Unraveling Neuro-Proteogenomic Landscape and Therapeutic Implications for Human Behaviors and Psychiatric Disorders

Abstract

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioral traits and the disease etiology of neuropsychiatric disorders. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits such as sleeping, smoking, feelings, alcohol intake, mental health, and psychiatric disorders. Integrating with established drug information, we validated 13 out of 13 matched combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets. This consortium effort provides a large-scale proteogenomic resource for biomedical research on human behaviors and other neuro-related phenotypes.

Figure 1:. Overview of the mapped protein quantitative trait loci (pQTL).

a. Pleiotropic trans-pQTL counts and overlap of the mapped pQTL with existing eQTL. The upper barplot shows the number of proteins share trans-pQTL (gene annotations based on gene closest to the trans-pQTL). The scatterplot shows the genomic location of significant cis-pQTL in red (P < 5×10⁻⁸), significant trans-pQTL in blue (P < 5×10⁻⁸/184), and the shading within the dots indicates significance of the corresponding/nearest cis-eQTL for the respective protein. b. Scatterplot of the pQTL lead variants association signals v.s. their distance to the transcription start site (TSS) of the corresponding/nearest coding genes. c. Scatterplot of the absolute estimated genetic effects of the pQTL lead variants v.s. their minor allele frequencies (MAFs). d. The scatterplot in c shown in logarithm scale. e. Number of mapped pQTL per protein v.s. the linear mixed model estimated heritability in the ORCADES cohort. f. The variance explained by the mapped pQTL summed up for each protein v.s. the estimated heritability. g. For the proteins with significant cis-pQTL mapped, the lead variant signal strength v.s. the estimated heritability of each protein.

Figure 2:. Causality between the proteins and neuro-related phenotypes inferred by Mendelian randomization (MR) analyses.

The forest plot shows the significant MR results (false discovery rate < 0.05) based on LD-pruned (r² < 0.001) instrumental variants within each cis-pQTL. Inverse-variance weighted (IVW) estimates are provided as the solid round dots, and the whiskers indicate 95% confidence intervals. The numbers of instrumental variants in the cis-pQTL are given to the right of the whiskers. As a colocalization measure, the HEIDI (heterogeneity in dependent instruments) test evidence (p > 0.05) are given as the diamonds, where the largest diamonds correspond to a p-value of 1. The upper part of the plot shows the results where the proteins are known druggable targets, while the lower part shows the results for new protein targets.

Figure 3:. Regional association patterns of the pQTL and the colocalized neuro-related complex traits.

The displayed protein-trait pairs correspond to the Mendelian randomization discoveries in Figure 2 with the HEIDI p-value > 0.05. Each subfigure shows the pQTL region of 1Mb centered at the lead variant. The vertical dashed line in each subfigure marks the transcription start site of the corresponding protein’s coding gene.

Figure 4:. Causality between the proteins and UK Biobank disease phenotypes inferred by Mendelian randomization (MR) analyses.

The forest plot shows the significant MR results (false discovery rate < 0.05) based on LD-pruned (r² < 0.001) instrumental variants within each cis-pQTL. Inverse-variance weighted (IVW) estimates are provided as the solid round dots, and the whiskers indicate 95% confidence intervals. The numbers of instrumental variants in the cis-pQTL are given to the right of the whiskers. As a colocalization measure, the HEIDI (heterogeneity in dependent instruments) test evidence (p > 0.05) are given as the diamonds, where the largest diamonds correspond to a p-value of 1. The upper part of the plot shows the results where the proteins are known druggable targets, while the lower part shows the results for new protein targets.

Figure 5:. Drug targets revealed by Mendelian randomization (MR) analyses.

The MR results with 5% false discovery rate are considered. a. The number of MR inferred pairs of proteins and traits split into four categories: new (drug) targets, druggable targets that have drugs with unclear clinical function, re-purposing targets that have established drugs but for different diseases, and validated known targets where the established drugs have pharmacological effects that match the MR results. b. Numbers of re-purposing and validated drug targets per protein analysed. c. The validated known drug targets, the description of the drugs, and the corresponding consistent MR estimated effects. d. Potential mechanism of the adverse effect of Clenbuterol that targets NGF. e. Potential mechanism of Fostamatinib treating Chronic immune thrombocytopenia through CTSS. f. Potential pharmacology of DPEP1’s re-purposing drug on schizophrenia.