Tissue Type-Specific Bioenergetic Abnormalities in Adults with Major Depression.
David G HarperJ Eric JensenCaitlin RavichandranRoy H PerlisMaurizio FavaPerry F RenshawDan V IosifescuPublished in: Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology (2016)
Brain bioenergetic abnormalities have been observed frequently in adults with major depressive disorder (MDD); however, results have been inconsistent regarding whether decreased or increased metabolism was observed. Phosphorus-31 magnetic resonance spectroscopy (31P MRS) allows for the quantification of bioenergetic molecules, containing high-energy phosphates, over the whole brain as well as measuring the differences between gray matter and white matter. We recruited 50 subjects with a current diagnosis of MDD, not currently treated with psychotropic medication, between ages of 18 and 65 (mean±SD age: 43.4±13.6; 46% female) and 30 healthy volunteers, matched for age and gender (39.0±12.5 years of age; 36.6% female). All subjects received a T1 MP-FLASH scan for tissue segmentation followed by 31P MRS, chemical shift imaging scan with 84 voxels of data collected over the entire brain utilizing a dual-tuned, proton-phosphorus coil to minimize subject movement. Phosphocreatine and inorganic phosphate (Pi) varied in opposite directions across gray matter and white matter when MDD subjects were compared with controls. This finding suggests alterations in high-energy phosphate metabolism and regulation of oxidative phosphorylation in MDD patients. In addition, within the MDD group, gray matter Pi, a regulator of oxidative phosphorylation, correlated positively with severity of depression. These data support a model that includes changes in brain bioenergetic function in subjects with major depression.
Keyphrases
- major depressive disorder
- white matter
- bipolar disorder
- multiple sclerosis
- resting state
- computed tomography
- end stage renal disease
- newly diagnosed
- functional connectivity
- healthcare
- chronic kidney disease
- electronic health record
- high resolution
- depressive symptoms
- machine learning
- cerebral ischemia
- emergency department
- mental health
- prognostic factors
- protein kinase
- big data
- magnetic resonance
- peritoneal dialysis
- adverse drug
- heavy metals
- patient reported