Decoding the genomics of neurodegenerative diseases with large-scale, long-read sequencing | LC 25

Biography

Kimberley Billingsley leads the Applied Neurogenomics group within the National Institutes of Health Center for Alzheimer’s and Related Dementias (CARD). Her research focuses on understanding the impact of complex genetic variations, such as structural variants, on neurodegenerative diseases, including Alzheimer’s and Parkinson’s. Kimberley develops scalable workflows for long-read sequencing and integrates multi-omics data to identify translational targets, advancing equitable research across diverse populations.

Abstract

Neurodegenerative diseases, such as Alzheimer’s and Parkinson’s, affect millions globally. However, much of the genetic variation contributing to disease risk remains unexplored, especially in underrepresented populations.

While genetic studies have primarily focused on single nucleotide variants (SNVs), other critical forms of variation, such as structural variants (SVs) and short tandem repeats, are understudied due to the limitations of short-read sequencing (SRS), which captures fewer than half of all SVs. Long-read sequencing (LRS) addresses this gap by enabling more comprehensive detection of these variants and providing deeper insights into their functional roles.

Despite its potential, large-scale application of LRS has been constrained by technical challenges and high costs. To overcome these barriers, we developed a scalable wet-lab protocol and computational pipeline (Napu) for Oxford Nanopore sequencing. This approach was applied to diverse cohorts, including:

- Neurologically normal controls from North American Brain Expression Consortium (n = 222, European ancestry)

- Human Brain Collection Core (n = 165, African ancestry)

- Alzheimer’s disease samples from Religious Orders Study and Memory Aging Project (n = 350)

- Parkinson’s case-control samples from Parkinson’s Progression Markers Initiative (n = 700)

The resulting resource achieved approximately 40× genome coverage with a median N50 of 30 kb. We identified hundreds of thousands of SVs, predominantly insertions and deletions, and produced locally phased assemblies covering 95% of protein-coding genes.

By integrating matched expression datasets, such as RNA sequencing and cap-analysis gene expression sequencing, we performed quantitative trait locus analyses, identifying SVs driving gene expression in the frontal cortex and blood. Additionally, haplotype-specific methylation analysis across millions of CpGs uncovered cis-regulatory SVs inaccessible with SRS.

These findings highlight the transformative power of LRS in decoding complex regulatory mechanisms and identifying population-specific disease-associated loci, offering a critical resource for advancing neurodegenerative disease research.