A unified model-based framework for doublet or multiplet detection in single-cell multiomics data.

Droplet-based single-cell sequencing techniques rely on the fundamental assumption that each droplet encapsulates a single cell, enabling individual cell omics profiling. However, the inevitable issue of multiplets, where two or more cells are encapsulated within a single droplet, can lead to spurious cell type annotations and obscure true biological findings. The issue of multiplets is exacerbated in single-cell multiomics settings, where integrating cross-modality information for clustering can inadvertently promote the aggregation of multiplet clusters and increase the risk of erroneous cell type annotations. Here, we propose a compound Poisson model-based framework for multiplet detection in single-cell multiomics data. Leveraging experimental cell hashing results as the ground truth for multiplet status, we conducted trimodal DOGMA-seq experiments and generated 17 benchmarking datasets from two tissues, involving a total of 280,123 droplets. We demonstrated that the proposed method is an essential tool for integrating cross-modality multiplet signals, effectively eliminating multiplet clusters in single-cell multiomics data-a task at which the benchmarked single-omics methods proved inadequate.

After surgically induced remission, ileal and colonic mucosa-associated microbiota predicts Crohn's disease recurrence.

BACKGROUND AND AIMS: Investigating the tissue-associated microbiota after surgically induced remission may help to understand the mechanisms initiating intestinal inflammation in Crohn's disease. METHODS: Crohn's disease patients undergoing ileocolic resection were prospectively recruited in six academic centers. Biopsy samples from the neoterminal ileum, colon and rectosigmoid were obtained from colonoscopies performed after surgery. Microbial DNA was extracted for 16S rRNA gene sequencing. Microbial diversity and taxonomic differential relative abundance were analyzed. A random forest model was applied to analyze the performance of clinical and microbial features to predict recurrence. A Rutgeerts score ≥i2 was deemed as endoscopic recurrence. RESULTS: A total of 349 postoperative colonoscopies and 944 biopsy samples from 262 Crohn's disease patients were analyzed. Ileal inflammation accounted for most of the explained variance of the ileal and colonic mucosa-associated microbiota. Samples obtained from 97 patients who were in surgically induced remission at first postoperative colonoscopy who went on to develop endoscopic recurrence at second colonoscopy showed lower diversity and microbial deviations when compared to patients who remained in endoscopic remission. Depletion of genus Anaerostipes and increase of several genera from class Gammaproteobacteria at the three biopsy sites increase the risk of further recurrence. Gut microbiome was able to predict future recurrence better than clinical features. CONCLUSION: Ileal and colonic mucosa-associated microbiome deviations precede development of new onset ileal inflammation after surgically induced remission and show good predictive performance for future recurrence. These findings suggest that targeted microbial modulation is a plausible modality to prevent postoperative Crohn's disease recurrence.

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.

Clinical predictors of early and late endoscopic recurrence following ileocolonic resection in Crohn's disease.

BACKGROUND AND AIM: Multiple factors are suggested to place Crohn's disease patients at risk of recurrence after ileocolic resection with conflicting associations. We aimed to identify clinical predictors of recurrence at first (early) and further (late) postoperative colonoscopy. METHODS: Crohn's disease patients undergoing ileocolic resection were prospectively recruited at six North American centers. Clinical data was collected and endoscopic recurrence was defined as Rutgeerts score ≥i2. A multivariable model was fitted to analyze variables independently associated with recurrence. RESULTS: A total of 365 patients undergoing 674 postoperative colonoscopies were included with a median age of 32 years, 189 (51.8%) were male and 37 (10.1%) non-Whites. Postoperatively, 133 (36.4%) used anti-TNF and 30 (8.2%) were smokers. At first colonoscopy, 109 (29.9%) had recurrence. Male gender (OR = 1.95, 95% CI 1.12 - 3.40), non-White ethnicity (OR = 2.48, 95% CI 1.09 - 5.63), longer interval between surgery and colonoscopy (OR = 1.09, 95% CI 1.002 - 1.18), and postoperative smoking (OR = 2.78, 95% CI 1.16 - 6.67) were associated with recurrence, while prophylactic anti-TNF reduced the risk (OR = 0.28, 95% CI 0.14 - 0.55). Postoperative anti-TNF prophylaxis had a protective effect on anti-TNF experienced patients but not on anti-TNF naïve patients. Among patients without recurrence at first colonoscopy, Rutgeerts score i1 was associated with subsequent recurrence (OR = 4.43, 95% CI 1.73 - 11.35). CONCLUSIONS: We identified independent clinical predictors of early and late Crohn's disease postoperative endoscopic recurrence. Clinical factors traditionally used for risk stratification failed to predict recurrence and need to be revised.

Identifying high-impact variants and genes in exomes of Ashkenazi Jewish inflammatory bowel disease patients.

Inflammatory bowel disease (IBD) is a group of chronic digestive tract inflammatory conditions whose genetic etiology is still poorly understood. The incidence of IBD is particularly high among Ashkenazi Jews. Here, we identify 8 novel and plausible IBD-causing genes from the exomes of 4453 genetically identified Ashkenazi Jewish IBD cases (1734) and controls (2719). Various biological pathway analyses are performed, along with bulk and single-cell RNA sequencing, to demonstrate the likely physiological relatedness of the novel genes to IBD. Importantly, we demonstrate that the rare and high impact genetic architecture of Ashkenazi Jewish adult IBD displays significant overlap with very early onset-IBD genetics. Moreover, by performing biobank phenome-wide analyses, we find that IBD genes have pleiotropic effects that involve other immune responses. Finally, we show that polygenic risk score analyses based on genome-wide high impact variants have high power to predict IBD susceptibility.

Genetic coding variant in complement factor B (CFB) is associated with increased risk for perianal Crohn's disease and leads to impaired CFB cleavage and phagocytosis.

OBJECTIVE: Perianal Crohn's disease (pCD) occurs in up to 40% of patients with CD and is associated with poor quality of life, limited treatment responses and poorly understood aetiology. We performed a genetic association study comparing CD subjects with and without perianal disease and subsequently performed functional follow-up studies for a pCD associated SNP in Complement Factor B (CFB). DESIGN: Immunochip-based meta-analysis on 4056 pCD and 11 088 patients with CD from three independent cohorts was performed. Serological and clinical variables were analysed by regression analyses. Risk allele of rs4151651 was introduced into human CFB plasmid by site-directed mutagenesis. Binding of recombinant G252 or S252 CFB to C3b and its cleavage was determined in cell-free assays. Macrophage phagocytosis in presence of recombinant CFB or serum from CFB risk, or protective CD or healthy subjects was assessed by flow cytometry. RESULTS: Perianal complications were associated with colonic involvement, OmpC and ASCA serology, and serology quartile sum score. We identified a genetic association for pCD (rs4151651), a non-synonymous SNP (G252S) in CFB, in all three cohorts. Recombinant S252 CFB had reduced binding to C3b, its cleavage was impaired, and complement-driven phagocytosis and cytokine secretion were reduced compared with G252 CFB. Serine 252 generates a de novo glycosylation site in CFB. Serum from homozygous risk patients displayed significantly decreased macrophage phagocytosis compared with non-risk serum. CONCLUSION: pCD-associated rs4151651 in CFB is a loss-of-function mutation that impairs its cleavage, activation of alternative complement pathway, and pathogen phagocytosis thus implicating the alternative complement pathway and CFB in pCD aetiology.

Serum Lipidomic Screen Identifies Key Metabolites, Pathways, and Disease Classifiers in Crohn's Disease.

BACKGROUND: There is an unmet medical need for biomarkers that capture host and environmental contributions in inflammatory bowel diseases (IBDs). This study aimed at testing the potential of circulating lipids as disease classifiers given their major roles in inflammation. METHODS: We applied a previously validated comprehensive high-resolution liquid chromatography-mass spectrometry-based untargeted lipidomic workflow covering 25 lipid subclasses to serum samples from 100 Crohn's disease (CD) patients and 100 matched control subjects. Findings were replicated and expanded in another 200 CD patients and 200 control subjects. Key metabolites were tested for associations with disease behavior and location, and classification models were built and validated. Their association with disease activity was tested using an independent cohort of 42 CD patients. RESULTS: We identified >70 metabolites with strong association (P < 1 × 10-4, q < 5 × 10-4) to CD. Highly performing classification models (area under the curve > 0.84-0.97) could be built with as few as 5 to 9 different metabolites, representing 6 major correlated lipid clusters. These classifiers included a phosphatidylethanolamine ether (O-16:0/20:4), a sphingomyelin (d18:1/21:0) and a cholesterol ester (14:1), a very long-chain dicarboxylic acid [28:1(OH)] and sitosterol sulfate. These classifiers and correlated lipids indicate a dysregulated metabolism in host cells, notably in peroxisomes, as well as dysbiosis, oxidative stress, compromised inflammation resolution, or intestinal membrane integrity. A subset of these were associated with disease behavior or location. CONCLUSIONS: Untargeted lipidomic analyses uncovered perturbations in the circulating human CD lipidome, likely resulting from multiple pathogenic mechanisms. Models using as few as 5 biomarkers had strong disease classifier characteristics, supporting their potential use in diagnosis or prognosis.

This study reports a comprehensive untargeted lipidomic analysis of 600 serum samples from patients with Crohn's disease and matched control subjects, identified and replicated ~70 metabolites associated with Crohn's disease, and developed highly performing classification models (area under the curve > 0.84-0.97) with as few as 5 metabolites.

SECANT: a biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics.

The recent advance of single cell sequencing (scRNA-seq) technology such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) allows researchers to quantify cell surface protein abundance and RNA expression simultaneously at single cell resolution. Although CITE-seq and other similar technologies have gained enormous popularity, novel methods for analyzing this type of single cell multi-omics data are in urgent need. A limited number of available tools utilize data-driven approach, which may undermine the biological importance of surface protein data. In this study, we developed SECANT, a biology-guided SEmi-supervised method for Clustering, classification, and ANnoTation of single-cell multi-omics. SECANT is used to analyze CITE-seq data, or jointly analyze CITE-seq and scRNA-seq data. The novelties of SECANT include (1) using confident cell type label identified from surface protein data as guidance for cell clustering, (2) providing general annotation of confident cell types for each cell cluster, (3) utilizing cells with uncertain or missing cell type label to increase performance, and (4) accurate prediction of confident cell types for scRNA-seq data. Besides, as a model-based approach, SECANT can quantify the uncertainty of the results through easily interpretable posterior probability, and our framework can be potentially extended to handle other types of multi-omics data. We successfully demonstrated the validity and advantages of SECANT via simulation studies and analysis of public and in-house datasets from multiple tissues. We believe this new method will be complementary to existing tools for characterizing novel cell types and make new biological discoveries using single-cell multi-omics data.

Comprehensive benchmarking of CITE-seq versus DOGMA-seq single cell multimodal omics.

The recently developed method TEA-seq and similar DOGMA-seq single cell trimodal omics assays provide unprecedented opportunities for understanding cell biology, but independent evaluation is lacking. We explore the utility of DOGMA-seq compared to the bimodal CITE-seq assay in activated and stimulated human peripheral blood T cells. We find that single cell trimodal omics measurements after digitonin (DIG) permeabilization were generally better than after an alternative "low-loss lysis" (LLL) permeabilization condition. Next, we find that DOGMA-seq with optimized DIG permeabilization and its ATAC library provides more information, although its mRNA and cell surface protein libraries have slightly inferior quality, compared to CITE-seq.

A Role for CXCR3 Ligands as Biomarkers of Post-Operative Crohn's Disease Recurrence.

BACKGROUND AND AIMS: Crohn's disease [CD] recurrence following ileocolic resection [ICR] is common. We sought to identify blood-based biomarkers associated with CD recurrence. METHODS: CD patients undergoing ICR were recruited across six centres. Serum samples were obtained at post-operative colonoscopy. A multiplex immunoassay was used to analyse 92 inflammation-related proteins [Olink Proteomics]. Bayesian analysis was used to identify proteins associated with increasing Rutgeerts score. Identified proteins were used in receiver operating characteristic [ROC] analysis to examine the ability to identify CD recurrence [Rutgeerts score ≥i2]. Existing single cell data were interrogated to further elucidate the role of the identified proteins. RESULTS: Data from 276 colonoscopies in 213 patients were available. Median time from surgery to first and second colonoscopy was 7 (interquartile range [IQR] 6-9) and 19 [IQR 16-23] months, respectively. Disease recurrence was evident at 60 [30%] first and 36 [49%] second colonoscopies. Of 14 proteins significantly associated with Rutgeerts score, the strongest signal was seen for CXCL9 and MMP1. Among patients on anti-tumour necrosis factor drugs, CXCL9 and CXCL11 were most strongly associated with Rutgeerts score. Both are CXCR3 ligands. Incorporation of identified proteins into ROC analysis improved the ability to identify disease recurrence as compared to C-reactive protein alone: area under the curve [AUC] 0.75 (95% confidence interval [CI]: 0.66-0.82] vs 0.64 [95% CI 0.56-0.72], p = 0.012. Single cell transcriptomic data provide evidence that innate immune cells are the primary source of the identified proteins. CONCLUSIONS: CXCR3 ligands are associated with CD recurrence following ICR. Incorporation of novel blood-based candidate biomarkers may aid in identification of CD recurrence.

Serum Analyte Profiles Associated With Crohn's Disease and Disease Location.

BACKGROUND: Crohn's disease (CD) can affect any segment of the digestive tract but is most often localized in the ileal, ileocolonic, and colorectal regions of the intestines. It is believed that the chronic inflammation in CD is a result of an imbalance between the epithelial barrier, the immune system, and the intestinal microbiota. The aim of the study was to identify circulating markers associated with CD and/or disease location in CD patients. METHODS: We tested 49 cytokines, chemokines, and growth factors in serum samples from 300 patients with CD and 300 controls. After quality control, analyte levels were tested for association with CD and disease location. RESULTS: We identified 13 analytes that were higher in CD patients relative to healthy controls and that remained significant after conservative Bonferroni correction (P < 0.0015). In particular, CXCL9, CXCL1, and interleukin IL-6 had the greatest effect and were highly significant (P < 5 × 10-7). We also identified 9 analytes that were associated with disease location, with VEGF, IL-12p70, and IL-6 being elevated in patients with colorectal disease (P < 3 × 10-4). CONCLUSIONS: Multiple serum analytes are elevated in CD. These implicate the involvement of multiple cell types from the immune, epithelial, and endothelial systems, suggesting that circulating analytes reflect the inflammatory processes that are ongoing within the gut. Moreover, the identification of distinct profiles according to disease location supports the existence of a biological difference between ileal and colonic CD, consistent with previous genetic and clinical observations.

The Development and Initial Findings of A Study of a Prospective Adult Research Cohort with Inflammatory Bowel Disease (SPARC IBD).

BACKGROUND: Clinical and molecular subcategories of inflammatory bowel disease (IBD) are needed to discover mechanisms of disease and predictors of response and disease relapse. We aimed to develop a study of a prospective adult research cohort with IBD (SPARC IBD) including longitudinal clinical and patient-reported data and biosamples. METHODS: We established a cohort of adults with IBD from a geographically diverse sample of patients across the United States with standardized data and biosample collection methods and sample processing techniques. At enrollment and at time of lower endoscopy, patient-reported outcomes (PRO), clinical data, and endoscopy scoring indices are captured. Patient-reported outcomes are collected quarterly. The quality of clinical data entry after the first year of the study was assessed. RESULTS: Through January 2020, 3029 patients were enrolled in SPARC, of whom 66.1% have Crohn's disease (CD), 32.2% have ulcerative colitis (UC), and 1.7% have IBD-unclassified. Among patients enrolled, 990 underwent colonoscopy. Remission rates were 63.9% in the CD group and 80.6% in the UC group. In the quality study of the cohort, there was 96% agreement on year of diagnosis and 97% agreement on IBD subtype. There was 91% overall agreement describing UC extent as left-sided vs extensive or pancolitis. The overall agreement for CD behavior was 83%. CONCLUSION: The SPARC IBD is an ongoing large prospective cohort with longitudinal standardized collection of clinical data, biosamples, and PROs representing a unique resource aimed to drive discovery of clinical and molecular markers that will meet the needs of precision medicine in IBD.

Whole-genome sequencing of African Americans implicates differential genetic architecture in inflammatory bowel disease.

Whether or not populations diverge with respect to the genetic contribution to risk of specific complex diseases is relevant to understanding the evolution of susceptibility and origins of health disparities. Here, we describe a large-scale whole-genome sequencing study of inflammatory bowel disease encompassing 1,774 affected individuals and 1,644 healthy control Americans with African ancestry (African Americans). Although no new loci for inflammatory bowel disease are discovered at genome-wide significance levels, we identify numerous instances of differential effect sizes in combination with divergent allele frequencies. For example, the major effect at PTGER4 fine maps to a single credible interval of 22 SNPs corresponding to one of four independent associations at the locus in European ancestry individuals but with an elevated odds ratio for Crohn disease in African Americans. A rare variant aggregate analysis implicates Ca2+-binding neuro-immunomodulator CALB2 in ulcerative colitis. Highly significant overall overlap of common variant risk for inflammatory bowel disease susceptibility between individuals with African and European ancestries was observed, with 41 of 241 previously known lead variants replicated and overall correlations in effect sizes of 0.68 for combined inflammatory bowel disease. Nevertheless, subtle differences influence the performance of polygenic risk scores, and we show that ancestry-appropriate weights significantly improve polygenic prediction in the highest percentiles of risk. The median amount of variance explained per locus remains the same in African and European cohorts, providing evidence for compensation of effect sizes as allele frequencies diverge, as expected under a highly polygenic model of disease.

Inflamed Ulcerative Colitis Regions Associated With MRGPRX2-Mediated Mast Cell Degranulation and Cell Activation Modules, Defining a New Therapeutic Target.

BACKGROUND & AIMS: Recent literature has implicated a key role for mast cells in murine models of colonic inflammation, but their role in human ulcerative colitis (UC) is not well established. A major advance has been the identification of mrgprb2 (human orthologue, MRGPX2) as mediating IgE-independent mast cell activation. We sought to define mechanisms of mast cell activation and MRGPRX2 in human UC. METHODS: Colon tissues were collected from patients with UC for bulk RNA sequencing and lamina propria cells were isolated for MRGPRX2 activation studies and single-cell RNA sequencing. Genetic association of all protein-altering G-protein coupled receptor single-nucleotide polymorphism was performed in an Ashkenazi Jewish UC case-control cohort. Variants of MRGPRX2 were transfected into Chinese hamster ovary (CHO) and human mast cell (HMC) 1.1 cells to detect genotype-dependent effects on ß-arrestin recruitment, IP-1 accumulation, and phosphorylated extracellular signal-regulated kinase. RESULTS: Mast cell-specific mediators and adrenomedullin (proteolytic precursor of PAMP-12, an MRGPRX2 agonist) are up-regulated in inflamed compared to uninflamed UC. MRGPRX2 stimulation induces carboxypeptidase secretion from inflamed UC. Of all protein-altering GPCR alleles, a unique variant of MRGPRX2, Asn62Ser, was most associated with and was bioinformatically predicted to alter arrestin recruitment. We validated that the UC protective serine allele enhances ß-arrestin recruitment, decreases IP-1, and increases phosphorylated extracellular signal-regulated kinase with MRGPRX2 agonists. Single-cell RNA sequencing defines that adrenomedullin is expressed by activated fibroblasts and epithelial cells and that interferon gamma is a key upstream regulator of mast cell gene expression. CONCLUSION: Inflamed UC regions are distinguished by MRGPRX2-mediated activation of mast cells, with decreased activation observed with a UC-protective genetic variant. These results define cell modules of UC activation and a new therapeutic target.

Common and Rare Variant Prediction and Penetrance of IBD in a Large, Multi-ethnic, Health System-based Biobank Cohort.

BACKGROUND AND AIMS: Polygenic risk scores (PRS) may soon be used to predict inflammatory bowel disease (IBD) risk in prevention efforts. We leveraged exome-sequence and single nucleotide polymorphism (SNP) array data from 29,358 individuals in the multiethnic, randomly ascertained health system-based BioMe biobank to define effects of common and rare IBD variants on disease prediction and pathophysiology. METHODS: PRS were calculated from European, African American, and Ashkenazi Jewish (AJ) reference case-control studies, and a meta-GWAS run using all three association datasets. PRS were then combined using regression to assess which combination of scores best predicted IBD status in European, AJ, Hispanic, and African American cohorts in BioMe. Additionally, rare variants were assessed in genes associated with very early-onset IBD (VEO-IBD), by estimating genetic penetrance in each BioMe population. RESULTS: Combining risk scores based on association data from distinct ancestral populations improved IBD prediction for every population in BioMe and significantly improved prediction among European ancestry UK Biobank individuals. Lower predictive power for non-Europeans was observed, reflecting in part substantially lower African IBD case-control reference sizes. We replicated associations for two VEO-IBD genes, ADAM17 and LRBA, with high dominant model penetrance in BioMe. Autosomal recessive LRBA risk alleles are associated with severe, early-onset autoimmunity; we show that heterozygous carriage of an African-predominant LRBA protein-altering allele is associated with significantly decreased LRBA and CTLA-4 expression with T-cell activation. CONCLUSIONS: Greater genetic diversity in African populations improves prediction across populations, and generalizes some VEO-IBD genes. Increasing African American IBD case-collections should be prioritized to reduce health disparities and enhance pathophysiological insight.

GMM-Demux: sample demultiplexing, multiplet detection, experiment planning, and novel cell-type verification in single cell sequencing.

Identifying and removing multiplets are essential to improving the scalability and the reliability of single cell RNA sequencing (scRNA-seq). Multiplets create artificial cell types in the dataset. We propose a Gaussian mixture model-based multiplet identification method, GMM-Demux. GMM-Demux accurately identifies and removes multiplets through sample barcoding, including cell hashing and MULTI-seq. GMM-Demux uses a droplet formation model to authenticate putative cell types discovered from a scRNA-seq dataset. We generate two in-house cell-hashing datasets and compared GMM-Demux against three state-of-the-art sample barcoding classifiers. We show that GMM-Demux is stable and highly accurate and recognizes 9 multiplet-induced fake cell types in a PBMC dataset.

BREM-SC: a bayesian random effects mixture model for joint clustering single cell multi-omics data.

Droplet-based single cell transcriptome sequencing (scRNA-seq) technology, largely represented by the 10× Genomics Chromium system, is able to measure the gene expression from tens of thousands of single cells simultaneously. More recently, coupled with the cutting-edge Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), the droplet-based system has allowed for immunophenotyping of single cells based on cell surface expression of specific proteins together with simultaneous transcriptome profiling in the same cell. Despite the rapid advances in technologies, novel statistical methods and computational tools for analyzing multi-modal CITE-Seq data are lacking. In this study, we developed BREM-SC, a novel Bayesian Random Effects Mixture model that jointly clusters paired single cell transcriptomic and proteomic data. Through simulation studies and analysis of public and in-house real data sets, we successfully demonstrated the validity and advantages of this method in fully utilizing both types of data to accurately identify cell clusters. In addition, as a probabilistic model-based approach, BREM-SC is able to quantify the clustering uncertainty for each single cell. This new method will greatly facilitate researchers to jointly study transcriptome and surface proteins at the single cell level to make new biological discoveries, particularly in the area of immunology.

Challenges in IBD Research: Precision Medicine.

Precision medicine is part of five focus areas of the Challenges in IBD research document, which also includes preclinical human IBD mechanisms, environmental triggers, novel technologies, and pragmatic clinical research. The Challenges in IBD Research document provides a comprehensive overview of current gaps in inflammatory bowel diseases (IBD) research and delivers actionable approaches to address them. It is the result of a multidisciplinary input from scientists, clinicians, patients, and funders, and represents a valuable resource for patient centric research prioritization. In particular, the precision medicine section is focused on highlighting the main gap areas that must be addressed to get closer to treatments tailored to the biological and clinical characteristics of each patient, which is the aim of precision medicine. The main gaps were identified in: 1) understanding and predicting the natural history of IBD: disease susceptibility, activity, and behavior; 2) predicting disease course and treatment response; and 3) optimizing current and developing new molecular technologies. Suggested approaches to bridge these gaps include prospective longitudinal cohort studies to identify and validate precision biomarkers for prognostication of disease course, and prediction and monitoring of treatment response. To achieve this, harmonization across studies is key as well as development of standardized methods and infrastructure. The implementation of state-of-the-art molecular technologies, systems biology and machine learning approaches for multi-omics and clinical data integration and analysis will be also fundamental. Finally, randomized biomarker-stratified trials will be critical to evaluate the clinical utility of validated signatures and biomarkers in improving patient outcomes and cost-effective care.

Correction: Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population.

[This corrects the article DOI: 10.1371/journal.pgen.1007329.].

Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population.

As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p<10-16). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC (sites VCF available via FTP at ftp.broadinstitute.org/pub/ExAC_release/release0.3/) to pinpoint genetic variation that contributes to variable disease predisposition across populations.