Thousands of genes are expressed differently in the brains of men and women, researchers have discovered.
The findings could help explain differences in neurodevelopmental, psychiatric, and neurodegenerative disorders between the sexes.
While men are more likely to experience schizophrenia, attention deficit hyperactivity disorder, and Parkinson’s disease, women are more prone to mood disorders and Alzheimer’s disease.
The U.S. study, inScience, is the first systemic single-cell survey of sex differences in gene expression across multiple regions of the human brain.
“Together, these findings provide a comprehensive map of molecular sex differences in the human brain and offer initial insight into their underlying mechanisms and potential functional consequences,” Alex DeCasien, PhD, from the National Institute of Mental Health in Bethesda, Maryland, told Inside Precision Medicine.
DeCasien and co-workers conducted a high-resolution analysis of gene expression in tissue samples from the brains of 15 men and 15 women using single-nucleus RNA sequencing.
They then used data from earlier large neuroimaging studies to select six cortical regions to sample, four of which showed sex-related differences in grey matter volume and two in which no such differences were found.
The team found subtle but widespread differences in gene activity between men and women. Biological sex explained very little of the variance in gene expression across the brain, at less than 1%, but differences were widespread—with more than 3000 genes showing different expression according to sex in at least one cortical region.
The greatest sex-related differences in gene expression were on the sex chromosomes. However, most of the genes showing sex-related variations in expression were autosomal—carried on one of the 22 numbered non-sex chromosomes.
The predominant driver for sex-biased expression of genes on these autosomal chromosomes were sex steroid hormones such as estrogen and testosterone.
Surprisingly, more than half the X chromosome genes in women were expressed in both alleles for at least one cell type. This indicated that many had escaped X chromosome inactivation—a female phenomenon in which one of the two X chromosomes is switched off early in development to stop women producing double the number of X-linked gene products to men.
“That finding has implications for understanding sex-biased disease susceptibility because several genes implicated in neurodevelopmental disorders reside on the X chromosome,” commented Jessica Tollkuhn, PhD, from Cold Spring Harbor Laboratory, and S Marc Breedlove, from Michigan State University, in an accompanying Perspective article.
They noted that autosomal genes showing sex-biased expression were substantially enriched for extracellular matrix components, hormone signaling pathways, and metabolic processes. “Genes with greater expression in women were enriched for mitochondrial and synaptic functions, whereas male-biased genes were associated with metabolic and structural pathways,” the editorialists added.
“By pinpointing these sexually differentiated processes, the data provide a treasure trove for the discovery of biomarkers of and/or therapeutic targets for differential disease risk in men and women.”
DeCasien and team added: “These findings raise the possibility that sex differences in gene expression modulate the magnitude of genetic effects at risk loci, contributing to differences in disease vulnerability and to reduced portability of polygenic risk prediction across sexes.”
You’ve probably heard some version of this idea before: that many of us have an “inner Neanderthal.” That is to say, around 45,000 years ago, when Homo sapiens first arrived in Europe, they met members of a cousin species—the broad-browed, heavier-set Neanderthals—and, well, one thing led to another, which is why some people now carry a small amount of Neanderthal DNA.
This DNA is arguably the 21st century’s most celebrated discovery in human evolution. It has been connected to all kinds of traits and health conditions, and it helped win the Swedish geneticist Svante Pääbo a Nobel Prize.
But in 2024, a pair of French population geneticists called into question the foundation of the popular and pervasive theory.
Lounès Chikhi and Rémi Tournebize, then colleagues at the Université de Toulouse, proposed an alternative explanation for the very same genomic patterns. The problem, they said, was that the original evidence for the inner Neanderthal was based on a statistical assumption: that humans, Neanderthals, and their ancestors all mated randomly in huge, continent-size populations. That meant a person in South Africa was just as likely to reproduce with a person in West Africa or East Africa as with someone from their own community.
Archaeological, genetic, and fossil evidence all shows, though, that Homo sapiens evolved in Africa in smaller groups, cut off from one another by deserts, mountains, and cultural divides. People sometimes crossed those barriers, but more often they partnered up within them.
In the terminology of the field, this dynamic is called population structure. Because of structure, genes do not spread evenly through a population but can concentrate in some places and be totally absent from others. The human gene pool is not so much an Olympic-size swimming pool as a complex network of tidal pools whose connectivity ebbs and flows over time.
This dynamic greatly complicates the math at the heart of evolutionary biology, which long relied on assumptions like randomly mating populations to extract general principles from limited data. If you take structure into account, Chikhi told me recently, then there are other ways to explain the DNA that some living people share with Neanderthals—ways that don’t require any interspecies sex at all.
“I believe most species are spatially organized and structured in different, complex ways,” says Chikhi, who has researched population structure for more than two decades and has also studied lemurs, orangutans, and island birds. “It’s a general failure of our field that we do not compare our results in a clear way with alternative scenarios.” (Pääbo did not respond to multiple requests for comment.)
The inner Neanderthal became a story we could tell ourselves about our flaws and genetic destiny: Don’t blame me; blame the prognathic caveman hiding in my cells.
Chikhi and Tournebize’s argument is about population structure, yes, but at heart, it is actually one about methods—how modern evolutionary science deploys computer models and statistical techniques to make sense of mountains upon mountains of genetic data.
They’re not the only scientists who are worried. “People think we really understand how genomes evolve and can write sophisticated algorithms for saying what happened,” says William Amos, a University of Cambridge population geneticist who has been critical of the “inner Neanderthal” theory. But, he adds, those models are “based on simple assumptions that are often wrong.”
And if they’re wrong, what’s at stake is far more than a single evolutionary mystery.
A captivating story of interspecies passion
Back in 2010, Pääbo’s lab pulled off something of a miracle. The researchers were able to extract DNA from nuclei in the cells of 40,000-year-old Neanderthal bones. DNA breaks down quickly after death, but the group got enough of it from three different individuals to produce a draft sequence of the entire Neanderthal genome, with 4 billion base pairs.
As part of their study, they performed a statistical test comparing their Neanderthal genome with the genomes of five present-day people from different parts of the world. That’s how they discovered that modern humans of non-African ancestry had a small amount of DNA in common with Neanderthals, a species that diverged from the Homosapiens line more than 400,000 years ago, that they did not share with either modern humans of African ancestry or our closest living relative, the chimpanzee.
This model of a Neanderthal man was exhibited in the “Prehistory Gallery” at London’s Wellcome Historical Medical Museum in the 1930s.
WELLCOME COLLECTION
Pääbo’s team interpreted this as evidence of sexual reproduction between ancient Homo sapiens and the Neanderthals they encountered after they expanded out of Africa. “Neanderthals are not totally extinct,” Pääbo said to the BBC in 2010. “In some of us, they live on a little bit.”
The discovery was monumental on its own—but even more so because it reversed a previous consensus. More than a decade earlier, in 1997, Pääbo had sequenced a much smaller amount of Neanderthal DNA, in that case from a cell structure called a mitochondrion. It was different enough from Homo sapiens mitochondrial DNA for his team to cautiously conclude there had been “little or no interbreeding” between the two species.
After 2010, though, the idea of hybridization, also called admixture, effectively became canon. Top journals like Science and Naturepublished study after study on the inner Neanderthal. Some scientists have argued that Homo sapiens would never have adapted to colder habitats in Europe and Asia without an infusion of Neanderthal DNA. Other research teams used Pääbo’s techniques to find genetic traces of interbreeding with an extinct group of hominins in Asia, called the Denisovans, and a mysterious “ghost lineage” in Africa. Biologists used similar tests to find evidence of interbreeding between chimpanzees and bonobos, polar and brown bears, and all kinds of other animals.
The inner-Neanderthal hypothesis also took a turn for the personal. Various studies linked Neanderthal DNA to a head-spinning range of conditions: alcoholism, asthma, autism, ADHD, depression, diabetes, heart disease, skin cancer, and severe covid-19. Some researchers suggested that Neanderthal DNA had an impact on hair and skin color, while others assigned individuals a “NeanderScore” that was correlated with skull shape and prevalence of schizophrenia markers. Commercial genetic testing companies like 23andMe started offering customers Neanderthal ancestry reports.
The inner Neanderthal became a story we could tell ourselves about our flaws and genetic destiny: Don’t blame me; blame the prognathic caveman hiding in my cells. Or as Latif Nasser, a host of the popular-science program Radiolab, put it when he was hospitalized with Crohn’s disease, another Neanderthal-associated condition: “I just keep imagining these tiny Neanderthals … just, like, stabbing me and drawing these little droplets of blood out of me.”
“These things become meaningful to people,” Chikhi says. “What we say will be important to how people view themselves.”
The pitfalls of simplistic solutions
When population geneticists built the theoretical framework for evolutionary biology in the early 20th century, genes were only abstract units of heredity inferred from experiments with peas and fruit flies. Population genetics developed theory far more quickly than it accumulated data. As a result, many data-driven scientists dismissed the study of evolution as a form of storytelling based on unexamined assumptions and preconceived ideas.
By the ’90s, though, genes were no longer abstractions but sequenced segments of DNA. Genomic sequencing grounded evolutionary studies in the kind of hard data that a chemist or physicist could respect.
Yet biologists could not simply read evolutionary history from genomes as though they were books. They were trying to determine which of a nearly infinite number of plausible histories was the most likely to have created the patterns they observed in a small sample of genomes. For that, they needed simplified, algorithmic models of evolution. The study of evolution shifted from storytelling to statistics, and from biology to computer science.
That suited Chikhi, who as a child was drawn to the predictable laws and numerical precision of math and science. He entered the field in the mid-’90s just as the first big studies of human DNA were settling old debates about human origins. DNA showed that Africa harbored far more genetic diversity than the entire rest of the planet. The new evidence supported the idea that modern humans evolved for hundreds of thousands of years in Africa and expanded to the other continents only in the last 100,000 years. For Chikhi, whose parents were Algerian immigrants, this discovery was a powerful challenge to the way some archaeologists and biologists talked about race. DNA could be used to deconstruct rather than encourage the pernicious idea that human races had deep-seated evolutionary differences based on their places of origin.
At the same time, though, he was wary of the tendency to treat DNA as the final verdict on open questions in evolution. Chikhi had been surprised when, back in 1997, Pääbo and his team used that small amount of mitochondrial DNA to rule out hybridization between Homo sapiens and Neanderthals. He didn’t think that the absence of Neanderthal DNA there necessarily meant it wouldn’t be found elsewhere in the Homo sapiens genome.
Chikhi’s own research in the aughts opened his eyes to the gaps between historical reality and models of evolution. For one, despite the assumption of random mating, none of the animals Chikhi studied actually mated randomly. Orangutans lived in highly fragmented habitats, which restricted their pool of potential mates, and female birds were often extremely picky about their male partners.
These factors could confound an evolutionary biologist’s traditional statistical tool kit. Scientists were starting to apply a mathematical technique to estimate historical population sizes for a species from the genome of just a single individual. This method showed sharp population declines in the histories of many different species. Chikhi realized, though, that the apparent declines could be an artifact of treating a structured population as one that evolved with random mating; in that case, the technique could indicate a bottleneck even if all the subgroups were actually growing in size. “This is completely counterintuitive,” he says.
That’s at least partly why, when Pääbo’s 2010 Neanderthal genome came out, Chikhi was impressed with the sheer technical accomplishment but also leery of the findings about hybridization. “It was the type of thing we conclude too quickly based on genetic data,” he says. Pääbo’s work mentioned population structure as a possible alternative explanation—but didn’t follow up.
Just a couple of years later, a pair of independent scientists named Anders Eriksson and Andrea Manica picked up the idea, building a model with simple population structure that explicitly excluded admixture. They simulated human evolution starting from 500,000 years ago and found that their model produced the same genomic patterns Pääbo’s group had interpreted as evidence of hybridization.
“Working with structured models is really out of the comfort zone of a lot of population geneticists,” says Eriksson, now a professor at the University of Tartu in Estonia.
Their research impressed Chikhi. “At the time, I thought people would focus on population structure in the evolution of humans,” he says. Instead, he watched as the inner-Neanderthal hypothesis took on a life of its own. Scientists produced new methods to quantify hybridization but rarely examined whether population structure would yield the same results. To Chikhi, this wasn’t science; it was storytelling, like some of the old narratives about the evolution of racial differences.
Chikhi and Tournebize decided to take a crack at the problem themselves. “I’ve always been very skeptical about science, and population genetics in particular,” says Tournebize, now a researcher at the French National Research Institute for Sustainable Development. “We make a lot of assumptions, and the models we use are very simplistic.” As detailed in a 2024 paper published in Nature Ecology & Evolution, they built a model of human evolution that replaced randomly mating continent-wide populations with many smaller populations linked by occasional migration. Then they let it run—a million times.
At the end of the simulation, they kept the 20 scenarios that produced genomes most similar to the ones in a sample of actual Homosapiens and Neanderthals. Many of these scenarios produced long segments of DNA like the ones their peers argued could only have been inherited from Neanderthals. They showed that several statistics, which other scientists had proposed as measurements of Neanderthal DNA, couldn’t actually distinguish between hybridization and population structure. What’s more, they showed that many of the models that supported hybridization failed to accurately predict other known features of human evolution.
“A model will say there was admixture but then predict diversity that is totally incompatible with what we actually know of human diversity,” Chikhi says. “Nobody seems to care.”
So how did Neanderthal DNA wind up in living people if not via interspecies passion? Chikhi and Tournebize think it’s more likely that it was inherited by both Neanderthals and some sapiens groups in Africa from a common ancestor living at least half a million years ago. If the sapiens groups carrying those genetic variants included the people who migrated out of Africa, then the two human species would have already had the DNA in common when they came into contact in Europe and Asia—no sex required.
“The interpretation of genetic data is not straightforward,” Chikhi says. “We always have to make assumptions. Nobody takes data and magically comes up with a solution.”
Embracing the uncertainty
Most of the half-dozen population geneticists I spoke with praised Chikhi and Tournebize’s ingenuity and appreciated the spirit of their critique. “Their paper forces us to think more critically about the model we use for inference and consider alternatives,” says Aaron Ragsdale, a population geneticist at the University of Wisconsin–Madison. His own work likewise suggests that the earliest Homo sapiens populations in Africa were probably structured—and that this is the likely reason for genomic patterns that other research groups had attributed to hybridization with a mysterious “ghost lineage” of hominins in Africa.
Yet most researchers still believe that modern humans and Neanderthals did probably have children with each other tens of thousands of years ago. Several pointed to the fact that fossil DNA of Homo sapiens who died thousands of years ago had longer chunks of apparent Neanderthal DNA than living people, which is exactly what you would expect if they had a more recent Neanderthal ancestor. (To address this possibility, Chikhi and Tournebize included DNA from 10 ancient humans in their study and found that most of them fit the structured model.) And while the Harvard population geneticist David Reich, who helped design the statistical test from Pääbo’s 2010 study, declined an interview, he did say he thought Chikhi and Tournebize’s model was “weak” and “very contrived,” adding that “there are multiple lines of evidence for Neanderthal admixture into modern humans that make the evidence for this overwhelming.” (Two other authors of that study, Richard Green and Nick Patterson, did not respond to requests for comment.)
Nevertheless, most scientists these days welcome the development of structured, or “spatially explicit,” models that account for the fact that any given member of a population is usually more closely related to individuals living nearby than to those living far away.
Loosening our attachment to certain narratives of evolution can create space for wonder at the sheer complexity of life’s history.
Other scientists also say that random mating isn’t the only assumption in population genetics that merits scrutiny. Models rarely factor in natural selection, which can also create genetic patterns that look like hybridization. Another common assumption is that everyone’s DNA mutates at the same, constant rate. “All the theory says the mutation rate is fixed,” says Amos, the Cambridge population geneticist. But he thinks that rate would have slowed drastically in the group of Homo sapiens that expanded to Europe around 45,000 years ago. This, too, could have created genomic patterns that other scientists interpret as evidence of interbreeding with Neanderthals.
Commercial genetic testing companies like 23andMe started offering customers Neanderthal ancestry reports.
COURTESY OF 23ANDME
The point here isn’t that a complex model of evolution with many moving pieces is necessarily better than a simple one. Scientists need to reduce complexity in order to see the underlying processes more clearly. But simple models require assumptions, and scientists need to reevaluate those assumptions in light of what they learn. “As you get more data, you can justify more complex models of the world,” says Mark Thomas, a population geneticist at University College London, who wrote a history of random mating in population genetics that highlighted how the field was starting to see it as “a limiting assumption as opposed to a simplifying one.”
It can feel discouraging to couch conversations about the past in confusing terms like “population structure” and “mutation rates.” It seems almost antithetical to the spirit of science to talk more about uncertainty at the same time we are developing powerful technologies and enormous data sets for analyzing evolution. These tools often yield novel answers, but they can also limit the questions we ask. The French archaeologist Ludovic Slimak, for example, has complained that the idea of the inner Neanderthal has domesticated our image of Neanderthals and made it difficult to imagine their humanity as distinct from our own. Investigating Neanderthal DNA is sexier to many young researchers than searching for archaeological and fossil evidence of how Neanderthals actually lived.
Loosening our attachment to certain narratives of evolution can create space for wonder at the sheer complexity of life’s history. Ultimately, that’s what Chikhi and Tournebize hope to do. After all, they don’t believe the question of population structure versus hybridization is either-or. It’s possible, and even likely, that both played a role in human evolution. “Our structured model does not necessarily mean that no admixture ever took place,” Chikhi and Tournebize wrote in their study. “What our results suggest is that, if admixture ever occurred, it is currently hard to identify using existing methods.”
Future methods might disentangle the different factors, but it’s just as important, Chikhi says, for scientists to be up-front about their assumptions and test alternatives. “There’s still so much uncertainty on so many aspects of the demographic history of Neanderthals and Homo sapiens,” he notes.
Keep that in mind the next time you read about your inner Neanderthal. The association between this DNA and some diseases may be real, of course—but would journals publish these studies without the additional claim that the DNA is from Neanderthals? Any good storyteller knows that sex sells, even in science.
Ben Crair is a science and travel writer based in Berlin.
The results of a study headed by researchers at Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, indicate that the gut microbiome and epigenetics are intertwined, and that both contribute to neurodevelopment.
The researchers showed that epigenetic changes present at birth can impact how an infant’s gut microbiome develops during their first year. They also identified specific epigenetic changes and gut microbes that were associated with signs of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) when the children were three years old.
“Certain bacteria seem to offer protection, which is exciting because it suggests there could be ways to support a child’s development through diet or probiotics in the future,” said research lead and gastroenterologist Francis Ka Leung Chan, MD. Chan is co-senior author of the team’s published paper in Cell Press Blue, titled “Epigenome-microbiome interplay in early life associates with infants’ neurodevelopmental outcomes,” in which they stated, “We showed that epigenetic alterations at birth were associated with early-life microbiome development and that they determine the risks of neurodevelopmental consequences in children.”
The first years of life are critical for brain development and immune system maturation. Though previous studies have shown that both early epigenetic changes and gut microbiome development can impact health in later life, little is known about how these two systems interact. “Recent data suggest that epigenetic programming of gene expression profiles is sensitive to the early-life environment and can impact health outcomes in children,” the authors wrote. “One environmental cue known to trigger host epigenetic modifications is the genes of bacteria, fungi, and viruses inside the human body, collectively known as the microbiome.”
Co-senior author and public health researcher Hein Min Tun, PhD, of The Chinese University of Hong Kong, commented, “We wanted to see how the epigenome and microbiome interact in early life and if their interaction could influence a child’s risk of developing neurodevelopmental conditions like ASD and ADHD.” The authors added, “New understanding of host-microbe-epigenome interactions and mechanisms of epigenetic changes in early life can be leveraged for the prevention, early detection, and novel interventions of common childhood diseases.”
For their study the researchers characterized DNA methylation patterns from the umbilical cord blood of 571 infants. They paired this information with gut microbiome data collected from 969 infants at two, six, and 12 months of age, and from their parents during the third trimester of pregnancy. When the children reached 36 months of age, the researchers used a behavioral questionnaire to assess their neurodevelopment and investigate links between the microbiome, epigenome, and early signs of ASD and ADHD.
“This, to our knowledge, represents the first longitudinal study with multiple sample types to depict the intimate interplay between perinatal exposures, epigenetic hallmarks, and gut microbiome development and neurodevelopmental outcomes within the first three years of life,” the authors stated.
They found that an infant’s epigenome at birth was associated with birth mode, length of gestation, having older siblings, and maternal allergies, but it was not affected by their parents’ gut microbiomes. Microbiome development, on the other hand, was associated with birth mode, antibiotics, having older siblings, and breastfeeding. Infants who were born by Caesarean section (CS) showed different patterns of DNA methylation for several genes involved in immune responses and brain development. “Some of the changes in methylations of immune- and nervous-system-related genes, associated with CS delivery, are linked to neurodevelopmental outcomes,” they noted.
Their reported findings, the team suggested, “… resonate with studies linking CS to increased risks of immune-mediated and neurodevelopmental disorders, providing mechanistic plausibility through epigenomic and microbial dysbiosis.” The team also showed that an infant’s epigenome at birth impacted how their microbiome developed during their first year. Specifically, infants developed less diverse gut microbiomes at 12 months of age when they showed higher rates of DNA methylation in immune genes involved in recognizing pathogens. “We found that methylation rates in the major histocompatibility complex (MHC) region of infants at birth were linked to differences in the diversity of the infant gut microbiome at 12 months,” they commented.
The behavioral survey revealed that signs of ASD and ADHD in three-year-olds were associated with specific epigenetic patterns and the presence of certain gut microbes. “Importantly, we reported that epigenetic modifications were associated with an increased susceptibility to neurodevelopmental conditions in children, and these effects were in part mediated by microbial colonization.”
However, other microbial species seemed to mitigate these effects: infants with epigenetic patterns associated with ASD or ADHD were less likely to show signs of the disorders if they acquired Lachnospira pectinoschiza and Parabacteroides distasonis, respectively, during their first year. “We discovered a kind of conversation happening: a baby’s epigenetic setting at birth can influence their risk for neurodevelopmental disorders, but the presence of certain ‘good’ bacteria in their gut can step in and modify the risk,” Tun reported. “The foundations for brain health are laid very early, even before birth. However, we don’t want people to think this means a child’s developmental path is fixed at birth. These are complex conditions with many causes, and we’ve only uncovered a small piece of a very large puzzle.”
The researchers are continuing to follow the children who participated in the study to see how these early-life factors relate to their health as they grow. They note that laboratory experiments are needed to confirm the associations between gut microbes and neurodevelopment. In their discussion, the team wrote, “In conclusion, our findings revealed dual alterations to the neonatal epigenome and gut microbiome by perinatal factors and highlight the role of the ‘holo-epigenome’—the integrated host epigenome and microbiome—as a key mediator of neuro-immune outcomes. Interventions targeting microbial restoration or epigenetic modulation during critical developmental windows may mitigate risks of neurodevelopmental disorders.”
First author and gastroenterologist Siew Chien Ng, MD, PhD, added, “The ultimate goal is to develop safe, non-intrusive early interventions such as specific probiotics or live biotherapeutics, that could help nurture a healthy gut microbiome and potentially reduce the risk of neurodevelopmental challenges.”
ObjectiveThis meta-analysis evaluated the efficacy and safety of transcranial direct current stimulation (tDCS) for treating Attention-Deficit/Hyperactivity Disorder (ADHD).MethodsFollowing PRISMA guidelines, we analyzed 28 randomized controlled trials (RCTs) involving 1,864 participants. Outcomes encompassed core ADHD symptoms, hot and cold executive functions (EFs)—including inhibitory control, working memory, and cognitive flexibility—as well as safety profiles based on adverse events. A multilevel meta-analysis was performed using a random-effects model. Subgroup analyses and meta-regressions were conducted to explore potential moderating factors.ResultsCompared to sham stimulation, tDCS did not significantly improve core ADHD symptoms (standardized mean difference (SMD) = –0.29, 95% CI [–0.59, 0.01], p= 0.05). Similarly, no significant overall effects were observed for cold EFs: inhibitory control (Hedges’ g(g)= –0.11, 95% CI [–0.26, 0.05], p=0.19), working memory (g= 0.13, 95% CI [–0.06, 0.32], p= 0.26), or cognitive flexibility (SMD = –0.42, 95% CI [–1.13, 0.29], p= 0.24). The effect on hot EFs was also non-significant (g = 0.27, 95% CI [–0.14, 0.70], p = 0.19). Exploratory analyses indicated that anode placement at Fp2 was associated with improvement in both inhibitory control (g= –0.52, 95% CI [–0.93, –0.11], p=0.01) and working memory (g = 0.72, 95% CI [0.22, 1.22], p = 0.004), although the overall test for interaction was not significant for inhibitory control (p= 0.19). The most common adverse reactions were mild and transient local skin symptoms, such as itching and redness (RR = 1.42, p=0.04).ConclusiontDCS was well-tolerated but did not demonstrate significant overall efficacy for core ADHD symptoms or executive functions. Anodal stimulation at Fp2 showed potential selective benefits warranting further investigation. tDCS is not currently recommended as a standalone treatment for ADHD. Future research should optimize stimulation protocols and explore combined interventions with behavioral or cognitive therapies.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42024612055.
Background: Digital mental health technologies (DMHTs) are playing an increasing role in mental health services. The quality of evidence for DMHTs is variable, and there are concerns that evidence is not sufficient to support decision-making. Objective: This study used a cross-sectional analysis of evidence supporting DMHTs included in National Institute for Health and Care Excellence (NICE) evaluations to examine the strength of evidence available for decision-making. Methods: We identified all NICE evaluations relating to DMHTs by reviewing details of published NICE evaluations on the NICE website. From each of these evaluations, we identified included DMHTs and reviewed committee documentation to identify studies that provided supporting evidence for each of these technologies. We extracted information on a series of items relating to study quality and summarized the characteristics of evidence both at the level of individual studies and across the package of evidence from multiple studies supporting DMHTs. We also identified key evidence gaps in available evidence. Results: We included nine NICE evaluations relating to anxiety, depression, psychosis, insomnia, attention deficit hyperactivity disorder (ADHD), and tic disorders. These evaluations included 30 DMHTs and referenced 78 supporting studies. We identified common evidence gaps relating to effectiveness compared to relevant comparators, use of appropriate outcomes, including health-related quality of life, cost of delivery, and impact on resource use, and reporting of adverse events. Conclusions: Our study highlights that some DMHTs have been supported by high-quality studies and that evidence to support DMHTs is likely to be developed across a series of studies. However, there are often key evidence gaps that need to be addressed to provide a stronger case for adoption. Developers should ensure that they consider these gaps while planning evidence generation, and where possible, address them earlier in the product lifecycle.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/825f13db8cbad54213afa5c433d7adde" />
IntroductionAttention-deficit/hyperactivity disorder (ADHD) in adults often co-occurs with eating disorders (EDs), potentially through shared difficulties in emotional regulation, and executive functions. This study explored the associations between cognitive flexibility as a component of executive functions, core adult ADHD symptom dimensions and emotional eating-related eating behaviorsin adults with ADHD and healthy controls, within the framework of executive functions.MethodsThis case-control study included 76 adults with ADHD and 69 healthy controls. Participants completed the Self-Report Wender-Reimherr Adult Attention Deficit Disorder Scale (SR-WRAADDS), Emotional Eating Questionnaire (EEQ), Hospital Anxiety and Depression Scale, Cognitive Control and Flexibility Questionnaire (CCFQ), and Berg’s Card Sorting Test. Group differences were tested with t-tests, correlations with Spearman’s ρ, and hierarchical regression (Approval No: I11-798-23).ResultsThe ADHD group had significantly higher EEQ scores (t = 5.39, p =0.001). The ADHD group also showed lower CCFQ total score (t (125) = –5.52, p <0.001). EEQ scores were positively correlated with SR-WRAADDS Attention Deficit (ρ =0.331, p =0.003), and CCFQ Cognitive Control over Emotion (ρ = −0.256, p =0.02). Regression analysis identified attention deficit as the only significant predictor of the EEQ total scorein the ADHD group.DiscussionOur findings suggest that impairments in executive functioning—including cognitive flexibility, attentional regulation, and emotion-related control mechanisms—may play a more central role in the relationship between ADHD and emotional eating-related eating behaviors. Longitudinal studies are warrented to further elucidate these mechanisms.
Exploring neuro-privacy and trust in AI – our proposal for ARIA’s Trust Everything, Everywhere programme.
We’re proud to share that Relatix Health has applied for funding from the UK’s Advanced Research and Invention Agency (ARIA) under its Trust Everything, Everywhere programme. This initiative explores how trust can be built across the digital and physical worlds, and we believe that conversation must include people whose minds work differently.
Our proposal focuses on one of the most pressing and least understood challenges of the digital age: how people with neurodevelopmental and neurodiverse conditions, including autism, ADHD, schizophrenia, borderline traits, and psychopathy, experience, interact with, and build trust in AI systems. In a world increasingly mediated by algorithms, the ways these systems interpret, respond to, and store our most personal thoughts and data matter profoundly.
Throughout history, individuals living with stigmatized neurocognitive conditions have been marginalized or misrepresented by institutions, by society, and now, potentially, by AI. Some may over-trust technology that feels neutral or supportive; others may under-trust it because of past harm or bias. We want to ensure that digital systems meet people where they are, building trust rather than eroding it, while protecting privacy and supporting quality of life, health, and wellbeing.
Through this work, Relatix Health aims to lead the way in ethical and inclusive neuro-AI design: protecting privacy, reducing stigma, and helping define standards for responsible data handling in the era of AI. Our goal is to make sure that the next generation of AI-driven tools, from chatbots to diagnostics, truly serves everyone, regardless of how their brain is wired.
We know how often things have already gone wrong, from chatbots unintentionally encouraging depressive or paranoid thoughts, to credit and gambling platforms optimizing for addiction or impulsive behaviour. These systems were not built with sufficient safeguards for people with neurodevelopmental conditions, who may react differently to AI-optimized interactions. Many respond by disengaging digitally, and may feel that an AI-driven world is a minefield because it was not built for them.
Join us in shaping a radically different future where cognitive diversity and digital trust can coexist, and AI tools are built to truly support and empower. To learn more about our mission or to collaborate, contact our team.
