Prediction of susceptibility to major depression by a model of interactions of multiple functional genetic variants and environmental factors

Abstract

Major depressive disorder (MDD) is the most common psychiatric disorder and the second overall cause of disability. Even though a significant amount of the variance in the MDD phenotype is explained by inheritance, specific genetic variants conferring susceptibility to MDD explain only a minimal proportion of MDD causality. Moreover, genome-wide association studies have only identified two small-sized effect loci that reach genome-wide significance. In this study, a group of Mexican-American patients with MDD and controls recruited for a pharmacogenetic study were genotyped for nonsynonymous single-nucleotide polymorphisms (nsSNPs) and used to explore the interactions of multiple functional genetic variants with risk-classification tree analysis. The risk-classification tree analysis model and linkage disequilibrium blocks were used to replicate exploratory findings in the database of genotypes and phenotypes (dbGaP) for major depression, and pathway analysis was performed to explore potential biological mechanisms using the branching events. In exploratory analyses, we found that risk-classification tree analysis, using 15 nsSNPs that had a nominal association with MDD diagnosis, identified multiple increased-MDD genotype clusters and significant additive interactions in combinations of genotype variants that were significantly associated with MDD. The results in the dbGaP for major depression disclosed a multidimensional dependent phenotype constituted of MDD plus significant modifiers (smoking, marriage status, age, alcohol abuse/dependence and gender), which then was used for the association tree analysis. The reconstructed tree analysis for the dbGaP data showed robust reliability and replicated most of the genes involved in the branching process found in our exploratory analyses. Pathway analysis using all six major events of branching (PSMD9, HSD3B1, BDNF, GHRHR, PDE6C and PDLIM5) was significant for positive regulation of cellular and biological processes that are relevant to growth and organ development. Our findings not only provide important insights into the biological pathways underlying innate susceptibility to MDD but also offer a predictive framework based on interactions of multiple functional genetic variants and environmental factors. These findings identify novel targets for therapeutics and for translation into preventive, clinical and personalized health care.

Figure 1

Tree analyses performed to assess MDD risk in cluster of variants. Eight nsSNPs had high-order interactions in the control of tree growth; they are located in the following genes: HSD3B1, PDLIM5, PSMD9, BDNF, USP36, PDE6C, PSMB4 and MYOC genes. Light-pink nodes=low MDD risk; light-green nodes=moderate MDD risk; light-blue nodes=high MDD risk; and purple node=reference MDD risk. Sensitivity=40%, specificity=83% and accuracy=63% (sensitivity refers to the proportion of cases who are correctly predicted as case; specificity refers to the proportion of controls who are correctly predicted as control; and accuracy refers to the proportion of cases and controls who are correctly predicted as case or control).

Figure 2

ARPA using dbGaP data reconstructed a tree resembling the tree generated during the exploratory phase with the Mexican-American MDD sample in Figure 1. Most of the genes involved in the branching process, that is, PDE6C, PSMD9, HSD3B1, BDNF and PDLIM5, were replicated. This tree has one gene (GHRHR) not present in the exploratory tree. Reconstruction of the tree highlighted that some covariates used by the multidimensional phenotype, that is, nicotine and alcohol use, provided a significant weight to the process of discriminating MDD-affected individuals from unaffected during the branching. For easier understanding, Figure 1 tree is reproduced in the right upper corner inset and genes in the two trees are color-coordinated.

Figure 3

Network analyses showed that all the genes involved in the major branching events in Figure 2 are related to positive regulation of cellular, biological processes and relevant to growth and organ development (the nerve growth-factor signaling pathway and retinal cone-cell development, also see Supplementary Table 5). All the symbols are explained in the MetaCore legend (Supplementary Material, Supplementary Figure 1).