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February 6, 2026
Acid-suppressive medications, including proton pump inhibitors (PPIs) and histamine-2 (H2) receptor antagonists, are often prescribed during pregnancy to treat heartburn and gastroesophageal reflux disease.
Research shows changes in the gut microbiome can negatively affect neurodevelopment. Since acid-suppressive medications alter gut microbiota, maternal use during pregnancy may impact offspring’s neurodevelopment. Because PPIs and H2 receptor antagonists readily cross the placental barrier, they could potentially influence fetal neurodevelopment.
The link between prenatal exposure to acid-suppressive medications and major neuropsychiatric disorders is not well understood. With the use of these medications during pregnancy rising, it is important to assess their impact on children's long-term neurodevelopment. This study examined whether maternal use of acid-suppressive drugs is associated with increased risk of neuropsychiatric disorders in children, using a large, nationwide birth cohort from South Korea.
South Korea operates a single-payer health insurance system, providing coverage for over 97% of its citizens. The National Health Insurance Service (NHIS) maintains a comprehensive database with sociodemographic details, medical diagnoses, procedures, prescriptions, health examinations, and vital statistics for all insured individuals.
A Korean research team analyzed data from over three million mother-child pairs (2010–2017) to assess the risks of prenatal exposure to acid-suppressing medications. They applied propensity scoring to adjust for maternal age, number of children, medical history, and outpatient visits before pregnancy, to minimize confounding factors. That narrowed the cohort to just over 800,000 pairs, with half in the exposed group.
With these adjustments, prenatal exposure to acid-suppressing medications was associated with 14% greater likelihood of being subsequently diagnosed with ADHD.
Yet, when 151,737 exposed births were compared to the same number of sibling controls, no association was found between prenatal exposure and subsequent ADHD, which suggests unaccounted familial and genetic factors influenced the preceding results.
The Take-Away:
Evidence of these medications negatively affecting pregnancies is mixed, mostly observational, and generally reassuring when these medications are used appropriately. Untreated GERD and gastritis, however, have known risks and associations with the development of various cancers. With no evidence of an association with ADHD (or for that matter any other neuropsychiatric disorder), there is no current evidence-based reason for expectant mothers to discontinue use of acid-suppressing medications.
Acid-Suppressive Medications and Risk of Neuropsychiatric Disorders in Children,” JAMA (2026), https://doi.org/10.1001/jama.2025.23956.
Xu YS, Chen ZR, Bian Y, Gao Y, Xin L, Wang LW. Association Between Gastroesophageal Reflux Disease and Extraesophageal Malignancies: A Systematic Review and Meta-Analysis. Cancers (Basel). 2025 Dec 4;17(23):3881. doi: 10.3390/cancers17233881. PMID: 41375082; PMCID: PMC12691378.
With the growth of the Internet, we are flooded with information about attention deficit hyperactivity disorder from many sources, most of which aim to provide useful and compelling "facts" about the disorder. But, for the cautious reader, separating fact from opinion can be difficult when writers have not spelled out how they have come to decide that the information they present is factual.
My blog has several guidelines to reassure readers that the information they read about ADHD is up-to-date and dependable. They are as follows:
Nearly all the information presented is based on peer-reviewed publications in the scientific literature about ADHD. "Peer-reviewed" means that other scientists read the article and made suggestions for changes and approved that it was of sufficient quality for publication. I say "nearly all" because in some cases I've used books or other information published by colleagues who have a reputation for high-quality science.
When expressing certainty about putative facts, I am guided by the principles of evidence-based medicine, which recognizes that the degree to which we can be certain about the truth of scientific statements depends on several features of the scientific papers used to justify the statements, such as the number of studies available and the quality of the individual studies. For example, compare these two types of studies. One study gives drug X to 10 ADHD patients and reported that 7 improved. Another gave drug Y to 100 patients and a placebo to 100 other patients and used statistics to show that the rate of improvement was significantly greater in the drug-treated group. The second study is much better and much larger, so we should be more confident in its conclusions. The rules of evidence are fairly complex and can be viewed at the Oxford Center for Evidenced Based Medicine (OCEBM;http://www.cebm.net/).
The evidenced-based approach incorporates two types of information: a) the quality of the evidence and b) the magnitude of the treatment effect. The OCEBM levels of evidence quality are defined as follows (higher numbers are better:
Non-randomized, controlled studies. In these studies, the treatment group is compared to a group that receives a placebo treatment, which is a fake treatment not expected to work.
It is possible to have high-quality evidence proving that a treatment works but the treatment might not work very well. So it is important to consider the magnitude of the treatment effect, also called the "effect size" by statisticians. For ADHD, it is easiest to think about ranking treatments on a ten-point scale. The stimulant medications have a quality rating of 5 and also have the strongest magnitude of effect, about 9 or 10.Omega-3 fatty acid supplementation 'works' with a quality rating of 5, but the score for the magnitude of the effect is only 2, so it doesn't work very well. We have to take into account patient or parent preferences, comorbid conditions, prior response to treatment, and other issues when choosing a treatment for a specific patient, but we can only use an evidence-based approach when deciding which treatments are well-supported as helpful for a disorder.
A recent CNN report, http://tinyurl.com/yannlfd6, highlighted a paper published in Pediatrics, which reported that pregnant women who use acetaminophen during pregnancy put their unborn child at two-fold increased risk for attention deficit hyperactivity disorder (ADHD). In that study, acetaminophen use during pregnancy was common; nearly half of women surveyed used the painkiller during pregnancy. Other studies have reported similar associations of acetaminophen, also known as paracetamol with ADHD or with other problems in childhood (e.g., https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5300094/, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4177119/, https://www.ncbi.nlm.nih.gov/pubmed/24566677, https://www.ncbi.nlm.nih.gov/pubmed/24163279). Given these prior findings, it seems unlikely that the new report is a chance finding. But does it make any biological sense? One answer to that question came from an epigenetic study. Such studies figure out if assaults from the environment change the genetic code. One epigenetic study found that prenatal exposure changes the fetal genome via a process called methylation. Such genomic changes could increase the risk for ADHD (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540511/). Because all of these studies are observational studies, one cannot assert with certainty that there is a causal link between acetaminophen use during pregnancy.
The observed association could be due to some unmeasured third factor. Although the researchers did a respectable job ruling out some third factors, we must acknowledge some uncertainty in the finding. That said, what should pregnant women do if they need acetaminophen. I suggest you bring this information to your physician and ask if there is a suitable alternative.
Antipsychotic medications are used to treat a variety of psychiatric disorders, including schizophrenia, bipolar disorder, sleeping problems, major depression, and severe anxiety.
Untreated maternal mental illness is associated with poor health outcomes for both mothers and their offspring. On the other hand, one must guard against any potential direct harms of medications on development – including neurological development – of the fetus.
Because prenatal use of antipsychotics is infrequent, previous observational studies have suffered from small sample sizes that have not enabled precise and reliable assessment of risk. The clinical decision about whether to continue antipsychotic treatment in patients who become pregnant has therefore remained inconclusive.
In search of more reliable guidance, an international study team conducted a systematic search of the peer-reviewed medical literature to perform the first meta-analysis on this topic.
They evaluated study quality and only included studies rated “good” or better.
Identification of ADHD was determined by clinical diagnosis.
Meta-analysis of four studies encompassing over eight million participants found a slight association. Children exposed to maternal antipsychotics during pregnancy were 11% more likely to be diagnosed with ADHD subsequently.
But even in observational studies with millions of participants, such associations – especially when slight to begin with – could be due to unmeasured confounders.
The team therefore compared children with gestational exposure to siblings from the same mother who were not exposed, to address shared genetic and social factors at the family level.
Meta-analysis of two population-based sibling-matched studies with a combined total of over 4.6 million participants in Denmark, Norway, Sweden, Finland, Iceland, and Hong Kong found no significant association between gestational exposure to antipsychotic medications and subsequent diagnosis of ADHD.
The team concluded, “Our systematic review and meta-analysis of observational studies indicates that the heightened risks of ADHD and ASD observed in children gestationally exposed to antipsychotics appear to be attributable to maternal characteristics, rather than having a causal relation to the antipsychotic itself.”
ADHD is one of the most common neurodevelopmental disorders in children, yet anyone familiar with this disorder, from clinicians and researchers to parents and patients, knows how differently it can manifest from one individual to the next. One person diagnosed with ADHD may primarily struggle with focus and staying on-task; another may find it nearly impossible to regulate their impulses or even start tasks; a third may frequently find themselves frozen with overwhelm and subject to emotional reactivity…
These are not just variations in severity; they may reflect genuinely different patterns of brain organization.
Our current diagnostic system groups all of these presentations under a single label (ADHD), with three behavioral subtypes (Hyperactive, Inattentive, and Combined) defined by symptom checklists. This framework has real clinical value of course, but it was built from behavioral observation rather than neurobiology, and may leave room for substantial heterogeneity to remain unexplained. In a new study, published in JAMA Psychiatry, researchers asked whether it’s possible to identify distinct neurobiologically subgroups within ADHD by analyzing patterns of brain structure, and whether those subgroups would map onto meaningful clinical differences.
How the Brain Was Analyzed
Researchers analyzed structural MRI scans from 446 children with ADHD and 708 typically-developing children across multiple research sites. From each scan, they constructed a morphometric similarity network; that is, a map of how different brain regions resemble one another in their structural properties. These networks reflect underlying biological organization, including shared patterns of cellular architecture and gene expression across brain regions.
From each individual's network, the research team calculated three properties that capture how each brain region functions within the broader network: how many connections it has, how efficiently it communicates with other regions, and how well it bridges different functional communities in the brain. Regions that score highly on these measures are sometimes called "hubs" and they play particularly influential roles in how information is integrated across the brain.
Rather than comparing the ADHD group to controls as a whole and looking for average differences, they used a normative modeling approach. This works similarly to a growth chart in pediatric medicine: instead of asking whether a child is above or below the group average, it asks how much a given child deviates from the expected range for their age and sex. This allows for individual variation across the ADHD group rather than flattening it into a single average profile.
The team then applied a data-driven clustering algorithm to these individual deviation profiles, allowing the data to reveal whether subgroups of children with ADHD shared similar patterns of brain network atypicality, without using any clinical symptom information to guide the clustering.
The Results:
Three stable, reproducible subtypes emerged from this analysis.
The first subtype was characterized by the most widespread differences from the normative range, particularly in regions connecting the medial prefrontal cortex to the pallidum (a deep brain structure involved in motivation and emotional regulation). Children in this group had the highest levels of both inattention and hyperactivity/impulsivity, and over a four-year follow-up period showed more persistent difficulties with emotional self-regulation than the other groups. They also had a higher rate of mood disorder comorbidity during follow-up, though this difference did not reach statistical significance given the sample size. The brain deviation patterns of this subtype showed correspondence with the spatial distributions of several neurotransmitter systems, including serotonin, dopamine, and acetylcholine, all of which have been previously implicated in ADHD pathophysiology.
The second subtype showed alterations concentrated in the anterior cingulate cortex and pallidum, a circuit involved in action control and response selection. This subtype had a predominantly hyperactive/impulsive profile, and its brain deviation patterns were associated with glutamate and cannabinoid receptor distributions.
The third subtype showed more focal differences in the superior frontal gyrus, a region involved in sustained attention. This subtype had a predominantly inattentive profile, with brain patterns linked to a specific serotonin receptor subtype.
A particularly important observation was that these brain-derived groupings aligned with clinically meaningful symptom differences, even though no symptom information was used in the clustering process. The fact that an analysis of brain structure alone arrived at groupings that correspond to recognizable clinical patterns is meaningful evidence that these subtypes reflect genuine neurobiological differences rather than statistical noise.
Replication in an Independent Sample
Scientific findings are only as trustworthy as their ability to replicate. The research team tested this clustering model in an entirely independent cohort of 554 children with ADHD from the Healthy Brain Network, a large, publicly available dataset collected under different conditions. The three subtypes were successfully identified in this new sample, with strong correlations between the brain deviation patterns observed in the original and validation cohorts. Differences in hyperactivity/impulsivity across subtypes were consistent with the discovery cohort, providing meaningful external validation of the approach.
What This Does and Doesn't Mean
It is important to be clear about what these findings do and do not imply. This study does not establish that these three subtypes are categorically distinct biological entities with sharp boundaries. They probably represent distinguishable regions along an underlying continuum of neurobiological variation. The neurochemical associations reported are exploratory and spatial in nature; they describe correspondences between brain deviation maps and neurotransmitter receptor density maps derived from separate imaging studies, and do not directly establish that any particular neurotransmitter system is altered in each subtype, nor do they currently inform treatment decisions.
The samples were not entirely medication-naive, and the strict comorbidity exclusion criteria may limit how well these findings generalize to typical clinical populations where comorbidities are the rule rather than the exception. All data came from research sites in the United States and China, and broader generalizability remains to be established.
What the study does demonstrate is that structured neurobiological heterogeneity exists within the ADHD diagnosis, that it can be reliably detected using brain imaging and data-driven methods, and that it aligns with meaningful clinical differences. The subtype defined by the most extensive brain network differences and the most severe, persistent clinical profile may be of particular importance, representing a group that could benefit most from early identification and targeted support.
The longer-term goal of this line of research is to move toward a more biologically grounded understanding of ADHD that complements existing diagnostic approaches and that may ultimately help guide more individualized treatment decisions. That goal, for now, remains a research ambition rather than a clinical reality, but this study takes a meaningful step in that direction.
Managing high blood pressure requires more than just getting a prescription; it means taking medication consistently, day after day, often for years. For people with ADHD, that kind of routine can be genuinely difficult. In our new study, published in BMC Medicine, we set out to understand just how much ADHD affects whether people stick with their blood pressure medication, and whether ADHD treatment itself might make a difference.
Why This Question Matters
Hypertension affects nearly a third of adults worldwide and is one of the leading drivers of heart disease and stroke. At the same time, ADHD, long thought of as a childhood disorder, affects around 2.5% of adults and is increasingly recognized as a risk factor for cardiovascular problems, including high blood pressure. Yet no large-scale study had ever examined whether having ADHD affects how well people follow through with their blood pressure treatment. We wanted to fill that gap.
What We Did
We analyzed health records from over 12 million adults across seven countries, Australia, Denmark, the Netherlands, Norway, Sweden, the UK, and the US, who had started antihypertensive (blood pressure-lowering) medication between 2010 and 2020. About 320,000 of them had ADHD. We tracked two things: whether they stopped their blood pressure medication entirely within five years, and whether they were taking it consistently enough (covering at least 80% of days) over one, two, and five years of follow-up.
What We Found
Across nearly all countries, adults with ADHD were more likely to stop their blood pressure medication and less likely to take it consistently. Overall, those with ADHD had about a 14% higher rate of discontinuing treatment within five years, and were 45% more likely to have poor adherence in the first year, a gap that widened to 64% by the five-year mark. These patterns were most pronounced in middle-aged and older adults.
Interestingly, young adults with ADHD were actually slightly less likely to discontinue treatment than their peers without ADHD, a finding we think may reflect the fact that younger people with ADHD are often more actively engaged with healthcare systems, especially given the cardiovascular monitoring that comes with ADHD medication use.
Perhaps the most encouraging finding was this: among people with ADHD who were also taking ADHD medication, adherence to blood pressure treatment was substantially better. Those on ADHD medication were about 38% less likely to have poor adherence at one year, and nearly 50% less likely at five years. While we can't establish causation from this type of study, one plausible explanation is that treating ADHD, reducing inattention and impulsivity, makes it easier to maintain the routines that consistent medication use requires. It's also possible that people on ADHD medication simply have more regular contact with healthcare providers, which keeps other health problems better monitored and managed.
What This Means in Practice
The core ADHD symptoms of inattention and poor organization are precisely the traits that make long-term medication adherence difficult. Add in the complexity of managing multiple disorders and medications, and it's easy to see why people with ADHD face extra challenges. Our findings suggest that clinicians treating adults with ADHD for cardiovascular disorders should be aware of these challenges and consider tailored support strategies, things like regular follow-up appointments, patient education, and tools that help with routine and organization.
There's also a broader message here about the potential ripple effects of treating ADHD well. Supporting someone in managing their ADHD may not just improve their attention and daily functioning; it may also help them take better care of their physical health, including disorders as serious as hypertension.
Future research should explore which specific support strategies are most effective, and whether these findings hold in lower- and middle-income countries where the data don't yet exist.
If you or someone you know has ADHD, you may be familiar with the challenge of staying on medication. Stimulants like methylphenidate (Ritalin) are the most common and effective treatment for ADHD, but a surprisingly large number of people stop taking them within the first year. In our new study, published in Translational Psychiatry, we sought to determine whether a person's genetic makeup plays a role in the development of the disorder.
What We Did
We analyzed data from over 18,000 people with ADHD in Denmark, all of whom had started stimulant medication. We tracked whether they stopped treatment within the first year, defined as going more than six months without filling a prescription. Nearly 4 in 10 (39%) had discontinued by that point. We then looked at their genetic data to see whether DNA differences could help explain who was more likely to stop.
What We Found
The short answer is: genetics does play a role, but it's modest. No single gene had a dramatic effect. Instead, we found that a collection of small genetic influences—distributed across the genome—contributed to the likelihood of stopping treatment early.
One of the most consistent findings was that people with a higher genetic predisposition for psychiatric disorders like schizophrenia, depression, or general mental health difficulties were more likely to discontinue their medication. This was true across all age groups. Interestingly, having a higher genetic risk for ADHD itself was not associated with stopping treatment, suggesting that the genetics of having ADHD and the genetics of staying on medication are quite different things.
We also found that the genetic picture looks different depending on age. In children under 16, body weight genetics (BMI) played a surprising role, children with a genetic tendency toward higher weight were actually less likely to stop, possibly because stimulant-related appetite suppression is less of a problem for them. In older adolescents and adults, higher genetic potential for educational attainment and IQ was linked to staying on treatment, possibly reflecting better access to information and healthcare support.
On the rare variant side, we found a tentative signal that people who stopped treatment had fewer disruptive variants in genes involved in dopamine, the brain chemical that stimulants work on. This might mean that those who continue on medication genuinely have more disruption in their dopamine system and benefit more from stimulant treatment.
What This Means
Our findings suggest that stopping ADHD medication early isn't simply a matter of willpower or forgetting to take a pill. Biology matters. A person's broader genetic vulnerabilities, particularly for other psychiatric disorders, may make it harder to stay on treatment, perhaps because of side effects, poor response, or the complexity of managing multiple mental health challenges at once.
We're still far from being able to use genetics to predict who will stop their medication, the effects we found are real but small, and much of the variation in treatment persistence remains unexplained. But this work is a step toward understanding the biological foundations of treatment challenges in ADHD, and hopefully toward more personalized approaches to care in the future.
Larger studies and research that can distinguish why people stop (side effects versus poor response versus practical barriers), will be the next steps.
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