Cardiovascular DiseaseNCT03225183
RNA Sequencing in the Framingham Heart Study Third Generation Cohort Exam 2
An observational study of Cardiovascular Disease and Hypertension, run by National Heart, Lung, and Blood Institute (NHLBI) at 1 site in United States.
Trial summary
Background: The Framingham Heart Study (FHS) was initiated by the U.S Public Health Service in 1948 and turned over to the newly established National Heart Institute in 1951. The FHS is now jointly led by the National Heart, Lung, and Blood Institute and Boston University. Read more about this study
- Who is it for?
- Ages 21 to 100 years
- Conditions the study is for
- Cardiovascular Disease, Hypertension
- How many people
- 1,700 participants
- Where
- 1 siteUnited States
- Study dates
- 14 Jul 2017to 17 Jun 2019
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 21 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Framingham Heart Study participants
Who may be able to join
- To accomplish the Aims of this project we propose to conduct RNA-seq on FHS Third Generation cohort participants with WGS as part of TOPMed. This can only be accomplished in FHS Third Generation cohort participants who attended exam 2 when PaxGene tubes were collected for RNA isolation. Therefore, we propose to conduct RNA-seq on FHS Third Generation cohort exam 2 attendees with PaxGene tubes (total n=3300) and in whom we will have direct or imputed WGS from TOPMed (n=1700).
Who cannot join
None listed.
Trial locations and contacts
1 site in 1 country.
United States1 site
Framingham Heart Study
Framingham, Massachusetts, 01702
About this study
Official title: An RNA Sequencing Study in the Framingham Heart Study Third Generation Cohort Exam 2
Background:
The Framingham Heart Study (FHS) was initiated by the U.S Public Health Service in 1948 and turned over to the newly established National Heart Institute in 1951. The FHS is now jointly led by the National Heart, Lung, and Blood Institute and Boston University. The FHS currently studies risk factors, and the genetics of heart and blood vessel disease, and other health conditions in three generations of study participants. Scientists want to use the data collected from this study to do more research. They want to use a technique that determines the sequence of ribonucleic acid (RNA) molecules.
Read more
Objective:
To study genes related to certain diseases and health conditions. These include heart and blood vessel diseases, lung and blood diseases, stroke, memory loss, and cancer.
Eligibility:
People in the FHS Third Generation cohort who already attended exam 2.
Design:
Researchers will study samples that have already been collected in the FHS. There will be no active examination or burden to participants. During FHS visits, participants gave blood samples. They gave permission for the blood to be used for genetic research. RNA will be generated from the samples. They will be given a new ID separate from any personal data. They will be stored in a secure FHS lab. The samples will be analyzed. Only certified researchers can access them.
No study participants will be contacted in relation to this project.
...
Read the detailed description
RNA sequencing (RNA-seq) is a powerful tool to evaluate the transcriptome with incredible depth and clarity. As compared to gene expression arrays, RNA-seq allows the identification and quantification of a larger set of known transcripts (including long non-coding RNAs [lncRNAs]), novel transcripts, alternative splicing events, and allele-specific expression (including parent-of-origin allele-specific expression); all with a vastly higher signal-to-noise ratio compared to gene expression profiling via microarrays. The relations of these transcriptomic features to health and disease in very large population studies is underexplored. It is our belief that this proposed project will identify new biomarkers of disease risk and provide insights into disease pathogenesis. The Framingham Heart Study (FHS) is uniquely suited to conduct RNA-seq because of the wealth of existing phenotype resources in conjunction with whole genome sequence (WGS) data from TOPMed and methylomic data, data and other omics data that can be leveraged at extremely low cost to maximize the impact of an investment in RNA-seq.
The advent of high-throughput RNA-seq technology has revolutionized transcriptomic profiling at an unprecedented scale, leading to the discovery of new RNA species and deepening our understanding of transcriptomic dynamics. Compared to microarray-based RNA profiling, RNA-seq is appreciated for its ability to reveal the complexity of the transcriptome, encompassing previously unknown coding and lncRNA species, novel transcribed regions, alternative splicing, allele-specific expression, and fusion genes This project proposes to build upon and extend the work conducted using gene expression arrays in the FHS by examining complex transcriptomic features that cannot be determined using microarray-based expression data.
In this proposal we focus on expression levels of protein-coding RNAs, lncRNAs, alternative splicing, and allele-specific expression. There are ~18,000 mRNA transcripts at the gene-level for protein-coding RNAs. Alternative splicing is a tightly regulated process that produces different mRNA isoforms from genes that contain multiple exons. One major application of RNA-seq is to detect even subtle differences in exon splicing. lncRNAs are non-protein coding transcripts longer than 200 nucleotides and have been implicated in many biological process. For example, some lncRNAs impact the expression of nearby protein-coding genes, some can bind to enzymes regulating transcription patterns, and other lncRNAs are precursors of small RNAs. A number of computational methods have been developed to detect alternative splicing and lncRNAs from RNA-seq data. Identification of alternative splicing and lncRNAs will be standardized across TOPMed studies and we will conduct analyses on centrally called splice data as well as lncRNAs. Allele-specific expression (ASE), which cannot be measured using microarrays, allows the differentiation between transcripts from the two haplotypes of an individual at heterozygous sites. ASE enables a more granular understanding of how a disease-related genotype affects gene expression. ASE has been linked to human disease in small sample sets but has not been examined fully in large populations. Standard
bioinformatics tools have been developed to study ASE. In addition, with TOPMed WGS data on parents from the FHS Offspring cohort, it will be possible to study parent-of-origin ASE, thus furthering our ability to dissect factors that contribute to the transgenerational inheritance of cardiometabolic disease.
In this Application, we propose to extend the investigation of transcriptomics in FHS Third Generation cohort exam 2 participants. The aims of conducting RNA-seq in the FHS Third Generation cohort mirror and extend those of our original microarray-based gene expression profiling. Specifically, we will examine the association of complex transcriptomic variation to: 1) cardiometabolic disease outcomes, 2) genetic sequence variation, and 3) multiple layers of omic data (Aims 1-3). With the proposed RNA-seq data, investigators as well as the general scientific community (via dbGaP access) will have the ability to study transcriptomics from different perspectives always leveraging existing resources to advance the scientific value of this project. To maximize the return on investment, sequencing will be performed by a designated TOPMed RNA-seq laboratory, and the aims of this project will be coordinated with other
TOPMed studies that are conducting RNA-seq.
- Conditions
- Cardiovascular Disease, Hypertension
- Keywords
- TOPMed, Blood Pressure, Long Noncoding RNA, Gene Expression, MicroRNA, Natural History
- Medical subject headings
- Cardiovascular Diseases, Hypertension
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 1 | Framingham Heart Study participants |
What is being measured
The primary outcome is the main question the study is designed to answer.
1. To relate transcriptomic variation to CVD and its risk factors (blood pressure, lipids, glycemia, adiposity, smoking, and alcohol), including evaluating RNAs as biomarkers of risk and establishing causation via Mendelian randomization
Will look at CVD events related to RNA sequence. a. Characterize the relation of protein-coding gene expression to CVD and its risk factors; b. Characterize the relations of lncRNAs to CVD and risk factors; c. Characterize the relations of RNA splicing variation to CVD and its risk factors; d. Characterize the relations of allele-specific expression, and parent-oforigin allele specific expression, to CVD and its risk factors
Measured: Observational
2. To determine the association of genetic sequence variation from whole genome sequencing with gene expression via RNA-seq.
Will look at CVD events related to RNA sequence and add gene expression results to analysisa. Identify genetic variants associated with expression of protein coding RNAs (eQTLs); b. Identify genetic variants associated with alternative splicing (sQTLS); c. Identify genetic variants associated with expression of lncRNAs
Measured: Observational
3. To relate complex transcriptomic variation to other blood-based omics
Will look at CVD events related to RNA sequence and add Metabolic profiling data to analysis modela. Determine the association of transcriptomic variation with DNA methylation (methylome); b. Determine the association of transcriptomic variation with circulating protein levels (proteome); c. Determine the association of transcriptomic variation with circulating metabolites (metabolome)
Measured: Observational
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Jul 2017
- Study start14 Jul 2017
- Primary completion15 Mar 2019
- Study completion17 Jun 2019
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Cardiovascular DiseaseStudies of the same condition, open and under way.
- More trials run by National Heart, Lung, and Blood Institute (NHLBI)The sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 1,700 participants (actual)
Sponsor and investigators
- Sponsor type
- US National Institutes of Health
- Responsible party
- Sponsor
- Investigators
- Daniel Levy, M.D., Principal investigator, National Heart, Lung, and Blood Institute (NHLBI)
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03225183
- Sponsor's protocol ID
- 999917133
- Other IDs
- 17-H-N133
- Status last verified
- Jun 2022
- First submitted
- 20 Jul 2017
- Last updated
- 15 Jun 2022
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Yao C, Chen BH, Joehanes R, Otlu B, Zhang X, Liu C, Huan T, Tastan O, Cupples LA, Meigs JB, Fox CS, Freedman JE, Courchesne P, O'Donnell CJ, Munson PJ, Keles S, Levy D. Integromic analysis of genetic variation and gene expression identifies networks for cardiovascular disease phenotypes. Circulation. 2015 Feb 10;131(6):536-49. doi: 10.1161/CIRCULATIONAHA.114.010696. Epub 2014 Dec 22.
PubMed 25533967Huan T, Esko T, Peters MJ, Pilling LC, Schramm K, Schurmann C, Chen BH, Liu C, Joehanes R, Johnson AD, Yao C, Ying SX, Courchesne P, Milani L, Raghavachari N, Wang R, Liu P, Reinmaa E, Dehghan A, Hofman A, Uitterlinden AG, Hernandez DG, Bandinelli S, Singleton A, Melzer D, Metspalu A, Carstensen M, Grallert H, Herder C, Meitinger T, Peters A, Roden M, Waldenberger M, Dorr M, Felix SB, Zeller T; International Consortium for Blood Pressure GWAS (ICBP); Vasan R, O'Donnell CJ, Munson PJ, Yang X, Prokisch H, Volker U, van Meurs JB, Ferrucci L, Levy D. A meta-analysis of gene expression signatures of blood pressure and hypertension. PLoS Genet. 2015 Mar 18;11(3):e1005035. doi: 10.1371/journal.pgen.1005035. eCollection 2015 Mar.
PubMed 25785607Joehanes R, Johnson AD, Barb JJ, Raghavachari N, Liu P, Woodhouse KA, O'Donnell CJ, Munson PJ, Levy D. Gene expression analysis of whole blood, peripheral blood mononuclear cells, and lymphoblastoid cell lines from the Framingham Heart Study. Physiol Genomics. 2012 Jan 18;44(1):59-75. doi: 10.1152/physiolgenomics.00130.2011. Epub 2011 Nov 1.
PubMed 22045913
Study at a glance
From the registry record, last updated by the sponsor on 15 Jun 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- An RNA Sequencing Study in the Framingham Heart Study Third Generation Cohort Exam 2
- ClinicalTrials.gov ID
- NCT03225183
- Acronym / sponsor ID
- 999917133
- Conditions
- Cardiovascular Disease, Hypertension
- Keywords
- TOPMed, Blood Pressure, Long Noncoding RNA, Gene Expression, MicroRNA, Natural History
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,700 participants (actual)
- Lead sponsor
- National Heart, Lung, and Blood Institute (NHLBI)US National Institutes of Health
- Study start
- 14 Jul 2017 (actual)
- Primary completion
- 15 Mar 2019 (actual)
- Study completion
- 17 Jun 2019 (actual)
- First posted
- 21 Jul 2017 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Background:
The Framingham Heart Study (FHS) was initiated by the U.S Public Health Service in 1948 and turned over to the newly established National Heart Institute in 1951. The FHS is now jointly led by the National Heart, Lung, and Blood Institute and Boston University. The FHS currently studies risk factors, and the genetics of heart and blood vessel disease, and other health conditions in three generations of study participants. Scientists want to use the data collected from this study to do more research. They want to use a technique that determines the sequence of ribonucleic acid (RNA) molecules.
Objective:
To study genes related to certain diseases and health conditions. These include heart and blood vessel diseases, lung and blood diseases, stroke, memory loss, and cancer.
Eligibility:
People in the FHS Third Generation cohort who already attended exam 2.
Design:
Researchers will study samples that have already been collected in the FHS. There will be no active examination or burden to participants. During FHS visits, participants gave blood samples. They gave permission for the blood to be used for genetic research. RNA will be generated from the samples. They will be given a new ID separate from any personal data. They will be stored in a secure FHS lab. The samples will be analyzed. Only certified researchers can access them.
No study participants will be contacted in relation to this project.
...
Detailed description
RNA sequencing (RNA-seq) is a powerful tool to evaluate the transcriptome with incredible depth and clarity. As compared to gene expression arrays, RNA-seq allows the identification and quantification of a larger set of known transcripts (including long non-coding RNAs [lncRNAs]), novel transcripts, alternative splicing events, and allele-specific expression (including parent-of-origin allele-specific expression); all with a vastly higher signal-to-noise ratio compared to gene expression profiling via microarrays. The relations of these transcriptomic features to health and disease in very large population studies is underexplored. It is our belief that this proposed project will identify new biomarkers of disease risk and provide insights into disease pathogenesis. The Framingham Heart Study (FHS) is uniquely suited to conduct RNA-seq because of the wealth of existing phenotype resources in conjunction with whole genome sequence (WGS) data from TOPMed and methylomic data, data and other omics data that can be leveraged at extremely low cost to maximize the impact of an investment in RNA-seq.
The advent of high-throughput RNA-seq technology has revolutionized transcriptomic profiling at an unprecedented scale, leading to the discovery of new RNA species and deepening our understanding of transcriptomic dynamics. Compared to microarray-based RNA profiling, RNA-seq is appreciated for its ability to reveal the complexity of the transcriptome, encompassing previously unknown coding and lncRNA species, novel transcribed regions, alternative splicing, allele-specific expression, and fusion genes This project proposes to build upon and extend the work conducted using gene expression arrays in the FHS by examining complex transcriptomic features that cannot be determined using microarray-based expression data.
In this proposal we focus on expression levels of protein-coding RNAs, lncRNAs, alternative splicing, and allele-specific expression. There are ~18,000 mRNA transcripts at the gene-level for protein-coding RNAs. Alternative splicing is a tightly regulated process that produces different mRNA isoforms from genes that contain multiple exons. One major application of RNA-seq is to detect even subtle differences in exon splicing. lncRNAs are non-protein coding transcripts longer than 200 nucleotides and have been implicated in many biological process. For example, some lncRNAs impact the expression of nearby protein-coding genes, some can bind to enzymes regulating transcription patterns, and other lncRNAs are precursors of small RNAs. A number of computational methods have been developed to detect alternative splicing and lncRNAs from RNA-seq data. Identification of alternative splicing and lncRNAs will be standardized across TOPMed studies and we will conduct analyses on centrally called splice data as well as lncRNAs. Allele-specific expression (ASE), which cannot be measured using microarrays, allows the differentiation between transcripts from the two haplotypes of an individual at heterozygous sites. ASE enables a more granular understanding of how a disease-related genotype affects gene expression. ASE has been linked to human disease in small sample sets but has not been examined fully in large populations. Standard
bioinformatics tools have been developed to study ASE. In addition, with TOPMed WGS data on parents from the FHS Offspring cohort, it will be possible to study parent-of-origin ASE, thus furthering our ability to dissect factors that contribute to the transgenerational inheritance of cardiometabolic disease.
In this Application, we propose to extend the investigation of transcriptomics in FHS Third Generation cohort exam 2 participants. The aims of conducting RNA-seq in the FHS Third Generation cohort mirror and extend those of our original microarray-based gene expression profiling. Specifically, we will examine the association of complex transcriptomic variation to: 1) cardiometabolic disease outcomes, 2) genetic sequence variation, and 3) multiple layers of omic data (Aims 1-3). With the proposed RNA-seq data, investigators as well as the general scientific community (via dbGaP access) will have the ability to study transcriptomics from different perspectives always leveraging existing resources to advance the scientific value of this project. To maximize the return on investment, sequencing will be performed by a designated TOPMed RNA-seq laboratory, and the aims of this project will be coordinated with other
TOPMed studies that are conducting RNA-seq.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| 1 | – | –Framingham Heart Study participants |
Who may qualify
- Ages
- 21 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Framingham Heart Study participants
Key inclusion criteria (1 listed)
- To accomplish the Aims of this project we propose to conduct RNA-seq on FHS Third Generation cohort participants with WGS as part of TOPMed. This can only be accomplished in FHS Third Generation cohort participants who attended exam 2 when PaxGene tubes were collected for RNA isolation. Therefore, we propose to conduct RNA-seq on FHS Third Generation cohort exam 2 attendees with PaxGene tubes (total n=3300) and in whom we will have direct or imputed WGS from TOPMed (n=1700).
Key exclusion criteria (0 listed)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
1. To relate transcriptomic variation to CVD and its risk factors (blood pressure, lipids, glycemia, adiposity, smoking, and alcohol), including evaluating RNAs as biomarkers of risk and establishing causation via Mendelian randomization
Time frame: Observational
Will look at CVD events related to RNA sequence. a. Characterize the relation of protein-coding gene expression to CVD and its risk factors; b. Characterize the relations of lncRNAs to CVD and risk factors; c. Characterize the relations of RNA splicing variation to CVD and its risk factors; d. Characterize the relations of allele-specific expression, and parent-oforigin allele specific expression, to CVD and its risk factors
2. To determine the association of genetic sequence variation from whole genome sequencing with gene expression via RNA-seq.
Time frame: Observational
Will look at CVD events related to RNA sequence and add gene expression results to analysisa. Identify genetic variants associated with expression of protein coding RNAs (eQTLs); b. Identify genetic variants associated with alternative splicing (sQTLS); c. Identify genetic variants associated with expression of lncRNAs
3. To relate complex transcriptomic variation to other blood-based omics
Time frame: Observational
Will look at CVD events related to RNA sequence and add Metabolic profiling data to analysis modela. Determine the association of transcriptomic variation with DNA methylation (methylome); b. Determine the association of transcriptomic variation with circulating protein levels (proteome); c. Determine the association of transcriptomic variation with circulating metabolites (metabolome)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Jun 2022.
- Background: PubMed 25533967Yao C, Chen BH, Joehanes R, Otlu B, Zhang X, Liu C, Huan T, Tastan O, Cupples LA, Meigs JB, Fox CS, Freedman JE, Courchesne P, O'Donnell CJ, Munson PJ, Keles S, Levy D. Integromic analysis of genetic variation and gene expression identifies networks for cardiovascular disease phenotypes. Circulation. 2015 Feb 10;131(6):536-49. doi: 10.1161/CIRCULATIONAHA.114.010696. Epub 2014 Dec 22.
- Background: PubMed 25785607Huan T, Esko T, Peters MJ, Pilling LC, Schramm K, Schurmann C, Chen BH, Liu C, Joehanes R, Johnson AD, Yao C, Ying SX, Courchesne P, Milani L, Raghavachari N, Wang R, Liu P, Reinmaa E, Dehghan A, Hofman A, Uitterlinden AG, Hernandez DG, Bandinelli S, Singleton A, Melzer D, Metspalu A, Carstensen M, Grallert H, Herder C, Meitinger T, Peters A, Roden M, Waldenberger M, Dorr M, Felix SB, Zeller T; International Consortium for Blood Pressure GWAS (ICBP); Vasan R, O'Donnell CJ, Munson PJ, Yang X, Prokisch H, Volker U, van Meurs JB, Ferrucci L, Levy D. A meta-analysis of gene expression signatures of blood pressure and hypertension. PLoS Genet. 2015 Mar 18;11(3):e1005035. doi: 10.1371/journal.pgen.1005035. eCollection 2015 Mar.
- Background: PubMed 22045913Joehanes R, Johnson AD, Barb JJ, Raghavachari N, Liu P, Woodhouse KA, O'Donnell CJ, Munson PJ, Levy D. Gene expression analysis of whole blood, peripheral blood mononuclear cells, and lymphoblastoid cell lines from the Framingham Heart Study. Physiol Genomics. 2012 Jan 18;44(1):59-75. doi: 10.1152/physiolgenomics.00130.2011. Epub 2011 Nov 1.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Daniel Levy, M.D. principal investigator
National Heart, Lung, and Blood Institute (NHLBI)
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Cardiovascular Disease and Hypertension, run by National Heart, Lung, and Blood Institute (NHLBI) at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 0 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 15 Jun 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
1. To relate transcriptomic variation to CVD and its risk factors (blood pressure, lipids, glycemia, adiposity, smoking, and alcohol), including evaluating RNAs as biomarkers of risk and establishing causation via Mendelian randomization (time frame: Observational). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03225183, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Jun 2022.