GB-XMAP
Development of a system-theoretical methodology to characterize altered gene expression in neuropsychiatric diseases and inflammatory bowel diseases
Disordered communication between the gut and the brain can promote the development of neuropsychiatric and inflammatory bowel diseases. The aim of the GB-XMAP research network is to elucidate the disease-relevant molecular mechanisms that are common between schizophrenia and ulcerative colitis, as well as to develop a systems medicine model of potential dysfunction of the gut-brain axis. Well-characterized molecular genetic risk factors, relevant for both diseases, should be considered for this purpose. Therefore, RNA sequencing data from more than 1.000 patients and 1.500 healthy control individuals are collected and evaluated using genetic datasets of known genome-wide association studies. The datasets are combined to a disease-spanning interaction map by using bioinformatic methods and mathematical modeling techniques.
The specific aim is to identify relevant target genes and molecular mechanisms, which could be the basis to develop effective therapies for mental illness and inflammatory bowel diseases in laboratory experiments.
The GB-XMAP research network intends to establish a new disease-spanning network alliance within the research and funding concept "e:Med - Establishing systems medicine in Germany". This alliance consists of working groups from the e:Med research consortia "SysINFLAME" (inflammatory research) and "IntegraMent" (neuropsychiatric diseases) as well as the research group "de.NBI-SysBio" (Systems-biological Modeling) of the German Network for Bioinformatics. As a result, this alliance contributes to an intensive interdisciplinary crosslinking of systems medicine research groups.
Publications
Bej, S., A.-M. Galow, R. David, M. Wolfien, and O. Wolkenhauer (2021). "Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling." BMC Bioinf 22(1): 1–17. doi.org/10.1186/s12859-021-04469-x.
Bej, S., J. Sarkar, S. Biswas, P. Mitra, P. Chakrabarti, and O. Wolkenhauer (2022). "Identification and epidemiological characterization of Type-2 diabetes sub-population using an unsupervised machine learning approach." Nutrition & Diabetes 12(1): 27. doi.org/10.1038/s41387-022-00206-2.
Bej, S., K. Schulz, P. Srivastava, M. Wolfien, and O. Wolkenhauer (2021). "A Multi-Schematic Classifier-Independent Oversampling Approach for Imbalanced Datasets." IEEE Access 9: 123358–123374. doi.org/10.1109/ACCESS.2021.3108450.
Degenhardt, F., M. Wendorff, M. Wittig, E. Ellinghaus, L. W. Datta, J. Schembri, S. C. Ng, E. Rosati, M. Hubenthal, D. Ellinghaus, E. S. Jung, W. Lieb, S. Abedian, R. Malekzadeh, J. H. Cheon, P. Ellul, A. Sood, V. Midha, B. K. Thelma, S. H. Wong, S. Schreiber, K. Yamazaki, M. Kubo, G. Boucher, J. D. Rioux, T. L. Lenz, S. R. Brant, and A. Franke (2019). "Construction and benchmarking of a multi-ethnic reference panel for the imputation of HLA class I and II alleles." Hum Mol Genet 28(12): 2078-2092. www.ncbi.nlm.nih.gov/pubmed/30590525.
Mucha, S., H. Baurecht, N. Novak, E. Rodríguez, S. Bej, G. Mayr, H. Emmert, D. Stölzl, S. Gerdes, E. S. Jung, F. Degenhardt, M. Hübenthal, E. Ellinghaus, J. C. Kässens, L. Wienbrandt, W. Lieb, M. Müller-Nurasyid, M. Hotze, N. Dand, S. Grosche, I. Marenholz, A. Arnold, G. Homuth, C. O. Schmidt, U. Wehkamp, M. M. Nöthen, P. Hoffmann, L. Paternoster, M. Standl, K. Bønnelykke, T. S. Ahluwalia, H. Bisgaard, A. Peters, C. Gieger, M. Waldenberger, H. Schulz, K. Strauch, T. Werfel, Y.-A. Lee, M. Wolfien, P. Rosenstiel, O. Wolkenhauer, S. Schreiber, A. Franke, S. Weidinger, and D. Ellinghaus (2020). "Protein-coding variants contribute to the risk of atopic dermatitis and skin-specific gene expression." Journal of Allergy and Clinical Immunology 145(4): 1208–1218. doi.org/10.1016/j.jaci.2019.10.030.
Schultz, K., S. Bej, W. Hahn, M. Wolfien, P. Srivastava, and O. Wolkenhauer (2024). "ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets." Pattern Recognition 147. doi.org/10.1016/j.patcog.2023.110138.
Shadrin, A. A., S. Mucha, D. Ellinghaus, M. B. Makarious, C. Blauwendraat, A. A. K. Sreelatha, A. Heras-Garvin, J. Ding, M. Hammer, A. Foubert-Samier, W. G. Meissner, O. Rascol, A. Pavy-Le Traon, O. Frei, K. S. O'Connell, S. Bahrami, S. Schreiber, W. Lieb, M. Muller-Nurasyid, U. Schminke, G. Homuth, C. O. Schmidt, M. M. Nothen, and P. Hoffmann (2021). "Shared Genetics of Multiple System Atrophy and Inflammatory Bowel Disease." MOVEMENT DISORDERS 36(2): 449-459. doi.org/10.1002/mds.28338.
Thaventhiran, J. E. D., H. Lango Allen, O. S. Burren, W. Rae, D. Greene, E. Staples, Z. Zhang, J. H. R. Farmery, I. Simeoni, E. Rivers, J. Maimaris, C. J. Penkett, J. Stephens, S. V. V. Deevi, A. Sanchis-Juan, N. S. Gleadall, M. J. Thomas, R. B. Sargur, P. Gordins, H. E. Baxendale, M. Brown, P. Tuijnenburg, A. Worth, S. Hanson, R. J. Linger, M. S. Buckland, P. J. Rayner-Matthews, K. C. Gilmour, C. Samarghitean, S. L. Seneviratne, D. M. Sansom, A. G. Lynch, K. Megy, E. Ellinghaus, D. Ellinghaus, S. F. Jorgensen, T. H. Karlsen, K. E. Stirrups, A. J. Cutler, D. S. Kumararatne, A. Chandra, J. D. M. Edgar, A. Herwadkar, N. Cooper, S. Grigoriadou, A. P. Huissoon, S. Goddard, S. Jolles, C. Schuetz, F. Boschann, et al, and P. I. C. f. t. N. Bioresource (2020). "Whole-genome sequencing of a sporadic primary immunodeficiency cohort." Nature 583(7814): 90–95. doi.org/10.1038/s41586-020-2265-1.
Uellendahl-Werth, F., C. Maj, O. Borisov, S. Juzenas, E. M. Wacker, I. F. Jorgensen, T. A. Steiert, S. Bej, P. Krawitz, P. Hoffmann, C. Schramm, O. Wolkenhauer, K. Banasik, S. Brunak, S. Schreiber, T. H. Karlsen, F. Degenhardt, M. Nothen, A. Franke, T. Folseraas, and D. Ellinghaus (2022). "Cross-tissue transcriptome-wide association studies identify susceptibility genes shared between schizophrenia and inflammatory bowel disease." Commun Biol 5(1): 80. www.ncbi.nlm.nih.gov/pubmed/35058554.
Uellendahl-Werth, F., M. Wolfien, A. Franke, O. Wolkenhauer, and D. Ellinghaus (2020). "A benchmark of hemoglobin blocking during library preparation for mRNA-Sequencing of human blood samples." Sci Rep 10(5630): 1–10. doi.org/10.1038/s41598-020-62637-0.
Wacker, E. M., F. Uellendahl-Werth, S. Bej, O. Wolkenhauer, M. Vesterhus, W. Lieb, A. Franke, T. H. Karlsen, T. Folseraas, and D. Ellinghaus (2023). "Whole blood RNA-Seq identifies transcriptional differences between primary sclerosing cholangitis and ulcerative colitis." JHEP Report 0(0). doi.org/10.1016/j.jhepr.2023.100988.