Changes in glomerular filtration rate and metabolomic differences in severely ill coronavirus disease survivors 3 months after discharge

Desorption Separation Ionization Mass Spectrometry (DSI-MS) for Rapid Analysis of COVID-19

During the coronavirus disease 2019 (COVID-19) pandemic, which has witnessed over 772 million confirmed cases and over 6 million deaths globally, the outbreak of COVID-19 has emerged as a significant medical challenge affecting both affluent and impoverished nations. Therefore, there is an urgent need to explore the disease mechanism and to implement rapid detection methods. To address this, we employed the desorption separation ionization (DSI) device in conjunction with a mass spectrometer for the efficient detection and screening of COVID-19 urine samples. The study encompassed patients with COVID-19, healthy controls (HC), and patients with other types of pneumonia (OP) to evaluate their urine metabolomic profiles. Subsequently, we identified the differentially expressed metabolites in the COVID-19 patients and recognized amino acid metabolism as the predominant metabolic pathway involved. Furthermore, multiple established machine learning algorithms validated the exceptional performance of the metabolites in discriminating the COVID-19 group from healthy subjects, with an area under the curve of 0.932 in the blind test set. This study collectively suggests that the small-molecule metabolites detected from urine using the DSI device allow for rapid screening of COVID-19, taking just three minutes per sample. This approach has the potential to expand our understanding of the pathophysiological mechanisms of COVID-19 and offers a way to rapidly screen patients with COVID-19 through the utilization of machine learning algorithms.

Interactions between the principal risk factors for reduction of the eGFR in unvaccinated COVID‑19 survivors: Normal pre-COVID‑19 eGFR, not having diabetes and being hospitalized

There are contradictory results regarding changes in estimated glomerular filtration rate (eGFR) in coronavirus disease 2019 (COVID-19) survivors. An analysis of eGFR changes and clinical characteristics associated with those changes was conducted among COVID-19 survivors. eGFR values were compared at different time points (before and 4-, 8- and 12-months after COVID-19 infection). A multivariate generalized linear mixed model (GENLINMIXED procedure) with a binary logistic regression link was used to determine factors associated with eGFR reduction of ≥10 ml/min/1.73 m2. Being hospitalized (RR=2.90, 95% CI=1.10-7.68, P=0.032), treated with Ivermectin (RR=14.02, 95% CI=4.11-47.80, P<0.001) or anticoagulants (RR=6.51, 95% CI=2.69-15.73, P<0.001) are risk factors for a reduced eGFR. Having a low eGFR (<90 ml/min/1.73 m2) before COVID-19 infection, having B-positive blood type, diabetes, taking vitamin C during the acute phase of COVID-19 or suffering from chronic COVID-19 symptoms, were identified as protective factors. Analysis involving a two-way interaction (A x B, where A and B are factors) demonstrated that the combination of patients with a normal eGFR value before COVID-19 infection without diabetes (RR=58.60, 95% CI=11.62-295.38, P<0.001), or a normal eGFR value with being hospitalized for COVID-19 (RR=38.07, 95% CI=8.68-167.00, P<0.001), increased the probability of a reduced eGFR. The changes in eGFR in COVID-19 survivors varied depending on patient characteristics. Furthermore, the principal risk factors for post-COVID-19 eGFR reduction were analyzed in separate models.

Long-term renal outcomes of patients with COVID-19: a meta-analysis of observational studies

BACKGROUND

Kidney involvement is common in hospitalized coronavirus disease 2019 (COVID-19) patients during the acute phase, little is known about the long-term impact of COVID-19 on the kidney.

METHODS

This is a systematic review and meta-analysis on long-term renal outcomes among COVID-19 patients. We carried out a systematic literature search in PUBMED, EMBASE, SCOPUS, and Cochrane COVID-19 study register and performed the random-effects meta-analysis of rates. The search was last updated on November 23, 2022.

RESULTS

The study included 12 moderate to high-quality cohort studies involving 6976 patients with COVID-19-associated acute kidney injury and 5223 COVID-19 patients without acute kidney injury. The summarized long-term renal non-recovery rate, dialysis-dependent rate, and complete recovery rate among patients with COVID-19-associated AKI was 22% (12-33%), 6% (2-12%), and 63% (44-81%) during a follow-up of 90-326.5 days. Heterogeneity could be explained by differences in the prevalence of chronic kidney disease and proportion of acute kidney injury requiring renal replacement therapy using meta-regression; patients with more comorbidities or higher renal replacement therapy rate had higher non-recovery rates. The summarized long-term kidney function decrease rate among patients without acute kidney injury was 22% (3-51%) in 90-199 days, with heterogeneity partially explained by severity of infection.

CONCLUSION

Patients with more comorbidities tend to have a higher renal non recovery rate after COVID-19-associated acute kidney injury; for COVID-19 patients without acute kidney injury, decrease in kidney function may occur during long-term follow-up. Regular evaluation of kidney function during the post-COVID-19 follow-up among high-risk patients may be necessary.

Lactate dehydrogenase contribution to symptom persistence in long COVID: A pooled analysis

There's critical need for risk predictors in long COVID. This meta-analysis evaluates the evidence for an association between plasma lactate dehydrogenase (LDH) and long COVID and explores the contribution of LDH to symptoms persistent across the distinct post-acute sequelae of COVID-19 (PASC) domains. PubMed, EMBASE, Web of Science, and Google Scholar were searched for articles published up to 20 March 2023 for studies that reported data on LDH levels in COVID-19 survivors with and without PASC. Random-effect meta-analysis was employed to estimate the standardized mean difference (SMD) with corresponding 95% confidence interval of each outcome. There were a total of 8289 study participants (3338 PASC vs. 4951 controls) from 46 studies. Our meta-analysis compared to the controls showed a significant association between LDH elevation and Resp-PASC [SMD = 1.07, 95%CI = 0.72, 1.41, p = 0.01] but not Cardio-PASC [SMD = 1.79, 95%CI = -0.02, 3.61, p = 0.05], Neuro-PASC [SMD = 0.19, 95%CI = -0.24, 0.61, p = 0.40], and Gastrointestinal-PASC [SMD = 0.45, 95%CI = -1.08, 1.98, p = 0.56]. This meta-analysis suggests elevated LDH can be used for predicting Resp-PASC, but not Cardio-PASC, Neuro-PASC or gastrointestinal-PASC. Thus, elevated plasma LDH following COVID infection may be considered as a disease biomarker.

Nanopore membrane chip-based isolation method for metabolomic analysis of plasma small extracellular vesicles from COVID-19 survivors

Multiple studies showed that metabolic disorders play a critical role in respiratory infectious diseases, including COVID-19. Metabolites contained in small extracellular vesicles (sEVs) are different from those in plasma at the acute stage, while the metabolic features of plasma sEVs of COVID-19 survivors remain unknown. Here, we used a nanopore membrane-based microfluidic chip for plasma sEVs separation, termed ExoSEC, and compared the sEVs obtained by UC, REG, and ExoSEC in terms the time, cost, purity, and metabolic features. The results indicated the ExoSEC was much less costly, provided higher purity by particles/proteins ratio, and achieved 205-fold and 2-fold higher sEVs yield, than UC and REG, respectively. Moreover, more metabolites were identified and several signaling pathways were significantly enriched in ExoSEC-sEVs compared to UC-sEVs and REG-sEVs. Furthermore, we detected 306 metabolites in plasma sEVs using ExoSEC from recovered asymptomatic (RA), moderate (RM), and severe/critical COVID-19 (RS) patients without underlying diseases 3 months after discharge. Our study demonstrated that COVID-19 survivors, especially RS, experienced significant metabolic alteration and the dysregulated pathways mainly involved fatty acid biosynthesis, phenylalanine metabolism, etc. Metabolites of the fatty acid biosynthesis pathway bore a significantly negative association with red blood cell counts and hemoglobin, which might be ascribed to hypoxia or respiratory failure in RM and RS but not in RA at the acute stage. Our study confirmed that ExoSEC could provide a practical and economical alternative for high throughput sEVs metabolomic study.

Long COVID: The latest manifestations, mechanisms, and potential therapeutic interventions

COVID-19 caused by SARS-CoV-2 infection affects humans not only during the acute phase of the infection, but also several weeks to 2 years after the recovery. SARS-CoV-2 infects a variety of cells in the human body, including lung cells, intestinal cells, vascular endothelial cells, olfactory epithelial cells, etc. The damages caused by the infections of these cells and enduring immune response are the basis of long COVID. Notably, the changes in gene expression caused by viral infection can also indirectly contribute to long COVID. We summarized the occurrences of both common and uncommon long COVID, including damages to lung and respiratory system, olfactory and taste deficiency, damages to myocardial, renal, muscle, and enduring inflammation. Moreover, we provided potential treatments for long COVID symptoms manifested in different organs and systems, which were based on the pathogenesis and the associations between symptoms in different organs. Importantly, we compared the differences in symptoms and frequency of long COVID caused by breakthrough infection after vaccination and infection with different variants of concern, in order to provide a comprehensive understanding of the characteristics of long COVID and propose improvement for tackling COVID-19.

Alterations in the Kynurenine-Tryptophan Pathway and Lipid Dysregulation Are Preserved Features of COVID-19 in Hemodialysis

Coronavirus disease 2019 (COVID-19)-induced metabolic alterations have been proposed as a source for prognostic biomarkers and may harbor potential for therapeutic exploitation. However, the metabolic impact of COVID-19 in hemodialysis (HD), a setting of profound a priori alterations, remains unstudied. To evaluate potential COVID-19 biomarkers in end-stage kidney disease (CKD G5), we analyzed the plasma metabolites in different COVID-19 stages in patients with or without HD. We recruited 18 and 9 asymptomatic and mild, 11 and 11 moderate, 2 and 13 severely affected, and 10 and 6 uninfected HD and non-HD patients, respectively. Plasma samples were taken at the time of diagnosis and/or upon admission to the hospital and analyzed by targeted metabolomics and cytokine/chemokine profiling. Targeted metabolomics confirmed stage-dependent alterations of the metabolome in non-HD patients with COVID-19, which were less pronounced in HD patients. Elevated kynurenine levels and lipid dysregulation, shown by an increase in circulating free fatty acids and a decrease in lysophospholipids, could distinguish patients with moderate COVID-19 from non-infected individuals in both groups. Kynurenine and lipid alterations were also associated with ICAM-1 and IL-15 levels in HD and non-HD patients. Our findings support the kynurenine pathway and plasma lipids as universal biomarkers of moderate and severe COVID-19 independent of kidney function.

Serum metabolomic abnormalities in survivors of non-severe COVID-19

Metabolic reprogramming is a distinctive characteristic of SARS-CoV-2 infection, which refers to metabolic changes in hosts triggered by viruses for their survival and spread. It is current urgent to understand the metabolic health status of COVID-19 survivors and its association with long-term health consequences of infection, especially for the predominant non-severe patients. Herein, we show systemic metabolic signatures of survivors of non-severe COVID-19 from Wuhan, China at six months after discharge using metabolomics approaches. The serum amino acids, organic acids, purine, fatty acids and lipid metabolism were still abnormal in the survivors, but the kynurenine pathway and the level of itaconic acid have returned to normal. These metabolic abnormalities are associated with liver injury, mental health, energy production, and inflammatory responses. Our findings identify and highlight the metabolic abnormalities in survivors of non-severe COVID-19, which provide information on biomarkers and therapeutic targets of infection and cues for post-hospital care and intervention strategies centered on metabolism reprogramming.