Semantic Multi-Classifier Systems Identify Predictive Processes in Heart Failure Models across Species.

Ludwig Lausser,Lea Siegle,Derk Frank,Hans Kestler,Wolfgang Rottbauer,Steffen Just

doi:10.3390/biom8040158

Abstract

Genetic model organisms have the potential of removing blind spots from the underlying gene regulatory networks of human diseases. Allowing analyses under experimental conditions they complement the insights gained from observational data. An inevitable requirement for a successful trans-species transfer is an abstract but precise high-level characterization of experimental findings. In this work, we provide a large-scale analysis of seven weak contractility/heart failure genotypes of the model organism zebrafish which all share a weak contractility phenotype. In supervised classification experiments, we screen for discriminative patterns that distinguish between observable phenotypes (homozygous mutant individuals) as well as wild-type (homozygous wild-types) and carriers (heterozygous individuals). As the method of choice we use semantic multi-classifier systems, a knowledge-based approach which constructs hypotheses from a predefined vocabulary of high-level terms (e.g., Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways or Gene Ontology (GO) terms). Evaluating these models leads to a compact description of the underlying processes and guides the screening for new molecular markers of heart failure. Furthermore, we were able to independently corroborate the identified processes in Wistar rats.

Highlights

Human heart failure (HF) is the leading cause of hospitalization in Western world countries and is associated with high morbidity and mortality thereby putting a large burden on health care costs [1].Alarmingly, over the last decade, heart failure incidence further increased with a rate of about 1% per year mostly attributed to demographic changes and an aging population [2]
We analyzed several zebrafish lines suffering from heart failure which were identified in large-scale zebrafish
Weak contractility as a common phenotype of HF is known to be caused by many different genetic mutations [16,17]

Summary

Introduction

Human heart failure (HF) is the leading cause of hospitalization in Western world countries and is associated with high morbidity and mortality thereby putting a large burden on health care costs [1].Alarmingly, over the last decade, heart failure incidence further increased with a rate of about 1% per year mostly attributed to demographic changes and an aging population [2]. Up to now, the molecular underpinnings of HF are still only poorly defined but are essential for the development and the clinical implementation of targeted and tailored HF therapies. In this context, the use of established model organisms such as mice and zebrafish to model human heart failure enable the systematic dissection and definition of the molecular etiology of HF. Biomolecules 2018, 8, 158 forward genetics mutagenesis screens [3] We characterized these HF zebrafish mutants phenotypically and molecularly, identified the respective underlying genetic defects and verified the relevance in human heart failure [4,5,6,7]. The molecular networks and common denominators of HF in these mutants are still unknown so far

Methods

Results

Conclusion