Male sex predisposes to many kidney diseases. Considering that androgens exert deleterious effects in a variety of cell types within the kidney, we hypothesized that dihydrotestosterone (DHT) would alter the biology of the renal tubular cell by inducing changes in the proteome. We employed stable isotope labeling with amino acids (SILAC) in an indirect spike-in fashion to accurately quantify the proteome in DHT- and 17β-estradiol (EST)-treated human proximal tubular epithelial cells (PTEC). Of the 5043 quantified proteins, 76 were differentially regulated. Biological processes related to energy metabolism were significantly enriched among DHT-regulated proteins. SILAC ratios of 3 candidates representing glycolysis, N-acetylglucosamine metabolism and fatty acid β-oxidation, namely glucose-6-phosphate isomerase (GPI), glucosamine-6-phosphate-N-acetyltransferase 1 (GNPNAT1), and mitochondrial trifunctional protein subunit alpha (HADHA), were verified in vitro. In vivo, renal GPI and HADHA protein expression was significantly increased in males. Furthermore, male sex was associated with significantly higher GPI, GNPNAT1, and HADHA kidney protein expression in two different murine models of diabetes. Enrichment analysis revealed a link between our DHT-regulated proteins and oxidative stress within the diabetic kidney. This finding was validated in vivo, as we observed increased oxidative stress levels in control and diabetic male kidneys, compared with females. This in depth quantitative proteomics study of human primary PTEC response to sex hormone administration suggests that male sex hormone stimulation results in perturbed energy metabolism in kidney cells, and that this perturbation results in increased oxidative stress in the renal cortex. The proteome-level changes associated with androgens may play a crucial role in the development of structural and functional changes in the diseased kidney. With our findings, we propose a possible link between diabetic and non-diabetic kidney disease progression and male sex hormone levels. Data are available via ProteomeXchange (https://www.ebi.ac.uk/pride/archive/) with identifier PXD003811.