Bioinformatic and genomic approaches to study cardiovascular diseases

Research output: ThesisDoctoral ThesisCollection of Articles

Abstract

Next generation sequencing (NGS) technologies provide the potential for developing high-throughput and low-cost platforms for medical research and diagnostics, which is expected to accelerate the findings of root causes and treatments of human diseases. In addition to short read lengths of NGS technology; another limiting factor to clinical applications of genomic NGS is downstream bioinformatics analysis. Several challenging computation problems have to be solved before we realize the full potential of NGS technology. These include management of large quantities of data, efficient analyses, fusion of data from various sources, and interpretation of identified variants. Endothelial cell (EC) dysfunction is a hallmark of several cardiovascular diseases (CVDs). Loss of functional peroxisome proliferator-activated receptor gamma (PPARγ) leads to EC dysfunction, and development of pulmonary arterial hypertension (PAH). However, the role of PPARγ in angiogenesis in the development of PAH is unknown. In this study, RNA sequencing and bioinformatic strategies were used to quantify and reveal global gene expression changes associated with loss of PPARγ, in a bid to unravel the mechanisms by which PPARγ modulates endothelial homeostasis, regulates angiogenic response, and could contribute to the pathobiology of human cardiovascular diseases. This study reveals, for the first time in an animal model, that loss of PPARγ leads to attenuated ECs migratory capacity and decreased angiogenic potential. Implemented bioinformatics approach revealed a novel molecular mechanism and novel downstream target gene for PPARγ. Furthermore, this study reports the first genetic analysis of dilated cardiomyopathy (DCM) patients in Finland; evaluates the efficacy of NGS in genetic diagnostics of DCM patients, and demonstrates the need for a rigorous and clinically oriented bioinformatics variant assessment and interpretation strategy. In addition, bioinformatics data mining approach was used to evaluate the significance of titin (TTN) truncating variants (TTNtv) in the pathogenesis of DCM. Mutations in genes encoding sarcomere proteins are the leading cause of DCM, with TTNtv accounting for ~21% of DCM cases. Clinical significance of variants in cardiomyopathy-associated genes is difficult to assess due to population genetic variation, and diagnostic yield of genetic testing is not well understood among DCM patients. Moreover, the genetic profile of DCM in Finnish population is poorly understood. In this study, a novel targeted resequencing approach, oligonucleotide-selective sequencing (OS-Seq), was used to investigate the genetic landscape of DCM among Finnish patients, and the approach enabled genetic diagnosis for 35.2% of the patients. Notably, 17.2% of Finnish DCM patients had TTNtv predicted to cause loss of function. Truncating TTN mutations, especially in A-band region, represent the most common cause of DCM. Clinical interpretation of these variants can be challenging, as these variants are also present in reference populations. Meta analyses of TTNtv reported in largest available reference population database, and those identified in accumulated DCM cohorts showed that 50 - 53% of TTNtv in the reference population were located in low transcript count regions, thus, possessing low likelihood of being disease-causing. On this basis, a variant assessment strategy that prioritizes TTNtv affecting at least five transcripts of the gene was developed.
Original languageEnglish
Awarding Institution
  • University of Helsinki
Supervisors/Advisors
  • Alastalo, Tero-Pekka, Supervisor
Award date29 Apr 2016
Place of PublicationHelsinki
Publisher
Print ISBNs978-951-51-2004-5
Electronic ISBNs978-951-51-2005-2
Publication statusPublished - 2016
MoE publication typeG5 Doctoral dissertation (article)

Fields of Science

  • 3123 Gynaecology and paediatrics
  • 3111 Biomedicine

Cite this

@phdthesis{c3d5bc3c2e99458db6d8e72e2977191f,
title = "Bioinformatic and genomic approaches to study cardiovascular diseases",
abstract = "Next generation sequencing (NGS) technologies provide the potential for developing high-throughput and low-cost platforms for medical research and diagnostics, which is expected to accelerate the findings of root causes and treatments of human diseases. In addition to short read lengths of NGS technology; another limiting factor to clinical applications of genomic NGS is downstream bioinformatics analysis. Several challenging computation problems have to be solved before we realize the full potential of NGS technology. These include management of large quantities of data, efficient analyses, fusion of data from various sources, and interpretation of identified variants. Endothelial cell (EC) dysfunction is a hallmark of several cardiovascular diseases (CVDs). Loss of functional peroxisome proliferator-activated receptor gamma (PPARγ) leads to EC dysfunction, and development of pulmonary arterial hypertension (PAH). However, the role of PPARγ in angiogenesis in the development of PAH is unknown. In this study, RNA sequencing and bioinformatic strategies were used to quantify and reveal global gene expression changes associated with loss of PPARγ, in a bid to unravel the mechanisms by which PPARγ modulates endothelial homeostasis, regulates angiogenic response, and could contribute to the pathobiology of human cardiovascular diseases. This study reveals, for the first time in an animal model, that loss of PPARγ leads to attenuated ECs migratory capacity and decreased angiogenic potential. Implemented bioinformatics approach revealed a novel molecular mechanism and novel downstream target gene for PPARγ. Furthermore, this study reports the first genetic analysis of dilated cardiomyopathy (DCM) patients in Finland; evaluates the efficacy of NGS in genetic diagnostics of DCM patients, and demonstrates the need for a rigorous and clinically oriented bioinformatics variant assessment and interpretation strategy. In addition, bioinformatics data mining approach was used to evaluate the significance of titin (TTN) truncating variants (TTNtv) in the pathogenesis of DCM. Mutations in genes encoding sarcomere proteins are the leading cause of DCM, with TTNtv accounting for ~21{\%} of DCM cases. Clinical significance of variants in cardiomyopathy-associated genes is difficult to assess due to population genetic variation, and diagnostic yield of genetic testing is not well understood among DCM patients. Moreover, the genetic profile of DCM in Finnish population is poorly understood. In this study, a novel targeted resequencing approach, oligonucleotide-selective sequencing (OS-Seq), was used to investigate the genetic landscape of DCM among Finnish patients, and the approach enabled genetic diagnosis for 35.2{\%} of the patients. Notably, 17.2{\%} of Finnish DCM patients had TTNtv predicted to cause loss of function. Truncating TTN mutations, especially in A-band region, represent the most common cause of DCM. Clinical interpretation of these variants can be challenging, as these variants are also present in reference populations. Meta analyses of TTNtv reported in largest available reference population database, and those identified in accumulated DCM cohorts showed that 50 - 53{\%} of TTNtv in the reference population were located in low transcript count regions, thus, possessing low likelihood of being disease-causing. On this basis, a variant assessment strategy that prioritizes TTNtv affecting at least five transcripts of the gene was developed.",
keywords = "3123 Gynaecology and paediatrics, 3111 Biomedicine",
author = "Akinrinade, {Oyediran Olulana}",
note = "M1 - 82 s. + liitteet Helsingin yliopisto Volume: Proceeding volume:",
year = "2016",
language = "English",
isbn = "978-951-51-2004-5",
series = "Dissertationes Scholae Doctoralis Ad Sanitatem Investigandam Universitatis Helsinkiensis",
publisher = "University of Helsinki",
number = "19/2016",
address = "Finland",
school = "University of Helsinki",

}

Bioinformatic and genomic approaches to study cardiovascular diseases. / Akinrinade, Oyediran Olulana.

Helsinki : University of Helsinki, 2016. 82 p.

Research output: ThesisDoctoral ThesisCollection of Articles

TY - THES

T1 - Bioinformatic and genomic approaches to study cardiovascular diseases

AU - Akinrinade, Oyediran Olulana

N1 - M1 - 82 s. + liitteet Helsingin yliopisto Volume: Proceeding volume:

PY - 2016

Y1 - 2016

N2 - Next generation sequencing (NGS) technologies provide the potential for developing high-throughput and low-cost platforms for medical research and diagnostics, which is expected to accelerate the findings of root causes and treatments of human diseases. In addition to short read lengths of NGS technology; another limiting factor to clinical applications of genomic NGS is downstream bioinformatics analysis. Several challenging computation problems have to be solved before we realize the full potential of NGS technology. These include management of large quantities of data, efficient analyses, fusion of data from various sources, and interpretation of identified variants. Endothelial cell (EC) dysfunction is a hallmark of several cardiovascular diseases (CVDs). Loss of functional peroxisome proliferator-activated receptor gamma (PPARγ) leads to EC dysfunction, and development of pulmonary arterial hypertension (PAH). However, the role of PPARγ in angiogenesis in the development of PAH is unknown. In this study, RNA sequencing and bioinformatic strategies were used to quantify and reveal global gene expression changes associated with loss of PPARγ, in a bid to unravel the mechanisms by which PPARγ modulates endothelial homeostasis, regulates angiogenic response, and could contribute to the pathobiology of human cardiovascular diseases. This study reveals, for the first time in an animal model, that loss of PPARγ leads to attenuated ECs migratory capacity and decreased angiogenic potential. Implemented bioinformatics approach revealed a novel molecular mechanism and novel downstream target gene for PPARγ. Furthermore, this study reports the first genetic analysis of dilated cardiomyopathy (DCM) patients in Finland; evaluates the efficacy of NGS in genetic diagnostics of DCM patients, and demonstrates the need for a rigorous and clinically oriented bioinformatics variant assessment and interpretation strategy. In addition, bioinformatics data mining approach was used to evaluate the significance of titin (TTN) truncating variants (TTNtv) in the pathogenesis of DCM. Mutations in genes encoding sarcomere proteins are the leading cause of DCM, with TTNtv accounting for ~21% of DCM cases. Clinical significance of variants in cardiomyopathy-associated genes is difficult to assess due to population genetic variation, and diagnostic yield of genetic testing is not well understood among DCM patients. Moreover, the genetic profile of DCM in Finnish population is poorly understood. In this study, a novel targeted resequencing approach, oligonucleotide-selective sequencing (OS-Seq), was used to investigate the genetic landscape of DCM among Finnish patients, and the approach enabled genetic diagnosis for 35.2% of the patients. Notably, 17.2% of Finnish DCM patients had TTNtv predicted to cause loss of function. Truncating TTN mutations, especially in A-band region, represent the most common cause of DCM. Clinical interpretation of these variants can be challenging, as these variants are also present in reference populations. Meta analyses of TTNtv reported in largest available reference population database, and those identified in accumulated DCM cohorts showed that 50 - 53% of TTNtv in the reference population were located in low transcript count regions, thus, possessing low likelihood of being disease-causing. On this basis, a variant assessment strategy that prioritizes TTNtv affecting at least five transcripts of the gene was developed.

AB - Next generation sequencing (NGS) technologies provide the potential for developing high-throughput and low-cost platforms for medical research and diagnostics, which is expected to accelerate the findings of root causes and treatments of human diseases. In addition to short read lengths of NGS technology; another limiting factor to clinical applications of genomic NGS is downstream bioinformatics analysis. Several challenging computation problems have to be solved before we realize the full potential of NGS technology. These include management of large quantities of data, efficient analyses, fusion of data from various sources, and interpretation of identified variants. Endothelial cell (EC) dysfunction is a hallmark of several cardiovascular diseases (CVDs). Loss of functional peroxisome proliferator-activated receptor gamma (PPARγ) leads to EC dysfunction, and development of pulmonary arterial hypertension (PAH). However, the role of PPARγ in angiogenesis in the development of PAH is unknown. In this study, RNA sequencing and bioinformatic strategies were used to quantify and reveal global gene expression changes associated with loss of PPARγ, in a bid to unravel the mechanisms by which PPARγ modulates endothelial homeostasis, regulates angiogenic response, and could contribute to the pathobiology of human cardiovascular diseases. This study reveals, for the first time in an animal model, that loss of PPARγ leads to attenuated ECs migratory capacity and decreased angiogenic potential. Implemented bioinformatics approach revealed a novel molecular mechanism and novel downstream target gene for PPARγ. Furthermore, this study reports the first genetic analysis of dilated cardiomyopathy (DCM) patients in Finland; evaluates the efficacy of NGS in genetic diagnostics of DCM patients, and demonstrates the need for a rigorous and clinically oriented bioinformatics variant assessment and interpretation strategy. In addition, bioinformatics data mining approach was used to evaluate the significance of titin (TTN) truncating variants (TTNtv) in the pathogenesis of DCM. Mutations in genes encoding sarcomere proteins are the leading cause of DCM, with TTNtv accounting for ~21% of DCM cases. Clinical significance of variants in cardiomyopathy-associated genes is difficult to assess due to population genetic variation, and diagnostic yield of genetic testing is not well understood among DCM patients. Moreover, the genetic profile of DCM in Finnish population is poorly understood. In this study, a novel targeted resequencing approach, oligonucleotide-selective sequencing (OS-Seq), was used to investigate the genetic landscape of DCM among Finnish patients, and the approach enabled genetic diagnosis for 35.2% of the patients. Notably, 17.2% of Finnish DCM patients had TTNtv predicted to cause loss of function. Truncating TTN mutations, especially in A-band region, represent the most common cause of DCM. Clinical interpretation of these variants can be challenging, as these variants are also present in reference populations. Meta analyses of TTNtv reported in largest available reference population database, and those identified in accumulated DCM cohorts showed that 50 - 53% of TTNtv in the reference population were located in low transcript count regions, thus, possessing low likelihood of being disease-causing. On this basis, a variant assessment strategy that prioritizes TTNtv affecting at least five transcripts of the gene was developed.

KW - 3123 Gynaecology and paediatrics

KW - 3111 Biomedicine

M3 - Doctoral Thesis

SN - 978-951-51-2004-5

T3 - Dissertationes Scholae Doctoralis Ad Sanitatem Investigandam Universitatis Helsinkiensis

PB - University of Helsinki

CY - Helsinki

ER -

Akinrinade OO. Bioinformatic and genomic approaches to study cardiovascular diseases. Helsinki : University of Helsinki, 2016. 82 p. (Dissertationes Scholae Doctoralis Ad Sanitatem Investigandam Universitatis Helsinkiensis; 19/2016 ).