Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells.

Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal.

Whole-exome sequencing identifies rare genetic variants associated with human plasma metabolites.

Metabolite levels measured in the human population are endophenotypes for biological processes. We combined sequencing data for 3,924 (whole-exome sequencing, WES, discovery) and 2,805 (whole-genome sequencing, WGS, replication) donors from a prospective cohort of blood donors in England. We used multiple approaches to select and aggregate rare genetic variants (minor allele frequency [MAF] < 0.1%) in protein-coding regions and tested their associations with 995 metabolites measured in plasma by using ultra-high-performance liquid chromatography-tandem mass spectrometry. We identified 40 novel associations implicating rare coding variants (27 genes and 38 metabolites), of which 28 (15 genes and 28 metabolites) were replicated. We developed algorithms to prioritize putative driver variants at each locus and used mediation and Mendelian randomization analyses to test directionality at associations of metabolite and protein levels at the ACY1 locus. Overall, 66% of reported associations implicate gene targets of approved drugs or bioactive drug-like compounds, contributing to drug targets' validating efforts.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program.

Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

The influence of rare variants in circulating metabolic biomarkers.

Circulating metabolite levels are biomarkers for cardiovascular disease (CVD). Here we studied, association of rare variants and 226 serum lipoproteins, lipids and amino acids in 7,142 (discovery plus follow-up) healthy participants. We leveraged the information from multiple metabolite measurements on the same participants to improve discovery in rare variant association analyses for gene-based and gene-set tests by incorporating correlated metabolites as covariates in the validation stage. Gene-based analysis corrected for the effective number of tests performed, confirmed established associations at APOB, APOC3, PAH, HAL and PCSK (p<1.32x10-7) and identified novel gene-trait associations at a lower stringency threshold with ACSL1, MYCN, FBXO36 and B4GALNT3 (p<2.5x10-6). Regulation of the pyruvate dehydrogenase (PDH) complex was associated for the first time, in gene-set analyses also corrected for effective number of tests, with IDL and LDL parameters, as well as circulating cholesterol (pMETASKAT<2.41x10-6). In conclusion, using an approach that leverages metabolite measurements obtained in the same participants, we identified novel loci and pathways involved in the regulation of these important metabolic biomarkers. As large-scale biobanks continue to amass sequencing and phenotypic information, analytical approaches such as ours will be useful to fully exploit the copious amounts of biological data generated in these efforts.

The T helper type 2 response to cysteine proteases requires dendritic cell-basophil cooperation via ROS-mediated signaling.

The mechanisms that initiate T helper type 2 (T(H)2) responses are poorly understood. Here we demonstrate that cysteine protease-induced T(H)2 responses occur via 'cooperation' between migratory dermal dendritic cells (DCs) and basophils positive for interleukin 4 (IL-4). Subcutaneous immunization with papain plus antigen induced reactive oxygen species (ROS) in lymph node DCs and in dermal DCs and epithelial cells of the skin. ROS orchestrated T(H)2 responses by inducing oxidized lipids that triggered the induction of thymic stromal lymphopoietin (TSLP) by epithelial cells mediated by Toll-like receptor 4 (TLR4) and the adaptor protein TRIF; by suppressing production of the T(H)1-inducing molecules IL-12 and CD70 in lymph node DCs; and by inducing the DC-derived chemokine CCL7, which mediated recruitment of IL-4(+) basophils to the lymph node. Thus, the T(H)2 response to cysteine proteases requires DC-basophil cooperation via ROS-mediated signaling.

Population-wide copy number variation calling using variant call format files from 6,898 individuals.

Copy number variants (CNVs) play an important role in a number of human diseases, but the accurate calling of CNVs remains challenging. Most current approaches to CNV detection use raw read alignments, which are computationally intensive to process. We use a regression tree-based approach to call germline CNVs from whole-genome sequencing (WGS, >18x) variant call sets in 6,898 samples across four European cohorts, and describe a rich large variation landscape comprising 1,320 CNVs. Eighty-one percent of detected events have been previously reported in the Database of Genomic Variants. Twenty-three percent of high-quality deletions affect entire genes, and we recapitulate known events such as the GSTM1 and RHD gene deletions. We test for association between the detected deletions and 275 protein levels in 1,457 individuals to assess the potential clinical impact of the detected CNVs. We describe complex CNV patterns underlying an association with levels of the CCL3 protein (MAF = 0.15, p = 3.6x10-12 ) at the CCL3L3 locus, and a novel cis-association between a low-frequency NOMO1 deletion and NOMO1 protein levels (MAF = 0.02, p = 2.2x10-7 ). This study demonstrates that existing population-wide WGS call sets can be mined for germline CNVs with minimal computational overhead, delivering insight into a less well-studied, yet potentially impactful class of genetic variant.

Freiburg RNA tools: a central online resource for RNA-focused research and teaching.

The Freiburg RNA tools webserver is a well established online resource for RNA-focused research. It provides a unified user interface and comprehensive result visualization for efficient command line tools. The webserver includes RNA-RNA interaction prediction (IntaRNA, CopraRNA, metaMIR), sRNA homology search (GLASSgo), sequence-structure alignments (LocARNA, MARNA, CARNA, ExpaRNA), CRISPR repeat classification (CRISPRmap), sequence design (antaRNA, INFO-RNA, SECISDesign), structure aberration evaluation of point mutations (RaSE), and RNA/protein-family models visualization (CMV), and other methods. Open education resources offer interactive visualizations of RNA structure and RNA-RNA interaction prediction as well as basic and advanced sequence alignment algorithms. The services are freely available at http://rna.informatik.uni-freiburg.de.

GRIN3B missense mutation as an inherited risk factor for schizophrenia: whole-exome sequencing in a family with a familiar history of psychotic disorders.

Glutamate is the most important excitatory neurotransmitter in the brain. The N-methyl-D-aspartate (NMDA) receptor is a glutamate-gated ionotropic cation channel that is composed of several subunits and modulated by a glycine binding site. Many forms of synaptic plasticity depend on the influx of calcium ions through NMDA receptors, and NMDA receptor dysfunction has been linked to a number of neuropsychiatric disorders, including schizophrenia. Whole-exome sequencing was performed in a family with a strong history of psychotic disorders over three generations. We used an iterative strategy to obtain condense and meaningful variants. In this highly affected family, we found a frameshift mutation (rs10666583) in the GRIN3B gene, which codes for the GluN3B subunit of the NMDA receptor in all family members with a psychotic disorder, but not in the healthy relatives. Matsuno et al., also reported this null variant as a risk factor for schizophrenia in 2015. In a broader sample of 22 patients with psychosis, the allele frequency of the rs10666583 mutation variant was increased compared to those of healthy population samples and unaffected relatives. Compared to the 1000 Genomes Project population, we found a significant increase of this variant with a large effect size among patients. The amino acid shift degrades the S1/S2 glycine binding domain of the dominant modulatory GluN3B subunit of the NMDA receptor, which subsequently affects the permeability of the channel pore to calcium ions. A decreased glycine affinity for the GluN3B subunit might cause impaired functional capability of the NMDA receptor and could be an important risk factor for the pathogenesis of psychotic disorders.

MoDPepInt: an interactive web server for prediction of modular domain-peptide interactions.

UNLABELLED: MoDPepInt (Modular Domain Peptide Interaction) is a new easy-to-use web server for the prediction of binding partners for modular protein domains. Currently, we offer models for SH2, SH3 and PDZ domains via the tools SH2PepInt, SH3PepInt and PDZPepInt, respectively. More specifically, our server offers predictions for 51 SH2 human domains and 69 SH3 human domains via single domain models, and predictions for 226 PDZ domains across several species, via 43 multidomain models. All models are based on support vector machines with different kernel functions ranging from polynomial, to Gaussian, to advanced graph kernels. In this way, we model non-linear interactions between amino acid residues. Results were validated on manually curated datasets achieving competitive performance against various state-of-the-art approaches. AVAILABILITY AND IMPLEMENTATION: The MoDPepInt server is available under the URL http://modpepint.informatik.uni-freiburg.de/.

Cluster based prediction of PDZ-peptide interactions.

BACKGROUND: PDZ domains are one of the most promiscuous protein recognition modules that bind with short linear peptides and play an important role in cellular signaling. Recently, few high-throughput techniques (e.g. protein microarray screen, phage display) have been applied to determine in-vitro binding specificity of PDZ domains. Currently, many computational methods are available to predict PDZ-peptide interactions but they often provide domain specific models and/or have a limited domain coverage. RESULTS: Here, we composed the largest set of PDZ domains derived from human, mouse, fly and worm proteomes and defined binding models for PDZ domain families to improve the domain coverage and prediction specificity. For that purpose, we first identified a novel set of 138 PDZ families, comprising of 548 PDZ domains from aforementioned organisms, based on efficient clustering according to their sequence identity. For 43 PDZ families, covering 226 PDZ domains with available interaction data, we built specialized models using a support vector machine approach. The advantage of family-wise models is that they can also be used to determine the binding specificity of a newly characterized PDZ domain with sufficient sequence identity to the known families. Since most current experimental approaches provide only positive data, we have to cope with the class imbalance problem. Thus, to enrich the negative class, we introduced a powerful semi-supervised technique to generate high confidence non-interaction data. We report competitive predictive performance with respect to state-of-the-art approaches. CONCLUSIONS: Our approach has several contributions. First, we show that domain coverage can be increased by applying accurate clustering technique. Second, we developed an approach based on a semi-supervised strategy to get high confidence negative data. Third, we allowed high order correlations between the amino acid positions in the binding peptides. Fourth, our method is general enough and will easily be applicable to other peptide recognition modules such as SH2 domains and finally, we performed a genome-wide prediction for 101 human and 102 mouse PDZ domains and uncovered novel interactions with biological relevance. We make all the predictive models and genome-wide predictions freely available to the scientific community.

A graph kernel approach for alignment-free domain-peptide interaction prediction with an application to human SH3 domains.

MOTIVATION: State-of-the-art experimental data for determining binding specificities of peptide recognition modules (PRMs) is obtained by high-throughput approaches like peptide arrays. Most prediction tools applicable to this kind of data are based on an initial multiple alignment of the peptide ligands. Building an initial alignment can be error-prone, especially in the case of the proline-rich peptides bound by the SH3 domains. RESULTS: Here, we present a machine-learning approach based on an efficient graph-kernel technique to predict the specificity of a large set of 70 human SH3 domains, which are an important class of PRMs. The graph-kernel strategy allows us to (i) integrate several types of physico-chemical information for each amino acid, (ii) consider high-order correlations between these features and (iii) eliminate the need for an initial peptide alignment. We build specialized models for each human SH3 domain and achieve competitive predictive performance of 0.73 area under precision-recall curve, compared with 0.27 area under precision-recall curve for state-of-the-art methods based on position weight matrices. We show that better models can be obtained when we use information on the noninteracting peptides (negative examples), which is currently not used by the state-of-the art approaches based on position weight matrices. To this end, we analyze two strategies to identify subsets of high confidence negative data. The techniques introduced here are more general and hence can also be used for any other protein domains, which interact with short peptides (i.e. other PRMs). AVAILABILITY: The program with the predictive models can be found at http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/SH3PepInt.tar.gz. We also provide a genome-wide prediction for all 70 human SH3 domains, which can be found under http://www.bioinf.uni-freiburg.de/Software/SH3PepInt/Genome-Wide-Predictions.tar.gz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Enteric commensal bacteria potentiate epithelial restitution via reactive oxygen species-mediated inactivation of focal adhesion kinase phosphatases.

The mechanisms by which enteric commensal microbiota influence maturation and repair of the epithelial barrier are relatively unknown. Epithelial restitution requires active cell migration, a process dependent on dynamic turnover of focal cell-matrix adhesions (FAs). Here, we demonstrate that natural, commensal bacteria stimulate generation of reactive oxygen species (ROS) in intestinal epithelia. Bacteria-mediated ROS generation induces oxidation of target cysteines in the redox-sensitive tyrosine phosphatases, LMW-PTP and SHP-2, which in turn results in increased phosphorylation of focal adhesion kinase (FAK), a key protein regulating the turnover of FAs. Accordingly, phosphorylation of FAK substrate proteins, focal adhesion formation, and cell migration are all significantly enhanced by bacterial contact in both in vitro and in vivo models of wound closure. These results suggest that commensal bacteria regulate cell migration via induced generation of ROS in epithelial cells.

Muscadine grape skin extract reverts snail-mediated epithelial mesenchymal transition via superoxide species in human prostate cancer cells.

BACKGROUND: Snail transcription factor can induce epithelial-mesenchymal transition (EMT), associated with decreased cell adhesion-associated molecules like E-cadherin, increased mesenchymal markers like vimentin, leading to increased motility, invasion and metastasis. Muscadine grape skin extract (MSKE) has been shown to inhibit prostate cancer cell growth and induce apoptosis without affecting normal prostate epithelial cells. We investigated novel molecular mechanisms by which Snail promotes EMT in prostate cancer cells via Reactive Oxygen Species (ROS) and whether it can be antagonized by MSKE. METHODS: ARCaP and LNCaP cells overexpressing Snail were utilized to examine levels of reactive oxygen species (ROS), specifically, superoxide, in vitro using Dihydroethidium (DHE) or HydroCy3 dyes. Mitosox staining was performed to determine whether the source of ROS was mitochondrial in origin. We also investigated the effect of Muscadine grape skin extract (MSKE) on EMT marker expression by western blot analysis. Migration and cell viability using MTS proliferation assay was performed following MSKE treatments. RESULTS: Snail overexpression in ARCaP and LNCaP cells was associated with increased concentration of mitochondrial superoxide, in vitro. Interestingly, MSKE decreased superoxide levels in ARCaP and LNCaP cells. Additionally, MSKE and Superoxide Dismutase (SOD) reverted EMT as evidenced by decreased vimentin levels and re-induction of E-cadherin expression in ARCaP-Snail cells after 3 days, concomitant with reduced cell migration. MSKE also decreased Stat-3 activity in ARCaP-Snail cells. CONCLUSIONS: This study shows that superoxide species may play a role in Snail transcription factor-mediated EMT. Therefore, therapeutic targeting of Snail with various antioxidants such as MSKE may prove beneficial in abrogating EMT and ROS-mediated tumor progression in human prostate cancer.

Genetic influences on circulating retinol and its relationship to human health.

Retinol is a fat-soluble vitamin that plays an essential role in many biological processes throughout the human lifespan. Here, we perform the largest genome-wide association study (GWAS) of retinol to date in up to 22,274 participants. We identify eight common variant loci associated with retinol, as well as a rare-variant signal. An integrative gene prioritisation pipeline supports novel retinol-associated genes outside of the main retinol transport complex (RBP4:TTR) related to lipid biology, energy homoeostasis, and endocrine signalling. Genetic proxies of circulating retinol were then used to estimate causal relationships with almost 20,000 clinical phenotypes via a phenome-wide Mendelian randomisation study (MR-pheWAS). The MR-pheWAS suggests that retinol may exert causal effects on inflammation, adiposity, ocular measures, the microbiome, and MRI-derived brain phenotypes, amongst several others. Conversely, circulating retinol may be causally influenced by factors including lipids and serum creatinine. Finally, we demonstrate how a retinol polygenic score could identify individuals more likely to fall outside of the normative range of circulating retinol for a given age. In summary, this study provides a comprehensive evaluation of the genetics of circulating retinol, as well as revealing traits which should be prioritised for further investigation with respect to retinol related therapies or nutritional intervention.

Quantitative imaging of cartilage and bone morphology, reactive oxygen species, and vascularization in a rodent model of osteoarthritis.

OBJECTIVE: To assess temporal changes in cartilage and bone morphology, reactive oxygen species (ROS), and vascularization in rats with monosodium iodoacetate (MIA)-induced osteoarthritis (OA), using advanced imaging methodologies. METHODS: Right knees of 8-week-old male Wistar rats were injected with 1 mg MIA in 50 µl saline and left knees were injected with 50 µl saline as controls. After 1, 2, and 3 weeks (n = 5 at each time point), changes in cartilage morphology and composition were quantified using equilibrium partitioning of an ionic contrast agent microfocal computed tomography (µCT), and changes in subchondral and trabecular bone were assessed by standard µCT. ROS were characterized by in vivo fluorescence imaging at 1, 11, and 21 days (n = 5 at each time point). Three weeks following fluorescence imaging, alterations in knee joint vascularity were quantified with µCT after perfusion of a vascular contrast agent. RESULTS: Femoral cartilage volume, thickness, and proteoglycan content were significantly decreased in MIA-injected knees compared with control knees, accompanied by loss of trabecular bone and erosion of subchondral bone surface. ROS quantities were significantly increased 1 day after MIA injection and subsequently decreased gradually, having returned to normal by 21 days. Vascularity in whole knees and distal femora was significantly increased at 21 days after MIA injection. CONCLUSION: Contrast-enhanced µCT and fluorescence imaging were combined to characterize articular cartilage, subchondral bone, vascularization, and ROS, providing unprecedented 3-dimensional joint imaging and quantification in multiple tissues during OA progression. These advanced imaging techniques have the potential to become standardized methods for comprehensive evaluation of articular joint degeneration and evaluation of therapeutic efficacy.

Folate receptor-targeted antioxidant therapy ameliorates renal ischemia-reperfusion injury.

Antioxidant therapy can protect against ischemic injury, but the inability to selectively target the kidney would require extremely high doses to achieve effective local concentrations of drug. Here, we developed a directed therapeutic that specifically targets an antioxidant to renal proximal tubule cells via the folate receptor. Because a local increase in superoxide contributes to renal ischemic injury, we created the folate-antioxidant conjugate 4-hydroxy-Tempo (tempol)-folate to target folate receptors, which are highly expressed in the proximal tubule. Dihydroethidium high-performance liquid chromatography demonstrated that conjugated tempol retained its efficacy to scavenge superoxide in proximal tubule cells. In a mouse model of renal ischemia-reperfusion injury, tempol-folate reduced renal superoxide levels more effectively than tempol alone. Furthermore, electron spin resonance revealed the successful targeting of the tempol-folate conjugate to the kidney and other tissues expressing folate receptors. Administration of tempol-folate protected the renal function of mice after ischemia-reperfusion injury and inhibited infiltration of macrophages. In conclusion, kidney-specific targeting of an antioxidant has therapeutic potential to prevent renal ischemic injury. Conjugation of other pharmaceuticals to folate may also facilitate the development of treatments for other kidney diseases.

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology.

Blood cells contain functionally important intracellular structures, such as granules, critical to immunity and thrombosis. Quantitative variation in these structures has not been subjected previously to large-scale genetic analysis. We perform genome-wide association studies of 63 flow-cytometry derived cellular phenotypes-including cell-type specific measures of granularity, nucleic acid content and reactivity-in 41,515 participants in the INTERVAL study. We identify 2172 distinct variant-trait associations, including associations near genes coding for proteins in organelles implicated in inflammatory and thrombotic diseases. By integrating with epigenetic data we show that many intracellular structures are likely to be determined in immature precursor cells. By integrating with proteomic data we identify the transcription factor FOG2 as an early regulator of platelet formation and α-granularity. Finally, we show that colocalisation of our associations with disease risk signals can suggest aetiological cell-types-variants in IL2RA and ITGA4 respectively mirror the known effects of daclizumab in multiple sclerosis and vedolizumab in inflammatory bowel disease.