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Approved Research

Integrative analysis of immune-mediated disease risk variants and cell type specific promoter interactions

Principal Investigator: Dr Mohamood Adhil Mohammed Iqbal
Approved Research ID: 96728
Approval date: April 25th 2023

Lay summary

Genetic variants showing associations with distinct diseases commonly map to non-coding DNA regulatory regions. Many of these regions are located considerable distances away from the genes they regulate and come into their proximity through 3D chromosomal interactions. We connect such variants with their putative target genes based on 3D chromosomal interaction data using the Promoter Capture Hi-C (PCHi-C) assay. 

We possess a comprehensive collection of high-resolution PCHi-C data from various tissues and conditions. Using our in-house prioritisation algorithms, we can combine these data with disease-related variants such as SNPs to detect novel genes for therapeutic targeting. This enables us to determine the most likely tissues and conditions in which disease variants enact their effects and provides novel insights into disease mechanisms and therapeutic approaches. Broadly, our approach is to:

  1. i) Link disease-variants to (distal) target genes through promoter interactions
  2. ii) Determine the cell-type specificity of these interactions
  3. iii) Establish functional context: gene networks, regulatory interactions, biological function

This approach is especially promising for treatment and diagnosis of complex and poorly characterised diseases, that have historically been difficult to tackle. In this context, we aim to use our technology to:

  1. i) Reveal novel therapeutic targets
  2. ii) Aid precise diagnosis of disease sub-types 
  3. iii) Determine disease progression status

To this end, we integrate our 3D chromosomal maps with a wide range of additional data relating to: regulatory features such as enhancers, chromatin accessibility, transcriptional activity, genotype (exome, whole-genome, somatic mutations), and clinical information.

Therefore, we are applying to access UK Biobank resources in order to obtain such data. Initially, we will focus on autoimmune diseases such as Systemic Lupus Erythematosus, and we will expand our efforts to additional disease areas such as cancer. The proposed work will take approximately 36 months.