View details for DOI 10.1161/circ.152.suppl_3.4373447

View details for Web of Science ID 001613909300046

View details for DOI 10.1161/circ.152.suppl_3.4373610

View details for Web of Science ID 001613905000014

Abstract

Cortisol dysregulation has been proposed as a biomarker of long COVID (LC), but findings remain inconsistent. Prior reports suggested low cortisol levels in LC, yet collection times and study designs varied substantially. To evaluate morning serum cortisol distributions in an independent LC cohort, accounting for circadian timing and sleep patterns, we performed a retrospective cross-sectional study of consecutive adults seen at the Stanford Long COVID Clinic between 14 February 2022 and 31 July 2024 (IRB #62996). Eligible participants had confirmed SARS-CoV-2 infection, symptoms persisting ≥3 months per NASEM criteria, completion of the Alliance Sleep Questionnaire (ASQ), and a morning serum cortisol measured using the Roche Elecsys® Cortisol II assay. Analyses were restricted to collections between 05:00-10:00, categorized as early morning peak (EMP: 05:00-08:00) or mid-morning (MMP: 08:01-10:00). Cortisol was classified as low (<6.2 μg/dL), normal (6.2-19.4 μg/dL), or elevated (>19.4 μg/dL). Among 86 LC patients (69.8% female; mean age 45.4 ± 12.9 years), the mean serum cortisol level was 15.67 ± 6.76 μg/dL. Overall, 62.8% of patients had cortisol within the reference range, 36.0% had elevated levels, and only 1.2% (n = 1) had a low value. Cortisol distributions were comparable across the EMP and MMP collection windows, with no statistically significant differences observed by sleep alignment. Inflammatory markers, including CRP and D-dimer, were largely within reference ranges across all cortisol strata. Contrary to earlier reports, low morning cortisol was rare in this LC cohort; most values were normal or elevated. Findings underscore the importance of circadian timing when interpreting cortisol in LC and highlight the need for prospective studies with serial measurements to determine biomarker utility.

View details for DOI 10.3390/biomedicines13112636

View details for PubMedID 41301729

Abstract

Exosomes are extracellular vesicles 30 to 150 nm in size, mediating the paracrine effects of mesenchymal stem cells (MSCs) and induced pluripotent stem cell-derived cardiomyocytes (iCMs) when used to restore the injured myocardium. While both MSC- and iCM-derived exosomes (MSC-Exo, iCM-Exo) improve cardiac function, their mechanisms of action remain incompletely understood. This study investigates the shared and distinct effects of iCM-Exo and MSC-Exo in a porcine ischemia-reperfusion injury model.Female Yorkshire swine underwent proximal left anterior descending artery occlusion with a catheter balloon to induce ischemia-reperfusion injury. Ten 500-μL transendocardial injections delivered a total of 5×1011 iCM-Exo or MSC-Exo into the peri-infarct region. Cardiac function was assessed via MRI at weeks 2 and 4, while transcriptomic sequencing of peri-infarct tissue alongside exosomal cargo were performed to elucidate molecular drivers of exosome influenced, post ischemic modulation of gene expression.Cardiac MRI revealed that iCM-Exo significantly improved left ventricular ejection fraction, myocardial viability, scar size, and ventricular remodeling compared with MSC-Exo and PBS controls. Transcriptomic analysis revealed both shared and distinct gene expression patterns between the treatments. Shared pathways, including extracellular matrix remodeling and neurovascular integration, contributed to baseline cardiac improvement. Distinct pathways in iCM-Exo treatment involved metabolic reorganization and cardiomyocyte-specific processes, while MSC-Exo emphasized structural stabilization and anti-inflammatory responses.These findings highlight the complementary roles of iCM-Exo and MSC-Exo in myocardial repair with shared pathways contributing to baseline improvement and distinct pathways driving differences in efficacy. Future studies investigating the potential of combinatorial approaches may provide further insights into optimizing the therapeutic outcomes for patients with heart failure.

View details for DOI 10.1161/JAHA.124.037005

View details for PubMedID 41128145

View details for DOI 10.1016/j.cej.2025.167391

View details for Web of Science ID 001566145700001

Abstract

The COVID-19 pandemic has revealed that the impact of SARS-CoV-2 infection extends well beyond the acute phase, with long-term sequelae affecting multiple organ systems, most notably, the cardiovascular system. Long COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), is characterized by persistent symptoms such as fatigue, dyspnea, chest pain, and palpitations, which can last for months or even years after initial recovery. Increasing evidence implicates immune dysregulation, endothelial dysfunction, persistent viral antigens, and coagulopathy as central drivers of cardiovascular complications. Mechanistic studies demonstrate that direct viral infection of cardiac and vascular cells, along with autoantibody formation and cytokine-mediated injury, contribute to myocardial inflammation, fibrosis, and arrhythmias. Sex-based immunological differences and underlying comorbidities further influence individual susceptibility and disease trajectory. Large-scale epidemiological studies have confirmed significantly increased risks of pericarditis, cardiomyopathy, dysrhythmias, and heart failure among COVID-19 survivors. In parallel, the emergence of advanced preclinical platforms, including patient-derived induced pluripotent stem cell (iPSC)-based cardiac organoids, engineered heart tissues, and organ-on-a-chip systems has enabled mechanistic dissection of Long COVID pathophysiology. These human-relevant models, when integrated with clinical datasets and artificial intelligence (AI)-driven analytics, offer powerful tools for biomarker discovery, risk stratification, and precision therapeutic development. This review synthesizes the current understanding of cardiovascular involvement in Long COVID, highlights key mechanistic insights from both clinical and preclinical studies, and outlines future directions for diagnostic and therapeutic innovation.

View details for DOI 10.1016/j.yjmcc.2025.09.008

View details for PubMedID 41038267

Abstract

One in ten Americans carry a lifetime risk of ischemic heart failure, the most severe form of ischemic heart disease. Carrying a nearly 50% five‑year mortality rate, no interventional therapy exists to treat the underlying cause, microvascular malperfusion. In efforts to combat microvascular malperfusion, our group has utilized synergistic application of endothelial progenitor cells (EPCs) and smooth muscle cells (SMCs) to induce angiogenesis in ischemic myocardium.Cells are then embedded into a rapidly manufacturable compressed collagen (CC) patch to provide a biosimilar scaffold ready for transplantation. The performance of the cellular compressed collagen patch was then tested on a rodent acute myocardial infarction model of ischemic heart failure.By post‑transplantation Day 28, the cellular CC patch improved left ventricular ejection fraction when compared to an acellular CC patch and control (cellular: 49.1 ± 1.8%; acellular: 38.0 ± 2.6%; control: 39.2 ± 2.1%; ANOVA P = .0006). Cellular CC patch transplantation also induced mature angiogenesis as shown by arteriolar density (cellular: 1084 ± 98 αSMA+vWF+/mm2; acellular: 338 ± 57 αSMA+vWF+/mm2; control: 449 ± 39 αSMA+vWF+/mm2; ANOVA P = .0003) and vascular maturation index (cellular: 0.67 ± 0.04; acellular: 0.48 ± 0.02; and control: 0.46 ± 0.04, P = .001).In conclusion, transplantation of a rapidly manufacturable EPC‑SMC‑based compressed collagen patch effectively rescues myocardial function by enhancing neovascularization and attenuating post‑infarction myocardial injury.

View details for DOI 10.1093/stcltm/szaf035

View details for PubMedID 40973918

View details for PubMedCentralID PMC12449208

Abstract

Digital biometrics can be used to monitor disease, but there is limited research on their applications for assessing postacute sequelae of SARS-CoV-2 (PASC) or long COVID.To better understand digital biometric patterns in long COVID using wearable device technology and whether there are any differences between the nirmatrelvir-ritonavir and placebo-ritonavir intervention arms.This secondary analysis is an exploratory substudy of a placebo-controlled randomized clinical trial (Selective Trial of Paxlovid for PASC [STOP-PASC]) that was conducted from November 2022 to September 2023 at Stanford University. Trial participants were randomized, and a subset enrolled into the prespecified substudy.Participants were randomized 2:1 to receive oral nirmatrelvir (300 mg) and ritonavir (100 mg) or placebo-ritonavir twice daily for 15 days. Substudy participants were provided with a smartwatch and asked to wear it for 24 hours a day, 7 days a week for the 15-week study.Mean changes in digital biometric measures in physical activity, heart rate, and oxygen saturation tracked by a smartwatch. Biometric measures were summarized by treatment arm for each of 5 different time frames: baseline, treatment period, and 3 subsequent time intervals. Summary measure trajectories were clustered and demographics and clinical characteristics were compared among clusters using absolute standardized differences expressed in units of SDs.Of the 94 participants enrolled in the substudy, 50 (37 in nirmatrelvir-ritonavir and 13 in placebo-ritonavir) met the analysis eligibility criteria based on wear time and data completeness. These participants had a mean (SD) age of 42.7 (13.2) years and included 29 females (58.0%). Using mixed models for repeated measures, no significant differences were detected between the intervention arms in the change in biometric measures over time, consistent with the patient-reported outcomes in the STOP-PASC trial. In the overall substudy cohort, latent class mixed models and cluster analysis identified distinct longitudinal trajectories of long COVID over the 15-week study that tracked with different symptoms. Participants with lower daytime physical activity reported more severe fatigue (9 of 9 [100%] vs 21 of 23 [91.3%]; absolute standardized difference [ASD], 0.30), shortness of breath (9 of 9 [100%] vs 7 of 23 [30.4%]; ASD, 1.31), and cardiovascular symptoms (8 of 9 [88.9%] vs 12 of 23 [52.2%]; ASD, 0.70). Those with higher nighttime physical activity reported more gastrointestinal symptoms (2 of 3 [66.7%] vs 11 of 35 [31.4%]; ASD, 0.50). Additionally, participants with higher median daytime heart rates reported less fatigue (7 of 9 [77.8%] vs 39 of 40 [97.5%]; ASD, 0.63) and shortness of breath (3 of 9 [33.3%] vs 23 of 40 [57.5%]; ASD, 0.50) compared with those with lower heart rates.This secondary analysis identified distinct longitudinal trajectories of physiological and behavioral digital biometric measures captured from wearable devices that reflect the heterogeneity and track with different symptoms of long COVID. Digital biometric measures from wearable devices have promising utility for long COVID research.ClinicalTrials.gov Identifier: NCT05576662.

View details for DOI 10.1001/jamanetworkopen.2025.26901

View details for PubMedID 40810942

View details for PubMedCentralID PMC12355292

View details for DOI 10.1007/s10286-025-01123-x

View details for PubMedID 40272628

Abstract

In this study, we aimed to better understand the duration and severity of autonomic dysfunction in adults with Long COVID (LC) and evaluate its impact on function and quality of life. We also sought to assess risk factors of moderate to severe autonomic dysfunction in LC as well as the risk of developing postural tachycardia syndrome (POTS).Autonomic dysfunction is a common complication of LC, however, longitudinal prevalence and autonomic symptom burden in Long COVID patients is not well-established.We utilized a cohort of LC patients, initially recruited in 2020-2021 for a prior study on autonomic dysfunction. Participants completed an online battery of questionnaires, including the COMPASS-31 for autonomic symptom severity and the RAND-36 for quality of life assessment. Multivariable logistic regression identified predictors of moderate-to-severe autonomic dysfunction and risk factors for developing postural tachycardia syndrome (POTS).526 adults (median age 48.5 [41-56] years, 88.8% female) were included in the final analysis, with a median symptom duration of 36 [30-40] months. 71.9% of participants had a COMPASS-31 score ≥ 20, indicating moderate to severe autonomic dysfunction. Significant predictors of COMPASS-31 scores ≥ 20 included female sex and joint hypermobility. 33.4% reported a new POTS diagnosis following SARS-CoV-2 infection, with significant predictors being age (OR=0.97, p=0.001) and joint hypermobility (OR=1.99, p=0.001). 37.5% of LC patients had to quit their job or drop out of school due to their LC illness.Evidence of persistent autonomic dysfunction was seen in 71.9% of LC participants in our study up to 3.5 years after initial SARS-CoV-2 infection, suggesting that chronic autonomic dysfunction is common in LC, with POTS being the most common autonomic diagnosis reported. Moderate to severe autonomic dysfunction was significantly correlated with impaired function and capacity, highlighting the need to address autonomic dysfunction as a key component of Long COVID management. Disclaimer: Abstracts were not reviewed by Neurology® and do not reflect the views of Neurology® editors or staff. Disclosure: An immediate family member of Miss Eastin has received personal compensation for serving as an employee of Laura's House. Jannika Machnik has nothing to disclose. An immediate family member of Dr. Larsen has stock in Health Care Select SPDR. An immediate family member of Dr. Larsen has stock in Ishares Biotechnology. Dr. Larsen has stock in Amazon. Lauren Stiles has received personal compensation for serving as an employee of Dysautonomia International. Jordan Seliger has nothing to disclose. The institution of Prof. Geng has received research support from Pfizer, Inc.. The institution of Prof. Geng has received research support from NIH. The institution of Prof. Geng has received research support from AHRQ. Dr. Bonilla has nothing to disclose. Author has nothing to discloseDr. Miglis has received personal compensation in the range of

Abstract

Protein corona, a layer predominantly composed of proteins and other biomolecules that forms on nanoparticle surfaces upon interaction with biological fluids, has recently been extensively utilized to enhance the depth of plasma proteomics and biomarker discovery. In this study, we integrate protein corona profiling with mass spectrometry (MS)-based bottom-up proteomics (BUP), machine learning, and causality analysis to identify potential biomarkers in the field of cardio-oncology. We selected prostate cancer (PC) and atherosclerosis as model cardio-oncology diseases, given that PC is the most prevalent cancer among men in the United States and frequently coexists with atherosclerotic cardiovascular disease (ASCVD), which contributes to the progression of metastatic PC (mPC). Protein corona profiles were generated from 35 plasma samples categorized into four groups: mPC with ASCVD, nonmetastatic PC (nmPC) with ASCVD, mPC without ASCVD, and nmPC without ASCVD. MS-based BUP analysis identified 887 unique proteins within the protein corona. Gene Ontology (GO) analysis of the 260 proteins common to all samples revealed key plasma proteomic pathways significantly associated with ASCVD and mPC. Using Least Absolute Shrinkage and Selection Operator (LASSO) regularization, we isolated 22 proteins strongly associated with ASCVD or mPC, including chaperonin containing TCP1 subunit 7 (CCT7), which was common to both conditions. Automated formal reasoning and causality analysis of these 22 proteins identified thromboxane-A synthase 1 (TBXAS1) as a primary causal factor linked to both ASCVD and mPC. TBXAS1 plays a critical role in promoting platelet aggregation, vascular smooth muscle cell proliferation, endothelial dysfunction, and thrombosis. In this proof-of-concept study, CCT7 and TBXAS1 emerged as potential biomarkers for both ASCVD and mPC, suggesting their utility as dual biomarkers for early detection and targeted therapeutic interventions. By combining nanomedicine with advanced analytical methods, our integrated approach provides a robust framework for uncovering causal relationships between biomarkers and disease states.

View details for DOI 10.1016/j.cej.2025.161134

View details for PubMedID 40190726

View details for PubMedCentralID PMC11970620

View details for DOI 10.1016/j.cej.2025.161134

View details for Web of Science ID 001443130100001

View details for DOI 10.1016/j.jacbts.2025.01.012

View details for PubMedID 40139867

Abstract

Autonomic dysfunction is a common and often debilitating feature of long-COVID (LC), however, studies evaluating frequency and severity of chronic autonomic dysfunction in LC are limited. We utilized an established online cohort of participants with LC to assess duration and severity of autonomic dysfunction, impact on quality of life, risk factors of autonomic diagnoses including postural tachycardia syndrome (POTS), and efficacy of common treatments.Our international cohort included 526 adults with LC aged 20-65 years who previously completed baseline evaluations of LC symptoms, autonomic symptom burden, and quality of life. Participants repeated survey instruments and completed new instruments assessing risk factors and symptom mitigation strategies. A subset of individuals completed a 10-min active stand test. Multivariable logistic regression identified predictors of autonomic symptom burden and incident autonomic diagnoses including POTS.A total of 71.9% of participants with LC had a Composite Autonomic Symptom Score-31 (COMPASS-31) score ≥ 20, suggestive of moderate-to-severe autonomic dysfunction. The median symptom duration was 36 [30-40] months, and 37.5% of participants could no longer work or had to drop out of school due to their illness. In addition, 40.5% of individuals with autonomic dysfunction were newly diagnosed with POTS, representing 33% of the total LC cohort. Female sex and joint hypermobility were associated with an increased risk of autonomic dysfunction.Evidence of chronic moderate-to-severe autonomic dysfunction was seen in most participants with LC in our cohort and was significantly associated with reduced quality of life and functional disability. POTS was the most common post-COVID autonomic diagnosis.

View details for DOI 10.1007/s10286-025-01111-1

View details for PubMedID 39907931

View details for PubMedCentralID 9639503

View details for DOI 10.3390/biomedicines13112636