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Whole genome sequence analysis of long non-coding RNAs for plasma lipid traits

Authors
Yuxuan Wang, Margaret Sunitha Selvaraj, Pradeep Natarajan, Gina M Peloso
Name and Date of Professional Meeting
ASHG (October 27, 2022)
Associated paper proposal(s)
Working Group(s)
Abstract Text
Background. Elevated blood lipids are heritable risk factors and major modifiable cause of cardiovascular disease. While long non-coding RNAs
(lncRNAs) have important regulatory functions for lipid metabolism in model systems, the relationship between genetic variation in lncRNAs and
blood lipid levels in humans is not well understood. We now utilize large-scale whole genome sequencing (WGS) studies and new statistical
methods for variant set tests to assess the association between lncRNAs across the genome and plasma lipid traits. Methods. We analyzed
66,329 individuals with TOPMed freeze8 WGS data and lipid levels (LDL-C, HDL-C, TC and TG). We defined lncRNA testing units by integrating
annotations from four different genome annotation projects: GENCODE (v38), FANTOM CAT(robust), NONCODE (v6), and lncRNAKB (v7). We
aggregated rare (MAF < 1%) variants for each lncRNA based on the lncRNA genomic locations and conducted the rare variants aggregate test
using the STAAR framework incorporating multiple functional annotations. We further performed conditional analyses adjusting for previously
reported common variants that associated with lipids. Since there are overlapping regions between the lncRNAs, we estimated the effective
number of aggregate-based tests (Meff) for multiple testing correction. Results. In total, we conducted RV aggregate tests in 166k lncRNA
regions with 113,587 effective number of aggregate-based tests. We identified 40, 31, 30, and 30 genome-wide significant (p < 0.05/113587 =
4.4e-07) lncRNAs with LDL, HDL, TC and TG, respectively, in 16 loci. After conditioning on known lipid-associated variants, 21, 15, 16, and 11
associations remained significant. Of the significant lncRNAs in the conditional analysis, 16, 11, 14, and 10 associations were near at least a
known lipid mendelian gene, including ENSG00000233271.1 near PCSK9 associated with LDL-C, NONHSAG026009.2 near APOE associated with
TC, NONHSAG108446.1 near CETP associated with HDL-C, and NONHSAG009700.3 near APOA5 associated with TG. The remaining associations
were all in lipid GWAS regions, except ENSG00000260441.5, which is an antisense to PLA2G15 that is associated with HDL-C. Conclusions. We
discovered several associations between lncRNAs and plasma lipid traits, which provide insights into potential lipid regulatory mechanisms of
GWAS loci. We will further seek replications in UK Biobank WGS and investigate the effects of lncRNAs on gene expression.
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