Systems Biology Approaches for Target Identification and Therapeutic Development in Chronic Diseases

QC 2025-05-07

Abstract

Chronic diseases such as metabolic, renal, or liver disorders involve complex interactions of genes, cell types, and tissues. This doctoral thesis leverages systems biology by integrating transcriptomics with other omics data to map biological interactions and identify novel therapeutic targets. By viewing gene perturbations as interconnected networks rather than isolated factors, the research uncovers key drivers of disease and matches them with potential interventions. A combination of bulk and single-cell RNA sequencing is used: bulk RNA-seq provides a broad view of tissue-level changes, while single-cell RNA-seq pinpoints changes in specific cell populations. Together, these approaches enable more precise identification of drug targets for chronic diseases and facilitate drug repositioning to expedite therapy development.The thesis is structured into three key sections. The first part (Paper I) integrates transcriptomic, proteomic and lipidomic data, exploring PKLR as a druggable target of non-alcoholic fatty liver disease (NAFLD). This study investigates whether small-molecule inhibitors of PKLR expression could serve as therapeutic agents, offering a drug repurposing strategy to mitigate disease progression. The second part (Papers II–IV) relies on gene co-expression network, and leverages both bulk and single cell transcriptomics to discover disease-associated molecular drivers of hepatocellular carcinoma (HCC) and chronic kidney disease (CKD), respectively. These studies illustrate how single cell data can locate key molecular targets in diverse cell types within tissues, and help to understand molecular mechanism of these diseases.In the final section (Paper V), a whole-body single-cell gene expression atlas is introduced, providing a foundational reference for human biology. This resource enhances the systems biology toolkit, enabling rapid contextualization of newly identified disease genes and drug targets. Researchers can determine tissue and cell-type specificity, facilitating a clearer understanding of therapeutic strategies for chronic diseases.Overall, this thesis underscores the power of systems biology in deciphering disease mechanisms and advancing precision medicine. The integration of multi-omics data with network analysis fosters a holistic understanding of chronic diseases, leading to effective and targeted treatments. Beyond identifying therapeutic targets, the research contributes a lasting resource in form of the single-cell gene expression atlas, bridging molecular discoveries withIclinical applications. These insights accelerate the development of novel, data- driven therapies for complex diseases, advancing translational medicine.

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