Multimodal single-cell analyses reveal mechanisms of perianal fistula in diverse patients with Crohn's disease.

BACKGROUND: Crohn's disease complicated by perianal fistulae is more prevalent and severe in patients of African ancestry. METHODS: We profiled single cells from diverse patients with Crohn's disease with perianal fistula from colorectal mucosa and fistulous tracts. Immunofluorescence was performed to validate predicted cell-cell interactions. Unstimulated monocytes were chronically cultured in diverse cohorts. A subset was analyzed by single-nucleus RNA + ATAC sequencing. FINDINGS: Fistulous tract cells from complete proctectomies demonstrated enrichment of myeloid cells compared to paired rectal tissues. Ligand-receptor analysis highlights myeloid-stromal cross-talk and cellular senescence, with cellular co-localization validated by immunofluorescence. Chitinase-3 like-protein-1 (CHI3L1) is a top upregulated gene in stromal cells from fistulae expressing both destructive and fibrotic gene signatures. Monocyte cultures from patients of African ancestry and controls demonstrated differences in CHI3L1 and oncostatin M (OSM) expression upon differentiation compared to individuals of European ancestry. Activating protein-1 footprints are present in ATAC-seq peaks in stress response genes, including CHI3L1 and OSM; genome-wide chromatin accessibility including JUN footprints was observed, consistent with reported mechanisms of inflammatory memory. Regulon analyses confirm known cell-specific transcription factor regulation and implicate novel ones in fibroblast subsets. All pseudo-bulked clusters demonstrate enrichment of genetic loci, establishing multicellular contributions. In the most significant African American Crohn's genetic locus, upstream of prostaglandin E receptor 4, lymphoid-predominant ATAC-seq peaks were observed, with predicted RORC footprints. CONCLUSIONS: Population differences in myeloid-stromal cross-talk implicate fibrotic and destructive fibroblasts, senescence, epigenetic memory, and cell-specific enhancers in perianal fistula pathogenesis. The transcriptomic and epigenetic data provided here may guide optimization of promising mesenchymal stem cell therapies for perianal fistula. FUNDING: This work was supported by grants U01DK062422, U24DK062429, and R01DK123758.

Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system.

Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.

Advancing genomics to improve health equity.

Health equity is the state in which everyone has fair and just opportunities to attain their highest level of health. The field of human genomics has fallen short in increasing health equity, largely because the diversity of the human population has been inadequately reflected among participants of genomics research. This lack of diversity leads to disparities that can have scientific and clinical consequences. Achieving health equity related to genomics will require greater effort in addressing inequities within the field. As part of the commitment of the National Human Genome Research Institute (NHGRI) to advancing health equity, it convened experts in genomics and health equity research to make recommendations and performed a review of current literature to identify the landscape of gaps and opportunities at the interface between human genomics and health equity research. This Perspective describes these findings and examines health equity within the context of human genomics and genomic medicine.

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.

The role of admixture in the rare variant contribution to inflammatory bowel disease.

BACKGROUND: Identification of rare variants involved in complex, polygenic diseases like Crohn's disease (CD) has accelerated with the introduction of whole exome/genome sequencing association studies. Rare variants can be used in both diagnostic and therapeutic assessments; however, since they are likely to be restricted to specific ancestry groups, their contributions to risk assessment need to be evaluated outside the discovery population. Prior studies implied that the three known rare variants in NOD2 are absent in West African and Asian populations and only contribute in African Americans via admixture. METHODS: Whole genome sequencing (WGS) data from 3418 African American individuals, 1774 inflammatory bowel disease (IBD) cases, and 1644 controls were used to assess odds ratios and allele frequencies (AF), as well as haplotype-specific ancestral origins of European-derived CD variants discovered in a large exome-wide association study. Local and global ancestry was performed to assess the contribution of admixture to IBD contrasting European and African American cohorts. RESULTS: Twenty-five rare variants associated with CD in European discovery cohorts are typically five-fold lower frequency in African Americans. Correspondingly, where comparisons could be made, the rare variants were found to have a predicted four-fold reduced burden for IBD in African Americans, when compared to European individuals. Almost all of the rare CD European variants were found on European haplotypes in the African American cohort, implying that they contribute to disease risk in African Americans primarily due to recent admixture. In addition, proportion of European ancestry correlates the number of rare CD European variants each African American individual carry, as well as their polygenic risk of disease. Similar findings were observed for 23 mutations affecting 10 other common complex diseases for which the rare variants were discovered in European cohorts. CONCLUSIONS: European-derived Crohn's disease rare variants are even more rare in African Americans and contribute to disease risk mainly due to admixture, which needs to be accounted for when performing cross-ancestry genetic assessments.

Deep learning on electronic medical records identifies distinct subphenotypes of diabetic kidney disease driven by genetic variations in the Rho pathway.

Kidney disease affects 50% of all diabetic patients; however, prediction of disease progression has been challenging due to inherent disease heterogeneity. We use deep learning to identify novel genetic signatures prognostically associated with outcomes. Using autoencoders and unsupervised clustering of electronic health record data on 1,372 diabetic kidney disease patients, we establish two clusters with differential prevalence of end-stage kidney disease. Exome-wide associations identify a novel variant in ARHGEF18, a Rho guanine exchange factor specifically expressed in glomeruli. Overexpression of ARHGEF18 in human podocytes leads to impairments in focal adhesion architecture, cytoskeletal dynamics, cellular motility, and RhoA/Rac1 activation. Mutant GEF18 is resistant to ubiquitin mediated degradation leading to pathologically increased protein levels. Our findings uncover the first known disease-causing genetic variant that affects protein stability of a cytoskeletal regulator through impaired degradation, a potentially novel class of expression quantitative trait loci that can be therapeutically targeted.

Life is pain: Fibromyalgia as a nexus of multiple liability distributions.

Fibromyalgia is a complex disease of unclear etiology that is complicated by difficulties in diagnosis, treatment, and clinical heterogeneity. To clarify this etiology, healthcare-based data are leveraged to assess the influences on fibromyalgia in several domains. Prevalence is less than 1% of females in our population register data, and about 1/10th that in males. Fibromyalgia often presents with co-occurring conditions including back pain, rheumatoid arthritis, and anxiety. More comorbidities are identified with hospital-associated biobank data, falling into three broad categories of pain-related, autoimmune, and psychiatric disorders. Selecting representative phenotypes with published genome-wide association results for polygenic scoring, we confirm genetic predispositions to psychiatric, pain sensitivity, and autoimmune conditions show associations with fibromyalgia, although these may differ by ancestry group. We conduct a genome-wide association analysis of fibromyalgia in biobank samples, which did not result in any genome-wide significant loci; further studies with increased sample size are necessary to identify specific genetic effects on fibromyalgia. Overall, fibromyalgia appears to have strong clinical and likely genetic links to several disease categories, and could usefully be understood as a composite manifestation of these etiological sources.

A machine learning model identifies patients in need of autoimmune disease testing using electronic health records.

Systemic autoimmune rheumatic diseases (SARDs) can lead to irreversible damage if left untreated, yet these patients often endure long diagnostic journeys before being diagnosed and treated. Machine learning may help overcome the challenges of diagnosing SARDs and inform clinical decision-making. Here, we developed and tested a machine learning model to identify patients who should receive rheumatological evaluation for SARDs using longitudinal electronic health records of 161,584 individuals from two institutions. The model demonstrated high performance for predicting cases of autoantibody-tested individuals in a validation set, an external test set, and an independent cohort with a broader case definition. This approach identified more individuals for autoantibody testing compared with current clinical standards and a greater proportion of autoantibody carriers among those tested. Diagnoses of SARDs and other autoimmune conditions increased with higher model probabilities. The model detected a need for autoantibody testing and rheumatology encounters up to five years before the test date and assessment date, respectively. Altogether, these findings illustrate that the clinical manifestations of a diverse array of autoimmune conditions are detectable in electronic health records using machine learning, which may help systematize and accelerate autoimmune testing.

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.

A lncRNA from an inflammatory bowel disease risk locus maintains intestinal host-commensal homeostasis.

Inflammatory bowel diseases (IBD) are known to have complex, genetically influenced etiologies, involving dysfunctional interactions between the intestinal immune system and the microbiome. Here, we characterized how the RNA transcript from an IBD-associated long non-coding RNA locus ("CARINH-Colitis Associated IRF1 antisense Regulator of Intestinal Homeostasis") protects against IBD. We show that CARINH and its neighboring gene coding for the transcription factor IRF1 together form a feedforward loop in host myeloid cells. The loop activation is sustained by microbial factors, and functions to maintain the intestinal host-commensal homeostasis via the induction of the anti-inflammatory factor IL-18BP and anti-microbial factors called guanylate-binding proteins (GBPs). Extending these mechanistic insights back to humans, we demonstrate that the function of the CARINH/IRF1 loop is conserved between mice and humans. Genetically, the T allele of rs2188962, the most probable causal variant of IBD within the CARINH locus from the human genetics study, impairs the inducible expression of the CARINH/IRF1 loop and thus increases genetic predisposition to IBD. Our study thus illustrates how an IBD-associated lncRNA maintains intestinal homeostasis and protects the host against colitis.

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.

Second-Line Biologic Therapy Following Tumor Necrosis Factor Antagonist Failure: A Real-World Propensity Score-Weighted Analysis.

BACKGROUND& AIMS: Tumor necrosis factor (TNF) antagonists often are used as first-line medications to treat moderate to severe inflammatory bowel disease (IBD), but many patients do not achieve or maintain response. Our aim was to compare the effectiveness of second-line treatments (ustekinumab, vedolizumab, or a second TNF antagonist) after TNF antagonist exposure in patients with Crohn's disease (CD) and ulcerative colitis (UC) from 2 electronic health records-based cohorts. METHODS: We identified patients with prior TNF antagonist exposure who switched to a different biologic in the Mount Sinai Health System (MSHS) electronic health records (CD, n = 527; UC, n = 165) and the Study of a Prospective Adult Research Cohort (SPARC) from the Inflammatory Bowel Disease Plexus Program of the Crohn's & Colitis Foundation (CD, n = 412; UC, n = 129). Treatment failure was defined as the composite of any IBD-related surgery, IBD-related hospitalization, new prescription of oral/intravenous corticosteroids, or need to switch to a third biologic agent. Time-to-event analysis was conducted with inverse probability of treatment-weighted data. RESULTS: Overall, treatment failure occurred in 85% of MSHS and 72% of SPARC CD patients. In SPARC, the likelihood of treatment failure was significantly lower with ustekinumab compared with vedolizumab as second-line treatment (adjusted hazard ratio, 0.66; 95% CI, 0.54-0.82; P < .001), a trend confirmed in MSHS (adjusted hazard ratio, 0.89; 95% CI, 0.77-1.04; P = .15). In both cohorts, the superiority of ustekinumab compared with vedolizumab was shown when considering treatment failure as prescription of steroids or a third biologic agent. In UC, no differences between second-line treatment groups were identified. CONCLUSIONS: In 2 independent real-world cohort settings, second-line therapy in CD with ustekinumab after TNF antagonist treatment failure was associated with a lower likelihood of treatment failure than second-line vedolizumab.

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.

Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts.

BACKGROUND: Binary diagnosis of coronary artery disease does not preserve the complexity of disease or quantify its severity or its associated risk with death; hence, a quantitative marker of coronary artery disease is warranted. We evaluated a quantitative marker of coronary artery disease derived from probabilities of a machine learning model. METHODS: In this cohort study, we developed and validated a coronary artery disease-predictive machine learning model using 95 935 electronic health records and assessed its probabilities as in-silico scores for coronary artery disease (ISCAD; range 0 [lowest probability] to 1 [highest probability]) in participants in two longitudinal biobank cohorts. We measured the association of ISCAD with clinical outcomes-namely, coronary artery stenosis, obstructive coronary artery disease, multivessel coronary artery disease, all-cause death, and coronary artery disease sequelae. FINDINGS: Among 95 935 participants, 35 749 were from the BioMe Biobank (median age 61 years [IQR 18]; 14 599 [41%] were male and 21 150 [59%] were female; 5130 [14%] were with diagnosed coronary artery disease) and 60 186 were from the UK Biobank (median age 62 [15] years; 25 031 [42%] male and 35 155 [58%] female; 8128 [14%] with diagnosed coronary artery disease). The model predicted coronary artery disease with an area under the receiver operating characteristic curve of 0·95 (95% CI 0·94-0·95; sensitivity of 0·94 [0·94-0·95] and specificity of 0·82 [0·81-0·83]) and 0·93 (0·92-0·93; sensitivity of 0·90 [0·89-0·90] and specificity of 0·88 [0·87-0·88]) in the BioMe validation and holdout sets, respectively, and 0·91 (0·91-0·91; sensitivity of 0·84 [0·83-0·84] and specificity of 0·83 [0·82-0·83]) in the UK Biobank external test set. ISCAD captured coronary artery disease risk from known risk factors, pooled cohort equations, and polygenic risk scores. Coronary artery stenosis increased quantitatively with ascending ISCAD quartiles (increase per quartile of 12 percentage points), including risk of obstructive coronary artery disease, multivessel coronary artery disease, and stenosis of major coronary arteries. Hazard ratios (HRs) and prevalence of all-cause death increased stepwise over ISCAD deciles (decile 1: HR 1·0 [95% CI 1·0-1·0], 0·2% prevalence; decile 6: 11 [3·9-31], 3·1% prevalence; and decile 10: 56 [20-158], 11% prevalence). A similar trend was observed for recurrent myocardial infarction. 12 (46%) undiagnosed individuals with high ISCAD (≥0·9) had clinical evidence of coronary artery disease according to the 2014 American College of Cardiology/American Heart Association Task Force guidelines. INTERPRETATION: Electronic health record-based machine learning was used to generate an in-silico marker for coronary artery disease that can non-invasively quantify atherosclerosis and risk of death on a continuous spectrum, and identify underdiagnosed individuals. FUNDING: National Institutes of Health.

NOX1 is essential for TNFα-induced intestinal epithelial ROS secretion and inhibits M cell signatures.

OBJECTIVE: Loss-of-function mutations in genes generating reactive oxygen species (ROS), such as NOX1, are associated with IBD. Mechanisms whereby loss of ROS drive IBD are incompletely defined. DESIGN: ROS measurements and single-cell transcriptomics were performed on colonoids stratified by NOX1 genotype and TNFα stimulation. Clustering of epithelial cells from human UC (inflamed and uninflamed) scRNASeq was performed. Validation of M cell induction was performed by immunohistochemistry using UEA1 (ulex europaeus agglutin-1 lectin) and in vivo with DSS injury. RESULTS: TNFα induces ROS production more in NOX1-WT versus NOX1-deficient murine colonoids under a range of Wnt-mediated and Notch-mediated conditions. scRNASeq from inflamed and uninflamed human colitis versus TNFα stimulated, in vitro colonoids defines substantially shared, induced transcription factors; NOX1-deficient colonoids express substantially lower levels of STAT3 (signal transducer and activator of transcription 3), CEBPD (CCAAT enhancer-binding protein delta), DNMT1 (DNA methyltransferase) and HIF1A (hypoxia-inducible factor) baseline. Subclustering unexpectedly showed marked TNFα-mediated induction of M cells (sentinel cells overlying lymphoid aggregates) in NOX1-deficient colonoids. M cell induction by UEA1 staining is rescued with H2O2 and paraquat, defining extra- and intracellular ROS roles in maintenance of LGR5+ stem cells. DSS injury demonstrated GP2 (glycoprotein-2), basal lymphoplasmacytosis and UEA1 induction in NOX1-deficiency. Principal components analyses of M cell genes and decreased DNMT1 RNA velocity correlate with UC inflammation. CONCLUSIONS: NOX1 deficiency plus TNFα stimulation contribute to colitis through dysregulation of the stem cell niche and altered cell differentiation, enhancing basal lymphoplasmacytosis. Our findings prioritise ROS modulation for future therapies.

Genome-wide polygenic score to predict chronic kidney disease across ancestries.

Chronic kidney disease (CKD) is a common complex condition associated with high morbidity and mortality. Polygenic prediction could enhance CKD screening and prevention; however, this approach has not been optimized for ancestrally diverse populations. By combining APOL1 risk genotypes with genome-wide association studies (GWAS) of kidney function, we designed, optimized and validated a genome-wide polygenic score (GPS) for CKD. The new GPS was tested in 15 independent cohorts, including 3 cohorts of European ancestry (n = 97,050), 6 cohorts of African ancestry (n = 14,544), 4 cohorts of Asian ancestry (n = 8,625) and 2 admixed Latinx cohorts (n = 3,625). We demonstrated score transferability with reproducible performance across all tested cohorts. The top 2% of the GPS was associated with nearly threefold increased risk of CKD across ancestries. In African ancestry cohorts, the APOL1 risk genotype and polygenic component of the GPS had additive effects on the risk of CKD.

Neutralizing Anti-Granulocyte Macrophage-Colony Stimulating Factor Autoantibodies Recognize Post-Translational Glycosylations on Granulocyte Macrophage-Colony Stimulating Factor Years Before Diagnosis and Predict Complicated Crohn's Disease.

BACKGROUND & AIMS: Anti-granulocyte macrophage-colony stimulating factor autoantibodies (aGMAbs) are detected in patients with ileal Crohn's disease (CD). Their induction and mode of action during or before disease are not well understood. We aimed to investigate the underlying mechanisms associated with aGMAb induction, from functional orientation to recognized epitopes, for their impact on intestinal immune homeostasis and use as a predictive biomarker for complicated CD. METHODS: We characterized using enzyme-linked immunosorbent assay naturally occurring aGMAbs in longitudinal serum samples from patients archived before the diagnosis of CD (n = 220) as well as from 400 healthy individuals (matched controls) as part of the US Defense Medical Surveillance System. We used biochemical, cellular, and transcriptional analysis to uncover a mechanism that governs the impaired immune balance in CD mucosa after diagnosis. RESULTS: Neutralizing aGMAbs were found to be specific for post-translational glycosylation on granulocyte macrophage-colony stimulating factor (GM-CSF), detectable years before diagnosis, and associated with complicated CD at presentation. Glycosylation of GM-CSF was altered in patients with CD, and aGMAb affected myeloid homeostasis and promoted group 1 innate lymphoid cells. Perturbations in immune homeostasis preceded the diagnosis in the serum of patients with CD presenting with aGMAb and were detectable in the noninflamed CD mucosa. CONCLUSIONS: Anti-GMAbs predict the diagnosis of complicated CD long before the diagnosis of disease, recognize uniquely glycosylated epitopes, and impair myeloid cell and innate lymphoid cell balance associated with altered intestinal immune homeostasis.

Single-cell transcriptomics reveals conserved cell identities and fibrogenic phenotypes in zebrafish and human liver.

The mechanisms underlying liver fibrosis are multifaceted and remain elusive with no approved antifibrotic treatments available. The adult zebrafish has been an underutilized tool to study liver fibrosis. We aimed to characterize the single-cell transcriptome of the adult zebrafish liver to determine its utility as a model for studying liver fibrosis. We used single-cell RNA sequencing (scRNA-seq) of adult zebrafish liver to study the molecular and cellular dynamics at a single-cell level. We performed a comparative analysis to scRNA-seq of human liver with a focus on hepatic stellate cells (HSCs), the driver cells in liver fibrosis. scRNA-seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA-seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish. Human and zebrafish HSCs show conservation of transcriptional profiles, and we uncover collectin subfamily member 11 (colec11) as a novel, conserved marker for zebrafish HSCs. To demonstrate the power of scRNA-seq to study liver fibrosis using zebrafish, we performed scRNA-seq on our zebrafish model of a pediatric liver disease with mutation in mannose phosphate isomerase (MPI) and characteristic early liver fibrosis. We found fibrosis signaling pathways and upstream regulators conserved across MPI-depleted zebrafish and human HSCs. CellPhoneDB analysis of zebrafish transcriptome identified neuropilin 1 as a potential driver of liver fibrosis. Conclusion: This study establishes the first scRNA-seq atlas of the adult zebrafish liver, highlights the high degree of similarity to human liver, and strengthens its value as a model to study liver fibrosis.

Population-Based Penetrance of Deleterious Clinical Variants.

Importance: Population-based assessment of disease risk associated with gene variants informs clinical decisions and risk stratification approaches. Objective: To evaluate the population-based disease risk of clinical variants in known disease predisposition genes. Design, Setting, and Participants: This cohort study included 72 434 individuals with 37 780 clinical variants who were enrolled in the BioMe Biobank from 2007 onwards with follow-up until December 2020 and the UK Biobank from 2006 to 2010 with follow-up until June 2020. Participants had linked exome and electronic health record data, were older than 20 years, and were of diverse ancestral backgrounds. Exposures: Variants previously reported as pathogenic or predicted to cause a loss of protein function by bioinformatic algorithms (pathogenic/loss-of-function variants). Main Outcomes and Measures: The primary outcome was the disease risk associated with clinical variants. The risk difference (RD) between the prevalence of disease in individuals with a variant allele (penetrance) vs in individuals with a normal allele was measured. Results: Among 72 434 study participants, 43 395 were from the UK Biobank (mean [SD] age, 57 [8.0] years; 24 065 [55%] women; 2948 [7%] non-European) and 29 039 were from the BioMe Biobank (mean [SD] age, 56 [16] years; 17 355 [60%] women; 19 663 [68%] non-European). Of 5360 pathogenic/loss-of-function variants, 4795 (89%) were associated with an RD less than or equal to 0.05. Mean penetrance was 6.9% (95% CI, 6.0%-7.8%) for pathogenic variants and 0.85% (95% CI, 0.76%-0.95%) for benign variants reported in ClinVar (difference, 6.0 [95% CI, 5.6-6.4] percentage points), with a median of 0% for both groups due to large numbers of nonpenetrant variants. Penetrance of pathogenic/loss-of-function variants for late-onset diseases was modified by age: mean penetrance was 10.3% (95% CI, 9.0%-11.6%) in individuals 70 years or older and 8.5% (95% CI, 7.9%-9.1%) in individuals 20 years or older (difference, 1.8 [95% CI, 0.40-3.3] percentage points). Penetrance of pathogenic/loss-of-function variants was heterogeneous even in known disease predisposition genes, including BRCA1 (mean [range], 38% [0%-100%]), BRCA2 (mean [range], 38% [0%-100%]), and PALB2 (mean [range], 26% [0%-100%]). Conclusions and Relevance: In 2 large biobank cohorts, the estimated penetrance of pathogenic/loss-of-function variants was variable but generally low. Further research of population-based penetrance is needed to refine variant interpretation and clinical evaluation of individuals with these variant alleles.

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.