title: From Mouse Models to Patients: A Comparative  Bioinformatic Analysis of HFpEF and HFrEF
creator: Lanzer, Jan David
subject: ddc-004
subject: 004 Data processing Computer science
subject: ddc-570
subject: 570 Life sciences
subject: ddc-610
subject: 610 Medical sciences Medicine
description: Heart failure (HF) represents an immense health burden with currently no curative  therapeutic strategies. Study of HF patient heterogeneity has led to the recognition of  HF with preserved (HFpEF) and reduced ejection fraction (HFrEF) as distinct syndromes  regarding molecular characteristics and clinical presentation. Until the recent past,  HFrEF represented the focus of research, reflected in the development of a number of  therapeutic strategies. However, the pathophysiological concepts applicable to HFrEF  may not be necessarily applicable to HFpEF. HF induces a series of ventricular  modeling processes that involve, among others, hallmarks of hypertrophy, fibrosis,  inflammation, all of which can be observed to some extent in HFpEF and HFrEF. Thus,  by direct comparative analysis between HFpEF and HFrEF, distinctive features can be  uncovered, possibly leading to improved pathophysiological understanding and  opportunities  for  therapeutic  intervention.  Moreover,  recent  advances  in  biotechnologies, animal models, and digital infrastructure have enabled large-scale  collection of molecular and clinical data, making it possible to conduct a bioinformatic  comparative analysis of HFpEF and HFrEF.  Here, I first evaluated the field of HF transcriptome research by revisiting published  studies and data sets to provide a consensus gene expression reference. I discussed the  patient clientele that was captured, revealing that HFpEF patients were not represented.  Thus, I applied alternative approaches to study HFpEF. I utilized a mouse surrogate  model of HFpEF and analyzed single cell transcriptomics to gain insights into the  interstitial tissue remodeling. I contrasted this analysis by comparison of fibroblast  activation patterns found in mouse models resembling HFrEF. The human reference  was used to further demonstrate similarities between models and patients and a novel  possible biomarker for HFpEF was introduced.  Mouse models only capture selected aspects of HFpEF but largely fail to imitate the  complex multi-factor and multi-organ syndrome present in humans. To account for  this complexity, I performed a top-down analysis in HF patients by analyzing  phenome-wide comorbidity patterns. I derived clinical insights by contrasting HFpEF  and HFrEF patients and their comorbidity profiles. These profiles were then used to  predict associated genetic profiles, which could be also recovered in the HFpEF mouse  model, providing hypotheses about the molecular links of comorbidity profiles.  My work provided novel insights into HFpEF and HFrEF syndromes and exemplified an  interdisciplinary bioinformatic approach for a comparative analysis of both syndromes  using different data modalities.
date: 2023
type: Dissertation
type: info:eu-repo/semantics/doctoralThesis
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/33556/1/20230713_PhD_JanLanzer_pdfa.pdf
identifier: DOI:10.11588/heidok.00033556
identifier: urn:nbn:de:bsz:16-heidok-335560
identifier:   Lanzer, Jan David  (2023) From Mouse Models to Patients: A Comparative Bioinformatic Analysis of HFpEF and HFrEF.  [Dissertation]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/33556/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng