We report a multi-omic resource generated by applying quantitative trait locus (xQTL) analyses to RNA sequence, DNA methylation and histone acetylation data from the dorsolateral prefrontal cortex of 411 older adults who have all three data types. We identify SNPs significantly associated with gene expression, DNA methylation and histone modification levels. Many of these SNPs influence multiple molecular features, and we demonstrate that SNP effects on RNA expression are fully mediated by epigenetic features in 9% of these loci. Further, we illustrate the utility of our new resource, xQTL Serve, by using it to prioritize the cell type(s) most affected by an xQTL. We also reanalyze published genome wide association studies using an xQTL-weighted analysis approach and identify 18 new schizophrenia and 2 new bipolar susceptibility variants, which is more than double the number of loci that can be discovered with a larger blood-based expression eQTL resource.
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We thank the participants of ROS and MAP for their essential contributions and gift to these projects. This work has been supported by National Institute of Health (NIH) grants P330AG10161, U01 AG046152, R01AG16042, R01 AG036836, R01 AG015819, R01 AG017917 and R01 AG036547. The U01 AG046152 grant (to P.L.D.J. and D.A.B.) is a component of the AMP-AD Target Discovery and Preclinical Validation Consortium, a program of the National Institute of Aging and the Foundation of the NIH.
The authors declare no competing financial interests.
Integrated supplementary information
Supplementary Figure 1 Number of aligned reads for RNA-seq data per batch and RIN scores per RNA-seq batch.
Supplementary Figure 2 –log10 P-values of Spearman’s correlation between top expression PCs and 11 technical and biological confounding factors.
Batch refers to the date of RNA preparation. PMI refers to the postmortem interval. Genotype PCs were computed as the top 3 PCs of genotype data. Study index refers to RUSH vs MAP samples.
Number of features (genes, methylation probes, histone peaks) associated with significant xQTLs vs. the number of PCs (hidden confounds) shown. The optimal number of PCs to account for was 10 for all three -omic data types. To avoid overfitting, this analysis was only performed on features that reside on chromosome 18.
π1 statistics used for assessing xQTL sharing. As the window size for testing mQTL decreases, which by construction reduces the number of mQTL SNPs, the π1 of eQTL p-values associated with the mQTL SNPs is found to increase.
Supplementary Figures 1–5 (PDF 584 kb)
Subject demographics (XLSX 12 kb)
Provenance of omic datasets (XLSX 12 kb)
Replication based on φ1 (XLSX 16 kb)
Sharing of xQTL SNPs based on φ1 (XLSX 12 kb)
Mediation analysis based on causal inference test (XLSX 13 kb)
Partitioned heritability (1MB window) (XLSX 36 kb)
Partitioned heritability (100KB window) (XLSX 18 kb)
Number of SNPs detected with xQTL-weighted GWAS (XLSX 40 kb)
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Ng, B., White, C., Klein, H. et al. An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome. Nat Neurosci 20, 1418–1426 (2017). https://doi.org/10.1038/nn.4632
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