Genotype-stratified Default Mode Network hyperconnectivity in major depressive disorder: an MR imaging genetics study

Major depressive disorder (MDD) is a prevalent and debilitating psychiatric condition defined by complex genetic and neurobiological underpinnings. The current study investigated the genetic variants associated with the disease and impact of significant variants on neurotransmitter pathways and their association with inherent brain connectivity patterns in MDD.

A total of 69 patients diagnosed with MDD were recruited. Whole-exome sequencing (WES) was carried out in 30 patients to identify relevant genetic variants. This was followed by the genotyping of two frequently observed variants in TPH1 (rs1799913) and DAOA (rs2391191) genes in additional 39 patients using Sanger Sequencing. All subjects participated in resting-state functional MRI (rs-fMRI), and genotype-connectivity associations were analysed using the CONN toolbox. Functional connectivity was evaluated within the Default Mode Network (DMN), and its associations with HAM-D scores and the incidence of depressive episodes were also examined.

WES revealed variants in 21 genes involved in neurotransmission, synaptic plasticity, and intracellular signaling pathways. Individuals possessing altered TPH1 (rs1799913) and DAOA (rs2391191) genotypes demonstrated significantly increased connectivity within the DMN, particularly involving the posterior cingulate cortex, precuneus, dorsomedial prefrontal cortex, and subcalcarine gyrus. The heightened synchrony of the DMN exhibited a positive correlation with the severity of the Hamilton Depression Rating Scale and the occurrence of depressive episodes, suggesting a relationship between genotype, connectivity, and symptoms.

This study demonstrates that variations in TPH1 (rs1799913) and DAOA (rs2391191) genes are associated with atypical reinforcement of DMN connectivity in MDD. The findings support the role of serotonergic and glutamatergic pathways in maladaptive neural coupling and suggest that genotype-stratified DMN metrics may serve as intermediate neural phenotypes. Their status as disease-specific endophenotypes cannot be established in the absence of healthy or familial comparison groups. Further comprehensive, longitudinal research is essential to validate these results and evaluate their relevance for tailored interventions.