A call from patient-researchers to advance research on long COVID.

Long COVID is a chronic and often disabling illness with long-term consequences. Although progress has been made in the clinical characterization of long COVID, no approved treatments exist and disconnects between patients and researchers threaten to hinder future progress. Incorporating patients as active collaborators in long COVID research can bridge the gap and accelerate progress toward treatments and cures.

Transcriptional Isoforms of NAD+ kinase regulate oxidative stress resistance and melanoma metastasis.

Metastasizing cancer cells encounter a multitude of stresses throughout the metastatic cascade. Oxidative stress is known to be a major barrier for metastatic colonization, such that metastasizing cancer cells must rewire their metabolic pathways to increase their antioxidant capacity. NADPH is essential for regeneration of cellular antioxidants and several NADPH-regenerating pathways have been shown to play a role in metastasis. We have found that metastatic melanoma cells have increased levels of both NADPH and NADP+ suggesting increased de novo biosynthesis of NADP+. De novo biosynthesis of NADP+ occurs through a single enzymatic reaction catalyzed by NAD+ kinase (NADK). Here we show that different NADK isoforms are differentially expressed in metastatic melanoma cells, with Isoform 3 being specifically upregulated in metastasis. We find that Isoform 3 is more potent in expanding the NADP(H) pools, increasing oxidative stress resistance and promoting metastatic colonization compared to Isoform 1. We have found that Isoform 3 is transcriptionally upregulated by oxidative stress through the action of NRF2. Together, our work presents a previously uncharacterized role of NADK isoforms in oxidative stress resistance and metastasis and suggests that NADK Isoform 3 is a potential therapeutic target in metastatic disease.

Long COVID science, research and policy.

Long COVID represents the constellation of post-acute and long-term health effects caused by SARS-CoV-2 infection; it is a complex, multisystem disorder that can affect nearly every organ system and can be severely disabling. The cumulative global incidence of long COVID is around 400 million individuals, which is estimated to have an annual economic impact of approximately $1 trillion-equivalent to about 1% of the global economy. Several mechanistic pathways are implicated in long COVID, including viral persistence, immune dysregulation, mitochondrial dysfunction, complement dysregulation, endothelial inflammation and microbiome dysbiosis. Long COVID can have devastating impacts on individual lives and, due to its complexity and prevalence, it also has major ramifications for health systems and economies, even threatening progress toward achieving the Sustainable Development Goals. Addressing the challenge of long COVID requires an ambitious and coordinated-but so far absent-global research and policy response strategy. In this interdisciplinary review, we provide a synthesis of the state of scientific evidence on long COVID, assess the impacts of long COVID on human health, health systems, the economy and global health metrics, and provide a forward-looking research and policy roadmap.

Designing and optimizing clinical trials for long COVID.

Long COVID is a debilitating, multisystemic illness following a SARS-CoV-2 infection whose duration may be indefinite. Over four years into the pandemic, little knowledge has been generated from clinical trials. We analyzed the information available on ClinicalTrials.gov, and found that the rigor and focus of trials vary widely, and that the majority test non-pharmacological interventions with insufficient evidence. We highlight promising trials underway, and encourage the proliferation of clinical trials for treating Long COVID and other infection-associated chronic conditions and illnesses (IACCIs). We recommend several guidelines for Long COVID trials: First, pharmaceutical trials with potentially curative, primary interventions should be prioritized, and both drug repurposing and new drug development should be pursued. Second, study designs should be both rigorous and accessible, e.g., triple-blinded randomized trials that can be conducted remotely, without participants needing to leave their homes. Third, studies should have multiple illness comparator cohorts for IACCIs such as myalgic encephalomyelitis (ME/CFS) and dysautonomia, and screen for the full spectrum of symptomatology and pathologies of these illnesses. Fourth, studies should consider inclusion/exclusion criteria with an eye towards equity and breadth of representation, including participants of all races, ethnicities, and genders most impacted by COVID-19, and including all levels of illness severity. Fifth, involving patient-researchers in all aspects of studies brings immensely valuable perspectives that will increase the impact of trials. We also encourage the development of efficient clinical trial designs including methods to study several therapies in parallel.

Decoding the role of tRNA modifications in cancer progression.

Epitranscriptomic modification of tRNA has recently gained traction in the field of cancer biology. The presence of such modifications on tRNA appears to allow for translational control of processes central to progression and malignant transformation. Methyltransferase Like 1 protein (METTL1), along with other epitranscriptomic writers (e.g. NSUN3, NAT10, ELP3, etc.), has recently been investigated in multiple cancer types. Here, we review the impact of such tRNA modifications in tumorigenesis and the progression of cancer toward drug resistance and metastasis. Regulation of central cellular processes relied upon by malignant cancer cells through modulation of the tRNA epitranscriptome represents an area with great potential to bring novel first-in-class therapies to the clinic.

Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs.

Post-Acute Sequelae of SARS-CoV-2 infection (PASC), also known as Long-COVID, encompasses a variety of complex and varied outcomes following COVID-19 infection that are still poorly understood. We clustered over 600 million condition diagnoses from 14 million patients available through the National COVID Cohort Collaborative (N3C), generating hundreds of highly detailed clinical phenotypes. Assessing patient clinical trajectories using these clusters allowed us to identify individual conditions and phenotypes strongly increased after acute infection. We found many conditions increased in COVID-19 patients compared to controls, and using a novel method to associate patients with clusters over time, we additionally found phenotypes specific to patient sex, age, wave of infection, and PASC diagnosis status. While many of these results reflect known PASC symptoms, the resolution provided by this unprecedented data scale suggests avenues for improved diagnostics and mechanistic understanding of this multifaceted disease.

Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID.

BACKGROUND: Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. METHODS: We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative. We calculate summary statistics, effect sizes, and Kaplan-Meier curves to better understand COVID-19 reinfections. RESULTS: Here we validate previous findings of reinfection incidence (6.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present findings that the proportion of Long COVID diagnoses is higher following initial infection than reinfection for infections in the same epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between initial infection and reinfection (chi-squared value: 25,697, p-value: <0.0001) with a medium effect size (Cramer's V: 0.20, DoF = 3). Individuals who experienced severe initial and first reinfection were older in age and at a higher mortality risk than those who had mild initial infection and reinfection. CONCLUSIONS: In a large patient cohort, we find that the severity of reinfection appears to be associated with the severity of initial infection and that Long COVID diagnoses appear to occur more often following initial infection than reinfection in the same epoch. Future research may build on these findings to better understand COVID-19 reinfections.

More than three years after the start of the COVID-19 pandemic, individuals are frequently reporting multiple COVID-19 infections. However, these reinfections remain poorly understood. Here, we investigate COVID-19 reinfections in a large electronic health record cohort of over 3 million patients. We use data summary techniques and statistical tests to characterize reinfections and their relationships with disease severity, biomarkers, and Long COVID. We find that individuals with severe initial infection are more likely to experience severe reinfection, that some protein levels are lower, leading to reinfection, and that a lower proportion of individuals are diagnosed with Long COVID following reinfection than initial infection. Our work highlights the prevalence and impact of reinfections and suggests the need for further research.

Variation in nutritional quality in UK retail eggs.

Fatty acid (FA), carotenoid and vitamin contents of UK eggs were assessed for four production systems (caged (CA), free-range (FR), organic (OR) and extensive organic (EO)) as well as season. The impact of enforced housing, due to avian influenza, was also investigated. Production system did not alter vitamin D3, B2 or B9 content, but significantly influenced nutritionally desirable FA, carotenoid and vitamins A and E - concentrations decreased as production intensity increased, although for most, CA and FR did not differ significantly. Vitamin E and FA profiles for OR and EO were also similar, although carotenoids were higher in EO eggs. In contrast, FA, carotenoids, vitamins E and B9 were consistent throughout the year, unlike vitamins A, D3 and B2, which fluctuated with season; D and B2 were higher in July than January and lower vitamin A was the only detected implication from enforced housing of FR and OR birds.

Mechanical compression regulates tumor spheroid invasion into a 3D collagen matrix.

Uncontrolled growth of tumor cells in confined spaces leads to the accumulation of compressive stress within the tumor. Although the effects of tension within 3D extracellular matrices (ECMs) on tumor growth and invasion are well established, the role of compression in tumor mechanics and invasion is largely unexplored. In this study, we modified a Transwell assay such that it provides constant compressive loads to spheroids embedded within a collagen matrix. We used microscopic imaging to follow the single cell dynamics of the cells within the spheroids, as well as invasion into the 3D ECMs. Our experimental results showed that malignant breast tumor (MDA-MB-231) and non-tumorigenic epithelial (MCF10A) spheroids responded differently to a constant compression. Cells within the malignant spheroids became more motile within the spheroids and invaded more into the ECM under compression; whereas cells within non-tumorigenic MCF10A spheroids became less motile within the spheroids and did not display apparent detachment from the spheroids under compression. These findings suggest that compression may play differential roles in healthy and pathogenic epithelial tissues and highlight the importance of tumor mechanics and invasion.

Spatial Mapping of Hematopoietic Clones in Human Bone Marrow.

Clonal hematopoiesis (CH) is the expansion of somatically mutated cells in the hematopoietic compartment of individuals without hematopoietic dysfunction. Large CH clones (i.e., >2% variant allele fraction) predispose to hematologic malignancy, but CH is detected at lower levels in nearly all middle-aged individuals. Prior work has extensively characterized CH in peripheral blood, but the spatial distribution of hematopoietic clones in human bone marrow is largely undescribed. To understand CH at this level, we developed a method for spatially aware somatic mutation profiling and characterized the bone marrow of a patient with polycythemia vera. We identified the complex clonal distribution of somatic mutations in the hematopoietic compartment, the restriction of somatic mutations to specific subpopulations of hematopoietic cells, and spatial constraints of these clones in the bone marrow. This proof of principle paves the way to answering fundamental questions regarding CH spatial organization and factors driving CH expansion and malignant transformation in the bone marrow. SIGNIFICANCE: CH occurs commonly in humans and can predispose to hematologic malignancy. Although well characterized in blood, it is poorly understood how clones are spatially distributed in the bone marrow. To answer this, we developed methods for spatially aware somatic mutation profiling to describe clonal heterogeneity in human bone marrow. See related commentary by Austin and Aifantis, p. 139.

Impact of COVID-19 vaccination on symptoms and immune phenotypes in vaccine-naïve individuals with Long COVID.

Background: Long COVID contributes to the global burden of disease. Proposed root cause hypotheses include the persistence of SARS-CoV-2 viral reservoir, autoimmunity, and reactivation of latent herpesviruses. Patients have reported various changes in Long COVID symptoms after COVID-19 vaccinations, leaving uncertainty about whether vaccine-induced immune responses may alleviate or worsen disease pathology. Methods: In this prospective study, we evaluated changes in symptoms and immune responses after COVID-19 vaccination in 16 vaccine-naïve individuals with Long COVID. Surveys were administered before vaccination and then at 2, 6, and 12 weeks after receiving the first vaccine dose of the primary series. Simultaneously, SARS-CoV-2-reactive TCR enrichment, SARS-CoV-2-specific antibody responses, antibody responses to other viral and self-antigens, and circulating cytokines were quantified before vaccination and at 6 and 12 weeks after vaccination. Results: Self-report at 12 weeks post-vaccination indicated 10 out of 16 participants had improved health, 3 had no change, 1 had worse health, and 2 reported marginal changes. Significant elevation in SARS-CoV-2-specific TCRs and Spike protein-specific IgG were observed 6 and 12 weeks after vaccination. No changes in reactivities were observed against herpes viruses and self-antigens. Within this dataset, higher baseline sIL-6R was associated with symptom improvement, and the two top features associated with non-improvement were high IFN-ß and CNTF, among soluble analytes. Conclusions: Our study showed that in this small sample, vaccination improved the health or resulted in no change to the health of most participants, though few experienced worsening. Vaccination was associated with increased SARS-CoV-2 Spike protein-specific IgG and T cell expansion in most individuals with Long COVID. Symptom improvement was observed in those with baseline elevated sIL-6R, while elevated interferon and neuropeptide levels were associated with a lack of improvement.

CD44 and ß1-integrin are both engaged in cell traction force generation in hyaluronic acid-rich extracellular matrices.

Mechanical properties of the extracellular matrices (ECMs) critically regulate a number of important cell function including growth, differentiation and migration. Type I collagen and glycosaminoglycans (GAGs) are two primary components of ECMs that contribute to tissue mechanics with the collagen fiber network sustaining tension and GAGs withstanding compression. Collagen stiffness as well as its architecture are known to be important role players in cell-ECM mechanical interactions, however, much less is known about how GAGs within ECMs regulate cell force generation and invasion. Inspired by a recent theoretical work from the Shenoy lab that GAGs play important roles in cell - ECM interactions, we hereby present experimental studies on the role of hyaluronic acid (HA, an unsulfated GAG) in single tumor cell traction force generation within HA collagen cogels using a recently developed 3D cell traction force microscopy. Our work revealed that CD44, a cell surface adhesion receptor to HA, was engaged in cell traction force generation in conjunction with ß1-integrin. Furthermore, we found that HA significantly modified the architecture and mechanics of the collagen fiber network, decreased tumor cells' propensity to remodel the collagen network, decreased traction force generation and transmission distance, and attenuated tumor invasion in agreement with theoretical predictions. Our findings highlighted the significance of CD44 and HA engagement in cell-ECM mechanical interactions, providing new insights on the mechanical model of cellular force transmission.

Droplet Digital PCR for Oncogenic KMT2A Fusion Detection.

Acute myeloid leukemia (AML) is an aggressive blood cancer diagnosed in approximately 120,000 individuals worldwide each year. During treatment for AML, detecting residual disease is essential for prognostication and treatment decision-making. Currently, methods for detecting residual AML are limited to identifying approximately 1:100 to 1:1000 leukemic cells (morphology and DNA sequencing) or are difficult to implement (flow cytometry). AML arising after chemotherapy or radiation exposure is termed therapy-related AML (t-AML) and is exceptionally aggressive and treatment resistant. t-AML is often driven by oncogenic fusions that result from prior treatments that introduce double-strand DNA breaks. The most common t-AML-associated translocations affect KMT2A. There are at least 80 known KMT2A fusion partners, but approximately 80% of fusions involve only five partners-AF9, AF6, AF4, ELL, and ENL. We present a novel droplet digital PCR assay targeting the most common KMT2A-rearrangements to enable detection of rare AML cells harboring these fusions. This assay was benchmarked in cell lines and patient samples harboring oncogenic KMT2A fusions and demonstrated a limit of detection of approximately 1:1,000,000 cells. Future application of this assay could improve disease detection and treatment decision-making for patients with t-AML with KMT2A fusions and premalignant oncogenic fusion detection in at-risk individuals after chemotherapy exposure.

Mechanical compression regulates tumor spheroid invasion into a 3D collagen matrix.

Uncontrolled growth of tumor cells in confined spaces leads to the accumulation of compressive stress within the tumor. Although the effects of tension within 3D extracellular matrices on tumor growth and invasion are well established, the role of compression in tumor mechanics and invasion is largely unexplored. In this study, we modified a Transwell assay such that it provides constant compressive loads to spheroids embedded within a collagen matrix. We used microscopic imaging to follow the single cell dynamics of the cells within the spheroids, as well as invasion into the 3D extracellular matrices (EMCs). Our experimental results showed that malignant breast tumor (MDA-MB-231) and non-tumorigenic epithelial (MCF10A) spheroids responded differently to a constant compression. Cells within the malignant spheroids became more motile within the spheroids and invaded more into the ECM under compression; whereas cells within non-tumorigenic MCF10A spheroids became less motile within the spheroids and did not display apparent detachment from the spheroids under compression. These findings suggest that compression may play differential roles in healthy and pathogenic epithelial tissues and highlights the importance of tumor mechanics and invasion.

Coding long COVID: characterizing a new disease through an ICD-10 lens.

BACKGROUND: Naming a newly discovered disease is a difficult process; in the context of the COVID-19 pandemic and the existence of post-acute sequelae of SARS-CoV-2 infection (PASC), which includes long COVID, it has proven especially challenging. Disease definitions and assignment of a diagnosis code are often asynchronous and iterative. The clinical definition and our understanding of the underlying mechanisms of long COVID are still in flux, and the deployment of an ICD-10-CM code for long COVID in the USA took nearly 2 years after patients had begun to describe their condition. Here, we leverage the largest publicly available HIPAA-limited dataset about patients with COVID-19 in the US to examine the heterogeneity of adoption and use of U09.9, the ICD-10-CM code for "Post COVID-19 condition, unspecified." METHODS: We undertook a number of analyses to characterize the N3C population with a U09.9 diagnosis code (n = 33,782), including assessing person-level demographics and a number of area-level social determinants of health; diagnoses commonly co-occurring with U09.9, clustered using the Louvain algorithm; and quantifying medications and procedures recorded within 60 days of U09.9 diagnosis. We stratified all analyses by age group in order to discern differing patterns of care across the lifespan. RESULTS: We established the diagnoses most commonly co-occurring with U09.9 and algorithmically clustered them into four major categories: cardiopulmonary, neurological, gastrointestinal, and comorbid conditions. Importantly, we discovered that the population of patients diagnosed with U09.9 is demographically skewed toward female, White, non-Hispanic individuals, as well as individuals living in areas with low poverty and low unemployment. Our results also include a characterization of common procedures and medications associated with U09.9-coded patients. CONCLUSIONS: This work offers insight into potential subtypes and current practice patterns around long COVID and speaks to the existence of disparities in the diagnosis of patients with long COVID. This latter finding in particular requires further research and urgent remediation.

Long COVID: major findings, mechanisms and recommendations.

Long COVID is an often debilitating illness that occurs in at least 10% of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. More than 200 symptoms have been identified with impacts on multiple organ systems. At least 65 million individuals worldwide are estimated to have long COVID, with cases increasing daily. Biomedical research has made substantial progress in identifying various pathophysiological changes and risk factors and in characterizing the illness; further, similarities with other viral-onset illnesses such as myalgic encephalomyelitis/chronic fatigue syndrome and postural orthostatic tachycardia syndrome have laid the groundwork for research in the field. In this Review, we explore the current literature and highlight key findings, the overlap with other conditions, the variable onset of symptoms, long COVID in children and the impact of vaccinations. Although these key findings are critical to understanding long COVID, current diagnostic and treatment options are insufficient, and clinical trials must be prioritized that address leading hypotheses. Additionally, to strengthen long COVID research, future studies must account for biases and SARS-CoV-2 testing issues, build on viral-onset research, be inclusive of marginalized populations and meaningfully engage patients throughout the research process.

SARS-CoV-2 Reinfection is Preceded by Unique Biomarkers and Related to Initial Infection Timing and Severity: an N3C RECOVER EHR-Based Cohort Study.

Although the COVID-19 pandemic has persisted for over 2 years, reinfections with SARS-CoV-2 are not well understood. We use the electronic health record (EHR)-based study cohort from the National COVID Cohort Collaborative (N3C) as part of the NIH Researching COVID to Enhance Recovery (RECOVER) Initiative to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. We validate previous findings of reinfection incidence (5.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present novel findings that Long COVID diagnoses occur closer to the index date for infection or reinfection in the Omicron BA epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between first infection and reinfection (chi-squared value: 9446.2, p-value: 0) with a medium effect size (Cramer's V: 0.18, DoF = 4).

Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes.

BACKGROUND: Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested. METHODS: We present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning. FINDINGS: We found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems. INTERPRETATION: Semantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC. FUNDING: NIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.