A lateral electrophoretic flow diagnostic assay

Immunochromatographic assays are a cornerstone tool in disease screening. To complement existing lateral flow assays (based on wicking flow) we introduce a lateral flow format that employs directed electrophoretic transport. The format is termed a “lateral e-flow assay” and is designed to support multiplexed detection using immobilized reaction volumes of capture antigen. To fabricate the lateral e-flow device, we employ mask-based UV photopatterning to selectively immobilize unmodified capture antigen along the microchannel in a barcode-like pattern. The channel-filling polyacrylamide hydrogel incorporates a photoactive moiety (benzophenone) to immobilize capture antigen to the hydrogel without a priori antigen modification. We report a heterogeneous sandwich assay using low-power electrophoresis to drive biospecimen through the capture antigen barcode. Fluorescence barcode readout is collected via a low-resource appropriate imaging system (CellScope). We characterize lateral e-flow assay performance and demonstrate a serum assay for antibodies to the hepatitis C virus (HCV). In a pilot study, the lateral e-flow assay positively identifies HCV+ human sera in 60 min. The lateral e-flow assay provides a flexible format for conducting multiplexed immunoassays relevant to confirmatory diagnosis in near-patient settings

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Characterization and Synthesis of Photoactive Hydrogels for Multiparameter Proteoform Measurements from Single Cells

Heterogeneity is a fundamental property of biological systems. The central dogma of biology posits that a gene encoded in DNA is transcribed into messenger RNA and translated to protein. Yet, a single gene does not necessarily map to a single protein. Protein isoforms (i.e., protein variants) produced during transcription or translation are subject to post-translational modifications, yielding a molecularly diverse collection of proteoforms. The molecular heterogeneity of proteoforms gives rise to the variable behavior of individual cells, and propagates across length scales to produce the readily observable traits that make each organism unique. Conversely, in the context of therapeutic interventions, elucidating why a treatment may elicit different responses in different individuals requires a fundamental understanding of biological heterogeneity at the cellular and molecular scales. Yet, the inverse relationship between specificity and analytical sensitivity makes discriminating between closely related proteoforms with single cell resolution a formidable challenge. To address the specificity challenge, our group pioneered electrophoretic separation assays from single cells, combining an immunoreactivity measurement with a simultaneous measurement of a second property (e.g., molecular mass, charge, cellular compartment). Such multiparameter measurements facilitate quantitation of non-specific antigen-antibody binding, and thus eliminate the need for proteoform-specific antibodies. Notably, proteoform detection in scEP assays occurs within a porous hydrogel matrix, and thus is subject to reaction-transport constraints. In this work, we apply fundamental principles of mass transport and reaction kinetics to in-gel enzyme-catalyzed and in-gel click chemistry reactions to expand the suite of measurable proteoform properties on the scEP platform. First, given the prevalence of enzymes, an important class of protein chemical catalysts, as drug targets, we were interested in measuring enzymatic activity from single cells. Analogous to the non-specific antigen-antibody binding events that confound immunoassay signal, multiple distinct enzymes may act on the same substrate. As a result, we hypothesized that the upstream separation step in scEP assays can confer additional specificity to enzymatic activity measurements from single cells. To assess feasibility of measuring enzymatic activity from single cells, we studied the effect of immobilizing enzymes in UV-reactive hydrogel matrices on the intrinsic catalytic activity of the enzyme. Next, we aimed to address the perennial tradeoff between specificity and analytical sensitivity in single cell proteoform measurements. The electrophoretic separation step in scEP assays spatially fractionates proteoforms according to a physical property (i.e., mass, charge). In the absence of proteoform-specific antibodies, the total signal is divided into discrete fractions. As a result, a simultaneous increase in analytical sensitivity is required to detect smaller protein quantities. To increase analytical sensitivity of the scEP platform, we evaluate an enzymatic signal amplification strategy for in-gel immunoassays.Lastly, to expand the measurement modalities compatible with scEP assays, we established a modular approach to fabricate chemically multifunctional hydrogels. UV-activated protein immobilization in hydrogels, which mitigates loss of proteins extracted from single cells, is central to the success of scEP assays. However, the current benzophenone-based immobilization approach is irreversible, limiting proteoform detection to single separation modalities (i.e., mass or charge) and in-gel detection with affinity probes. To support capabilities such as multi-dimensional separations and possible integration with off-gel proteoform detection, we developed a sequential click chemistry approach to confer reversible protein immobilization in hydrogels, among other chemical functions

Kinetic Analysis of Enzymes Immobilized in Porous Film Arrays

Measuring the catalytic activity of immobilized enzymes underpins development of biosensing, bioprocessing, and analytical chemistry tools. To expand the range of approaches available for measuring enzymatic activity, we report on a technique to probe activity of enzymes immobilized in porous materials in the absence of confounding mass transport artifacts. We measured reaction kinetics of calf intestinal alkaline phosphatase (CIAP) immobilized in benzophenone-modified polyacrylamide (BPMA-PAAm) gel films housed in an array of fluidically isolated chambers. To ensure kinetics measurements are not confounded by mass transport limitations, we employed Weisz’s modulus (Φ), which compares observed enzyme-catalyzed reaction rates to characteristic substrate diffusion times. We characterized activity of CIAP immobilized in BPMA-PAAm gels in a reaction-limited regime (Φ ≪ 0.15 for all measurements), allowing us to isolate the effect of immobilization on enzymatic activity. Immobilization of CIAP in BPMA-PAAm gels produced a ∼2× loss in apparent enzyme–substrate affinity (<i>K</i>_m) and ∼200× decrease in intrinsic catalytic activity (<i>k</i>_cat) relative to in-solution measurements. As estimating <i>K</i>_m and <i>k</i>_cat requires multiple steps of data manipulation, we developed a computational approach (bootstrapping) to propagate uncertainty in calibration data through all data manipulation steps. Numerical simulation revealed that calibration error is only negligible when the normalized root-mean-squared error (NRMSE) in the calibration falls below 0.05%. Importantly, bootstrapping is independent of the mathematical model, and thus generalizable beyond enzyme kinetics studies. Furthermore, the measurement tool presented can be readily adapted to study other porous immobilization supports, facilitating rational design (immobilization method, geometry, enzyme loading) of immobilized-enzyme devices

A lateral electrophoretic flow diagnostic assay.

Immunochromatographic assays are a cornerstone tool in disease screening. To complement existing lateral flow assays (based on wicking flow) we introduce a lateral flow format that employs directed electrophoretic transport. The format is termed a "lateral e-flow assay" and is designed to support multiplexed detection using immobilized reaction volumes of capture antigen. To fabricate the lateral e-flow device, we employ mask-based UV photopatterning to selectively immobilize unmodified capture antigen along the microchannel in a barcode-like pattern. The channel-filling polyacrylamide hydrogel incorporates a photoactive moiety (benzophenone) to immobilize capture antigen to the hydrogel without a priori antigen modification. We report a heterogeneous sandwich assay using low-power electrophoresis to drive biospecimen through the capture antigen barcode. Fluorescence barcode readout is collected via a low-resource appropriate imaging system (CellScope). We characterize lateral e-flow assay performance and demonstrate a serum assay for antibodies to the hepatitis C virus (HCV). In a pilot study, the lateral e-flow assay positively identifies HCV+ human sera in 60 min. The lateral e-flow assay provides a flexible format for conducting multiplexed immunoassays relevant to confirmatory diagnosis in near-patient settings

A lateral electrophoretic flow diagnostic assay.

Immunochromatographic assays are a cornerstone tool in disease screening. To complement existing lateral flow assays (based on wicking flow) we introduce a lateral flow format that employs directed electrophoretic transport. The format is termed a "lateral e-flow assay" and is designed to support multiplexed detection using immobilized reaction volumes of capture antigen. To fabricate the lateral e-flow device, we employ mask-based UV photopatterning to selectively immobilize unmodified capture antigen along the microchannel in a barcode-like pattern. The channel-filling polyacrylamide hydrogel incorporates a photoactive moiety (benzophenone) to immobilize capture antigen to the hydrogel without a priori antigen modification. We report a heterogeneous sandwich assay using low-power electrophoresis to drive biospecimen through the capture antigen barcode. Fluorescence barcode readout is collected via a low-resource appropriate imaging system (CellScope). We characterize lateral e-flow assay performance and demonstrate a serum assay for antibodies to the hepatitis C virus (HCV). In a pilot study, the lateral e-flow assay positively identifies HCV+ human sera in 60 min. The lateral e-flow assay provides a flexible format for conducting multiplexed immunoassays relevant to confirmatory diagnosis in near-patient settings

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)