Phage display sequencing reveals that genetic, environmental, and intrinsic factors influence variation of human antibody epitope repertoire.

Phage-displayed immunoprecipitation sequencing (PhIP-seq) has enabled high-throughput profiling of human antibody repertoires. However, a comprehensive overview of environmental and genetic determinants shaping human adaptive immunity is lacking. In this study, we investigated the effects of genetic, environmental, and intrinsic factors on the variation in human antibody repertoires. We characterized serological antibody repertoires against 344,000 peptides using PhIP-seq libraries from a wide range of microbial and environmental antigens in 1,443 participants from a population cohort. We detected individual-specificity, temporal consistency, and co-housing similarities in antibody repertoires. Genetic analyses showed the involvement of the HLA, IGHV, and FUT2 gene regions in antibody-bound peptide reactivity. Furthermore, we uncovered associations between phenotypic factors (including age, cell counts, sex, smoking behavior, and allergies, among others) and particular antibody-bound peptides. Our results indicate that human antibody epitope repertoires are shaped by both genetics and environmental exposures and highlight specific signatures of distinct phenotypes and genotypes.

Getting up to speed with transcription elongation by RNA polymerase II.

Recent advances in sequencing techniques that measure nascent transcripts and that reveal the positioning of RNA polymerase II (Pol II) have shown that the pausing of Pol II in promoter-proximal regions and its release to initiate a phase of productive elongation are key steps in transcription regulation. Moreover, after the release of Pol II from the promoter-proximal region, elongation rates are highly dynamic throughout the transcription of a gene, and vary on a gene-by-gene basis. Interestingly, Pol II elongation rates affect co-transcriptional processes such as splicing, termination and genome stability. Increasing numbers of factors and regulatory mechanisms have been associated with the steps of transcription elongation by Pol II, revealing that elongation is a highly complex process. Elongation is thus now recognized as a key phase in the regulation of transcription by Pol II.

iPSC-derived organ-on-a-chip models for personalized human genetics and pharmacogenomics studies.

Genome-wide association studies (GWAS) have now correlated hundreds of genetic variants with complex genetic diseases and drug efficacy. Functional characterization of these factors remains challenging, particularly because of the lack of human model systems. Molecular and nanotechnological advances, in particular the ability to generate patient-specific PSC lines, differentiate them into diverse cell types, and seed and combine them on microfluidic chips, have led to the establishment of organ-on-a-chip (OoC) platforms that recapitulate organ biology. OoC technology thus provides unique personalized platforms for studying the effects of host genetics and environmental factors on organ physiology. In this review we describe the technology and provide examples of how OoCs may be used for disease modeling and pharmacogenetic research.

RNF12 is an X-Encoded dose-dependent activator of X chromosome inactivation.

In somatic cells of female placental mammals, one X chromosome is inactivated to minimize sex-related dosage differences of X-encoded genes. Random X chromosome inactivation (XCI) in the embryo is a stochastic process, in which each X has an independent probability to initiate XCI, triggered by the nuclear concentration of one or more X-encoded XCI-activators. Here, we identify the E3 ubiquitin ligase RNF12 as an important XCI-activator. Additional copies of mouse Rnf12 or human RNF12 result in initiation of XCI in male mouse ES cells and on both X chromosomes in a substantial percentage of female mouse ES cells. This activity is dependent on an intact open reading frame of Rnf12 and correlates with the transgenic expression level of RNF12. Initiation of XCI is markedly reduced in differentiating female heterozygous Rnf12(+/-) ES cells. These findings provide evidence for a dose-dependent role of RNF12 in the XCI counting and initiation process.

X inactivation counting and choice is a stochastic process: evidence for involvement of an X-linked activator.

Female mammalian cells achieve dosage compensation of X-encoded genes by X chromosome inactivation (XCI). This process is thought to involve X chromosome counting and choice. To explore how this process is initiated, we analyzed XCI in tetraploid XXXX, XXXY, and XXYY embryonic stem cells and found that every X chromosome within a single nucleus has an independent probability to initiate XCI. This finding suggests a stochastic mechanism directing XCI counting and choice. The probability is directly proportional to the X chromosome:ploidy ratio, indicating the presence of an X-encoded activator of XCI, that itself is inactivated by the XCI process. Deletion of a region including Xist, Tsix, and Xite still results in XCI on the remaining wild-type X chromosome in female cells. This result supports a stochastic model in which each X chromosome in a nucleus initiates XCI independently and positions an X-encoded trans-acting XCI-activator outside the deleted region.

Kinetics of Xist-induced gene silencing can be predicted from combinations of epigenetic and genomic features.

To initiate X-Chromosome inactivation (XCI), the long noncoding RNA Xist mediates chromosome-wide gene silencing of one X Chromosome in female mammals to equalize gene dosage between the sexes. The efficiency of gene silencing is highly variable across genes, with some genes even escaping XCI in somatic cells. A gene's susceptibility to Xist-mediated silencing appears to be determined by a complex interplay of epigenetic and genomic features; however, the underlying rules remain poorly understood. We have quantified chromosome-wide gene silencing kinetics at the level of the nascent transcriptome using allele-specific Precision nuclear Run-On sequencing (PRO-seq). We have developed a Random Forest machine-learning model that can predict the measured silencing dynamics based on a large set of epigenetic and genomic features and tested its predictive power experimentally. The genomic distance to the Xist locus, followed by gene density and distance to LINE elements, are the prime determinants of the speed of gene silencing. Moreover, we find two distinct gene classes associated with different silencing pathways: a class that requires Xist-repeat A for silencing, which is known to activate the SPEN pathway, and a second class in which genes are premarked by Polycomb complexes and tend to rely on the B repeat in Xist for silencing, known to recruit Polycomb complexes during XCI. Moreover, a series of features associated with active transcriptional elongation and chromatin 3D structure are enriched at rapidly silenced genes. Our machine-learning approach can thus uncover the complex combinatorial rules underlying gene silencing during X inactivation.

A Combined mRNA- and miRNA-Sequencing Approach Reveals miRNAs as Potential Regulators of the Small Intestinal Transcriptome in Celiac Disease.

Celiac disease (CeD) is triggered by gluten and results in inflammation and villous atrophy of the small intestine. We aimed to explore the role of miRNA-mediated deregulation of the transcriptome in CeD. Duodenal biopsies of CeD patients (n = 33) and control subjects (n = 10) were available for miRNA-sequencing, with RNA-sequencing also available for controls (n = 5) and CeD (n = 6). Differential expression analysis was performed to select CeD-associated miRNAs and genes. MiRNA‒target transcript pairs selected from public databases that also displayed a strong negative expression correlation in the current dataset (R < -0.7) were used to construct a CeD miRNA‒target transcript interaction network. The network includes 2030 miRNA‒target transcript interactions, including 423 experimentally validated pairs. Pathway analysis found that interactions are involved in immune-related pathways (e.g., interferon signaling) and metabolic pathways (e.g., lipid metabolism). The network includes 13 genes previously prioritized to be causally deregulated by CeD-associated genomic variants, including STAT1. CeD-associated miRNAs might play a role in promoting inflammation and decreasing lipid metabolism in the small intestine, thereby contributing unbalanced cell turnover in the intestinal crypt. Some CeD-associated miRNAs deregulate genes that are also affected by genomic CeD-risk variants, adding an additional layer of complexity to the deregulated transcriptome in CeD.

Deconvolution of bulk blood eQTL effects into immune cell subpopulations.

BACKGROUND: Expression quantitative trait loci (eQTL) studies are used to interpret the function of disease-associated genetic risk factors. To date, most eQTL analyses have been conducted in bulk tissues, such as whole blood and tissue biopsies, which are likely to mask the cell type-context of the eQTL regulatory effects. Although this context can be investigated by generating transcriptional profiles from purified cell subpopulations, current methods to do this are labor-intensive and expensive. We introduce a new method, Decon2, as a framework for estimating cell proportions using expression profiles from bulk blood samples (Decon-cell) followed by deconvolution of cell type eQTLs (Decon-eQTL). RESULTS: The estimated cell proportions from Decon-cell agree with experimental measurements across cohorts (R ≥ 0.77). Using Decon-cell, we could predict the proportions of 34 circulating cell types for 3194 samples from a population-based cohort. Next, we identified 16,362 whole-blood eQTLs and deconvoluted cell type interaction (CTi) eQTLs using the predicted cell proportions from Decon-cell. CTi eQTLs show excellent allelic directional concordance with eQTL (≥ 96-100%) and chromatin mark QTL (≥87-92%) studies that used either purified cell subpopulations or single-cell RNA-seq, outperforming the conventional interaction effect. CONCLUSIONS: Decon2 provides a method to detect cell type interaction effects from bulk blood eQTLs that is useful for pinpointing the most relevant cell type for a given complex disease. Decon2 is available as an R package and Java application (https://github.com/molgenis/systemsgenetics/tree/master/Decon2) and as a web tool (www.molgenis.org/deconvolution).

Tissue alarmins and adaptive cytokine induce dynamic and distinct transcriptional responses in tissue-resident intraepithelial cytotoxic T lymphocytes.

The respective effects of tissue alarmins interleukin (IL)-15 and interferon beta (IFNß), and IL-21 produced by T cells on the reprogramming of cytotoxic T lymphocytes (CTLs) that cause tissue destruction in celiac disease is poorly understood. Transcriptomic and epigenetic profiling of primary intestinal CTLs showed massive and distinct temporal transcriptional changes in response to tissue alarmins, while the impact of IL-21 was limited. Only anti-viral pathways were induced in response to all the three stimuli, albeit with differences in dynamics and strength. Moreover, changes in gene expression were primarily independent of changes in H3K27ac, suggesting that other regulatory mechanisms drive the robust transcriptional response. Finally, we found that IL-15/IFNß/IL-21 transcriptional signatures could be linked to transcriptional alterations in risk loci for complex immune diseases. Together these results provide new insights into molecular mechanisms that fuel the activation of CTLs under conditions that emulate the inflammatory environment in patients with autoimmune diseases.

Molecular Biomarkers for Celiac Disease: Past, Present and Future.

Celiac disease (CeD) is a complex immune-mediated disorder that is triggered by dietary gluten in genetically predisposed individuals. CeD is characterized by inflammation and villous atrophy of the small intestine, which can lead to gastrointestinal complaints, malnutrition, and malignancies. Currently, diagnosis of CeD relies on serology (antibodies against transglutaminase and endomysium) and small-intestinal biopsies. Since small-intestinal biopsies require invasive upper-endoscopy, and serology cannot predict CeD in an early stage or be used for monitoring disease after initiation of a gluten-free diet, the search for non-invasive biomarkers is ongoing. Here, we summarize current and up-and-coming non-invasive biomarkers that may be able to predict, diagnose, and monitor the progression of CeD. We further discuss how current and emerging techniques, such as (single-cell) transcriptomics and genomics, can be used to uncover the pathophysiology of CeD and identify non-invasive biomarkers.

A Genome-Wide Functional Genomics Approach Identifies Susceptibility Pathways to Fungal Bloodstream Infection in Humans.

BACKGROUND: Candidemia, one of the most common causes of fungal bloodstream infection, leads to mortality rates up to 40% in affected patients. Understanding genetic mechanisms for differential susceptibility to candidemia may aid in designing host-directed therapies. METHODS: We performed the first genome-wide association study on candidemia, and we integrated these data with variants that affect cytokines in different cellular systems stimulated with Candida albicans. RESULTS: We observed strong association between candidemia and a variant, rs8028958, that significantly affects the expression levels of PLA2G4B in blood. We found that up to 35% of the susceptibility loci affect in vitro cytokine production in response to Candida. Furthermore, potential causal genes located within these loci are enriched for lipid and arachidonic acid metabolism. Using an independent cohort, we also showed that the numbers of risk alleles at these loci are negatively correlated with reactive oxygen species and interleukin-6 levels in response to Candida. Finally, there was a significant correlation between susceptibility and allelic scores based on 16 independent candidemia-associated single-nucleotide polymorphisms that affect monocyte-derived cytokines, but not with T cell-derived cytokines. CONCLUSIONS: Our results prioritize the disturbed lipid homeostasis and oxidative stress as potential mechanisms that affect monocyte-derived cytokines to influence susceptibility to candidemia.

Context-specific effects of genetic variants associated with autoimmune disease.

Autoimmune diseases such as rheumatoid arthritis and coeliac disease are typical examples of complex genetic diseases caused by a combination of genetic and non-genetic risk factors. Insight into the genetic risk factors (single nucleotide polymorphisms (SNPs)) has increased since genome-wide association studies (GWAS) became possible in 2007 and, for individual diseases, SNPs can now explain some 15-50% of genetic risk. GWAS have also shown that some 50% of the genetic risk factors for individual autoimmune diseases overlap between different diseases. Thus, shared risk factors may converge to pathways that, when perturbed by genetic variation, predispose to autoimmunity in general. This raises the question of what determines disease specificity, and suggests that identical risk factors may have different effects in various autoimmune diseases. Addressing this question requires translation of genetic risk factors to causal genes and then to molecular and cellular pathways. Since >90% of the genetic risk factors are found in the non-coding part of the genome (i.e. outside the exons of protein-coding genes) and can have an impact on gene regulation, there is an urgent need to better understand the non-coding part of the genome. Here, we will outline the methods being used to unravel the gene regulatory networks perturbed in autoimmune diseases and the importance of doing this in the relevant cell types. We will highlight findings in coeliac disease, which manifests in the small intestine, to demonstrate how cell type and disease context can impact on the consequences of genetic risk factors.

Understanding Celiac Disease by Genomics.

Celiac disease (CeD) is a complex immune-mediated disease. Genetic studies have implicated 43 predisposing loci that collectively explain some 50% of the genetic variance in CeD. More than ∼90% of CeD-associated single nucleotide polymorphisms (SNPs) localize to the non-coding genome, which we need to better understand to translate genetic knowledge into clinical practice. New genomic technologies and resources are permitting a systematic analysis of the functional elements in the non-coding part of the genome. Here we explain how investigating the regulatory and epigenomic landscape will help to pinpoint the cell types involved in CeD, and the driver genes and gene regulatory networks that are affected by CeD-associated SNPs.

A liver-specific long noncoding RNA with a role in cell viability is elevated in human nonalcoholic steatohepatitis.

Hepatocyte apoptosis in nonalcoholic steatohepatitis (NASH) can lead to fibrosis and cirrhosis, which permanently damage the liver. Understanding the regulation of hepatocyte apoptosis is therefore important to identify therapeutic targets that may prevent the progression of NASH to fibrosis. Recently, increasing evidence has shown that long noncoding (lnc) RNAs are involved in various biological processes and that their dysregulation underlies a number of complex human diseases. By performing gene expression profiling of 4,383 lncRNAs in 82 liver samples from individuals with NASH (n = 48), simple steatosis but no NASH (n = 11), and healthy controls (n = 23), we discovered a liver-specific lncRNA (RP11-484N16.1) on chromosome 18 that showed significantly elevated expression in the liver tissue of NASH patients. This lncRNA, which we named lnc18q22.2 based on its chromosomal location, correlated with NASH grade (r = 0.51, P = 8.11 × 10-7 ), lobular inflammation (r = 0.49, P = 2.35 × 10-6 ), and nonalcoholic fatty liver disease activity score (r = 0.48, P = 4.69 × 10-6 ). The association of lnc18q22.2 to liver steatosis and steatohepatitis was replicated in 44 independent liver biopsies (r = 0.47, P = 0.0013). We provided a genetic structure of lnc18q22.2 showing an extended exon 2 in liver. Knockdown of lnc18q22.2 in four different hepatocyte cell lines resulted in severe phenotypes ranging from reduced cell growth to lethality. This observation was consistent with pathway analyses of genes coexpressed with lnc18q22.2 in human liver or affected by lnc18q22.2 knockdown. CONCLUSION: We identified an lncRNA that can play an important regulatory role in liver function and provide new insights into the regulation of hepatocyte viability in NASH. (Hepatology 2017;66:794-808).

Refined mapping of autoimmune disease associated genetic variants with gene expression suggests an important role for non-coding RNAs.

Genome-wide association and fine-mapping studies in 14 autoimmune diseases (AID) have implicated more than 250 loci in one or more of these diseases. As more than 90% of AID-associated SNPs are intergenic or intronic, pinpointing the causal genes is challenging. We performed a systematic analysis to link 460 SNPs that are associated with 14 AID to causal genes using transcriptomic data from 629 blood samples. We were able to link 71 (39%) of the AID-SNPs to two or more nearby genes, providing evidence that for part of the AID loci multiple causal genes exist. While 54 of the AID loci are shared by one or more AID, 17% of them do not share candidate causal genes. In addition to finding novel genes such as ULK3, we also implicate novel disease mechanisms and pathways like autophagy in celiac disease pathogenesis. Furthermore, 42 of the AID SNPs specifically affected the expression of 53 non-coding RNA genes. To further understand how the non-coding genome contributes to AID, the SNPs were linked to functional regulatory elements, which suggest a model where AID genes are regulated by network of chromatin looping/non-coding RNAs interactions. The looping model also explains how a causal candidate gene is not necessarily the gene closest to the AID SNP, which was the case in nearly 50% of cases.

An iPSC-derived small intestine-on-chip with self-organizing epithelial, mesenchymal, and neural cells.

Human induced pluripotent stem cell (hiPSC)-derived intestinal organoids are valuable tools for researching developmental biology and personalized therapies, but their closed topology and relative immature state limit applications. Here, we use organ-on-chip technology to develop a hiPSC-derived intestinal barrier with apical and basolateral access in a more physiological in vitro microenvironment. To replicate growth factor gradients along the crypt-villus axis, we locally expose the cells to expansion and differentiation media. In these conditions, intestinal epithelial cells self-organize into villus-like folds with physiological barrier integrity, and myofibroblasts and neurons emerge and form a subepithelial tissue in the bottom channel. The growth factor gradients efficiently balance dividing and mature cell types and induce an intestinal epithelial composition, including absorptive and secretory lineages, resembling the composition of the human small intestine. This well-characterized hiPSC-derived intestine-on-chip system can facilitate personalized studies on physiological processes and therapy development in the human small intestine.

Coeliac disease in the Trøndelag Health Study (HUNT), Norway, a population-based cohort of coeliac disease patients.

PURPOSE: Coeliac disease (CD) is a common disorder and affects about 1% of the population worldwide. CD in the Trøndelag Health Study (HUNT) is a population-based cohort study which was established to provide new knowledge about CD that can improve the diagnostics and management, prevent the onset or progression and expand the knowledge about the role of genetics of the disease. PARTICIPANTS: The cohort is based on the fourth wave of the population-based HUNT study (HUNT4), Norway, performed during 2017-2019, also including linkage to hospital records and the Norwegian Patient Registry (NPR). A total of 54 541 HUNT4 participants with available sera were screened for CD by serology. All seropositive participants were invited to a clinical assessment, including endoscopy with duodenal biopsies, during 2019-2023. FINDINGS TO DATE: A total of 1107 HUNT4 participants (2%) were seropositive for CD and 1048 were eligible for clinical assessment, including biopsy. Of these, 724 participants attended the clinical assessment and 482 were identified with CD. In addition, 371 participants with CD were identified through the hospital records and NPR. In total, 853 participants in HUNT4 with biopsy-verified CD diagnosis were identified. FUTURE PLANS: All participants in the study will be invited to a follow-up assessment after at least 1 year, including repeated standard serological testing, endoscopy and tissue sampling. The collected data and material will be used to establish the true population-based prevalence of CD. The consequences of CD, including symptoms, deficiencies and comorbidity, will be investigated and possible triggers and predictors, will be studied. With access to serum samples from the previous HUNT surveys in HUNT Biobank, serological signs of CD in prediagnostic samples of seropositive individuals will be used. Genetic studies will identify new CD markers, assess genotype-phenotype links and explore gene-environment correlations. REGISTRATION: clinicaltrials.gov identifier: NCT04041622.

Genetic mapping across autoimmune diseases reveals shared associations and mechanisms.

Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.

Antigen-driven colonic inflammation is associated with development of dysplasia in primary sclerosing cholangitis.

Primary sclerosing cholangitis (PSC) is an immune-mediated disease of the bile ducts that co-occurs with inflammatory bowel disease (IBD) in almost 90% of cases. Colorectal cancer is a major complication of patients with PSC and IBD, and these patients are at a much greater risk compared to patients with IBD without concomitant PSC. Combining flow cytometry, bulk and single-cell transcriptomics, and T and B cell receptor repertoire analysis of right colon tissue from 65 patients with PSC, 108 patients with IBD and 48 healthy individuals we identified a unique adaptive inflammatory transcriptional signature associated with greater risk and shorter time to dysplasia in patients with PSC. This inflammatory signature is characterized by antigen-driven interleukin-17A (IL-17A)+ forkhead box P3 (FOXP3)+ CD4 T cells that express a pathogenic IL-17 signature, as well as an expansion of IgG-secreting plasma cells. These results suggest that the mechanisms that drive the emergence of dysplasia in PSC and IBD are distinct and provide molecular insights that could guide prevention of colorectal cancer in individuals with PSC.

Using Existing Clinical Information Models for Dutch Quality Registries to Reuse Data and Follow COUMT Paradigm.

BACKGROUND: Reuse of health care data for various purposes, such as the care process, for quality measurement, research, and finance, will become increasingly important in the future; therefore, "Collect Once Use Many Times" (COUMT). Clinical information models (CIMs) can be used for content standardization. Data collection for national quality registries (NQRs) often requires manual data entry or batch processing. Preferably, NQRs collect required data by extracting data recorded during the health care process and stored in the electronic health record. OBJECTIVES: The first objective of this study was to analyze the level of coverage of data elements in NQRs with developed Dutch CIMs (DCIMs). The second objective was to analyze the most predominant DCIMs, both in terms of the coverage of data elements as well as in their prevalence across existing NQRs. METHODS: For the first objective, a mapping method was used which consisted of six steps, ranging from a description of the clinical pathway to a detailed mapping of data elements. For the second objective, the total number of data elements that matched with a specific DCIM was counted and divided by the total number of evaluated data elements. RESULTS: An average of 83.0% (standard deviation: 11.8%) of data elements in studied NQRs could be mapped to existing DCIMs . In total, 5 out of 100 DCIMs were needed to map 48.6% of the data elements. CONCLUSION: This study substantiates the potential of using existing DCIMs for data collection in Dutch NQRs and gives direction to further implementation of DCIMs. The developed method is applicable to other domains. For NQRs, implementation should start with the five DCIMs that are most prevalently used in the NQRs. Furthermore, a national agreement on the leading principle of COUMT for the use and implementation for DCIMs and (inter)national code lists is needed.