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Etiology and Phenotypes of Cardiomyopathy in Southern Africa: The IMHOTEP Multicenter Pilot Study
Background: Cardiomyopathies are an important cause of heart failure in Africa yet there are limited data on etiology and clinical phenotypes. Objectives: The IMHOTEP (African Cardiomyopathy and Myocarditis Registry Program) was designed to systematically collect data on individuals diagnosed with cardiomyopathy living in Africa. Methods: In this multicenter pilot study, patients (age ≥13 years) were eligible for inclusion if they had a diagnosis of cardiomyopathy or myocarditis. Cases were grouped and analyzed according to phenotype; dilated cardiomyopathy (DCM) including myocarditis and peripartum cardiomyopathy, hypertrophic cardiomyopathy (HCM), arrhythmogenic cardiomyopathy (ACM), and restrictive cardiomyopathy (RCM). Results: A total of 665 unrelated index cases (median age 35 [27-44] years; 51.1% female) were recruited at 3 centers in South Africa and 1 center in Mozambique. DCM (n = 478) was the most common type of cardiomyopathy, accounting for 72% of the cohort; ACM (n = 78), HCM (n = 70), and RCM (n = 39) were less frequent. While the age of onset and sex distribution of HCM and ACM were similar to European and North American populations, DCM and RCM had a younger age of onset and occurred more frequently in women and those with African ancestry. Causes of cardiomyopathy were diverse; familial (27%), nonfamilial/idiopathic (36%), and secondary (37%) etiologies were observed. Conclusions: In the largest study of cardiomyopathy to-date on the African continent, we observe that DCM is the dominant form of cardiomyopathy in Southern Africa. The age of onset was significantly younger in African patients with notable sex and ethnic disparities in DCM.
Pathogen-derived HLA-E bound epitopes reveal broad primary anchor pocket tolerability and conformationally malleable peptide binding
AbstractThrough major histocompatibility complex class Ia leader sequence-derived (VL9) peptide binding and CD94/NKG2 receptor engagement, human leucocyte antigen E (HLA-E) reports cellular health to NK cells. Previous studies demonstrated a strong bias for VL9 binding by HLA-E, a preference subsequently supported by structural analyses. However,Mycobacteria tuberculosis(Mtb) infection and Rhesus cytomegalovirus-vectored SIV vaccinations revealed contexts where HLA-E and the rhesus homologue, Mamu-E, presented diverse pathogen-derived peptides to CD8+T cells, respectively. Here we present crystal structures of HLA-E in complex with HIV and Mtb-derived peptides. We show that despite the presence of preferred primary anchor residues, HLA-E-bound peptides can adopt alternative conformations within the peptide binding groove. Furthermore, combined structural and mutagenesis analyses illustrate a greater tolerance for hydrophobic and polar residues in the primary pockets than previously appreciated. Finally, biochemical studies reveal HLA-E peptide binding and exchange characteristics with potential relevance to its alternative antigen presenting function in vivo.
High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response.
Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is a global health challenge requiring better understanding of pathophysiology and new therapeutic approaches. Here, we applied high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (noninfected critical illness, postoperative inflammation, and healthy volunteers) involving 2612 samples (from 1611 patients) and 4553 liquid chromatography-mass spectrometry analyses acquired through a single batch of continuous measurements, with a throughput of 100 samples per day. We show how this scale of data can delineate proteins, pathways, and coexpression modules in sepsis and be integrated with paired leukocyte transcriptomic data (837 samples from n = 649 patients). We mapped the plasma proteomic landscape of the host response in sepsis, including changes over time, and identified features relating to etiology, clinical phenotypes (including organ failures), and severity. This work reveals subphenotypes informative for sepsis response state, disease processes, and outcome; identifies potential biomarkers; and advances opportunities for a precision medicine approach to sepsis.
A disease-associated gene desert directs macrophage inflammation through ETS2.
Increasing rates of autoimmune and inflammatory disease present a burgeoning threat to human health1. This is compounded by the limited efficacy of available treatments1 and high failure rates during drug development2, highlighting an urgent need to better understand disease mechanisms. Here we show how functional genomics could address this challenge. By investigating an intergenic haplotype on chr21q22-which has been independently linked to inflammatory bowel disease, ankylosing spondylitis, primary sclerosing cholangitis and Takayasu's arteritis3-6-we identify that the causal gene, ETS2, is a central regulator of human inflammatory macrophages and delineate the shared disease mechanism that amplifies ETS2 expression. Genes regulated by ETS2 were prominently expressed in diseased tissues and more enriched for inflammatory bowel disease GWAS hits than most previously described pathways. Overexpressing ETS2 in resting macrophages reproduced the inflammatory state observed in chr21q22-associated diseases, with upregulation of multiple drug targets, including TNF and IL-23. Using a database of cellular signatures7, we identified drugs that might modulate this pathway and validated the potent anti-inflammatory activity of one class of small molecules in vitro and ex vivo. Together, this illustrates the power of functional genomics, applied directly in primary human cells, to identify immune-mediated disease mechanisms and potential therapeutic opportunities.
Mouse podoplanin supports adhesion and aggregation of platelets under arterial shear: A novel mechanism of haemostasis.
The podoplanin-CLEC-2 axis is critical in mice for prevention of hemorrhage in the cerebral vasculature during mid-gestation. This raises the question as to how platelets are captured by podoplanin on neuroepithelial cells in a high shear environment. In this study, we demonstrate that mouse platelets form stable aggregates on mouse podoplanin at arterial shear through a CLEC-2 and Src kinase-dependent pathway. Adhesion and aggregation are also dependent on the platelet glycoprotein (GP) receptors, integrin αIIbβ3 and GPIb, and the feedback agonists ADP and thromboxane A2 (TxA2). CLEC-2 does not bind to von Willebrand factor (VWF) suggesting that the interaction with podoplanin is sufficient to both tether and activate platelets. Consistent with this, the surface plasmon resonance measurements reveal that mouse CLEC-2 binds to mouse podoplanin with nanomolar affinity. The present findings demonstrate a novel pathway of hemostasis in which podoplanin supports platelet capture and activation at arteriolar rates of shear.
Functional heterogeneity and high frequencies of cytomegalovirus-specific CD8(+) T lymphocytes in healthy seropositive donors.
Human cytomegalovirus (HCMV) infection is largely asymptomatic in the immunocompetent host, but remains a major cause of morbidity in immunosuppressed individuals. Using the recently described technique of staining antigen-specific CD8(+) T cells with peptide-HLA tetrameric complexes, we have demonstrated high levels of antigen-specific cells specific for HCMV peptides and show that this may exceed 4% of CD8(+) T cells in immunocompetent donors. Moreover, by staining with tetramers in combination with antibodies to cell surface markers and intracellular cytokines, we demonstrate functional heterogeneity of HCMV-specific populations. A substantial proportion of these are effector cytotoxic T lymphocytes, as demonstrated by their ability to lyse peptide-pulsed targets in "fresh" killing assays. These data suggest that the immune response to HCMV is periodically boosted by a low level of HCMV replication and that sustained immunological surveillance contributes to the maintenance of host-pathogen homeostasis. These observations should improve our understanding of the immunobiology of persistent viral infection.
A retrospective analysis of outcomes in low- and intermediate-high-risk pulmonary embolism patients managed on an ambulatory medical unit in the UK.
Pulmonary embolism (PE) is common and guidelines recommend outpatient care only for PE patients with low predicted mortality. Outcomes for patients with intermediate-to-high predicted mortality managed as outpatients are unknown. Electronic records were analysed for adults with PE managed on our ambulatory care unit over 2 years. Patients were stratified into low or intermediate-to-high mortality risk groups using the Pulmonary Embolism Severity Index (PESI). Primary outcomes were the proportion of patients ambulated, 30-day all-cause mortality, 30-day PE-specific mortality and 30-day re-admission rate. Of 199 PE patients, 74% were ambulated and at 30 days, all-cause mortality was 2% (four out of 199) and PE-specific mortality was 1% (two out of 199). Ambulated patients had lower PESI scores, better vital signs and lower troponin levels (morning attendance favoured ambulation). Over a third of ambulated patients had an intermediate-to-high risk PESI score but their all-cause mortality rate was low at 1.9% (one out of 52). In patients with intermediate-to-high risk, oxygen saturation was higher and pulse rate lower in those who were ambulated. Re-admission rate did not differ between ambulated and admitted patients. Two-thirds of patients with intermediate-to-high risk PE were ambulated and their mortality rate remained low. It is possible for selected patients with intermediate-to-high risk PESI scores to be safely ambulated.
Pillar data-acquisition strategies for cryo-electron tomography of beam-sensitive biological samples
For cryo-electron tomography (cryo-ET) of beam-sensitive biological specimens, a planar sample geometry is typically used. As the sample is tilted, the effective thickness of the sample along the direction of the electron beam increases and the signal-to-noise ratio concomitantly decreases, limiting the transfer of information at high tilt angles. In addition, the tilt range where data can be collected is limited by a combination of various sample-environment constraints, including the limited space in the objective lens pole piece and the possible use of fixed conductive braids to cool the specimen. Consequently, most tilt series are limited to a maximum of ±70°, leading to the presence of a missing wedge in Fourier space. The acquisition of cryo-ET data without a missing wedge, for example using a cylindrical sample geometry, is hence attractive for volumetric analysis of low-symmetry structures such as organelles or vesicles, lysis events, pore formation or filaments for which the missing information cannot be compensated by averaging techniques. Irrespective of the geometry, electron-beam damage to the specimen is an issue and the first images acquired will transfer more high-resolution information than those acquired last. There is also an inherent trade-off between higher sampling in Fourier space and avoiding beam damage to the sample. Finally, the necessity of using a sufficient electron fluence to align the tilt images means that this fluence needs to be fractionated across a small number of images; therefore, the order of data acquisition is also a factor to consider. Here, an n-helix tilt scheme is described and simulated which uses overlapping and interleaved tilt series to maximize the use of a pillar geometry, allowing the entire pillar volume to be reconstructed as a single unit. Three related tilt schemes are also evaluated that extend the continuous and classic dose-symmetric tilt schemes for cryo-ET to pillar samples to enable the collection of isotropic information across all spatial frequencies. A fourfold dose-symmetric scheme is proposed which provides a practical compromise between uniform information transfer and complexity of data acquisition.
Structural and functional characterization of nanobodies that neutralize Omicron variants of SARS-CoV-2.
The Omicron strains of SARS-CoV-2 pose a significant challenge to the development of effective antibody-based treatments as immune evasion has compromised most available immune therapeutics. Therefore, in the 'arms race' with the virus, there is a continuing need to identify new biologics for the prevention or treatment of SARS-CoV-2 infections. Here, we report the isolation of nanobodies that bind to the Omicron BA.1 spike protein by screening nanobody phage display libraries previously generated from llamas immunized with either the Wuhan or Beta spike proteins. The structure and binding properties of three of these nanobodies (A8, H6 and B5-5) have been characterized in detail providing insight into their binding epitopes on the Omicron spike protein. Trimeric versions of H6 and B5-5 neutralized the SARS-CoV-2 variant of concern BA.5 both in vitro and in the hamster model of COVID-19 following nasal administration. Thus, either alone or in combination could serve as starting points for the development of new anti-viral immunotherapeutics.
Cytoplasmic Citrate Flux Modulates the Immune Stimulatory NKG2D Ligand MICA in Cancer Cells.
Immune surveillance of cancer cells is facilitated by the Natural Killer Group 2D (NKG2D) receptor expressed by different lymphocyte subsets. It recognizes NKG2D ligands that are rarely expressed on healthy cells, but upregulated by tumorigenesis, presenting a target for immunological clearance. The molecular mechanisms responsible for NKG2D ligand regulation remain complex. Here we report that cancer cell metabolism supports constitutive surface expression of the NKG2D ligand MHC class I chain-related proteins A (MICA). Knockout of the N-glycosylation gene N-acetylglucosaminyltransferase V (MGAT5) in HEK293 cells induced altered metabolism and continuous high MICA surface expression. MGAT5 knockout cells were used to examine the association of cell metabolism and MICA expression through genetic, pharmacological and metabolic assays. Findings were verified in cancer cell lines. Cells with constitutive high MICA expression showed enhanced spare respiratory capacity and elevated mitochondrial efflux of citrate, determined by extracellular flux analysis and metabolomics. MICA expression was reduced by inhibitors of mitochondrial function, FCCP and etomoxir e.g., and depended on conversion of citrate to acetyl-CoA and oxaloacetate by ATP citrate lyase, which was also observed in several cancer cell types. Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) analysis revealed that upregulated MICA transcription was associated with an open chromatin structure at the MICA transcription start site. We identify mitochondria and cytoplasmic citrate as key regulators of constitutive MICA expression and we propose that metabolic reprogramming of certain cancer cells facilitates MICA expression and NKG2D-mediated immune recognition.
An isoform quantitative trait locus in SBNO2 links genetic susceptibility to Crohn's disease with defective antimicrobial activity.
Despite major advances in linking single genetic variants to single causal genes, the significance of genetic variation on transcript-level regulation of expression, transcript-specific functions, and relevance to human disease has been poorly investigated. Strawberry notch homolog 2 (SBNO2) is a candidate gene in a susceptibility locus with different variants associated with Crohn's disease and bone mineral density. The SBNO2 locus is also differentially methylated in Crohn's disease but the functional mechanisms are unknown. Here we show that the isoforms of SBNO2 are differentially regulated by lipopolysaccharide and IL-10. We identify Crohn's disease associated isoform quantitative trait loci that negatively regulate the expression of the noncanonical isoform 2 corresponding with the methylation signals at the isoform 2 promoter in IBD and CD. The two isoforms of SBNO2 drive differential gene networks with isoform 2 dominantly impacting antimicrobial activity in macrophages. Our data highlight the role of isoform quantitative trait loci to understand disease susceptibility and resolve underlying mechanisms of disease.
Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY.
Accurate placenta pathology assessment is essential for managing maternal and newborn health, but the placenta's heterogeneity and temporal variability pose challenges for histology analysis. To address this issue, we developed the 'Histology Analysis Pipeline.PY' (HAPPY), a deep learning hierarchical method for quantifying the variability of cells and micro-anatomical tissue structures across placenta histology whole slide images. HAPPY differs from patch-based features or segmentation approaches by following an interpretable biological hierarchy, representing cells and cellular communities within tissues at a single-cell resolution across whole slide images. We present a set of quantitative metrics from healthy term placentas as a baseline for future assessments of placenta health and we show how these metrics deviate in placentas with clinically significant placental infarction. HAPPY's cell and tissue predictions closely replicate those from independent clinical experts and placental biology literature.
Extended correlation functions for spatial analysis of multiplex imaging data
Abstract Imaging platforms for generating highly multiplexed histological images are being continually developed and improved. Significant improvements have also been made in the accuracy of methods for automated cell segmentation and classification. However, less attention has focused on the quantification and analysis of the resulting point clouds, which describe the spatial coordinates of individual cells. We focus here on a particular spatial statistical method, the cross-pair correlation function (cross-PCF), which can identify positive and negative spatial correlation between cells across a range of length scales. However, limitations of the cross-PCF hinder its widespread application to multiplexed histology. For example, it can only consider relations between pairs of cells, and cells must be classified using discrete categorical labels (rather than labeling continuous labels such as stain intensity). In this paper, we present three extensions to the cross-PCF which address these limitations and permit more detailed analysis of multiplex images: topographical correlation maps can visualize local clustering and exclusion between cells; neighbourhood correlation functions can identify colocalization of two or more cell types; and weighted-PCFs describe spatial correlation between points with continuous (rather than discrete) labels. We apply the extended PCFs to synthetic and biological datasets in order to demonstrate the insight that they can generate.
Germline and somatic genetic variants in the p53 pathway interact to affect cancer risk, progression and drug response
AbstractInsights into oncogenesis derived from cancer susceptibility loci could facilitate better cancer management and treatment through precision oncology. However, therapeutic applications have thus far been limited by our current lack of understanding regarding both their interactions with somatic cancer driver mutations and their influence on tumorigenesis. Here, by integrating germline datasets relating to cancer susceptibility with tumour data capturing somatically-acquired genetic variation, we provide evidence that single nucleotide polymorphism (SNPs) and somatic mutations in the p53 tumor suppressor pathway can interact to influence cancer development, progression and treatment response. We go on to provide human genetic evidence of a tumor-promoting role for the pro-survival activities of p53, which supports the development of more effective therapy combinations through their inhibition in cancers retaining wild-type p53.SignificanceWe describe significant interactions between heritable and somatic genetic variants in the p53 pathway that affect cancer susceptibility, progression and treatment response. Our results offer evidence of how cancer susceptibility SNPs can interact with cancer driver genes to affect cancer progression and identify novel therapeutic targets.