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Key Points The central challenge of the intestinal immune system is balancing the need to respond to pathogens while co-existing with commensal bacteria and food antigens. Data from genome-wide association (GWA) studies support the concept that dysregulation of the normally controlled immune responses to commensal gut bacteria in a genetically susceptible individual drives the development of inflammatory bowel disease. GWA studies provide a broad view of the relative contributions of various genomic loci to common human diseases and involve genotyping a large number of single-nucleotide polymorphisms (SNPs) that sample human genetic variation throughout the genome. Crohn's disease, but not ulcerative colitis, is associated with functional polymorphisms in the NOD2 (nucleotide-binding oligomerization domain protein 2), ATG16L1 (autophagy related 16-like protein 1) and IRGM (immunity-related GTPase family, M) gene regions. These genes have been implicated in the innate immune system and intracellular processing of bacterial components. Crohn's disease-associated polymorphisms in NOD2 are associated with a decreased ability of the NOD2 protein to appropriately sense bacterial peptidoglycan and activate nuclear factor-κB and mitogen-activated protein kinase pathways. Further studies assessing the altered function of ATG16L1 and IRGM polymorphisms associated with Crohn's disease will be important in establishing the extent to which Crohn's disease occurs as a result of a primary defect in bacterial sensing by the innate immune system. Consistent with previous epidemiological observations, several genes are associated with both Crohn's disease and ulcerative colitis, notably IL23R (encoding interleukin-13 receptor), IL12B (encoding the p40 subunit for IL-12 and IL-23) and STAT3 (encoding signal transducer and activator of transcription 3), all of which are involved in IL-23R signalling. The homeodomain-containing transcription factor NKX2-3 (NK2 transcription factor related, locus 3), which is involved in lymphocyte development, differentiation and organization, is also associated with both Crohn's disease and ulcerative colitis. Within the IL23R gene region, there are multiple independent signals showing association with inflammatory bowel disease and similar patterns of association have been observed in psoriasis and ankylosing spondylitis. The contributions of the IL23R region polymorphisms to intestinal inflammation are complex, reflecting contributions from both the innate and adaptive immune systems. Great progress has been made recently in the identification of genes or genetic loci that are associated with inflammatory bowel diseases. This knowledge is now providing insight into the pathogenesis of these diseases, highlighting roles for genes involved in bacterial sensing and cytokine signalling. Genome-wide association studies efficiently and powerfully assay common genetic variation. The application of these studies to Crohn's disease has provided insight into the immunopathogenesis of this disease, implicating a role for genes of the innate and adaptive immune systems. In this Review, I discuss our current understanding of the genetics and immunopathogenesis of Crohn's disease and ulcerative colitis. Crohn's disease, but not ulcerative colitis, is associated with genetic variation in NOD2 and an autophagy gene, ATG16L1 , both of which affect the intracellular processing of bacterial components. By contrast, variation in the gene encoding the interleukin-23 (IL-23) receptor subunit, as well as in the IL12B , STAT3 and NKX2-3 gene regions, is associated with both Crohn's disease and ulcerative colitis. Comparative analyses of gene associations between these two inflammatory bowel diseases reveal common and unique mechanisms of their immunopathogenesis.

Recent advances in genetics have deepened our understanding of the pathogenic mechanisms behind autoimmune and immune-mediated diseases. This has revealed both shared pathways and a considerable degree of heterogeneity between diseases. Recent advances in genome-wide association studies (GWAS) across autoimmune and immune-mediated diseases have augmented our understanding of pathogenic mechanisms underlying these diseases. This has further highlighted their heterogeneous nature, both within and between diseases. Furthermore, varying responses to therapy have also served to underline the importance of this heterogeneity in the manner in which these diseases are diagnosed and treated. Here we discuss our current understanding of the shared pathways of autoimmunity, including the tumor necrosis factor (TNF), major histocompatibility complex (MHC), interleukin 23 receptor (IL23R) and protein tyrosine phosphatase non-receptor type 22 (PTPN22) pathways. In addition, we summarize effective specific therapies tested across major autoimmune diseases, highlighting the insight they have provided into disease mechanisms and their implications for potential future improvements.

This article reviews the many new insights into autoimmune disease brought about through genomic investigations. The major autoimmune diseases, including rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis, type 1 diabetes mellitus, psoriasis, and inflammatory bowel disease, share epidemiologic, clinical, and therapeutic features. In each of these diseases, chronic and often intermittent inflammation contributes over time to the destruction of target organs that house inciting antigens or are the sites of immune-complex deposition. For some of these disorders, such as inflammatory bowel disease, the contribution of autoimmune mechanisms is questioned, but the overlap of genetic associations that have been identified during the past 5 years suggests a shared immune pathogenesis. At the same time, genetic data . . .

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. 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. 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. 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. National Institutes of Health.

Crohn’s disease is a chronic inflammatory intestinal disease that is frequently accompanied by aberrant healing and stricturing complications. Crosstalk between activated myeloid and stromal cells is critical in the pathogenicity of Crohn’s disease 1 , 2 , and increases in intravasating monocytes are correlated with a lack of response to anti-TNF treatment 3 . The risk alleles with the highest effect on Crohn’s disease are loss-of-function mutations in NOD2 4 , 5 , which increase the risk of stricturing 6 . However, the mechanisms that underlie pathogenicity driven by NOD2 mutations and the pathways that might rescue a lack of response to anti-TNF treatment remain largely uncharacterized. Here we use direct ex vivo analyses of patients who carry risk alleles of NOD2 to show that loss of NOD2 leads to dysregulated homeostasis of activated fibroblasts and macrophages. CD14 + peripheral blood mononuclear cells from carriers of NOD2 risk alleles produce cells that express high levels of collagen, and elevation of conserved signatures is observed in nod2- deficient zebrafish models of intestinal injury. The enrichment of STAT3 regulation and gp130 ligands in activated fibroblasts and macrophages suggested that gp130 blockade might rescue the activated program in NOD2-deficient cells. We show that post-treatment induction of the STAT3 pathway is correlated with a lack of response to anti-TNF treatment in patients, and demonstrate in vivo in zebrafish the amelioration of the activated myeloid–stromal niche using the specific gp130 inhibitor bazedoxifene. Our results provide insights into NOD2-driven fibrosis in Crohn’s disease, and suggest that gp130 blockade may benefit some patients with Crohn’s disease—potentially as a complement to anti-TNF therapy. NOD2 deficiency drives fibrosis and stricturing complications in Crohn’s disease through dysregulated homeostasis of activated fibroblasts and macrophages, which is ameliorated by gp130 blockade in human cell and zebrafish models.

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 - C olitis A ssociated IRF1 antisense R egulator of In testinal H omeostasis”) 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.

IL-22 is one of the factors that, although important for wound healing, also promote tumorigenesis; the regulation of IL-22BP, the IL-22 binding protein, via the NLRP3 and NLRP6 inflammasomes provides an unanticipated mechanism, controlling IL-22 and thereby the development of colon cancer. Inflammasome regulation of interleukin receptor IL-22-binding protein (IL-22BP) is a soluble receptor that specifically binds to and neutralizes the cytokine interleukin (IL) 22, but its physiological function in vivo is unknown. Using a new IL-22BP-knockout mouse strain, this study shows that IL-22BP is required for epithelial tissue repair in a mouse model of colitis and to prevent the development of colon cancer owing to unrestrained IL-22-mediated epithelial proliferation. IL-22BP is downregulated by an inflammasome- and IL-18-dependent mechanism after initial tissue damage to allow for repair. Chronic mucosal inflammation and tissue damage predisposes patients to the development of colorectal cancer 1 . This association could be explained by the hypothesis that the same factors and pathways important for wound healing also promote tumorigenesis. A sensor of tissue damage should induce these factors to promote tissue repair and regulate their action to prevent development of cancer. Interleukin 22 (IL-22), a cytokine of the IL-10 superfamily, has an important role in colonic epithelial cell repair, and its levels are increased in the blood and intestine of inflammatory bowel disease patients 2 , 3 . This cytokine can be neutralized by the soluble IL-22 receptor, known as the IL-22 binding protein (IL-22BP, also known as IL22RA2); however, the significance of endogenous IL-22BP in vivo and the pathways that regulate this receptor are unknown 4 , 5 . Here we describe that IL-22BP has a crucial role in controlling tumorigenesis and epithelial cell proliferation in the colon. IL-22BP is highly expressed by dendritic cells in the colon in steady-state conditions. Sensing of intestinal tissue damage via the NLRP3 or NLRP6 inflammasomes led to an IL-18-dependent downregulation of IL-22BP, thereby increasing the ratio of IL-22/IL-22BP. IL-22, which is induced during intestinal tissue damage, exerted protective properties during the peak of damage, but promoted tumour development if uncontrolled during the recovery phase. Thus, the IL-22–IL-22BP axis critically regulates intestinal tissue repair and tumorigenesis in the colon.

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. Early diagnosis can significantly improve treatment options and prevent severe organ damage in individuals with autoimmune diseases. Here, the authors develop a machine learning model that uses electronic health records to identify patients with clinical suspicion of autoimmune diseases.

Polygenic risk scores (PRSs) have been offered since 2019 to screen in vitro fertilization embryos for genetic liability to adult diseases, despite a lack of comprehensive modeling of expected outcomes. Here we predict, based on the liability threshold model, the expected reduction in complex disease risk following polygenic embryo screening for a single disease. A strong determinant of the potential utility of such screening is the selection strategy , a factor that has not been previously studied. When only embryos with a very high PRS are excluded, the achieved risk reduction is minimal. In contrast, selecting the embryo with the lowest PRS can lead to substantial relative risk reductions, given a sufficient number of viable embryos. We systematically examine the impact of several factors on the utility of screening, including: variance explained by the PRS, number of embryos, disease prevalence, parental PRSs, and parental disease status. We consider both relative and absolute risk reductions, as well as population-averaged and per-couple risk reductions, and also examine the risk of pleiotropic effects. Finally, we confirm our theoretical predictions by simulating ‘virtual’ couples and offspring based on real genomes from schizophrenia and Crohn’s disease case-control studies. We discuss the assumptions and limitations of our model, as well as the potential emerging ethical concerns.

Genetics of complex diseases Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases, but most confer quite small increments of risk. There seems to be a large component of heritability somehow evading detection. Possible explanations for this 'missing heritability' include great numbers of small-effect variants yet to be found, rare structural or epigenetic variation not detected by current genotyping technology and hard-to-detect gene–gene and gene–environment interactions. Teri Manolio and colleagues examine the research strategies most likely to distinguish between these and other possible explanations. Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, ‘missing’ heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.