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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.

The resolution of causal genetic variants informs understanding of disease biology. We used regulatory quantitative trait loci (QTLs) from the BLUEPRINT, GTEx and eQTLGen projects to fine-map putative causal variants for 12 immune-mediated diseases. We identify 340 unique loci that colocalize with high posterior probability (≥98%) with regulatory QTLs and apply Bayesian frameworks to fine-map associations at each locus. We show that fine-mapping credible sets derived from regulatory QTLs are smaller compared to disease summary statistics. Further, they are enriched for more functionally interpretable candidate causal variants and for putatively causal insertion/deletion (INDEL) polymorphisms. Finally, we use massively parallel reporter assays to evaluate candidate causal variants at the ITGA4 locus associated with inflammatory bowel disease. Overall, our findings suggest that fine-mapping applied to disease-colocalizing regulatory QTLs can enhance the discovery of putative causal disease variants and enhance insights into the underlying causal genes and molecular mechanisms.

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

Summary 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.

Microglia, the tissue-resident macrophages of the central nervous system (CNS), play critical roles in immune defense, development and homeostasis. However, isolating microglia from humans in large numbers is challenging. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single-cell and bulk RNA sequencing, we identify how age, sex and clinical pathology influence microglia gene expression and which genetic variants have microglia-specific functions using expression quantitative trait loci (eQTL) mapping. We follow up one of our findings using a human induced pluripotent stem cell-based macrophage model to fine-map a candidate causal variant for Alzheimer's disease at the BIN1 locus. Our study provides a population-scale transcriptional map of a critically important cell for human CNS development and disease.

Funder: MS is funded by Medical Research Council (MC-A652-5QA20), Funder: This work was supported by the Wellcome Trust grant (206194) and EU FP7 High Impact Project BLUEPRINT (HEALTH-F5-2011-282510), Neutrophils play fundamental roles in innate immune response, shape adaptive immunity, and are a potentially causal cell type underpinning genetic associations with immune system traits and diseases. Here, we profile the binding of myeloid master regulator PU.1 in primary neutrophils across nearly a hundred volunteers. We show that variants associated with differential PU.1 binding underlie genetically-driven differences in cell count and susceptibility to autoimmune and inflammatory diseases. We integrate these results with other multi-individual genomic readouts, revealing coordinated effects of PU.1 binding variants on the local chromatin state, enhancer-promoter contacts and downstream gene expression, and providing a functional interpretation for 27 genes underlying immune traits. Collectively, these results demonstrate the functional role of PU.1 and its target enhancers in neutrophil transcriptional control and immune disease susceptibility.

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. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these newly 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 3bp indel p.Lys2169del (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis [OMIM 194380], associated with higher 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.

47 p.-11 fig., Mitochondrial DNA (mtDNA) variants influence the risk of late-onset human diseases, but the reasons for this are poorly understood. Undertaking a hypothesis-free analysis of 5,689 blood-derived biomarkers with mtDNA variants in 16,220 healthy donors, here we show that variants defining mtDNA haplogroups Uk and H4 modulate the level of circulating N-formylmethionine (fMet), which initiates mitochondrial protein translation. In human cytoplasmic hybrid (cybrid) lines, fMet modulated both mitochondrial and cytosolic proteins on multiple levels, through transcription, post-translational modification and proteolysis by an N-degron pathway, abolishing known differences between mtDNA haplogroups. In a further 11,966 individuals, fMet levels contributed to all-cause mortality and the disease risk of several common cardiovascular disorders. Together, these findings indicate that fMet plays a key role in common age-related disease through pleiotropic effects on cell proteostasis., This work was supported by Health Data Research UK, which is funded by the UK Medical Research Council, the Engineering and Physical Sciences Research Council, the Economic and Social Research Council, the Department of Health and Social Care (England), the Chief Scientist Office of the Scottish Government Health and Social Care Directorates, the Health and Social Care Research and Development Division (Welsh Government), the Public Health Agency (Northern Ireland), the British Heart Foundation and Wellcome. N.C. is supported by an EBI–Sanger Postdoctoral Fellowship. A.G.-D. receives funding from the NIHR Biomedical Research Centre based at Cambridge University Hospitals NHS Foundation Trust. E.Y.-D. was funded by the Isaac Newton Trust/Wellcome Trust ISSF/University of Cambridge Joint Research Grants Scheme. J.M.M.H. was funded by the NIHR Cambridge BRC (BRC-1215-20014)*. P.F.C.is a Wellcome Trust Principal Research Fellow (212219/Z/18/Z) and a UK NIHR Senior Investigator, who receives support from the Medical Research Council Mitochondrial Biology Unit (MC_UU_00015/9), the Evelyn Trust and the NIHR Biomedical Research Centre based at Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge. C.H.W.-G. is supported by a RCUK/UKRI Research Innovation Fellowship awarded by the Medical Research Council (MR/R007446/1) and by the Cambridge Centre for Parkinson-Plus. N.S. is supported by the Wellcome Trust(grant number 098051 until 30 September 2016 and 206194 from 1 October 2016),the Cambridge BHF Centre of Research Excellence (RE/18/1/34212) and the NIHR Cambridge Biomedical Research Centre Biomedical Resources Grant, University of Cambridge, Cardiovascular Theme (RG64226). J.D. holds a British Heart Foundation Professorship and an NIHR Senior Investigator Award*. R.A.L. is supported by grants from Parkinson’s UK. Sequencing of INTERVAL samples was supported by the Wellcome Trust (grant number 206194). Metabolon metabolomics assays were funded by the NIHR BioResource, the Wellcome Trust (grant number 206194) and the NIHR Cambridge BRC (BRC-1215-20014)*. Nightingale Health NMR assays were funded by the European Commission Framework Programme 7 (HEALTH-F2-2012-279233). SomaLogic assays were funded by Merck and the NIHR Cambridge BRC (BRC-1215-20014)*. ICICLE-PD was funded by Parkinson’s UK (J-0802, G-1301, G-1507) and the Lockhart Parkinson’s Disease Research Fund and supported by the NIHR Newcastle Biomedical Research Unit and the NIHR Cambridge Biomedical Research Centre (146281). The EPIC-Norfolk study (https://doi.org/10.22025/2019.10.105.00004) has received funding from the Medical Research Council (MR/N003284/1 and MC-UU_12015/1) and Cancer Research UK (C864/A14136). Genetic work in the EPIC-Norfolk study was funded by the Medical Research Council (MC_PC_13048). Metabolite measurements in the EPIC-Norfolk study were supported by the MRC Cambridge Initiative in Metabolic Science (MR/L00002/1) and the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement no. 115372.

Tumors subvert immune cell function to evade immune responses, yet the complex mechanisms driving immune evasion remain poorly understood. Here we show that tumors induce de novo steroidogenesis in T lymphocytes to evade anti-tumor immunity. Using a transgenic steroidogenesis-reporter mouse line we identify and characterize de novo steroidogenic immune cells, defining the global gene expression identity of these steroid-producing immune cells and gene regulatory networks by using single-cell transcriptomics. Genetic ablation of T cell steroidogenesis restricts primary tumor growth and metastatic dissemination in mouse models. Steroidogenic T cells dysregulate anti-tumor immunity, and inhibition of the steroidogenesis pathway is sufficient to restore anti-tumor immunity. This study demonstrates T cell de novo steroidogenesis as a mechanism of anti-tumor immunosuppression and a potential druggable target., Multiple mechanisms of immune evasion exploited by cancer cells have been described. Here, the authors show that genetic inactivation or pharmacological inhibition of tumor-induced Th2-mediated de novo steroidogenesis are sufficient to restore an efficient anti-tumor immune response and restrict tumor growth.

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, Author summary Cardiovascular diseases (CVD) are the number one cause of death globally. Various metabolic biomarkers including lipid and lipoprotein particles have been implicated as risk factors for the development of CVD. Understanding how these biomarkers are regulated can lead to increased understanding of CVD aetiology and the potential identification of drug targets. Here we take advantage of high resolution measurements on a large cohort of 7,142 healthy blood donors with whole-exome and whole-genome sequencing data to explore the influence of rare variation on circulating metabolic biomarker levels. Using a novel approach leveraging the information gained from various measurements on the same participants we are able to identify a novel biological pathway involved in the regulation of intermediate-density and low-density lipoproteins as well as circulating cholesterol, confirm various established gene associations and identify potential novel gene associations that merit further replication. This work highlights the advantages that can be gained by combining high resolution genotypic and phenotypic measurements in one large cohort.

SummaryBlood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including 563,946 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering the full allele frequency spectrum of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood cell traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell GWAS to interrogate clinically meaningful variants across the full allelic spectrum of human variation.

SUMMARYThousands of genetic associations with phenotypes of blood cells are known, but few are with phenotypes relevant to cell function. We performed GWAS of 63 flow-cytometry phenotypes, including measures of cell granularity, nucleic acid content, and reactivity, in 39,656 participants in the INTERVAL study, identifying 2,172 variant-trait associations. These include associations mediated by functional cellular structures such as secretory granules, implicated in vascular, thrombotic, inflammatory and neoplastic diseases. By integrating our results with epigenetic data and with signals from molecular abundance/disease GWAS, we infer the hematopoietic origins of population phenotypic variation and identify the transcription factor FOG2 as a regulator of plateletα-granularity. We show how flow cytometry genetics can suggest cell types mediating complex disease risk and suggest efficacious drug targets, presenting Daclizumab/Vedolizumab in autoimmune disease as positive controls. Finally, we add to existing evidence supporting IL7/IL7-R as drug targets for multiple sclerosis.

The identification of causal genetic variants for common diseases improves understanding of disease biology. Here we use data from the BLUEPRINT project to identify regulatory quantitative trait loci (QTL) for three primary human immune cell types and use these to fine-map putative causal variants for twelve immune-mediated diseases. We identify 340 unique, non major histocompatibility complex (MHC) disease loci that colocalise with high (>98%) posterior probability with regulatory QTLs, and apply Bayesian frameworks to fine-map associations at each locus. We show that fine-mapping applied to regulatory QTLs yields smaller credible set sizes and higher posterior probabilities for candidate causal variants compared to disease summary statistics. We also describe a systematic under-representation of insertion/deletion (INDEL) polymorphisms in credible sets derived from publicly available disease meta-analysis when compared to QTLs based on genome-sequencing data. Overall, our findings suggest that fine-mapping applied to disease-colocalising regulatory QTLs can enhance the discovery of putative causal disease variants and provide insights into the underlying causal genes and molecular mechanisms.

Summary Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation., Graphical Abstract, Highlights • Largest genome-wide association study of blood cell traits to date • Empiric assessments of omnigenic and infinitesimal models of polygenic variation • Functional insights into how genetic variants impact human hematopoiesis • Assessment of the effect of polygenic trait scores upon blood diseases, Analysis of blood cell traits in the UK Biobank and other cohorts illuminates the full genetic architecture of hematopoietic phenotypes, with evidence supporting the omnigenic model for complex traits and linking polygenic burden with monogenic blood diseases.

Microglia, the tissue resident macrophages of the CNS, are implicated in a broad range of neurological pathologies, from acute brain injury to dementia. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single cell and bulk RNA sequencing, we defined distinct cellular populations of acutelyin vivo-activated microglia, and characterised a dramatic switch in microglial population composition in patients suffering from acute brain injury. We mapped expression quantitative trait loci (eQTLs) in human microglia and show that many disease-associated eQTLs in microglia replicate well in a human induced pluripotent stem cell (hIPSC) derived macrophage model system. Using ATAC-seq from 95 individuals in this hIPSC model we fine-map candidate causal variants at risk loci for Alzheimer’s disease, the most prevalent neurodegenerative condition in acute brain injury patients. Our study provides the first population-scale transcriptional map of a critically important cell for neurodegenerative disorders.

Regulatory variants are often context specific, modulating gene expression in a subset of possible cellular states. Although these genetic effects can play important roles in disease, the molecular mechanisms underlying context specificity are poorly understood. Here, we identified shared quantitative trait loci (QTLs) for chromatin accessibility and gene expression in human macrophages exposed to IFNγ, Salmonella and IFNγ plus Salmonella. We observed that ~60% of stimulus-specific expression QTLs with a detectable effect on chromatin altered the chromatin accessibility in naive cells, thus suggesting that they perturb enhancer priming. Such variants probably influence binding of cell-type-specific transcription factors, such as PU.1, which can then indirectly alter the binding of stimulus-specific transcription factors, such as NF-κB or STAT2. Thus, although chromatin accessibility assays are powerful for fine-mapping causal regulatory variants, detecting their downstream effects on gene expression will be challenging, requiring profiling of large numbers of stimulated cellular states and time points.

The hydrocyanines are a class of dyes that can detect reactive oxygen species (ROS) in cell culture, tissue explants, and in vivo. The hydrocyanines selectively react with radical oxidants, such as superoxide via an amine oxidation mechanism to generate cyanine dyes, thereby imaging ROS. The hydrocyanines can detect nanomolar levels of cellular ROS with tunable emission wavelengths between 560–830 nm. The hydrocyanine dyes have excellent stability against auto-oxidation and can be easily synthesized, and this enabled their rapid commercialization. Herein, we discuss in detail the properties of the hydrocyanine dyes and their current applications across biology and medicine.

Identifying cellular functions dysregulated by disease associated variants could implicate novel pathways for drug targeting or modulation in cell therapies. Variants associated with immune diseases point towards the role of CD4+ regulatory T cells (Tregs), cell type critical for immune homeostasis. To translate the effects of immune disease alleles on Treg function we mapped genetic regulation (QTL) of gene expression and chromatin activity in Tregs. We identified 123 loci where Treg QTLs colocalized with immune disease variants. These colocalizations indicated that dysregulation of key Treg pathways, including cell activation via CD28 and IL-2 signalling mediated by STAT5A contribute to the shared pathobiology of immune diseases. Finally, using disease GWAS signals colocalizing with Treg QTLs, we identified 34 known drug targets and 270 targets with drug tractability evidence. Our study is the first in-depth characterization of immune disease variant effects on Treg gene expression modulation and dysregulation of Treg function.

MotivationCopy number variants (CNVs) are large deletions or duplications at least 50 to 200 base pairs long. They play an important role in multiple disorders, but accurate calling of CNVs remains challenging. Most current approaches to CNV detection use raw read alignments, which are computationally intensive to process.ResultsWe use a regression tree-based approach to call 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. 61.8% of detected events have been previously reported in the Database of Genomic Variants. 23% of high-quality deletions affect entire genes, and we recapitulate known events such as theGSTM1andRHDgene 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 the LD structure and copy number variation underlying the association between levels of the CCL3 protein and a complex structural variant (MAF = 0.15, p = 3.6×10-12) affectingCCL3L3, a paralog of theCCL3gene. We also identify acis-association between a low-frequencyNOMO1deletion and the protein product of this gene (MAF = 0.02, p = 2.2×10-7), for which nocis-ortrans-single nucleotide variant-driven protein quantitative trait locus (pQTL) has been documented to date. This work demonstrates that existing population-wide WGS call-sets can be mined for CNVs with minimal computational overhead, delivering insight into a less well-studied, yet potentially impactful class of genetic variant.AvailabilityThe regression tree based approach, UN-CNVc, is available as an R and bash executable on GitHub athttps://github.com/agilly/un-cnvc.Contacteleftheria.zeggini@helmholtz-muenchen.de;arthur.gilly@helmholtz-muenchen.deSupplementary InformationSupplementary information is appended.

Neutrophils play fundamental roles in innate inflammatory response, shape adaptive immunity1, and have been identified as a potentially causal cell type underpinning genetic associations with immune system traits and diseases2,3 The majority of these variants are non-coding and the underlying mechanisms are not fully understood. Here, we profiled the binding of one of the principal myeloid transcriptional regulators, PU.1, in primary neutrophils across nearly a hundred volunteers, and elucidate the coordinated genetic effects of PU.1 binding variation, local chromatin state, promoter-enhancer interactions and gene expression. We show that PU.1 binding and the associated chain of molecular changes underlie genetically-driven differences in cell count and autoimmune disease susceptibility. Our results advance interpretation for genetic loci associated with neutrophil biology and immune disease.

The role of rare variants in complex traits remains uncharted. Here, we conduct deep whole genome sequencing of 1457 individuals from an isolated population, and test for rare variant burdens across six cardiometabolic traits. We identify a role for rare regulatory variation, which has hitherto been missed. We find evidence of rare variant burdens that are independent of established common variant signals (ADIPOQ and adiponectin, P = 4.2 × 10−8; APOC3 and triglyceride levels, P = 1.5 × 10−26), and identify replicating evidence for a burden associated with triglyceride levels in FAM189B (P = 2.2 × 10−8), indicating a role for this gene in lipid metabolism., Rare genetic variants can contribute to complex traits but this contribution is not well understood. Here, the authors analyse deep whole genome sequencing data across 1457 individuals from an isolated Greek population and find association of rare variant burdens with cardiometabolic traits.

Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

SummaryGlutamate 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.

Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

The original version of this Article contained an error in Fig. 2. In panel a, the two legend items “rare” and “common” were inadvertently swapped. This has been corrected in both the PDF and HTML versions of the Article.

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. Contact: ed.grubierf-inu.kitamrofni@nefokcab Supplementary information: Supplementary data are available at Bioinformatics online.

N-formyl peptide receptors (FPRs) are critical regulators of host defense in phagocytes and are also expressed in epithelia. FPR signaling and function have been extensively studied in phagocytes, yet their functional biology in epithelia is poorly understood. We describe a novel intestinal epithelial FPR signaling pathway that is activated by an endogenous FPR ligand, annexin A1 (ANXA1), and its cleavage product Ac2-26, which mediate activation of ROS by an epithelial NADPH oxidase, NOX1. We show that epithelial cell migration was regulated by this signaling cascade through oxidative inactivation of the regulatory phosphatases PTEN and PTP-PEST, with consequent activation of focal adhesion kinase (FAK) and paxillin. In vivo studies using intestinal epithelial specific Nox1(-/-IEC) and AnxA1(-/-) mice demonstrated defects in intestinal mucosal wound repair, while systemic administration of ANXA1 promoted wound recovery in a NOX1-dependent fashion. Additionally, increased ANXA1 expression was observed in the intestinal epithelium and infiltrating leukocytes in the mucosa of ulcerative colitis patients compared with normal intestinal mucosa. Our findings delineate a novel epithelial FPR1/NOX1-dependent redox signaling pathway that promotes mucosal wound repair.

Radical oxidants, such as superoxide and the hydroxyl radical, play a pivotal role in biology. Technologies that can selectively image radical oxidants in various biological systems can play an important role in biology and medicine. Radical oxidants are critically involved in a wide variety of pathophysiologic events ranging from atherosclerosis to cancer, and radical oxidants are therefore, excellent diagnostic biomarkers for a wide range of diseases. Radical oxidants are also implicated in the efficacy of antibiotics and anticancer drugs, consistently, the radical oxidant probes can be useful in drug discovery process. Radical oxidants are also important in the process of evolution because of their role in DNA mutagenesis and leading to drug resistance. In conclusion, radical oxidants are implicated in over 150 inflammatory diseases and are involved in aging, toxicity, cell growth, signaling, cell differentiation, cell damage, tumor survival and drug efficacy, consequently, there is tremendous interest in imaging radical oxidants in biological systems. Hydrocyanines, therefore, are playing increasingly important role in studying redox and disease biology.

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.

Ultrasound contrast agents (UCAs) have tremendous potential for in vivo molecular imaging because of their high sensitivity. However, the diagnostic potential of UCAs has been difficult to exploit because current UCAs are based on pre-formed microbubbles, which can only detect cell surface receptors. Here, we demonstrate that chemical reactions that generate gas forming molecules can be used to perform molecular imaging by ultrasound in vivo. This new approach was demonstrated by imaging reactive oxygen species in vivo with allylhydrazine, a liquid compound that is converted into nitrogen and propylene gas after reacting with radical oxidants. We demonstrate that allylhydrazine encapsulated within liposomes can detect a 10 micromolar concentration of radical oxidants by ultrasound, and can image oxidative stress in mice, induced by lipopolysaccharide, using a clinical ultrasound system. We anticipate numerous applications of chemically-generated microbubbles for molecular imaging by ultrasound, given ultrasound's ability to detect small increments above the gas saturation limit, its spatial resolution and widespread clinical use.

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.

The accurate and sensitive detection of radical oxidants is a central problem in the field of chemical biology.[1] Radical oxidants can be detected in vitro with fluorescent leucodyes such as dihydroethidium (DHE),[2] dihydrorhodamine (DHR),[3] the hydrocyanines,[4] redoxfluor-1,[5a] and their organelle-specific analogues.[5b] Although these probes are widely used in cell culture, their accuracy is compromised by their high levels of background fluorescence,[6] which is caused by their spontaneous oxidation that is catalyzed by light or oxygen. Radical oxidants can be detected by using DHE, DHR, and the hydrocyanines, as they undergo an amine oxidation reaction[7] with cellular oxidants, such as superoxide or hydroxyl radicals. However, the probes also generate background fluorescence by undergoing the same amine oxidation reaction with air and light; this reaction is often attributed to the effects of singlet oxygen (1O2).[8]

[reaction: see text] Methyl 3-(trialkylsilanyloxy)-2-diazo-3-butenoate undergoes Lewis acid-catalyzed Mukaiyama aldol addition with aromatic and aliphatic aldehydes in the presence of low catalytic amounts of Lewis acids in nearly quantitative yields. Scandium(III) triflate is the preferred catalyst and, notably, addition proceeds without decomposition of the diazo moiety. Diazoacetoacetate products from reactions with aromatic aldehydes undergo rhodium(II)-catalyzed ring closure to cyclobutanones with high diastereocontrol. Examples of complimentary Mannich-type addition reactions with imines are reported.

The low detection sensitivity of enzyme linked immunosorbent assays (ELISAs) is a central problem in science and limits progress in multiple areas of biology and medicine. In this report we demonstrate that the hydrocyanines, a family of fluorescent reactive oxygen species (ROS) probes, can act as turn on fluorescent horseradish peroxidase (HRP) probes and thereby increase the sensitivity of conventional ELISAs by two orders of magnitude.

Summary : 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/ Contact : backofen@informatik.uni-freiburg.de Supplementary information : Supplementary data are available at Bioinformatics online.

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. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-S1-S5) contains supplementary material, which is available to authorized users.