Choline elevation in amygdala region at recovery indicates longer survival without depressive episode: a magnetic resonance spectroscopy study

Abstract

Rationale Depression, with variable longitudinal patterns, recurs in one third of patients. We lack useful predictors of its course/ outcome, and proton magnetic resonance spectroscopy (1H-MRS) of brain metabolites is an underused research modality in finding outcome correlates. Objectives To determine if brain metabolite levels/changes in the amygdala region observed early in the recovery phase indicate depression recurrence risk in patients receiving maintenance therapy. Methods Forty-eight patients on stable-dose antidepressant (AD) maintenance therapy were analyzed from recovery onset until (i) recurrence of depression or (ii) start of AD discontinuation. Two 1H-MRS scans (6 months apart) were performed with a focus on amygdala at the beginning of recovery. N-acetylaspartate (NAA), choline-containing metabolites (Cho), and Glx (glutamine/ glutamate and GABA) were evaluated with regard to time without recurrence, and risks were assessed by Cox proportional hazard modeling. Results Twenty patients had depression recurrence, and 23 patients reached AD discontinuation. General linear model repeated measures analysis displayed three-way interaction of measurement time, metabolite level, and recurrence on maintenance therapy, in a multivariate test, Wilks' lambda = 0.857, F(2,40) = 3.348, p = 0.045. Cho levels at the beginning of recovery and subsequent changes convey the highest risk for earlier recurrence. Patients experiencing higher amygdala Cho after recovery are at a significantly lower risk for depression recurrence (hazard ratio = 0.32; 95% confidence interval 0.13-0.77). Conclusion Cho levels/changes in the amygdala early in the recovery phase correlate with clinical outcome. In the absence of major NAA fluctuations, changes in Cho and Glx may suggest a shift towards reduction in (previously increased) glutamatergic neurotransmission. Investigation of a larger sample with greater sampling frequency is needed to confirm the possible predictive role of metabolite changes in the amygdala region early in the recovery phase.

Evidence of persistent glial cell dysfunction in the anterior cingulate cortex of juvenile idiopathic arthritis children: a proton MRS study

“…The Cho is a marker to detect the turnover of glial cell membrane in CNS and is also an essential precursor of acetylcholine and membrane lipids, phosphatidylcholine, and sphingomyelin [ 19 – 22 ]. The reduction of tCho/tCr levels in the ACC of JIA was consistent with previously reported alterations in the brain phospholipid metabolism, which may lead to altered lipid membrane turnover and neuroplasticity [ 23 , 24 ]. The decreased tCho/tCr ratio also supported the impaired astrocytic functioning and altered neuroplasticity in JIA patients.…”

Circulating choline pathway nutrients and depression after ischemic stroke

“…Choline pathway nutrients, including choline and betaine, could ameliorate neurological impairment, increase neuroplasticity, and promote recovery after stroke [8–10]. It has been reported that subjects with major depressive disorder had lower urinary choline levels [11], and higher choline levels were observed in the amygdala region of patients with a lower risk of depression recurrence [12]. Moreover, previous animal studies demonstrated that supplemental choline or betaine in rats model could reverse early life‐induced depression and produce substantive antidepressant‐like effects [13,14].…”

Challenges in CNS drug development and the role of imaging

“…Alice Egerton reviews the use of another neurochemical imaging approach, magnetic resonance spectroscopy, for drug development, highlighting its potential but also a number of issues that need to be resolved (Egerton 2021). Several studies test mechanism of action of drugs to inform the development of these drugs or treatment approaches generally (Nathan & Bakker 2021;Grimm et al 2021;Gilleen et al 2021) and, potentially, also of a biomarker to predict recovery following treatment (Henigsberg et al 2021). The special issue also includes reviews that draw on evidence from imaging studies to consider models of antidepressant action and how to improve personalized treatment prediction (Paulus & Thompson 2021;Godlewska & Harmer 2021).…”