Abstract

The cardiac troponin T variations have often been used as an example of the application of clinical genotyping for prognostication and risk stratification measures for the management of patients with a family history of sudden cardiac death or familial cardiomyopathy. Given the disparity in patient outcomes and therapy options, we investigated the impact of variations on the intermolecular interactions across the thin filament complex as an example of an unbiased systems biology method to better define clinical prognosis to aid future management options. We present a novel unbiased dynamic model to define and analyse the functional, structural and physico-chemical consequences of genetic variations among the troponins. This was subsequently integrated with clinical data from accessible global multi-centre systematic reviews of familial cardiomyopathy cases from 106 articles of the literature: 136 disease-causing variations pertaining to 981 global clinical cases. Troponin T variations showed distinct pathogenic hotspots for dilated and hypertrophic cardiomyopathies; considering the causes of cardiovascular death separately, there was a worse survival in terms of sudden cardiac death for patients with a variation at regions 90–129 and 130–179 when compared to amino acids 1–89 and 200–288. Our data support variations among 90–130 as being a hotspot for sudden cardiac death and the region 131–179 for heart failure death/transplantation outcomes wherein the most common phenotype was dilated cardiomyopathy. Survival analysis into regions of high risk (regions 90–129 and 130–180) and low risk (regions 1–89 and 200–288) was significant for sudden cardiac death (p = 0.011) and for heart failure death/transplant (p = 0.028). Our integrative genomic, structural, model from genotype to clinical data integration has implications for enhancing clinical genomics methodologies to improve risk stratification.

Details

Title
Prognostic implications of troponin T variations in inherited cardiomyopathies using systems biology
Author
Shakur Rameen 1   VIAFID ORCID Logo  ; Ochoa, Juan Pablo 2 ; Robinson, Alan J 3 ; Niroula Abhishek 4 ; Chandran Aneesh 5 ; Rahman Taufiq 6 ; Vihinen Mauno 4 ; Monserrat Lorenzo 7   VIAFID ORCID Logo 

 Massachusetts Institute of Technology, The Koch Institute for Integrative Cancer Research, Boston, United States (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786); Wellcome Trust Genome Campus, Wellcome Trust Sanger Institute, Hinxton, UK (GRID:grid.52788.30) (ISNI:0000 0004 0427 7672) 
 University of A Coruña, Hospital Marítimo de Oza (15006), Institute of Biomedical Investigation of A Coruña (INIBIC), A Coruña, Spain (GRID:grid.8073.c) (ISNI:0000 0001 2176 8535); Health In Code. As Xubias s/n, Edificio El Fortín, Cardiology department, A Coruña, Spain (GRID:grid.8073.c) 
 Cambridge Biomedical Campus, Medical Research Council Mitochondrial Biology Unit, The Keith Peters Building, Cambridge, UK (GRID:grid.14105.31) (ISNI:0000000122478951) 
 Lund University, Protein Structure and Bioinformatics, Department of Experimental Medical Science, Lund, Sweden (GRID:grid.4514.4) (ISNI:0000 0001 0930 2361) 
 Kannur University, Department of Biotechnology & Microbiology, Kannur, India (GRID:grid.444523.0) (ISNI:0000 0000 8811 3173); University of Cambridge, Department of Pharmacology, Cambridge, UK (GRID:grid.5335.0) (ISNI:0000000121885934) 
 University of Cambridge, Department of Pharmacology, Cambridge, UK (GRID:grid.5335.0) (ISNI:0000000121885934) 
 Health In Code. As Xubias s/n, Edificio El Fortín, Cardiology department, A Coruña, Spain (GRID:grid.4514.4) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20567944
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2540467619
Copyright
© The Author(s) 2021. corrected publication 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.