論文

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.

Systemic lupus erythematosus (SLE) is prototypical autoimmune disease driven by pathological T cell–B cell interactions1,2. Expansion of T follicular helper (TFH) and T peripheral helper (TPH) cells, two T cell populations that provide help to B cells, is a prominent feature of SLE3,4. Human TFH and TPH cells characteristically produce high levels of the B cell chemoattractant CXCL13 (refs. 5,6), yet regulation of T cell CXCL13 production and the relationship between CXCL13+ T cells and other T cell states remains unclear. Here, we identify an imbalance in CD4+ T cell phenotypes in patients with SLE, with expansion of PD-1+/ICOS+ CXCL13+ T cells and reduction of CD96hi IL-22+ T cells. Using CRISPR screens, we identify the aryl hydrocarbon receptor (AHR) as a potent negative regulator of CXCL13 production by human CD4+ T cells. Transcriptomic, epigenetic and functional studies demonstrate that AHR coordinates with AP-1 family member JUN to prevent CXCL13+ TPH/TFH cell differentiation and promote an IL-22+ phenotype. Type I interferon, a pathogenic driver of SLE7, opposes AHR and JUN to promote T cell production of CXCL13. These results place CXCL13+ TPH/TFH cells on a polarization axis opposite from T helper 22 (TH22) cells and reveal AHR, JUN and interferon as key regulators of these divergent T cell states.

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

Alternative splicing events are a major causal mechanism for complex traits, but they have been understudied due to the limitation of short-read sequencing. Here, we generate a full-length isoform annotation of human immune cells from an individual by long-read sequencing for 29 cell subsets. This contains a number of unannotated transcripts and isoforms such as a read-through transcript of TOMM40-APOE in the Alzheimer’s disease locus. We profile characteristics of isoforms and show that repetitive elements significantly explain the diversity of unannotated isoforms, providing insight into the human genome evolution. In addition, some of the isoforms are expressed in a cell-type specific manner, whose alternative 3’-UTRs usage contributes to their specificity. Further, we identify disease-associated isoforms by isoform switch analysis and by integration of several quantitative trait loci analyses with genome-wide association study data. Our findings will promote the elucidation of the mechanism of complex diseases via alternative splicing.

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.

Objective Systemic lupus erythematosus (SLE), an autoimmune disorder, has been associated withnearly 100 susceptibility loci. Nevertheless, these loci only partially explain SLE heritability and their putative causal variants are rarely prioritised, which make challenging to elucidate disease biology. To detect new SLE loci and causal variants, we performed the largest genome-wide meta-analysis for SLE in East Asian populations. Methods We newly genotyped 10 029 SLE cases and 180 167 controls and subsequently meta-analysed them jointly with 3348 SLE cases and 14 826 controls from published studies in East Asians. We further applied a Bayesian statistical approach to localise the putative causal variants for SLE associations. Results We identified 113 genetic regions including 46 novel loci at genome-wide significance (p<5×10 -8). Conditional analysis detected 233 association signals within these loci, which suggest widespread allelic heterogeneity. We detected genome-wide associations at six new missense variants. Bayesian statistical fine-mapping analysis prioritised the putative causal variants to a small set of variants (95% credible set size ≤10) for 28 association signals. We identified 110 putative causal variants with posterior probabilities ≥0.1 for 57 SLE loci, among which we prioritised 10 most likely putative causal variants (posterior probability ≥0.8). Linkage disequilibrium score regression detected genetic correlations for SLE with albumin/globulin ratio (r g =-0.242) and non-albumin protein (r g =0.238). Conclusion Thisstudy reiterates the power of large-scale genome-wide meta-analysis for novel genetic discovery. These findings shed light on genetic and biological understandings of SLE.

Mobile genetic elements (MEs) are heritable mutagens that recursively generate structural variants (SVs). ME variants (MEVs) are difficult to genotype and integrate in statistical genetics, obscuring their impact on genome diversification and traits. We developed a tool that accurately genotypes MEVs using short-read whole-genome sequencing (WGS) and applied it to global human populations. We find unexpected population-specific MEV differences, including an Alu insertion distribution distinguishing Japanese from other populations. Integrating MEVs with expression quantitative trait loci (eQTL) maps shows that MEV classes regulate tissue-specific gene expression by shared mechanisms, including creating or attenuating enhancers and recruiting post-transcriptional regulators, supporting class-wide interpretability. MEVs more often associate with gene expression changes than SNVs, thus plausibly impacting traits. Performing genome-wide association study (GWAS) with MEVs pinpoints potential causes of disease risk, including a LINE-1 insertion associated with keloid and fasciitis. This work implicates MEVs as drivers of human divergence and disease risk.

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 × 10−8), 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.

Objectives Despite the involvement of B cells in the pathogenesis of immune-mediated diseases (IMDs), biological mechanisms underlying their function are scarcely understood. To overcome this gap, here we constructed and investigated a large-scale repertoire catalogue of five B cell subsets of patients with IMDs. Methods We mapped B cell receptor regions from RNA sequencing data of sorted B cell subsets. Our dataset consisted of 595 donors under IMDs and health. We characterised the repertoire features from various aspects, including their association with immune cell transcriptomes and clinical features and their response to belimumab treatment. Results Heavy-chain complementarity-determining region 3 (CDR-H3) length among naïve B cells was shortened among autoimmune diseases. Strong negative correlation between interferon signature strength and CDR-H3 length was observed in naïve B cells and suggested the role for interferon in premature B cell development. VDJ gene usage was skewed especially in plasmablasts and unswitched-memory B cells of patients with systemic lupus erythematosus (SLE). We developed a scoring system to quantify this skewing, and it positively correlated with peripheral helper T cell transcriptomic signatures and negatively correlated with the amount of somatic hyper mutations in plasmablasts, suggesting the association of extrafollicular pathway. Further, this skewing led to high usage of IGHV4-34 gene with 9G4 idiotypes in unswitched-memory B cells, which showed a prominent positive correlation with disease activity in SLE. Gene usage skewing in unswitched-memory B cells was ameliorated after belimumab treatment. Conclusions Our multimodal repertoire analysis enabled us the system-level understanding of B cell abnormality in diseases.

Multimodal T cell profiling can enable more precise characterization of elusive cell states underlying disease. Here, we integrated single-cell RNA and surface protein data from 500,089 memory T cells to define 31 cell states from 259 individuals in a Peruvian tuberculosis (TB) progression cohort. At immune steady state >4 years after infection and disease resolution, we found that, after accounting for significant effects of age, sex, season and genetic ancestry on T cell composition, a polyfunctional type 17 helper T (TH17) cell–like effector state was reduced in abundance and function in individuals who previously progressed from Mycobacterium tuberculosis (M.tb) infection to active TB disease. These cells are capable of responding to M.tb peptides. Deconvoluting this state—uniquely identifiable with multimodal analysis—from public data demonstrated that its depletion may precede and persist beyond active disease. Our study demonstrates the power of integrative multimodal single-cell profiling to define cell states relevant to disease and other traits.

Memory-phenotype (MP) CD4+ T lymphocytes develop from naïve cells via self-recognition at homeostasis. While previous studies defined MP cells as a heterogeneous population that comprises T helper 1 (TH1)/17–like subsets, functional significance of the T-bet− Rorγt− subpopulation remains unknown. Here we show that MP lymphocytes as a whole population can differentiate into TH1/17/regulatory T (Treg) cells to mediate mild and persistent inflammation in lymphopenic environments, whereas naïve cells exhibit strong, TH1-dominated responses. Moreover, we demonstrate that MP lymphocytes comprise not only TH1/17-differentiated subsets but a polyclonal, transcriptomically immature “undifferentiated” subpopulation at homeostasis. Furthermore, our data argue that while the T-bet+ Rorγt− MP subset is terminally TH1-differentiated, its undifferentiated counterpart retains the capacity to rapidly proliferate to differentiate into TH1/17/Treg cells, with the latter response tonically constrained by preexisting Treg cells. Together, our results identify undifferentiated MP CD4+ T lymphocytes as a unique precursor that has a diverse differentiation potential to generate TH1/17/Treg cells to contribute to pathogenesis of inflammation.

Infectious disease is the result of interactions between host and pathogen and can depend on genetic variations in both. We conduct a genome-to-genome study of paired human and Mycobacterium tuberculosis genomes from a cohort of 1556 tuberculosis patients in Lima, Peru. We identify an association between a human intronic variant (rs3130660, OR = 10.06, 95%CI: 4.87 − 20.77, P = 7.92 × 10−8) in the FLOT1 gene and a subclavaluee of Mtb Lineage 2. In a human macrophage infection model, we observe hosts with the rs3130660-A allele exhibited stronger interferon gene signatures. The interacting strains have altered redox states due to a thioredoxin reductase mutation. We investigate this association in a 2020 cohort of 699 patients recruited during the COVID-19 pandemic. While the prevalence of the interacting strain almost doubled between 2010 and 2020, its infection is not associated with rs3130660 in this recent cohort. These findings suggest a complex interplay among host, pathogen, and environmental factors in tuberculosis dynamics.

Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (ntotal = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified latent genetic components, which pinpointed responsible variants and biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (for example, allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human diseases through genetics.