Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions.

T-cells recognize antigens and induce specialized gene expression programs (GEPs) enabling functions including proliferation, cytotoxicity, and cytokine production. Traditionally, different classes of helper T-cells express mutually exclusive responses - for example, Th1, Th2, and Th17 programs. However, new single-cell RNA sequencing (scRNA-Seq) experiments have revealed a continuum of T-cell states without discrete clusters corresponding to these subsets, implying the need for new analytical frameworks. Here, we advance the characterization of T-cells with T-CellAnnoTator (TCAT), a pipeline that simultaneously quantifies pre-defined GEPs capturing activation states and cellular subsets. From 1,700,000 T-cells from 700 individuals across 38 tissues and five diverse disease contexts, we discover 46 reproducible GEPs reflecting the known core functions of T-cells including proliferation, cytotoxicity, exhaustion, and T helper effector states. We experimentally characterize several novel activation programs and apply TCAT to describe T-cell activation and exhaustion in Covid-19 and cancer, providing insight into T-cell function in these diseases.

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles.

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.

Low-frequency and rare genetic variants associated with rheumatoid arthritis risk.

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.

Non-coding autoimmune risk variant defines role for ICOS in T peripheral helper cell development.

Fine-mapping and functional studies implicate rs117701653, a non-coding single nucleotide polymorphism in the CD28/CTLA4/ICOS locus, as a risk variant for rheumatoid arthritis and type 1 diabetes. Here, using DNA pulldown, mass spectrometry, genome editing and eQTL analysis, we establish that the disease-associated risk allele is functional, reducing affinity for the inhibitory chromosomal regulator SMCHD1 to enhance expression of inducible T-cell costimulator (ICOS) in memory CD4+ T cells from healthy donors. Higher ICOS expression is paralleled by an increase in circulating T peripheral helper (Tph) cells and, in rheumatoid arthritis patients, of blood and joint fluid Tph cells as well as circulating plasmablasts. Correspondingly, ICOS ligation and carriage of the rs117701653 risk allele accelerate T cell differentiation into CXCR5-PD-1high Tph cells producing IL-21 and CXCL13. Thus, mechanistic dissection of a functional non-coding variant in human autoimmunity discloses a previously undefined pathway through which ICOS regulates Tph development and abundance.

The genetic basis of autoimmunity seen through the lens of T cell functional traits.

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?

Blood immunophenotyping identifies distinct kidney histopathology and outcomes in patients with lupus nephritis.

Lupus nephritis (LN) is a frequent manifestation of systemic lupus erythematosus, and fewer than half of patients achieve complete renal response with standard immunosuppressants. Identifying non-invasive, blood-based pathologic immune alterations associated with renal injury could aid therapeutic decisions. Here, we used mass cytometry immunophenotyping of peripheral blood mononuclear cells in 145 patients with biopsy-proven LN and 40 healthy controls to evaluate the heterogeneity of immune activation in patients with LN and to identify correlates of renal parameters and treatment response. Unbiased analysis identified 3 immunologically distinct groups of patients with LN that were associated with different patterns of histopathology, renal cell infiltrates, urine proteomic profiles, and treatment response at one year. Patients with enriched circulating granzyme B+ T cells at baseline showed more severe disease and increased numbers of activated CD8 T cells in the kidney, yet they had the highest likelihood of treatment response. A second group characterized primarily by a high type I interferon signature had a lower likelihood of response to therapy, while a third group appeared immunologically inactive by immunophenotyping at enrollment but with chronic renal injuries. Main immune profiles could be distilled down to 5 simple cytometric parameters that recapitulate several of the associations, highlighting the potential for blood immune profiling to translate to clinically useful non-invasive metrics to assess immune-mediated disease in LN.

Urine proteomic signatures of histological class, activity, chronicity, and treatment response in lupus nephritis.

Lupus nephritis (LN) is a pathologically heterogenous autoimmune disease linked to end-stage kidney disease and mortality. Better therapeutic strategies are needed as only 30%-40% of patients completely respond to treatment. Noninvasive biomarkers of intrarenal inflammation may guide more precise approaches. Because urine collects the byproducts of kidney inflammation, we studied the urine proteomic profiles of 225 patients with LN (573 samples) in the longitudinal Accelerating Medicines Partnership in RA/SLE cohort. Urinary biomarkers of monocyte/neutrophil degranulation (i.e., PR3, S100A8, azurocidin, catalase, cathepsins, MMP8), macrophage activation (i.e., CD163, CD206, galectin-1), wound healing/matrix degradation (i.e., nidogen-1, decorin), and IL-16 characterized the aggressive proliferative LN classes and significantly correlated with histological activity. A decline of these biomarkers after 3 months of treatment predicted the 1-year response more robustly than proteinuria, the standard of care (AUC: CD206 0.91, EGFR 0.9, CD163 0.89, proteinuria 0.8). Candidate biomarkers were validated and provide potentially treatable targets. We propose these biomarkers of intrarenal immunological activity as noninvasive tools to diagnose LN and guide treatment and as surrogate endpoints for clinical trials. These findings provide insights into the processes involved in LN activity. This data set is a public resource to generate and test hypotheses and validate biomarkers.

High-dimensional phenotyping to define the genetic basis of cellular morphology.

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 < 10-6) 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.

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

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.

Human leukocyte antigen-DQA1*04:01 and rs2040406 variants are associated with elevated risk of childhood Burkitt lymphoma.

Burkitt lymphoma (BL) is responsible for many childhood cancers in sub-Saharan Africa, where it is linked to recurrent or chronic infection by Epstein-Barr virus or Plasmodium falciparum. However, whether human leukocyte antigen (HLA) polymorphisms, which regulate immune response, are associated with BL has not been well investigated, which limits our understanding of BL etiology. Here we investigate this association among 4,645 children aged 0-15 years, 800 with BL, enrolled in Uganda, Tanzania, Kenya, and Malawi. HLA alleles are imputed with accuracy >90% for HLA class I and 85-89% for class II alleles. BL risk is elevated with HLA-DQA1*04:01 (adjusted odds ratio [OR] = 1.61, 95% confidence interval [CI] = 1.32-1.97, P = 3.71 × 10-6), with rs2040406(G) in HLA-DQA1 region (OR = 1.43, 95% CI = 1.26-1.63, P = 4.62 × 10-8), and with amino acid Gln at position 53 versus other variants in HLA-DQA1 (OR = 1.36, P = 2.06 × 10-6). The associations with HLA-DQA1*04:01 (OR = 1.29, P = 0.03) and rs2040406(G) (OR = 1.68, P = 0.019) persist in mutually adjusted models. The higher risk rs2040406(G) variant for BL is associated with decreased HLA-DQB1 expression in eQTLs in EBV transformed lymphocytes. Our results support the role of HLA variation in the etiology of BL and suggest that a promising area of research might be understanding the link between HLA variation and EBV control.

Associations Between Rheumatoid Arthritis Clinical Factors and Synovial Cell Types and States.

OBJECTIVE: Recent studies have uncovered diverse cell types and states in the rheumatoid arthritis (RA) synovium; however, limited data exist correlating these findings with patient-level clinical information. Using the largest cohort to date with clinical and multicell data, we determined associations between RA clinical factors with cell types and states in the RA synovium. METHODS: The Accelerated Medicines Partnership Rheumatoid Arthritis study recruited patients with active RA who were not receiving disease-modifying antirheumatic drugs (DMARDs) or who had an inadequate response to methotrexate (MTX) or tumor necrosis factor inhibitors. RA clinical factors were systematically collected. Biopsies were performed on an inflamed joint, and tissue were disaggregated and processed with a cellular indexing of transcriptomes and epitopes sequencing pipeline from which the following cell type percentages and cell type abundance phenotypes (CTAPs) were derived: endothelial, fibroblast, and myeloid (EFM); fibroblasts; myeloid; T and B cells; T cells and fibroblasts (TF); and T and myeloid cells. Correlations were measured between RA clinical factors, cell type percentage, and CTAPs. RESULTS: We studied 72 patients (mean age 57 years, 75% women, 83% seropositive, mean RA duration 6.6 years, mean Disease Activity Score-28 C-reactive Protein 3 [DAS28-CRP3] score 4.8). Higher DAS28-CRP3 correlated with a higher T cell percentage (P < 0.01). Those receiving MTX and not a biologic DMARD (bDMARD) had a higher percentage of B cells versus those receiving no DMARDs (P < 0.01). Most of those receiving bDMARDs were categorized as EFM (57%), whereas none were TF. No significant difference was observed across CTAPs for age, sex, RA disease duration, or DAS28-CRP3. CONCLUSION: In this comprehensive screen of clinical factors, we observed differential associations between DMARDs and cell phenotypes, suggesting that RA therapies, more than other clinical factors, may impact cell type/state in the synovium and ultimately influence response to subsequent therapies.

Dynamic regulatory elements in single-cell multimodal data implicate key immune cell states enriched for autoimmune disease heritability.

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+CXCL10+ myeloid cell states. We argue that dynamic regulatory elements can help identify precise cell states enriched for disease-critical genetic variation.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution.

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.

Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant.

TRAF1/C5 was among the first loci shown to confer risk for inflammatory arthritis in the absence of an associated coding variant, but its genetic mechanism remains undefined. Using Immunochip data from 3,939 patients with juvenile idiopathic arthritis (JIA) and 14,412 control individuals, we identified 132 plausible common non-coding variants, reduced serially by single-nucleotide polymorphism sequencing (SNP-seq), electrophoretic mobility shift, and luciferase studies to the single variant rs7034653 in the third intron of TRAF1. Genetically manipulated experimental cells and primary monocytes from genotyped donors establish that the risk G allele reduces binding of Fos-related antigen 2 (FRA2), encoded by FOSL2, resulting in reduced TRAF1 expression and enhanced tumor necrosis factor (TNF) production. Conditioning on this JIA variant eliminated attributable risk for rheumatoid arthritis, implicating a mechanism shared across the arthritis spectrum. These findings reveal that rs7034653, FRA2, and TRAF1 mediate a pathway through which a non-coding functional variant drives risk of inflammatory arthritis in children and adults.

Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin.

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.

Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease.

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.

The T cell receptor sequence influences the likelihood of T cell memory formation.

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 αßTCR 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.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians.

A quarter of humanity is estimated to be latently infected with Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n=63) or did not progress to TB (controls, n=63). Transcriptomic profiling of monocyte-derived dendritic cells (DCs) and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Five genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.