Comprehensive classification of proteins based on structures that engage lipids by COMPOSEL.

Structures can now be predicted for any protein using programs like AlphaFold and Rosetta, which rely on a foundation of experimentally determined structures of architecturally diverse proteins. The accuracy of such artificial intelligence and machine learning (AI/ML) approaches benefits from the specification of restraints which assist in navigating the universe of folds to converge on models most representative of a given protein's physiological structure. This is especially pertinent for membrane proteins, with structures and functions that depend on their presence in lipid bilayers. Structures of proteins in their membrane environments could conceivably be predicted from AI/ML approaches with user-specificized parameters that describe each element of the architecture of a membrane protein accompanied by its lipid environment. We propose the Classification Of Membrane Proteins based On Structures Engaging Lipids (COMPOSEL), which builds on existing nomenclature types for monotopic, bitopic, polytopic and peripheral membrane proteins as well as lipids. Functional and regulatory elements are also defined in the scripts, as shown with membrane fusing synaptotagmins, multidomain PDZD8 and Protrudin proteins that recognize phosphoinositide (PI) lipids, the intrinsically disordered MARCKS protein, caveolins, the ß barrel assembly machine (BAM), an adhesion G-protein coupled receptor (aGPCR) and two lipid modifying enzymes - diacylglycerol kinase DGKε and fatty aldehyde dehydrogenase FALDH. This demonstrates how COMPOSEL communicates lipid interactivity as well as signaling mechanisms and binding of metabolites, drug molecules, polypeptides or nucleic acids to describe the operations of any protein. Moreover COMPOSEL can be scaled to express how genomes encode membrane structures and how our organs are infiltrated by pathogens such as SARS-CoV-2.

Design and analysis of outcomes following SARS-CoV-2 infection in veterans.

BACKGROUND: Understanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs' (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. METHODS: In a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts within each month utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. RESULTS: From an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 39 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). CONCLUSION: This successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.

A multi-institutional study evaluating pediatric burn injuries during the COVID-19 pandemic.

During the COVID-19 pandemic, children were out of school due to Stay-at-Home orders. The objective of this study was to investigate how the COVID-19 pandemic may have impacted the incidence of burn injuries in children. Eight Level I Pediatric Trauma Centers participated in a retrospective study evaluating children <18 years old with traumatic injuries defined by the National Trauma Data Bank. Patients with burn injuries were identified by ICD-10 codes. Historical controls from March-September 2019 ("Control" cohort) were compared to patients injured after the start of the COVID-19 pandemic from March-September 2020 ("COVID" cohort). A total of 12,549 pediatric trauma patients were included, of which 916 patients had burn injuries. Burn injuries increased after the start of the pandemic (COVID 522/6711 [7.8%] vs. Control 394/5838 [6.7%], p=0.03). There were no significant differences in age, race, insurance status, burn severity, injury severity score, intent or location of injury, and occurrence on a weekday or weekend between cohorts. There was an increase in flame burns (COVID 140/522 [26.8%] vs. Control 75/394 [19.0%], p=0.01) and a decrease in contact burns (COVID 118/522 [22.6%] vs. Control 112/394 [28.4%], p=0.05). More patients were transferred from an outside institution (COVID 315/522 patients [60.3%] vs. Control 208/394 patients [52.8%], p=0.02), and intensive care unit length of stay increased (COVID median 3.5 days [interquartile range 2.0-11.0] vs. Control median 3.0 days [interquartile range 1.0-4.0], p=0.05). Pediatric burn injuries increased after the start of the COVID-19 pandemic despite Stay-at-Home orders intended to optimize health and increase public safety.

Pediatric injury trends and relationships with social vulnerability during the COVID-19 pandemic: a multi-institutional analysis.

BACKGROUND: The impact of the COVID-19 pandemic on pediatric injury, particularly relative to a community's vulnerability, is unknown. The objective of this study was to describe the change in pediatric injury during the first 6 months of the COVID-19 pandemic compared to prior years, focusing on intentional injury relative to the Social Vulnerability Index (SVI). METHODS: All patients <18 years meeting inclusion criteria for the National Trauma Data Bank between 1/1/2016 and 9/30/2020 at 9 Level 1 Pediatric Trauma Centers were included. The COVID cohort (children injured in the first 6 months of the pandemic) were compared to an averaged Historical cohort (corresponding dates, 2016-2019). Demographic and injury characteristics, and hospital-based outcomes were compared. Multivariable logistic regression was used to estimate the adjusted odds of intentional injury associated with SVI, moderated by exposure to the pandemic. Interrupted time series analysis with autoregressive integrated moving average modeling was used to predict expected injury patterns. Volume trends and observed vs expected rates of injury were analyzed. RESULTS: 47,385 patients met inclusion criteria, with 8,991 treated in 2020 and 38,394 treated in 2016-2019. The COVID cohort included 7,068 patients and the averaged Historical cohort included 5,891 patients (SD 472), indicating a 20% increase in pediatric injury (p = 0.031). Penetrating injuries increased (722(10.2%) COVID vs 421(8.0%) Historical, p < 0.001), specifically firearm injuries (163(2.3%) COVID vs. 105(1.8%) Historical, p = 0.043). Bicycle collisions (505(26.3%) COVID vs. 261(18.2%) Historical, p < 0.001) and collisions on other land transportation (e.g. all-terrain vehicles) (525(27.3%) COVID vs. 280(19.5%) Historical, p < 0.001) also increased. Overall, SVI was associated with intentional injury (OR 7.9, 95% CI 6.5-9.8), a relationship which increased during the pandemic. CONCLUSIONS: Pediatric injury increased during the pandemic across multiple sites and states. The relationship between increased vulnerability and intentional injury increased during the pandemic. LEVEL OF EVIDENCE: III, Prognostic and Epidemiologic Study.

SARS-CoV-2 Omicron Subvariants Balance Host Cell Membrane, Receptor, and Antibody Docking via an Overlapping Target Site.

Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging rapidly and offer surfaces that are optimized for recognition of host cell membranes while also evading antibodies arising from vaccinations and previous infections. Host cell infection is a multi-step process in which spike heads engage lipid bilayers and one or more angiotensin-converting enzyme 2 (ACE-2) receptors. Here, the membrane binding surfaces of Omicron subvariants are compared using cryo-electron microscopy (cEM) structures of spike trimers from BA.2, BA.2.12.1, BA.2.13, BA.2.75, BA.3, BA.4, and BA.5 viruses. Despite significant differences around mutated sites, they all maintain strong membrane binding propensities that first appeared in BA.1. Both their closed and open states retain elevated membrane docking capacities, although the presence of more closed than open states diminishes opportunities to bind receptors while enhancing membrane engagement. The electrostatic dipoles are generally conserved. However, the BA.2.75 spike dipole is compromised, and its ACE-2 affinity is increased, and BA.3 exhibits the opposite pattern. We propose that balancing the functional imperatives of a stable, readily cleavable spike that engages both lipid bilayers and receptors while avoiding host defenses underlies betacoronavirus evolution. This provides predictive criteria for rationalizing future pandemic waves and COVID-19 transmissibility while illuminating critical sites and strategies for simultaneously combating multiple variants.

Transmembrane Membrane Readers form a Novel Class of Proteins That Include Peripheral Phosphoinositide Recognition Domains and Viral Spikes.

Membrane proteins are broadly classified as transmembrane (TM) or peripheral, with functions that pertain to only a single bilayer at a given time. Here, we explicate a class of proteins that contain both transmembrane and peripheral domains, which we dub transmembrane membrane readers (TMMRs). Their transmembrane and peripheral elements anchor them to one bilayer and reversibly attach them to another section of bilayer, respectively, positioning them to tether and fuse membranes while recognizing signals such as phosphoinositides (PIs) and modifying lipid chemistries in proximity to their transmembrane domains. Here, we analyze full-length models from AlphaFold2 and Rosetta, as well as structures from nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, using the Membrane Optimal Docking Area (MODA) program to map their membrane-binding surfaces. Eukaryotic TMMRs include phospholipid-binding C1, C2, CRAL-TRIO, FYVE, GRAM, GTPase, MATH, PDZ, PH, PX, SMP, StART and WD domains within proteins including protrudin, sorting nexins and synaptotagmins. The spike proteins of SARS-CoV-2 as well as other viruses are also TMMRs, seeing as they are anchored into the viral membrane while mediating fusion with host cell membranes. As such, TMMRs have key roles in cell biology and membrane trafficking, and include drug targets for diseases such as COVID-19.

Pediatric Injury Transfer Patterns During the COVID-19 Pandemic: An Interrupted time Series Analysis.

INTRODUCTION: With the expected surge of adult patients with COVID-19, the Children's Hospital Association recommended a tiered approach to divert children to pediatric centers. Our objective was understanding changes in interfacility transfer to Pediatric Trauma Centers (PTCs) during the first 6 mo of the pandemic. METHODS: Children aged < 18 y injured between January 1, 2016 and September 30, 2020, who met National Trauma Databank inclusion criteria from 9 PTCs were included. An interrupted time-series analysis was used to estimate an expected number of transferred patients compared to observed volume. The "COVID" cohort was compared to a historical cohort (historical average [HA]), using an average across 2016-2019. Site-based differences in transfer volume, demographics, injury characteristics, and hospital-based outcomes were compared between cohorts. RESULTS: Twenty seven thousand thirty one/47,382 injured patients (57.05%) were transferred to a participating PTC during the study period. Of the COVID cohort, 65.4% (4620/7067) were transferred, compared to 55.7% (3281/5888) of the HA (P < 0.001). There was a decrease in 15-y-old to 17-y-old patients (10.43% COVID versus 12.64% HA, P = 0.003). More patients in the COVID cohort had injury severity scores ≤ 15 (93.25% COVID versus 87.63% HA, P < 0.001). More patients were discharged home after transfer (31.80% COVID versus 21.83% HA, P < 0.001). CONCLUSIONS: Transferred trauma patients to Level I PTC increased during the COVID-19 pandemic. The proportion of transferred patients discharged from emergency departments increased. Pediatric trauma transfers may be a surrogate for referring emergency department capacity and resources and a measure of pediatric trauma triage capability.

Design and Analysis of Outcomes following SARS-CoV-2 Infection in Veterans (preprint)

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSUnderstanding how SARS-CoV-2 infection impacts long-term patient outcomes requires identification of comparable persons with and without infection. We report the design and implementation of a matching strategy employed by the Department of Veterans Affairs (VA) COVID-19 Observational Research Collaboratory (CORC) to develop comparable cohorts of SARS-CoV-2 infected and uninfected persons for the purpose of inferring potential causative long-term adverse effects of SARS-CoV-2 infection in the Veteran population. MethodsIn a retrospective cohort study, we identified VA health care system patients who were and were not infected with SARS-CoV-2 on a rolling monthly basis. We generated matched cohorts utilizing a combination of exact and time-varying propensity score matching based on electronic health record (EHR)-derived covariates that can be confounders or risk factors across a range of outcomes. ResultsFrom an initial pool of 126,689,864 person-months of observation, we generated final matched cohorts of 208,536 Veterans infected between March 2020-April 2021 and 3,014,091 uninfected Veterans. Matched cohorts were well-balanced on all 38 covariates used in matching after excluding patients for: no VA health care utilization; implausible age, weight, or height; living outside of the 50 states or Washington, D.C.; prior SARS-CoV-2 diagnosis per Medicare claims; or lack of a suitable match. Most Veterans in the matched cohort were male (88.3%), non-Hispanic (87.1%), white (67.2%), and living in urban areas (71.5%), with a mean age of 60.6, BMI of 31.3, Gagne comorbidity score of 1.4 and a mean of 2.3 CDC high-risk conditions. The most common diagnoses were hypertension (61.4%), diabetes (34.3%), major depression (32.2%), coronary heart disease (28.5%), PTSD (25.5%), anxiety (22.5%), and chronic kidney disease (22.5%). ConclusionsThis successful creation of matched SARS-CoV-2 infected and uninfected patient cohorts from the largest integrated health system in the United States will support cohort studies of outcomes derived from EHRs and sample selection for qualitative interviews and patient surveys. These studies will increase our understanding of the long-term outcomes of Veterans who were infected with SARS-CoV-2.

Progressive membrane-binding mechanism of SARS-CoV-2 variant spike proteins.

Membrane recognition by viral spike proteins is critical for infection. Here we show the host cell membrane-binding surfaces of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike variants Alpha, Beta, Gamma, Delta, Epsilon, Kappa, and Omicron as well as SARS-CoV-1 and pangolin and bat relatives. They show increases in membrane binding propensities over time, with all spike head mutations in variants, and particularly BA.1, impacting the protein's affinity to cell membranes. Comparison of hundreds of structures yields a progressive model of membrane docking in which spike protein trimers shift from initial perpendicular stances to increasingly tilted positions that draw viral particles alongside host cell membranes before optionally engaging angiotensin-converting enzyme 2 (ACE2) receptors. This culminates in the assembly of the symmetric fusion apparatus, with enhanced membrane interactions of variants explaining their unique cell fusion capacities and COVID-19 disease transmission rates.

Temporal variation in individual social risk factors associated with testing positive for SARS-CoV-2 among veterans in the veterans health administration.

PURPOSE: Marginalized communities have been disproportionally impacted by SARS-CoV-2. How the associations between social determinants of health and the risk of SARS-CoV-2 infection shifted across time is unknown. In this evaluation, we examine individual-level social determinants of health as social risk factors for SARS-CoV-2 infection across the first 12 months of the pandemic among US Veterans. METHODS: We conducted a retrospective cohort analysis of 946,358 Veterans who sought testing or treatment for SARS-CoV-2 infection in U.S. Department of Veterans Affairs medical facilities. We estimated risk ratios for testing positive by social risk factors, adjusting for demographics, comorbidities, and time. Adjusted models were stratified by pandemic phase to assess temporal fluctuations in social risks. RESULTS: Approximately 19% of Veterans tested positive for SARS-CoV-2. Larger household size was a persistent risk factor and this association increased over time. Early in the pandemic, lower county-level population density was associated with lower SARS-CoV-2 infection risk, but between June 1 and August 31, 2020, this trend reversed. CONCLUSIONS: Temporal fluctuations in social risks associated with Veterans' SARS-CoV-2 infection suggest the need for ongoing, real-time tracking as the social and medical environment continues to evolve.

Multifaceted membrane binding head of the SARS-CoV-2 spike protein.

The SARS-CoV-2 spike protein presents a surface with enormous membrane binding potential to host tissues and organelles of infected cells. Its exposed trimeric head binds not only the angiotensin-converting enzyme 2 (ACE2), but also host phospholipids which are missing from all existing structures. Hence, the membrane interaction surfaces that mediate viral fusion, entry, assembly and egress remain unclear. Here the spike:membrane docking sites are identified based on membrane optimal docking area (MODA) analysis of 3D structures of spike proteins in closed and open conformations at endocytic and neutral pH levels as well as ligand complexes. This reveals multiple membrane binding sites in the closed spike head that together prefer convex membranes and are modulated by pH, fatty acids and post-translational modifications including glycosylation. The exposure of the various membrane interaction sites adjusts upon domain repositioning within the trimer, allowing formation of intermediate bilayer complexes that lead to the prefusion state while also enabling ACE2 receptor recognition. In contrast, all antibodies that target the spike head would block the membrane docking process that precedes ACE2 recognition. Together this illuminates the engagements of the spike protein with plasma, endocytic, ER or exocytic vesicle membranes that help to drive the cycle of viral infection, and offers novel sites for intervention.

The COVID-19 pandemic and associated rise in pediatric firearm injuries: A multi-institutional study.

BACKGROUND: Firearm sales in the United States (U.S.) markedly increased during the COVID-19 pandemic. Our objective was to determine if firearm injuries in children were associated with stay-at-home orders (SHO) during the COVID-19 pandemic. We hypothesized there would be an increase in pediatric firearm injuries during SHO. METHODS: This was a multi institutional, retrospective study of institutional trauma registries. Patients <18 years with traumatic injuries meeting National Trauma Data Bank (NTDB) criteria were included. A "COVID" cohort, defined as time from initiation of state SHO through September 30, 2020 was compared to "Historical" controls from an averaged period of corresponding dates in 2016-2019. An interrupted time series analysis (ITSA) was utilized to evaluate the association of the U.S. declaration of a national state of emergency with pediatric firearm injuries. RESULTS: Nine Level I pediatric trauma centers were included, contributing 48,111 pediatric trauma patients, of which 1,090 patients (2.3%) suffered firearm injuries. There was a significant increase in the proportion of firearm injuries in the COVID cohort (COVID 3.04% vs. Historical 1.83%; p < 0.001). There was an increased cumulative burden of firearm injuries in 2020 compared to a historical average. ITSA showed an 87% increase in the observed rate of firearm injuries above expected after the declaration of a nationwide emergency (p < 0.001). CONCLUSION: The proportion of firearm injuries affecting children increased during the COVID-19 pandemic. The pandemic was associated with an increase in pediatric firearm injuries above expected rates based on historical patterns.

Spatial Clustering of County-Level COVID-19 Rates in the U.S.

Despite the widespread prevalence of cases associated with the coronavirus disease 2019 (COVID-19) pandemic, little is known about the spatial clustering of COVID-19 in the United States. Data on COVID-19 cases were used to identify U.S. counties that have both high and low COVID-19 incident proportions and clusters. Our results suggest that there are a variety of sociodemographic variables that are associated with the severity of COVID-19 county-level incident proportions. As the pandemic evolved, communities of color were disproportionately impacted. Subsequently, it shifted from communities of color and metropolitan areas to rural areas in the U.S. Our final period showed limited differences in county characteristics, suggesting that COVID-19 infections were more widespread. The findings might address the systemic barriers and health disparities that may result in high incident proportions of COVID-19 clusters.