CXCL10+ CCL2+ inflammatory macrophage state that is shared and strikingly abundant in severe COVID-19 bronchoalveolar lavage samples, inflamed RA synovium, inflamed CD ileum, and UC colon. These cells exhibited a distinct arrangement of pro-inflammatory and interferon response genes, including elevated levels of CXCL10, CXCL9, CCL2, CCL3, GBP1, STAT1, and IL1B. Further, we found this macrophage phenotype is induced upon co-stimulation by IFN-γ and TNF-α. Conclusions: Our integrative analysis identified immune cell states shared across inflamed tissues affected by inflammatory diseases and COVID-19. Our study supports a key role for IFN-γ together with TNF-α in driving an abundant inflammatory macrophage phenotype in severe COVID-19-affected lungs, as well as inflamed RA synovium, CD ileum, and UC colon, which may be targeted by existing immunomodulatory therapies.
MeSH term(s)	Arthritis, Rheumatoid/genetics ; Arthritis, Rheumatoid/immunology ; Bronchoalveolar Lavage Fluid/cytology ; Bronchoalveolar Lavage Fluid/immunology ; COVID-19/genetics ; COVID-19/immunology ; Colitis, Ulcerative/genetics ; Colitis, Ulcerative/immunology ; Colon/immunology ; Crohn Disease/genetics ; Crohn Disease/immunology ; Cytokines/immunology ; Humans ; Inflammation/genetics ; Inflammation/immunology ; Lung/immunology ; Lung Diseases, Interstitial/genetics ; Lung Diseases, Interstitial/immunology ; Lupus Erythematosus, Systemic/genetics ; Lupus Erythematosus, Systemic/immunology ; Macrophages/immunology ; Phenotype ; RNA-Seq ; SARS-CoV-2
Chemical Substances	Cytokines
Language	English
Publishing date	2021-04-20
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2484394-5
ISSN	1756-994X ; 1756-994X
ISSN (online)	1756-994X
ISSN	1756-994X
DOI	10.1186/s13073-021-00881-3
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