Metabolomic signatures associated with depression and predictors of antidepressant response in humans: A CAN-BIND-1 report

Abstract

One of the biggest challenges in treating depression is the heterogeneous and qualitative nature of its clinical presentations. This highlights the need to find quantitative molecular markers to tailor existing treatment strategies to the individual’s biological system. In this study, high-resolution metabolic phenotyping of urine and plasma samples from the CAN-BIND study collected before treatment with two common pharmacological strategies, escitalopram and aripiprazole, was performed. Here we show that a panel of LDL and HDL subfractions were negatively correlated with depression in males. For treatment response, lower baseline concentrations of apolipoprotein A1 and HDL were predictive of escitalopram response in males, while higher baseline concentrations of apolipoprotein A2, HDL and VLDL subfractions were predictive of aripiprazole response in females. These findings support the potential of metabolomics in precision medicine and the possibility of identifying personalized interventions for depression.

From a non‐targeted metabolomics approach to a targeted biomarkers strategy to highlight testosterone abuse in equine. Illustration of a methodological transfer between platforms and laboratories

“…40 As depicted in Figure S1, QC samples were successfully grouped, compared to the total variability observed, confirming the analytical robustness. 37,41 The sample collected at D145 was considered as an outlier in this study and was subsequently excluded (Figure S1). A careful review of IS signals confirmed the stability of the retention time, peak area and the mass accuracy which remained below 5 ppm.…”

Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders

“…This heterogeneity presents a challenge to traditional biomarker and drug discovery research that is based on the binary classifications of diseases, such as DSM diagnosis; and given the wide range of phenotypes within diseases, this "topdown" approach to biomarker discover is imprecise at best. There may be advantages, therefore, to also incorporate a "bottom-up" strategy to identify relevant clinical phenotypes and associated biomarkers that will refine our understand of the pathophysiology underlying disease and ultimately develop personalized treatment approaches (38,39).…”

Metabolomics of Major Depressive Disorder: A Systematic Review of Clinical Studies

“…Title and abstract Title and abstract Of the studies evaluated in our review, 21 evaluated therapeutic approaches [10,13,14,[18][19][20][21]26,29,33,[36][37][38]40,43,[48][49][50]55,56,58]. One study assessed arms with bupropion, venlafaxine, and mirtazapine [36].…”

“…Of the studies evaluated in our review, 21 evaluated therapeutic approaches [ 10 , 13 , 14 , 18 - 21 , 26 , 29 , 33 , 36 - 38 , 40 , 43 , 48 - 50 , 55 , 56 , 58 ]. One study assessed arms with bupropion, venlafaxine, and mirtazapine [ 36 ].…”

“…A higher LDL/HDL ratio was found in MDD patients along with a reduction in omega-3 fatty acids levels [ 47 , 60 ] and a positive correlation between the Montgomery-Åsberg Depression Rating Scale (MADRS) score and serum levels of LDL, triglycerides, cholesterol, free cholesterol, phospholipids and apolipoprotein B before treatment [ 50 ]. Furthermore, a study that compared eight weeks of treatment with fluoxetine found reduced ApoB (lipoprotein B)/ApoA1 (lipoprotein A1) [ 58 ].…”