Multi-omic analysis elucidates the genetic basis of hydrocephalus

Abstract

We conducted PrediXcan analysis of hydrocephalus risk in ten neurological tissues and whole blood. Decreased expression of MAEL in the brain was significantly associated (Bonferroni-adjusted p < 0.05) with hydrocephalus. PrediXcan analysis of brain imaging and genomics data in the independent UK Biobank (N = 8,428) revealed that MAEL expression in the frontal cortex is associated with white matter and total brain volumes. Among the top differentially expressed genes in brain, we observed a significant enrichment for gene-level associations with these structural phenotypes, suggesting an effect on disease risk through regulation of brain structure and integrity. We found additional support for these genes through analysis of the choroid plexus transcriptome of a murine model of hydrocephalus. Finally, differential protein expression analysis in patient cerebrospinal fluid recapitulated disease-associated expression changes in neurological tissues, but not in whole blood. Our findings provide convergent evidence highlighting the importance of tissue-specific pathways and mechanisms in the pathophysiology of hydrocephalus.

Keywords: BioVU; GWAS; PrediXcan; TWAS; UK Biobank; electronic health records; human genetics; hydrocephalus; neurodevelopmental disorders; proteomics; transcriptomics.

Figure 1.. Overview of our approach

We leverage a large DNA biobank, BioVU (Roden et al., 2008), linked to deidentified electronic health record (EHR) data. We applied PrediXcan (Gamazon et al., 2015, 2018), which estimates the tissue-specific, genetically determined component of gene expression (i.e., the “germline genetic profile” of the gene expression trait) based on common variants (minor allele frequency >1%) and imputation against a reference transcriptome panel. For this study, we used GTEx transcriptome data in 10 neurological tissues and whole blood (Battle et al., 2017). The genetic component of expression was then tested for association with phenotype to identify gene-level associations. We performed systematic validation using independent replication of genetic results in the UK Biobank (Bycroft et al., 2018), analysis of structural brain magnetic resonance imaging (MRI) phenotypes in the UK Biobank (Elliott et al., 2018), and analysis of choroid plexus isolated from a mouse model of hydrocephalus (Robledo et al., 2008) and compared genetically determined gene expression changes to proteomic analysis of cerebrospinal fluid (CSF) isolated from infants with hydrocephalus compared to non-affected controls. A summary of each phenotype and the corresponding sample size can be found in Table S4.

Figure 2.. Genome-wide scan identifies tissue-specific gene-level associations with hydrocephalus

(A) Volcano plot showing odds ratio (OR, x axis) versus −log (p value, y axis) for gene expression differences between cases and controls in the frontal cortex. (B) Q-Q plot demonstrating a significant association between MAEL and hydrocephalus after correction using Benjamini-Hochberg FDR in the frontal cortex. MAEL is study-wide significant (adjusted p < 0.05) after Bonferroni adjustment for the number of gene-tissue pairs tested in the study. (C) Manhattan plot showing the gene-level association p values and chromosomal location of the signal from MAEL in the frontal cortex. The experiment-wide significant gene MAEL is also the unique gene in the cis region with a nominal gene-level association (p < 0.05) with hydrocephalus. (D–I) Analogous analyses were performed in hypothalamus tissue (D–F) and whole blood (G–I). See also Data S1.

Figure 3.. Differentially expressed genes in neurological tissues and whole blood

(A) Gene-level associations (PrediXcan) with hydrocephalus status, determined by logistic regression (with sex and age and the genotype-based principal components as covariates), in each neurological tissue and whole blood, including genes that depart from null expectation. MAEL expression in frontal cortex was experiment-wide significant (Bonferroni-adjusted p < 0.05) across all tissue-gene pairs tested. (B) Significance and effect size of gene-level associations in neurological tissues identifying outliers. Gene associations within each neurological tissue are color coded. (C) Hierarchical gene clustering of the nominally significant gene-level associations (p < 0.05), with whole blood an outlier relative to the neurological tissues. (D) Number of tissues in which gene-level nominal associations (p < 0.05) with hydrocephalus are detected. See also Data S1.

Figure 4.. MAEL expression profile and model of MAEL-mediated trait effect

(A) Population-based expression of MAEL in males (blue) and females (red) across 44 tissues included in GTEx. MAEL is most highly expressed in frontal cortex among brain regions and displays low expression in whole blood. Box edges show interquartile range, whiskers 1.5 × the interquartile range, and center lines the median. (B) Tissue specificity (x axis) as quantified by τ (see STAR methods) versus frequency of genes (y axis) across the genome. MAEL is one of the most tissue-specific genes in the genome (τ = 0.997). (C) Canonical model of MAEL-mediated alteration of transposon movement and depression of H3K9me3, leading to recruitment of RNA polymerase II (RNA Pol II) and transcription of previously repressed genes.

Figure 5.. Genomic analysis of brain MRI data in the independent UK Biobank validates gene-level associations with hydrocephalus in the same (significant) discovery tissue

Using PrediXcan analysis of brain imaging and genomic data, we validated the study-wide significant association of MAEL in frontal cortex (Bonferroni-adjusted replication p < 0.05). We then considered the associations with the imaging-based phenotypes of the top differentially expressed genes in frontal cortex. (A) For the hydrocephalus-associated genes (p < 0.05; in red) in the frontal cortex from the BioVU analysis, the Q-Q plots show the PrediXcan p values for their association with white matter volume (A) and total brain volume (B) in the UK Biobank. The departure from the diagonal line indicates enrichment for gene-level associations with the imaging-based phenotypes among the hydrocephalus-associated genes. For comparison, a Q-Q plot for a random set of genes (of equal count; in blue) is included.

Figure 6.. CSF proteomic signature of patients with hydrocephalus recapitulates gene expression associations identified by PrediXcan

(A) Q-Q plot showing significance for three proteins implicated by LC-MS analysis of CSF isolated from patients with hydrocephalus in the association of their genetically determined expression in the frontal cortex (−log₁₀ p value from the PrediXcan analysis shown on the y axis). (B) PrediXcan p values in frontal cortex of the proteomic signature from CSF (true) versus the remaining proteins (false), demonstrating greater statistical significance (i.e., lower p value from PrediXcan) for the proteins in the CSF signature in frontal cortex (left, p = 0.04) but not in whole blood (right, p = 0.83). Significance was assessed using a Mann-Whitney U test. Box edges show interquartile range, whiskers 1.5 × the interquartile range, and center lines the median.