Inflammatory risk contributes to post-COVID endothelial dysfunction through anti-ACKR1 autoantibody.

Subclinical vascular impairment can be exacerbated in individuals who experience sustained inflammation after COVID-19 infection. Our study explores the prevalence and impact of autoantibodies on vascular dysfunction in healthy COVID-19 survivors, an area that remains inadequately investigated. Focusing on autoantibodies against the atypical chemokine receptor 1 (ACKR1), COVID-19 survivors demonstrated significantly elevated anti-ACKR1 autoantibodies, correlating with systemic cytokines, circulating damaged endothelial cells, and endothelial dysfunction. An independent cohort linked these autoantibodies to increased vascular disease outcomes during a median 6.7-yr follow-up. We analyzed a single-cell transcriptome atlas of endothelial cells from diverse mouse tissues, identifying enriched Ackr1 expressions in venous regions of the brain and soleus muscle vasculatures, which holds intriguing implications for tissue-specific venous thromboembolism manifestations reported in COVID-19. Functionally, purified immunoglobulin G (IgG) extracted from patient plasma did not trigger cell apoptosis or increase barrier permeability in human vein endothelial cells. Instead, plasma IgG enhanced antibody-dependent cellular cytotoxicity mediated by patient PBMCs, a phenomenon alleviated by blocking peptide or liposome ACKR1 recombinant protein. The blocking peptide uncovered that purified IgG from COVID-19 survivors possessed potential epitopes in the N-terminal extracellular domain of ACKR1, which effectively averted antibody-dependent cellular cytotoxicity. Our findings offer insights into therapeutic development to mitigate autoantibody reactivity in blood vessels in chronic inflammation.

Matrix metallopeptidase 9 contributes to the beginning of plaque and is a potential biomarker for the early identification of atherosclerosis in asymptomatic patients with diabetes.

Aims: To determine the roles of matrix metallopeptidase-9 (MMP9) on human coronary artery smooth muscle cells (HCASMCs) in vitro, early beginning of atherosclerosis in vivo in diabetic mice, and drug naïve patients with diabetes. Methods: Active human MMP9 (act-hMMP9) was added to HCASMCs and the expressions of MCP-1, ICAM-1, and VCAM-1 were measured. Act-hMMP9 (n=16) or placebo (n=15) was administered to diabetic KK.Cg-Ay/J (KK) mice. Carotid artery inflammation and atherosclerosis measurements were made at 2 and 10 weeks after treatment. An observational study of newly diagnosed drug naïve patients with type 2 diabetes mellitus (T2DM n=234) and healthy matched controls (n=41) was performed and patients had ultrasound of carotid arteries and some had coronary computed tomography angiogram for the assessment of atherosclerosis. Serum MMP9 was measured and its correlation with carotid artery or coronary artery plaques was determined. Results: In vitro, act-hMMP9 increased gene and protein expressions of MCP-1, ICAM-1, VCAM-1, and enhanced macrophage adhesion. Exogenous act-hMMP9 increased inflammation and initiated atherosclerosis in KK mice at 2 and 10 weeks: increased vessel wall thickness, lipid accumulation, and Galectin-3+ macrophage infiltration into the carotid arteries. In newly diagnosed T2DM patients, serum MMP9 correlated with carotid artery plaque size with a possible threshold cutoff point. In addition, serum MMP9 correlated with number of mixed plaques and grade of lumen stenosis in coronary arteries of patients with drug naïve T2DM. Conclusion: MMP9 may contribute to the initiation of atherosclerosis and may be a potential biomarker for the early identification of atherosclerosis in patients with diabetes. Clinical trial registration: https://clinicaltrials.gov, identifier NCT04424706.

High-Throughput Microfluidic Extraction of Platelet-free Plasma for MicroRNA and Extracellular Vesicle Analysis.

Cell-free RNAs and extracellular vesicles (EVs) are valuable biomarkers in liquid biopsies, but they are prone to preanalytical variabilities such as nonstandardized centrifugation or ex vivo blood degradation. Herein, we report a high-throughput and label-free inertial microfluidic device (ExoArc) for isolation of platelet-free plasma from blood for RNA and EV analysis. Unlike conventional inertial microfluidic devices widely used for cell sorting, a submicrometer size cutoff (500 nm) was achieved which completely removed all leukocytes, RBCs, platelets, and cellular debris based on differential lateral migration induced by Dean vortices. The single-step operation also reduced platelet-associated miRNAs (∼2-fold) compared to centrifugation. We clinically validated ExoArc for plasma miRNA profiling (39 samples) and identified a 7-miRNA panel that detects non-small cell lung cancer with ∼90% sensitivity. ExoArc was also coupled with size exclusion chromatography (SEC) to isolate EVs within 50 min with ∼10-fold higher yield than ultracentrifugation. As a proof-of-concept for EV-based transcriptomics analysis, we performed miRNA analysis in healthy and type 2 diabetes mellitus (T2DM) subjects (n = 3 per group) by coupling ExoArc and ExoArc+SEC with quantitative polymerase chain reaction (RT-qPCR) assay. Among 293 miRNAs detected, plasmas and EVs showed distinct differentially expressed miRNAs in T2DM subjects. We further demonstrated automated in-line EV sorting from low volume culture media for continuous EV monitoring. Overall, the developed ExoArc offers a convenient centrifugation-free workflow to automate plasma and EV isolation for point-of-care diagnostics and quality control in EV manufacturing.

Isolating Small Extracellular Vesicles from Small Volumes of Blood Plasma using size exclusion chromatography and density gradient ultracentrifugation: A Comparative Study.

Small extracellular vesicles (sEVs) are heterogeneous biological vesicles released by cells under both physiological and pathological conditions. Due to their potential as valuable diagnostic and prognostic biomarkers in human blood, there is a pressing need to develop effective methods for isolating high-purity sEVs from the complex milieu of blood plasma, which contains abundant plasma proteins and lipoproteins. Size exclusion chromatography (SEC) and density gradient ultracentrifugation (DGUC) are two commonly employed isolation techniques that have shown promise in addressing this challenge. In this study, we aimed to determine the optimal combination and sequence of SEC and DGUC for isolating sEVs from small plasma volumes, in order to enhance both the efficiency and purity of the resulting isolates. To achieve this, we compared sEV isolation using two combinations: SEC-DGUC and DGUC-SEC, from unit volumes of 500 µl plasma. Both protocols successfully isolated high-purity sEVs; however, the SEC-DGUC combination yielded higher sEV protein and RNA content. We further characterized the isolated sEVs obtained from the SEC-DGUC protocol using flow cytometry and mass spectrometry to assess their quality and purity. In conclusion, the optimized SEC-DGUC protocol is efficient, highly reproducible, and well-suited for isolating high-purity sEVs from small blood volumes.

Label-free virtual staining of neutrophil extracellular traps (NETs) in microfluidics.

Neutrophils are the most abundant circulating white blood cells and one of their critical functions to eliminate pathogenic threats includes the release of extracellular DNA, also known as neutrophil extracellular traps (NETs), which is dysregulated in many diseases including cancer, type 2 diabetes mellitus and infectious diseases. Currently, conventional methods to quantify the NET formation (NETosis) rely on fluorescence antibody-based NET labelling or circulating NET-associated protein detection by ELISA, which are expensive, laborious, and time-consuming. In this work, we employed a novel "virtual staining" using deep convolutional neural networks (CNNs) to facilitate label-free quantification of NETs trapped in a micropillar array in a microfluidic device. Virtual staining is constructed to establish relations between morphological features in phase contrast images and fluorescence features in Sytox-green (DNA dye) images. We first investigated the effect of different learning rates on model training and optimized the learning rate to achieve the best model which can provide outputs close to Sytox green staining based on various reconstruction metrics (e.g., structural similarity (SSIM) and pixel-wise error (MAE, MSE)). The virtual staining of different NET concentrations was investigated which showed a linear correlation with fluorescent staining. As a proof of concept for clinical testing, the model was used to characterize purified neutrophils treated with NETosis inducers, including lipopolysaccharide (LPS), phorbol 12-myristate 13-acetate (PMA), and calcium ionophore (CaI), and successfully detected different NET profiles for different treatments. Collectively, these results demonstrated the potential of using deep learning for enhanced label-free image analysis of NETs for clinical research, drug discovery and point-of-care testing of diseases.

Generalized metabolic flux analysis framework provides mechanism-based predictions of ophthalmic complications in type 2 diabetes patients.

Chronic metabolic diseases arise from changes in metabolic fluxes through biomolecular pathways and gene networks accumulated over the lifetime of an individual. While clinical and biochemical profiles present just real-time snapshots of the patients' health, efficient computation models of the pathological disturbance of biomolecular processes are required to achieve individualized mechanistic insights into disease progression. Here, we describe the Generalized metabolic flux analysis (GMFA) for addressing this gap. Suitably grouping individual metabolites/fluxes into pools simplifies the analysis of the resulting more coarse-grain network. We also map non-metabolic clinical modalities onto the network with additional edges. Instead of using the time coordinate, the system status (metabolite concentrations and fluxes) is quantified as function of a generalized extent variable (a coordinate in the space of generalized metabolites) that represents the system's coordinate along its evolution path and evaluates the degree of change between any two states on that path. We applied GMFA to analyze Type 2 Diabetes Mellitus (T2DM) patients from two cohorts: EVAS (289 patients from Singapore) and NHANES (517) from the USA. Personalized systems biology models (digital twins) were constructed. We deduced disease dynamics from the individually parameterized metabolic network and predicted the evolution path of the metabolic health state. For each patient, we obtained an individual description of disease dynamics and predict an evolution path of the metabolic health state. Our predictive models achieve an ROC-AUC in the range 0.79-0.95 (sensitivity 80-92%, specificity 62-94%) in identifying phenotypes at the baseline and predicting future development of diabetic retinopathy and cataract progression among T2DM patients within 3 years from the baseline. The GMFA method is a step towards realizing the ultimate goal to develop practical predictive computational models for diagnostics based on systems biology. This tool has potential use in chronic disease management in medical practice. Supplementary Information: The online version contains supplementary material available at 10.1007/s13755-023-00218-x.

Adiposity impacts cognitive function in Asian populations: an epidemiological and Mendelian Randomization study.

Background: Obesity and related metabolic disturbances including diabetes, hypertension and hyperlipidemia predict future cognitive decline. Asia has a high prevalence of both obesity and metabolic disease, potentially amplifying the future burden of dementia in the region. We aimed to investigate the impact of adiposity and metabolic risk on cognitive function in Asian populations, using an epidemiological analysis and a two-sample Mendelian Randomization (MR) study. Methods: The Health for Life in Singapore (HELIOS) Study is a population-based cohort of South-East-Asian men and women in Singapore, aged 30-84 years. We analyzed 8769 participants with metabolic and cognitive data collected between 2018 and 2021. Whole-body fat mass was quantified with Dual X-Ray Absorptiometry (DEXA). Cognition was assessed using a computerized cognitive battery. An index of general cognition ' g ' was derived through factor analysis. We tested the relationship of fat mass indices and metabolic measures with ' g ' using regression approaches. We then performed inverse-variance-weighted MR of adiposity and metabolic risk factors on ' g ', using summary statistics for genome-wide association studies of BMI, visceral adipose tissue (VAT), waist-hip-ratio (WHR), blood pressure, HDL cholesterol, triglycerides, fasting glucose, HbA1c, and general cognition. Findings: Participants were 58.9% female, and aged 51.4 (11.3) years. In univariate analysis, all 29 adiposity and metabolic measures assessed were associated with ' g ' at P < 0.05. In multivariable analyses, reduced ' g ' was consistently associated with increased visceral fat mass index and lower HDL cholesterol (P < 0.001), but not with blood pressure, triglycerides, or glycemic indices. The reduction in ' g ' associated with 1SD higher visceral fat, or 1SD lower HDL cholesterol, was equivalent to a 0.7 and 0.9-year increase in chronological age respectively (P < 0.001). Inverse variance MR analyses showed that reduced ' g ' is associated with genetically determined elevation of VAT, BMI and WHR (all P < 0.001). In contrast, MR did not support a causal role for blood pressure, lipid, or glycemic indices on cognition. Interpretation: We show an independent relationship between adiposity and cognition in a multi-ethnic Asian population. MR analyses suggest that both visceral adiposity and raised BMI are likely to be causally linked to cognition. Our findings have important implications for preservation of cognitive health, including further motivation for action to reverse the rising burden of obesity in the Asia-Pacific region. Funding: The Nanyang Technological University-the Lee Kong Chian School of Medicine, National Healthcare Group, National Medical Research Council, Ministry of Education, Singapore.

Clinical trials on the pharmacological treatment of long COVID: A systematic review.

The postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC), also known as post-acute coronavirus disease 19 (COVID-19) or the long COVID syndrome (long COVID) is an emerging public health concern. A substantial proportion of individuals may remain symptomatic months after initial recovery. An updated review of published and ongoing trials focusing on managing long COVID will help identify gaps and address the unmet needs of patients suffering from this potentially debilitating syndrome. A comprehensive literature search was conducted on the international databases and clinical trial registries from inception to 31 July 2022. This review included 6 published trials and 54 trial registration records. There is significant heterogeneity in the characterization of long COVID and ascertainment of primary outcomes. Most of the trials are focused on individual symptoms of long COVID or isolated organ dysfunction, classified according to cardiovascular, respiratory and functional capacity, neurological and psychological, fatigue, and olfactory dysfunction. Most of the interventions are related to the mechanisms causing the individual symptoms. Although the six published trials showed significant improvement in the symptoms or organ dysfunction studied, these initial studies lack internal and external validity limiting the generalizability. This review provides an update of the pharmacological agents that could be used to treat long COVID. Further standardization of the diagnostic criteria, inclusion of participants with concomitant chronic cardiometabolic diseases and standardization of outcomes will be essential in future clinical trials.

DYNAMIC cohort study evaluating metabolic predictors of influenza vaccine immune response in older adults.

Immunosenescence (age-related immune dysfunction) and inflamm-aging contribute to suboptimal immune responses in older adults to standard-dose influenza vaccines, which may be exacerbated in those with metabolic co-morbidities. We sought to investigate metabolic factors/predictors of influenza vaccine immune response in an older adult (age ≥65 years) cohort in Singapore, where influenza typically circulates year-round. The primary outcome for the DYNAMIC prospective cohort study was haemagglutination-inhibition titer (HAI) response to each of the trivalent inactivated influenza vaccine strains at day 28 (D28) compared to baseline (D0), as assessed by seroconversion and D28/D0 log2 HAI fold rise. Baseline blood samples were tested for total Vitamin D (25-(OH) D) levels. We enrolled 234 participants in June-Dec 2017. Two hundred twenty completed all study visits. The median age was 71 [IQR 68-75] years, 67 (30.5%) had diabetes mellitus (DM), and the median BMI was 24.9 [IQR 22.2-27.8] kg/m2. Median baseline totals 25-(OH) D was 29 [IQR: 21-29] ng/ml. Age, DM, obesity, and baseline 25-(OH) D were not associated with HAI fold rise in multivariable analysis. More recent prior influenza vaccination and higher baseline HAI titers were associated with lower HAI fold rise for influenza A/HK/H3N2. Physical activity was associated with a higher HAI fold rise for influenza A/HK/H3N2 in a dose-response relationship (p-test for trend = 0.015). Older adults with well-controlled metabolic co-morbidities retain HAI response to the influenza vaccine, and physical activity had a beneficial effect on immune response, particularly for influenza A/HK/H3N2.

Cushing's Disease Management: Glimpse Into 2051.

Major advancements are expected in medicine and healthcare in the 21st century- "Digital Age", mainly due to the application of data technologies and artificial intelligence into healthcare. In this perspective article we share a short story depicting the future Cushings' Disease patient and the postulated diagnostic and management approaches. In the discussion, we explain the advances in recent times which makes this future state plausible. We postulate that endocrinology care will be completely reinvented in the Digital Age.

Cardiorespiratory fitness and fat oxidation during exercise in Chinese, Indian, and Malay men with elevated body mass index.

A cross-sectional pilot investigation was performed in Chinese, Indian, and Malay men (15 each) with elevated body mass index to compare (i) cardiorespiratory fitness (CRF) and (ii) fat oxidation at rest and maximal fat oxidation during exercise. Predicted CRF (Chinese: 37.0 (5.1) mL·kg-1·min-1; Indian: 34.8 (5.6) mL·kg-1·min-1; Malay: 33.0 (7.1) mL·kg-1·min-1; P = 0.208) and resting fat oxidation were similar among groups. Maximal fat oxidation during exercise was lower in Indian (3.81 (1.02) mg·kg-1·min-1, P = 0.004) and Malay (3.36 (0.95) mg·kg-1·min-1, P < 0.001) than Chinese (5.17 (1.23) mg·kg-1·min-1) men. Fat oxidation during exercise may contribute toward obesity risk in Asian populations. ClinicalTrials.gov Identifier: NCT05337111.

Reactive Oxygen Species Scavenging Nanomedicine for the Treatment of Ischemic Heart Disease.

Ischemic heart disease (IHD) is the leading cause of disability and mortality worldwide. Reactive oxygen species (ROS) have been shown to play key roles in the progression of diabetes, hypertension, and hypercholesterolemia, which are independent risk factors that lead to atherosclerosis and the development of IHD. Engineered biomaterial-based nanomedicines are under extensive investigation and exploration, serving as smart and multifunctional nanocarriers for synergistic therapeutic effect. Capitalizing on cell/molecule-targeting drug delivery, nanomedicines present enhanced specificity and safety with favorable pharmacokinetics and pharmacodynamics. Herein, the roles of ROS in both IHD and its risk factors are discussed, highlighting cardiovascular medications that have antioxidant properties, and summarizing the advantages, properties, and recent achievements of nanomedicines that have ROS scavenging capacity for the treatment of diabetes, hypertension, hypercholesterolemia, atherosclerosis, ischemia/reperfusion, and myocardial infarction. Finally, the current challenges of nanomedicines for ROS-scavenging treatment of IHD and possible future directions are discussed from a clinical perspective.

Hypercoagulability, endotheliopathy, and inflammation approximating 1 year after recovery: Assessing the long-term outcomes in COVID-19 patients.

Sustained hypercoagulability and endotheliopathy are present in convalescent COVID-19 patients for up to 4 months from recovery. The hemostatic, endothelial, and inflammatory profiles of 39 recovered COVID-19 patients were evaluated up to 16 months after recovery from COVID-19. These values were compared with a control group of healthy volunteers (n = 124). 39 patients (71.8% males, median age 43 years) were reviewed at a mean of 12.7 ± 3.6 months following recovery. One patient without cardiovascular risk factors had post COVID-19 acute ischaemic limb. Elevated D-dimer and Factor VIII levels above normal ranges were noted in 17.9% (7/39) and 48.7% (19/39) of patients respectively, with a higher median D-dimer 0.34 FEU µg/mL (IQR 0.28, 0.46) (p < .001) and Factor VIII 150% (IQR 171, 203) (p = .004), versus controls. Thrombin generation (Thromboscreen) showed a higher median endogenous thrombin potential (ETP) of 1352 nM*min (IQR 1152, 1490) (p = .002) and a higher median peak height of 221.4 nM (IQR 170.2, 280.4) (p = 0.01) and delayed lag time 2.4 min (1.42-2.97) (p = 0.0002) versus controls. Raised vWF:Ag and ICAM-1 levels were observed in 17.9% (7/39) and 7.7% (3/39) of patients respectively, with a higher median VWF:Ag 117% (IQR 86, 154) (p = 0.02) and ICAM-1 54.1 ng/mL (IQR 43.8, 64.1) (p = .004) than controls. IL-6 was noted to be raised in 35.9% (14/39) of patients, with a higher median IL-6 of 1.5 pg/mL (IQR 0.6, 3.0) (p = 0.004) versus controls. Subgroup analysis stratifying patients by COVID-19 severity and COVID-19 vaccination preceding SARS-CoV-2 infection did not show statistically significant differences. Hypercoagulability, endothelial dysfunction, and inflammation are still detectable in some patients approximately 1 year after recovery from COVID-19.

Microfluidic Impedance-Deformability Cytometry for Label-Free Single Neutrophil Mechanophenotyping.

The intrinsic biophysical states of neutrophils are associated with immune dysfunctions in diseases. While advanced image-based biophysical flow cytometers can probe cell deformability at high throughput, it is nontrivial to couple different sensing modalities (e.g., electrical) to measure other critical cell attributes including cell viability and membrane integrity. Herein, an "optics-free" impedance-deformability cytometer for multiparametric single cell mechanophenotyping is reported. The microfluidic platform integrates hydrodynamic cell pinching, and multifrequency impedance quantification of cell size, deformability, and membrane impedance (indicative of cell viability and activation). A newly-defined "electrical deformability index" is validated by numerical simulations, and shows strong correlations with the optical cell deformability index of HL-60 experimentally. Human neutrophils treated with various biochemical stimul are further profiled, and distinct differences in multimodal impedance signatures and UMAP analysis are observed. Overall, the integrated cytometer enables label-free cell profiling at throughput of >1000 cells min-1 without any antibodies labeling to facilitate clinical diagnostics.

SARS-CoV-2 mRNA Vaccination and Graves' Disease: A Report of 12 Cases and Review of the Literature.

CONTEXT AND OBJECTIVE: Thyroid autoimmunity has been reported to be associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the SARS-CoV-2 vaccination recently. We report a series of patients who presented with new onset or relapse of Graves' disease-related hyperthyroidism shortly after receiving the SARS-CoV-2 messenger RNA (mRNA) vaccine at a single tertiary institution in Singapore. METHODS AND RESULTS: We describe 12 patients who developed hyperthyroidism within a relatively short interval (median onset, 17 [range, 5-63] days) after receiving the SARS-CoV-2 mRNA vaccine. The majority were females (11/12) with median age of 35.5 (range, 22-74) years. Six patients had new-onset hyperthyroidism, whereas the other 6 had relapse of previously well-controlled Graves' disease. TSH receptor antibody concentrations ranged from 2.4 to 32 IU/L. The majority of the patients were able to go for the second dose of the vaccine without any further exacerbations. Literature review revealed 21 other similar cases reported from across the world. CONCLUSION: Our case series provides insight into the characteristics of individuals in whom Graves' disease was triggered by the SARS-CoV-2 vaccination. Clinicians need to be vigilant of precipitation or exacerbation of autoimmune thyroid disorders in predisposed individuals after exposure to the SARS-CoV-2 vaccination. Further epidemiological and mechanistic studies are required to elucidate the possible associations between the SARS-CoV-2 vaccines and the development of thyroid autoimmunity.