52 Works

Additional file 1 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 1: Mapping of differentially expressed ir-lncRNAs to protein coding genes. (A) Diagram representation of the random walk with restart global propagation network algorithm. (B) Walkscore distribution of protein-coding genes in TCGA-BRCA, with cutoff set at walkscore ≥ 0.01 to generate a ranked list of protein-coding genes in proximity of differentially expressed ir-lncRNAs.

Additional file 5 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 5: Spearman correlation coefficients of ir-lncRNAs with immune checkpoint expression in TCGA-BRCA.

Additional file 9 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 9: Correlation of 3 ir-lncRNA signature with immune subpopulations across tumor types. Pearson correlation heatmap between immune cell subpopulation enrichment scores and 3 ir-lncRNA scores.

Additional file 9 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 9: Table S9. Summary of univariate Cox proportional hazard analysis of the previously identified CpGs. Column variables represent Name; chr; chromosome number, pos; position, CpG name, relation_to_Island; where is CpG located in relationship to island, UCSC RefGene Name; UCSC gene name, UCSC RefGene Accession; UCSC gene accession, UCSC RefGene Group; where in respect to gene is CpG located, Beta; estimated coefficient beta from the model, StandardError; standard error, Z; z-score, LRT; likelihood ratio...

Additional file 1 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 1: Mapping of differentially expressed ir-lncRNAs to protein coding genes. (A) Diagram representation of the random walk with restart global propagation network algorithm. (B) Walkscore distribution of protein-coding genes in TCGA-BRCA, with cutoff set at walkscore ≥ 0.01 to generate a ranked list of protein-coding genes in proximity of differentially expressed ir-lncRNAs.

Additional file 3 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 3: Propagation walkscores of 127 proxy protein-coding genes in the TCGA-BRCA cohort.

Additional file 7 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 7: Akaike information criterion (AIC), delta AIC, and HRs for death (overall survival) and corresponding 95%-confidence interval for ICR and 3 ir-lncRNA signature in 18 solid cancer TCGA datasets and RAQA cohort.

Assessing the genetic burden of familial hypercholesterolemia in a large middle eastern biobank

Geethanjali Devadoss Gandhi, Waleed Aamer, Navaneethakrishnan Krishnamoorthy, Najeeb Syed, Elbay Aliyev, Aljazi Al-Maraghi, Muhammad Kohailan, Jamil Alenbawi, Mohammed Elanbari, Borbala Mifsud, Younes Mokrab, Charbel Abi Khalil & Khalid A. Fakhro
Abstract Background The genetic architecture underlying Familial Hypercholesterolemia (FH) in Middle Eastern Arabs is yet to be fully described, and approaches to assess this from population-wide biobanks are important for public health planning and personalized medicine. Methods We evaluate the pilot phase cohort (n = 6,140 adults) of the Qatar Biobank (QBB) for FH using the Dutch Lipid Clinic Network (DLCN) criteria, followed by an in-depth characterization of all genetic alleles in known dominant (LDLR,...

Additional file 2 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 2: Table S2. Summary of different models tested for estimating differences between controls and COVID-19 patients for immune cell proportions. Adjusted R2, residual standard error (sigma), AIC, and p.value for each tested model for each cell type are shown. The following models were tested, mod1; Age and ethnicity as covariates, mod2; age as a covariate, mod3; ethnicity as a covariate, mod4; no covariates.

Additional file 3 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 3: Table S3. Summary of identified differentially methylated CpGs between COVID-19 patients and controls. A. All significant CpGs B. Variable description from Table S2A. C. Significant CpGs from genes previously described as COVID-19 important [1]. D. Functional annotation of genes from Supplemental table 3C.

Additional file 4 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 4: Table S4. Summary of differentially methylated pathways detected between COVID-19 patients and controls based on CpG sites.

Additional file 9 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 9: Table S9. Summary of univariate Cox proportional hazard analysis of the previously identified CpGs. Column variables represent Name; chr; chromosome number, pos; position, CpG name, relation_to_Island; where is CpG located in relationship to island, UCSC RefGene Name; UCSC gene name, UCSC RefGene Accession; UCSC gene accession, UCSC RefGene Group; where in respect to gene is CpG located, Beta; estimated coefficient beta from the model, StandardError; standard error, Z; z-score, LRT; likelihood ratio...

DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Abstract Background COVID-19 infections could be complicated by acute respiratory distress syndrome (ARDS), increasing mortality risk. We sought to assess the methylome of peripheral blood mononuclear cells in COVID-19 with ARDS. Methods We recruited 100 COVID-19 patients with ARDS under mechanical ventilation and 33 non-COVID-19 controls between April and July 2020. COVID-19 patients were followed at four time points for 60 days. DNA methylation and immune cell populations were measured at each time point. A...

Additional file 3 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 3: Propagation walkscores of 127 proxy protein-coding genes in the TCGA-BRCA cohort.

Additional file 4 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 4: Canonical pathways, diseases and functions associated with the 127 proxy protein-coding genes.

Additional file 6 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 6: Prognostic value of ICR classifier across solid cancers. Forest plot showing HRs for death (overall survival) and corresponding 95%-confidence interval for the continuous ICR score and number of patients for each TCGA cancer cohort and RAQA breast cancer cohort. Significant positive HRs are visualized in blue and significant negative HRs are visualized in red. ICR enabled (HR < 1, p-value < 0.05) cancer types are indicated with orange asterisks and ICR disabled...

Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Abstract Background Advances in our understanding of the tumor microenvironment have radically changed the cancer field, highlighting the emerging need for biomarkers of an active, favorable tumor immune phenotype to aid treatment stratification and clinical prognostication. Numerous immune-related gene signatures have been defined; however, their prognostic value is often limited to one or few cancer types. Moreover, the area of non-coding RNA as biomarkers remains largely unexplored although their number and biological roles are rapidly...

Additional file 7 of Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Shimaa Sherif, Raghvendra Mall, Hossam Almeer, Adviti Naik, Abdulaziz Al Homaid, Remy Thomas, Jessica Roelands, Sathiya Narayanan, Mahmoud Gasim Mohamed, Shahinaz Bedri, Salha Bujassoum Al-Bader, Kulsoom Junejo, Davide Bedognetti, Wouter Hendrickx & Julie Decock
Additional file 7: Akaike information criterion (AIC), delta AIC, and HRs for death (overall survival) and corresponding 95%-confidence interval for ICR and 3 ir-lncRNA signature in 18 solid cancer TCGA datasets and RAQA cohort.

Additional file 10 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 10: Table S10. Description of the eight genes that are predictors of mortality. Data were collected from Gene Ontology (GO) to identify the functional annotation of each gene and recently published COVID-19 related articles to highlight the role of each gene in relation to COVID-19.

Additional file 11 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 11. Supplementary Figures.

Additional file 7 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 7: Table S7. Summary of immune cell changes and differentially methylated CpGs between recovered and dead patients over four time points 7A. Immune cell changes between recovered and dead patients over four time points, 7B. Differential methylation of CpGs between recovered and died patients over four time points. The b_0, b_1, b_2, and b_3 coefficients correspond to the reference model parameters, where survival phenotype is used as a reference. The d_0, d_1, d_2,...

Additional file 1 of DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Additional file 1:Table S1. Baseline characteristics of COVID-19 patients and controls.

DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

Martina Bradic, Sarah Taleb, Binitha Thomas, Omar Chidiac, Amal Robay, Nessiya Hassan, Joel Malek, Ali Ait Hssain & Charbel Abi Khalil
Abstract Background COVID-19 infections could be complicated by acute respiratory distress syndrome (ARDS), increasing mortality risk. We sought to assess the methylome of peripheral blood mononuclear cells in COVID-19 with ARDS. Methods We recruited 100 COVID-19 patients with ARDS under mechanical ventilation and 33 non-COVID-19 controls between April and July 2020. COVID-19 patients were followed at four time points for 60 days. DNA methylation and immune cell populations were measured at each time point. A...

Additional file 1 of Assessing the genetic burden of familial hypercholesterolemia in a large middle eastern biobank

Geethanjali Devadoss Gandhi, Waleed Aamer, Navaneethakrishnan Krishnamoorthy, Najeeb Syed, Elbay Aliyev, Aljazi Al-Maraghi, Muhammad Kohailan, Jamil Alenbawi, Mohammed Elanbari, Borbala Mifsud, Younes Mokrab, Charbel Abi Khalil & Khalid A. Fakhro
Supplementary Material 1

Assessing the genetic burden of familial hypercholesterolemia in a large middle eastern biobank

Geethanjali Devadoss Gandhi, Waleed Aamer, Navaneethakrishnan Krishnamoorthy, Najeeb Syed, Elbay Aliyev, Aljazi Al-Maraghi, Muhammad Kohailan, Jamil Alenbawi, Mohammed Elanbari, Borbala Mifsud, Younes Mokrab, Charbel Abi Khalil & Khalid A. Fakhro
Abstract Background The genetic architecture underlying Familial Hypercholesterolemia (FH) in Middle Eastern Arabs is yet to be fully described, and approaches to assess this from population-wide biobanks are important for public health planning and personalized medicine. Methods We evaluate the pilot phase cohort (n = 6,140 adults) of the Qatar Biobank (QBB) for FH using the Dutch Lipid Clinic Network (DLCN) criteria, followed by an in-depth characterization of all genetic alleles in known dominant (LDLR,...

Registration Year

  • 2022
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Affiliations

  • Weill Cornell Medical College in Qatar
    52
  • Hamad Medical Corporation
    48
  • Hamad bin Khalifa University
    48
  • Cornell University
    28
  • Centre Hospitalier Universitaire de Clermont-Ferrand
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  • Memorial Sloan Kettering Cancer Center
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  • Sidra Medical and Research Center
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  • University of Genoa
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  • Hamad General Hospital
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  • Qatar Foundation
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