Prognostic implications of troponin T variations in inherited cardiomyopathies using systems biology

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...

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Published inNpj genomic medicine Vol. 6; no. 1; pp. 47 - 11
Main Authors Shakur, Rameen, Ochoa, Juan Pablo, Robinson, Alan J., Niroula, Abhishek, Chandran, Aneesh, Rahman, Taufiq, Vihinen, Mauno, Monserrat, Lorenzo
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 14.06.2021
Nature Publishing Group
Nature Portfolio
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ISSN2056-7944
2056-7944
DOI10.1038/s41525-021-00204-w

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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.
AbstractList 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.
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.
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.
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.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.
ArticleNumber 47
Author Ochoa, Juan Pablo
Niroula, Abhishek
Chandran, Aneesh
Robinson, Alan J.
Vihinen, Mauno
Monserrat, Lorenzo
Shakur, Rameen
Rahman, Taufiq
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Snippet The cardiac troponin T variations have often been used as an example of the application of clinical genotyping for prognostication and risk stratification...
Abstract The cardiac troponin T variations have often been used as an example of the application of clinical genotyping for prognostication and risk...
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SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 47
SubjectTerms 631/553
692/308/2056
Bioinformatics
Biomedical and Life Sciences
Biomedicine
Cardiology and Cardiovascular Disease
Cardiomyopathy
Clinical Medicine
Congestive heart failure
Death
Defibrillators
Dilated cardiomyopathy
Disease hot spots
Gene Function
Gene Therapy
Genetic analysis
Genetic diversity
Genomics
Genotypes
Genotyping
Heart failure
Heart transplantation
Human Genetics
Internal Medicine
Kardiologi och kardiovaskulära sjukdomar
Klinisk medicin
Medical and Health Sciences
Medical prognosis
Medicin och hälsovetenskap
Phenotypes
Phenotypic variations
Structure-function relationships
Survival
Survival analysis
Transplants & implants
Troponin
Troponin T
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Title Prognostic implications of troponin T variations in inherited cardiomyopathies using systems biology
URI https://link.springer.com/article/10.1038/s41525-021-00204-w
https://www.ncbi.nlm.nih.gov/pubmed/34127679
https://www.proquest.com/docview/2540467619
https://www.proquest.com/docview/2541321525
https://pubmed.ncbi.nlm.nih.gov/PMC8203786
https://doaj.org/article/d83b655e70d2430db526ecf35be2769f
Volume 6
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