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Mood is indirectly related to serotonin, norepinephrine and dopamine levels in humans: a meta-analysis of monoamine depletion studies

Abstract

Dysfunction in the monoamine systems of serotonin (5-HT), norepinephrine (NE) and dopamine (DA) may causally be related to major depressive disorder (MDD). Monoamine depletion studies investigate the direct effects of monoamines on mood. Acute tryptophan depletion (ATD) or para-chlorophenylalanine (PCPA) deplete 5-HT, acute phenylalanine/tyrosine depletion (APTD) or alpha-methyl-para-tyrosine (AMPT) deplete NE/DA. Available depletion studies found conflicting results in heterogeneous populations: healthy controls, patients with previous MDD in remission and patients suffering from MDD. The decrease in mood after 5-HT and NE/DA depletion in humans is reviewed and quantified. Systematic search of MEDLINE and EMBASE (1966–October 2006) and cross-references was carried out. Randomized studies applying ATD, PCPA, APTD or AMPT vs control depletion were included. Pooling of results by meta-analyses was stratified for studied population and design of the study (within or between subjects). Seventy-three ATD, 2 PCPA, 10 APTD and 8 AMPT studies were identified of which 45 ATD and 8 APTD studies could be meta-analyzed. 5-HT or NE/DA depletion did not decrease mood in healthy controls. 5-HT or NE/DA depletion slightly lowered mood in healthy controls with a family history of MDD. In drug-free patients with MDD in remission, a moderate mood decrease was found for ATD, without an effect of APTD. ATD induced relapse in patients with MDD in remission who used serotonergic antidepressants. In conclusion, monoamine depletion studies demonstrate decreased mood in subjects with a family history of MDD and in drug-free patients with MDD in remission, but do not decrease mood in healthy humans. Although depletion studies usefully investigate the etiological link of 5-HT and NE with MDD, they fail to demonstrate a causal relation. They presumably clarify a vulnerability trait to become depressed. Directions for further investigation of this vulnerability trait are proposed.

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Acknowledgements

We thank Mrs Natasha Wiebe, MMath PStat, Research Associate at the University of Alberta, Canada and especially Dr Rob JPM Scholten, MD, PhD, epidemiologist and director of the Dutch Cochrane Centre at the Academic Medical Centre, Amsterdam for their indispensable help with the statistic methods used in this review. This study was partially funded by the program Opleiding Onderzoekers GGZ (OOG) (project number 100-002-002) by ZonMw, the Hague, the Netherlands.

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Appendix

Appendix

Differences between intervention and control measurements

In depletion studies changes in mood scores typically represented mean mood-scores both before (pre) and after (post) the depletion/challenge (experimental intervention) and the placebo/sham/control-intervention. Because the mood scores were not necessarily identical at the start of the experiment and the control, we first calculated the mean change in mood-score (pooled difference) for the experimental and control condition separately per study. Some studies also provided the standard deviation (SD) of the pooled differences. When the standard deviation was not reported, we calculated the standard deviation of the pooled difference for paired data:

In this formula, the correlation coefficient R was calculable in four studies only36, 59, 81, 105 and ranged between 0.42 and 1.00 for the experimental and between 0.34 and 0.95 for the control condition. To be able to calculate the standard deviation of the change between pre- and post-test mood scores for the rest of the studies we imputed a correlation coefficient R of 0.5. This value was considered to be a conservative assumption.

Statistics for studies with a within subjects design

The difference in the changes of mood scores between intervention and control were expressed as difference of change scores:

For this difference the SD of the difference was calculated by again applying formula (A1), with an assumed R of 0.5.

To acknowledge the different mood scales to measure change in mood, the difference in changes between experimental and control condition were standardized by calculating Hedges’ adjusted g, which is similar to Cohen's d, but includes an adjustment for small sample bias:126

In this formula nAB and nBA represent the number of subjects randomized to intervention or control as first test in the study. If the numbers for nAB and nBA were not reported, we assumed that the sample was split half for the two sequences. For Hedges’ g an SE was calculated as follows:146, 147

Statistics for studies with a between subjects design

For between subject studies comparable statistics were used to calculate the mean change in mood-scores. Because the between-subjects design is a parallel group design, Hedges’ g was calculated with formula (A3) in which for nAB and nBA nINT and nCONT were substituted. The formula for the SE was slightly different to acknowledge the absence of paired data:

Statistics for relapse rates

For relapse rates of MDD after depletion provided in a within subjects design the difference in relapse rates was calculated as

in which N is the total number of patients included. The standard error then is

in which b represents the number of patients with a relapse after the intervention but not the control condition and c the number of patients with a relapse after the control but not the intervention.148 If the numbers of ‘pairs’ were not extractable from the paper, a conservative approach was used assuming the minimal number of patients relapsing both after the intervention and the control condition (maximal c), resulting in the largest SE.

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Ruhé, H., Mason, N. & Schene, A. Mood is indirectly related to serotonin, norepinephrine and dopamine levels in humans: a meta-analysis of monoamine depletion studies. Mol Psychiatry 12, 331–359 (2007). https://doi.org/10.1038/sj.mp.4001949

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