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SARS-CoV-2 Research


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Lab Cheng-Jian Xu

Research Group

Clinical Bioinformatics

Personalized medicine offers a significant opportunity to enhance public health by accounting for individual variability in genes, environment, and lifestyle. The "Clinical Bioinformatics" research group follows this direction, aiming to unravel the intricate molecular mechanisms underlying infection and aging. Through this pursuit, we strive to develop precise, individualized treatment strategies.

Our research aims to develop and apply "bioinformatics approaches" to pinpoint the genetic and epigenetic factors influencing infection-induced immune responses by integrating multi-omics data from patients and constructing computational models that predict an individual’s risk of infectious diseases. We interact with experimental collaborators and clinical experts to verify our findings and promote their translation into medical treatments or diagnostic procedures. Our ultimate goal is to contribute to the main research focus of CiiM/MHH: the tailored and improved prevention, diagnosis, and treatment of infectious diseases and cancer for individual patients or patient groups.

Within this framework, the team led by Prof. Dr. Cheng-Jian Xu is primarily dedicated to the domains of diagnosis, risk assessment, early detection, and patient stratification.

Focus

The Clinical Bioinformatics research group focuses on the development and application of computational approaches to enhance our comprehension of infection and aging. They place emphasis on investigating the role of epigenetic modifications in these pathophysiological conditions. This involves analyzing samples from cohort studies through the utilization of whole-genome epigenetic profiling, single-cell transcriptomics technologies, and systems genetics methodologies. The ultimate goal is to develop tailored therapeutic strategies based on detailed molecular stratification of disease sub-entities. This represents a significant advancement towards the realization of individualized medicine.

Empowering personalized medicine through data-driven insights and innovative bioinformatics solutions

Prof. Dr. Cheng-Jian Xu

Dr. Cheng-Jian Xu is a professor in the field of Clinical Bioinformatics. With a Ph.D. in Chemometrics from Central South University, he possesses over two decades of experience in data science. Throughout his career, Dr. Xu has pioneered innovative methods for analyzing complex biological, chemical, and clinical data, unraveling critical insights into genetic variations and their role in disease susceptibility. His research has led to the identification of novel biomarkers for early disease prediction. As a passionate advocate for interdisciplinary research, Dr. Xu continues to push the boundaries of bioinformatics, with a commitment to advancing both scientific knowledge and its real-world applications. His work has not only transformed our understanding of genomics but has also paved the way for personalized medicine and improved patient outcomes. 

Projects

Epigenetic Markers for Diagnosing Immune Response to Infection

Numerous studies have evaluated the variability of individual human immune responses. Recent research within the Human Functional Genomics Project (HFGP) has effectively characterized the impact of genetic and environmental factors on immune responses in healthy individuals. However, the extent to which epigenetic modifications influence this variability in immune response remains largely unexplored.

Our proposal aims to systematically generate, analyze, and integrate epigenomic data alongside other omics data, such as the genome, transcriptome, proteome, metabolome, and microbiome, in conjunction with immune-related phenotypes (e.g., cell frequencies, antibody or cytokine levels). Computational techniques will be utilized for this purpose. Cutting-edge technologies available at MHH and its partner institutes will facilitate the creation of comprehensive multi-omics datasets. We will identify key driver genes within immune pathways that react to infections, such as COVID-19 and HIV infection, as well as the specific immune cell types in which they exert their influence. We will investigate how genetic variants, through the regulation of the methylome, impact immune pathways, particularly within the context of infection, and how they contribute to susceptibility or severity of infections.

1. Gupta, M. K., Peng, H., Li, Y. & Xu, C.-J. The role of DNA methylation in personalized medicine for immune-related diseases. Pharmacology & Therapeutics 108508 (2023). doi:10.1016/j.pharmthera.2023.108508

2. Xu CJ, Soderhall C, Bustamante M, Baiz N, et.al (2018) DNA methylation in childhood asthma: an epigenome-wide meta-analysis. Lancet Respir Med 6(5): 379-388.

Funding: Helmholtz Initiative and Networking Fund, ViiV health care

Risk Assessment: disease risk prediction through artificial intelligence of cross-omics data

Complex diseases have strong genetic and environmental components. Environmental factors can have sustained effects on gene expression through the modulation of epigenetic features. Previous studies have constructed models to assess individual disease risk, but these models usually investigate only a single layer of ‘omics’ data, such as the genome, epigenome, transcriptome, proteome, or metabolome. Given the complex biological nature of infectious diseases, such as hepatitis D virus infection, leveraging the information from multi-omics data, especially from single cell omics, may improve prediction.

Our objective is to employ artificial intelligence methodologies to methodically integrate extensive multi-omics data encompassing the genome, DNA-methylome of blood and disease-relevant tissue cells, and environmental variables. The AI-driven prediction model facilitates the identification of paramount factors contributing to diseases. Furthermore, it holds promise for the formulation of novel clinical applications aimed at diagnosing high-risk patients, a pivotal stride towards personalized medicine.

  1. van Breugel, M., Qi, C., Xu, Z., Pedersen, C.-E. T., Petoukhov, I., Vonk, J. M., Gehring, U., Berg, M., Bügel, M., Capraij, O. A., Forno, E., Morin, A., Eliasen, A. U., Jiang, Y., van den Berge, M., Nawijn, M. C., Li, Y., Chen, W., Bont, L., Bønnelykke, K., Celedón, J. C., Koppelman, G. H. & Xu, C.-J. Nasal DNA methylation at three CpG sites predicts childhood allergic disease. medRxiv 2022.06.17.22276520 (2022). doi:10.1101/2022.06.17.22276520
  2. Oltmanns, C., Liu, Z., Mischke, J., Tauwaldt, J., Mekonnen, Y. A., Urbanek-Quaing, M., Debarry, J., Maasoumy, B., Wedemeyer, H., Kraft, A. R. M., Xu, C.-J*. & Cornberg*, M. Reverse inflammaging: Long-term effects of HCV cure on biological age. Journal of Hepatology 78, 90–98 (2023).

Funding: German Research Foundation(DFG)

Contact

Selected publications

1. Gupta, M. K., Peng, H., Li, Y. & Xu, C.-J. The role of DNA methylation in personalized medicine for immune-related diseases. Pharmacology & Therapeutics 108508 (2023). doi:10.1016/j.pharmthera.2023.108508

2. Oltmanns, C., Liu, Z., Mischke, J., Tauwaldt, J., Mekonnen, Y. A., Urbanek-Quaing, M., Debarry, J., Maasoumy, B., Wedemeyer, H., Kraft, A. R. M., Xu, C.-J*. & Cornberg*, M. Reverse inflammaging: Long-term effects of HCV cure on biological age. Journal of Hepatology78, 90–98 (2023).

3. Rabold K., Zoodsma M., Grondman I., Kuijpers, Y,… , Xu CJ*. & Netea-Maier R. T*, Reprogramming of myeloid cells and their progenitors in patients with non-medullary thyroid carcinoma. Nature Communications 13, 6149 (2022).

4. van Breugel M, Qi C. Xu Zl, … Chen Wei, Bont L, Bønnelykke11 K, Celedón JC, Koppelman GH and Xu CJ, Nasal DNA methylation at three CpG sites predicts childhood allergic disease. Nature Communications 13, 7415 (2022)

5. Xu CJ, Söderhäll C, Bustamante M, Baiz N, Gruzieva O, et.alDNA methylation in childhood asthma: an epigenome-wide meta-analysis. Lancet Respir Med, 6, 379 (2018)

A complete list of Cheng-Jian Xu's publications can be found on Google Scholar.