Functional regulatory variants implicate distinct transcriptional networks in dementia

Abstract

Predicting the function of noncoding variation is a major challenge in modern genetics. In this study, we used massively parallel reporter assays to screen 5706 variants identified from genome-wide association studies for both Alzheimer’s disease (AD) and progressive supranuclear palsy (PSP), identifying 320 functional regulatory variants (frVars) across 27 loci, including the complex 17q21.31 region. We identified and validated multiple risk loci using CRISPR interference or excision, including complement 4 ( C4A ) and APOC1 in AD and PLEKHM1 and KANSL1 in PSP. Functional variants disrupt transcription factor binding sites converging on enhancers with cell type–specific activity in PSP and AD, implicating a neuronal SP1-driven regulatory network in PSP pathogenesis. These analyses suggest that noncoding genetic risk is driven by common genetic variants through their aggregate activity on specific transcriptional programs.

Single nucleus multiomics identifies ZEB1 and MAFB as candidate regulators of Alzheimer’s disease-specific cis regulatory elements

“…Nine of the 37 KANSL1 linked peaks are found in both AD and control donors, and 14 are neuron-specific ( Figure 3G ). One of these linked peaks found in the promoter overlaps an eQTL 30 (rs2532404) associated with progressive supranuclear palsy 31 and was recently shown via CRISPRi to regulate KANSL1 expression in iPSC-derived neurons 21 .…”

“…We compared the > 300,000 links to pre-existing, large-scale functional genomic datasets to determine which candidate elements had previously shown evidence of regulatory activity. Three data types were considered to provide orthogonal evidence of regulatory activity: 1) massively parallel reporter assays (MPRAs) 21,52-54 , 2) eQTL studies 30,55 , and 3) HiC 56 datasets. We found significant enrichments of links across each of these datasets despite several MPRAs being performed in cancer cell lines ( Figure 5B ).…”

“…For additional validation, we selected 51 neuronal links for testing in a luciferase reporter assay ( Table S9 ). We performed these assays in the neuroepithelial-derived human embryonic kidney 293 (HEK293 and 293FT) cell lines because of the similar chromatin accessibility landscape to that found in brain tissues 21 . These cell lines are also technically tractable as they are highly transfectable and allow for efficient screening of regions of interest.…”

“…Excitatory and inhibitory neuron ATAC-seq peaks were intersected with H3K27ac peaks identified from GLU (NeuN + /SOX6 - ) or GABA (NeuN + /SOX6 + ) neuronal nuclei 28 and from neuronal (NeuN + ) nuclei 11 . MPRA data was obtained from 21,52-54 , eQTL data was obtained from 30,55 , and neuronal HiC loop calls were obtained from 56 .…”

“…Recent advances in single cell technologies have allowed profiling of gene expression 12–18 and chromatin accessibility 10 , either separately or in parallel from the same samples 19,20 . While these studies have examined the cell type–specific transcriptional and epigenetic differences between tissues from brain donors with AD and unaffected controls, few have rigorously interrogated the regulatory mechanisms responsible for these alterations 11,21 . Integrating single nucleus RNA-seq (snRNA-seq) and single nucleus ATAC-seq (snATAC-seq) data allows identification of potential cis regulatory elements (CREs) by correlating chromatin accessibility with nearby gene expression.…”