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Title Disease and phenotype relevant genetic variants identified from histone acetylomes in human hearts |
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Type Young Investigator Award |
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Theme ACC Asia & SCS 32nd Annual Scientific Meeting |
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Topic Basic Science |
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Main Author Lek Wen Tan1 2 |
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Presenting Author Lek Wen Tan1 2 |
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Co-Author Eleanor Wong1 2 Chukwuemeka George Anene-Nzelu1 2 Thomas P. Cappola3 Marie Loh2 4 5 John Chambers4 5 Shyam Prabhakar1 Roger Foo1 2 |
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Department / Institution / Country Human Genetics 3 / Genome Institute of Singapore / Singapore1 Medicine / National University of Singapore / Singapore2 Perlman School of Medicine / University of Pennsylvania / United States3 Epidemiology and Biostatistics / Imperial College London / United Kingdom4 Lee Kong Chian School of Medicine / Nanyang Technological University / Singapore5 |
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Objective(s) Identifying genetic markers for heterogeneous complex diseases such as heart failure has been challenging, and may require prohibitively large cohort sizes in genome-wide association studies (GWAS) in order to meet genome-wide statistical significance. On the other hand, chromatin quantitative trait loci (QTL), elucidated by direct epigenetic profiling of specific human tissues, may contribute towards prioritising sub-threshold variants for disease-association. |
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Material and Method We captured non-coding genetic variants by performing enhancer H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq) in 70 human control and end-stage failing hearts. |
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Result(s) We mapped out a comprehensive catalogue of 47,321 putative human heart enhancers. 3,897 differential acetylation peaks (FDR 5%) pointed to pathways altered in heart failure (HF). To identify cardiac histone acetylation QTLs (haQTLs), we regressed out confounding factors including HF disease status, and employed the G-SCI test to call out 1,680 haQTLs (FDR 10%). RNA-seq performed on the same heart samples proved a subset of haQTLs to have significant association also to gene expression (expression QTLs), either in cis (180), or through long range interactions (81), identified by Hi-C and Hi-ChIP performed on a subset of hearts. Finally, 62 unique loci were identified by colocalisation of haQTLs with heart-related GWAS datasets. |
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Conclusion Population genetic variants at noncoding enhancer loci may indeed have functional value for disease and phenotype if they perturb transcription factor binding motifs, leading to chromatin and gene expression differences. The haQTL dataset here should now prove useful for prioritising more genetic variants from other heart-related GWAS. The approach of chromatin QTL and 3D connectome analyses in disease-relevant tissue promises not just to resolve the identity of functional genetic variants, but target genes with correlated expression changes may be implicated to represent important pathways for new disease therapy. |