Prevalence and trends in mono- and co-infection of COVID-19, influenza A/B, and respiratory syncytial virus, January 2018–June 2023

ObjectivesThis study aimed to determine the impact of the COVID-19 pandemic on the overall prevalence and co-infection rates for COVID-19, influenza A/B, and respiratory syncytial virus in a large national population.MethodsWe conducted a retrospective review of 1,318,118 multi-component nucleic acid amplification tests for COVID-19, influenza A/B, and RSV performed at Labcorp® sites from January 2018 to June 2023, comparing positivity rates and co-infection rates by age, sex, and seasonality.ResultsIn 2021–2023, 1,232 (0.10%) tested positive for COVID-19 and influenza A/B, 366 (0.03%) tested positive for COVID-19 and RSV, 874 (0.07%) tested for influenza A/B and RSV, and 13 (0.001%) tested positive for COVID-19, influenza A/B, and RSV. RSV positivity rates were particularly higher in Q2 and Q3 of 2021 and in Q3 of 2022. Higher influenza A positivity proportions were found in Q4 of 2021 and again in Q2 and Q4 of 2022. Influenza B positivity had been minimal since the start of the pandemic, with a slight increase observed in Q2 of 2023.ConclusionOur findings highlight the need for adaptability in preparation for upper respiratory infection occurrences throughout the year as we adjust to the COVID-19 pandemic due to the observed changes in the seasonality of influenza and RSV. Our results highlight low co-infection rates and suggest heightened concerns for co-infections during peaks of COVID-19, influenza, and RSV, which may perhaps be reduced

Characterization and Modeling of Metabolic Stress Responses in Cellular Aging

Cellular aging describes the buildup of changes over time that affect normal mechanisms of cells, tissues and organisms throughout their lifespan, which can lead to any number of potential health risks, diseases or other disorders. One of the major causes of these changes is declining mitochondrial function, though the cause of this energy stress is still debated. The prevailing experimental model for aging studies examines cells in a senescent state as the hallmark of aging. Yet this permanent, post-mitotic phase is more commonly observed in vitro. Aged cells in vivo often retain their mitotic potential, indicative of a paused, quiescent state. This thesis proposes a new platform to study aging through perturbations of mitochondrial function via an experimental energy restriction in quiescence (ERiQ) model that may be more relevant to aging in tissues. This model causes adaptive changes in major stress response pathways for AKT, NF-κB, p53 and mTOR as a reaction to reduced ATP, NAD+ and NADP levels. The construction of a theoretical computational model, complementary to the experimental model, is based on feedback motifs that investigate the interplay between those key stress response pathways. The in silico model demonstrates adaptations to sudden energetic perturbations, promoting pro-survival phenotypes and recovery. This thesis hypothesizes that the very same survival mechanisms are chronically activated during aging, but also cause conflicting responses that actively suppress mitochondrial function to contribute to a lockstep progression of decline. The model makes predictions consistent with inhibitory and gain-of-function experiments in aging. The relevance of ERiQ as a model to study aging is further emphasized by a transcription factor (TF) meta-analysis of gene expression datasets accrued from 18 tissues from individuals at different biological ages, which were compared to 7 different experimental platforms. Experimental datasets included replicative senescence and ERiQ, in which ATP was transiently reduced. TF motifs in promoter regions of trimmed sets of target genes were scanned using JASPAR and TRANSFAC motifs and TF signatures established a global mapping of agglomerating motifs with distinct clusters when ranked hierarchically. Remarkably, the majority of in vivo aged tissues correlated with the ERiQ profile instead of senescence, confirming its relevance as a new experimental model. Fitting motifs in a minimalistic protein-protein interaction (PPI) network model allowed us to probe for connectivity to distinct stress sensors, as well as identify novel targets of study in transcription factors that significantly switch enrichment between ERiQ and senescence. In the PPI, DNA damage sensors ATM and ATR linked to one subnetwork associated with senescence. By contrast, energy sensors PTEN and AMPK connected to the nodes in the ERiQ subnetwork. These data suggest that energy deprivation may be linked to transcriptional patterns characteristic of many aged tissues distinct from cumulative DNA damage associated with senescence. Finally, this thesis exemplifies the combined use of the predictive power of the computational model with experimental investigation in vitro. Preliminary experiments show how the model can be refined to reflect how certain conditions may alter metabolic output and offer intriguing insights into the future of cellular aging studies.Ph.D., Biomedical Engineering -- Drexel University, 201

Simulation of Cellular Energy Restriction in Quiescence (ERiQ)—A Theoretical Model for Aging

Cellular responses to energy stress involve activation of pro-survival signaling nodes, compensation in regulatory pathways and adaptations in organelle function. Specifically, energy restriction in quiescent cells (ERiQ) through energetic perturbations causes adaptive changes in response to reduced ATP, NAD+ and NADP levels in a regulatory network spanned by AKT, NF-κB, p53 and mTOR. Based on the experimental ERiQ platform, we have constructed a minimalistic theoretical model consisting of feedback motifs that enable investigation of stress-signaling pathways. The computer simulations reveal responses to acute energetic perturbations, promoting cellular survival and recovery to homeostasis. We speculated that the very same stress mechanisms are activated during aging in post-mitotic cells. To test this hypothesis, we modified the model to be deficient in protein damage clearance and demonstrate the formation of energy stress. Contrasting the network’s pro-survival role in acute energetic challenges, conflicting responses in aging disrupt mitochondrial maintenance and contribute to a lockstep progression of decline when chronically activated. The model was analyzed by a local sensitivity analysis with respect to lifespan and makes predictions consistent with inhibitory and gain-of-function experiments in aging

Global mapping of transcription factor motifs in human aging.

Biological aging is a complex process dependent on the interplay of cell autonomous and tissue contextual changes which occur in response to cumulative molecular stress and manifest through adaptive transcriptional reprogramming. Here we describe a transcription factor (TF) meta-analysis of gene expression datasets accrued from 18 tissue sites collected at different biological ages and from 7 different in-vitro aging models. In-vitro aging platforms included replicative senescence and an energy restriction model in quiescence (ERiQ), in which ATP was transiently reduced. TF motifs in promoter regions of trimmed sets of target genes were scanned using JASPAR and TRANSFAC. TF signatures established a global mapping of agglomerating motifs with distinct clusters when ranked hierarchically. Remarkably, the ERiQ profile was shared with the majority of in-vivo aged tissues. Fitting motifs in a minimalistic protein-protein network allowed to probe for connectivity to distinct stress sensors. The DNA damage sensors ATM and ATR linked to the subnetwork associated with senescence. By contrast, the energy sensors PTEN and AMPK connected to the nodes in the ERiQ subnetwork. These data suggest that metabolic dysfunction may be linked to transcriptional patterns characteristic of many aged tissues and distinct from cumulative DNA damage associated with senescence

Image_1_Prevalence and trends in mono- and co-infection of COVID-19, influenza A/B, and respiratory syncytial virus, January 2018–June 2023.JPEG

ObjectivesThis study aimed to determine the impact of the COVID-19 pandemic on the overall prevalence and co-infection rates for COVID-19, influenza A/B, and respiratory syncytial virus in a large national population.MethodsWe conducted a retrospective review of 1,318,118 multi-component nucleic acid amplification tests for COVID-19, influenza A/B, and RSV performed at Labcorp® sites from January 2018 to June 2023, comparing positivity rates and co-infection rates by age, sex, and seasonality.ResultsIn 2021–2023, 1,232 (0.10%) tested positive for COVID-19 and influenza A/B, 366 (0.03%) tested positive for COVID-19 and RSV, 874 (0.07%) tested for influenza A/B and RSV, and 13 (0.001%) tested positive for COVID-19, influenza A/B, and RSV. RSV positivity rates were particularly higher in Q2 and Q3 of 2021 and in Q3 of 2022. Higher influenza A positivity proportions were found in Q4 of 2021 and again in Q2 and Q4 of 2022. Influenza B positivity had been minimal since the start of the pandemic, with a slight increase observed in Q2 of 2023.ConclusionOur findings highlight the need for adaptability in preparation for upper respiratory infection occurrences throughout the year as we adjust to the COVID-19 pandemic due to the observed changes in the seasonality of influenza and RSV. Our results highlight low co-infection rates and suggest heightened concerns for co-infections during peaks of COVID-19, influenza, and RSV, which may perhaps be reduced.</p

Data_Sheet_1_Prevalence and trends in mono- and co-infection of COVID-19, influenza A/B, and respiratory syncytial virus, January 2018–June 2023.docx

ObjectivesThis study aimed to determine the impact of the COVID-19 pandemic on the overall prevalence and co-infection rates for COVID-19, influenza A/B, and respiratory syncytial virus in a large national population.MethodsWe conducted a retrospective review of 1,318,118 multi-component nucleic acid amplification tests for COVID-19, influenza A/B, and RSV performed at Labcorp® sites from January 2018 to June 2023, comparing positivity rates and co-infection rates by age, sex, and seasonality.ResultsIn 2021–2023, 1,232 (0.10%) tested positive for COVID-19 and influenza A/B, 366 (0.03%) tested positive for COVID-19 and RSV, 874 (0.07%) tested for influenza A/B and RSV, and 13 (0.001%) tested positive for COVID-19, influenza A/B, and RSV. RSV positivity rates were particularly higher in Q2 and Q3 of 2021 and in Q3 of 2022. Higher influenza A positivity proportions were found in Q4 of 2021 and again in Q2 and Q4 of 2022. Influenza B positivity had been minimal since the start of the pandemic, with a slight increase observed in Q2 of 2023.ConclusionOur findings highlight the need for adaptability in preparation for upper respiratory infection occurrences throughout the year as we adjust to the COVID-19 pandemic due to the observed changes in the seasonality of influenza and RSV. Our results highlight low co-infection rates and suggest heightened concerns for co-infections during peaks of COVID-19, influenza, and RSV, which may perhaps be reduced.</p

Follow-Up SARS-CoV-2 PCR Testing Outcomes From a Large Reference Lab in the US

By analyzing COVID-19 sequential COVID-19 test results of patients across the United States, we herein attempt to quantify some of the observations we've made around long-term infection (and false-positive rates), as well as provide observations on the uncertainty of sampling variability and other dynamics of COVID-19 infection in the United States. Retrospective cohort study of a registry of RT-PCR testing results for all patients tested at any of the reference labs operated by Labcorp® including both positive, negative, and inconclusive results, from March 1, 2020 to January 28, 2021, including patients from all 50 states and outlying US territories. The study included 22 million patients with RT-PCR qualitative test results for SARS-CoV-2, of which 3.9 million had more than one test at Labcorp. We observed a minuscule &amp;lt;0.1% basal positive rate for follow up tests &amp;gt;115 days, which could account for false positives, long-haulers, and/or reinfection but is indistinguishable in the data. In observing repeat-testing, for patients who have a second test after a first RT-PCR, 30% across the cohort tested negative on the second test. For patients who test positive first and subsequently negative within 96 h (40% of positive test results), 18% of tests will subsequently test positive within another 96-h span. For those who first test negative and then positive within 96 h (2.3% of negative tests), 56% will test negative after a third and subsequent 96-h period. The sudden changes in RT-PCR test results for SARS-CoV-2 from this large cohort study suggest that negative test results during active infection or exposure can change rapidly within just days or hours. We also demonstrate that there does not appear to be a basal false positive rate among patients who test positive &amp;gt;115 days after their first RT-PCR positive test while failing to observe any evidence of widespread reinfection.</jats:p

Use of hemoglobin A1c to identify dysglycemia in cystic fibrosis

Background Cystic fibrosis (CF) leads to pancreatic endocrine dysfunction with progressive glycemic disturbance. Approximately 30%–50% of people with CF eventually develop CF–related diabetes (CFRD). Pre-CFRD states progress from indeterminant glycemia (INDET) to impaired fasting glucose (IFG) or impaired glucose tolerance (IGT). Screening guidelines recommend inconvenient annual 2-hour oral glucose tolerance tests (OGTTs), beginning at age 10 years. More efficient methods, such as hemoglobin A1C (HbA1c), have been evaluated, but only limited, relatively small studies have evaluated the association between HbA1c and pre-CFRD dysglycemic states. Objective To determine whether HbA1c is an appropriate screening tool for identifying patients with pre-CFRD dysglycemia to minimize the burden of annual OGTTs. Methods This retrospective review evaluated medical records data of all University of Massachusetts Memorial Health System CF patients with an HbA1c result within 90 days of an OGTT between 1997 and 2019. Exclusion criteria were uncertain CF diagnosis, other forms of diabetes, or incomplete OGTT. In total, 56 patients were included and categorized according to OGTT results (American Diabetes Association criteria): normal glucose tolerance, INDET, IFG, or IGT. Associations were evaluated between HbA1c and OGTT results and between HbA1c and pre-CFRD dysglycemic states. Results Mean HbA1c was not significantly different between patients with normal glucose tolerance and those in the INDET (p = 0.987), IFG (p = 0.690), and IGT (p = 0.874) groups. Analysis of variance confirmed the lack of association between HbA1c and glycemia, as mean HbA1c was not significantly different amongst the four categories (p = 0.250). Conclusion There is increasing awareness of the impact of pre-CFRD states, including reduced pulmonary function and nutritional status. Unfortunately, our results do not support using HbA1c as a screening tool for pre-CFRD dysglycemia, specifically INDET, IFG, and IGT. Further studies are warranted to evaluate more efficient screening methods to reduce the burden of annual OGTTs. </jats:sec