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Abstract: TH-PO423

Integrating Multi-Omics for Precision Medicine: Identification of Drug Targets and Biomarkers for ADPKD from Large Patient Cohorts

Session Information

Category: Genetic Diseases of the Kidneys

  • 1201 Genetic Diseases of the Kidneys: Cystic

Authors

  • Skroblin, Philipp, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Urbanke, Hendrik, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Castro, Ricardo, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Stumm, Jürgen, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Naujock, Maximilian, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Mitrovic, Mitja, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Lo, I-Ju, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Bayerlova, Michaela, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Landesfeind, Manuel, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Sauer, Sven, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Schmidt, Antje, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Radresa, Olivier, Evotec International GmbH, Goettingen, Niedersachsen, Germany
  • Andag, Uwe, Evotec International GmbH, Goettingen, Niedersachsen, Germany
Background

Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic cause of kidney failure. There is an unmet medical need for biomarkers (early diagnosis, reliable prognosis) and for effective and safe therapy. Especially research on the molecular drivers of ADPKD progression is challenging due to the lack of available biopsies. An integrative approach utilizing patient samples and ADPKD models can bridge this gap.

Methods

Blood samples from NURTuRE-CKD participants (200 ADPKD, 2,000 other CKD) were subjected to genotyping and deep mRNA-Seq. Selected serum and urine samples were analyzed by proteomics and metabolomics. Whole-exome sequencing (WES) data were provided by the NURTuRE consortium. Cyst-forming renal organoids were differentiated from human iPSCs carrying a loss-of-function mutation in PKD1 and subjected to snRNA-Seq.

Results

In NURTuRE omics data we observed that: (1) ADPKD patients’ blood transcriptomes constitute a cluster that is distinct from age-, sex- and eGFR-matched non-ADPKD samples (other CKD), (2) several proteins are differentially abundant in ADPKD vs. other CKD urine proteomics, (3) among NURTuRE-CKD patients, WES revealed carriers of PKD1 and PKD2 pathogenic mutations who had previously not been diagnosed with PKD and may represent early or pre-onset cases of ADPKD. To provide more insight into early disease mechanisms, we performed snRNA-Seq of human iPSC-derived cyst-forming renal organoids. To leverage their combined power, we used these datasets reflecting different aspects of the disease to build a multi-layered similarity network while maintaining source information. This network was incorporated into a larger graph database, which allows for the expansion of feature information and the generation of embeddings for biological interpretation facilitated by machine learning.

Conclusion

Our integrated multi-omics analysis framework utilizes patient samples and cyst-forming organoids to enable the analysis of molecular mechanisms underpinning ADPKD, especially in early disease stages. This will facilitate the discovery of diagnostic or prognostic biomarkers and novel targets.