Oral and non-oral lichen planus show genetic heterogeneity and differential risk for autoimmune disease and oral cancer.

Lichen planus (LP) is a T-cell-mediated inflammatory disease affecting squamous epithelia in many parts of the body, most often the skin and oral mucosa. Cutaneous LP is usually transient and oral LP (OLP) is most often chronic, so we performed a large-scale genetic and epidemiological study of LP to address whether the oral and non-oral subgroups have shared or distinct underlying pathologies and their overlap with autoimmune disease. Using lifelong records covering diagnoses, procedures, and clinic identity from 473,580 individuals in the FinnGen study, genome-wide association analyses were conducted on carefully constructed subcategories of OLP (n = 3,323) and non-oral LP (n = 4,356) and on the combined group. We identified 15 genome-wide significant associations in FinnGen and an additional 12 when meta-analyzed with UKBB (27 independent associations at 25 distinct genomic locations), most of which are shared between oral and non-oral LP. Many associations coincide with known autoimmune disease loci, consistent with the epidemiologic enrichment of LP with hypothyroidism and other autoimmune diseases. Notably, a third of the FinnGen associations demonstrate significant differences between OLP and non-OLP. We also observed a 13.6-fold risk for tongue cancer and an elevated risk for other oral cancers in OLP, in agreement with earlier reports that connect LP with higher cancer incidence. In addition to a large-scale dissection of LP genetics and comorbidities, our study demonstrates the use of comprehensive, multidimensional health registry data to address outstanding clinical questions and reveal underlying biological mechanisms in common but understudied diseases.

Efficient and accurate mixed model association tool for single-cell eQTL analysis.

Understanding the genetic basis of gene expression can help us understand the molecular underpinnings of human traits and disease. Expression quantitative trait locus (eQTL) mapping can help in studying this relationship but have been shown to be very cell-type specific, motivating the use of single-cell RNA sequencing and single-cell eQTLs to obtain a more granular view of genetic regulation. Current methods for single-cell eQTL mapping either rely on the "pseudobulk" approach and traditional pipelines for bulk transcriptomics or do not scale well to large datasets. Here, we propose SAIGE-QTL, a robust and scalable tool that can directly map eQTLs using single-cell profiles without needing aggregation at the pseudobulk level. Additionally, SAIGE-QTL allows for testing the effects of less frequent/rare genetic variation through set-based tests, which is traditionally excluded from eQTL mapping studies. We evaluate the performance of SAIGE-QTL on both real and simulated data and demonstrate the improved power for eQTL mapping over existing pipelines.

Blended Genome Exome (BGE) as a Cost Efficient Alternative to Deep Whole Genomes or Arrays.

Genomic scientists have long been promised cheaper DNA sequencing, but deep whole genomes are still costly, especially when considered for large cohorts in population-level studies. More affordable options include microarrays + imputation, whole exome sequencing (WES), or low-pass whole genome sequencing (WGS) + imputation. WES + array + imputation has recently been shown to yield 99% of association signals detected by WGS. However, a method free from ascertainment biases of arrays or the need for merging different data types that still benefits from deeper exome coverage to enhance novel coding variant detection does not exist. We developed a new, combined, "Blended Genome Exome" (BGE) in which a whole genome library is generated, an aliquot of that genome is amplified by PCR, the exome regions are selected and enriched, and the genome and exome libraries are combined back into a single tube for sequencing (33% exome, 67% genome). This creates a single CRAM with a low-coverage whole genome (2-3x) combined with a higher coverage exome (30-40x). This BGE can be used for imputing common variants throughout the genome as well as for calling rare coding variants. We tested this new method and observed >99% r 2 concordance between imputed BGE data and existing 30x WGS data for exome and genome variants. BGE can serve as a useful and cost-efficient alternative sequencing product for genomic researchers, requiring ten-fold less sequencing compared to 30x WGS without the need for complicated harmonization of array and sequencing data.

An esophagus cell atlas reveals dynamic rewiring during active eosinophilic esophagitis and remission.

Coordinated cell interactions within the esophagus maintain homeostasis, and disruption can lead to eosinophilic esophagitis (EoE), a chronic inflammatory disease with poorly understood pathogenesis. We profile 421,312 individual cells from the esophageal mucosa of 7 healthy and 15 EoE participants, revealing 60 cell subsets and functional alterations in cell states, compositions, and interactions that highlight previously unclear features of EoE. Active disease displays enrichment of ALOX15+ macrophages, PRDM16+ dendritic cells expressing the EoE risk gene ATP10A, and cycling mast cells, with concomitant reduction of TH17 cells. Ligand-receptor expression uncovers eosinophil recruitment programs, increased fibroblast interactions in disease, and IL-9+IL-4+IL-13+ TH2 and endothelial cells as potential mast cell interactors. Resolution of inflammation-associated signatures includes mast and CD4+ TRM cell contraction and cell type-specific downregulation of eosinophil chemoattractant, growth, and survival factors. These cellular alterations in EoE and remission advance our understanding of eosinophilic inflammation and opportunities for therapeutic intervention.

Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria.

Accumulating evidence suggests that cardiovascular disease (CVD) is associated with an altered gut microbiome. Our understanding of the underlying mechanisms has been hindered by lack of matched multi-omic data with diagnostic biomarkers. To comprehensively profile gut microbiome contributions to CVD, we generated stool metagenomics and metabolomics from 1,429 Framingham Heart Study participants. We identified blood lipids and cardiovascular health measurements associated with microbiome and metabolome composition. Integrated analysis revealed microbial pathways implicated in CVD, including flavonoid, γ-butyrobetaine, and cholesterol metabolism. Species from the Oscillibacter genus were associated with decreased fecal and plasma cholesterol levels. Using functional prediction and in vitro characterization of multiple representative human gut Oscillibacter isolates, we uncovered conserved cholesterol-metabolizing capabilities, including glycosylation and dehydrogenation. These findings suggest that cholesterol metabolism is a broad property of phylogenetically diverse Oscillibacter spp., with potential benefits for lipid homeostasis and cardiovascular health.

Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease.

Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.

Comprehensive Association Analyses of Extraintestinal Manifestations in Inflammatory Bowel Disease.

BACKGROUND & AIMS: Patients with inflammatory bowel disease (IBD) frequently develop extraintestinal manifestations (EIMs) that contribute substantially to morbidity. We assembled the largest multicohort data set to date to investigate the clinical, serologic, and genetic factors associated with EIM complications in IBD. METHODS: Data were available in 12,083 unrelated European ancestry IBD cases with presence or absence of EIMs (eg, ankylosing spondylitis [ankylosing spondylitis and sacroiliitis], primary sclerosing cholangitis [PSC], peripheral arthritis, and skin and ocular manifestations) across 4 cohorts (Cedars-Sinai Medical Center, National Institute for Diabetes and Digestive and Kidney Diseases IBD Genetics Consortium, Sinai Helmsley Alliance for Research Excellence Consortium, and Risk Stratification and Identification of Immunogenetic and Microbial Markers of Rapid Disease Progression in Children with Crohn's Disease cohort). Clinical and serologic parameters were analyzed by means of univariable and multivariable regression analyses using a mixed-effects model. Within-case logistic regression was performed to assess genetic associations. RESULTS: Most EIMs occurred more commonly in female subjects (overall EIM: P = 9.0E-05, odds ratio [OR], 1.2; 95% CI, 1.1-1.4), with CD (especially colonic disease location; P = 9.8E-09, OR, 1.7; 95% CI, 1.4-2.0), and in subjects who required surgery (both CD and UC; P = 3.6E-19, OR, 1.7; 95% CI, 1.5-1.9). Smoking increased risk of EIMs except for PSC, where there was a "protective" effect. Multiple serologic associations were observed, including with PSC (anti-nuclear cytoplasmic antibody; IgG and IgA, anti-Saccharomyces cerevisiae antibodies; and anti-flagellin) and any EIM (anti-nuclear cytoplasmic antibody; IgG and IgA, anti-Saccharomyces cerevisiae antibodies; and anti-Pseudomonas fluorescens-associated sequence). We identified genome-wide significant associations within major histocompatibility complex (ankylosing spondylitis and sacroiliitis, P = 1.4E-15; OR, 2.5; 95% CI, 2.0-3.1; PSC, P = 2.7E-10; OR, 2.8; 95% CI, 2.0-3.8; ocular, P = 2E-08, OR, 3.6; 95% CI, 2.3-5.6; and overall EIM, P = 8.4E-09; OR, 2.2; 95% CI, 1.7-2.9) and CPEB4 (skin, P = 2.7E-08; OR, 1.5; 95% CI, 1.3-1.8). Genetic associations implicated tumor necrosis factor, JAK-STAT, and IL6 as potential targets for EIMs. Contrary to previous reports, only 2% of our subjects had multiple EIMs and most co-occurrences were negatively correlated. CONCLUSIONS: We have identified demographic, clinical, and genetic associations with EIMs that revealed underlying mechanisms and implicated novel and existing drug targets-important steps toward a more personalized approach to IBD management.

Translational genetics identifies a phosphorylation switch in CARD9 required for innate inflammatory responses.

Population genetics continues to identify genetic variants associated with diseases of the immune system and offers a unique opportunity to discover mechanisms of immune regulation. Multiple genetic variants linked to severe fungal infections and autoimmunity are associated with caspase recruitment domain-containing protein 9 (CARD9). We leverage the CARD9 R101C missense variant to uncover a biochemical mechanism of CARD9 activation essential for antifungal responses. We demonstrate that R101C disrupts a critical signaling switch whereby phosphorylation of S104 releases CARD9 from an autoinhibited state to promote inflammatory responses in myeloid cells. Furthermore, we show that CARD9 R101C exerts dynamic effects on the skin cellular contexture during fungal infection, corrupting inflammatory signaling and cell-cell communication circuits. Card9 R101C mice fail to control dermatophyte infection in the skin, resulting in high fungal burden, yet show minimal signs of inflammation. Together, we demonstrate how translational genetics reveals molecular and cellular mechanisms of innate immune regulation.

Absence of a pancreatic microbiome in intraductal papillary mucinous neoplasm.

OBJECTIVE: This study aims to validate the existence of a microbiome within intraductal papillary mucinous neoplasm (IPMN) that can be differentiated from the taxonomically diverse DNA background of next-generation sequencing procedures. DESIGN: We generated 16S rRNA amplicon sequencing data to analyse 338 cyst fluid samples from 190 patients and 19 negative controls, the latter collected directly from sterile syringes in the operating room. A subset of samples (n=20) and blanks (n=5) were spiked with known concentrations of bacterial cells alien to the human microbiome to infer absolute abundances of microbial traces. All cyst fluid samples were obtained intraoperatively and included IPMNs with various degrees of dysplasia as well as other cystic neoplasms. Follow-up culturing experiments were conducted to assess bacterial growth for microbiologically significant signals. RESULTS: Microbiome signatures of cyst fluid samples were inseparable from those of negative controls, with no difference in taxonomic diversity, and microbial community composition. In a patient subgroup that had recently undergone invasive procedures, a bacterial signal was evident. This outlier signal was not characterised by higher taxonomic diversity but by an increased dominance index of a gut-associated microbe, leading to lower taxonomic evenness compared with the background signal. CONCLUSION: The 'microbiome' of IPMNs and other pancreatic cystic neoplasms does not deviate from the background signature of negative controls, supporting the concept of a sterile environment. Outlier signals may appear in a small fraction of patients following recent invasive endoscopic procedures. No associations between microbial patterns and clinical or cyst parameters were apparent.

Chemical tools to expand the ligandable proteome: diversity-oriented synthesis-based photoreactive stereoprobes.

Chemical proteomics enables the global assessment of small molecule-protein interactions in native biological systems and has emerged as a versatile approach for ligand discovery. The range of small molecules explored by chemical proteomics has, however, been limited. Here, we describe a diversity-oriented synthesis (DOS)-inspired library of stereochemically-defined compounds bearing diazirine and alkyne units for UV light-induced covalent modification and click chemistry enrichment of interacting proteins, respectively. We find that these 'photo-stereoprobes' interact in a stereoselective manner with hundreds of proteins from various structural and functional classes in human cells and demonstrate that these interactions can form the basis for high-throughput screening-compatible nanoBRET assays. Integrated phenotypic analysis and chemical proteomics identified photo-stereoprobes that modulate autophagy by engaging the mitochondrial serine protease CLPP. Our findings show the utility of photo-stereoprobes for expanding the ligandable proteome, furnishing target engagement assays, and discovering and characterizing bioactive small molecules by cell-based screening.

Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA.

Single-cell RNA sequencing and other profiling assays have helped interrogate cells at unprecedented resolution and scale, but are inherently destructive. Raman microscopy reports on the vibrational energy levels of proteins and metabolites in a label-free and nondestructive manner at subcellular spatial resolution, but it lacks genetic and molecular interpretability. Here we present Raman2RNA (R2R), a method to infer single-cell expression profiles in live cells through label-free hyperspectral Raman microscopy images and domain translation. We predict single-cell RNA sequencing profiles nondestructively from Raman images using either anchor-based integration with single molecule fluorescence in situ hybridization, or anchor-free generation with adversarial autoencoders. R2R outperformed inference from brightfield images (cosine similarities: R2R >0.85 and brightfield <0.15). In reprogramming of mouse fibroblasts into induced pluripotent stem cells, R2R inferred the expression profiles of various cell states. With live-cell tracking of mouse embryonic stem cell differentiation, R2R traced the early emergence of lineage divergence and differentiation trajectories, overcoming discontinuities in expression space. R2R lays a foundation for future exploration of live genomic dynamics.

Linking microbial genes to plasma and stool metabolites uncovers host-microbial interactions underlying ulcerative colitis disease course.

Understanding the role of the microbiome in inflammatory diseases requires the identification of microbial effector molecules. We established an approach to link disease-associated microbes to microbial metabolites by integrating paired metagenomics, stool and plasma metabolomics, and culturomics. We identified host-microbial interactions correlated with disease activity, inflammation, and the clinical course of ulcerative colitis (UC) in the Predicting Response to Standardized Colitis Therapy (PROTECT) pediatric inception cohort. In severe disease, metabolite changes included increased dipeptides and tauro-conjugated bile acids (BAs) and decreased amino-acid-conjugated BAs in stool, whereas in plasma polyamines (N-acetylputrescine and N1-acetylspermidine) increased. Using patient samples and Veillonella parvula as a model, we uncovered nitrate- and lactate-dependent metabolic pathways, experimentally linking V. parvula expansion to immunomodulatory tryptophan metabolite production. Additionally, V. parvula metabolizes immunosuppressive thiopurine drugs through xdhA xanthine dehydrogenase, potentially impairing the therapeutic response. Our findings demonstrate that the microbiome contributes to disease-associated metabolite changes, underscoring the importance of these interactions in disease pathology and treatment.

Host genetic regulation of human gut microbial structural variation.

Although the impact of host genetics on gut microbial diversity and the abundance of specific taxa is well established1-6, little is known about how host genetics regulates the genetic diversity of gut microorganisms. Here we conducted a meta-analysis of associations between human genetic variation and gut microbial structural variation in 9,015 individuals from four Dutch cohorts. Strikingly, the presence rate of a structural variation segment in Faecalibacterium prausnitzii that harbours an N-acetylgalactosamine (GalNAc) utilization gene cluster is higher in individuals who secrete the type A oligosaccharide antigen terminating in GalNAc, a feature that is jointly determined by human ABO and FUT2 genotypes, and we could replicate this association in a Tanzanian cohort. In vitro experiments demonstrated that GalNAc can be used as the sole carbohydrate source for F. prausnitzii strains that carry the GalNAc-metabolizing pathway. Further in silico and in vitro studies demonstrated that other ABO-associated species can also utilize GalNAc, particularly Collinsella aerofaciens. The GalNAc utilization genes are also associated with the host's cardiometabolic health, particularly in individuals with mucosal A-antigen. Together, the findings of our study demonstrate that genetic associations across the human genome and bacterial metagenome can provide functional insights into the reciprocal host-microbiome relationship.

Reverse metabolomics for the discovery of chemical structures from humans.

Determining the structure and phenotypic context of molecules detected in untargeted metabolomics experiments remains challenging. Here we present reverse metabolomics as a discovery strategy, whereby tandem mass spectrometry spectra acquired from newly synthesized compounds are searched for in public metabolomics datasets to uncover phenotypic associations. To demonstrate the concept, we broadly synthesized and explored multiple classes of metabolites in humans, including N-acyl amides, fatty acid esters of hydroxy fatty acids, bile acid esters and conjugated bile acids. Using repository-scale analysis1,2, we discovered that some conjugated bile acids are associated with inflammatory bowel disease (IBD). Validation using four distinct human IBD cohorts showed that cholic acids conjugated to Glu, Ile/Leu, Phe, Thr, Trp or Tyr are increased in Crohn's disease. Several of these compounds and related structures affected pathways associated with IBD, such as interferon-γ production in CD4+ T cells3 and agonism of the pregnane X receptor4. Culture of bacteria belonging to the Bifidobacterium, Clostridium and Enterococcus genera produced these bile amidates. Because searching repositories with tandem mass spectrometry spectra has only recently become possible, this reverse metabolomics approach can now be used as a general strategy to discover other molecules from human and animal ecosystems.

Identification of highly selective SIK1/2 inhibitors that modulate innate immune activation and suppress intestinal inflammation.

The salt-inducible kinases (SIK) 1-3 are key regulators of pro- versus anti-inflammatory cytokine responses during innate immune activation. The lack of highly SIK-family or SIK isoform-selective inhibitors suitable for repeat, oral dosing has limited the study of the optimal SIK isoform selectivity profile for suppressing inflammation in vivo. To overcome this challenge, we devised a structure-based design strategy for developing potent SIK inhibitors that are highly selective against other kinases by engaging two differentiating features of the SIK catalytic site. This effort resulted in SIK1/2-selective probes that inhibit key intracellular proximal signaling events including reducing phosphorylation of the SIK substrate cAMP response element binding protein (CREB) regulated transcription coactivator 3 (CRTC3) as detected with an internally generated phospho-Ser329-CRTC3-specific antibody. These inhibitors also suppress production of pro-inflammatory cytokines while inducing anti-inflammatory interleukin-10 in activated human and murine myeloid cells and in mice following a lipopolysaccharide challenge. Oral dosing of these compounds ameliorates disease in a murine colitis model. These findings define an approach to generate highly selective SIK1/2 inhibitors and establish that targeting these isoforms may be a useful strategy to suppress pathological inflammation.

Early cellular and molecular signatures correlate with severity of West Nile virus infection.

Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases of encephalitis and death. To identify cellular and molecular signatures distinguishing WNV severity, we employed systems profiling of peripheral blood from asymptomatic and severely ill individuals infected with WNV. We interrogated immune responses longitudinally from acute infection through convalescence employing single-cell protein and transcriptional profiling complemented with matched serum proteomics and metabolomics as well as multi-omics analysis. At the acute time point, we detected both elevation of pro-inflammatory markers in innate immune cell types and reduction of regulatory T cell activity in participants with severe infection, whereas asymptomatic donors had higher expression of genes associated with anti-inflammatory CD16+ monocytes. Therefore, we demonstrated the potential of systems immunology using multiple cell-type and cell-state-specific analyses to identify correlates of infection severity and host cellular activity contributing to an effective anti-viral response.

Cytotoxic Th1 cells mushroom after fungal exposures in Crohn's disease.

Fungi are consistently enriched in inflamed intestines, with elusive effects on host immunity. In a recent issue of Nature Medicine, Martini et al. identify a subset of Th1 cells able to lyse the epithelium, enriched in Crohn's disease patient samples after fungal exposure.

A distinct human cell type expressing MHCII and RORγt with dual characteristics of dendritic cells and type 3 innate lymphoid cells.

Recent studies have characterized various mouse antigen-presenting cells (APCs) expressing the lymphoid-lineage transcription factor RORγt (Retinoid-related orphan receptor gamma t), which exhibit distinct phenotypic features and are implicated in the induction of peripheral regulatory T cells (Tregs) and immune tolerance to microbiota and self-antigens. These APCs encompass Janus cells and Thetis cell subsets, some of which express the AutoImmune REgulator (AIRE). RORγt+ MHCII+ type 3 innate lymphoid cells (ILC3) have also been implicated in the instruction of microbiota-specific Tregs. While RORγt+ APCs have been actively investigated in mice, the identity and function of these cell subsets in humans remain elusive. Herein, we identify a rare subset of RORγt+ cells with dendritic cell (DC) features through integrated single-cell RNA sequencing and single-cell ATAC sequencing. These cells, which we term RORγt+ DC-like cells (R-DC-like), exhibit DC morphology, express the MHC class II machinery, and are distinct from all previously reported DC and ILC3 subsets, but share transcriptional and epigenetic similarities with DC2 and ILC3. We have developed procedures to isolate and expand them in vitro, enabling their functional characterization. R-DC-like cells proliferate in vitro, continue to express RORγt, and differentiate into CD1c+ DC2-like cells. They stimulate the proliferation of allogeneic T cells. The identification of human R-DC-like cells with proliferative potential and plasticity toward CD1c+ DC2-like cells will prompt further investigation into their impact on immune homeostasis, inflammation, and autoimmunity.

Protein Language Models Uncover Carbohydrate-Active Enzyme Function in Metagenomics.

In metagenomics, the pool of uncharacterized microbial enzymes presents a challenge for functional annotation. Among these, carbohydrate-active enzymes (CAZymes) stand out due to their pivotal roles in various biological processes related to host health and nutrition. Here, we present CAZyLingua, the first tool that harnesses protein language model embeddings to build a deep learning framework that facilitates the annotation of CAZymes in metagenomic datasets. Our benchmarking results showed on average a higher F1 score (reflecting an average of precision and recall) on the annotated genomes of Bacteroides thetaiotaomicron, Eggerthella lenta and Ruminococcus gnavus compared to the traditional sequence homology-based method in dbCAN2. We applied our tool to a paired mother/infant longitudinal dataset and revealed unannotated CAZymes linked to microbial development during infancy. When applied to metagenomic datasets derived from patients affected by fibrosis-prone diseases such as Crohn's disease and IgG4-related disease, CAZyLingua uncovered CAZymes associated with disease and healthy states. In each of these metagenomic catalogs, CAZyLingua discovered new annotations that were previously overlooked by traditional sequence homology tools. Overall, the deep learning model CAZyLingua can be applied in combination with existing tools to unravel intricate CAZyme evolutionary profiles and patterns, contributing to a more comprehensive understanding of microbial metabolic dynamics.