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Article ; Online: Low-frequency and rare genetic variants associated with rheumatoid arthritis risk.

Kronzer, Vanessa L / Sparks, Jeffrey A / Raychaudhuri, Soumya / Cerhan, James R

2024

Abstract: Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller ...

Abstract	Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller individual effects. Low-frequency and rare variants, such as those captured by next-generation sequencing, can also have a large role in heritability in some individuals. Rare variant discovery has informed the development of drugs such as inhibitors of PCSK9 and Janus kinases. Some 34 low-frequency and rare variants are currently associated with RA risk. One variant (19:10352442G>C in TYK2) was identified in five separate studies, and might therefore represent a promising therapeutic target. Following a set of best practices in future studies, including studying diverse populations, using large sample sizes, validating RA and serostatus, replicating findings, adjusting for other variants and performing functional assessment, could help to ensure the relevance of identified variants. Exciting opportunities are now on the horizon for genetics in RA, including larger datasets and consortia, whole-genome sequencing and direct applications of findings in the management, and especially treatment, of RA.
Language	English
Publishing date	2024-03-27
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2491532-4
ISSN	1759-4804 ; 1759-4790
ISSN (online)	1759-4804
ISSN	1759-4790
DOI	10.1038/s41584-024-01096-7
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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

Nature communications

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 ; Online: Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types.

Kim, Samuel S / Truong, Buu / Jagadeesh, Karthik / Dey, Kushal K / Shen, Amber Z / Raychaudhuri, Soumya / Kellis, Manolis / Price, Alkes L

Nature communications

2024 Volume 15, Issue 1, Page(s) 563

Abstract: Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at ... ...

Abstract	Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.
MeSH term(s)	Humans ; RNA-Seq ; Chromatin Immunoprecipitation Sequencing ; Depressive Disorder, Major ; Genome-Wide Association Study ; Chromatin/genetics ; Brain ; Single-Cell Analysis
Chemical Substances	Chromatin
Language	English
Publishing date	2024-01-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-024-44742-0
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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: The Power of Systems Biology: Insights on Lupus Nephritis from the Accelerating Medicines Partnership.

Fava, Andrea / Raychaudhuri, Soumya / Rao, Deepak A

Rheumatic diseases clinics of North America

2021 Volume 47, Issue 3, Page(s) 335–350

Abstract: The Accelerating Medicines Partnership (AMP) SLE Network united resources from academic centers, government, nonprofit, and industry to accelerate discovery in lupus nephritis (LN). The AMP SLE Network developed a set of protocols for high-throughput ... ...

Abstract	The Accelerating Medicines Partnership (AMP) SLE Network united resources from academic centers, government, nonprofit, and industry to accelerate discovery in lupus nephritis (LN). The AMP SLE Network developed a set of protocols for high-throughput analyses to systematically study kidney tissue, urine, and blood in LN. This article summarizes approaches and results from phase 1 of AMP SLE Network effort, including single cell RNA-seq analysis of LN kidney biopsies, cellular and proteomic studies of LN urine, and mass cytometry immunophenotyping of blood cells. This work provides a framework to guide studies of the clinical implications of active cellular/molecular pathways in LN.
MeSH term(s)	Biomarkers ; Biopsy ; Humans ; Lupus Nephritis/drug therapy ; Proteomics ; Systems Biology
Chemical Substances	Biomarkers
Language	English
Publishing date	2021-06-16
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	92118-x
ISSN	1558-3163 ; 0889-857X
ISSN (online)	1558-3163
ISSN	0889-857X
DOI	10.1016/j.rdc.2021.04.003
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Article ; Online: Immunoprofiling comes of age.

Raychaudhuri, Soumya / Gupta, Rajat M

Nature medicine

2019 Volume 25, Issue 3, Page(s) 362–364

Language	English
Publishing date	2019-03-06
Publishing country	United States
Document type	Journal Article ; Comment
ZDB-ID	1220066-9
ISSN	1546-170X ; 1078-8956
ISSN (online)	1546-170X
ISSN	1078-8956
DOI	10.1038/s41591-019-0387-5
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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: HATK: HLA analysis toolkit.

Choi, Wanson / Luo, Yang / Raychaudhuri, Soumya / Han, Buhm

Bioinformatics (Oxford, England)

2020 Volume 37, Issue 3, Page(s) 416–418

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 ... ...

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.
MeSH term(s)	Alleles ; Amino Acid Sequence ; Chromosome Mapping ; Genetic Predisposition to Disease ; HLA Antigens/genetics ; Histocompatibility Testing ; Humans ; Software
Chemical Substances	HLA Antigens
Language	English
Publishing date	2020-08-06
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btaa684
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Article ; Online: Mapping rare and common causal alleles for complex human diseases.

Raychaudhuri, Soumya

Cell

2011 Volume 147, Issue 1, Page(s) 57–69

Abstract: Advances in genotyping and sequencing technologies have revolutionized the genetics of complex disease by locating rare and common variants that influence an individual's risk for diseases, such as diabetes, cancers, and psychiatric disorders. However, ... ...

Abstract	Advances in genotyping and sequencing technologies have revolutionized the genetics of complex disease by locating rare and common variants that influence an individual's risk for diseases, such as diabetes, cancers, and psychiatric disorders. However, to capitalize on these data for prevention and therapies requires the identification of causal alleles and a mechanistic understanding for how these variants contribute to the disease. After discussing the strategies currently used to map variants for complex diseases, this Primer explores how variants may be prioritized for follow-up functional studies and the challenges and approaches for assessing the contributions of rare and common variants to disease phenotypes.
MeSH term(s)	Chromatin Assembly and Disassembly ; Chromosome Mapping ; Disease/genetics ; Genetic Predisposition to Disease ; Genetic Variation ; Genetics, Population ; Genome-Wide Association Study ; Humans ; Polymorphism, Single Nucleotide ; Quantitative Trait Loci
Language	English
Publishing date	2011-09-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	187009-9
ISSN	1097-4172 ; 0092-8674
ISSN (online)	1097-4172
ISSN	0092-8674
DOI	10.1016/j.cell.2011.09.011
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