Characterizing the Causal Pathway for Genetic Variants Associated with Neurological Phenotypes Using Human Brain-Derived Proteome Data

Abstract

Leveraging high-dimensional molecular datasets can help us develop mechanistic insight into associations between genetic variants and complex traits. In this study, we integrated human proteome data derived from brain tissue to evaluate whether targeted proteins putatively mediate the effects of genetic variants on seven neurological phenotypes (Alzheimer disease, amyotrophic lateral sclerosis, depression, insomnia, intelligence, neuroticism, and schizophrenia). Applying the principles of Mendelian randomization (MR) systematically across the genome highlighted 43 effects between genetically predicted proteins derived from the dorsolateral prefrontal cortex and these outcomes. Furthermore, genetic colocalization provided evidence that the same causal variant at 12 of these loci was responsible for variation in both protein and neurological phenotype. This included genes such as DCC, which encodes the netrin-1 receptor and has an important role in the development of the nervous system (p = 4.29 × 10^-11 with neuroticism), as well as SARM1, which has been previously implicated in axonal degeneration (p = 1.76 × 10^-08 with amyotrophic lateral sclerosis). We additionally conducted a phenome-wide MR study for each of these 12 genes to assess potential pleiotropic effects on 700 complex traits and diseases. Our findings suggest that genes such as SNX32, which was initially associated with increased risk of Alzheimer disease, may potentially influence other complex traits in the opposite direction. In contrast, genes such as CTSH (which was also associated with Alzheimer disease) and SARM1 may make worthwhile therapeutic targets because they did not have genetically predicted effects on any of the other phenotypes after correcting for multiple testing.

Keywords: Mendelian randomization; brain-derived proteins; cognitive; genetic colocalization; neurological; phenome-wide association study; protein quantitative trait loci; psychaitric.

Figure 1

A Manhattan Plot to Highlight Genetically Predicted Effects Based on Mendelian Randomization and Genetic Colocalization Analyses on Neurological Phenotypes Points correspond to the −log10 p values that reflect genetically predicted effects between protein quantitative trait loci and neurological phenotypes. The red dashed line indicates the multiple testing correction applied in analyses (p = 0.05/692 = 7.23 × 10⁻⁰⁵). Effects that surpassed this threshold were only included in this plot if they also provided evidence of genetic colocalization, and these effects are colored based on their associated traits.

Figure 2

Locuszoom Plots to Illustrate Evidence of Genetic Colocalization between Proteins and Neurological Phenotypes Regional −log10 p values at the FLOT2 locus on (A) flottilin-2 levels and (B) intelligence and also at the SIDT1 locus on (C) SIDT1 protein levels and (D) insomnia.

Figure 3

Phenome-wide Association Plots for (A) SNX32 and (B) SARM1 to Investigate Pleiotropic Effects Each point on these plots corresponds to the −log10 p values derived using the Wald ratio, which are clustered and colored based on the subcategory of each trait and oriented to reflect the direction of effect with each respective protein. Red dashed lines correspond to the multiple testing correction threshold of p < 0.5/700 = 7.14 × 10⁻⁰⁵.