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Related Experiment Video

Updated: Feb 8, 2026

Mapping Dysfunctional Protein-Protein Interactions in Disease
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A promoter interaction map for cardiovascular disease genetics.

Lindsey E Montefiori1, Debora R Sobreira1, Noboru J Sakabe1

  • 1Department of Human Genetics, The University of Chicago, Chicago, United States.

Elife
|July 11, 2018
PubMed
Summary

Cardiovascular disease (CVD) genetic risk loci often reside in non-coding DNA. High-resolution maps reveal long-range interactions, linking 1999 CVD single nucleotide polymorphisms (SNPs) to 347 target genes, many not the nearest gene.

Keywords:
GWAScapture Hi-Ccardiomyocytescardiovascular diseasechromosomesgene expressiongene regulationhumanhuman biologymedicine

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Area of Science:

  • Genomics
  • Cardiovascular Genetics
  • Epigenetics

Background:

  • Over 500 genetic loci are linked to cardiovascular disease (CVD) risk.
  • Most risk loci are in non-coding regions, making target gene identification challenging.

Purpose of the Study:

  • To create high-resolution promoter capture Hi-C (PCHi-C) maps in human induced pluripotent stem cells (iPSCs) and cardiomyocytes (CMs).
  • To identify and prioritize functional target genes for CVD-associated genetic loci.

Main Methods:

  • Generated high-resolution PCHi-C maps in iPSCs and iPSC-derived CMs.
  • Validated maps by analyzing promoter interactions with distal sequences and chromatin marks.
  • Linked CVD-associated single nucleotide polymorphisms (SNPs) to target genes using the CM PCHi-C map.

Main Results:

  • Promoters preferentially contact distal sequences with tissue-specific transcription factor motifs.
  • Identified 1999 CVD-associated SNPs interacting with 347 target genes in CMs.
  • Over 90% of SNP-target gene interactions did not involve the nearest gene; 40% of SNPs interacted with multiple genes.

Conclusions:

  • PCHi-C maps provide a valuable resource for identifying functional targets of CVD loci.
  • Long-range chromatin interactions are crucial for understanding the functional impact of non-coding genetic variants in CVD.
  • This study highlights the importance of considering 3D genome architecture in cardiovascular genetics research.