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Basic Science and Pathogenesis.

Karen Nuytemans1,2, Liyong Wang1,3, Luciana Bertholim Nasciben2

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Identifying Alzheimer's disease (AD) susceptibility genes in noncoding regions is challenging. Enhanced Hi-C Capture analyses (eHiCA) successfully nominated candidate genes in ambiguous AD genome-wide association study loci.

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Area of Science:

  • Genomics
  • Neuroscience
  • Molecular Biology

Background:

  • Identifying susceptibility genes in noncoding genome-wide association study (GWAS) loci for Alzheimer's disease (AD) is complex due to long-range regulatory element interactions.
  • Ambiguous AD GWAS loci often lack clear candidate genes or variants, hindering the determination of disease-driving elements.
  • High-resolution Hi-C data can map genomic interactions to resolve regulatory architecture in these challenging loci.

Purpose of the Study:

  • To identify underlying susceptibility genes in ambiguous noncoding AD GWAS loci.
  • To leverage high-resolution Hi-C data and Enhanced Hi-C Capture analyses (eHiCA) to map regulatory interactions.
  • To nominate candidate genes within complex AD GWAS loci.

Main Methods:

  • Construction of Hi-C libraries from brain frontal cortex and iPSC-derived AD-relevant cells.
  • Application of Enhanced Hi-C Capture analyses (eHiCA) with the DeepLoop pipeline at 5kb resolution.
  • Analysis focused on six ambiguous AD GWAS loci from the Bellenguez et al. study in non-Hispanic whites.

Main Results:

  • In the PICALM/EED locus, PICALM was identified as the strongest candidate susceptibility gene.
  • USP6NL/ECHDC3 and BCKDK/KAT8 loci revealed CELF2 and SETD1A, respectively, as looped candidate genes.
  • NME8 and ADAM10 were nominated in their respective loci, with GWAS variants linked to promoter/enhancer regions.

Conclusions:

  • eHiCA effectively nominates candidate genes in noncoding AD GWAS loci lacking clear candidates.
  • Chromatin regulatory maps are valuable tools for dissecting complex genetic associations in AD.
  • This approach enhances the understanding of AD genomics by resolving regulatory elements and their targets.