Depression varies widely among individuals, making treatment selection and dosing difficult, especially for newer drugs like ketamine. In a pilot study of 29 patients with treatment-resistant depression, researchers analyzed over 300 metabolites in cerebrospinal fluid and used multivariate analysis to reduce the data to two main dimensions. The first dimension correlated age with levels of specific metabolites and depression and anxiety scores. The second dimension correlated autism scores, male gender, and cognitive fatigue with bipolar diagnosis, lithium use, and another metabolite disturbance. The findings suggest that complex, treatment-resistant depression can be mapped onto two pathophysiological domains, which may eventually guide personalized treatment choices.
Gain of function disturbances in nutrient sensing are likely the largest component in human age-related disease. Mammalian target of rapamycin complex 1 (mTORC1) activity affects health span and longevity. The drugs ketamine and rapamycin are effective against chronic pain and depression, and both affect mTORC1 activity. In a study of 27 females with psychiatric disease, phosphorylated p70S6K, a marker for mTORC1 activity, was measured in blood samples. mTORC1 activity correlated with biometrics (height, macrocephaly, pupil distance) and neuropsychiatric profiles (anxiety, autism). Phosphorylated p70S6K was the best predictor for ketamine response across all cases and for rapamycin response in one instance. The data suggest a simple assay may allow cost-effective prediction of medication response.