Astrocytes are glial cells specific to the central nervous system and involved in numerous brain functions, including regulation of synaptic transmission and of immune reactions. There is mounting evidence suggesting astrocytic dysfunction in psychopathologies such as major depression, however, little is known about the underlying etiological mechanisms. Here we report a two-stage study investigating genome-wide DNA methylation associated with astrocytic markers in depressive psychopathology. We first characterized prefrontal cortex samples from 121 individuals (76 who died during a depressive episode and 45 healthy controls) for the astrocytic markers GFAP, ALDH1L1, SOX9, GLUL, SCL1A3, GJA1 and GJB6. A subset of 22 cases with consistently downregulated astrocytic markers was then compared with 17 matched controls using methylation binding domain-2 (MBD2) sequencing followed by validation with high-resolution melting and bisulfite Sanger sequencing. With these data, we generated a genome-wide methylation map unique to altered astrocyte-associated depressive psychopathology. The map revealed differentially methylated regions (DMRs) between cases and controls, the majority of which displayed reduced methylation levels in cases. Among intragenic DMRs, those found in GRIK2 (glutamate receptor, ionotropic kainate 2) and BEGAIN (brain-enriched guanylate kinase-associated protein) were most significant and also showed significant correlations with gene expression. Cell-sorted fractions were investigated and demonstrated an important non-neuronal contribution of methylation status in BEGAIN. Functional cell assays revealed promoter and enhancer-like properties in this region that were markedly decreased by methylation. Furthermore, a large number of our DMRs overlapped known Encyclopedia of DNA elements (ENCODE)-identified regulatory elements. Taken together, our data indicate significant differences in the methylation patterns specific to astrocytic dysfunction associated with depressive psychopathology, providing a potential framework for better understanding this disease phenotype.