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ADHD is usually framed as a dopamine-and-norepinephrine condition, but recent studies have revealed that serotonin may also play a significant role. To delve deeper into this, we conducted a systematic literature review of studies looking at serotonin, its receptors, and the serotonin transporter (SERT) in relation to ADHD. The result: serotonin appears to be an important piece of the puzzle, but the overall picture is quite complex.
An ADHD & Serotonin Literature Review:
The authors searched the literature without time limits and screened thousands of records to end up with 95 relevant publications. Those included animal/basic-science work, neuroimaging, pharmacodynamics, a couple of large genetic/transcriptomic studies (GWAS and a cortico-striatal TWAS), and a few clinical reports. Each paper was graded for quality: 17 high, 59 medium, and 19 low.
As the study points out, the idea that serotonin may play a role in the neurobiology of ADHD is not new, but this literature review “identified multiple individual strands of evidence gathered over several decades and brought them into a more coherent focus”. It concludes that serotonergic neurotransmission is implicated in ADHD. This doesn’t mean variations in serotonin levels cause ADHD, but that serotonin may be a plausible target for future treatments and research.
ADHD is polygenic and multi-systemic. For now, clinicians and patients should view serotonin as part of a complex network that may contribute to ADHD symptoms. More research is needed before making treatment decisions based on these findings.
Faraone, S. V., Ward, C. L., Boucher, M., Elbekai, R., & Brunner, E. (2025). Role of serotonin in the neurobiology of attention-deficit/hyperactivity disorder: a systematic literature review. Expert Opinion on Therapeutic Targets, 1–18. https://doi.org/10.1080/14728222.2025.2552324
Although there has been much research documenting that ADHD adults are at risk for other psychiatric and substance use disorders, relatively little is known about whether ADHD puts adults at risk specifically for somatic medical disorders.
Given that people with ADHD tend toward being disorganized and inattentive, and that they tend to favor short-term over long-term rewards, it seems logical that they should be at higher risk for adverse medical outcomes. But what does the data say?
In a systematic review of the literature, Instances and colleagues have provided a thorough overview of this issue. Although they found 126 studies, most were small and were of "modest quality". Thus, their results must be considered to be suggestive, not definitive for most of the somatic conditions they studied.
Also, they excluded articles about traumatic injuries because the association between ADHD and such injuries is well established. Using qualitative review methods, they classified associations as being a) well-established; b) tentative, or c) lacking sufficient data.
Only three conditions met their criteria for being a well-established association: asthma, sleep disorders, and obesity.
They found tentative evidence implicating ADHD as a risk factor for three conditions: migraine headaches, celiac disease, and diseases of the circulatory system.
These data are intriguing, but cannot tell us why ADHD people are at increased risk for somatic conditions. One possibility is that suffering from ADHD symptoms can lead to an unhealthy lifestyle, which leads to increased medical risk. Another possibility is that the biological systems that are dysregulated in ADHD are also dysregulated in some medical disorders. For example, we know that there is some overlap between the genes that increase the risk for ADHD and those that increase the risk for obesity. We also know that the dopamine system has been implicated in both disorders.
Instances and colleagues also point out that some medical conditions might lead to symptoms that mimic ADHD. They give sleep-disordered breathing as an example of a condition that can lead to the symptom of inattention.
But this seems to be the exception, not the rule. Other medical conditions co-occurring with ADHD seem to be true comorbidities, rather than the case of one disorder causing the other. Thus, primary care clinicians should be alert to the fact that many of their patients with obesity, asthma, or sleep disorders might also have ADHD.
By screening such patients for ADHD and treating that disorder, you may improve their medical outcomes indirectly via increased compliance with your treatment regime and an improvement in health behaviors. We don't yet have data to confirm these latter ideas, as the relevant studies have not yet been done.
Serotonin is a key chemical in the body that helps regulate mood, behavior, and also many physical functions such as sleep and digestion. It has also been linked to how ADHD (attention-deficit/hyperactivity disorder) develops in the brain. This study looks at how serotonin may be involved in both the mental health and physical health conditions that often occur alongside ADHD.
It is well-established that ADHD is more than just trouble focusing or staying still. For many, it brings along a host of other physical and mental health challenges. It is very common for those with ADHD to also have other diagnosed disorders. For example, those with ADHD are often also diagnosed with depression, anxiety, or sleep disorders. When these issues overlap, they are called comorbidities.
A new comprehensive review, led by Dr. Stephen V. Faraone and colleagues, delves into how serotonin (5-HT), a major brain chemical, may be at the heart of many of these common comorbidities.
Serotonin is a neurotransmitter most often linked to mood, but its role in regulating the body has much broader implications. It regulates sleep, digestion, metabolism, hormonal balance, and even immune responses. Although ADHD has long been associated with dopamine and norepinephrine dysregulation, this review suggests that serotonin also plays a central role, especially when it comes to comorbid conditions.
This research suggests that serotonin dysregulation could explain the diverse and sometimes puzzling range of symptoms seen in ADHD patients. It supports a more integrative model of ADHD—one that goes beyond the brain’s attention, reward and executive control circuits and considers broader physiological and psychological health.
future research into the role of serotonin could help develop more tailored interventions, especially for patients who don't respond well to stimulant medications. Future studies may focus on serotonin’s role in early ADHD development and how it interacts with environmental and genetic factors.
This study is a strong reminder that ADHD is a complex, multifaceted condition. Differential diagnosis is crucial to properly diagnosing and treating ADHD. Clinicians' understanding of the underlying link between ADHD and its common comorbidities may help future ADHD patients receive the individualized care they need. By shedding light on serotonin’s wide-reaching influence, this study may provide a valuable roadmap for improving how we diagnose and treat those with complex comorbidities in the future.
Taiwan's National Health Insurance program is a single-payer system that covers 99.6% of the island's 23 million residents. It includes family relationships.
This enabled a Taiwanese study team to examine the comorbidity of psychiatric disorders among close relatives in the entire population over eleven years, beginning at the start of 2001 and concluding at the end of2011.
For greater certainty of diagnosis, only persons twice diagnosed with the same psychiatric disorder were included as index individuals. There were 431,887 index patients, 152,443 of whom were ADHD index patients.
These index patients were then compared with all of their first-degree relatives (FDRs): parents, children, siblings, and twins. This produced 1,017,430 patient-FDR pairs, of which 401,301 were ADHD patient-FDR pairs.
Next, four controls were matched by age, gender, and type relative to each case, resulting in 4,069,720 control pairs.
After adjusting for age, gender, urbanization, and income level, ADHD patients were seven times more likely than controls to have first-degree relatives with ADHD. They were also seven times more likely to have FDRs with major depressive disorder, four times more likely to have FDRs with autism spectrum disorder, twice as likely to have FDRs with bipolar disorder, and 80%more likely to have FDRs with schizophrenia.
Stimulant medications, such as methylphenidate (Ritalin) and amphetamines (Adderall), are among the most widely prescribed drugs in the world. In the United States alone, prescription rates have climbed more than 50% over the past decade, driven largely by growing awareness of ADHD in both children and adults. Yet stimulants also have a long history of non-medical use, and concerns about their psychological risks persist among patients, families, and clinicians alike.
Two major studies now offer the clearest picture yet of what that risk actually looks like, and who it may affect.
The Background:
Before turning to the research, it helps to understand the landscape. A notable share of stimulant users misuse their medication: roughly one in four takes it in ways other than prescribed, and about one in eleven meets criteria for Prescription Stimulant Use Disorder (PSUD). Counterintuitively, most people with PSUD aren’t obtaining drugs illicitly — they’re misusing their own prescriptions.
This distinction between therapeutic and non-therapeutic use turns out to be critical when evaluating psychosis risk.
The Study:
A comprehensive meta-analysis by Jangra and colleagues pooled data across more than a dozen studies to compare psychotic outcomes in people using stimulants therapeutically versus non-therapeutically. The contrast was striking.
Among therapeutic users (more than 220,000 individuals taking stimulants at prescribed doses under medical supervision), psychotic episodes occurred in roughly one in five hundred people. When symptoms did appear, they typically emerged after prolonged treatment or in individuals with pre-existing psychiatric vulnerabilities, and they usually resolved when the medication was stopped.
Among non-therapeutic users (over 8,000 participants across twelve studies, many using methamphetamine or high-dose amphetamines), nearly one in three experienced psychotic symptoms. These episodes tended to be more severe, involving persecutory delusions and hallucinations, with faster onset and a greater likelihood of recurrence or persistence.
The biology underlying this difference is well understood. When stimulants are taken orally at guideline-recommended doses, they produce moderate, gradual changes in neurotransmitter activity central to attention and executive functions. The brain tolerates these changes relatively well. Non-therapeutic use, by contrast, often involves much higher doses that are frequently delivered through non-oral routes such as injection or smoking. This produces a rapid, excessive surge in dopamine activity, which is precisely the neurochemical pattern associated with psychotic symptoms.
The takeaway here is not that therapeutic stimulant use is risk-free, but that risk is strongly modulated by dose, route of administration, and individual psychiatric history. Clinicians are advised to monitor patients with pre-existing mood or psychotic disorders, particularly carefully.
A Nationwide Study Focuses on Methylphenidate Specifically:
Where the meta-analysis cast a wide net, a large-scale population study by Healy and colleagues drilled into a specific and clinically pressing question: does methylphenidate (the most commonly prescribed ADHD medication, also known as Ritalin) increase the risk of developing a psychotic disorder?
To find out, the researchers analyzed Finland's national health insurance database, tracking nearly 700,000 individuals diagnosed with ADHD. Finland's single-payer system made this kind of comprehensive, long-term tracking possible in a way that fragmented healthcare systems rarely allow.
Critically, the team adjusted for a range of confounding factors that have clouded previous research, including sex, parental education, parental history of psychosis, and the number of psychiatric visits and diagnoses prior to the ADHD diagnosis itself (a proxy for illness severity). After these adjustments, they found no significant difference in the risk of schizophrenia or non-affective psychosis between patients treated with methylphenidate and those who remained unmedicated. This held true even among patients with four or more years of continuous methylphenidate use.
The Take-Away:
When considered together, these studies offer meaningful reassurance without encouraging complacency.
For patients and families weighing ADHD treatment, the evidence suggests that methylphenidate used as prescribed does not increase psychosis risk, even over years of use. The rare cases of stimulant-associated psychosis in therapeutic settings are typically linked to high doses, pre-existing vulnerabilities, or both, and tend to resolve with discontinuation.
For clinicians, the findings reinforce the importance of baseline psychiatric assessment before initiating stimulant therapy, ongoing monitoring in patients with mood or psychotic disorder histories, and clear patient education about the risks of dose escalation or non-oral use.
The picture that emerges is one of a meaningful distinction between a medication used carefully within its therapeutic window and a drug misused outside of it. This distinction matters enormously when communicating risk to patients, policymakers, and the public.
ADHD is commonly treated with medication, but these treatments frequently cause side effects such as reduced appetite and disrupted sleep. Psychological and behavioral therapies exist as alternatives, but they tend to be expensive, hard to scale, and generally do little to address the motor difficulties that many children with ADHD experience — things like clumsy movement, poor handwriting, or difficulty with coordination.
Physical exercise has attracted attention as a more accessible option. But research findings have been mixed, partly because studies vary so widely in how exercise is delivered and what outcomes they measure. This meta-analysis, drawing on 21 studies involving 850 children and adolescents aged 5–20 with a clinical ADHD diagnosis, tries to cut through that noise.
Two types of motor skills
The researchers separated motor skills into two broad categories:
The Data:
Gross motor skills (16 studies, 613 participants)
Overall, exercise produced medium-to-large improvements in gross motor skills. The strongest gains were in:
No significant gains were found in balance or flexibility.
Fine motor skills (13 studies, 553 participants):
Exercise also produced medium-to-large improvements in fine motor skills, specifically:
The Results: What Kind of Exercise Works Best?
Two factors stood out consistently across both gross and fine motor skills: session length and frequency.
The type of exercise mattered; structured programs with clear motor-skill components (rather than unstructured physical activity) yielded stronger results.
These results are not without caveats, however. The authors urge caution in interpreting these findings. A few key limitations include:
The Bottom Line
This meta-analysis provides tentative moderate evidence that structured physical exercise can meaningfully support motor skill development in children and adolescents with ADHD — particularly when sessions run longer than 45 minutes and occur at least three times a week. The benefits appear most robust for object control, locomotion, handwriting, and manual dexterity.
That said, the evidence base still has real gaps. The authors call for better-designed, fully randomized controlled trials with consistent methods, standardized ways of measuring exercise intensity, and greater inclusion of children and adolescents who are not on medication — all of which would help clarify when, how, and for whom exercise works best.
Treatment guidelines for childhood ADHD recommend medications as the first-line treatment for most youth with ADHD. Still, concerns about side effects and long-term outcomes have increased interest in non-pharmacological approaches. Researchers at Saudi Arabian Armed Forces hospitals recently conducted a network meta-analysis comparing several interventions, including mindfulness-based therapy, cognitive behavioral therapy, behavioral parent training, neurofeedback, yoga, virtual reality programs, and digital working memory training.
Although the authors aimed to “provide a rigorous methodological approach to combine evidence from multiple treatment comparisons,” the study illustrates several pitfalls that arise when network meta-analysis is applied to a thin and heterogeneous evidence base.
What Network Meta-analysis Can and Cannot Do:
Network meta-analysis extends conventional meta-analysis by combining:
When the evidence network is large and well-connected, this approach can provide useful estimates of comparative effectiveness among many treatments.
This method is not always best, however, as many networks are sparse. This is especially true in areas such as complementary or behavioral therapies. In sparse networks, estimates rely heavily on indirect comparisons, and single studies can exert disproportionate influence over the results.
Conventional meta-analysis focuses on heterogeneity, meaning differences in results across studies within the same comparison.
Network meta-analysis must additionally evaluate consistency, whether the direct and indirect evidence agree.
However, when comparisons are supported by only one or two studies and the network is weakly connected, statistical tests for heterogeneity and consistency have very little power. In practice, this means the analysis often cannot detect problems even if they are present.
Sparse networks also make publication bias difficult to evaluate. This concern is particularly relevant in fields dominated by small trials and emerging therapies.
Why Such Treatment Rankings Are Appealing, but Potentially Problematic:
Many network meta-analyses summarize results using SUCRA, which estimates the probability that each treatment ranks best.
SUCRA, or Surface Under the Cumulative Ranking, is a key statistical metric in network meta-analyses. It is used to rank treatments by efficacy or safety. This is achieved by summarizing the probabilities of a treatment's rank into a single percentage, where a higher SUCRA value indicates a superior treatment. Ultimately, SUCRA helps pinpoint the most effective intervention among the ones compared.
Again, in well-supported networks, SUCRA can provide a useful summary of comparative effectiveness. But in sparse networks, rankings can create an illusion of precision, because treatments supported by a single small study may appear highly ranked simply due to random variation.
What Did this New Network Meta-analysis Study?
The study includes 16 trials with a total of 806 participants. But the structure of the evidence network is far weaker than this headline number suggests.
Based on the underlying studies:
This produces a very thin network, in which several interventions rely entirely on single studies.
Another challenge is that the included trials measure different outcomes. Some evaluate ADHD symptom severity, while others measure parental stress.
When studies use different outcome scales, meta-analysis typically relies on standardized measures such as the standardized mean difference to allow comparisons across studies. However, the analysis reports only mean-average differences, making it difficult to interpret the relative effect sizes.
Study Issues (including Limited Evidence and Risk of Bias):
The intervention supported by the largest number of studies (family mindfulness-based therapy) was one of the two approaches reported as producing statistically significant results. The other was BrainFit, which is supported by only a single previous trial.
Despite this limited evidence base, the study ranks interventions using SUCRA:
Notably, none of the runner-up interventions demonstrated statistically significant efficacy.
The authors acknowledge methodological limitations in the included studies:
“Blinding of participants and personnel (performance bias) exhibited notable concerns, as blinding for active treatment was not applicable in most studies.”
Such limitations are common in behavioral intervention trials, but they further increase uncertainty in already small evidence networks.
Conclusions:
The study ultimately concludes:
“This network meta-analysis supports MBT and BPT as effective non-pharmacological treatments for ADHD.”
However, the evidence underlying these claims is limited. Some analyses rely on very small numbers of studies and participants, and the network structure depends heavily on indirect comparisons.
Network meta-analysis can be a powerful tool when applied to a large, consistent, and well-connected body of evidence. When the evidence base is sparse, however, the resulting rankings and comparisons may appear statistically sophisticated while resting on a fragile evidentiary foundation.
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