Multi-faceted genomic and epigenomic profiling in Alzheimer's disease using Oxford Nanopore sequencing

Objectives:
This project aims to investigate structural variants (SVs) and DNA methylation patterns that may contribute to the development of Alzheimer’s disease (AD) by leveraging the strengths of both long-read and short-read sequencing technologies. Both genomic variations, such as single-nucleotide variants (SNVs) and SVs, and epigenomic variants, such as 5-methylcytosine (5mC), may spontaneously contribute significantly to AD risk. Although previous studies have identified AD-associated SNVs and differential methylation, their ability to resolve complex genomic regions—especially repetitive sequences, which constitute over 50% of the human genome is understudied due to the limitations of short-read sequencing. Also, the potential synergy between genetic variants and epigenetic modifications in AD is missing. This study will incorporate long-read technologies to address these issues.
Study Design:
We will analyze whole-genome sequencing datasets and associated phenotypic data from individuals diagnosed with AD and matched unaffected controls. SVs and DNA methylation events will be identified separately using short-read and long-read data. Long-read sequencing will be prioritized for its superior ability to detect large-scale genomic rearrangements and methylation signals in complex and repetitive regions. The integration of both sequencing technologies will enhance sensitivity, resolution, and accuracy.
Analysis Plan:
The analysis will include genome-wide detection and annotation of SVs and 5mC methylation, followed by comparative analysis between AD cases and controls. We will detect SVs and 5mC, and identify differentially methylated regions (DMRs) and AD-linked SV regions (SVRs) in AD patients after considering age and sex. These AD-associated patterns will be annotated with functional genomic elements and evaluate their potential contribution to AD pathogenesis. Finally, we will investigate the co-occurrence (with 100kb separation, adjustable) of SVs and aberrant methylation patterns, aiming to identify synergistic signatures that may improve our understanding of disease mechanisms and inform the development of diagnostic or therapeutic strategies.

Alzheimer's disease (AD) is an incurable neurodegenerative disorder with a strong genetic contribution (an estimated heritability ranging from 58% to 79%). Existing studies have focused on single-nucleotide variants and structural variants (SVs) and differential DNA methylation using short-read sequencing. However, these approaches are limited in reliably detecting SVs and DNA methylation in repeat regions, which compose >50% of the human genome, due to the limitation of short-read sequencing. Furthermore, the synergy of genomic variants and DNA methylation remains underexplored due to technical challenges. We want to investigate SVs and DNA methylation that is unique in AD patients compared to unaffected controls using long-read sequencing. To enhance the investigation, we will combine the data generated by both long-read sequencing and short-read sequencing. Our research is expected to offer novel insights to advance the understanding of AD development and to improve diagnostic or therapeutic approaches.