Tag: long covid genetics

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)

Multisystem inflammatory syndrome in children (MIS-C): Implications for long COVID

Abstract:

The COVID-19 pandemic caused by the coronavirus 2 of the severe acute respiratory syndrome (SARS-CoV-2) has significantly affected people around the world, leading to substantial morbidity and mortality. Although the pandemic has affected people of all ages, there is increasing evidence that children are less susceptible to SARS-CoV-2 infection and are more likely to experience milder symptoms than adults. However, children with COVID-19 can still develop serious complications, such as multisystem inflammatory syndrome in children (MIS-C).

This narrative review of the literature provides an overview of the epidemiology and immune pathology of SARS-CoV-2 infection and MIS-C in children. The review also examines the genetics of COVID-19 and MIS-C in children, including the genetic factors that can influence the susceptibility and severity of the diseases and their implications for personalized medicine and vaccination strategies.

By examining current evidence and insights from the literature, this review aims to contribute to the development of effective prevention and treatment strategies for COVID-19, MIS-C, and long COVID syndromes in children.

Source: Constantin T, Pék T, Horváth Z, Garan D, Szabó AJ. Multisystem inflammatory syndrome in children (MIS-C): Implications for long COVID. Inflammopharmacology. 2023 Jul 17. doi: 10.1007/s10787-023-01272-3. Epub ahead of print. PMID: 37460909. https://link.springer.com/article/10.1007/s10787-023-01272-3 (Full text)

Genome-wide Association Study of Long COVID

Abstract:

Infections can lead to persistent or long-term symptoms and diseases such as shingles after varicella zoster, cancers after human papillomavirus, or rheumatic fever after streptococcal infections(1,2). Similarly, infection by SARS-CoV-2 can result in Long COVID, a condition characterized by symptoms of fatigue and pulmonary and cognitive dysfunction(3-5). The biological mechanisms that contribute to the development of Long COVID remain to be clarified.

We leveraged the COVID-19 Host Genetics Initiative(6,7) to perform a genome-wide association study for Long COVID including up to 6,450 Long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We identified the first genome-wide significant association for Long COVID at the FOXP4 locus. FOXP4 has been previously associated with COVID-19 severity(6), lung function(8), and cancers(9), suggesting a broader role for lung function in the pathophysiology of Long COVID.

While we identify COVID-19 severity as a causal risk factor for Long COVID, the impact of the genetic risk factor located in the FOXP4 locus could not be solely explained by its association to severe COVID-19. Our findings further support the role of pulmonary dysfunction and COVID-19 severity in the development of Long COVID.

Source: Vilma Lammi, Tomoko Nakanishi, Samuel E. Jones, Shea J. Andrews, Juha Karjalainen, Beatriz Cortés, Heath E. O’Brien, Brian E. Fulton-Howard, Hele H. Haapaniemi, Axel Schmidt, Ruth E. Mitchell, Abdou Mousas, Massimo Mangino, Alicia Huerta-Chagoya, Nasa Sinnott-Armstrong, Elizabeth T. Cirulli, Marc Vaudel, Alex S.F. Kwong, Amit K. Maiti, Minttu Marttila, Chiara Batini, Francesca Minnai, Anna R. Dearman, C.A. Robert Warmerdam, Celia B. Sequeros, Thomas W. Winkler, Daniel M. Jordan, Lindsay Guare, Ekaterina Vergasova, Eirini Marouli, Pasquale Striano, Ummu Afeera Zainulabid, Ashutosh Kumar, Hajar Fauzan Ahmad, Ryuya Edahiro, Shuhei Azekawa, Long COVID Host Genetics Initiative, FinnGen, DBDS Genomic Consortium, GEN-COVID Multicenter Study, Joseph J. Grzymski, Makoto Ishii, Yukinori Okada, Noam D. Beckmann, Meena Kumari, Ralf Wagner, Iris M. Heid, Catherine John, Patrick J. Short, Per Magnus, Karina Banasik, Frank Geller, Lude H. Franke, Alexander Rakitko, Emma L. Duncan, Alessandra Renieri, Konstantinos K. Tsilidis, Rafael de Cid, Ahmadreza Niavarani, Teresa Tusié-Luna, Shefali S. Verma, George Davey Smith, Nicholas J. Timpson, Mark J. Daly, Andrea Ganna, Eva C. Schulte, J. Brent Richards, Kerstin U. Ludwig, Michael Hultström, Hugo Zeberg, Hanna M. Ollila. Genome-wide Association Study of Long COVID. medRxiv 2023.06.29.23292056; doi: https://doi.org/10.1101/2023.06.29.23292056  https://www.medrxiv.org/content/10.1101/2023.06.29.23292056v1.full-text (Full text)

Physiological underpinnings of long COVID: what have we learned?

In a review, Batta et al 2 , addressed the cardiovascular symptoms in COVID-19 patients with a focus on vascular dysfunction, arrhythmias, myocardial ischemia, and discussed the most updated recommendations for the treatment of COVID-19. We previously reported the presence of almost all the receptors of SARS-CoV-2 on cardiomyocytes which makes the heart a favorable target for this virus 3 . Batta et al 2 indicated that the vascular endothelial dysfunction is involved in the pathogenesis of SARS-CoV-2 and hence the activation of pro-inflammatory cytokines leading to increased vascular permeability and thrombosis in many organs.

Tachycardia was the most common cardiac presentation associated with SARS-CoV-2 infection, along with arrhythmias and conduction blocks, myocardial ischemia and injury, and hypertension. Interestingly, the authors reported that the elevated ACE-2 expression on endothelial cells of COVID -19 patients’ lungs indicates an elevated pro-hypertensive angiotensin II level leading to vasoconstriction and aldosterone-driven hypervolemia. Thus, the use of renin-angiotensin-aldosterone inhibitors in hypertension treatment of patients infected with SARS-CoV-2 was cautioned to avoid exacerbated cardiovascular clinical outcome.

An article from Gonzalez-Gonzalez et al. 4 reviewed the application of Virchow’s Triad in detail for the risk of developing stroke and related intravascular thrombotic diseases in the context of COVID-19 infection. The authors discussed each part of Virchow’s triad in detail, such as hypercoagulable state, vascular damage, and intravascular stasis of blood. They looked into literature on the effects of COVID-19 infection for the formation of intravascular and intracardiac clots (leading to stroke), formation of cardiac sequelae and autopsy studies reporting elevated markers in ventricular myocardium. The authors reviewed the risk factor for stroke development, differences between ischemic vs haemorrhagic stroke and frequent complications of COVID-19 patients such as pulmonary embolism. The authors also discussed the current treatment plans and recommended some differential treatment approaches for COVID-19 infection patients concerning known mechanisms of Virchow’s triad. Finally, the authors discussed the outcomes and long-term consequences of COVID-19 infection and the cardiovascular effects of COVID-19 vaccines.

The work from A. Mujalli and co-workers 5 investigated genetic pathways in patients with severe COVID-19 and comorbidities, by means of genome-wide transcriptomic datasets publicly available within the first year of the pandemic. Differential gene expression (DGE), gene ontology (GO), pathway enrichment, functional similarity, phenotypic analysis and drug target identification studies were conducted using a cohort of 120 COVID-19 patients, 281 patients with chronic comorbidities (153 CVD, 64 atherosclerosis, 33 diabetes, and 31 obesity), and 252 patients with different infectious diseases (145 respiratory syncytial virus, 95 influenza, and 12 MERS). In total, 29 genes were identified to contributing to the clinical severity of COVID-19 infection in patients with comorbidities. Remarkably, identified genes were found to be involved in immune cell homeostasis during innate immunity, mostly in monocyte and macrophage function. In addition, results from drug target identification studies show a mismatch between the currently used drugs in COVID-19 therapy and predicted drugs against identified genes.

Furtheremore, in this issue of the Journal, Chan et al 6 examined the association of COVID-19 with heart rate (HR) and blood pressure (BP) variability during exercise in a cohort of 18 patients with prior COVID-19 infection (equally split between symptomatic and asymptomatic), and a cohort of 9 controls who were never infected with COVID-19. Using a rigorous experimental design, the investigators measured HR and BP at regular intervals before, during, and after submaximal exercise, and quantified HR and BP variability on time and frequency domains. Baseline HR and BP were not significantly different between groups (symptomatic vs. asymptomatic vs. controls), nor were they different after completing a bout of submaximal exercise at a comparable workload. However, HR and BP variability was blunted only in individuals with prior symptomatic COVID-19 infection, but not in controls or those with a prior asymptomatic infection, suggesting an underlying degree of autonomic nervous system dysfunction in affected individuals.

The authors are to be lauded for their elegant and clinically relevant work, despite the obvious limitation of small sample size, since it provides much needed insight into COVID-19-induced abnormalities in cardiac physiology. The current findings provide a potential explanation for exercise intolerance, a frequently reported long-term symptom among survivors of COVID-19, since blunting of HR and BP variability are markers of impaired parasympathetic nervous system and poor cardiovascular health.In conclusion, the COVID-19 pandemic affected millions around the globe before it started abating with the advent of the emergent vaccines that were approved for use on emergency basis.

The WHO declared the end of the pandemic after three years of its surge. While millions succumbed to this deadly respiratory infection, survivors from this illness, particularity those who were severely sick, are reporting cardiac and nervous abnormalities. We hope that this series provides a new perspectives on the manifestations of COVID-19 in the heart, the brain, and the vasculature with the hope to guide therapeutic interventions for patients suffering from long term sequelae of SARS-CoV-2 infection.

Source: Moni Nader1, Georges E. Haddad, Jacobo Elies, Sriharsha Kantamneni and Firas Albadarin. Physiological underpinnings of long COVID: what have we learned? Front. Physiol. Sec. Clinical and Translational Physiology. Volume 14 – 2023 | doi: 10.3389/fphys.2023.122455 https://www.frontiersin.org/articles/10.3389/fphys.2023.1224550/full (Full text)

Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder

Abstract:

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused an ongoing pandemic of a pathology termed Coronavirus Disease 19 (COVID-19). Several studies reported that both COVID-19 and RTEL1 variants are associated with shorter telomere length, but a direct association between the two is not generally acknowledged. Here we demonstrate that up to 8.6% of severe COVID-19 patients bear RTEL1 ultra-rare variants, and show how this subgroup can be recognized.

Methods: A cohort of 2246 SARS-CoV-2-positive subjects, collected within the GEN-COVID Multicenter study, was used in this work. Whole exome sequencing analysis was performed using the NovaSeq6000 System, and machine learning methods were used for candidate gene selection of severity. A nested study, comparing severely affected patients bearing or not variants in the selected gene, was used for the characterisation of specific clinical features connected to variants in both acute and post-acute phases.

Results: Our GEN-COVID cohort revealed a total of 151 patients carrying at least one RTEL1 ultra-rare variant, which was selected as a specific acute severity feature. From a clinical point of view, these patients showed higher liver function indices, as well as increased CRP and inflammatory markers, such as IL-6. Moreover, compared to control subjects, they present autoimmune disorders more frequently. Finally, their decreased diffusion lung capacity for carbon monoxide after six months of COVID-19 suggests that RTEL1 variants can contribute to the development of SARS-CoV-2-elicited lung fibrosis.

Conclusion: RTEL1 ultra-rare variants can be considered as a predictive marker of COVID-19 severity, as well as a marker of pathological evolution in pulmonary fibrosis in the post-COVID phase. This notion can be used for a rapid screening in hospitalized infected people, for vaccine prioritization, and appropriate follow-up assessment for subjects at risk.

Trial Registration NCT04549831 (www.clinicaltrial.org)

Source: Bergantini, L., Baldassarri, M., d’Alessandro, M. et al. Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder. Respir Res 24, 158 (2023). https://doi.org/10.1186/s12931-023-02458-7 https://respiratory-research.biomedcentral.com/articles/10.1186/s12931-023-02458-7 (Full text)

Long COVID: a review and proposed visualization of the complexity of long COVID

Abstract:

Post-Acute Sequelae of Severe Acute Respiratory Syndrome Coronavirus – 2 (SARS-CoV-2) infection, or Long COVID, is a prevailing second pandemic with nearly 100 million affected individuals globally and counting. We propose a visual description of the complexity of Long COVID and its pathogenesis that can be used by researchers, clinicians, and public health officials to guide the global effort toward an improved understanding of Long COVID and the eventual mechanism-based provision of care to afflicted patients. The proposed visualization or framework for Long COVID should be an evidence-based, dynamic, modular, and systems-level approach to the condition.

Furthermore, with further research such a framework could establish the strength of the relationships between pre-existing conditions (or risk factors), biological mechanisms, and resulting clinical phenotypes and outcomes of Long COVID. Notwithstanding the significant contribution that disparities in access to care and social determinants of health have on outcomes and disease course of long COVID, our model focuses primarily on biological mechanisms. Accordingly, the proposed visualization sets out to guide scientific, clinical, and public health efforts to better understand and abrogate the health burden imposed by long COVID.

Source: Perumal R, Shunmugam L, Naidoo K, Abdool Karim SS, Wilkins D, Garzino-Demo A, Brechot C, Parthasarathy S, Vahlne A, Nikolich JŽ. Long COVID: a review and proposed visualization of the complexity of long COVID. Front Immunol. 2023 Apr 20;14:1117464. doi: 10.3389/fimmu.2023.1117464. PMID: 37153597; PMCID: PMC10157068. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10157068/ (Full text)

Thrombophilia and Immune-Related Genetic Markers in Long COVID

Abstract:

Aiming to evaluate the role of ten functional polymorphisms in long COVID, involved in major inflammatory, immune response and thrombophilia pathways, a cross-sectional sample composed of 199 long COVID (LC) patients and a cohort composed of 79 COVID-19 patients whose follow-up by over six months did not reveal any evidence of long COVID (NLC) were investigated to detect genetic susceptibility to long COVID.
Ten functional polymorphisms located in thrombophilia-related and immune response genes were genotyped by real time PCR. In terms of clinical outcomes, LC patients presented higher prevalence of heart disease as preexistent comorbidity. In general, the proportions of symptoms in acute phase of the disease were higher among LC patients.
The genotype AA of the interferon gamma (IFNG) gene was observed in higher frequency among LC patients (60%; p = 0.033). Moreover, the genotype CC of the methylenetetrahydrofolate reductase (MTHFR) gene was also more frequent among LC patients (49%; p = 0.045). Additionally, the frequencies of LC symptoms were higher among carriers of IFNG genotypes AA than among non-AA genotypes (Z = 5.08; p < 0.0001).
Two polymorphisms were associated with LC in both inflammatory and thrombophilia pathways, thus reinforcing their role in LC. The higher frequencies of acute phase symptoms among LC and higher frequency of underlying comorbidities might suggest that acute disease severity and the triggering of preexisting condition may play a role in LC development.
Source: da Silva R, de Sarges KML, Cantanhede MHD, da Costa FP, dos Santos EF, Rodrigues FBB, de Nazaré do Socorro de Almeida Viana M, de Meira Leite M, da Silva ALS, de Brito MTM, da Silva Torres MK, Queiroz MAF, Vallinoto IMVC, Henriques DF, dos Santos CP, Viana GMR, Quaresma JAS, Falcão LFM, Vallinoto ACR, dos Santos EJM. Thrombophilia and Immune-Related Genetic Markers in Long COVID. Viruses. 2023; 15(4):885. https://doi.org/10.3390/v15040885 https://www.mdpi.com/1999-4915/15/4/885 (Full text)

Long-COVID Inducement Mechanism Based on the Path Module Correlation Coefficient

Abstract:

As the number of COVID-19 cases increases, the long-COVID symptoms become the focus of clinical attention. Based on the statistical analysis of long-COVID symptoms in European and Chinese populations, this study proposes the path module correlation coefficient, which can estimate the correlation between two modules in a network, to evaluate the correlation between SARS-CoV-2 infection and long-COVID symptoms, providing a theoretical support for analyzing the frequency of long-COVID symptoms in European and Chinese populations.
The path module correlation coefficients between specific COVID-19-related genes in the European and Chinese populations and genes that may induce long-COVID symptoms were calculated. The results showed that the path module correlation coefficients were completely consistent with the frequency of long-COVID symptoms in the Chinese population, but slightly different in the European population. Furthermore, the cathepsin C (CTSC) gene was found to be a potential COVID-19-related gene by a path module correlation coefficient correction rate.
Our study can help to explore other long-COVID symptoms that have not yet been discovered and provide a new perspective to research this syndrome. Meanwhile, the path module correlation coefficient correction rate can help to find more species-specific genes related to COVID-19 in the future.
Source: Liu Z, Yin Z, Mi Z, Guo B. Long-COVID Inducement Mechanism Based on the Path Module Correlation Coefficient. Mathematics. 2023; 11(6):1368. https://doi.org/10.3390/math11061368 (Full text)

Identification of the pathogenic relationship between Long COVID and Alzheimer’s disease by bioinformatics methods

Abstract:

Background: The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused an unprecedented global health crisis. Although many Corona Virus Disease 2019 (COVID-19) patients have recovered, the long-term consequences of SARS-CoV-2 infection are unclear. Several independent epidemiological surveys and clinical studies have found that SARS-CoV-2 infection and Long COVID are closely related to Alzheimer’s disease (AD). This could lead to long-term medical challenges and social burdens following this health crisis. However, the mechanism between Long COVID and AD is unknown.

Methods: Genes associated with Long COVID were collected from the database. Two sets of AD-related clinical sample datasets were collected in the Gene Expression Omnibus (GEO) database by limiting screening conditions. After identifying the differentially expressed genes (DEGs) of AD, the significant overlapping genes of AD and Long COVID were obtained by taking the intersection. Then, four kinds of analyses were performed, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis, protein-protein interaction (PPI) analysis, identification of hub genes, hub gene verification and transcription factors (TFs) prediction.

Results: A total of 197 common genes were selected for subsequent analysis. GO and KEGG enrichment analysis showed that these genes were mainly enriched in multiple neurodegenerative disease related pathways. In addition, 20 important hub genes were identified using cytoHubba. At the same time, these hub genes were verified in another data set, where 19 hub gene expressions were significantly different in the two diseases and 6 hub genes were significantly different in AD patients of different genders. Finally, we collected 9 TFs that may regulate the expression of these hub genes in the Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TRUSST) database and verified them in the current data set.

Conclusion: This work reveals the common pathways and hub genes of AD and Long COVID, providing new ideas for
the pathogenic relationship between these two diseases and further mechanism research.

Source:

Bioinformatics and systems biology approach to identify the pathogenetic link of Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Background: The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global crisis. Although many people recover from COVID-19 infection, they are likely to develop persistent symptoms similar to those of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) after discharge. Those constellations of symptoms persist for months after infection, called Long COVID, which may lead to considerable financial burden and healthcare challenges. However, the mechanisms underlying Long COVID and ME/CFS remain unclear.

Methods: We collected the genes associated with Long COVID and ME/CFS in databases by restricted screening conditions and clinical sample datasets with limited filters. The common genes for Long COVID and ME/CFS were finally obtained by taking the intersection. We performed several advanced bioinformatics analyses based on common genes, including gene ontology and pathway enrichment analyses, protein–protein interaction (PPI) analysis, transcription factor (TF)–gene interaction network analysis, transcription factor–miRNA co-regulatory network analysis, and candidate drug analysis prediction.

Results: We found nine common genes between Long COVID and ME/CFS and gained a piece of detailed information on their biological functions and signaling pathways through enrichment analysis. Five hub proteins (IL-6, IL-1B, CD8A, TP53, and CXCL8) were collected by the PPI network. The TF–gene and TF–miRNA coregulatory networks were demonstrated by NetworkAnalyst. In the end, 10 potential chemical compounds were predicted.

Conclusion: This study revealed common gene interaction networks of Long COVID and ME/CFS and predicted potential therapeutic drugs for clinical practice. Our findings help to identify the potential biological mechanism between Long COVID and ME/CFS. However, more laboratory and multicenter evidence is required to explore greater mechanistic insight before clinical application in the future.

Source: Lv Y, Zhang T, Cai J, Huang C, Zhan S and Liu J. Bioinformatics and systems biology approach to identify the pathogenetic link of Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Front. Immunol. 13:952987  https://www.frontiersin.org/articles/10.3389/fimmu.2022.952987/full (Full text)