CCN3, POSTN, and PTHLH as potential key regulators of genomic integrity and cellular survival in iPSCs.

Reprogramming human somatic cells into a pluripotent state, achieved through the activation of well-defined transcriptional factors known as OSKM factors, offers significant potential for regenerative medicine. While OSKM factors are a robust reprogramming method, efficiency remains a challenge, with only a fraction of cells undergoing successful reprogramming. To address this, we explored genes related to genomic integrity and cellular survival, focusing on iPSCs (A53T-PD1) that displayed enhanced colony stability. Our investigation had revealed three candidate genes CCN3, POSTN, and PTHLH that exhibited differential expression levels and potential roles in iPSC stability. Subsequent analyses identified various protein interactions for these candidate genes. POSTN, significantly upregulated in A53T-PD1 iPSC line, showed interactions with extracellular matrix components and potential involvement in Wnt signaling. CCN3, also highly upregulated, demonstrated interactions with TP53, CDKN1A, and factors related to apoptosis and proliferation. PTHLH, while upregulated, exhibited interactions with CDK2 and genes involved in cell cycle regulation. RT-qPCR validation confirmed elevated CCN3 and PTHLH expression in A53T-PD1 iPSCs, aligning with RNA-seq findings. These genes' roles in preserving pluripotency and cellular stability require further exploration. In conclusion, we identified CCN3, POSTN, and PTHLH as potential contributors to genomic integrity and pluripotency maintenance in iPSCs. Their roles in DNA repair, apoptosis evasion, and signaling pathways could offer valuable insights for enhancing reprogramming efficiency and sustaining pluripotency. Further investigations are essential to unravel the mechanisms underlying their actions.

Retracing our steps: A review on autism research in children, its limitation and impending pharmacological interventions.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by three core impairments: impaired communication, impaired reciprocal social interaction, and restricted, repetitive, and stereotypical behavior patterns. Spectrum refers to the heterogeneity of presentation, severity of symptoms, and medical comorbidities associated with ASD. Among the most common underlying medical conditions are attention-deficit/hyperactivity disorder (ADHD), anxiety, depression, epilepsy, digestive disorders, metabolic disorders, and immune disorders. At present, in the absence of an objective and accurate diagnosis of ASD, such as a blood test, pharmacological management remains a challenge. There are no approved medications to treat the core symptoms of the disorder and behavioral interventions are typically used as first line treatment. Additionally, psychotropic drugs with different mechanisms of action have been approved to reduce associated symptoms and comorbidities, including aripiprazole, risperidone, and haloperidol for irritability and aggression, methylphenidate, atomoxetine, clonidine, and guanfacine for ADHD, and melatonin for sleep disturbances. The purpose of this review is to emphasize that it is imperative to develop objective, personalized diagnostic kits in order to tailor and individualize treatment strategies, as well as to describe the current pharmacological management options available in clinical practice and new prospects that may be helpful in managing ASD's core symptoms.

High-throughput autoantibody screening identifies differentially abundant autoantibodies in autism spectrum disorder.

Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by defects in two core domains, social/communication skills and restricted/repetitive behaviors or interests. There is no approved biomarker for ASD diagnosis, and the current diagnostic method is based on clinical manifestation, which tends to vary vastly between the affected individuals due to the heterogeneous nature of ASD. There is emerging evidence that supports the implication of the immune system in ASD, specifically autoimmunity; however, the role of autoantibodies in ASD children is not yet fully understood. Materials and methods: In this study, we screened serum samples from 93 cases with ASD and 28 healthy controls utilizing high-throughput KoRectly Expressed (KREX) i-Ome protein-array technology. Our goal was to identify autoantibodies with differential expressions in ASD and to gain insights into the biological significance of these autoantibodies in the context of ASD pathogenesis. Result: Our autoantibody expression analysis identified 29 differential autoantibodies in ASD, 4 of which were upregulated and 25 downregulated. Subsequently, gene ontology (GO) and network analysis showed that the proteins of these autoantibodies are expressed in the brain and involved in axonal guidance, chromatin binding, and multiple metabolic pathways. Correlation analysis revealed that these autoantibodies negatively correlate with the age of ASD subjects. Conclusion: This study explored autoantibody reactivity against self-antigens in ASD individuals' serum using a high-throughput assay. The identified autoantibodies were reactive against proteins involved in axonal guidance, synaptic function, amino acid metabolism, fatty acid metabolism, and chromatin binding.

The Potential Role of Thyroid Hormone Therapy in Neural Progenitor Cell Differentiation and Its Impact on Neurodevelopmental Disorders.

Thyroid hormone (T3) plays a vital role in brain development and its dysregulation can impact behavior, nervous system function, and cognitive development. Large case-cohort studies have associated abnormal maternal T3 during early pregnancy to epilepsy, autism, and attention deficit hyperactivity disorder (ADHD) in children. Recent experimental findings have also shown T3's influence on the fate of neural precursor cells and raise the question of its convergence with embryonic neural progenitors. Our objective was to investigate how T3 treatment affects neuronal development and functionality at the cellular level. In vitro experiments using neural precursor cells (NPCs) measured cell growth and numbers after exposure to varying T3 concentrations. Time points included week 0 (W0) representing NPCs treated with 100 nM T3 for 5 days, and differentiated cortical neurons assessed at weeks 3 (W3), 6 (W6), and 8 (W8). Techniques such as single-cell calcium imaging and whole-cell patch clamp were utilized to evaluate neuronal activity and function. IHC staining detected mature neuron markers, and RNA sequencing enabled molecular profiling. W6 and W8 neurons exhibited higher action potential frequencies, with W6 showing increased peak amplitudes and shortened inter-spike intervals by 50%, indicating enhanced activity. Transcriptomic analysis revealed that W6 T3-treated neurons formed a distinct cluster, suggesting accelerated maturation. Comparison with the whole transcriptome further unveiled a correlation between W6 neurons treated with T3 and neuronal regulatory elements associated with autism and ADHD. These findings provide insights into T3's impact on neuronal development and potential mechanisms of T3 dysregulation and neurodevelopmental disorders.

No Association Between Ct Value and COVID-19 Severity and Mortality in Qatar.

Background: The association between the cycle threshold (Ct) which reflects the SARS-CoV-2 viral load and the severity of COVID-19 is still not clear. We investigated the association between Ct values, symptoms and the risk of ICU admission and mortality from COVID-19 in Qatar. Methods: This case-control study used data of hospitalized individuals with confirmed COVID-19 during the period March to September 2020. Cases were defined as individuals with confirmed COVID-19 who were admitted to the intensive care unit (ICU) or died and controls as those who were not admitted to the ICU. The association between Ct value, symptoms, ICU admission and mortality was investigated using Ct value as a categorical variable (below and above 25) in multivariable regression models and adjusted for relevant confounders. Results: A total of 622 participants with median age 53 (IQR: 53-63), of which 69% were males, were included. There were 236 ICU admissions and 111 deaths. When categorized, Ct value (<25 vs ≥25) had no association with the odds of ICU admission (OR 0.85, 95% CI 0.56 to 1.29) or odds of mortality (OR 1.21, 95% CI 0.71 to 2.08). Respiratory (OR 2.95, 95% CI 1.57 to 5.56) and gastrointestinal symptoms (OR 1.99, 95% CI 1.18 to 3.35) were associated with higher odds of ICU admission. Similarly, respiratory (OR 4.96, 95% CI 1.10 to 22.43) and gastrointestinal symptoms (OR 3.17, 95% CI 1.29 to 7.84) were associated with higher odds of mortality. Conclusion: Although RT-PCR Ct has good diagnostic value, its prognostic value appears to be unreliable. Respiratory and gastrointestinal symptoms are associated with COVID-19 criticality and mortality in this setting.

Association of ABO blood types and clinical variables with COVID-19 infection severity in Libya.

Objective: The continuing COVID-19 pandemic is a coronavirus-related health emergency (severe acute respiratory syndrome coronavirus 2). Inadequate efforts are still being made to address the illness situation in Libya, and this must change. To address these issues, we looked into the demography and trend of the disease as well as the potential risk factors for infection. Methods: This study is a retrospective case-control study conducted online among 616 COVID-19 patients. The p0.05 value, odds ratios, and 95% confidence intervals were calculated and analyzed from the drawn data. Results: Males were at high risk of COVID-19 than females (odds ratio = 1.3, 95% confidence interval: 1.042-1.622; p = 0.02). Anosmia and ageusia were more prominent in females. Patients with an "AB" blood group are significantly susceptible to infection. Adults (31 and above) are highly liable to infection. The univariate logistic regression analysis revealed that smoking is a risk factor for those above 60 years (odds ratio = 2.228, 95% confidence interval: 1.145-4.336; p = 0.018). Individuals with chronic diseases such as diabetes and/or hypertension are more prone to COVID-19 (odds ratio = 10.045, 95% confidence interval: 3.078-32.794; p = 0.000 and odds ratio = 11.508, 95% confidence interval: 3.930-33.695; p = 0.000, respectively). Conclusion: This study provided for the first time the demographic data and the trend of COVID-19 infection in Libya, which will assist the stakeholders and governmental bodies in planning protection strategies against the pandemic.

Blood Proteomics Analysis Reveals Potential Biomarkers and Convergent Dysregulated Pathways in Autism Spectrum Disorder: A Pilot Study.

Autism spectrum disorder (ASD) is an umbrella term that encompasses several disabling neurodevelopmental conditions. These conditions are characterized by impaired manifestation in social and communication skills with repetitive and restrictive behaviors or interests. Thus far, there are no approved biomarkers for ASD screening and diagnosis; also, the current diagnosis depends heavily on a physician's assessment and family's awareness of ASD symptoms. Identifying blood proteomic biomarkers and performing deep blood proteome profiling could highlight common underlying dysfunctions between cases of ASD, given its heterogeneous nature, thus laying the foundation for large-scale blood-based biomarker discovery studies. This study measured the expression of 1196 serum proteins using proximity extension assay (PEA) technology. The screened serum samples included ASD cases (n = 91) and healthy controls (n = 30) between 6 and 15 years of age. Our findings revealed 251 differentially expressed proteins between ASD and healthy controls, of which 237 proteins were significantly upregulated and 14 proteins were significantly downregulated. Machine learning analysis identified 15 proteins that could be biomarkers for ASD with an area under the curve (AUC) = 0.876 using support vector machine (SVM). Gene Ontology (GO) analysis of the top differentially expressed proteins (TopDE) and weighted gene co-expression analysis (WGCNA) revealed dysregulation of SNARE vesicular transport and ErbB pathways in ASD cases. Furthermore, correlation analysis showed that proteins from those pathways correlate with ASD severity. Further validation and verification of the identified biomarkers and pathways are warranted.

Combined Noncoding RNA-mRNA Regulomics Signature in Reprogramming and Pluripotency in iPSCs.

Somatic cells are reprogrammed with reprogramming factors to generate induced pluripotent stem cells (iPSCs), offering a promising future for disease modeling and treatment by overcoming the limitations of embryonic stem cells. However, this process remains inefficient since only a small percentage of transfected cells can undergo full reprogramming. Introducing miRNAs, such as miR-294 and miR302/3667, with reprogramming factors, has shown to increase iPSC colony formation. Previously, we identified five transcription factors, GBX2, NANOGP8, SP8, PEG3, and ZIC1, which may boost iPSC generation. In this study, we performed quantitative miRNAome and small RNA-seq sequencing and applied our previously identified transcriptome to identify the potential miRNA-mRNA regulomics and regulatory network of other ncRNAs. From each fibroblast (N = 4), three iPSC clones were examined (N = 12). iPSCs and original fibroblasts expressed miRNA clusters differently and miRNA clusters were compared to mRNA hits. Moreover, miRNA, piRNA, and snoRNAs expression profiles in iPSCs and original fibroblasts were assessed to identify the potential role of ncRNAs in enhancing iPSC generation, pluripotency, and differentiation. Decreased levels of let-7a-5p showed an increase of SP8 as described previously. Remarkably, the targets of identifier miRNAs were grouped into pluripotency canonical pathways, on stemness, cellular development, growth and proliferation, cellular assembly, and organization of iPSCs.

Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review.

Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and symptoms that appear in early childhood. ASD is also associated with communication deficits and repetitive behavior in affected individuals. Various ASD detection methods have been developed, including neuroimaging modalities and psychological tests. Among these methods, magnetic resonance imaging (MRI) imaging modalities are of paramount importance to physicians. Clinicians rely on MRI modalities to diagnose ASD accurately. The MRI modalities are non-invasive methods that include functional (fMRI) and structural (sMRI) neuroimaging methods. However, diagnosing ASD with fMRI and sMRI for specialists is often laborious and time-consuming; therefore, several computer-aided design systems (CADS) based on artificial intelligence (AI) have been developed to assist specialist physicians. Conventional machine learning (ML) and deep learning (DL) are the most popular schemes of AI used for diagnosing ASD. This study aims to review the automated detection of ASD using AI. We review several CADS that have been developed using ML techniques for the automated diagnosis of ASD using MRI modalities. There has been very limited work on the use of DL techniques to develop automated diagnostic models for ASD. A summary of the studies developed using DL is provided in the Supplementary Appendix. Then, the challenges encountered during the automated diagnosis of ASD using MRI and AI techniques are described in detail. Additionally, a graphical comparison of studies using ML and DL to diagnose ASD automatically is discussed. We suggest future approaches to detecting ASDs using AI techniques and MRI neuroimaging.

Single Extracellular Vesicle Analysis Using Flow Cytometry for Neurological Disorder Biomarkers.

Extracellular vesicles (EVs) are membrane vesicles released from cells to the extracellular space, involved in cell-to-cell communication by the horizontal transfer of biomolecules such as proteins and RNA. Because EVs can cross the blood-brain barrier (BBB), circulating through the bloodstream and reflecting the cell of origin in terms of disease prognosis and severity, the contents of plasma EVs provide non-invasive biomarkers for neurological disorders. However, neuronal EV markers in blood plasma remain unclear. EVs are very heterogeneous in size and contents, thus bulk analyses of heterogeneous plasma EVs using Western blot and ELISA have limited utility. In this study, using flow cytometry to analyze individual neuronal EVs, we show that our plasma EVs isolated by size exclusion chromatography are mainly CD63-positive exosomes of endosomal origin. As a neuronal EV marker, neural cell adhesion molecule (NCAM) is highly enriched in EVs released from induced pluripotent stem cells (iPSCs)-derived cortical neurons and brain organoids. We identified the subpopulations of plasma EVs that contain NCAM using flow cytometry-based individual EV analysis. Our results suggest that plasma NCAM-positive neuronal EVs can be used to discover biomarkers for neurological disorders.

Hyperosmotic Stress Induces a Specific Pattern for Stress Granule Formation in Human-Induced Pluripotent Stem Cells.

Stress granules (SGs) are assemblies of selective messenger RNAs (mRNAs), translation factors, and RNA-binding proteins in small untranslated messenger ribonucleoprotein (mRNP) complexes in the cytoplasm. Evidence indicates that different types of cells have shown different mechanisms to respond to stress and the formation of SGs. In the present work, we investigated how human-induced pluripotent stem cells (hiPSCs/IMR90-1) overcome hyperosmotic stress compared to a cell line that does not harbor pluripotent characteristics (SH-SY5Y cell line). Gradient concentrations of NaCl showed a different pattern of SG formation between hiPSCs/IMR90-1 and the nonpluripotent cell line SH-SY5Y. Other pluripotent stem cell lines (hiPSCs/CRTD5 and hESCs/H9 (human embryonic stem cell line)) as well as nonpluripotent cell lines (BHK-21 and MCF-7) were used to confirm this phenomenon. Moreover, the formation of hyperosmotic SGs in hiPSCs/IMR90-1 was independent of eIF2α phosphorylation and was associated with low apoptosis levels. In addition, a comprehensive proteomics analysis was performed to identify proteins involved in regulating this specific pattern of hyperosmotic SG formation in hiPSCs/IMR90-1. We found possible implications of microtubule organization on the response to hyperosmotic stress in hiPSCs/IMR90-1. We have also unveiled a reduced expression of tubulin that may protect cells against hyperosmolarity stress while inhibiting SG formation without affecting stem cell self-renewal and pluripotency. Our observations may provide a possible cellular mechanism to better understand SG dynamics in pluripotent stem cells.

The Potential Role of COVID-19 in the Pathogenesis of Multiple Sclerosis-A Preliminary Report.

Coronavirus 2019 (COVID-19) is an infectious respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that mainly affects the lungs. COVID-19 symptoms include the presence of fevers, dry coughs, fatigue, sore throat, headaches, diarrhea, and a loss of taste or smell. However, it is understood that SARS-CoV-2 is neurotoxic and neuro-invasive and could enter the central nervous system (CNS) via the hematogenous route or via the peripheral nerve route and causes encephalitis, encephalopathy, and acute disseminated encephalomyelitis (ADEM) in COVID-19 patients. This review discusses the possibility of SARS-CoV-2-mediated Multiple Sclerosis (MS) development in the future, comparable to the surge in Parkinson's disease cases following the Spanish Flu in 1918. Moreover, the SARS-CoV-2 infection is associated with a cytokine storm. This review highlights the impact of these modulated cytokines on glial cell interactions within the CNS and their role in potentially prompting MS development as a secondary disease by SARS-CoV-2. SARS-CoV-2 is neurotropic and could interfere with various functions of neurons leading to MS development. The influence of neuroinflammation, microglia phagocytotic capabilities, as well as hypoxia-mediated mitochondrial dysfunction and neurodegeneration, are mechanisms that may ultimately trigger MS development.

Human induced pluripotent stem cell line (QBRIi013-A) derivation from a 6-year-old female diagnosed with Autism spectrum disorder (ASD) and intellectual disability (ID).

Autism spectrum disorder (ASD) is a childhood-onset neurodevelopmental disorder characterized by social interaction, behavior, and communication challenges. Here, we generated an induced pluripotent stem cell (iPSC) line, QBRIi013-A using a non-integrating Sendai virus from a 6-year-old female diagnosed with ASD and intellectual disability. The QBRIi013-A cell line was fully characterized and exhibited a pluripotency capacity and trilineage differentiation potential. Furthermore, it showed normal karyotype and genetic identity to the patient's PBMCs. Consequently, this iPSC line provides a valuable cell model in understanding the molecular mechanism underlying the complexities of ASD pathogenesis.

Circulating Non-Coding RNAs as a Signature of Autism Spectrum Disorder Symptomatology.

Autism spectrum disorder (ASD) is a multifaced neurodevelopmental disorder that becomes apparent during early childhood development. The complexity of ASD makes clinically diagnosing the condition difficult. Consequently, by identifying the biomarkers associated with ASD severity and combining them with clinical diagnosis, one may better factionalize within the spectrum and devise more targeted therapeutic strategies. Currently, there are no reliable biomarkers that can be used for precise ASD diagnosis. Consequently, our pilot experimental cohort was subdivided into three groups: healthy controls, individuals those that express severe symptoms of ASD, and individuals that exhibit mild symptoms of ASD. Using next-generation sequencing, we were able to identify several circulating non-coding RNAs (cir-ncRNAs) in plasma. To the best of our knowledge, this study is the first to show that miRNAs, piRNAs, snoRNAs, Y-RNAs, tRNAs, and lncRNAs are stably expressed in plasma. Our data identify cir-ncRNAs that are specific to ASD. Furthermore, several of the identified cir-ncRNAs were explicitly associated with either the severe or mild groups. Hence, our findings suggest that cir-ncRNAs have the potential to be utilized as objective diagnostic biomarkers and clinical targets.

Ingestion of probiotic (Lactobacillus helveticus and Bifidobacterium longum) alters intestinal microbial structure and behavioral expression following social defeat stress.

Social stress exacerbates anxious and depressive behaviors in humans. Similarly, anxiety- and depressive-like behaviors are triggered by social stress in a variety of non-human animals. Here, we tested whether oral administration of the putative anxiolytic probiotic strains Lactobacillus helveticus R0052 and Bifidobacterium longum R0175 reduces the striking increase in anxiety-like behavior and changes in gut microbiota observed following social defeat stress in Syrian hamsters. We administered the probiotic at two different doses for 21 days, and 16S rRNA gene amplicon sequencing revealed a shift in microbial structure following probiotic administration at both doses, independently of stress. Probiotic administration at either dose increased anti-inflammatory cytokines IL-4, IL-5, and IL-10 compared to placebo. Surprisingly, probiotic administration at the low dose, equivalent to the one used in humans, significantly increased social avoidance and decreased social interaction. This behavioral change was associated with a reduction in microbial richness in this group. Together, these results demonstrate that probiotic administration alters gut microbial composition and may promote an anti-inflammatory profile but that these changes may not promote reductions in behavioral responses to social stress.

Paving the Way toward Personalized Medicine: Current Advances and Challenges in Multi-OMICS Approach in Autism Spectrum Disorder for Biomarkers Discovery and Patient Stratification.

Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder characterized by impairments in two main areas: social/communication skills and repetitive behavioral patterns. The prevalence of ASD has increased in the past two decades, however, it is not known whether the evident rise in ASD prevalence is due to changes in diagnostic criteria or an actual increase in ASD cases. Due to the complexity and heterogeneity of ASD, symptoms vary in severity and may be accompanied by comorbidities such as epilepsy, attention deficit hyperactivity disorder (ADHD), and gastrointestinal (GI) disorders. Identifying biomarkers of ASD is not only crucial to understanding the biological characteristics of the disorder, but also as a detection tool for its early screening. Hence, this review gives an insight into the main areas of ASD biomarker research that show promising findings. Finally, it covers success stories that highlight the importance of precision medicine and the current challenges in ASD biomarker discovery studies.

Identification of potential transcription factors that enhance human iPSC generation.

Although many factors have been identified and used to enhance the iPSC reprogramming process, its efficiency remains quite low. In addition, reprogramming efficacy has been evidenced to be affected by disease mutations that are present in patient samples. In this study, using RNA-seq platform we have identified and validated the differential gene expression of five transcription factors (TFs) (GBX2, NANOGP8, SP8, PEG3, and ZIC1) that were associated with a remarkable increase in the number of iPSC colonies generated from a patient with Parkinson's disease. We have applied different bioinformatics tools (Gene ontology, protein-protein interaction, and signaling pathways analyses) to investigate the possible roles of these TFs in pluripotency and developmental process. Interestingly, GBX2, NANOGP8, SP8, PEG3, and ZIC1 were found to play a role in maintaining pluripotency, regulating self-renewal stages, and interacting with other factors that are involved in pluripotency regulation including OCT4, SOX2, NANOG, and KLF4. Therefore, the TFs identified in this study could be used as additional transcription factors that enhance reprogramming efficiency to boost iPSC generation technology.

COVID-19-Induced Hepatic Injury: A Systematic Review and Meta-Analysis.

Background The current pandemic of the novel coronavirus disease (COVID-19) is a global health challenge. Pulmonary dysfunction is the main outcome of COVID-19 infection. In critically ill patients, however, liver complications have also been reported. Thus, we conducted a systematic review and meta-analysis to draw generalized conclusions regarding impaired liver biochemistry and its potential relationship with COVID-19 disease severity. Materials and Methods We searched the PubMed, Scopus, and Web of Science databases for all the related literature published up to June 20, 2020. The data were analyzed using R statistical software. A random-effects model was employed for pooling the data. The risk of bias and quality of included studies was assessed using the modified Newcastle-Ottawa Scale (NOS) for cohort studies. Results The present meta-analysis comprises 10 retrospective and two prospective studies (6,976 COVID-19 patients). The serum analysis revealed significantly higher levels of alanine aminotransferases and aspartate aminotransferases and significantly lower albumin levels. Moreover, insignificant increases in serum levels of total bilirubin were observed. Upon subgroup analysis of six studies (severe cases, n=131; non-severe cases, n=334) stratified on the basis of disease severity, we found that these abnormalities were relatively higher in severe cases of COVID-19 (albumin [weighted mean difference (WMD), 34.03 g/L; 95% CI, 27.42 to 40.63; p<0.0001; I2=96.83%); alanine transaminase (ALT) [WMD, 31.66 U/L; 95% CI, 25.07 to 38.25; p<0.0001; I2=55.64%]; aspartate aminotransferase (AST) [WMD, 41.79 U/L; 95% CI, 32.85 to 50.72; p<0.0001; I2=51.43%]; total bilirubin [WMD, 9.97 µmol/L; 95% CI, 8.46 to 11.48; p<0.0001; I2=98%]) than in non-severe cases. Conclusion Deranged liver enzymes serve as prognostic factors to assess the severity of COVID-19. Liver markers should, therefore, be observed and monitored continuously.