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July 21, 2025
New research has uncovered important links between certain blood metabolites and ADHD by using a genetic method called Mendelian randomization. This approach leverages natural genetic differences to help identify which metabolites might actually cause changes in ADHD risk, offering stronger clues than traditional observational studies.
Key Metabolic Pathways Involved:
The study found 42 plasma metabolites with a causal relationship to ADHD. Most fall into two major groups:
Since many metabolites come from dietary sources like proteins and fats this supports the idea that diet could influence metabolic pathways involved in ADHD. However, because the study focused on genetic influences on metabolite levels, it doesn’t directly prove that dietary changes will have the same effects.
Notable Metabolites:
Five metabolites showed bidirectional links with ADHD, meaning genetic risk for ADHD also affects their levels which suggests a complex interaction between brain function and metabolism.
Twelve ADHD-related metabolites are targets of existing drugs or supplements, including:
While these findings highlight biological pathways, they don’t prove that changing diet will directly alter ADHD symptoms. Metabolite levels are shaped by genetics plus environment, lifestyle, and health factors, which require further study.
Conclusion:
This research provides stronger evidence of metabolic pathways involved in ADHD and points to new possibilities for diagnosis and treatment. Future work could explore how diet or drugs might safely adjust these metabolites to help manage ADHD.
While this study strengthens the link between amino acid and fatty acid metabolism and ADHD risk, suggesting that diet could play a role, ultimately more research is still needed before experts could use this research to give specific nutritional advice.
Shi S, Baranova A, Cao H, Zhang F. Exploring causal associations between plasma metabolites and attention-deficit/hyperactivity disorder. BMC Psychiatry. 2025 May 16;25(1):498. doi: 10.1186/s12888-025-06951-9. PMID: 40380147; PMCID: PMC12084988.
A relatively new area of ADHD research has been examining the association between ADHD and eating disorders (i.e., anorexia nervosa, bulimia nervosa, and binge-eating disorder). Nazar and colleagues conducted a systematic review and meta-analysis of extant studies.
They found only twelve studies that assessed the presence of eating disorders among people with ADHD and five that examined the prevalence of ADHD among patients with eating disorders. Although there were few studies, the total number of people studied was large, with 4,013 ADHD cases and 29,404 controls for the first set of studies and 1,044 eating disorder cases and 11,292 controls for the second set of studies. The meta-analyses of these data found that ADHD people had a 3.8-fold increased risk for an eating disorder compared with non-ADHD controls. The level of risk was similar for each of the eating disorders. Consistent with this, their second meta-analysis found that people with eating disorders had a 2.6-fold increased risk for ADHD compared with controls who did not have an eating disorder. The risk for ADHD was highest for those with binge-eating disorder (5.8-fold increased risk compared with controls).
This bidirectional association between ADHD and eating disorders provides converging evidence that this association is real and, given its magnitude, clinically significant. The results were similar for males and females and pediatric and adult populations.
We cannot tell from these data why ADHD is associated with eating disorders. Nazar et al. note that other work implicates both impulsivity and inattention in promoting bulimic symptoms, whereas inattention and hyperactivity are associated with craving. The association may also be due to the neurocognitive deficits of ADHD, which could lead to a distorted sense of self-awareness and body image.
Given that ADHD is also associated with obesity, some obese ADHD patients may have an underlying eating disorder, such as binge-eating, which has been associated with obesity in prospective studies. Also, lisdexamfetamine is FDA-approved for treating both binge eating and ADHD, which suggests the possibility that the two conditions share an underlying etiology involving the dopamine system. We do not know if treating ADHD would reduce the risk for eating disorders, as that hypothesis has not yet been tested. But such an effect would seem likely if ADHD behaviors mediate the association between the two disorders.
If we are to read what we believe on the Internet, dieting can cure many of the ills faced by humans. Much of what is written is true. Changes in dieting can be good for heart disease, diabetes, high blood pressure, and kidney stones to name just a few examples. But what about ADHD? Food elimination diets have been extensively studied for their ability to treat ADHD. They are based on the very reasonable idea that allergies or toxic reactions to foods can have effects on the brain and could lead to ADHD symptoms.
Although the idea is reasonable, it is not such an easy task to figure out what foods might cause allergic reactions that could lead to ADHD symptoms. Some proponents of elimination diets have proposed eliminating a single food, others include multiple foods, and some go as far as to allow only a few foods to be eaten to avoid all potential allergies. Most readers will wonder if such restrictive diets, even if they did work, are feasible. That is certainly a concern for very restrictive diets.
Perhaps the most well-known ADHD diet is the Feingold diet(named after its creator). This diet eliminates artificial food colorings and preservatives that have become so common in the western diet. Some have claimed that the increasing use of colorings and preservatives explains why the prevalence of ADHD is greater in Western countries and has been increasing over time. But those people have it wrong. The prevalence of ADHD is similar around the world and has not been increasing over time. That has been well documented but details must wait for another blog.
The Feingold and other elimination diets have been studied by meta-analysis. This means that someone analyzed several well-controlled trials published by other people. Passing the test of meta-analysis is the strongest test of any treatment effect. When this test is applied to the best studies available, there is evidence that the exclusion of fool colorings helps reduce ADHD symptoms. But more restrictive diets are not effective. So removing artificial food colors seems like a good idea that will help reduce ADHD symptoms. But although such diets ‘work’, they do network very well. On a scale of one to 10where 10 is the best effect, drug therapy scores 9 to 10 but eliminating food colorings scores only 3 or 4. Some patients or parents of patients might want this diet change first in the hopes that it will work well for them. That is a possibility, but if that is your choice, you should not delay the more effective drug treatments for too long in the likely event that eliminating food colorings is not sufficient. You can learn more about elimination diets from Nigg, J. T., and K.Holton (2014). "Restriction and elimination diets in ADHD treatment."Child Adolesc Psychiatr Clin N Am 23(4): 937-953.
Keep in mind that the treatment guidelines from professional organizations point to ADHD drugs as the first-line treatment for ADHD. The only exception is for preschool children where medication is only the first-line treatment for severe ADHD; the guidelines recommend that other preschoolers with ADHD be treated with non-pharmacologic treatments, when available. You can learn more about non-pharmacologic treatments for ADHD from a book I recently edited: Faraone, S. V. &Antshel, K. M. (2014). ADHD: Non-Pharmacologic Interventions. Child AdolescPsychiatr Clin N Am 23, xiii-xiv.
A Swedish-Danish-Dutch team used the Swedish Medical Birth Register to identify the almost 1.7 million individuals born in the country between 1980 and 1995. Then, using the Multi-Generation Register, they identified 341,066 pairs of full siblings and 46,142 pairs of maternal half-siblings, totaling 774,416 individuals.
The team used the National Patient Register to identify diagnoses of ADHD, as well as neurodevelopmental disorders (autism spectrum disorder, developmental disorders, intellectual disability, motor disorders), externalizing psychiatric disorders (oppositional defiant and related disorders, alcohol misuse, drug misuse), and internalizing psychiatric disorders (depression, anxiety disorder, phobias, stress disorders, obsessive-compulsive disorder).
The team found that ADHD was strongly correlated with general psychopathology overall (r =0.67), as well as with the neurodevelopmental (r = 0.75), externalizing (r =0.67), and internalizing (r = 0.67) sub factors.
To tease out the effects of heredity, shared environment, and non-shared environment, a multivariate correlation model was used. Genetic variables were estimated by fixing them to correlate between siblings at their expected average gene sharing (0.5for full siblings, 0.25 for half-siblings). Non-genetic environmental components shared by siblings (such as growing up in the same family) were estimated by fixing them to correlate at 1 across full and half-siblings. Finally, non-shared environmental variables were estimated by fixing them to correlate at zero across all siblings.
This model estimated the heritability of the general psychopathology factor at 49%, with the contribution of the shared environment at 7 percent and the non-shared environment at 44%. After adjusting for the general psychopathology factor, ADHD showed a significant and moderately strong phenotypic correlation with the neurodevelopmental-specific factor (r = 0.43), and a significantly smaller correlation with the externalizing-specific factor (r = 0.25).
For phenotypic correlation between ADHD and the general psychopathology factor, genetics explained 52% of the total correlation, the non-shared environment 39%, and the shared familial environment only 9%. For the phenotypic correlation between ADHD and the neurodevelopmental-specific factor, genetics explained the entire correlation because the other two factors had competing effects that canceled each other out. For the phenotypic correlation between ADHD and the externalizing-specific factor, genetics explained 23% of the correlation, shared environment 22%, and non-shared environment 55%.
The authors concluded that "ADHD is more phenotypically and genetically linked to neurodevelopmental disorders than to externalizing and internalizing disorders, after accounting for a general psychopathology factor. ... After accounting for the general psychopathology factor, the correlation between ADHD and the neurodevelopmental-specific factor remained moderately strong, and was largely genetic in origin, suggesting substantial unique sharing of biological mechanisms among disorders. In contrast, the correlation between ADHD and the externalizing-specific factor was much smaller and was largely explained by-shared environmental effects. Lastly, the correlation between ADHD and the internalizing subfactor was almost entirely explained by the general psychopathology factor. This finding suggests that the comorbidity of ADHD and internalizing disorders are largely due to shared genetic effects and non-shared environmental influences that have effects on general psychopathology."
Executive functions (EFs) are the cognitive control systems that allow people to pursue goals, make decisions, and adapt to changing circumstances. Researchers generally break them into three overlapping capacities: working memory (holding and manipulating information in mind), inhibitory control (suppressing impulses and filtering out distractions), and cognitive flexibility (switching between tasks or mental frameworks). Strong EFs in childhood predict academic achievement, social competence, and long-term mental health; weaknesses in these areas that go unaddressed can persist into adulthood, undermining school performance, career prospects, and well-being.
The Background:
Interest in training these skills has grown rapidly, but most research has been conducted in Western settings. China presents a distinctive context. Collectivist values make group-based programs culturally natural, and parental investment in academic outcomes is high. Both of these factors should, in theory, work in an intervention’s favor. At the same time, tightly scheduled school days (sessions typically capped at 30 minutes or less) constrain what is actually deliverable. A growing number of randomized controlled trials (RCTs) have tested EF interventions with Chinese children, but until now, no one has pulled that evidence together systematically.
The Study:
A new network meta-analysis did exactly that. The researchers screened RCTs involving Chinese children aged 3–12, including both typically developing children and those showing subclinical signs of ADHD or autism spectrum disorder (ASD), for instance, siblings of children with an ASD diagnosis. Children who already carried a formal neurodevelopmental diagnosis were excluded. Fifty-two trials covering nearly 3,000 children met the inclusion criteria. Interventions fell into four categories:
The headline finding is that three of the four intervention types produced statistically significant improvements across all three EF domains. The exception was the hybrid physical-cognitive program, which did not reach significance for inhibitory control. Positive results across the board might sound encouraging until you look at the actual effect sizes.
The Results:
The actual effects were negligible. Every significant result fell well below what methodologists define as a “small” effect (a standardized mean difference, or SMD, of 0.2). The largest effect size in the entire analysis was an SMD of 0.097 (less than half that threshold). The authors summarize the interventions’ effects as “modest,” but that is generous phrasing for numbers that, in practical terms, amount to very little. The analysis also showed signs of publication bias, meaning that studies with null or negative results may not have been published, potentially inflating even these modest figures.
The Take-Away:
It is important to note that these results don’t necessarily mean that this is the last word on EF training. The results apply specifically to Chinese children working within the time constraints of Chinese school schedules, and they exclude children with diagnosed ADHD, a population for whom cognitive interventions sometimes show larger effects. Generalizing beyond those boundaries is unwarranted.
What the findings do suggest is that structured EF programs, as currently implemented in Chinese educational settings, are not delivering meaningful real-world benefits. Statistical significance, it is worth remembering, is not the same as practical significance, and the gap between the two is sharp here.
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Language is powerful. The words we choose not only reflect our understanding of the world but also actively shape it. Recently, this truth has been at the center of a growing debate in the mental health field regarding how we talk about ADHD.
In a recent paper published in The Lancet Psychiatry titled “The Power of Words: Respectful Language in ADHD Research,” French and colleagues advocated for a shift toward "neurodiversity-affirmative language”. Rooted in the social model of disability, their proposal encourages researchers to abandon traditional medical terminology, e.g., words like disorder and deficit, in favor of more neutral terms such as condition and challenge.
My colleague, Dr. Michael Miller, and I read this with great interest. We completely agree that revising language is essential to good science and that, both as researchers and as human beings, we are ethically bound to speak respectfully. However, we felt compelled to write a response. In our new paper, we argue that while language must evolve, it must do so scientifically.
The Two Prerequisites for Language Change
If we are going to fundamentally shift our scientific lexicon, two requirements must be met:
Currently, the proposal by French and colleagues meets neither requirement. While they claim consensus is accumulating that certain terms are disrespectful, they provide zero empirical evidence that this view is shared by the community of individuals living with ADHD. Even proponents of patient-centered language admit there is surprisingly little data supporting specific language changes.
More alarmingly, the recommended changes severely dilute the scientific accuracy of our field. Let’s look at two examples.
Why a "Deficit" is Not Just a “Challenge"
French and colleagues suggest replacing the term deficit with challenge. On the surface, challenge sounds softer and more affirming. But scientifically, these words are not interchangeable.
For decades, the term deficit has been defined by a specific performance metric that falls substantially below an expected level. It is a measurable reality. A challenge, on the other hand, refers to a new or difficult task that tests someone's ability.
Every single human being is "challenged" by complex neuropsychological tests, but only some individuals who face that challenge demonstrate scientifically significant deficits. If we relabel measurable deficits as universal challenges, we sacrifice the exactness required to communicate scientific findings and accurately measure the effects of life-changing treatments.
ADHD is a Disorder, Not Just a "Condition"
Another proposal is to replace the word disorder with condition.
In mainstream psychiatry, a disorder is a clinically significant disturbance that causes distress or disability. The word purposefully separates natural human variation from the suffering (pathos) that gives pathology its meaning.
Condition is a completely neutral term. Pregnancy is a condition. Being tall is a condition. Calling ADHD a condition distances the diagnosis from the profound suffering it can cause.
French et al. argue against framing ADHD as a disorder because it exists on a spectrum without a clear cutoff, its manifestation is context-dependent, and its definition evolves. But if we apply that logic across all of medicine, the concept of disease unravels:
The Real-World Danger of Imprecise Language
This is not merely an academic debate over semantics. The language we use has real-world implications. In the United States and across the globe, our healthcare, educational, and legal systems run on precise medical language. Terms like impairment, dysfunction, and disorder are legally and administratively required to justify support services, workplace accommodations, specialized educational therapies, and medications. The language of pathology in diagnostic manuals regulates the flow of these resources.
If we reclassify ADHD as a neutral condition characterized only by challenges, we risk erecting massive bureaucratic barriers. Imprecise language could easily be used by institutions or insurance companies to deny vital care to the people who need it most.
The Need for Lexical Discipline
Attempting to characterize a clinical disorder entirely through its strengths happens in a scientific vacuum. We cannot ignore the vast body of rigorous evidence confirming that ADHD meets the long-standing criteria used by mental health science to identify clinical disorders.
As professionals, our respect for the ADHD community demands a commitment to language that is clear, correct, and evidence-based. To build genuine consensus about how we talk about ADHD, we need meaningful, collaborative dialogue that integrates compelling empirical data and rigorous theory.
This standard of "lexical discipline" is not just a technical preference. It is a vital mechanism through which science and the mental health professions uphold their duty to society.
For many ADHD patients, getting properly diagnosed and starting meds is only half the battle. The next step is figuring out the exact right dose. Historically, clinical guidelines have provided scant guidance on this critical step. This lack of direction can inadvertently foster two extremes in clinical practice: therapeutic inertia (settling for a subtherapeutic dose that leaves symptoms undertreated) or uncritical escalation (driving doses higher and higher beyond licensed limits without meaningful benefit).
To clear up this pharmacological gray area, an international team of researchers published the first comprehensive dose-effect network meta-analysis of ADHD medications in The Lancet Psychiatry. By pulling together a massive vault of clinical trial data, they mapped out exactly how efficacy and tolerability shift as doses increase.
Traditional meta-analyses evaluate head-to-head, pairwise data, comparing one drug at a specific dose directly against a placebo. However, this study utilized an advanced Bayesian hierarchical network model using restricted cubic splines.
This mathematical framework allowed the researchers to combine both direct trial data and indirect evidence simultaneously across 113 double-blind randomized controlled trials (RCTs). In total, the study evaluated data from 14,138 children/adolescents and 11,016 adults. By standardizing various formulations into basic equivalents (e.g., converting amphetamines to dextroamphetamine equivalents), they created a clear, unified map of dose ranges.
The study yielded distinct dose-response curves depending on the patient's age and the specific medication class. Rather than a linear trend in which "more medicine equals more benefit," most treatments reach a clear statistical plateau or ceiling.
For Children and Adolescents (under 18)
In the pediatric population, medications hit clear peak efficacy boundaries:
For both amphetamines and guanfacine, escalating the dosage past these points resulted in U-shaped curves, meaning further dose hikes yielded diminishing group-level symptom reduction.
For Adults (18 and older)
Adult profiles showed slightly different trajectories:
The ultimate goal of this landmark analysis is to guide shared decision-making between clinicians, patients, and families. The results send a dual message to the medical community:
A medication's true efficacy hinges on its tolerability, typically measured by how often patients discontinue treatment due to severe side effects. For amphetamines, this dropout risk scales linearly with dosage, notably exceeding placebo in children above 25 mg/day and becoming prominent in adults past 50 mg/day. In contrast, methylphenidate shows no clear dose-dependent dropout risk in pediatric patients, whereas adults face a steep risk curve: increasing the dose from 60 mg/day to 90 mg/day raises the dropout risk from 7.3% to 10.0% for only modest symptom relief. Finally, youth taking guanfacine experience a sharp climb in discontinuation risks, reaching a 9.8% median risk at 4 mg/day before data limitations obscure further trends.
The authors strongly emphasize that these findings represent group averages. Because individual metabolism, genetics, and comorbidities vary widely, some specific patients may legitimately require and tolerate higher off-label doses. However, if an unusually high dose is needed, the study suggests it should prompt a careful clinical pause, either to reassess for co-occurring conditions (like anxiety, autism, or sleep disorders) or to manage realistic expectations regarding what the medication can achieve.
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