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. 2021 Jan 22;32(6):885-896.
doi: 10.1093/hmg/ddab016. Online ahead of print.

Multi-omics analyses of cognitive traits and psychiatric disorders highlights brain-dependent mechanisms

Roxanna Korologou-Linden  1   2 , Genevieve M Leyden  1   2   3 , Caroline L Relton  1   2 , Rebecca C Richmond  1   2 , Tom G Richardson  1   2
Affiliations

Multi-omics analyses of cognitive traits and psychiatric disorders highlights brain-dependent mechanisms

Roxanna Korologou-Linden et al. Hum Mol Genet. .

Abstract

Integrating findings from genome-wide association studies with molecular datasets can develop insight into the underlying functional mechanisms responsible for trait-associated genetic variants. We have applied the principles of Mendelian randomization (MR) to investigate whether brain-derived gene expression (n = 1194) may be responsible for mediating the effect of genetic variants on eight cognitive and psychological outcomes (attention deficit hyperactivity disorder (ADHD), Alzheimer's disease, bipolar disorder, depression, intelligence, insomnia, neuroticism and schizophrenia). Transcriptome-wide analyses identified 83 genes associated with at least one outcome (PBonferroni < 6.72 × 10-6), with multiple-trait colocalization also implicating changes to brain-derived DNA methylation at nine of these loci. Comparing effects between outcomes identified evidence of enrichment which may reflect putative causal relationships, such as an inverse relationship between genetic liability towards schizophrenia risk and cognitive ability in later life. Repeating these analyses in whole blood (n = 31 684), we replicated 58.2% of brain-derived effects (based on P < 0.05). Finally, we undertook phenome-wide evaluations at associated loci to investigate pleiotropic effects with 700 complex traits. This highlighted pleiotropic loci such as FURIN (initially implicated in schizophrenia risk (P = 1.05 × 10-7)) which had evidence of an effect on 28 other outcomes, as well as genes which may have a more specific role in disease pathogenesis (e.g. SLC12A5 which only provided evidence of an effect on depression (P = 7.13 × 10-10)). Our results support the utility of whole blood as a valuable proxy for informing initial target identification but also suggest that gene discovery in a tissue-specific manner may be more informative. Finally, non-pleiotropic loci highlighted by our study may be of use for therapeutic translational endeavours.

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Figures

Figure 1
Figure 1
A heatmap illustrating MR effect estimates between the brain-derived gene expression for 83 genes and eight neurological and psychiatric traits and disease.
Figure 2
Figure 2
A bi-directional Manhattan plot depicting the transcriptome-wide effects for gene expression on intelligence. The top plot represents effects derived from brain tissue (purple, n = 1194), whereas the bottom plot illustrates the same analysis using whole blood data (red, n = 31 684). Genes surviving multiple testing (P < 6.72 × 10−6 in brain, P < 3.27 × 10−6 in blood) based on single SNP analyses were additionally subjected to genetic colocalization (PPA > 0.8). Loci highlighted in blue survived multiple testing in brain-derived tissue but not in whole blood (despite the large difference in sample size). Loci which are labelled in red on the inverse plot represent candidates that were not identified in our brain tissue analysis but may survive multiple testing corrections in larger samples.
Figure 3
Figure 3
A Manhattan plot representing the transcriptome-wide associations between brain-derived expression and neuroticism. Genes surviving multiple testing (P < 3.27 × 10−6) based on single SNP analyses were additionally subjected to genetic colocalization (PPA > 0.8). Points highlighted in pink provided evidence from multiple trait colocalization analyses that brain-derived DNA methylation, as well as gene expression, share a causal variant at these loci with neuroticism susceptibility.
Figure 4
Figure 4
Bi-directional phenome-wide association plots depicting MR results between brain-derived gene expression and over 700 different traits and outcomes for (A) FURIN, (B) SLC12A5 and (C) NMB. Points are coloured and clustered based on the subcategories of traits.
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