Category: Overlapping Illnesses

Long COVID-19 and Insulin Autoimmune Syndrome: A Case Report

Abstract:

Purpose: To describe a case report of a patient with symptoms associated with metabolic alterations 1 month after having COVID-19.

Methods: Laboratory tests, clinical evaluations, and body composition assessments were performed by specialists.

Findings: The patient presented excessive sweating, hot flashes, dizziness, blurred vision, and seizure. Laboratory tests indicated low glucose levels after convulsions (50, 42.7, and 55 mg/dL), high insulin levels (basal, 638 µIU/mL; 2-hour, >1000 µU/mL), and positivity for anti-insulin antibodies. The patient was diagnosed with insulin autoimmune syndrome. Treatment with azathioprine and nutritional recommendations improved remission.

Implications: SARS-CoV-2 infection or vaccination might induce insulin tolerance failure.

Source: Corona-Meraz FI, Quintero-Castillo BP, Hernández-Palma LA, Machado-Sulbaran AC. Long COVID-19 and Insulin Autoimmune Syndrome: A Case Report. Clin Ther. 2023 Jul 29:S0149-2918(23)00250-3. doi: 10.1016/j.clinthera.2023.06.026. Epub ahead of print. PMID: 37524570. https://pubmed.ncbi.nlm.nih.gov/37524570/

Amino acids, post-translational modifications, nitric oxide, and oxidative stress in serum and urine of long COVID and ex COVID human subjects

Abstract:

In this study, we investigated the status of amino acids, their post-translational modifications (PTM), major nitric oxide (NO) metabolites and of malondialdehyde (MDA) as a biomarker of oxidative stress in serum and urine samples of long COVID (LoCo, n = 124) and ex COVID (ExCo, n = 24) human subjects collected in 2022.

Amino acids and metabolites were measured by gas chromatography–mass spectrometry (GC–MS) methods using stable-isotope labelled analogs as internal standards. There were no differences with respect to circulating and excretory arginine and asymmetric dimethylarginine (ADMA). LoCo participants excreted higher amounts of guanidino acetate than ExCo participants (17.8 ± 10.4 µM/mM vs. 12.6 ± 8.86 µM/mM, P = 0.005). By contrast, LoCo participants excreted lower amounts of the advanced glycation end-product (AGE) NG-carboxyethylarginine (CEA) than ExCo participants did (0.675 ± 0.781 µM/mM vs. 1.16 ± 2.04 µM/mM, P = 0.0326).

The serum concentrations of MDA did not differ between the groups, indicating no elevated oxidative stress in LoCo or ExCo. The serum concentration of nitrite was lower in LoCo compared to ExCo (1.96 ± 0.92 µM vs. 2.56 ± 1.08 µM; AUC, 0.718), suggesting altered NO synthesis in the endothelium. The serum concentration of nitrite correlated inversely with the symptom anxiety (r = − 0.293, P = 0.0003). The creatinine-corrected urinary excretion of Lys and its metabolite L-5-hydroxy-Lys correlated positively with COVID toes (r = 0.306, P = 0.00027) and sore throat (r = 0.302, P = 0.0003).

Our results suggest that amino acid metabolism, PTM and oxidative stress are not severely affected in long COVID. LoCo participants may have a lower circulating NO reservoir than ExCo.

Source: Mikuteit, M., Baskal, S., Klawitter, S. et al. Amino acids, post-translational modifications, nitric oxide, and oxidative stress in serum and urine of long COVID and ex COVID human subjects. Amino Acids (2023). https://doi.org/10.1007/s00726-023-03305-1 https://link.springer.com/article/10.1007/s00726-023-03305-1 (Full text)

A retrospective cohort analysis leveraging augmented intelligence to characterize long COVID in the electronic health record: A precision medicine framework

Abstract:

Physical and psychological symptoms lasting months following an acute COVID-19 infection are now recognized as post-acute sequelae of COVID-19 (PASC). Accurate tools for identifying such patients could enhance screening capabilities for the recruitment for clinical trials, improve the reliability of disease estimates, and allow for more accurate downstream cohort analysis.

In this retrospective cohort study, we analyzed the EHR of hospitalized COVID-19 patients across three healthcare systems to develop a pipeline for better identifying patients with persistent PASC symptoms (dyspnea, fatigue, or joint pain) after their SARS-CoV-2 infection. We implemented distributed representation learning powered by the Machine Learning for modeling Health Outcomes (MLHO) to identify novel EHR features that could suggest PASC symptoms outside of typical diagnosis codes. MLHO applies an entropy-based feature selection and boosting algorithms for representation mining. These improved definitions were then used for estimating PASC among hospitalized patients.

30,422 hospitalized patients were diagnosed with COVID-19 across three healthcare systems between March 13, 2020 and February 28, 2021. The mean age of the population was 62.3 years (SD, 21.0 years) and 15,124 (49.7%) were female.

We implemented the distributed representation learning technique to augment PASC definitions. These definitions were found to have positive predictive values of 0.73, 0.74, and 0.91 for dyspnea, fatigue, and joint pain, respectively.

We estimated that 25 percent (CI 95%: 6-48), 11 percent (CI 95%: 6-15), and 13 percent (CI 95%: 8-17) of hospitalized COVID-19 patients will have dyspnea, fatigue, and joint pain, respectively, 3 months or longer after a COVID-19 diagnosis. We present a validated framework for screening and identifying patients with PASC in the EHR and then use the tool to estimate its prevalence among hospitalized COVID-19 patients.

Source: Strasser ZH, Dagliati A, Shakeri Hossein Abad Z, Klann JG, Wagholikar KB, Mesa R, Visweswaran S, Morris M, Luo Y, Henderson DW, Samayamuthu MJ; Consortium for Clinical Characterization of COVID-19 by EHR (4CE); Omenn GS, Xia Z, Holmes JH, Estiri H, Murphy SN. A retrospective cohort analysis leveraging augmented intelligence to characterize long COVID in the electronic health record: A precision medicine framework. PLOS Digit Health. 2023 Jul 25;2(7):e0000301. doi: 10.1371/journal.pdig.0000301. PMID: 37490472; PMCID: PMC10368277. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10368277/ (Full text)

Myocarditis and Myocardial Injury in Long COVID Syndrome: A Comprehensive Review of the Literature

Abstract:

The repercussions of coronavirus disease 2019 (COVID-19) have been devastating on a global scale. Long COVID, which affects patients for weeks or even months after their initial infection, is not limited to individuals with severe symptoms and can affect people of all ages. The condition can impact various physiological systems, leading to chronic health conditions and long-term disabilities that present  significant challenges for healthcare systems worldwide.

This review explores the link between long COVID and cardiovascular complications such as myocardial injury and myocarditis. It also highlights the prevalence of these complications and identifies risk factors for their development in long COVID patients.

Myocardial injury occurs due to direct cellular damage and T-cell-mediated cytotoxicity resulting in elevated cardiac biomarkers. Diagnostic techniques like electrocardiogram, troponin level testing, and magnetic resonance imaging can help identify myocarditis, but endomyocardial biopsy is considered the goldstandard diagnostic technique.

Guideline-directed medical therapy is recommended for COVID-19 myocarditis patients for better prognosis while being monitored under comprehensive care management approaches. Therefore, it’s critical to develop effective screening techniques specifically for vulnerable populations while conducting further research that addresses the effects of long COVID on society’s physical health.

Source: Paruchuri S, Farwa U, Jabeen S, et al. (July 25, 2023) Myocarditis and Myocardial Injury in Long COVID Syndrome: A Comprehensive Review of the Literature. Cureus 15(7): e42444. DOI 10.7759/cureus.42444 https://assets.cureus.com/uploads/review_article/pdf/162949/20230725-18887-1iha61y.pdf (Full text as PDF file)

First insights from patients presenting with long/post-COVID syndrome in primary care: an exploratory report

Abstract:

Background: Following the global pandemic of coronavirus disease 2019 (COVID-19), the long COVID or post-COVID syndrome refers to a relatively complex novel clinical entity. We conducted this study to assess the primary epidemiological features, main symptoms, and comorbidities probably related to this syndrome in patients referred to our long/post-COVID primary care unit during the initial months of its operation.

Methods and material: This single-center prospective observational study was conducted between April 2022 and December 2022 and enrolled 71 patients (33 men, 38 women) who were examined due to persisting symptoms after recovering from COVID-19 infection, with the mean time of the first visit estimated at 3.12 ± 2.41 months from their acute COVID-19 illness. A thorough medical history, clinical examination, laboratory, and any other tests were performed on all patients when necessary.

Results: The most common symptoms of long/post-COVID reported were fatigue (63.4 %), a persistent cough (45.1 %), stress manifestations (42.3 %), arthralgia or myalgia (33.8 %), tachycardia (32.4 %), depression manifestations (29.6 %), exertional dyspnea (28.2 %), and sleep disorders (25.4 %). Hypertension (in about 40 %) and the presence of five or more symptoms during the acute COVID-19 illness (in approximately 52 %) could be regarded as factors increasing the long/post-COVID appearance. The long/post-COVID syndrome affects even patients not experiencing severe COVID-19 illness. Unvaccinated patients are at higher risk of severe COVID-19 (p =0.014), higher risk of hospitalization (p =0.002), and in higher need of respiratory support with high flow (p =0.017) when compared to vaccinated ones. Hospitalized patients appear to be older than outpatients (59 ± 12.42 vs 52.78 ± 11.48 years of age; p =0.032.

Conclusion: The long/post-COVID syndrome is an established clinical entity, and several clinical features, symptoms, and patient profiles have to be assessed from the initial medical contact in primary care to exclude early any other clinical conditions and offer guided therapeutic strategies to those patients. HIPPOKRATIA 2022, 26 (4):138-142.

Source: Sotiriadou M, Birka S, Oikonomidou E, Κouzoukidou E, Mpogiatzidis P. First insights from patients presenting with long/post-COVID syndrome in primary care: an exploratory report. Hippokratia. 2022 Oct-Dec;26(4):138-142. PMID: 37497527; PMCID: PMC10367945. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10367945/ (Full text)

Host genetic polymorphisms involved in long-term symptoms of COVID-19

Abstract:

Host genetic polymorphisms are recognized as a critical determinant of diversity in clinical symptoms of Coronavirus disease 2019 (COVID-19). Accordingly, this study aimed to determine possible associations between single nucleotide polymorphisms (SNPs) in 37 candidate genetic variants and clinical consequences of COVID-19 – especially long-term symptoms, Long COVID.

A total of 260 COVID-19 patients, divided into mild (n = 239) and severe (n = 21) and further categorized based on the presence of Long COVID (no, n = 211; yes, n = 49), were recruited. Genotyping of selected polymorphisms responsible for viral entry, immune response, and inflammation was performed using MassARRAY system.

Out of 37 SNPs, 9 including leucine zipper transcription factor like-1 (LZTFL1) rs10490770 C allele, LZTFL1 rs11385942 dupA allele, nicotinamide adenine dinucleotide synthetase-1 (NADSYN1) rs12785878 TT genotype, plexin A-4 (PLXNA4) rs1424597 AA genotype, LZTFL1 rs17713054 A allele, interleukin-10 (IL10) rs1800896 TC genotype and C allele, angiotensin converting enzyme-2 (ACE2) rs2285666 T allele, and plasmanylethanolamine desaturase-1 (PEDS1) rs6020298 GG genotype and G allele were significantly associated with an increased risk of developing Long COVID, whereas interleukin-10 receptor subunit beta (IL10RB) rs8178562 GG genotype was significantly associated with a reduced risk of Long COVID. Kaplan-Meier curve displayed that the above gene polymorphisms were significantly associated with cumulative rate of Long COVID occurrence.

Polymorphisms in LZTFL1 rs10490770,  LZTFL1 rs11385942,  LZTFL1 rs17713054,  NADSYN1 rs12785878,  PLXNA4 rs1424597, IL10 rs1800896,  ACE2 rs2285666, PEDS1 rs6020298, and IL10RB rs8178562 appear to be genetic factors involved in development of Long COVID.

Source: Udomsinprasert W, Nontawong N, Saengsiwaritt W, Panthan B, Jiaranai P, Thongchompoo N, Santon S, Runcharoen C, Sensorn I, Jittikoon J, Chaikledkaew U, Chantratita W. Host genetic polymorphisms involved in long-term symptoms of COVID-19. Emerg Microbes Infect. 2023 Dec;12(2):2239952. doi: 10.1080/22221751.2023.2239952. PMID: 37497655; PMCID: PMC10392286. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392286/ (Full text)

Initial COVID-19 Severity and Long-COVID Manifestations: An Observational Analysis

Abstract:

Objective: New-onset or persistent symptoms beyond after 4 weeks from COVID-19 are termed “long-COVID.” Whether the initial severity of COVID-19 has a bearing on the clinicoradiological manifestations of long COVID is an area of interest.

Material and methods: We did an observational analysis of the long-COVID patients after categorizing them based on their course of COVID-19 illness into mild, moderate, and severe groups. The clinical and radiological profile was compared across these groups.

Results: Out of 150 long-COVID patients recruited in the study, about 79% (118), 14% (22), and 7% (10) had a history of mild, moderate, and severe COVID-19, respectively. Fatigue (P = .001), breathlessness (P = .001), tachycardia (P = .002), tachypnea (P < .001), raised blood pressure (P < .001), crepitations (P = .04), hypoxia at rest (P < .001), significant desaturation in 6-minute walk test (P = .27), type 1 respiratory failure (P = .001), and type 2 respiratory failure (P = .001) were found to be significantly higher in the long-COVID patients with a history of severe COVID-19. These patients also had the highest prevalence of abnormal chest X-ray (60%) and honeycombing in computed tomography scan thorax (25%, P = .027).

Conclusion: The course of long COVID bears a relationship with initial COVID-19 severity. Patients with severe COVID-19 are prone to develop more serious long-COVID manifestations.

Source: Goel N, Goyal N, Spalgais S, Mrigpuri P, Varma-Basil M, Khanna M, Nagaraja R, Menon B, Kumar R. Initial COVID-19 Severity and Long-COVID Manifestations: An Observational Analysis. Thorac Res Pract. 2023 Jan;24(1):22-28. doi: 10.5152/ThoracResPract.2023.21307. PMID: 37503595. https://thoracrespract.org/en/initial-covid-19-severity-and-long-covid-manifestations-an-observational-analysis-165530 (Full text as PDF file)

Evidence of a Novel Mitochondrial Signature in Systemic Sclerosis Patients with Chronic Fatigue Syndrome

Abstract:

Symptoms of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are common in rheumatic diseases, but no studies report the frequency of these in early systemic sclerosis. There are no known biomarkers that can distinguish between patients with ME/CFS, although mitochondrial abnormalities are often demonstrated.

We sought to assess the prevalence of ME/CFS in limited cutaneous SSc (lcSSc) patients early in their disease (<5 years from the onset of non-Raynaud’s symptoms) and to determine if alterations in mitochondrial electron transport chain (ETC) transcripts and mitochondrial DNA (mtDNA) integrity could be used to distinguish between fatigued and non-fatigued patients.

All SSc patients met ACR/EULAR classification criteria. ME/CFS-related symptoms were assessed through validated questionnaires, and the expression of ETC transcripts and mtDNA integrity were quantified via qPCR.

SSc patients with ME/CFS could be distinguished from non-fatigued patients through ETC gene analysis; specifically, reduced expression of ND4 and CyB and increased expression of Cox7C. ND4 and CyB expression correlated with indicators of disease severity.

Further prospective and functional studies are needed to determine if this altered signature can be further utilized to better identify ME/CFS in SSc patients, and whether ME/CFS in early SSc disease could predict more severe disease outcomes.

Source: van Eeden C, Redmond D, Mohazab N, Larché MJ, Mason AL, Cohen Tervaert JW, Osman MS. Evidence of a Novel Mitochondrial Signature in Systemic Sclerosis Patients with Chronic Fatigue Syndrome. International Journal of Molecular Sciences. 2023; 24(15):12057. https://doi.org/10.3390/ijms241512057 https://www.mdpi.com/1422-0067/24/15/12057 (Full text)

A population-based investigation into the prevalence of chronic fatigue syndrome in United States military Veterans with chronic pain

Abstract:

Objective: Chronic fatigue syndrome (CFS) is a debilitating illness characterized by persistent fatigue among other symptoms. Pain symptoms are common and included in the diagnostic criteria for CFS but are not required for diagnosis. Despite the association between CFS and pain, few studies have examined CFS in the context of chronic pain (CP) conditions. The current study estimates the period prevalence of comorbid CFS among military Veterans with CP and compares sociodemographic characteristics and CP conditions of Veterans with CP + CFS to those with CP without CFS.

Methods: This study included Veterans Health Administration (VHA) data on 2,261,030 patients with chronic pain in 2018. Sociodemographic characteristics included age, sex, race, ethnicity, and rurality. Descriptive statistics were used to describe the sample and between-group comparisons included independent samples t-tests and chi-square tests of independence. Effect sizes were also examined.

Results: A total of 15,248 (0.67%) of Veterans with CP also had a diagnosis of CFS. Veterans diagnosed with CP + CFS were younger and were more likely to be female, White, non-Hispanic, and rural-dwelling. However, small and weak effect sizes were observed for these differences. The majority of Veterans with CP + CFS had limb/extremity (69.20%) back pain (53.44%), or abdominal/bowel pain (24.11%).

Conclusion: CDC treatment recommendations for CFS include treating pain first, studying CFS in the context of CP is critically important. Veterans diagnosed with CP + CFS appear demographically similar, compared to Veterans with CP without CFS. Examining the utilization of pain-related healthcare services among this group would be a useful next step.

Source: Jenna L. Adamowicz, Emily B. K. Thomas, Brian C. Lund, Mary A. Driscoll, Mark Vander Weg & Katherine Hadlandsmyth (2023) A population-based investigation into the prevalence of chronic fatigue syndrome in United States military Veterans with chronic pain, Fatigue: Biomedicine, Health & Behavior, DOI: 10.1080/21641846.2023.2239977

Genetic Risk Factors for Severe and Fatigue Dominant Long COVID and Commonalities with ME/CFS Identified by Combinatorial Analysis

Abstract:

Background Long COVID is a debilitating chronic condition that has affected over 100 million people globally. It is characterized by a diverse array of symptoms, including fatigue, cognitive dysfunction and respiratory problems. Studies have so far largely failed to identify genetic associations, the mechanisms behind the disease, or any common pathophysiology with other conditions such as ME/CFS that present with similar symptoms.

Methods We used a combinatorial analysis approach to identify combinations of genetic variants significantly associated with the development of long COVID and to examine the biological mechanisms underpinning its various symptoms. We compared two subpopulations of long COVID patients from Sano Genetics’ Long COVID GOLD study cohort, focusing on patients with severe or fatigue dominant phenotypes. We evaluated the genetic signatures previously identified in an ME/CFS population against this long COVID population to understand similarities with other fatigue disorders that may be triggered by a prior viral infection. Finally, we also compared the output of this long COVID analysis against known genetic associations in other chronic diseases, including a range of metabolic and neurological disorders, to understand the overlap of pathophysiological mechanisms.

Results Combinatorial analysis identified 73 genes that were highly associated with at least one of the long COVID populations included in this analysis. Of these, 9 genes have prior associations with acute COVID-19, and 14 were differentially expressed in a transcriptomic analysis of long COVID patients. A pathway enrichment analysis revealed that the biological pathways most significantly associated with the 73 long COVID genes were mainly aligned with neurological and cardiometabolic diseases.

Expanded genotype analysis suggests that specific SNX9 genotypes are a significant contributor to the risk of or protection against severe long COVID infection, but that the gene-disease relationship is context dependent and mediated by interactions with KLF15 and RYR3.

Comparison of the genes uniquely associated with the Severe and Fatigue Dominant long COVID patients revealed significant differences between the pathways enriched in each subgroup. The genes unique to Severe long COVID patients were associated with immune pathways such as myeloid differentiation and macrophage foam cells. Genes unique to the Fatigue Dominant subgroup were enriched in metabolic pathways such as MAPK/JNK signaling. We also identified overlap in the genes associated with Fatigue Dominant long COVID and ME/CFS, including several involved in circadian rhythm regulation and insulin regulation. Overall, 39 SNPs associated in this study with long COVID can be linked to 9 genes identified in a recent combinatorial analysis of ME/CFS patient from UK Biobank.

Among the 73 genes associated with long COVID, 42 are potentially tractable for novel drug discovery approaches, with 13 of these already targeted by drugs in clinical development pipelines. From this analysis for example, we identified TLR4 antagonists as repurposing candidates with potential to protect against long term cognitive impairment pathology caused by SARS-CoV-2. We are currently evaluating the repurposing potential of these drug targets for use in treating long COVID and/or ME/CFS.

Conclusion This study demonstrates the power of combinatorial analytics for stratifying heterogeneous populations in complex diseases that do not have simple monogenic etiologies. These results build upon the genetic findings from combinatorial analyses of severe acute COVID-19 patients and an ME/CFS population and we expect that access to additional independent, larger patient datasets will further improve the disease insights and validate potential treatment options in long COVID.

Source: Krystyna Taylor, Matthew Pearson, Sayoni Das, Jason Sardell, Karolina Chocian, Steve Gardners. Genetic Risk Factors for Severe and Fatigue Dominant Long COVID and Commonalities with ME/CFS Identified by Combinatorial Analysis. medRxiv 2023.07.13.23292611; doi: https://doi.org/10.1101/2023.07.13.23292611 https://www.medrxiv.org/content/10.1101/2023.07.13.23292611v1.full-text (Full text)