School of Medicine and Health Sciences Poster Presentations

Title

RNA Sequencing Identifies Long Non-Coding RNAs Related to Multiple Risk Factors for Cardiovascular Diseases

Poster Number

340

Document Type

Poster

Status

Medical Resident

Abstract Category

Cardiology/Cardiovascular Research

Keywords

cardiovascular disease, hypertension, non-coding RNA, RNA sequencing, atrial fibrillation

Publication Date

Spring 2018

Abstract

INTRODUCTION

Cardiovascular diseases (CVD) remains the major cause of mortality partially because it is frequently silent until it strikes. Only 50% of CVD risk is explained by current risk factors, leaving a significant unidentified risk of CVD. In prior studies, advanced RNA sequencing identified blood RNA biomarkers of coronary artery disease (CAD), which are currently being validated in a multi-center trial. Presently, the RNAseq data was reanalyzed to identify RNA biomarkers of other CVD risks.

METHODS

Patients (112) presenting for elective angiography were consented and whole blood was drawn into an RNA preservative for storage at -80˚C. RNA was isolated, DNAsed, ribosomal RNA-depleted, and sequenced (SeqLL). Reads were aligned to the human transcriptome, counted, and analyzed for differential expression. A total of 96 samples were satisfactory for analysis, with an average of ~5 million informative reads per sample.

RESULTS

Hypertension: 78 transcripts were differentially expressed in hypertensive patients. Many had established relationships with blood pressure regulation, with an interesting change in LINC00467, a known regulator of the DKK axis, and corroborated by a parallel change in dickkopf3 (DKK3). Titin-antisense1 (TTN-AS1), another lncRNA, was also elevated 2-fold in hypertensive patients, and has been associated by GWAS with atrial fibrillation.

Race/ethnicity: African-Americans (AA) are at increased risk of hypertension and stroke. Examination of CAD vs normal in AAs identified 294 DEG, including TTN-AS1. A separate study examining transcripts modulated during heart failure, also observed that TTN-AS1 was regulated.

TTN-AS1 Targets: Analysis of co-expression data suggest that TTN-AS1 modulates certain transcripts by interfering with miRNAs. Several had prior GWAS connections to CVD, including ATP1B1, associated with Long QT syndrome; HDAC9, associated twice with Moyamoya Disease, involving cerebrovascular remodeling and stroke; NME7, associated twice with venous thromboembolism; and SYNPO2L, which is a newly identified GWAS loci for BP regulation and AFib.

CONCLUSIONS

Prior GWAS studies on very large cohorts have identified SNP loci for CVDs, but many have been uninterpretable because they fell within introns, intergenic regions, and/or non-coding transcripts. RNAseq allows us to cross-validate human RNA expression patterns in patients at risk for CVD, with putative risk SNPs, to narrow the candidate list. A top cross-validated hit is TTN-AS1, which is a long non-coding RNA that appears to modulate multiple known risk alleles for CVD, warranting more careful analysis.

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RNA Sequencing Identifies Long Non-Coding RNAs Related to Multiple Risk Factors for Cardiovascular Diseases

INTRODUCTION

Cardiovascular diseases (CVD) remains the major cause of mortality partially because it is frequently silent until it strikes. Only 50% of CVD risk is explained by current risk factors, leaving a significant unidentified risk of CVD. In prior studies, advanced RNA sequencing identified blood RNA biomarkers of coronary artery disease (CAD), which are currently being validated in a multi-center trial. Presently, the RNAseq data was reanalyzed to identify RNA biomarkers of other CVD risks.

METHODS

Patients (112) presenting for elective angiography were consented and whole blood was drawn into an RNA preservative for storage at -80˚C. RNA was isolated, DNAsed, ribosomal RNA-depleted, and sequenced (SeqLL). Reads were aligned to the human transcriptome, counted, and analyzed for differential expression. A total of 96 samples were satisfactory for analysis, with an average of ~5 million informative reads per sample.

RESULTS

Hypertension: 78 transcripts were differentially expressed in hypertensive patients. Many had established relationships with blood pressure regulation, with an interesting change in LINC00467, a known regulator of the DKK axis, and corroborated by a parallel change in dickkopf3 (DKK3). Titin-antisense1 (TTN-AS1), another lncRNA, was also elevated 2-fold in hypertensive patients, and has been associated by GWAS with atrial fibrillation.

Race/ethnicity: African-Americans (AA) are at increased risk of hypertension and stroke. Examination of CAD vs normal in AAs identified 294 DEG, including TTN-AS1. A separate study examining transcripts modulated during heart failure, also observed that TTN-AS1 was regulated.

TTN-AS1 Targets: Analysis of co-expression data suggest that TTN-AS1 modulates certain transcripts by interfering with miRNAs. Several had prior GWAS connections to CVD, including ATP1B1, associated with Long QT syndrome; HDAC9, associated twice with Moyamoya Disease, involving cerebrovascular remodeling and stroke; NME7, associated twice with venous thromboembolism; and SYNPO2L, which is a newly identified GWAS loci for BP regulation and AFib.

CONCLUSIONS

Prior GWAS studies on very large cohorts have identified SNP loci for CVDs, but many have been uninterpretable because they fell within introns, intergenic regions, and/or non-coding transcripts. RNAseq allows us to cross-validate human RNA expression patterns in patients at risk for CVD, with putative risk SNPs, to narrow the candidate list. A top cross-validated hit is TTN-AS1, which is a long non-coding RNA that appears to modulate multiple known risk alleles for CVD, warranting more careful analysis.