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2.
CJC Open ; 4(5): 479-487, 2022 May.
Article in English | MEDLINE | ID: covidwho-1800144

ABSTRACT

Background: The COVID-19 pandemic has reduced access to endomyocardial biopsy (EMB) rejection surveillance in heart transplant (HT) recipients. This study is the first in Canada to assess the role for noninvasive rejection surveillance in personalizing titration of immunosuppression and patient satisfaction post-HT. Methods: In this mixed-methods prospective cohort study, adult HT recipients more than 6 months from HT had their routine EMBs replaced by noninvasive rejection surveillance with gene expression profiling (GEP) and donor-derived cell-free DNA (dd-cfDNA) testing. Demographics, outcomes of noninvasive surveillance score, hospital admissions, patient satisfaction, and health status on the medical outcomes study 12-item short-form health survey (SF-12) were collected and analyzed, using t tests and χ2 tests. Thematic qualitative analysis was performed for open-ended responses. Results: Among 90 patients, 31 (33%) were enrolled. A total of 36 combined GEP/dd-cfDNA tests were performed; 22 (61%) had negative results for both, 10 (27%) had positive GEP/negative dd-cfDNA results, 4 (11%) had negative GEP/positive dd-cfDNA results, and 0 were positive on both. All patients with a positive dd-cfDNA result (range: 0.19%-0.81%) underwent EMB with no significant cellular or antibody-mediated rejection. A total of 15 cases (42%) had immunosuppression reduction, and this increased to 55% in patients with negative concordant testing. Overall, patients' reported satisfaction was 90%, and on thematic analysis they were more satisfied, with less anxiety, during the noninvasive testing experience. Conclusions: Noninvasive rejection surveillance was associated with the ability to lower immunosuppression, increase satisfaction, and reduce anxiety in HT recipients, minimizing exposure for patients and providers during a global pandemic.


Contexte: La pandémie de COVID-19 a réduit l'accès à la biopsie endomyocardique pour surveiller le risque de rejet après une greffe du cœur. Cette étude est la première à être menée au Canada pour évaluer le rôle de la surveillance non invasive du risque de rejet en personnalisant le titrage de l'immunosuppression et la satisfaction du patient après la greffe cardiaque. Méthodologie: Dans le cadre de cette étude de cohorte prospective à méthodes mixtes, des adultes ayant reçu une greffe cardiaque depuis plus de six mois ont vu leurs biopsies endomyocardiques régulières remplacées par une surveillance non invasive du risque de rejet qui consiste à établir le profil de l'expression génique et à analyser l'ADN acellulaire dérivé du donneur. Les données démographiques, les résultats du score de surveillance non invasive, les admissions à l'hôpital, la satisfaction des patients et l'état de santé tirés du questionnaire SF-12 (questionnaire abrégé sur la santé comprenant 12 items) de l'étude sur les issues médicales ont été colligés et analysés au moyen des tests T et des tests χ2. Les réponses ouvertes ont fait l'objet d'une analyse qualitative thématique. Résultats: Parmi 90 patients, 31 (33 %) ont été recrutés. Au total, 36 tests combinés de profilages de l'expression génique et d'ADN acellulaire dérivé du donneur ont été réalisés; les résultats ont été négatifs pour les deux tests dans 22 cas (61 %), positifs pour le profilage de l'expression génique et négatifs pour l'ADN acellulaire dans 10 cas (27 %), négatifs pour le profilage de l'expression génique et positifs pour l'ADN acellulaire dans quatre cas (11 %) et aucun cas n'a donné de résultats positifs pour les deux types de tests. Tous les patients qui ont donné des résultats positifs à l'analyse de l'ADN acellulaire dérivé du donneur (fourchette : 0,19 % à 0,81 %) ont subi une biopsie endomyocardique n'ayant révélé aucun rejet cellulaire ou à médiation par anticorps important. Au total, 15 cas (42 %) affichaient une immunosuppression réduite, proportion qui a grimpé à 55 % chez les patients dont les tests de concordance ont donné des résultats négatifs. Dans l'ensemble, le niveau de satisfaction rapporté par les patients était de 90 % et, à l'analyse thématique, ils étaient plus satisfaits et moins anxieux pendant les tests non invasifs. Conclusions: La surveillance non invasive du risque de rejet a été associée à la capacité de diminuer l'immunosuppression, d'augmenter la satisfaction et de réduire l'anxiété chez les patients qui ont reçu une greffe cardiaque, en plus de réduire l'exposition des patients et du personnel médical dans le contexte d'une pandémie.

3.
EBioMedicine ; 78: 103982, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1783293

ABSTRACT

BACKGROUND: Endothelial cell (EC) activation, endotheliitis, vascular permeability, and thrombosis have been observed in patients with severe coronavirus disease 2019 (COVID-19), indicating that the vasculature is affected during the acute stages of SARS-CoV-2 infection. It remains unknown whether circulating vascular markers are sufficient to predict clinical outcomes, are unique to COVID-19, and if vascular permeability can be therapeutically targeted. METHODS: Prospectively evaluating the prevalence of circulating inflammatory, cardiac, and EC activation markers as well as developing a microRNA atlas in 241 unvaccinated patients with suspected SARS-CoV-2 infection allowed for prognostic value assessment using a Random Forest model machine learning approach. Subsequent ex vivo experiments assessed EC permeability responses to patient plasma and were used to uncover modulated gene regulatory networks from which rational therapeutic design was inferred. FINDINGS: Multiple inflammatory and EC activation biomarkers were associated with mortality in COVID-19 patients and in severity-matched SARS-CoV-2-negative patients, while dysregulation of specific microRNAs at presentation was specific for poor COVID-19-related outcomes and revealed disease-relevant pathways. Integrating the datasets using a machine learning approach further enhanced clinical risk prediction for in-hospital mortality. Exposure of ECs to COVID-19 patient plasma resulted in severity-specific gene expression responses and EC barrier dysfunction, which was ameliorated using angiopoietin-1 mimetic or recombinant Slit2-N. INTERPRETATION: Integration of multi-omics data identified microRNA and vascular biomarkers prognostic of in-hospital mortality in COVID-19 patients and revealed that vascular stabilizing therapies should be explored as a treatment for endothelial dysfunction in COVID-19, and other severe diseases where endothelial dysfunction has a central role in pathogenesis. FUNDING: This work was directly supported by grant funding from the Ted Rogers Center for Heart Research, Toronto, Ontario, Canada and the Peter Munk Cardiac Center, Toronto, Ontario, Canada.


Subject(s)
COVID-19 , MicroRNAs , Vascular Diseases , COVID-19/diagnosis , COVID-19/mortality , Capillary Permeability , Humans , MicroRNAs/metabolism , SARS-CoV-2 , Vascular Diseases/virology
4.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327551

ABSTRACT

STRUCTURED ABSTRACT Background Endothelial cell (EC) activation, endotheliitis, vascular permeability, and thrombosis have been observed in patients with severe COVID-19, indicating that the vasculature is affected during the acute stages of SARS-CoV-2 infection. It remains unknown whether circulating vascular markers are sufficient to predict clinical outcomes, are unique to COVID-19, and if vascular permeability can be therapeutically targeted. Methods Evaluating the prevalence of circulating inflammatory, cardiac and EC activation markers, and the development of a microRNA atlas in 241 patients with suspected SARS-CoV-2 infection, allowed their prognostic value to be assessed by a Random Forest model machine learning approach. Subsequent ex vivo experiments assessed EC permeability responses to patient plasma and were used to uncover modulated gene regulatory networks from which rational therapeutic design was inferred. Findings Multiple inflammatory and EC activation biomarkers were associated with mortality in COVID-19 patients and in severity-matched SARS-CoV-2-negative patients, while dysregulation of specific microRNAs at presentation was specific for poor COVID-19-related outcomes and revealed disease-relevant pathways. Integrating the datasets using a machine learning approach further enhanced clinical risk prediction for in-hospital mortality. Exposure of ECs to COVID-19 patient plasma resulted in severity-specific gene expression responses and EC barrier dysfunction which was ameliorated using angiopoietin-1 mimetic or recombinant Slit2-N. Interpretation Integration of multi-omics data identified microRNA and vascular biomarkers prognostic of in-hospital mortality in COVID-19 patients and revealed that vascular stabilizing therapies should be explored as a treatment for endothelial dysfunction in COVID-19, and other severe diseases where endothelial dysfunction has a central role in pathogenesis. RESEARCH IN CONTEXT Evidence before this study While diagnostic testing has allowed for the rapid identification of COVID-19 cases, the lack of post-diagnosis risk assessment metrics, especially among the highest-risk subgroups, thereby undermined the cascade and allocation of care. To date, the integration of clinical data with broad omics technologies has opened up new avenues for efficiently delineating complex patient phenotypes and their associations with clinical outcomes, with circulating profiles of plasma microRNAs (miRNA), in particular, having been shown to be tightly associated with disease, and capable of providing not only detailed prognostic information but also mechanistic insight. Added value of this study Markers of endothelial dysfunction at presentation, while indicative of poor outcomes in COVID-19-positive patients, likely reflect systemic vascular dysfunction in critically ill patients and are not specific to SARS-CoV-2 infection. More so, the generation of a plasma microRNA atlas uncovers COVID-19-specific prognostic markers and multiple disease-specific pathways of interest, including endothelial barrier dysfunction. Furthermore, synthesis of electronic health record data with clinically relevant multi-omic datasets using a machine learning approach provides substantially better metrics by which mortality can be estimated in patients with severe COVID-19. Finally, targeted stabilization of the endothelial barrier with Q-Peptide and Slit2-N are novel therapeutic avenues that should be explored in COVID-19 patients. Implications of all the available evidence Together, our work provides biological insight into the role of the endothelium in SARS-CoV-2 infection, the importance of miRNA as disease- and pathway-specific biomarkers, and the exciting possibility that endothelial barrier stabilizing treatments might hold promise in COVID-19.

5.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-310206

ABSTRACT

The standard way to estimate the parameters $Θ_\text{SEIR}$ (e.g., the transmission rate $β$) of an SEIR model is to use grid search, where simulations are performed on each set of parameters, and the parameter set leading to the least $L_2$ distance between predicted number of infections and observed infections is selected. This brute-force strategy is not only time consuming, as simulations are slow when the population is large, but also inaccurate, since it is impossible to enumerate all parameter combinations. To address these issues, in this paper, we propose to transform the non-differentiable problem of finding optimal $Θ_\text{SEIR}$ to a differentiable one, where we first train a recurrent net to fit a small number of simulation data. Next, based on this recurrent net that is able to generalize SEIR simulations, we are able to transform the objective to a differentiable one with respect to $Θ_\text{SEIR}$, and straightforwardly obtain its optimal value. The proposed strategy is both time efficient as it only relies on a small number of SEIR simulations, and accurate as we are able to find the optimal $Θ_\text{SEIR}$ based on the differentiable objective. On two COVID-19 datasets, we observe that the proposed strategy leads to significantly better parameter estimations with a smaller number of simulations.

6.
Mayo Clin Proc ; 96(10): 2528-2539, 2021 10.
Article in English | MEDLINE | ID: covidwho-1294052

ABSTRACT

OBJECTIVE: To identify risk factors associated with severe COVID-19 infection in a defined Midwestern US population overall and within different age groups. PATIENTS AND METHODS: We used the Rochester Epidemiology Project research infrastructure to identify persons residing in a defined 27-county Midwestern region who had positive results on polymerase chain reaction tests for COVID-19 between March 1, 2020, and September 30, 2020 (N=9928). Age, sex, race, ethnicity, body mass index, smoking status, and 44 chronic disease categories were considered as possible risk factors for severe infection. Severe infection was defined as hospitalization or death caused by COVID-19. Associations between risk factors and severe infection were estimated using Cox proportional hazard models overall and within 3 age groups (0 to 44, 45 to 64, and 65+ years). RESULTS: Overall, 474 (4.8%) persons developed severe COVID-19 infection. Older age, male sex, non-White race, Hispanic ethnicity, obesity, and a higher number of chronic conditions were associated with increased risk of severe infection. After adjustment, 36 chronic disease categories were significantly associated with severe infection. The risk of severe infection varied significantly across age groups. In particular, persons 0 to 44 years of age with cancer, chronic neurologic disorders, hematologic disorders, ischemic heart disease, and other endocrine disorders had a greater than 3-fold increased risk of severe infection compared with persons of the same age without those conditions. Associations were attenuated in older age groups. CONCLUSION: Older persons are more likely to experience severe infections; however, severe cases occur in younger persons as well. Our data provide insight regarding younger persons at especially high risk of severe COVID-19 infection.


Subject(s)
COVID-19/epidemiology , Health Status Disparities , Severity of Illness Index , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Child , Child, Preschool , Chronic Disease/epidemiology , Comorbidity , Humans , Infant , Male , Middle Aged , Midwestern United States , Risk Factors , Young Adult
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