Tuesday, February 25, 2025

What happened to the Serotonin Hypothesis?

 


Biogenic amine hypotheses of depression date back 60 years at this point.  Ron Pies and I reviewed a couple of the key papers by Kety, Schildkraut and others that were some of the first to apply what was known about biogenic amine neurotransmitters to depression. These papers were elegantly written, keenly aware of the dangers of biological reductionism, and very clear that much more study needed to be done to either accept or reject the biogenic amine hypotheses.  Those hypotheses eventually extended to the specific neurotransmitters -  norepinephrine, serotonin, and dopamine.  Much has been written about the Chemical Imbalance Theory and more recently a Serotonin Theory of depression even though they do not exist.

I decided to study the transition in hypotheses over the course of my career by looking at major psychiatric diagnosis and counting the number of hypotheses in the literature for each diagnosis.  For the purpose of this post I will be posting a list of hypotheses about depression and discussing the implications. In general, there are many hypotheses about disorders that seem to linger in the literature. I have not found any solid evidence that hypotheses are accepted or rejected. There is also the possibility that they can be combined to produce new comprehensive hypotheses.  At this point I have not been able to identify any solid theories based on the development of hypotheses.  But before I get into that a brief discussion of definitions is in order to add some consistency to the rest of this essay. 

I will be using definitions from a book written in 1986 (1) because I think they are the clearest. The logical place to start is with a definition of a theory.  Theory is commonly mistaken for a hypothesis.  The best case in point that I can think of is the Serotonin Theory or Chemical Imbalance Theory.  By definition, a theory is a group of related principles that can explain and predict phenomenon in a restricted domain. The domain will vary according to the discipline. Medicine and psychiatry depend on empirical theories that in turn are proven or disproven based on observation and evidence. That demarcation extends to biology in general.  Examples of theories include Evolution, Thermodynamics, The Periodic Table in chemistry, and Germ Theory.  Any casual look at the biogenic amine hypotheses with respect to serotonin, norepinephrine, or dopamine will clearly show an elaboration of the neurochemistry and molecular biology of these systems. It will also show that the research is ongoing and that levels of prediction are not generalized enough for any marker to be used for prediction. At that level, biogenic amine theories do not exist and never have. There is additional confusion added by the common term conspiracy theories because in science they are really pseudo-theories and do not satisfy the general definition of a theory.  They provide false explanations and predictions.

Scientific laws explain how any branch of science organizes observations and explains them.  A good example would be the First, Second and Third laws of thermodynamics.  They are taught in physical science and engineering courses and do predict observations in physical systems at the macro level.  There are some specific laws in biology like mitochondrial DNA being inherited only from the mother and both parents contributing equal amounts of genes to offspring in sexual reproduction.

And finally, a hypothesis is a first step in developing laws and theories.  It consists of speculation about experimental observations at a more fundamental level.  The Serotonin Hypothesis for example was proposed since multiple observations about serotonin in depression were converging to suggest it played a central role in the disorder. It also occurred at a time when there was much active research on neurotransmitters and synaptic function. If it had been more widely accepted and there was a more comprehensive formulation that would have happened.  It did not and in at least one authoritative source – the American College of Neuropsychopharmacology – the Serotonin Hypothesis disappeared after the Fourth Generation of Progress in 1995.

I have included that transition in the four slides that follow.  I decided to include material from Goodwin and Jamison's Manic-Depressive Illness because it includes a commentary from the pathophysiology section of their book on bipolar disorder:




 


 


 


A comparison of dedicated chapters on serotonin between the 4th and 5th generations is also useful.  In the 4th generation there were 12 serotonin focused chapters and in the 5th there was one general chapter.


 As noted in the final summary of serotonin (last slide) , the research emphasis transitioned from strictly neurochemistry to the associated neurobiology and macro observations of brain networks.  At the same time current literature continues to emphasize the importance of serotonin systems in psychiatric disorders.  Although the ACNP Generation of Progress texts stopped with 5th edition I searched for evidence of the serotonin or any biogenic amine hypothesis in a recent comparable text (5).  There were no neurotransmitter centric mechanisms with a more primary focus on imaging receptors and transporter proteins and how neural circuitry was impacted.  Suggested mechanisms for depression converged on neurotrophic, immune, and neuroendocrine pathways (see table of contents below). 



While there has been no overt rejection of the serotonin hypothesis – people remain interested in it and it is useful to consider why.

1:  The search for the underlying pathophysiology of psychiatric disorders has continued emphasis.  The speculative mechanisms are broad and there are numerous hypotheses carried forward – much like the serotonin hypothesis. It seems unlikely that there will be a single basic mechanism leading to disorders based on the heterogeneity and polygenic nature of studied populations (see number of variants for major depression in the Polygenic Score (PGS) Catalogue.      

2:  Studying biological systems requires an appreciation of complexity – particularly when prediction is a dimension of theories. It is well known for example that biologically identical or nearly identical organisms can produce different physical and behavioral outcomes and until all of those mechanisms are appreciated and incorporated into hypotheses and theories – widely accepted overall theories are unlikely.

3:  There are imperfect classifications in biology, medicine, and psychiatry. One of the basic tenets in medicine is that no two people with the same diagnosis are alike.  There are obvious differences in biology, psychological and sociocultural factors.    

4:  Physical theories are not perfect.  There is active debate about theories that seem to be settled science and whether or not they are complete.   Many of those theories are predictive up to a point and useful for many applications - but deficient in some ways.  This is all part of the active process of science.

Despite these considerations – obvious questions about the serotonin hypothesis persist.   Why are medications with a high affinity for serotonin receptors and serotonin transporter (SERT) effective medications for several disorders?  Why in a recent preclinical study (6) was elevated extracellular serotonin  a common signal for several treatments – some of which did not target serotonin systems?  And – is it possible that serotonin signals are just the initial sequence of a larger series of events that leads to an antidepressant or anxiolytic response?

I would be remiss to not remind readers of the importance of analyzing the rhetoric in any scientific paper you are reading on psychiatric topics. On the issue of theories for example, my original source makes the following observation:

“What is a theory” is not as hard to answer as jesting Pilate’s “What is truth?”.  Indeed, one difficulty with our question is that there are so many accepted answers, not that there is none.  That is, the term theory is used in several distinct and legitimate ways in science and medicine, and an explanatory catalogue of those uses would fill many pages.  

“We will limit ourselves to the concept of a theory that suggests understanding, reliability, and grounded belief.” (p. 113)

If you find yourself suddenly reading about theories, hypotheses, or laws in psychiatry or any other branch of medicine look for the author's definitions of those terms.  Most textbooks in medicine and biology may mention brief definitions and references to thermodynamics and evolution but beyond that the terms are missing.  These terms are much more common in physical sciences where the studied objects are more easily classified and experimental observations are clearer.   

So what is the answer to "When did the serotonin hypothesis of depression disappear?"  One short answer is "between 1995 and 2002."  But the reality is that it is still with us despite active campaigns against it and several proclamations in the press that it is "dead".  At this rate it may outlive its detractors.

 

George Dawson, MD, DFAPA

 

References:

1:  Albert DA, Munson R, Resnick MD.  Reasoning in medicine: an introduction to clinical inference.  Baltimore, USA:  The Johns Hopkins University Press, 1988: 112-149.

2:  Pies R, Dawson G.  The Serotonin Fixation: Much Ado About Nothing New. Psychiatric Times. 2022 Aug 22

3:  Goodwin FK,  Jamison KR.  Manic-Depressive Illness.  New York: Oxford University Press, 1990. 

4:  Bloom, F.E. and Kupfer, DJ. Neuropsychopharmacology: The Fourth Generation of Progress. New York: Raven Press, 1995.

5:  Davis KL, Charney D, Coyle JT, Nemeroff C. (2002) Neuropsychopharmacology: The Fifth Generation of Progress. Philadelphia: Lippincott Williams & Wilkins, 2002.

6:  Charney DS, Gordon JA, Buxbaum JD, Picciotto MR, Binder EB, Nestler EJ.  Charney and Nestler's Neurobiology of Mental Illness.  New York: Oxford University Press, 2025.

7:  Witt CE, Mena S, Holmes J, Hersey M, Buchanan AM, Parke B, Saylor R, Honan LE, Berger SN, Lumbreras S, Nijhout FH, Reed MC, Best J, Fadel J, Schloss P, Lau T, Hashemi P. Serotonin is a common thread linking different classes of antidepressants. Cell Chem Biol. 2023 Dec 21;30(12):1557-1570.e6. doi: 10.1016/j.chembiol.2023.10.009. Epub 2023 Nov 21. PMID: 37992715.


Supplementary 1:  I contacted several experts involved in this research over the years.  So far none of the researchers I have contacted have responded to my questions that were specific to the serotonin hypothesis. 

Supplementary 2:  The book cover images and quotes are all property of their copyright owners and do not imply any connection to this blog. They are used here for illustrative and educational purposes. I encourage any readers of this blog to do their own research by reading the reference materials.  The ACNP 4th and 5th Generation of Progress are both available to read free online at the ACNP web site.

Sunday, February 23, 2025

Should GLP-1 agonists be added to the drinking water?



For starters GLP-1 agonists are drugs like Ozempic and Weygovy.  See this post for a current list.  It is hard not to hear about them since they are heavily hyped in just about every form of media. They are being touted as a cure for just about everything.  Various celebrities are either promoting them or denying that a dramatic weight loss was associated with their use.  Some in the weight loss and exercise industry are pushing back with statements about side effects and rapid weight gain if you ever stop taking them.  The sales of these drugs is a windfall for the pharmaceutical industry and current pricing means that other businesses that make money from rationing access to medical care and medications will be trying to prevent their use.  I thought I would post a contrast today between the latest review of conditions these medications have been researched for and a new paper that suggests they may increase the frequency of psychiatric disorders.

The rest of the title comes from my experience in many medical settings over the decades.  Any time a medication is commonly prescribed you can count on someone saying “We should just put it in the drinking water.”  Examples over the years have been amoxicillin, H-2 blockers like ranitidine, statins, beta blockers, lorazepam, and even haloperidol.  It all depends on the prescription frequency in a particular setting. At the rate GLP-1 agonists have been hyped - somebody is saying it somewhere.  The irony in that statement is that many medications are now in the water supply and not doing anything for anybody.

When I describe this group of drugs as hyped that is exactly what I mean.  The only comparable hype has been for cannabis and psychedelics/hallucinogens.  Typical newspaper headlines about GLP-1s say they are wonder drugs and go on to describe them as indicated for several conditions ranging from addiction to Alzheimer’s disease.  Currently 5.4% of all medication prescriptions in the United States are for GLP-1 agonists.  These drugs have been around for 20 years and during that time transitioned from use primarily for Diabetes Mellitus Type 2 to weight loss. Despite all the clinical trials and experience with them I do not think the final verdict is in and the main papers relevant to this post will illustrate why.    

The first paper (1) is a large observational study using databases from the Veterans Administration (VA) health care system (1).  The authors describe the rationale of their study as looking at the real-world outcomes of the use of GLP-1 agonists – both the positive effects and adverse outcomes. They had an N of 1,955,135 followed for a median of 3.68 years looking at 175 health outcomes.  The authors use an interesting methodology.  Patients were recruited based on incident use of a medications for Type 2 diabetes mellitus (T2DM) between October 1, 2017 and December 31, 2023.  That created 4 groups based on the medical treatment of T2DM)  including GLP-1 agonists (N= 232,210), sulfonylureas (N= 247,146), Dipeptidyl peptidase-4 (DPP-4i) inhibitors (N= 225,116), and SGLT2i inhibitors (sodium-glucose cotransporter 2 inhibitors) (N= 429,172).  There was also a treatment as usual (TAU) group (N= 1,513,896) with Type 2 DM who took non-GLP-1 antihyperglycemics between the study dates of October 1, 2017 and December 31, 2023.  As a point of reference, I have included a table of the medications in each class used for T2DM. 

Glucagon-like peptide 1 (GLP-1) agonists

exenatide (Bydureon)

exenatide (Byetta)

liraglutide (Victoza)

liraglutide (Saxenda)

dulaglutide (Trulicity)

semaglutide (Wegovey)

semaglutide (Ozempic)

semaglutide (Rybelsus)

tirzepatide (Mounjaro)

tirzepatide (Zepbound)

 

 

Sulfonylureas

Glipizide

Glimepiride

Glyburide

 

 

 

dipeptidyl peptidase 4 (DPP4) inhibitors

alogliptin (Nesina, Vipidia)

sitagliptin (Januvia)

saxagliptin (Onglyza)

linagliptin (Tradjenta)

 

 

sodium−glucose cotransporter-2 (SGLT2) inhibitors)

bexagliflozin (Brenzavvy)

canagliflozin (Invokana)

dapagliflozin (Farxiga)

empagliflozin (Jardiance)

ertugliflozin (Steglatro)

 

This study was designed to assess groups on 175 health outcomes from these treatment cohorts compared with two control groups.  One control group was a composite of equal numbers of diabetic subjects using oral hypoglycemics and the other control groups was diabetics who continued GLP-1 agonists that they had already been started on.  Results varied but generally the health outcomes measured were significantly improved on the GLP-1 agonists compared with the controls and across categories.  For example, when GLP-1 agonists were compared with the sulfonylurea, DPP4, and SGLT2 classes outcomes were improved in 13.14%, 17.14%, and 11.43% of the outcomes respectively. 

Risk of adverse outcomes were 8%, 7.43%, and 16.57% in the same order.  Those adverse events in aggregate included: nausea and vomiting, gastroesophageal reflux disease (GERD), sleep disturbances, bone pain, abdominal pain, hypotension, headaches, nephrolithiasis, and anemia. 

When comparing the addition of GLP-1s to treatment as usual (the composite control) better outcomes were observed in 24% and increased risk of adverse outcomes in 10.86% of outcomes.

The reduced risk of several CNS disorders were estimated by hazard ratios and they were modestly decreased for alcohol use disorder, cannabis use disorder, stimulant use disorder, opioid use disorder, suicidal ideation of self-injury, bulimia, schizophrenia, seizures and neurocognitive disorders.  Risk reductions were in the 10-16% range. 

The authors of this paper use several graphing techniques to present their data.  They graphed hazard ratios for both improved and adverse outcomes and made negative log transformed Manhattan plots as a measure of statistical robustness as alternate graphing technique.  The paper is open access and I encourage reading the paper to see these data presentations.  I included a partial Forest plot at the top of this post to illustrate some of these graphs and the outcomes they measured. The blue dots indicate reduced risk relative to controls and the orange dots indicate increased risk (calculated as hazard ratios (3).

The strength of this study is that it summarizes a large amount of data across a VA database.  Since it is administrative data it is collected in nonstandard way and the diagnoses are not necessarily made by experts - this data may not be as robust as a prospective randomized clinical trial.  The population was older white veterans and that may be a factor when considering pleotropic effects.  The authors conclude that the GLP-1 agonists had broad pleotropic effects based on the spectrum of positive results and preclinical work.  They emphasize the positive results for neuropsychiatric diseases and disorders.  They discuss the issue of suicidal behavior and point out that earlier studies raised concerns to the point that the European Medicines Agency investigated and found no evidence for causality.  This study showed decreased suicidality and possible antidepressant effects.  The results generally showed significant positive effects on outcomes across major disease categories with a clear group of adverse effects.   


For comparison there is a recent large retrospective cohort study (2) that uses deidentified data on patients from 66 different health care organizations.  This appears to be a database with a commercial purpose, but I cannot identify what that purpose might be based on their web site.  In their rollover map, most of the deidentified patients in this database are Americans.  The study was approved by an IRB in China and I assume that is where the analysis takes place.  The study was focused on examining the effects of GLP-1 agonists on patients being treated for obesity.  Subjects were selected for a diagnosis of obesity and incident use of a GLP-1 agonist. It was a retrospective cohort analysis similar to the first study but propensity score matching was done to pair treatment subjects more closely with controls. Exclusion criteria included use of any other weight loss drug and any psychiatric diagnosis or significant symptom like suicidality.

The main results of this study are summarized in 3 tables in the body of the paper (Tables 2, 3, and 4).  Psychiatric outcomes were measured over a period of 5 years and the percentage of patients with major depression, any anxiety, any psychiatric disorder and suicidality (ideation or behaviors) we measured at 6 months, 1 year, 3 years, and 5 years.  The cumulative incidences of disorders and suicidality increased over these intervals.  Hazard ratios were calculated compared with the control population and they were generally doubled.  

Results stratified on demographic factors and GLP-1 agonist potency showed that both sexes had higher than expected psychiatric morbidity associated with GLP-1 agonist use but that women had significantly higher hazard ratios across all categories. Age was inversely correlated with older populations having lower risk of psychiatric comorbidity. Finally, the potency of the GLP-1 agonist directly correlated with potency of the GLP-1 agonist and time of exposure.  The authors discuss the limitations of their study and implications for future use and study.

Both studies generally illustrate some of the advantages and problems of conducting large clinical trials. The numbers in the hundreds of thousands or million plus range would be very difficult if not impossible to conduct randomized clinical trials on.  It is manageable using the naturalistic retrospective designs employed here commonly referred to as real world designs.  The obvious limiting factor is expense and the methodological problem of drop outs over time.  In these specific cases the first study is selecting a subject cohort based on a diagnosis of diabetes mellitus type 2 (DMT2) and the second obesity.  Both are heterogeneous populations with some overlap.  If I was influenced at all by some of the current psychiatric literature, I might suggest transdiagnostic features common to both but the importance of that term seems inflated relative to common medical diagnostic formulations.  Instead - I will use the parlance of medical trials and point out that there are signals in both papers.  Those signals are both good and not so good.  In the first paper there were clearly improvements in many medical outcomes when T2DM was treated with GLP-1 agonists in about 25% of the conditions studied and adverse outcomes in about 10%.  Improvement occurred in conditions outside of the endocrine/metabolic sphere including some psychiatric conditions. In the second study, significant increases in psychiatric conditions were noted to occur associated with GLP-1 agonist potency and total exposure in a population selected for obesity treatment.  The authors are careful to point out that obesity and metabolic syndrome may be a risk factor for mood disorders and they provide an excellent discussion of how trial design and patient selection may have affected these results.  

When these trials are reported in the news, they are generally not reported as showing modest results.  Side effects are typically ignored.  I have not heard anything about the study that showed that increased rather than decreased psychiatric morbidity may be a possible outcome.  The media generally reports them as miracle drugs and patients with the best possible results are given as examples.

GLP-1 agonists are clearly serious medications with potentially serious adverse effects.  The prescription of these medications requires close monitoring and thorough patient education.  If I was prescribing these medications today - in the informed consent discussion I would include the potential for modest outcomes, potentially increased psychiatric side effects, the general potential for side effects, and why outcomes may be variable.  I would also make sure to let people know that long term outcomes at this point are not known with any degree of certainty.    

   

George Dawson, MD, DFAPA

 

References:

1:  Xie Y, Choi T, Al-Aly Z. Mapping the effectiveness and risks of GLP-1 receptor agonists. Nat Med. 2025 Jan 20. doi: 10.1038/s41591-024-03412-w. Epub ahead of print. PMID: 39833406.

2:  Kornelius E, Huang JY, Lo SC, Huang CN, Yang YS. The risk of depression, anxiety, and suicidal behavior in patients with obesity on glucagon like peptide-1 receptor agonist therapy. Sci Rep. 2024 Oct 18;14(1):24433. doi: 10.1038/s41598-024-75965-2. PMID: 39424950; PMCID: PMC11489776

3:  Spruance SL, Reid JE, Grace M, Samore M. Hazard ratio in clinical trials. Antimicrob Agents Chemother. 2004 Aug;48(8):2787-92. doi: 10.1128/AAC.48.8.2787-2792.2004. PMID: 15273082; PMCID: PMC478551.

4:  Sam AH, Salem V, Ghatei MA. Rimonabant: From RIO to Ban. J Obes. 2011;2011:432607. doi: 10.1155/2011/432607. Epub 2011 Jul 6. PMID: 21773005; PMCID: PMC3136184


Graphic credit:

Table at the top of the post of form Reference 1 and it is not copyrighted. The comparison Table was made by me.