Opti-Biologics

“Presenting Scientific Research for Optimization of Everyday Life"

Journal Review #3: Serotonin & Depression, is there a link?


July 29, 2022

"The serotonin theory of depression: a systematic umbrella review of the evidence"

Authors:
 Joanna MoncrieffRuth E. CooperTom StockmannSimone AmendolaMichael P. Hengartner & Mark A. Horowitz
Journal: Molecular psychiatry, Published July 20th, 2022
DOI:  https://doi.org/10.1038/s41380-022-01661-0
 
Depression, a prominent mental illness around the globe, has been extensively studied since the conception of causation. The most commonly known causes of depression are lower serotonin levels, lower serotonin binding to the serotonin receptor, and decreased signal amplification downstream of serotonin binding. While there has been extensive research investigating the role of serotonin in depression, few systematic reviews have been performed comparing the data quality to similar papers. 
A meta-analysis is a study that compares data sets from multiple papers to draw conclusions about that field of research. Each individual study is carefully selected according to data quality, sample size, and methodology. Analysis of these individual papers eventually leads to the assignment of a weighted number. This weighted number of each data set can be used to actively compare data from one paper to another, thus leading to a combined factor of effect magnitude. This combined factor ultimately leads to a conclusion regarding the data as a whole in the field. A third party can establish a magnitude number for each of the papers and compare data using this magnitude number. It is often used to compare studies in a field that have conflicting results. An example of how beneficial these studies are is laid out here. A randomized controlled trial (RCT) finds that a 96-hour fast has no effect on blood glucose levels. However, another RCT found that blood glucose was significantly reduced after a 96-hour fast. As a reader, the data is hard to follow; not everyone has the time to carefully read through a methods section with absolute precision. A third-party institute that has no bias initiates a meta-analysis to compare these experiments and finds that the first study had a sample size of 10 people, while the second study had a sample size of 100. Another important note in the meta-analysis is that the first study used commercially-available strips while the second study used medical-grade blood glucose meters. Using developed algorithms, the first study is assigned a magnitude number of 1, and the second study a magnitude number of 80. These numbers directly correlate with the quality of the data. Statistical analysis can be run using these magnitude numbers and the meta-analysis will reach a conclusion, most likely in this case, that fasting for 96 hours significantly reduces blood glucose.
An umbrella review is a review of the meta-analysis reviews. You might be thinking, if these meta-analysis reviews properly gauge the data quality of an individual study, then how would a review of these reviews be helpful? The umbrella review compiles many systematic reviews, analyzing their data quality and comparing that data to other systematic reviews. They are often used in fields that have a number of meta-analyses and conflicting results. The Umbrella reviews oftentimes become a helpful tool for making a well-supported conclusion based on multiple lines of evidence. 
Serotonin’s correlation has been heavily investigated in a multitude of meta-analyses. Despite recently emerging conflicting results, the general public and physicians continue to blame serotonin for depression. This has led to increased use of serotonergic-related drugs, including SSRIs, with Sertraline at number 12 for the most prescribed drugs of 2019 with 37 million prescriptions and a total of 7.8 million patients. Despite the ongoing battle with depression in people across the globe, there seems to be no definitive mechanism that explains why depression occurs and why the body sustains it. The complacency of research and physicians in understanding depression outside of serotonergic mechanisms is to blame for the spread of invalidated data. 
While there is active criticism to be done on this umbrella review, there are only minor flaws. The researchers concluded that when data across studies is properly weighted and compared, serotonin is unlikely to be linked with depression. There is still a heaping amount of evidence in the literature that supports depression being caused by a chemical imbalance in the brain. The key word in this sentence is "the brain." Lots of the studies used plasma serotonin, which may or may not accurately represent the amount of serotonin being released in the brain. While this is no flaw of the researchers conducting the umbrella review, it is a major flaw in the studies reviewed by them. 
While levels of plasma serotonin may not be directly correlated to depression, a chemical imbalance may still be the culprit. The studies performed rarely analyzed multiple neurotransmitters and the ratios between them. Recently, the importance of hormone ratios has increased in interest in the field of endocrinology, or the study of hormones. The importance of hormone ratios goes into the interactive effects between hormones. An example of this may be vitamin D and calcitriol, or dopamine and prolactin. More specifically, studies have been correlated the importance of estrogen and androgen (testosterone and similar hormones) ratios in the onset of osteoporosis. Could depression be an imbalanced ratio of neurotransmitters?
Neurotransmitters are chemicals released by neurons, a cell type in the nervous system that can fire action potentials (electrical signals) in response to a stimulus and have an effect on the surrounding neurons. The neuron can be broken into three distinct anatomical parts: the soma, which contains the dendrites; the axon; and the axon terminal. The soma is the main cell body of the neuron, and it contains most of the cell machinery, including the nucleus. Surrounding the soma are dendrites, which are tiny finger-like projections that receive chemical information and in turn fire an action potential (or not). This electrical signal can be propagated down the axon, which is basically like a supersonic tunnel that specializes in maximizing the speed of the signal, and finally reaches the axon terminal. This axon terminal contains machinery such that when the electric signal arrives, specific voltage-gated calcium ion channels open and allow for calcium to flood into the cell. The calcium ions then facilitate neurotransmitter-containing vesicle release into the synaptic cleft. This synaptic cleft is a tiny gap between a neuron's axon terminal and a "receiving station". The receiving station can be another neuron, skeletal muscle, organ tissue, or even smooth muscle. The neurotransmitter will travel across the synapse and bind to its specific receptor. This binding will cause a chain of events inside of that postsynaptic cell. In general, these changes can be broken into two main categories: excitatory and inhibitory. When a neurotransmitter binds to its receptor and makes the postsynaptic neuron more likely to fire an action potential, we call this an excitatory action. If the neurotransmitter binds to the receptor and the postsynaptic neuron is less likely to fire an action potential, we call this an inhibitory action. The balance of each hormone released into the synapse at any given time is crucial for the behavior of the postsynaptic neuron. Despite the fact that each neuron contains only one neurotransmitter, multiple neurons may release chemicals into the same synaptic space. This begins to become more complicated when the number of neurotransmitters being released may be influenced by genetics, or epigenetics, and receptor sensitivity for each of the neurotransmitters. An example of how this may be impactful is laid out here: One neuron releases 10 molecules of serotonin, another neuron releases 8 molecules of dopamine, and the last neuron releases 1 molecule of GABA. The net effect on the postsynaptic neuron will be excitatory, thus sending an action potential down its axon and resulting in neurotransmitter release at a distant synapse. However, if the first neuron has been shut off, and the last neuron has been overactivated by some epigenetic regulation factor, the net effect on the postsynaptic neuron will be inhibitory, so it will not send a signal to the distant synapse. This can begin to affect memory, learning, recognition, etc. While further exploration of the topic must be addressed, it points the field in the right direction. 
The general public’s perception of health information is heavily dependent on physician communication and news coverage. Theories revolving around a complex topic such as depression should be constantly evaluated so that decades of misinformation are not spread.
 

Meet The Author

Hello everyone, 
My name is Joshua Giblin. I am a post-bachelor researcher/research technician at USC. My interests range from nutrition to nanomedicine and also practical science to improve everyday life. Through this blog, I aim to communicate practical scientific research and present it to curious individuals so that an educated decision can be made. Thank you for reading the blog and showing your support. 

Editors

A special thanks to the people involved behind the scenes. Without them, these informative and influential posts would not be what they are. 
Anna Richardson
Undergraduate

Molly Giblin
High School Student 

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