Major Depressive Disease (MDD) is a potentially life-threatening mood disorder characterized by depressed mood, loss of interest or pleasure, decreased energy, feelings of guilt or low self-worth, disturbed sleep or appetite, poor concentration and thoughts of death or suicide. Despite our increasing understanding of the neurobiology associated with MDD, the illness burden continues to rise as there is no breakthrough in antidepressant treatment or in the identification of specific locus of brain dysfunction in MDD. Of these, the amygdala has been considered an important locus of dysfunction. Studies to date, however, have been inconsistent with regards to how dysfunction of the amygdala contributes to MDD, possibly due to the inconsideration of important risk factors. This thesis used resting-state functional magnetic resonance imaging (fMRI) to investigate the functional connections of amygdala in a large sample of MDD patients compared to healthy subjects. Childhood trauma and serotonin polymorphism risk factors were incorporated into the analysis. Reduced resting state functional connectivity of the amygdala with VLPFC, OFC, caudate, insula, precuneus and cerebellum were observed in patients with MDD compared to healthy subjects. In subgroup analysis, MDD with high-risk serotonin polymorphisms was associated with reduced resting state functional connectivity with dorsolateral prefrontal cortex, dorsal posterior cingulate cortex, superior temporal, and some occipital regions. Furthermore, MDD with Severe childhood trauma was associated with reduced connectivity with the ventral lateral prefrontal cortex, orbitofrontal cortex, insula, parahippocampal gyrus, ventral anterior cingulate and thalamus. The results of this thesis clarify the differential contribution of the amygdala to the dysfunctional brain circuitry in MDD with or without risk factors. These findings have the potential to enhance our understanding of inter-individual differences in illness course and treatment response profiles of patients with MDD and also for biomarker identification in MDD based on risk factors.