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6 results on '"Erg��ener, Bekir"'

1. Additional file 1 of Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

Author

Seyres, Denis, Cabassi, Alessandra, Lambourne, John J., Burden, Frances, Farrow, Samantha, McKinney, Harriet, Batista, Joana, Kempster, Carly, Pietzner, Maik, Slingsby, Oliver, Cao, Thong Huy, Quinn, Paulene A., Stefanucci, Luca, Sims, Matthew C., Rehnstrom, Karola, Adams, Claire L., Frary, Amy, Erg��ener, Bekir, Kreuzhuber, Roman, Mocciaro, Gabriele, D���Amore, Simona, Koulman, Albert, Grassi, Luigi, Griffin, Julian L., Ng, Leong Loke, Park, Adrian, Savage, David B., Langenberg, Claudia, Bock, Christoph, Downes, Kate, Wareham, Nicholas J., Allison, Michael, Vacca, Michele, Kirk, Paul D. W., and Frontini, Mattia

Abstract

Additional file 1: Fig. S1. Overview of experimental design. A. Parameters used to define lean individuals amongst blood donors and controls. B. Overview of the analysis set-up to determine the effects of bariatric surgery. To minimise batch effects, 20 additional blood donors ("Controls") were recruited and were not previously present in the original BluePrint cohort. We applied a set of filters (METHODS) to identify low risk individuals within the 20 Controls, designed hereafter as "Lean-Control". C. Overview of multi-omics integration. In brief, data from 202 individuals identified as blood donors ("BD") in the present study, were collected from BluePrint consortium. It included, for monocytes and neutrophils, H3K27ac ChIP-seq, RNA-seq and 450K methylation arrays. Additionally, we obtained anthropometric measurements (BW, BMI) and generated plasma biochemistry assays, plasma metabolomics, plasma lipidomics on samples collected from the same individuals at the same time. Case groups were composed of obese individuals referred for bariatric surgery and lipodystrophy patients. Data for these groups were generated in this study. We applied a set of filters (METHODS) to identify low risk individuals within the 202 blood donors, designed hereafter as "Lean-BD".

Published
2022
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2. Additional file 6 of Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

Author

Seyres, Denis, Cabassi, Alessandra, Lambourne, John J., Burden, Frances, Farrow, Samantha, McKinney, Harriet, Batista, Joana, Kempster, Carly, Pietzner, Maik, Slingsby, Oliver, Cao, Thong Huy, Quinn, Paulene A., Stefanucci, Luca, Sims, Matthew C., Rehnstrom, Karola, Adams, Claire L., Frary, Amy, Erg��ener, Bekir, Kreuzhuber, Roman, Mocciaro, Gabriele, D���Amore, Simona, Koulman, Albert, Grassi, Luigi, Griffin, Julian L., Ng, Leong Loke, Park, Adrian, Savage, David B., Langenberg, Claudia, Bock, Christoph, Downes, Kate, Wareham, Nicholas J., Allison, Michael, Vacca, Michele, Kirk, Paul D. W., and Frontini, Mattia

Abstract

Additional file 6. Extended methods describing biochemical profiling.

Published
2022
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3. Additional file 4 of Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

Author

Seyres, Denis, Cabassi, Alessandra, Lambourne, John J., Burden, Frances, Farrow, Samantha, McKinney, Harriet, Batista, Joana, Kempster, Carly, Pietzner, Maik, Slingsby, Oliver, Cao, Thong Huy, Quinn, Paulene A., Stefanucci, Luca, Sims, Matthew C., Rehnstrom, Karola, Adams, Claire L., Frary, Amy, Erg��ener, Bekir, Kreuzhuber, Roman, Mocciaro, Gabriele, D���Amore, Simona, Koulman, Albert, Grassi, Luigi, Griffin, Julian L., Ng, Leong Loke, Park, Adrian, Savage, David B., Langenberg, Claudia, Bock, Christoph, Downes, Kate, Wareham, Nicholas J., Allison, Michael, Vacca, Michele, Kirk, Paul D. W., and Frontini, Mattia

Abstract

Additional file 4: Fig. S4. Related to Figure 3���Multi-omic signatures of extreme phenotype groups and their use in prediction. A. Plots showing individuals ranked by their predicted probability of belonging to the obese group. As in Figure 3C, but for the Methylation (monocytes), RNA-Seq (monocytes), Metabolites, and ChIP-Seq (monocytes) data layers. B. Multi-omic model trained using lipodystrophy patients often predicts obese individuals to belong to the lipodystrophy group. As in Figure 3C (final plot), but training the multi-layer model using the Lipodystrophy and Lean-BD groups (rather than the Obese and Lean-BD groups). Using this model, Obese individuals were often predicted as belonging to the Lipodystrophy group.

Published
2022
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4. Additional file 5 of Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

Author

Seyres, Denis, Cabassi, Alessandra, Lambourne, John J., Burden, Frances, Farrow, Samantha, McKinney, Harriet, Batista, Joana, Kempster, Carly, Pietzner, Maik, Slingsby, Oliver, Cao, Thong Huy, Quinn, Paulene A., Stefanucci, Luca, Sims, Matthew C., Rehnstrom, Karola, Adams, Claire L., Frary, Amy, Erg��ener, Bekir, Kreuzhuber, Roman, Mocciaro, Gabriele, D���Amore, Simona, Koulman, Albert, Grassi, Luigi, Griffin, Julian L., Ng, Leong Loke, Park, Adrian, Savage, David B., Langenberg, Claudia, Bock, Christoph, Downes, Kate, Wareham, Nicholas J., Allison, Michael, Vacca, Michele, Kirk, Paul D. W., and Frontini, Mattia

Subjects
digestive system diseases, health care economics and organizations
Abstract

Additional file 5: Fig. S5. Related to Figure 3���A common pattern of associations between the prioritised lipid species and known CMS risk factors. The pattern of association between the prioritised lipids and known CMS risk factors in the NASH cohort (NASH cohort; left) agrees with the results from the present study (BD cohort; right).

Published
2022
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5. Additional file 2 of Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

Author

Seyres, Denis, Cabassi, Alessandra, Lambourne, John J., Burden, Frances, Farrow, Samantha, McKinney, Harriet, Batista, Joana, Kempster, Carly, Pietzner, Maik, Slingsby, Oliver, Cao, Thong Huy, Quinn, Paulene A., Stefanucci, Luca, Sims, Matthew C., Rehnstrom, Karola, Adams, Claire L., Frary, Amy, Erg��ener, Bekir, Kreuzhuber, Roman, Mocciaro, Gabriele, D���Amore, Simona, Koulman, Albert, Grassi, Luigi, Griffin, Julian L., Ng, Leong Loke, Park, Adrian, Savage, David B., Langenberg, Claudia, Bock, Christoph, Downes, Kate, Wareham, Nicholas J., Allison, Michael, Vacca, Michele, Kirk, Paul D. W., and Frontini, Mattia

Abstract

Additional file 2: Fig. S2. Related to Figure 1���WGCNA analysis with BD individuals metabolite values and cluster functional annotation. A. Heatmap of BD individuals eigen-metabolites adjacencies in the consensus eigen-metabolites network. Each row and column correspond to one eigen metabolite (labelled by consensus module colour). The heatmap is colour-coded by adjacency, yellow indicating high adjacency (positive correlation) and blue low adjacency (negative correlation) as shown by the colour legend. B. Beeswarm plot using average eigen metabolites per cluster. Colours indicate cohorts.

Published
2022
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6. Additional file 3 of Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

Author

Seyres, Denis, Cabassi, Alessandra, Lambourne, John J., Burden, Frances, Farrow, Samantha, McKinney, Harriet, Batista, Joana, Kempster, Carly, Pietzner, Maik, Slingsby, Oliver, Cao, Thong Huy, Quinn, Paulene A., Stefanucci, Luca, Sims, Matthew C., Rehnstrom, Karola, Adams, Claire L., Frary, Amy, Erg��ener, Bekir, Kreuzhuber, Roman, Mocciaro, Gabriele, D���Amore, Simona, Koulman, Albert, Grassi, Luigi, Griffin, Julian L., Ng, Leong Loke, Park, Adrian, Savage, David B., Langenberg, Claudia, Bock, Christoph, Downes, Kate, Wareham, Nicholas J., Allison, Michael, Vacca, Michele, Kirk, Paul D. W., and Frontini, Mattia

Subjects
genetic processes, natural sciences
Abstract

Additional file 3: Fig. S3. Related to Figure 2���Summary plots of different feature numbers in all comparisons. Barplots showing the number of features significantly different for each comparison in H3K27ac distribution (ChIP-Seq), gene expression (RNA-Seq) and DNA methylation (RRBS). Each bar is colour coded to represent the different cell types.

Published
2022
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