Speaker
Description
Autosomal Dominant Polycystic Kidney Disease (ADPKD), the most common hereditary kidney disease, exhibits marked clinical heterogeneity driven by complex molecular mechanisms. While single-omics studies identify isolated pathways, defining the coordinated mechanistic framework of disease remains a challenge. In this study, we present an end-to-end R-based workflow to integrate high-throughput transcriptomic and metabolomic data, aiming to uncover latent pathological axes of ADPKD. We analyzed a longitudinal cohort of 254 ADPKD patients stratified by disease progression, hypertension and mortality status, encompassing untargeted plasma metabolomics (270 metabolites features) and whole-blood transcriptomics (17,725 transcripts features). Pre-processing and differential expression analyses for each group were conducted utilizing the DESeq2 R package. Prior to model estimation and integration, the transcriptomic and metabolomic datasets were variance-stabilized within R using the VST function and log-transformation, respectively. Functional enrichment and pathway analysis were subsequently performed using the clusterProfiler (v4.16.0), GSEA_0.1, and MetaboAnalyst 6.0 R packages and visualized using dot plots and gene-concept network plots in enrichplot (v1.28.4). Unsupervised multi-omics integration was performed using the MOFA (Multi-Omics Factor Analysis) R package (v4.3.3). Variance decomposition inferred five latent factors capturing shared variance across the omics layers. Factor 1 represented the primary component of variance and was characterized by a convergence of biologically coordinated pathways. All visualizations were rendered within the R environment leveraging the ggplot2 (v3.1.0). This study demonstrates the power of the R ecosystem as a comprehensive framework for multi-omics integration in rare diseases.
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Google Gemini was utilized during the preparation of this abstract strictly as a writing and formatting assistant. Its primary functions were to help refine the English language, improve the structural flow of the narrative, and condense the text to meet the conference's 250-word limit. The experimental design, data analysis, interpretation of results, and final conclusions were conducted independently by the authors
| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | Multi-omics integration, transcriptomics, metabolomics, R |
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| Virtual Option | This submission is for onsite presentation primarily, but I would also like it to be considered for pre-recorded virtual presentation if I don't get an onsite slot |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |