Human GeneticsGenetic & Genomic MedicinePeer-reviewed journal article
Genomic and molecular evidence that the lncRNA DSP-AS1 modulates Desmoplakin expression
Luisa FocoiD, Marzia De BortoliiD, Fabiola Del Greco MiD, Laura Sophie Frommelt, Chiara VolaniiD, Diana A. Riekschnitz, Benedetta Maria MottaiD, Christian FuchsbergeriD, Thomas DelerueiD, Uwe VölkeriD, Tianxiao HuaniD, Martin GögeleiD, Juliane WinkelmanniD, Marcus DörriD, Daniel A LevyiD, Mélanie WaldenbergeriD, Alexander TeumeriD, Peter Paul PramstalleriD, Alessandra RossiniiD, Cristian PattaroiD
Abstract
Cardiac desmosomes are specialized cell junctions responsible for cardiomyocytes mechanical coupling. Mutation in desmosomal genes cause autosomal dominant and recessive familial arrhythmogenic cardiomyopathy. Motivated by evidence that Mendelian diseases share genetic architecture with common complex traits, we assessed whether common variants in any desmosomal gene were associated with cardiac conduction traits in the general population. We analysed data of N=4342 Cooperative Health Research in South Tyrol (CHRIS) study participants. We tested associations between genotype imputed variants covering the five desmosomal genes DSP, JUP, PKP2, DSG2, and DSC2, and P-wave, PR, QRS, and QT electrocardiographic intervals, using linear mixed models. Functional annotation and interrogation of publicly available genome-wide association study resources implicated potential connection with antisense lncRNAs, DNA methylation sites, and complex traits. Causality was tested via two-sample Mendelian randomization (MR) analysis and validated with functional in vitro follow-up in human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). DSP variant rs2744389 was associated with QRS (P=3.5x10-6), with replication in the Microisolates in South Tyrol (MICROS) study (n=636; P=0.010). Observing that rs2744389 was associated with DSP-AS1 antisense lncRNA but not with DSP expression in multiple GTEx-v8 tissues, we conducted two-sample Mendelian randomization analyses that identified causal effects of DSP-AS1 on DSP expression (P=6.33x10-5; colocalization posterior probability=0.91) and QRS (P=0.015). In hiPSC-CMs, DSP-AS1 expression downregulation through a specific GapmerR matching sequence led to significant DSP upregulation at both mRNA and protein levels. The evidence that DSP-AS1 has a regulatory role on DSP opens the venue for further investigations on DSP- AS1s therapeutic potential for conditions caused by reduced desmoplakin production. Author SummaryArrhythmogenic Cardiomyopathy is a severe condition mainly caused by pathogenic variants in genes encoding components of the cardiac desmosome, a specialised cell junction. Given complex traits and Mendelian diseases share common genetic background, we hypothesised that common variants in any of the five desmosomal genes (DSP, JUP, PKP2, DSG2, and DSC2) could be associated with electrocardiographic measurements in general population individuals. Analyzing data from >4000 participants from the Cooperative Research In South Tyrol (CHRIS) study, we identified an association between a variant in the desmoplakin gene (DSP) and QRS, which represents the time needed for ventricular electrical activation. Downstream gene expression analyses showed that the identified variant was not associated with the expression of DSP but with that of an uncharacterized long non-coding antisense RNA, DSP-AS1. Mendelian randomization (MR) analyses, performed leveraging publicly available data, supported a causal effect of DSP-AS1 expression on DSP expression. In vitro functional follow-up showed that silencing DSP-AS1 induces DSP transcript and desmoplakin protein upregulation, suggesting that DSP-AS1 is involved in the regulation of DSP expression and validating MR findings. Our study represents a first step in the functional characterization of DSP-AS1, a potential target for treatment of diseases caused by low amounts of desmoplakin.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: Bayesian inference
- Citations
- 2
- FWCI
- 1.40
- Field percentile
- top 17%
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