Microscopic examination of spatial transcriptome using Seq-Scope.

Spatial barcoding technologies have the potential to reveal histological details of transcriptomic profiles; however, they are currently limited by their low resolution. Here, we report Seq-Scope, a spatial barcoding technology with a resolution comparable to an optical microscope. Seq-Scope is based on a solid-phase amplification of randomly barcoded single-molecule oligonucleotides using an Illumina sequencing platform. The resulting clusters annotated with spatial coordinates are processed to expose RNA-capture moiety. These RNA-capturing barcoded clusters define the pixels of Seq-Scope that are ∼0.5-0.8 µm apart from each other. From tissue sections, Seq-Scope visualizes spatial transcriptome heterogeneity at multiple histological scales, including tissue zonation according to the portal-central (liver), crypt-surface (colon) and inflammation-fibrosis (injured liver) axes, cellular components including single-cell types and subtypes, and subcellular architectures of nucleus and cytoplasm. Seq-Scope is quick, straightforward, precise, and easy-to-implement and makes spatial single-cell analysis accessible to a wide group of biomedical researchers.

FUBP1 is a general splicing factor facilitating 3' splice site recognition and splicing of long introns.

Splicing of pre-mRNAs critically contributes to gene regulation and proteome expansion in eukaryotes, but our understanding of the recognition and pairing of splice sites during spliceosome assembly lacks detail. Here, we identify the multidomain RNA-binding protein FUBP1 as a key splicing factor that binds to a hitherto unknown cis-regulatory motif. By collecting NMR, structural, and in vivo interaction data, we demonstrate that FUBP1 stabilizes U2AF2 and SF1, key components at the 3' splice site, through multivalent binding interfaces located within its disordered regions. Transcriptional profiling and kinetic modeling reveal that FUBP1 is required for efficient splicing of long introns, which is impaired in cancer patients harboring FUBP1 mutations. Notably, FUBP1 interacts with numerous U1 snRNP-associated proteins, suggesting a unique role for FUBP1 in splice site bridging for long introns. We propose a compelling model for 3' splice site recognition of long introns, which represent 80% of all human introns.

A deep catalogue of protein-coding variation in 983,578 individuals.

Rare coding variants that substantially affect function provide insights into the biology of a gene1-3. However, ascertaining the frequency of such variants requires large sample sizes4-8. Here we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. In total, 23% of the Regeneron Genetics Center Million Exome (RGC-ME) data come from individuals of African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The catalogue includes more than 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss of function (LOF), we identify 3,988 LOF-intolerant genes, including 86 that were previously assessed as tolerant and 1,153 that lack established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions that are depleted of missense variants despite being tolerant of pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this resource of coding variation from the RGC-ME dataset publicly accessible through a variant allele frequency browser.

Plasma proteomic associations with genetics and health in the UK Biobank.

The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics1.

Genetic variants regulating immune cell levels in health and disease.

The complex network of specialized cells and molecules in the immune system has evolved to defend against pathogens, but inadvertent immune system attacks on "self" result in autoimmune disease. Both genetic regulation of immune cell levels and their relationships with autoimmunity are largely undetermined. Here, we report genetic contributions to quantitative levels of 95 cell types encompassing 272 immune traits, in a cohort of 1,629 individuals from four clustered Sardinian villages. We first estimated trait heritability, showing that it can be substantial, accounting for up to 87% of the variance (mean 41%). Next, by assessing ∼8.2 million variants that we identified and confirmed in an extended set of 2,870 individuals, 23 independent variants at 13 loci associated with at least one trait. Notably, variants at three loci (HLA, IL2RA, and SH2B3/ATXN2) overlap with known autoimmune disease associations. These results connect specific cellular phenotypes to specific genetic variants, helping to explicate their involvement in disease.

Common and rare variant associations with clonal haematopoiesis phenotypes.

Clonal haematopoiesis involves the expansion of certain blood cell lineages and has been associated with ageing and adverse health outcomes1-5. Here we use exome sequence data on 628,388 individuals to identify 40,208 carriers of clonal haematopoiesis of indeterminate potential (CHIP). Using genome-wide and exome-wide association analyses, we identify 24 loci (21 of which are novel) where germline genetic variation influences predisposition to CHIP, including missense variants in the lymphocytic antigen coding gene LY75, which are associated with reduced incidence of CHIP. We also identify novel rare variant associations with clonal haematopoiesis and telomere length. Analysis of 5,041 health traits from the UK Biobank (UKB) found relationships between CHIP and severe COVID-19 outcomes, cardiovascular disease, haematologic traits, malignancy, smoking, obesity, infection and all-cause mortality. Longitudinal and Mendelian randomization analyses revealed that CHIP is associated with solid cancers, including non-melanoma skin cancer and lung cancer, and that CHIP linked to DNMT3A is associated with the subsequent development of myeloid but not lymphoid leukaemias. Additionally, contrary to previous findings from the initial 50,000 UKB exomes6, our results in the full sample do not support a role for IL-6 inhibition in reducing the risk of cardiovascular disease among CHIP carriers. Our findings demonstrate that CHIP represents a complex set of heterogeneous phenotypes with shared and unique germline genetic causes and varied clinical implications.

Rare coding variants in ten genes confer substantial risk for schizophrenia.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P < 2.14 × 10-6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-D-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

DNA Structure-Specific Cleavage of DNA-Protein Crosslinks by the SPRTN Protease.

Repair of covalent DNA-protein crosslinks (DPCs) by DNA-dependent proteases has emerged as an essential genome maintenance mechanism required for cellular viability and tumor suppression. However, how proteolysis is restricted to the crosslinked protein while leaving surrounding chromatin proteins unharmed has remained unknown. Using defined DPC model substrates, we show that the DPC protease SPRTN displays strict DNA structure-specific activity. Strikingly, SPRTN cleaves DPCs at or in direct proximity to disruptions within double-stranded DNA. In contrast, proteins crosslinked to intact double- or single-stranded DNA are not cleaved by SPRTN. NMR spectroscopy data suggest that specificity is not merely affinity-driven but achieved through a flexible bipartite strategy based on two DNA binding interfaces recognizing distinct structural features. This couples DNA context to activation of the enzyme, tightly confining SPRTN's action to biologically relevant scenarios.

Exome sequencing and analysis of 454,787 UK Biobank participants.

A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing1 to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study2. We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P ≤ 2.18 × 10-11. Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension (SLC9A3R2), diabetes (MAP3K15, FAM234A) and asthma (SLC27A3). Six genes were associated with brain imaging phenotypes, including two involved in neural development (GBE1, PLD1). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene-trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale.

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

Reliability and accuracy of single-molecule FRET studies for characterization of structural dynamics and distances in proteins.

Single-molecule Förster-resonance energy transfer (smFRET) experiments allow the study of biomolecular structure and dynamics in vitro and in vivo. We performed an international blind study involving 19 laboratories to assess the uncertainty of FRET experiments for proteins with respect to the measured FRET efficiency histograms, determination of distances, and the detection and quantification of structural dynamics. Using two protein systems with distinct conformational changes and dynamics, we obtained an uncertainty of the FRET efficiency ≤0.06, corresponding to an interdye distance precision of ≤2 Å and accuracy of ≤5 Å. We further discuss the limits for detecting fluctuations in this distance range and how to identify dye perturbations. Our work demonstrates the ability of smFRET experiments to simultaneously measure distances and avoid the averaging of conformational dynamics for realistic protein systems, highlighting its importance in the expanding toolbox of integrative structural biology.

RPA interacts with Rad52 to promote meiotic crossover and noncrossover recombination.

Meiotic recombination is initiated by programmed double-strand breaks (DSBs). Studies in Saccharomyces cerevisiae have shown that, following rapid resection to generate 3' single-stranded DNA (ssDNA) tails, one DSB end engages a homolog partner chromatid and is extended by DNA synthesis, whereas the other end remains associated with its sister. Then, after regulated differentiation into crossover- and noncrossover-fated types, the second DSB end participates in the reaction by strand annealing with the extended first end, along both pathways. This second-end capture is dependent on Rad52, presumably via its known capacity to anneal two ssDNAs. Here, using physical analysis of DNA recombination, we demonstrate that this process is dependent on direct interaction of Rad52 with the ssDNA binding protein, replication protein A (RPA). Furthermore, the absence of this Rad52-RPA joint activity results in a cytologically-prominent RPA spike, which emerges from the homolog axes at sites of crossovers during the pachytene stage of the meiotic prophase. Our findings suggest that this spike represents the DSB end of a broken chromatid caused by either the displaced leading DSB end or the second DSB end, which has been unable to engage with the partner homolog-associated ssDNA. These and other results imply a close correspondence between Rad52-RPA roles in meiotic recombination and mitotic DSB repair.

Germline Mutations in CIDEB and Protection against Liver Disease.

BACKGROUND: Exome sequencing in hundreds of thousands of persons may enable the identification of rare protein-coding genetic variants associated with protection from human diseases like liver cirrhosis, providing a strategy for the discovery of new therapeutic targets. METHODS: We performed a multistage exome sequencing and genetic association analysis to identify genes in which rare protein-coding variants were associated with liver phenotypes. We conducted in vitro experiments to further characterize associations. RESULTS: The multistage analysis involved 542,904 persons with available data on liver aminotransferase levels, 24,944 patients with various types of liver disease, and 490,636 controls without liver disease. We found that rare coding variants in APOB, ABCB4, SLC30A10, and TM6SF2 were associated with increased aminotransferase levels and an increased risk of liver disease. We also found that variants in CIDEB, which encodes a structural protein found in hepatic lipid droplets, had a protective effect. The burden of rare predicted loss-of-function variants plus missense variants in CIDEB (combined carrier frequency, 0.7%) was associated with decreased alanine aminotransferase levels (beta per allele, -1.24 U per liter; 95% confidence interval [CI], -1.66 to -0.83; P = 4.8×10-9) and with 33% lower odds of liver disease of any cause (odds ratio per allele, 0.67; 95% CI, 0.57 to 0.79; P = 9.9×10-7). Rare coding variants in CIDEB were associated with a decreased risk of liver disease across different underlying causes and different degrees of severity, including cirrhosis of any cause (odds ratio per allele, 0.50; 95% CI, 0.36 to 0.70). Among 3599 patients who had undergone bariatric surgery, rare coding variants in CIDEB were associated with a decreased nonalcoholic fatty liver disease activity score (beta per allele in score units, -0.98; 95% CI, -1.54 to -0.41 [scores range from 0 to 8, with higher scores indicating more severe disease]). In human hepatoma cell lines challenged with oleate, CIDEB small interfering RNA knockdown prevented the buildup of large lipid droplets. CONCLUSIONS: Rare germline mutations in CIDEB conferred substantial protection from liver disease. (Funded by Regeneron Pharmaceuticals.).

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls.

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Meta-imputation of transcriptome from genotypes across multiple datasets by leveraging publicly available summary-level data.

Transcriptome wide association studies (TWAS) can be used as a powerful method to identify and interpret the underlying biological mechanisms behind GWAS by mapping gene expression levels with phenotypes. In TWAS, gene expression is often imputed from individual-level genotypes of regulatory variants identified from external resources, such as Genotype-Tissue Expression (GTEx) Project. In this setting, a straightforward approach to impute expression levels of a specific tissue is to use the model trained from the same tissue type. When multiple tissues are available for the same subjects, it has been demonstrated that training imputation models from multiple tissue types improves the accuracy because of shared eQTLs between the tissues and increase in effective sample size. However, existing joint-tissue methods require access of genotype and expression data across all tissues. Moreover, they cannot leverage the abundance of various expression datasets across various tissues for non-overlapping individuals. Here, we explore the optimal way to combine imputed levels across training models from multiple tissues and datasets in a flexible manner using summary-level data. Our proposed method (SWAM) combines arbitrary number of transcriptome imputation models to linearly optimize the imputation accuracy given a target tissue. By integrating models across tissues and/or individuals, SWAM can improve the accuracy of transcriptome imputation or to improve power to TWAS while only requiring individual-level data from a single reference cohort. To evaluate the accuracy of SWAM, we combined 49 tissue-specific gene expression imputation models from the GTEx Project as well as from a large eQTL study of Depression Susceptibility Genes and Networks (DGN) Project and tested imputation accuracy in GEUVADIS lymphoblastoid cell lines samples. We also extend our meta-imputation method to meta-TWAS to leverage multiple tissues in TWAS analysis with summary-level statistics. Our results capitalize on the importance of integrating multiple tissues to unravel regulatory impacts of genetic variants on complex traits.

Long-term outcomes of high bleeding risk patients undergoing percutaneous coronary intervention: a Korean nationwide registry.

BACKGROUND AND AIMS: Patients with high bleeding risk (HBR) undergoing percutaneous coronary intervention (PCI) are at increased risk of not only bleeding, but also ischaemic events. This study aimed to determine the long-term relative risk of ischaemic and bleeding events in HBR patients. METHODS: This study was a nationwide cohort study, based on the Korean National Health Insurance Review and Assessment Service database. Patients diagnosed with stable angina or acute coronary syndrome and those who underwent PCI in Korea between 2009 and 2018 were included in the analysis. According to the Academic Research Consortium HBR criteria, the total population was divided into HBR and non-HBR groups. The co-primary outcomes were major bleeding events and ischaemic (composite of cardiac death, myocardial infarction, and ischaemic stroke) events. RESULTS: Among a total of 325 417 patients who underwent PCI, 66 426 patients (20.4%) had HBR. During the follow-up period, HBR patients had a higher risk for major bleeding events (23.9% vs. 8.9%, P < .001) and ischaemic events (33.8% vs. 14.4%, P < .001). However, the impact of HBR was significant for major bleeding events [hazard ratio (HR) 3.12, 95% confidence interval (CI) 3.04-3.21, P < .001] and for ischaemic events (HR 2.50, 95% CI 2.45-2.56, P < .001). The HBR group was also associated with a greater risk of all-cause mortality (HR 3.73, 95% CI 3.66-3.79, P < .001). The average annual rate of major bleeding events within the first year after PCI was 5.5% for a single major criterion, and 2.9% for a single minor criterion. CONCLUSIONS: Among patients undergoing PCI, those with HBR were at increased long-term risk for both bleeding and ischaemic events, with a greater risk of mortality compared to non-HBR patients.

expHRD: an individualized, transcriptome-based prediction model for homologous recombination deficiency assessment in cancer.

BACKGROUND: Homologous recombination deficiency (HRD) stands as a clinical indicator for discerning responsive outcomes to platinum-based chemotherapy and poly ADP-ribose polymerase (PARP) inhibitors. One of the conventional approaches to HRD prognostication has generally centered on identifying deleterious mutations within the BRCA1/2 genes, along with quantifying the genomic scars, such as Genomic Instability Score (GIS) estimation with scarHRD. However, the scarHRD method has limitations in scenarios involving tumors bereft of corresponding germline data. Although several RNA-seq-based HRD prediction algorithms have been developed, they mainly support cohort-wise classification, thereby yielding HRD status without furnishing an analogous quantitative metric akin to scarHRD. This study introduces the expHRD method, which operates as a novel transcriptome-based framework tailored to n-of-1-style HRD scoring. RESULTS: The prediction model has been established using the elastic net regression method in the Cancer Genome Atlas (TCGA) pan-cancer training set. The bootstrap technique derived the HRD geneset for applying the expHRD calculation. The expHRD demonstrated a notable correlation with scarHRD and superior performance in predicting HRD-high samples. We also performed intra- and extra-cohort evaluations for clinical feasibility in the TCGA-OV and the Genomic Data Commons (GDC) ovarian cancer cohort, respectively. The innovative web service designed for ease of use is poised to extend the realms of HRD prediction across diverse malignancies, with ovarian cancer standing as an emblematic example. CONCLUSIONS: Our novel approach leverages the transcriptome data, enabling the prediction of HRD status with remarkable precision. This innovative method addresses the challenges associated with limited available data, opening new avenues for utilizing transcriptomics to inform clinical decisions.

Comparison of 3- to 6-Month Versus 12-Month Dual Antiplatelet Therapy After Coronary Intervention Using the Contemporary Drug-Eluting Stents With Ultrathin Struts: The HOST-IDEA Randomized Clinical Trial.

BACKGROUND: Limited data are available on short-term dual antiplatelet therapy (DAPT) after percutaneous coronary intervention using third-generation drug-eluting stents with ultrathin struts and advanced polymer technology. We investigated whether 3- to 6-month DAPT was noninferior to 12-month DAPT after implantation of drug-eluting stents with ultrathin struts and advanced polymer technology. METHODS: We performed an open-label, randomized trial at 37 centers in South Korea. We enrolled patients undergoing percutaneous coronary intervention using the Orsiro biodegradable-polymer sirolimus-eluting stents or the Coroflex ISAR polymer-free sirolimus-eluting stents. Patients with ST-segment-elevation myocardial infarction were excluded. Patients were randomly assigned to receive either 3- to 6-month or 12-month DAPT after percutaneous coronary intervention. The choice of antiplatelet medications was at the physician's discretion. The primary outcome was a net adverse clinical event, a composite of cardiac death, target vessel myocardial infarction, clinically driven target lesion revascularization, stent thrombosis, or major bleeding, defined as Bleeding Academic Research Consortium type 3 or 5 at 12 months. The major secondary outcomes were target lesion failure, a composite of cardiac death, target vessel myocardial infarction, clinically driven target lesion revascularization, and major bleeding. RESULTS: A total of 2013 patients (mean age, 65.7±10.5 years; 1487 males [73.9%]; 1110 [55.1%] presented with acute coronary syndrome) were randomly assigned to 3- to 6-month DAPT (n=1002) or 12-month DAPT (n=1011). The primary outcome occurred in 37 (3.7%) patients in the 3- to 6-month DAPT group and 41 (4.1%) in the 12-month DAPT group. The noninferiority of the 3- to 6-month DAPT group to the 12-month DAPT group was met (absolute risk difference, -0.4% [1-sided 95% CI, -∞% to 1.1%]; P<0.001 for noninferiority). There were no significant differences in target lesion failure (hazard ratio, 0.98 [95% CI, 0.56-1.71], P=0.94) or major bleeding (hazard ratio, 0.82 [95% CI, 0.41-1.61], P=0.56) between the 2 groups. Across various subgroups, the treatment effect of 3- to 6-month DAPT was consistent for net adverse clinical event. CONCLUSIONS: Among patients undergoing percutaneous coronary intervention using third-generation drug-eluting stents, 3- to 6-month DAPT was noninferior to 12-month DAPT for net adverse clinical event. Further research is needed to generalize this finding to other populations and to determine the ideal regimen for 3- to 6-month DAPT. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02601157.

Tumour-associated myeloid cells expressing IL-10R2/IL-22R1 as a potential biomarker for diagnosis and recurrence of pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor survival rate, largely due to the lack of early diagnosis. Although myeloid cells are crucial in the tumour microenvironment, whether their specific subset can be a biomarker of PDAC progression is unclear. METHODS: We analysed IL-22 receptor expression in PDAC and peripheral blood. Additionally, we analysed gene expression profiles of IL-10R2+/IL-22R1+ myeloid cells and the presence of these cells using single-cell RNA sequencing and murine orthotropic PDAC models, respectively, followed by examining the immunosuppressive function of IL-10R2+/IL-22R1+ myeloid cells. Finally, the correlation between IL-10R2 expression and PDAC progression was evaluated. RESULTS: IL-10R2+/IL-22R1+ myeloid cells were present in PDAC and peripheral blood. Blood IL-10R2+ myeloid cells displayed a gene expression signature associated with tumour-educated circulating monocytes. IL-10R2+/IL-22R1+ myeloid cells from human myeloid cell culture inhibited T cell proliferation. By mouse models for PDAC, we found a positive correlation between pancreatic tumour growth and increased blood IL-10R2+/IL-22R1+ myeloid cells. IL-10R2+/IL-22R1+ myeloid cells from an early phase of the PDAC model suppressed T cell proliferation and cytotoxicity. IL-10R2+ myeloid cells indicated tumour recurrence 130 days sooner than CA19-9 in post-pancreatectomy patients. CONCLUSIONS: IL-10R2+/IL-22R1+ myeloid cells in the peripheral blood might be an early marker of PDAC prognosis.

Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.