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3. Results | PMC10556527 | |||
3.1. Strength of genetic instruments | T2DM | In our efforts to discern the causal influence of gut microbiota on T2DM, we amalgamated SNPs following a genome-wide significance criterion ( | PMC10556527 | |
3.2. Association of intestinal flora with T2DM | MR, T2DM | We found two families and six genera to be causally associated with T2DM using MR methods, as shown in The scatter plots above illustrate the causal association between gut microbiota and T2DM. The light blue, light green, dark blue, green, and pink lines correspond to the Inverse Variance Weighted, Simple Mode, MR-Egger, Weighted Median, and Weighted Model methods, respectively.Forest plot of the causal association between gut microbiota and T2DM. | PMC10556527 | |
3.3. Sensitivity analyses | T2DM | The Cochran Q test indicated no heterogeneity within the instrumental variables, as the MR estimates for the association between gut microbiota and T2DM.Leave-one-out plots for the causal association between gut microbiota and T2DM. | PMC10556527 | |
4. Discussion | MR, intestinal dysbiosis, T2DM | TYPE 2 DIABETES MELLITUS | In this study, we executed a bi-sample Mendelian randomization (MR) investigation, using data from the MiBioGen consortium and the consolidated GWAS dataset, to appraise the cause-and-effect relationship between particular intestinal microflora and T2DM. We identified two genera as protective factors for T2DM, namely genus.Numerous recent studies have consistently reported a strong correlation between gut microbiota and type T2DM (For the other four genera identified in this study besides genus.It is well known that T2DM cannot be completely cured under the current medical conditions, so it is crucial to prevent the occurrence of T2DM. Several reports have shown that intestinal dysbiosis and a decrease in short-chain fatty acid-producing bacteria increase the risk of type 2 diabetes mellitus (Traditional observational studies measure environmental exposure factors that are associated with behavioral, social, and psychological factors, resulting in bias. MR, however, is not affected by these confounding factors. Relative to other methods, MR has less measurement error in relation to its effects, and data from the GWAS are relatively easy to obtain and less costly when conducting MR analyses. | PMC10556527 |
5. Limitations | DISEASE | Initially, it's important to consider that allele frequency and disease prevalence can differ across various populations, hence, population stratification could introduce a confounding element in Mendelian random analysis, especially if the study population is diverse ( | PMC10556527 | |
6. Conclusions | To summarize, this two-sample MR study's findings offer genetic proof that the existence of genus | PMC10556527 | ||
Data availability statement | The data presented in this study is deposited in publicly available datasets. This data can be found at: gut bacteria from MiBioGen (data available at: | PMC10556527 | ||
Author contributions | KS: Data curation, Software, Writing—original draft, Writing—review and editing. YG: Formal Analysis, Methodology, Supervision, Writing—original draft, Writing—review and editing. HW: Data curation, Software, Validation, Writing—review and editing. XH: Conceptualization, Methodology, Validation, Writing—original draft, Writing—review and editing.We gratefully acknowledge the following consortiums: MiBioGen, the MRC Integrative Epidemiology Unit for making their GWAS summary-level statistics publicly available. | PMC10556527 | ||
Conflict of interest | The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. | PMC10556527 | ||
Publisher's note | All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | PMC10556527 | ||
Supplementary material | The Supplementary Material for this article can be found online at: Click here for additional data file.Click here for additional data file.Click here for additional data file. | PMC10556527 | ||
References | PMC10556527 | |||
Background | chronic hepatitis C virus, infection, fatigue | INFECTION | Most people who inject drugs (PWIDs) suffer from severe fatigue, and chronic hepatitis C virus (HCV) infection may play a role in this. However, there is scarce evidence about interventions that alleviate fatigue among PWIDs. The present study investigated the effect of integrated HCV treatment on fatigue in this population compared to the effect of standard HCV treatment, adjusted for sustained virological response of the HCV treatment. | PMC10123982 |
Methods | infectious disease, fatigue, Fatigue | MAY, SECONDARY, INFECTIOUS DISEASE | This multi-center, randomized controlled trial evaluated fatigue as a secondary outcome of integrated HCV treatment (the INTRO-HCV trial). From May 2017 to June 2019, 276 participants in Bergen and Stavanger, Norway, were randomly assigned to receive integrated and standard HCV treatment. Integrated treatment was delivered in eight decentralized outpatient opioid agonist therapy clinics and two community care centers; standard treatment was delivered in specialized infectious disease outpatient clinics at referral hospitals. Fatigue was assessed prior to treatment and 12 weeks after treatment using the nine-item Fatigue Severity Scale (FSS-9). We applied a linear mixed model to evaluate the impact of integrated HCV treatment on changes in FSS-9 (ΔFSS-9) sum scores. | PMC10123982 |
Results | At baseline, the mean FSS-9 sum score was 46 (standard deviation (SD): 15) for participants on integrated HCV treatment and 41 (SD: 16) for those on standard treatment. Twelve weeks after completed HCV treatment, the mean FSS-9 sum score for participants receiving integrated HCV treatment was 42 (SD: 15) and 40 (SD: 14) for those receiving standard HCV treatment. Integrated HCV treatment did not reduce the FSS-9 scores compared to standard HCV treatment (ΔFSS-9: -3.0, 95% confidence interval (CI): -6.4;0.4). | PMC10123982 | ||
Conclusions | fatigue, Fatigue | Fatigue is a common symptom among PWIDs. Integrated HCV treatment is at least equal to standard HCV treatment in improving fatigue. | PMC10123982 | |
Trial registration | ClinicalTrials.gov.no NCT03155906, 16/05/2017. | PMC10123982 | ||
Supplementary Information | The online version contains supplementary material available at 10.1186/s13011-023-00534-1. | PMC10123982 | ||
Keywords | Open access funding provided by University of Bergen. | PMC10123982 | ||
Background | HCV) infection, fatigue, chronic hepatitis C virus, HCV infection, Fatigue | Fatigue is a debilitating symptom that affects as many as 50 to 80% of people with chronic hepatitis C virus (HCV) infection [In this regard, some studies have suggested that HCV treatment may reduce fatigue [This randomized controlled trial investigated the impact of integrated HCV infection treatment on fatigue using the nine-item fatigue severity scale (FSS-9) among PWIDs receiving oral direct-acting antivirals (DAAs) in western Norway. More specifically, we compared the impact of integrated HCV treatment to standard HCV treatment on changes of FSS-9 sum scores, adjusted for SVR. | PMC10123982 | |
Methods | PMC10123982 | |||
Design and setting | The original study, the INTRO-HCV trial, was designed as a multi-center, randomized controlled trial [ | PMC10123982 | ||
Ethics approval and consent to participate | WEST | The present study was reviewed and approved by the Regional Ethical Committee for Health Research (REC) West, Norway (reference number: 2017/51/REK Vest, dated 29.03.2017/20.04.2017). All recruited participants were fully informed about the study, and their written informed consent was provided before their inclusion and randomization. All methods were carried out in accordance with relevant guidelines and regulations. | PMC10123982 | |
Interventions | A total of 148 participants were randomized into the integrated HCV treatment group and 150 into the standard HCV treatment group (Fig. Trial profile for the study. Legends: | PMC10123982 | ||
Intervention – standard HCV treatment | infectious diseases, infectious disease | INFECTIOUS DISEASES, INFECTIOUS DISEASE, DISORDERS | Participants in the standard HCV treatment group were referred to the centralized outpatient infectious disease clinic at the collaborating referral hospital for HCV treatment. An appointment was given and usually scheduled within a few weeks after the referral; the participants were informed of this by mail. Their clinical assessment could involve additional blood samples and imaging before initiating HCV treatment. In the first year of the study, HCV consultation with a consultant in infectious diseases was mandatory, but with increasing clinical experience and growing evidence, the primary assessment became voluntary. Participants were offered follow-up assessments, including blood samples, during treatment in the infectious disease outpatient clinic every four weeks as well as a posttreatment assessment 12 weeks after completion. This typically involved a total of 4 to 5 consultation visits at the outpatient clinic. They were responsible for retrieving and adhering to their prescriptions, and attending assessment appointments. At 12 weeks after the end of treatment (EOT12), blood samples, including HCV polymerase chain reaction, were drawn at infectious disease outpatient clinics, OAT clinics, and CCCs. In addition, participants met at OAT clinics or CCCs to assess their FSS-9 levels.In the standard HCV treatment, participants needed to travel to the hospital clinic and pay for the transport themselves, a distance that ranged from 1 to 25 km. They received standard follow-up in the OAT clinic for drug use disorders, and all other types of care – apart from HCV care – were integrated into the OAT follow-up. The OAT site staff encouraged participants to visit the infectious disease hospital clinics, but no further extensive follow-up was performed. There was a risk that scheduled appointments may overlap with other activities such as receiving OAT medication and other drug use treatment, since arrangements were not coordinated. | PMC10123982 |
Intervention – integrated HCV treatment | OAT | INFECTIOUS DISEASES | All assessments and medications for participants in the integrated treatment groups were provided onsite at the OAT clinics or CCCs, including DAAs, blood samples, and FSS-9 assessments. Compared with participants in the standard treatment group, participants in the integrated treatment group had no follow-ups in the referral hospital, and they received all assessments and medications at the local OAT clinics or CCC. In addition, they drew only two blood samples; prior to HCV treatment and at EOT12, and blood samples drawn every four weeks during the HCV treatment were not necessary. Integrated treatment was delivered at OAT clinics and CCC by multidisciplinary teams in both of the settings. The OAT clinics differed from the CCCs by offering OAT medications in addition to psychosocial approaches. The multidisciplinary teams at the OAT clinics were equipped with consultants in addiction medicine who were responsible for the OAT and other medical follow-ups and also psychologists providing mental health treatment. In both OAT and CCC settings, nurses and social workers, in cooperation with peer counselors, provided most of the participants’ daily follow-ups. All these professionals were existing clinical staff who closely worked together with the research nurses in management of the interventions and evaluations during the study period. For those eligible for HCV treatment, DAAs were administered by a nurse at OAT clinics/CCCs after a prescription from a consultant in infectious diseases. Contrary to standard HCV treatment, all HCV treatment and scheduled follow-ups during treatment were given in parallel with the observed intake of OAT medications and other care, in line with the study protocol. The number of deliveries of OAT and DAA medications per week was adapted to the level of functioning of each participant. For the most severely ill participants with the lowest level of daily functioning and high intake of multiple drugs, OAT medications and HCV treatment were usually dispensed daily in the OAT clinic, and intake was observed by a nurse. The multidisciplinary team planned assessments with participants, or drop-in approaches were applied. | PMC10123982 |
Data collection | fatigue | INFECTIOUS DISEASES | Participants were evaluated prior to HCV treatment and EOT12 to record their health status, including fatigue level according to the FSS-9 score, sociodemographic data, current drug use, blood samples, transient elastography, and clinical examination. The health assessments were conducted by specialized research nurses in close collaboration with the clinics’ consultants in addiction medicine and infectious diseases. A medical team followed up with those who did not meet the criteria for inclusion in the study. Data from the health assessments prior to and after HCV treatment were defined as the study’s baseline and EOT12 (endpoint), respectively. | PMC10123982 |
Randomization and masking | Selected participants were randomized at a 1:1 ratio using blocks of 10 stratified by city and assigned into integrated ( | PMC10123982 | ||
Measurement | Liver stiffness, fatigue | HEPATITIS B, VIRUS | We assessed fatigue using the FSS-9, including items considering mental and physical functioning, motivation, carrying out duties, and interfering with work, family, or social life. The FSS-9 is a well-known questionnaire to quantify fatigue during the week prior to the assessment [We drew blood samples, including hepatitis B virus surface antigen, HIV antigen/antibodies, thrombocytes, and aspartate aminotransferase, as well as HCV antibodies and HCV polymerase chain reactions. Liver stiffness was measured by calculating the aspartate aminotransferase to platelet ratio index and performing transient elastography at baseline (Additional file | PMC10123982 |
Statistical analyses | We used Stata SE version 17 (StataCorp, TX, USA) for descriptive analyses and linear mixed model analyses, and IBM SPSS version 26.0 for expectation–maximization calculation. The threshold for statistical significance was set to We dealt with any missing values in FSS-9 scores at baseline and EOT12 as “missing at random” when running expectation–maximization algorithm [The FSS-9 sum scores at baseline and EOT12 were calculated as described above (“ | PMC10123982 | ||
Results | PMC10123982 | |||
Characteristics at baseline | The median age was 44 years (interquartile range (IQR): 36–52) in the integrated HCV treatment group. Of those, 73% were male, and 58% had injected drugs recently. In the standard HCV treatment group, the median age was 42 years (IQR 34–49), 81% were male, and 64% had injected drugs recently. HCV genotype 3 was most prevalent, representing 65% of participants in the integrated HCV treatment group and 61% in the standard HCV treatment group. | PMC10123982 | ||
FSS-9 sum scores at baseline and EOT12 | At baseline, the mean FSS-9 sum score for participants on receiving integrated treatment was 46 (Standard deviation (SD): 15) and 41 (SD: 16) for those on standard treatment. The mean FSS-9 sum score in both groups was slightly left-skewed and tended toward a flattened distribution at baseline (Additional file | PMC10123982 | ||
Discussion | HCV [, fatigue | The present RCT demonstrated that, compared to standard HCV treatment, integrated HCV treatment did not reduce fatigue from baseline to EOT12 among PWIDs; however, a non-significant improvement in the fatigue level was observed. The fatigue level was high in both the integrated and the standard HCV treatment groups, with substantial intraindividual variation from baseline to EOT12.To our knowledge, this was the first trial conducted in outpatient OAT clinics and CCCs to investigate the impact of integrated HCV treatment on fatigue among PWIDs. Although no significant improvement in integrated HCV treatment compared to standard treatment was found, we revealed non-significant reduction in FSS-9 scores with integrated HCV treatment. This implies that an integrated approach is at least equal to or possibly more effective than standard HCV treatment in reducing fatigue symptoms in this population. Achieving SVR representing 85% and 64% of participants in integrated and standard HCV treatments, respectively, according to the INTRO-HCV trial [The present study demonstrated that integrated HCV treatment was at least equal to relieving fatigue symptoms among PWIDs than standard HCV treatment, adjusted for achieving SVR. The results align with existing literature on this topic [The integrated and standard treatment groups demonstrated substantial intraindividual variation in fatigue levels over time. This corresponds with the results detected in another fatigue study of people infected with HCV [ | PMC10123982 | |
Strengths and limitations | opioid dependence, fatigue, OAT, infectious disease, cognitive impairments | INFECTIOUS DISEASE | A major strength of this study is its trial design of individual randomization with balanced groups, which minimizes potential confounding. Furthermore, we included PWIDs who usually struggle with adherence to standard HCV treatment and have frequently discontinued previous HCV assessment and treatment in centralized infectious disease outpatient clinics. A limitation of this study is in the selection of outpatient clinics, where most participants received OAT to recover from opioid dependence, affecting the generalizability of our results to non-OAT populations. Another limitation is the almost 30% loss-to-follow-up of the FSS-9 assessment at EOT12 and the exclusion of 18 randomized participants due to missing FSS-9 assessments during the period. This may explain the five-point higher FSS-9 sum score in the intervention group than in the control group at baseline. Furthermore, due to system and individual delays and changes in national guidelines for HCV treatment throughout the study period, the FSS-9 assessments were not conducted in exact concurrence with HCV treatment initiation and EOT12. This could affect the interpretation of the predicted fatigue changes from baseline. Furthermore, the FSS-9 did not consider specific issues related to completing the questionnaire, such as cognitive impairments and physical disabilities. These issues could introduce information and recall bias of reported fatigue symptoms. Moreover, a time-to-treatment analysis from the first fatigue measurement to the HCV treatment initiation could be performed to adjust for changes in fatigue. However, the fatigue level was assumed to be substantially unchanged during the few weeks from the first health assessment to the HCV treatment initiation. | PMC10123982 |
Conclusion | fatigue | The present trial documented that fatigue is a common symptom among PWIDs. Integrated HCV treatment was at least equal to standard HCV treatment in alleviating fatigue. Integrated HCV treatment may be a treatment approach in other medical and psychosocial care to improve fatigue. | PMC10123982 | |
Acknowledgements | Alpers | BONNIER, ALPERS | We thank Nina Elisabeth Eltvik, Christer Kleppe, Rafael Alexander Leiva, and Christian Ohldieck for valuable help and input during the planning and preparation phases. We also thank the INTRO-HCV Study Group for important contribution relating to data collection.INTRO-HCV Study Group participating investigators:Bergen: Christer Frode Aas, Vibeke Bråthen Buljovcic, Fatemeh Chalabianloo, Jan Tore Daltveit, Silvia Eiken Alpers, Lars T. Fadnes (principal investigator), Trude Fondenes Eriksen, Per Gundersen, Velinda Hille, Kristin Holmelid Håberg, Kjell Arne Johansson, Rafael Alexander Leiva, Siv-Elin Leirvåg Carlsen, Martine Lepsøy Bonnier, Lennart Lorås, Else-Marie Løberg, Mette Hegland Nordbotn, Cathrine Nygård, Maria Olsvold, Christian Ohldieck, Lillian Sivertsen, Hugo Torjussen, Jørn Henrik Vold, Jan-Magnus ØklandStavanger: Tone Lise Eielsen, Nancy Laura Ortega Maldonado, Ewa Joanna WilkproLAR: Ronny Bjørnestad, Ole Jørgen Lygren, Marianne Cook PierronOslo: Olav Dalgard, Håvard Midgard, Svetlana SkurtveitBristol: Aaron G. Lim, Peter Vickerman | PMC10123982 |
Authors’ contributions | EML | JHV has led the study design, analysis, and writing the article preparation. FC, EML, CFA, AL, PV, KAJ, and LTF have contributed to the study design, analysis, and article preparation. All authors have read and approved the final article. | PMC10123982 | |
Funding | Open access funding provided by University of Bergen. This work was supported by The Norwegian Research Council (BEHANDLING, contract no 269855); and the Western Norway Regional Health Authority («Åpen prosjektstøtte») with Department of Addiction Medicine, Haukeland University Hospital, Bergen, Norway as responsible institution. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors were funded by their respective affiliations. | PMC10123982 | ||
Availability of data and materials | The datasets analyzed during the current study are not publicly available due data protection requirements but are available from the corresponding author on reasonable request. | PMC10123982 | ||
Declarations | PMC10123982 | |||
Ethics approval and consent to participate | WEST | The present study was reviewed and approved by the Regional Ethical Committee for Health Research (REC) West, Norway (reference number: 2017/51/REK Vest, dated 29.03.2017/20.04.2017). All recruited participants were fully informed about the study, and their written informed consent was provided before their inclusion and randomization. All methods were carried out in accordance with relevant guidelines and regulations. | PMC10123982 | |
Consent for publication | Not applicable. | PMC10123982 | ||
Competing interests | The authors declare no competing interests. | PMC10123982 | ||
References | PMC10123982 | |||
Background: | Viral infection | VIRAL INFECTION | Viral infection is associated with a significant rewire of the host metabolic pathways, presenting attractive metabolic targets for intervention. | PMC9937660 |
Methods: | VIRUS, SARS-COV-2 INFECTION | We chart the metabolic response of lung epithelial cells to SARS-CoV-2 infection in primary cultures and COVID-19 patient samples and perform in vitro metabolism-focused drug screen on primary lung epithelial cells infected with different strains of the virus. We perform observational analysis of Israeli patients hospitalized due to COVID-19 and comparative epidemiological analysis from cohorts in Italy and the Veteran’s Health Administration in the United States. In addition, we perform a prospective non-randomized interventional open-label study in which 15 patients hospitalized with severe COVID-19 were given 145 mg/day of nanocrystallized fenofibrate added to the standard of care. | PMC9937660 | |
Results: | inflammation | INFLAMMATION, SARS-COV-2 INFECTION | SARS-CoV-2 infection produced transcriptional changes associated with increased glycolysis and lipid accumulation. Metabolism-focused drug screen showed that fenofibrate reversed lipid accumulation and blocked SARS-CoV-2 replication through a PPARα-dependent mechanism in both alpha and delta variants. Analysis of 3233 Israeli patients hospitalized due to COVID-19 supported in vitro findings. Patients taking fibrates showed significantly lower markers of immunoinflammation and faster recovery. Additional corroboration was received by comparative epidemiological analysis from cohorts in Europe and the United States. A subsequent prospective non-randomized interventional open-label study was carried out on 15 patients hospitalized with severe COVID-19. The patients were treated with 145 mg/day of nanocrystallized fenofibrate in addition to standard-of-care. Patients receiving fenofibrate demonstrated a rapid reduction in inflammation and a significantly faster recovery compared to patients admitted during the same period. | PMC9937660 |
Conclusions: | SARS-CoV-2 infection | SARS-COV-2 INFECTION | Taken together, our data suggest that pharmacological modulation of PPARα should be strongly considered as a potential therapeutic approach for SARS-CoV-2 infection and emphasizes the need to complete the study of fenofibrate in large randomized controlled clinical trials. | PMC9937660 |
Funding: | Funding was provided by European Research Council Consolidator Grants OCLD (project no. 681870) and generous gifts from the Nikoh Foundation and the Sam and Rina Frankel Foundation (YN). The interventional study was supported by Abbott (project FENOC0003). | PMC9937660 | ||
Clinical trial number: | NCT04661930. | PMC9937660 | ||
Research organism | PMC9937660 | |||
Introduction | obesity, hyperlipidemia, inflammation, metabolic diseases, infection, respiratory distress, diabetes | OBESITY, VIRUS, SARS-COV-2 INFECTION, HYPERLIPIDEMIA, CORONAVIRUS INFECTION, INFLAMMATION, METABOLIC DISEASES, INFECTION, ELEVATED BLOOD GLUCOSE, CORONAVIRUS, SEVERE ACUTE RESPIRATORY SYNDROME, DIABETES | The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-strand RNA virus of the Recent work suggests that COVID-19 progression is dependent on metabolic mechanisms. Elevated blood glucose, obesity, and hyperlipidemia were found to be risk factors for SARS-CoV-2-induced acute respiratory distress, independently from diabetes (Metabolomics of COVID-19 patient sera showed alterations in circulating amino acids, glucose, and lipids, correlated with changes in inflammation and renal function (Alarmingly, evidence from previous coronavirus outbreaks suggests that the metabolic rewiring induced by infection has detrimental and long-term effects post-recovery. MERS infection was associated with long-term immune dysregulation and enhanced susceptibility to metabolic diseases (In this report, we charted the metabolic response of primary lung bronchiole and small airway epithelial cells to SARS-CoV-2 infection validating our results with multiple COVID-19 patient samples. We demonstrate intracellular lipid accumulation driven in part by the inhibition of PPARα-dependent lipid catabolism. Screening pharmacological modulators of the SARS-CoV-2 metabolic landscape showed that fenofibrate, and other PPARα-agonists that induce lipid catabolism, reversed metabolic changes and blocked SARS-CoV-2 replication in vitro. An observational study in 3,233 Israeli patients hospitalized due to COVID-19 was consistent with the in vitro observations, showing lower inflammation and faster recovery in patients taking fibrates, while those taking thiazolidinediones that lead to increased lipid accumulation in certain tissues (Moreover, we performed a prospective non-randomized interventional open-label study in which 15 patients hospitalized with severe COVID-19 were given 145 mg/day of nanocrystallized fenofibrate added to the standard of care. These patients demonstrated a rapid reduction in inflammation and a significantly faster recovery compared to patients admitted during the same period and treated with the same standard-of-care. This work demonstrates that pharmacological modulations of PPARα may be an effective treatment for coronavirus infection. The clinical translation of these findings can only be determined following randomized placebo-controlled clinical studies, which are currently ongoing in several international centers. | PMC9937660 |
Methods | PMC9937660 | |||
Experimental model and subject details | PMC9937660 | |||
Human subjects | All protocols involving human tissue were reviewed and exempted by The Hebrew University of Jerusalem, the Israeli Ministry of Health, Sheba Medical Center and Icahn School of Medicine at Mount Sinai Institutional Review Boards.Experiments using samples from human subjects were conducted in accordance with local regulations and with the approval of the institutional review board at the Icahn School of Medicine at Mount Sinai under protocol HS#12–00145 and the institutional review board at Sheba Medical Center under protocol SMC-7875–20.All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.In the observational studies - the Israeli study was approved by the local institutional review board of the Hadassah Medical Center (IRB approval number no. HMO 0247–20) and the local institutional review board of the Ichilov Medical Center (IRB approval number no. 0282–20-TLV). The Italian study was reviewed by the local ethical board (AVEC) of the IRCSS S.Orsola-Malpighi University Hospital (approval number LLD-RP2018).The interventional study was conducted in accordance with the Good Clinical Practice guidelines of the International Council for Harmonisation E6 and the principles of the Declaration of Helsinki or local regulations, whichever afforded greater patient protection. The study was reviewed and approved by the Barzilai Medical Center Research Ethics Committee (0105–20-BRZ). | PMC9937660 | ||
Cell culture | MYCOPLASMA | Normal human bronchial epithelial (NHBE) cells (Lonza, CC-2540 Lot# 580580), isolated from a 79-year-old Caucasian female and were maintained at 37 °C and 5% COCells were authenticated at the source and routinely screened for mycoplasma using PCR. | PMC9937660 | |
Viruses | INFECTIOUS, CYTOPATHIC EFFECT, PLAQUE, CORONAVIRUS, DISEASE | SARS-related coronavirus 2 (SARS-CoV-2), Isolate USA-WA1/2020 (NR-52281) was deposited by the Center for Disease Control and Prevention and obtained through BEI Resources, NIAID, NIH. SARS-CoV-2 was propagated in Vero E6 cells in DMEM supplemented with 2% Fetal Bovine Serum (FBS), 4.5 g/L D-glucose, 4 mM L-glutamine, 10 mM Non-Essential Amino Acids (NEAA), 1 mM Sodium Pyruvate, and 10 mM HEPES. Infectious titers of SARS-CoV-2 were determined by plaque assay in Vero E6 cells in Minimum Essential medium (MEM) supplemented with 4 mM L-glutamine, 0.2% Bovine Serum Albumin (BSA), 10 mM HEPES and 0.12% NaHCOIsolate hCoV-19/Israel/CVL-45526-NGS/2020 (alpha) and hCoV-19/Israel/CVL-12806/2021 (delta) were isolated from nasopharyngeal samples of SARS-CoV-2 positive individuals which contained the alpha sub-lineage B.1.1.50 (hCoV-19/Israel/CVL-45526-NGS/2020) and Delta B.1.617.2 (hCoV-19/Israel/CVL-12804/2021) variants by the central virology laboratory of the ministry of health and Sheba Medical Center. Confluent Vero E6 cells were incubated for one hour at 33 °C with the nasopharyngeal samples, followed by the addition of MEM-EAGLE supplemented with 2% Fetal Bovine Serum (FBS). Upon cytopathic effect detection, supernatants were aliquoted and stored at –80 °C. Infectious titers of SARS-CoV-2 were determined by a 50% endpoint titer (TCID50) for each variant in Vero E6 cells. Approximately 1×10All work involving live SARS-CoV-2 was performed in the CDC/USDA-approved BSL3 facility of the Global Health and Emerging Pathogens Institute at the Icahn School of Medicine at Mount Sinai or in the BSL3 facility of the central virology laboratory of the ministry of health and Sheba Medical Center in accordance with institutional and national biosafety requirements. | PMC9937660 | |
Methods details | PMC9937660 | |||
Analysis of gene expression by RNAseq | cough, tumor, fever | TUMOR, LUNG DISEASES, TUBERCULOSIS | Expression count matrices were retrieved from GEO: GSE147507-Series1 (Bronchial; culture), GSE153970 (Small airway; culture), GSE147507-Series15 (Autopsy), GSE145926- (Lavage). Differential gene expression analysis was performed using a Poisson-Tweedie distribution model using the tweeDEseq Bioconductor package (Bronchial culture samples are 3 independent primary normal human bronchial epithelial cultures infected apically with SARS-CoV-2 (USA-WA1/2020; MOI 2) for 24 hr, compared with three independent primary normal human bronchial epithelial Mock-infected with PBS for 24 hr.Small airway culture samples are three independent primary human airway epithelial cultures infected apically with SARS-CoV-2 (MOI 0.25) for 48 hr, compared with three independent primary human airway epithelial cultures Mock-infected with PBS for 48 hr.The autopsy samples are of two old (age >60) unidentified COVID-19 human subjects, who died due to COVID-19, had autopsy biopsy tissue acquisition post-mortem in Weill Cornell Medicine, and were provided as fixed samples for RNA extraction; the samples were compared with two old (age >60) unidentified human biopsy lung samples, taken during lung surgery and stored at Mount Sinai Institutional Biorepository and Molecular Pathology Shared Resource Facility (SRF) in the Department of Pathology, similarly provided as fixed samples for RNA extraction.COVID-19 patients’ lung epithelial cells are bronchoalveolar lavage fluid isolates from one severe case and five critical cases. The median age of the patients was 62.5 years, and the participants included four male and two female patients. All patients had Wuhan exposure history and had a cough and/or fever as the first symptom. Diagnosis of SARS-CoV-2 was based on clinical symptoms, exposure history, chest radiography and SARS-CoV-2 RNA-positive using commercial quantitative PCR with reverse transcription (qRT–PCR) assays. The samples were compared to three healthy donor controls. The median age was 24 years, and the participants included one female and three male patients. These donors were confirmed to be free of tuberculosis, tumor, and other lung diseases through CT imaging and other laboratory tests. | PMC9937660 |
Analysis of canonical splice variants | Reads were downloaded from SRA (GSE147507), and filtered and trimmed to remove low-quality reads and sequencing artifacts with fastp v20 ( | PMC9937660 | ||
Assembly of metabolic categories | Aggregate metabolic categories were created as previously described ( | PMC9937660 | ||
Processing, analysis, and graphic display of genomic data | HEAT | Hierarchical clustering, heat maps, correlation plots, and similarity matrices were created in Morpheus. Gene ontology enrichment analyses and clustering were performed using DAVID Informatics Resources 6.7 ( | PMC9937660 | |
Quantification of intracellular glucose | To detect glucose uptake, we used 2-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl) Amino)–2-Deoxyglucose (2-NDBG) a fluorescent analog of glucose (Invitrogen, USA; N13195). 2-NDBG is transported through SGLT-1 and GLUT-2. Increased uptake leads to 2-NDBG accumulation in the cells. Cells infected with SARS-CoV-2 for 96 hr were exposed to 6 mM of 2-NDBG for 24 hr. Cells were then fixed, counterstained with 1 μg/mL Hoechst 33258. Staining intensity was normalized to Hoechst 33258 across multiple fields of view. | PMC9937660 | ||
Quantification of lipids | phospholipidosis, Steatosis | PHOSPHOLIPIDOSIS, STEATOSIS | Lipid accumulation was measured using HCS LipidTOX Phospholipidosis and Steatosis Detection Kit according to the manufacturer’s instructions (ThermoFisher, USA; H34158). Briefly, cells were incubated in complete bronchial epithelial growth medium supplemented with 1 x phospholipidosis detection reagent for 48 hr. Cells were subsequently fixed in 4% PFA and stained with 1 X neutral lipid detected reagent for 30 min and counterstained with 1 μg mL-1 Hoechst 33258. Staining intensity was normalized to the amount of Hoechst 33258 positive nuclei across multiple fields of view. | PMC9937660 |
Metabolic analysis of glucose, lactate, and glutamine | IST, SARS-CoV-2 infected | Metabolic analysis of SARS-CoV-2 infected culture medium in the BSL3 facility was done using Accutrend Plus multiparameter meter (Roche Diagnostics). Culture medium was collected every 48 hr and stored at –80 °C prior to analysis. Measurements were carried out using Accutrend Plus Glucose and BM-Lactate Test Strips according to the manufacturer’s instructions. Each measurement was done in 3 technical measurements for each sample, validated throughout the process using calibration medium. Glucose uptake, as well as lactate production, were calculated based on the difference between sample and control medium.Metabolic analysis of SARS-CoV-2 proteins expressing culture medium in the BSL2 facility was done using amperometric glucose, lactate, and glutamine sensor array (IST, Switzerland) as previously described ( | PMC9937660 | |
Generation lentiviral SARS-CoV-2 constructs | VIRUS | Plasmids encoding the SARS-CoV-2 open-reading frames (ORFs) and eGFP control are a kind gift of Nevan Krogan (Addgene plasmid #141367–141395). Plasmids were acquired as bacterial LB-agar stabs and used per the provider’s instructions. Briefly, each stab was first seeded into agar LB (Bacto Agar; BD, USA) in 10 cm plates. Then, single colonies were inoculated into flasks containing LB (BD Difco LB Broth, Lennox; BD, USA) and 100 µg/ml penicillin (BI, Israel). Transfection-grade plasmid DNA was isolated from each flask using the ZymoPURE II Plasmid Maxiprep Kit (Zymo Research, USA) according to the manufacturer’s instructions.HEK 293T cells (ATCC, USA) were seeded in 10 cm cell culture plates at a density of 4x10The following day, cells were transfected with a SARS CoV 2 orf-expressing plasmid and the packaging plasmids using the TransIT-LT1 transfection reagent (Mirus Bio, USA) according to the provider’s instructions. Briefly, 6.65 µg SARS CoV 2 lentivector plasmid, 3.3 µg pVSV-G, and 5 µg psPAX2 were mixed in Opti-MEM reduced serum medium (Gibco, USA), with 45 µl of TransIT-LT1, kept at room temperature to complex and then added to each plate. Following 18 hr of incubation, the transfection medium was replaced with 293T medium and virus-rich supernatant was harvested after 48 hr and 96 hr. The supernatant was clarified by centrifugation (500×g, 5 min) and filtration (0.45 µm, Millex-HV, MerckMillipore). All virus stocks were aliquoted and stored at –80 °C.The packaging plasmids (psPAX2 and pVSV-G) are a kind gift from Prof. N. Benvenisti, Stem Cell Unit at The Hebrew University, Jerusalem, Israel. | PMC9937660 | |
SARS-CoV-2 proteins lentiviral transduction | Approximately 1×10 | PMC9937660 | ||
Metabolic flux quantification (Seahorse) | Mitochondrial Stress Test (Agilent; 103010–100) assay was conducted per manufacturer instructions as previously described (Free fatty acid oxidation was measured using XF Long Chain Fatty Acid Oxidation Stress Test Kit (Agilent; 103672–100) as previously described ( | PMC9937660 | ||
Generation PPARα CRISPR knock-out cells | KNOCKOUT | The PPARα knock-out cells were created using a Cas9-based, CRISPR system. Two different sgRNA oligos from the human GeCKO v.2 Human CRISPR Knockout Pooled Library (Addgene; #1000000048), PPARa HGLibA_37838 and HGLibB_37787, were cloned into the lentiCRISPR v2 plasmid (Addgene; #52961). The sgRNA cloning was performed according to the human GeCKO v.2 system instructions as previously described (The lentiCRISPR v2 plasmid is a kind gift from Prof. N. Benvenisti, Stem Cell Unit at the Hebrew University, Jerusalem, Israel. | PMC9937660 | |
RNA-Seq of viral infections | Approximately 1×10 | PMC9937660 | ||
Viral load by quantitative real-time PCR analysis | In BSL3 experiments conducted in the BSL3 facility at the Icahn School of Medicine at Mount Sinai, Genomic viral RNA was extracted from supernatants using TRIzol reagent according to the manufacturer’s instructions (Thermo Fisher). RNA was reverse transcribed into cDNA using oligo d(T) primers and SuperScript II Reverse Transcriptase (Thermo Fisher). Quantitative real-time PCR was performed on a LightCycler 480 Instrument II (Roche) using KAPA SYBR FAST qPCR Master Mix Kit (KAPA biosystems) and primers specific for the SARS-CoV-2 nsp14 transcript as described previously (In BSL3 experiments conducted in the BSL3 facility at the Sheba Medical Center, Total nucleic acids were extracted from all samples using MagNA Pure 96 DNA and Viral NA Small Volume Kit (Roche) according to the manufacturer protocol. Extracted RNA was transferred to 96 well PCR plate containing 20 µl of TaqPath 1-step Multiplex Master Mix No ROX (Applied Bioscience, Cat number: A28523). This was followed by a one-step RT-PCR (TaqPath COVID-19 assay kit; Thermo-Fisher). Thereafter, the plate was sealed with MicroAmp clear adhesive strip (Applied Bioscience, Cat number: 4306311). The plate was loaded onto a QuantStudio 5 Real-Time PCR System (Applied Bioscience, Cat number: AB-A28574) and the following amplification program was used: 25 °C for 2 min, X1 cycle 53 °C for 10 min, X1 cycle 95 °C for 2 min, X1 cycle 95 °C for 3 s, followed by 60 °C for 30 s, X40 cycles Ct threshold values were presented using the following values/parameters: MS2-15,000; by cycle 37; S gene- 20,000 by cycle 37; Orf1ab- 20,000 by cycle 37; Ngene- 20,000 by cycle 37. Samples that passed the Threshold is a Ct value >37 were re-tested or considered weak positive. The viral load for each sample was determined using genomic viral RNA purified from viral stocks to generate a standard curve. Error bars indicate the standard error from three biological replicates. | PMC9937660 | ||
Functional annotations of gene expression | Differentially expressed genes were tested for enrichment overlap within functional gene sets. The general test for functional enrichment of the differentially expressed genes against various functional categories was done using the PANTHER tool ( | PMC9937660 | ||
Drug treatments | Approximately 5×10 | PMC9937660 | ||
Western blot | LYSED, SECONDARY | NHBE, PPARα CRISPR-KO NHBE cells, or PPARα-OE HEK293T cells were washed in DPBS, lysed in 1 x Laemmli Loading buffer, and boiled at 100 °C; 40 μl of cleared lysate were analyzed in a pre-cast gradient polyacrylamide gel (Bolt 4 to 12%, Bis-Tris, 1.0 mm, Mini Protein Gel/ NW04120BOX, Invitrogen) using SeeBlue Plus2 Pre-stained Protein Standard (LC5925, Invitrogen) in MES SDS running buffer (B0002, Invitrogen) according to manufacturer’s instructions. The proteins were transferred to a PVDF membrane (iBlot 2 Transfer Stacks, PVDF, mini/ IB24002, Invitrogen) using iBlot2 (LifeSciences). The membrane was blocked with 5% BSA (160069, MPBio) in Tris-buffered saline plus 0.1% Tween 20 (TBST) for 1 hr at room temperature. The membranes were incubated in primary antibodies overnight at 4 °C. The next day, the membranes were washed in TBST (3 × 10 min) and then incubated with horseradish peroxidase-conjugated secondary antibody for 2 hr at room temperature. After the TBST washes (4 × 10 min), EZ-ECL kit (Sartorius; 20-500-1000A, 20-500-1000B) was used to detect the HRP activity. The membrane was imaged on a Vilber Fusion FX and band densitometry was performed on FIJI.The following commercial primary antibodies were used: anti-PPARα (1:1000;ab24509, Abcam) and anti-α-tubulin (1:2000; T6074, Sigma). Commercial horseradish peroxidase-conjugated secondary antibodies were: anti-rabbit (111-035-003, Jackson) and anti-mouse (115-035-003, Jackson). All primary antibodies were used in 5% BSA in TBST. Secondary antibodies were used at a 1:8000 dilution in TBST.The gel, ladder, and equipment to run and transfer the gel were kindly provided by Prof. Eran Meshorer, Institute of Life Sciences, The Hebrew University of Jerusalem. The anti-tubulin and both HRP-conjugated antibodies, as well as the HRP detection kit, were kindly provided by Prof. Benjamin Aroeti, Institute of Life Sciences, The Hebrew University of Jerusalem. | PMC9937660 | |
Quantification and statistical analysis | Work done in the BSL3 facility at the Icahn School of Medicine at Mount Sinai was done on NHBE from a single donor, repeated in three experimental repeats with three or more technical repeats in each experiment. Work done in the BSL3 facility at the Sheba Medical Center or in the BSL2 facility at The Hebrew University of Jerusalem was done on NHBE from two donors, repeated in three experimental repeats each (unless noted otherwise by the n value) with three or more technical repeats in each experiment. Work done in the BSL3 facility at the Sheba Medical Center in different variants was done separately and independently for each variant and repeated as listed above.Measurements were technically repeated three or four times for each sample, images were analyzed with five or more fields of view; Graphs show mean ± SEM; Continuous variables were compared with a Mann-Whitney U test or a two-sample t-test or ANOVA. Categorical variables were compared with a chi-squared or Fisher’s exact test, as appropriate. FDR correction was used to adjust for multiple comparisons and RNA seq comparisons; Hypergeometric testing was used to assess statistically significant enrichments. * indicates p<0.05, ** indicates p<0.01, *** indicates p<0.001, unless denoted otherwise. | PMC9937660 | ||
Observational studies | PMC9937660 | |||
Israeli study | obesity, death, chronic kidney disease, asthma, diabetes | OBESITY, DISEASE, LIVER DISEASE, CHRONIC OBSTRUCTIVE PULMONARY DISEASE, CEREBROVASCULAR ACCIDENT, ASTHMA, DYSLIPIDEMIA, REGRESSION, REGRESSION, HYPERTENSION, DIABETES | A retrospective, multi-center study was conducted in Hadassah and Ichilov Medical Centers. A total of 150,976 participants were diagnosed positive for SARS-COV-2 following WHO interim guidance (The retrospective study was designed to assess initial relationships between metabolic regulating drug use and COVID-19 clinical outcomes (28-day mortality and duration of hospitalization, ICU admission, mechanical ventilation, oxygen supplementation, disease severity at baseline, and inflammatory marker changes) versus a control group that did not take any drug of this type.COVID-19 poses a significant risk in older patients and patients with comorbidities (Comparisons were conducted between hospitalized COVID-19 patients using one or more metabolic regulating drugs (fibrates, thiazolidinediones, metformin, SGLT2 inhibitors, statins, or telmisartan [IRE1α inhibitor]) versus control patients not taking any metabolic regulating drugs. Baseline values are defined as measurements taken upon hospital admission. Statistical analyses were performed using SAS v9.4 (SAS, SAS Institute Cary, NC USA) software and R-3.6.3 (R Foundation for Statistical Computing, Vienna, Austria). Continuous variables were summarized by a median and interquartile range (IQR) and categorical variables by a count and percentage. Statistical testing was two-sided. A p-value <0.05 was considered statistically significant. Missing data was not imputed. Nominal p-values are presented since this was an exploratory study. Demographic and baseline clinical characteristics, comorbidities, and laboratory examinations, as well as initial univariate clinical outcomes, were compared between the groups (drugs versus no drugs) by data type using a two-sample t-test or Fisher’s exact test as appropriate.The relative risk of hospitalization, ICU admission, and 28-day all-cause-mortality of COVID-19 patients versus the general hospital population (1-year period, 5-year period, and 10-year period prior to study start date in patients 30 years and older) are presented with 95% confidence interval and level of significance (Wald test).Dynamic changes of inflammatory markers were depicted using locally weighted scatterplot smoothing (Lowess) plotting Time-to-event data is presented with Kaplan-Meier plots. Time-to-events are measured in days from the date of hospital admission to the date of in-hospital death, and release from the hospital or last follow-up or 28 days whichever is sooner. Cox regression was performed to compare time-to-event data between the groups adjusting for covariates that may have been imbalanced between the groups. We did not perform matching since Cox regression models applied to the entire study cohort can effectively address confounding attributable to observed covariates and maximize power by using all data available. Hazard ratios are comparing drug to control group, adjusted for covariates (age, sex, current smoker, asthma, chronic obstructive pulmonary disease, cerebrovascular accident, chronic heart disease, chronic liver disease, chronic kidney disease, obesity, diabetes, hypertension, and dyslipidemia) with a level of significance and 95% confidence interval. In cases of monotone likelihood (non-convergence of likelihood function), Firth’s penalized maximum likelihood bias reduction method for Cox regression was implemented. Cox Regression with Firth’s Penalized Likelihood has been shown to provide a solution in the case of monotone likelihood (non-convergence of likelihood function) and was shown to outperform Wald confidence intervals in these cases ( | PMC9937660 |
Italian study | obesity | OBESITY, CARDIOVASCULAR DISEASE, CHRONIC OBSTRUCTIVE PULMONARY DISEASE | A validation study was conducted by phone interviews of the last 2123 patients examined in the Outpatient Lipid Clinics of the University of Bologna and of the Niguarda Hospital in Milan during the last 12 months and on adequately dosed statins, fenofibrate, or both for at least 3 months. We excluded patients on lipid-lowering nutraceuticals (including polyunsaturated fatty acids), very low-dose or alternate-day statins, ezetimibe alone, PCSK9 inhibitors, and those on fibrates other than fenofibrate, in order to reduce the heterogeneity of the sample. Data were sampled based on comorbidities (obesity, chronic obstructive pulmonary disease, cardiovascular disease, managed as dummy variables), personal COVID history and severity, and contact with people affected by COVID. The study was carried out in adherence with the declaration of Helsinki. All participants were fully informed of the objectives of the questionnaire and gave their oral authorization to use their data for research purposes. The telephone calls were recorded. Age was compared between groups with ANOVA followed by post-hoc testing using Tukey’s method. Percentages were compared by a Chi-square test followed by Fisher’s exact test. | PMC9937660 |
US study | dementia, hypertension, chronic lung disease | DISEASE, DIABETES MELLITUS, ATHEROSCLEROTIC CARDIOVASCULAR DISEASE, HEART FAILURE, HYPERTENSION, CHRONIC LUNG DISEASE, CHRONIC LIVER DISEASE | A validation study was conducted using an existing observational cohort of 920,922 veterans with hypertension (defined by diagnostic codes for hypertension and at least two fills for antihypertensive medications from January 1, 2020, to October 25, 2020, and restricted to those veterans with evidence of using the Veterans Health Administration for their primary care). There were 5144 (0.6%) veterans in the cohort who tested positive for SARS-CoV-2 between March 14, 2020, and October 25, 2020. Medication use was determined by confirmed pharmacy fills. The cohort contained a diverse, non-homogenous patient population with different disease severity. To minimize baseline differences between fenofibrate users and the three comparison groups (non-users, statin users, and TZD users), 1:5 propensity score matching was performed using Stata version 15.0. Baseline matching variables included age, sex, body mass index, race/ethnicity, and history of atherosclerotic cardiovascular disease, heart failure, diabetes mellitus, chronic lung disease, chronic liver disease, dementia, and current or former smoker. We performed nearest neighbor matching with a caliper of 0.1. We required a<10% standardized difference in each of the matched covariates between matched groups, as well as Rubin’s B of ≤25% and Rubin’s R between 0.5–2 to verify sufficient matching. | PMC9937660 |
Interventional study | PMC9937660 | |||
Design and participants | pneumonia, multiple organ dysfunction, kidney disease, chronic kidney disease stage, hypersensitivity | PNEUMONIA, KIDNEY DISEASE, RESPIRATORY FAILURE, DISEASE, CHRONIC KIDNEY DISEASE STAGE 1, INFILTRATES, SEPTIC SHOCK, DISEASE, HYPERSENSITIVITY | The study was conducted as an open-label, phase 3 a clinical trial, in the Barzilai Medical Center, Ashkelon, Israel. The study was approved by the Barzilai Medical Center Research Ethics Committee (0105–20-BRZ). The study enrolled adults (≥18 years of age) with severe Covid-19 pneumonia, as confirmed by positive polymerase-chain-reaction (PCR) and evidenced by bilateral chest infiltrates on chest radiography or computed tomography. Eligible patients had a disease severity score of 4 (Hospitalized, requiring supplemental oxygen), increased oxygen requirement compared to baseline at home, a blood oxygen saturation of 93% or less on room air, or a ratio of the partial pressure of oxygen to the fraction of inspired oxygen (PaO2/FiO2) of less than 300 mm Hg, respiratory rate >30 breaths/min, and lung infiltrates >50% on chest CT within 72 hr of hospital admission or within 72 hr of a positive test result.Individuals who had respiratory failure, septic shock, and/or multiple organ dysfunction, SOFA ≥ 5 or Disease Severity Score ≤ 3 (requiring noninvasive mechanical ventilation, requiring extracorporeal membrane oxygenation (ECMO), invasive mechanical ventilation, or all) were excluded. Additionally, individuals with known hypersensitivity to fenofibrate, patient-reported history, or electronic medical record history of severe kidney disease (defined as any history of dialysis, history of chronic kidney disease stage IV or estimated Glomerular Filtration Rate (eGFR) of <30 ml/min/1.73 mAll participants provided written informed consent signed by the participant or legally authorized representative. Standard care according to local practice (supplemental oxygen, antiviral treatment, anticoagulants, vitamin D3, low-dose glucocorticoids, convalescent plasma and supportive care) was provided. However, concomitant treatment with another investigational agent (except antiviral drugs) or any immunomodulatory agent, was prohibited. Written informed consent was obtained from all the patients or, if written consent could not be provided, the patient’s legally authorized representative could provide oral consent with appropriate documentation by the investigator. The primary analysis was performed on day 14, a follow-up was done 28 days post-admission. | PMC9937660 |
Procedures | cough, low immunoinflammatory stress, fever | Participants who met the inclusion criteria were assigned to intervention with nanocrystallized fenofibrate (TriCor, AbbVie Inc, North Chicago, IL USA) at a dose of 145 mg (1 tablet) once per day. Standard care for severe-hospitalized COVID-19 patients was provided according to local practice: antiviral treatment, vitamin D3, low-dose glucocorticoids, convalescent plasma, and supportive care as well as antipyretics for symptoms of fever (products containing paracetamol, or non-steroidal anti-inflammatories such as aspirin and ibuprofen) and dextromethorphan for symptoms of cough. Standard chronic treatments were continued unless COVID-19, clinical status, or fenofibrate treatment was a contraindication for treatment. Control patients were collected from the observational study’s database and filtered to patients that met the inclusion criteria, admitted with low immunoinflammatory stress (NLR <10 at admission), and treated according to the standard care used in the interventional study. | PMC9937660 | |
Valuations | ’ disease, Death | For the evaluation of patients in this trial, the baseline was defined as the last observation before the administration of fenofibrate on day 0. The patients’ disease severity was assessed on an ordinal scale according to the following categories: The scale is as follows: (1) Death; (2) Hospitalized, on invasive mechanical ventilation or extracorporeal membrane oxygenation (ECMO); (3) Hospitalized, on non-invasive ventilation or high flow oxygen devices; (4) Hospitalized, requiring supplemental oxygen; (5) Hospitalized, not requiring supplemental oxygen; (6) Not hospitalized, limitation of activities; (7) Not hospitalized, no limitations of activities. Clinical status was recorded at baseline and every day during hospitalization. | PMC9937660 | |
Viral RNA and S-gene target failure (SGTF) detection by real-time PCR | Extracted RNA was transferred to 96-well PCR plate containing 20 µl of TaqPath 1-step Multiplex Master Mix No ROX (Applied Bioscience, Cat number: A28523). This was followed by a one-step RT-PCR (TaqPath COVID-19 assay kit; Thermo-Fisher). Thereafter, the plate was sealed with MicroAmp clear adhesive strip (Applied Bioscience, Cat number: 4306311). The plate was loaded onto a QuantStudio 5 Real-Time PCR System (Applied Bioscience, Cat number: AB-A28574) and the following amplification program was used: 25 °C for 2 min, X1 cycle 53 °C for 10 min, X1 cycle 95 °C for 2 min, X1 cycle 95 °C for 3 s, followed by 60 °C for 30 s, X40 cycles Ct threshold values were preset using the following values/parameters: MS2-15,000; by cycle 37; S gene- 20,000 by cycle 37; Orf1ab- 20,000 by cycle 37; Ngene- 20,000 by cycle 37. Samples that passed the Threshold is a Ct value >37 were re-tested or considered weak positive. Above threshold values of MS2, Orf1ab, and Ngene, but not S gene was considered S-gene target failure (SGTF). SGTF serves as a proxy for identifying B.1.1.7 cases ( | PMC9937660 | ||
Variant detection by real-time PCR | ENDO | Allplex SARS-CoV-2 Variants I Assay from Seegene Inc was used according to the manufacturer protocol to perform rRT-PCR. Briefly, Extracted RNA (5 µl) was transferred to 96 well PCR plate containing 15 µll of the master mix. Plates were then spun down at 2500 rpm for 5 s and analyzed on a CFX96 Touch Real-Time PCR from BioRad. Reverse Transcription reaction 1 cycle: 50 °C/20 min – 95 °C/15 min. PCR reaction 45 cycles: 94 °C/15 s – 58 °C/30 sec. Gene amplifications were analyzed by FAM (E484K mutation on S-Gene), HEX (RdRP), Cal Red 610 (N501Y mutation on S-Gene), Quasar 705 (69-70del on S-Gene), and Quasar 670 (Human Endo Internal control) fluorophores. Results were compiled and analyzed using the 2019-nCoV viewer from Seegene Inc according to the manufacturer’s instructions. | PMC9937660 | |
Statistical analysis | death | REGRESSION | Demographic data were summarized, continuous variables with non-normal distributions were expressed as median [IQR] and categorical variables were expressed as numbers and percentages (%). The sample size is detailed in each display item. Comparisons between groups were performed with Mann-Whitney U test for continuous variables and Fisher’s exact test or chi-squared test for categorical variables.Analysis of weighted differences in hospitalization duration, mortality, and incidence of oxygen weaning was done using the Mantel–Haenszel test. The cumulative rates of death and hospital discharge were compared using Kaplan-Meier curves, a log-rank test, and cause-specific Cox regression analysis. The hazard ratio (HR) was calculated using the Cox proportional hazard model comparing the treatment group versus the non-treatment group as previously described (Dynamic changes of inflammatory factors tracking from day 0 to day 8 after treatment were depicted using the Lowess model ( | PMC9937660 |
Ethics and oversight | All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.In the observational studies - the Israeli study was approved by the local institutional review board of the Hadassah Medical Center (IRB approval number no. HMO 0247–20) and the local institutional review board of the Ichilov Medical Center (IRB approval number no. 0282–20-TLV). The Italian study was reviewed by the local ethical board (AVEC) of the IRCSS S.Orsola-Malpighi University Hospital (approval number no. code LLD-RP2018).The American study was reviewed by the local institutional review board of Corporal Michael J. Crescenz VA Medical Center (IRB approval number 01654).The interventional study was conducted in accordance with the Good Clinical Practice guidelines of the International Council for Harmonisation E6 and the principles of the Declaration of Helsinki or local regulations, whichever afforded greater patient protection. The study was reviewed and approved by the Barzilai Medical Center Research Ethics Committee (0105–20-BRZ).Statistical analysis of the Israeli studies was done by BioStats Statistical Consulting Ltd. (Maccabim, Israel), funded by the sponsor. Data management is performed in compliance with GCP and 21 CFR part 1. Statistical analyses and reporting are performed in compliance with E6 GCP, E9, and ISO 14155. Independently validated by the author. Statistical analysis of the Italian study was done by Prof. Arrigo Cicero and Dr. Chiara Pavanello. Statistical analysis of the US study was done by Prof. Jordana Cohen. | PMC9937660 | ||
Software resources | Our custom Cell Analysis CellProfiler Pipeline is available at | PMC9937660 | ||
Results | PMC9937660 | |||
The metabolic fingerprint of SARS-CoV-2 infection | infected primary human bronchial epithelial | VIRUS | To elucidate the metabolic effects of SARS-CoV-2 we infected primary human bronchial epithelial cells with the virus ( | PMC9937660 |
Metabolic fingerprint of SARS-CoV-2 infection. | (
| PMC9937660 | ||
Metabolic signature of infection in COVID-19 patients’ samples and SARS-CoV-2 infected primary cells. | infection | INFECTION, SARS-COV-2 INFECTION | (Further transcriptional analysis shows that 58 ± 3% of differentially expressed genes are metabolism-related, with about 15 ± 2% of the genes associated with lipid metabolism (Mapping differentially expressed genes on the central carbon metabolism pathway showed that SARS-CoV-2 induces key glycolysis genes (To confirm these transcriptional signatures we validated our results in SARS-CoV-2-infected primary lung cells (Metabolic changes are often linked to endoplasmic stress. Indeed, SARS-CoV-2 infection of primary cells induced the dsRNA-activated protein kinase R (PKR/PERK) and IRE1 pathways leading to differential expression of ATF4 and splicing of XBP1. The ATF6 pathway of ER stress was seemingly unaffected by infection. Induction of PKR/PERK and IRE1 pathways were previously shown to lead to a Warburg-like shift to anaerobic glycolysis ( | PMC9937660 |
SARS-CoV-2 proteins cause direct modulation of metabolic pathways | To explore the role of viral proteins in the host metabolic response to SARS-CoV-2, we expressed a large protein panel ( | PMC9937660 | ||
SARS-CoV-2 proteins modulate host metabolic pathways. | Analysis of primary bronchial epithelial cells expressing different SARS-CoV-2 proteins for 72 hr using multiple independent assays. (
| PMC9937660 | ||
Gene expression patterns of SARS-CoV-2 proteins. | SARS-CoV-2 infection | SARS-COV-2 INFECTION | (To study the role of viral proteins in lipid metabolism, we measured the exogenous fatty acid oxidation using Seahorse (The inhibition of lipid catabolism by SARS-CoV-2 infection of primary lung epithelial cells and associated lipid accumulation is a unique host response ( | PMC9937660 |
Pharmacological modulation of SARS-CoV-2-induced metabolic pathways | SARS-CoV-2 infection | SARS-COV-2 INFECTION | The metabolic pathways induced by SARS-CoV-2 infection can be pharmacologically modulated at multiple points ( | PMC9937660 |
Metabolic intervention of SARS-CoV-2 shows the antiviral effect of PPARα activation. | (
| PMC9937660 | ||
PPARα is required for fenofibrate rescue and etomoxir reversal in SARS-CoV-2 infection in vitro. | (
| PMC9937660 |
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