# Computational and functional strategies to decipher lncRNAs in human atherosclerosis

> **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2022 · $660,276

## Abstract

This proposal addresses knowledge gaps in cell-specific function and disease causation of long non-coding
RNAs (lncRNAs) in human atherosclerosis. Despite prominent examples of functional lncRNAs in cardiovascular
diseases (CVD), their lack of conservation and cell-specificity have limited our understanding of their role in CVD.
These challenges are particularly problematic in human atherosclerosis which is characterized by complex multi-
cellular lesions. Further, recent single cell (sc)RNAseq data including our preliminary studies suggest that,
relative to mRNAs, lncRNA expression in primary human cells may be restricted to key cell subpopulations. An
overarching hypothesis is that many human lncRNAs modulate atherosclerosis and CVD risk via their
discrete expression and function in specific lesion cell subpopulations. Thus, more precise knowledge of
lncRNA cell-specific relationship to human atherosclerosis is required to drive mechanism-based clinical
translation. Here we address key questions for lncRNAs in human atherosclerosis and CVD risk. First, which
lncRNAs are expressed in human lesions and associate with clinical CVD? Second, for lncRNAs expressed in
human lesions, in which specific lesion cell subpopulation are they functional? In Aim 1, we will address the first
issue by analyzing differential expression of lncRNAs through deep RNAseq of a large nested case-control
(n=260 with “symptomatic/unstable” and n=260 with “asymptomatic/stable” plaques) study of carotid
atherosclerosis from the Munich Vascular Biobank (MVB). We will also determine whether lncRNAs demonstrate
differential allele specific expression (ASE) between symptomatic/unstable vs. asymptomatic/stable plaques and
if cis-eQTL variants for lncRNAs with differential ASE are associated with coronary heart disease (CHD) in large
public genetic datasets. Prioritized lncRNAs will undergo cell-specific functional genomic follow-up in human
vascular cells including our human induced pluripotent stem cell (hIPSC) vascular models. In Aim 2, we propose
to use a novel deconvolution algorithm and integration of large-scale bulk RNAseq data from Aim 1 with selective
single cell (sc)RNAseq of fresh lesions (n=60) to identify subpopulations and their lncRNAs that associate with
symptomatic/unstable plaques and have causal genetic relationships to CHD. ScRNAseq of the fresh carotid
lesions will be used to cluster cells and identify lesion subpopulations. Result from this analysis will permit
computational deconvolution of the cell subpopulation composition of all MVB bulk RNAseq lesions (n=520) and
assignment of subpopulation-specific lncRNA expression and relationship to symptomatic/unstable plaques.
Subpopulation-specific lncRNA cis-eQTLs also will be identified and used to determine their causal relationship
to CHD in genetic datasets. These findings, coupled to subpopulation-specific functional studies, will define
subpopulation-specific lncRNA functions in human atherosclerosis. Our...

## Key facts

- **NIH application ID:** 10347301
- **Project number:** 5R01HL150359-03
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Mingyao Li
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $660,276
- **Award type:** 5
- **Project period:** 2020-02-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10347301

## Citation

> US National Institutes of Health, RePORTER application 10347301, Computational and functional strategies to decipher lncRNAs in human atherosclerosis (5R01HL150359-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10347301. Licensed CC0.

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