Scientists have taken a giant leap forward with the development of tiny microneedles designed to detect subtle but critical changes in how the liver and kidneys process therapeutic drugs. The experimental technology, under development at the University of California, Los Angeles, aims to overcome longstanding limitations that have hindered wearable microneedle biosensors.

“Wearable microneedle biosensors promise real-time molecular monitoring for precision medicine but are limited by low sensitivity and tissue abrasion,” writes Dr. Jialun Zhu, lead author of a new study published in Science Translational Medicine.

“Overcoming these challenges, we recast electrode functionality not merely as a sensing substrate but as a mechanism for resilient, high signal-to-noise ratio measurements in tissue,” added Zhu, a bioengineer in UCLA’s Samueli School of Engineering.

In plainer English, the multidisciplinary UCLA team was able to get their system to work flawlessly compared with similar devices by other research groups.

Tracking drug clearance in real time

The team has developed a biosensor that in early research already shows promise for real-time in-tissue monitoring of drug pharmacokinetics. These preclinical studies also show that the device is both safe and highly accurate. However, it has not yet been tested in humans.

Still, if the technology seems futuristic, it may be because tiny wearables and implants that measure any number of biological processes have been themes in science fiction for decades. With refinements underway to improve precision medicine, the future has already arrived. Scientists involved in the project ranged from molecular and cellular biologists to biochemists and a team of bioengineers like Zhu.

One goal in precision medicine has been the development of a minimally invasive device that can monitor the clearance of drugs from a patient’s kidneys and liver, providing more accurate dosing guidelines. To address persistent problems that have impeded progress toward reaching that goal, the team engineered what it calls a “resilient nanostructured bioelectrode” using a microscopically thin layer of a precious metal.

“Our microneedle-based resilient nanostructured bioelectrode is fabricated using a bilayer process that strengthens the electrode with a micrometer-thick gold adhesion layer,” Zhu noted in the research paper.

The key reason that an accurate wearable biosensor is needed is explained by the growing number of medications with narrow therapeutic ranges. That means it is possible to provide doses that are either too low or too high. With a wearable such as the one under development, doctors can tell if they have prescribed a precise dose, and how well the drug is being processed and excreted.

Toward precision monitoring in organ dysfunction

In preclinical experiments, the biosensor enabled continuous in-tissue monitoring of drug pharmacokinetics, including changes associated with liver and kidney dysfunction. Scientists found in the animal model research that their experimental technology measured drug kinetics for six days and produced accurate parameters for drug dosing while also monitoring drug clearance from the liver and kidneys.

The system revealed, for example, that one chemotherapy drug, irinotecan, cleared out slowly in mice with liver damage. The technology also traced the kinetics of several antibiotics during various stages of chronic kidney disease.Comparison between conventional blood-based therapeutic drug monitoring and wearable ISF-based therapeutic drug and metabolic function monitoring. Credit: Science Translational Medicine (2026). DOI: 10.1126/scitranslmed.adr5493

An approach by other research groups has involved the use of wearable biosensors that incorporate microneedles, which measure minute molecular changes in drug concentrations. However, current microneedles suffer from issues such as low sensitivity and poor mechanical durability.

In contrast, Zhu and colleagues developed a more resilient, nanostructured microneedle that analyzes the biochemistry of interstitial fluids between cells. Their design incorporates sensors that endow it with a high degree of specificity and features a strong layer of gold that increases the needle surface area and resists corrosion.

Technology holds promise

In an editorial commentary, Molly Ogle, an associate editor at Science Translational Medicine, notes that wearable technology could play an important role in precision medicine. “The study demonstrates preclinical promise for minimally invasive therapeutic drug monitoring and functional assessment of hepatic and renal drug processing,” Ogle wrote.

Zhu and colleagues underscored, meanwhile, that their device not only has marked improvements over similar technology but also could be economically manufactured. They predict that their resilient nanostructured bioelectrode could be mass produced at less than $1.50 per sensor.

“These results establish the resilient nanostructured bioelectrode as a viable microneedle platform for high-fidelity in vivo deployment of electrochemical biosensors, enabling minimally invasive, longitudinal monitoring of low-concentration analytes and real-time assessment of organ function,” Zhu and the UCLA team concluded.

More than 200 mushrooms—primarily those belonging to a genus of gilled mushrooms called Psilocybe—contain the psychoactive compound psilocybin. In the brain of mammals, this chemical can bind to serotonin receptors and influence behavior and emotions, including aggression, appetite, and mood. Its effects on the social behavior of animals, however, remain largely undescribed.

In a new Frontiers in Behavioral Neuroscience study, researchers in Canada have tested whether the effects of psilocybin extend to the social behavior of the amphibious mangrove rivulus fish (Kryptolebias marmoratus).

“We show that an acute, low dose of psilocybin significantly reduces activity and aggressive attack behavior during social interactions in adult mangrove rivulus fish, a species that is naturally highly aggressive,” said first author Dayna Forsyth, a research associate and former MSc student at Acadia University in Nova Scotia.

“These findings provide the first evidence that psilocybin can selectively reduce escalated aggression in a vertebrate model without suppressing social interaction,” added senior author Dr. Suzie Currie, a biologist at The University of British Columbia.

Calm waters

Mangrove rivulus fish are innately aggressive, especially when paired with another individual. Their aggressive behaviors are straightforward and subtle changes can easily be detected. These fish are also self-fertilizing and produce embryos that are genetically identical. Therefore, this model ensures all observed effects are caused by psilocybin treatment rather than genetic differences between fish.

The team used three genetically distinct, laboratory-bred lines. Fish from one line were exposed to psilocybin, fish from a second served as stimulus fish. A third line was used to quantify whole-body concentrations and absorption of psilocybin.

For the first phase of the experiment, the focal fish was added into a tank containing a stimulus fish to measure baseline behavior. The fish were separated by an opaque cover placed over a fiberglass mesh barrier through which the fish could see and smell, but not reach, each other. After a five-minute adjustment period to the shared tank, the opaque barrier was removed and interaction monitored.

Twenty-four hours later, the same focal fish was put in a water tank in which psilocybin was dissolved. After exposure to the substance for 20 minutes, the fish was added into the tank occupied by the same stimulus fish of the day before. After removal of the opaque barrier, interaction was observed again.

Magic mushroom, mellow fish

Observation of behaviors to measure activity (time spent moving) and aggression levels (including swimming bursts) revealed that fish dosed with psilocybin showed decreased levels of activity and performed fewer swimming bursts compared to specimens that hadn’t received psilocybin treatment.

“Swimming bursts are high‑energy attack behaviors that represent an escalation of aggression towards the stimulus fish without making physical contact,” explained Currie. “Other types of aggressive behaviors, like head‑on displays, are more about communication and social assessment and require very little energy.”

“Psilocybin’s calming effect appears to selectively reduce energetically costly, escalated behaviors while lower‑energy social display behaviors remained largely unchanged,” said Forsyth. “This suggests that this compound can selectively dampen escalated social conflict rather than shutting down behavior altogether.”

Psilocybin also influenced activity levels, with dosed fish spending less time moving than control fish when paired with a conspecific.

Diving deeper

In the long run, non-human models in drug-screening experiments like this can provide robust results that can later be translated to humans. In the future, findings like those made here could help inform therapeutic research by clarifying which aspects of social behavior are most sensitive to psilocybin.

The team cautioned, however, that the current study did not test clinical treatments and results from fish cannot be directly extrapolated to humans.

The study also focused on single doses and short periods of exposure, and didn’t examine long-term effects, repeated dosing, or adaptation over time. Future studies are needed to confirm whether the lower level of aggression observed here can be sustained.

“Future studies can build on this work to explore how psilocybin alters neural signaling, which serotonin pathways are involved, and why some aspects of social behavior are affected while others are not,” concluded Currie. “These are questions that are difficult or impossible to answer directly in humans.”

A new meta-analysis of 55 studies involving more than 3 million people has found that 31% of individuals with cannabis use disorder (CUD) also struggle with major depressive disorder (MDD). While a link between these two conditions has been known for some time, this study provides the clearest evidence to date that the relationship goes both ways. CUD was also found to be present in 10% of those with MDD.

The findings are published in the Journal of Psychiatric Research.

An international team of scientists searched major databases to identify relevant studies published in English and Portuguese through to 2024. They used mathematical models to combine results from millions of people, ensuring they accounted for differences in age, gender, and location.

Setting matters

The team discovered that the overlap between MDD and CUD varies significantly depending on the setting. For example, in the community (among the general public or volunteers in the studies), rates of cannabis use disorder among people with depression are relatively low. However, in psychiatric clinics, the connection is much stronger. More than 28% of patients being treated for depression also meet the criteria for CUD.

The meta-analysis also revealed that the two disorders are often linked throughout a person’s life, even if they are not present at the same time. While 20% of those with cannabis use disorder were found to be depressed at the time they participated in their respective study, 35% had struggled with depression at some point during their lives.

The problem of overlapping symptoms

Despite these findings, the researchers note that several limitations may prevent us from getting a clear picture of what is happening. One major challenge is an overlap in diagnosis where symptoms of cannabis withdrawal, such as anxiety, irritability, and sleep disturbances, are very similar to the clinical signs of depression. This makes it difficult for doctors to determine whether someone is suffering from a depressive disorder or the effects of their cannabis use.

Additionally, much of the data comes from North America, so it may not reflect conditions in other countries or cultures.

Future screening

However, due to the high percentages involved, the study authors recommend that health care providers regularly screen for cannabis use in depressed patients. Likewise, they suggest evaluating depression levels in those seeking help for CUD.

“Differences between psychiatric and community samples—especially the markedly higher current CUD prevalence in patients with MDD—underscore the need for systematic screening across treatment settings,” wrote the team in their paper.

Because the two disorders appear deeply linked, catching one early may prevent the other from worsening.

College students with anxiety, depression and eating disorders may be more likely to start and to respond more positively to therapy offered via a digital app compared to referrals to in-person campus clinics, according to a study led by Penn State researchers and published in the journal Nature Human Behaviour.

Globally, an estimated 40% to 60% of college students experience a mental health disorder at some point, and the need for campus counseling services has increased faster than institutions’ capacity to provide these services, according to the researchers.

The research team wanted to see if a proactive intervention using a digital therapy app could effectively treat anxiety disorders, depression and eating disorders, as well as address the increased need for psychological services.

How the digital therapy app works

The commercially available app incorporates cognitive behavioral therapy (CBT) principles that coach individuals through identifying negative thinking patterns and developing skills and behavioral changes to address these patterns.

The researchers found that students receiving the digital intervention were more likely to report being symptom free at the six-week, six-month and two-year marks, and that these students were more likely to engage these services compared to the campus referral group.

Specifically, service uptake—or when a person actually receives a service—was seven times greater for college students assigned to a digital intervention than to on-campus clinic referrals. Approximately 74% of individuals given access to the digital intervention started the program, compared to 30% of individuals who were given a referral to a campus clinic and received at least one therapy session or a new medication prescription.

“One of the challenges with any digital intervention is that people sometimes download an app but then do not use it,” said lead author Michelle Newman, professor of psychology and psychiatry at Penn State.

“We were also interested in learning the extent to which people actually received services after being randomized to the app or on-campus counseling center. We found that uptake was significantly better in the digital intervention than referral to the counseling center.”

How the study was conducted

To test the effectiveness of the digital intervention, the researchers worked with 26 colleges and universities across the U.S. to send an email to the entire student body—what researchers call a population-level approach—inviting them to take part in a mental health screening.

Of the 39,194 individuals who completed the screening, 6,205 had clinical levels of or were at high risk of developing generalized anxiety disorder, panic disorder, social anxiety disorder, depression or an eating disorder. Those individuals completed an additional baseline survey and were randomized into one of two groups. One group received access to the coached digital intervention for six months, while the other group received referrals to their campus counseling center.

The therapy app offered six to eight 20-minute-long modules for each mental health problem. Participants in the digital therapy group completed an average of 2.4 modules and received about 15 messages from a trained therapy coach.

Newman explained that individuals in the digital therapy group began with modules addressing their main mental health concern and then worked with their coaches to receive additional modules that addressed co-occurring issues.

Measuring multiple disorders over time

“A unique aspect of the work was that we screened for five disorders—generalized anxiety disorder, social anxiety disorder, panic disorder, depression and eating disorders—and measured all disorders at every point in the treatment, because we know that disorders like depression and anxiety often co-occur, but that co-occurrence doesn’t necessarily happen simultaneously,” Newman said.

“The digital intervention overall had a significantly larger number of individuals who had no disorders at every timepoint in the study. We did not just treat individuals with clinical levels of these disorders, but we also prevented the onset in more of those in the digital intervention who screened to be at risk.”

For example, compared to the campus referral group, those who used the digital intervention had a 4.3% lower prevalence of having any mental health disorder at the six-week mark, 4.9% lower prevalence at the six-month mark and 3.8% lower prevalence at the two-year follow-up.

This result showed that the coached digital intervention both prevented the development of new disorders as well as treated disorders that were present before the intervention.

Implications beyond the pandemic

The researchers conducted the study during the height of the COVID-19 pandemic, recruiting participants from October 2019 to November 2021 and completing their data collection by October 2023. The results, they said, highlight the effectiveness of digital interventions at times when access to traditional, in-person services may have been constrained.

The population-level screening and digital therapy approach can complement existing in-person services beyond college campuses, Newman said.

“This approach could potentially be used anywhere where you have access to a full population in terms of email addresses, like at a company, to help disseminate mental health services that people might not think about seeking,” she said, explaining that the proactive screening process taken in the study helped individuals prevent disorders for which they were at high risk of developing and treated disorders for which they may not have sought face-to-face services.

Future work to personalize treatment

Next steps will make use of work led by Penn State graduate student Adam Calderon and Newman, who will use data from the current study and previous work by Newman’s lab to examine which individual characteristics may predict who would benefit from digital interventions, Newman said.

Embodying surgical robots with next-gen AI can safely augment practice if ethical and regulatory questions are addressed, say experts writing in Frontiers in Science. A team of pioneering surgeons and researchers from King’s College London says AI-enhanced surgical robotics could enable “true personalized surgery” and enhance the performance, situational awareness, decision-making, and effectiveness of surgical teams.

Their analysis also addresses regulatory questions including reducing risks from systems that continue to learn and change after approval. It also tackles how we can prevent dataset biases from reinforcing inequalities, and how we address the concentration of research and industry in resource-rich nations.

Lead author and robotic urological surgeon Prof Prokar Dasgupta, formerly of King’s College London and Guy’s Hospital, London—who recently performed the UK’s first long-distance robotic operation—said, “Using advanced AI and robotics in the operating room is very exciting. The next few years will see intelligent robots impact all stages of surgery—including techniques, emergency responses, team roles, workflows, and assistive functions.”

The authors warn that AI must sustain—not disrupt—operating rooms, and should support advances and refinement in surgical skill, procedure and technology, they warn. Most importantly, its use should be safeguarded by robust human and regulatory oversight, with surgeons remaining chief decision-makers.

Prof Dasgupta added, “With AI’s promise comes profound implications for clinical practice and the continued safe function of surgical teams. These warrant multistakeholder discussion to ensure clarity of liability, minimization of bias, integration of autonomous robotic systems within surgical teams, global equity, and robust product regulation.”

True personalized surgery

Anticipated advances include AI embedded into surgical robots, known as “embodied AI,” linked to sensor-equipped operating rooms that generate spatial understanding, adaptive learning, performance benchmarking, autonomous surgical assistance, and feedback to teams mid-operation.

Future surgical AI will also harness new data streams—gathered from patients, surgical teams, and sensors in robots—to provide real-time mid-operation guidance and decision support to optimize surgical actions.

Predictive AI could also allow surgeons to accurately visualize the outcomes of various actions before taking them—called cause-and-effect recognition. This could in the future be used to help improve patient outcomes.

First author Dr. Alejandro Granados from King’s College London said, “Surgery is on the brink of a profound transformation, where technology will not only help predict outcomes but also guide clinicians toward the most optimal, personalized treatment for each patient.”

Regulating adaptive systems

Currently, regulators authorize medical technologies based on their submitted form—but AI-embodied surgical robots present a challenge given their ability to learn, adapt, and change post-approval.

To address this challenge, the authors call for regulatory reforms, including changes to licensing pathways, device classifications, post-market monitoring, and compliance standards to better serve the higher risk profile of changing systems.

Dr. Granados said, “AI’s ability to learn presents an unprecedented puzzle. We are at a pivotal time in surgery where we need to begin answering those questions to ensure patients can benefit from the wealth of benefits AI-powered operating rooms bring.”

Clinical trials, the paper asserts, should adopt standardized metrics for evaluating AI software and assessing human–AI and human–robot interactions. It also recommends that regulators work alongside professional bodies to oversee surgical training as practice transitions from clinical expertise to data-driven approaches.

It also recommends new models of collaboration between academia, industry and health care systems in lower income countries to build cost-effective AI and robotic ecosystems from which all can benefit.

Prof Dasgupta said, “We require a new set of frameworks—spanning regulatory and compliance, trial methods, reporting standards, and training approaches—to ensure the ongoing safety and effectiveness of robotics and AI in surgery.”

Dr. Granados said, “Realizing this vision on a global scale will require careful stewardship. We must ensure that health care professionals and patients everywhere can benefit equitably from the compelling potential of AI and robotics innovation that is coming.”

Human decision-makers

The authors expect future iterations of robotics to operate with ever-greater degrees of autonomy while maintaining essential human oversight.

They describe how the surgeon’s role will shift towards supervision, coordination and high-level decision-making, while nurses, anesthetists and assistants can expect to gain additional skills. They also expect surgical teams to be complemented by clinical data scientists plus AI and robotic integration engineers.

Prof Dasgupta said, “Human surgeons must continue to be the chief decision-makers, and insights from AI models must be presented differently to members of the surgical team, based on their role, if we are to maintain the clear chain of authority necessary for safe surgical practice.”

Dr. Granados said, “AI and robotics, strategically deployed in the operating room, will form the foundation of the shift towards systems that learn from every procedure, support surgical teams in real time, and potentially deliver safer, more precise, and better outcomes for patients.

“However, we must ensure that human judgment remains central, while addressing today’s unmet surgical needs and disparities in who benefits from access.”

Multiple sclerosis (MS) is most prevalent in Northern Europe and Canada, and more common in the northernmost latitudes. In recent years, the number of cases has grown, particularly among women. The disease causes the patient’s own immune system to attack a protective coating known as myelin that surrounds nerve cells. When this sheath is destroyed, neuronal function decreases and the cells can ultimately die. This can result in visual disturbances, fatigue, mobility difficulties, and other neurological symptoms that may be permanent.

No treatment for neural damage

Current MS drugs suppress the immune system’s overactivation but are unable to repair the neural damage caused. This is a particular problem in the progressive form of the disease, where damage accumulates slowly over the years.

Researchers have long sought ways to initiate remyelination, a process where the destroyed myelin sheath grows back and the neurons recover. However, all drug candidates trialed so far have failed. The problem is that, particularly in the later stages of MS, the disease creates in the central nervous system local tissue conditions that inhibit remyelination.

Two solutions with the same outcome

In his doctoral thesis, Tapani Koppinen from Associate Professor Merja Voutilainen’s research group identified two different approaches for enhancing remyelination.

In the first approach, a drug molecule targets a stress mechanism intrinsic to brain cells. In areas damaged by MS, this stress response is constantly in overdrive, effectively preventing tissue-repairing cells from doing their job. When the mechanism was blocked using the new drug molecule, remyelination was significantly enhanced and accelerated in brain tissue with MS-like damage. The study was published in the Molecular Therapy journal in February.

The second approach focuses on scar tissue formed around affected areas, which serves as a physical barrier to neural regeneration. By affecting the composition of this scar tissue with the second drug molecule, this approach also succeeded in promoting neuronal recovery. An article focusing on this approach was published in November in the journal Neuropharmacology.

Surprisingly, these two drugs based on entirely different mechanisms led to very similar results: significant remyelination and reduced neuroinflammation in disease models, that is, animal and cell tests modeling the tissue pathology of MS.

First drug that boosts remyelination requires further research

For the time being, the results were achieved in laboratory animals and cell models. The more complex tissue conditions of human MS make it necessary to investigate the efficacy of the drug molecules in humans. One challenge for drugs targeting the brain is the blood-brain barrier, which blocks many substances from entering the brain. The researchers nevertheless demonstrated that both molecules effectively reach the central nervous system in laboratory animals.

“The goal is to enable the molecules we have developed to reach clinical trials, which could one day produce the first drugs that enhance remyelination in MS. In the meantime, our findings can help in investigating the pathogenic mechanisms of MS that inhibit remyelination,” Koppinen says.

Low doses of the investigational medicinal product endoxifen reduce breast density to the same extent as the standard treatment tamoxifen, but without causing such troublesome side effects. This is shown by a new study from Karolinska Institutet published in the Journal of the National Cancer Institute. The results may have implications for future preventive treatment of breast cancer.

Why tamoxifen isn’t ideal for all

Tamoxifen is a well-established drug that has been used for more than 40 years to reduce the risk of recurrence in patients with breast cancer. The drug is also approved for prevention of breast cancer in women at increased risk.

However, the side effects of tamoxifen are a major problem. Many women experience menopausal-like symptoms, such as hot flashes, which means that many do not complete the treatment.

How endoxifen was tested in women

Endoxifen is the most active metabolite formed when tamoxifen is broken down in the body. The new study investigated whether endoxifen in tablet form could provide the same biological impact and a more predictable effect than tamoxifen.

A total of 240 healthy, premenopausal women were randomized to receive a placebo or 1 or 2 mg of endoxifen daily for six months. The researchers then measured mammographic breast density. High mammographic density can contribute to an increased risk of breast cancer but a reduction during treatment can be a good measure of therapeutic outcome.

“Both 1 and 2 milligrams of endoxifen resulted in a clear reduction in breast density compared with the placebo,” says Mattias Hammarström, co-author and Ph.D. candidate at the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet.

Promising results and remaining questions

The results show that 1 mg of endoxifen reduced breast density by an average of 19% and 2 mg by 26%. Data from a previous study show that 20 mg of tamoxifen reduces density by approximately 18.5%. The effect of low-dose endoxifen thus corresponded to that seen with tamoxifen.

Participants who received 2 mg of endoxifen reported a greater worsening of hot flashes and night sweats compared with the lower-dose group, while the 1 mg group had a safety profile similar to that of the placebo with respect to serious side effects and biomarkers.

“Our results suggest that a lower dose may be sufficient to affect breast density, while also appearing to be better tolerated,” says Hammarström.

The study is a so-called proof-of-concept trial, meaning it is designed to demonstrate that a treatment produces the expected biological effect before larger and longer trials are conducted. However, the study cannot show whether endoxifen reduces the risk of breast cancer or recurrence.

Many common mental health disorders, including depression and anxiety, are associated with a tendency to internalize problems or, in other words, to direct feelings inwards instead of expressing them and sharing them with others. Past studies suggest that this tendency to withdraw from others and suppress emotions often emerges early, during childhood and adolescence.

Researchers at the University of Oslo and the Norwegian Institute of Public Health analyzed data collected from families in Norway to investigate the genetic underpinnings of children’s susceptibility to internalize problems.

Their findings, published in Nature Mental Health, show that this susceptibility is influenced both by the children’s genes and by those of their mothers and fathers.

“This paper grew out of a question I asked about four years ago, just after starting my postdoc,” Razieh Chegeni, first author of the paper, told Medical Xpress.

“I was at a conference and asked the behavioral geneticist Meike Bartels: why not put multiple polygenic scores and environmental factors into the same analysis and see which ones matter most for children and adolescent mental health?

“Her answer was that we did not really have the right methods for that yet. That stayed with me. Around the same time, I was starting to learn more about machine learning, especially regularized regression methods.”

Studying parent-child trios in Norway

When exploring the factors associated with a greater risk of developing specific mental health disorders, researchers often rely on polygenic scores. These are numerical estimates of a person’s genetic vulnerability to a specific disorder.

A central challenge in this field of research is that the effects of polygenic scores on the emergence of mental health disorders are typically very small compared to those of psychological and environmental factors, such as parenting styles, traumatic experiences, and friendships.

When the scores are modeled together with psychological and environmental factors, genetic effects tend to get lost and become difficult to uncover.

“Regularized regression made it possible to study many correlated predictors at once and still retain small but meaningful genetic contributions when they improve prediction,” said Chegeni.

“That was really the starting point for this paper. I became especially interested in direct and indirect parental genetic effects, because indirect parental effects sit right at the intersection of genetics and environment: parents’ genetically influenced traits may shape the environments their children grow up in.”

Chegeni and her colleagues wanted to explore the possibility that symptoms of anxiety and depression in children are influenced not only by the children’s own genetic predisposition to these disorders, but also indirectly by genetic characteristics of their parents. The researchers also tried to determine whether these indirect effects of parents’ genes were different in childhood and adolescence.

“One of the reasons this study was possible is that Norway built an extraordinary long-term family health resource,” explained Chegeni.

“Starting in 1999, the Norwegian Mother, Father and Child Cohort Study began recruiting families across the country, collecting information from parents during pregnancy and following children over time. As genetic data were available for mothers, fathers, and children, this gave us a rare opportunity to study mental health risk across the whole family rather than looking at the child alone.”

As part of their study, the researchers analyzed genetic and mental health-related data collected from 9,314 mother-father-child trios residing in Norway.

They specifically focused on reported symptoms of depression and anxiety at two different stages in the children’s development, namely when they were 8 years of age, and when they were 14. When children were 8, the symptoms were typically reported by their mothers, while at 14 they were reported by the adolescents themselves.

“Rosa Cheesman, Ph.D. and Ziada Ayorech, Ph.D. then calculated polygenic scores for 15 traits in each family member, including traits related to well-being, depression, ADHD, smoking, loneliness, and cognitive skills,” said Chegeni.

“A polygenic score is not a single ‘gene for’ a trait, but rather a summary of many small genetic influences associated with that trait. We used a machine-learning method called elastic net regression to analyze these many overlapping signals at the same time.”

Using a machine learning algorithm, the researchers compared four different genetic models to determine which one better accounted for the children’s vulnerability to internalize feelings. The first model only considered a child’s own genetic profile, the second the parents’ genetic profile, the third interaction effects across family members and the fourth combined all these factors.

“In simple terms, the child’s scores reflect a more direct genetic liability, while the parents’ scores may also capture indirect effects through the environment they help create for their child,” explained Chegeni.

“We found that the children’s tendency to depression and anxiety was linked not only to their own genetic predispositions, but also to parental genetic characteristics.”

What contributes to the development of depression and anxiety?

Overall, Chegeni and her colleagues found that the children’s depression and anxiety were most accurately predicted when considering both their own genetic profile and that of their parents. The parents’ genetic profile appeared to influence the children via indirect effects, such as their parenting style and the children’s home environment.

When the children reached adolescence, on the other hand, their own genetic profile appeared to play a greater role in their susceptibility to depression and anxiety. This was particularly evident for depression.

“Our findings suggest that risk may operate through more than one pathway: through the genes children inherit directly, and through parents’ genetically influenced traits that may shape caregiving, family climate, and the broader home environment,” said Chegeni.

“Importantly, we found that these patterns changed across development. Predictive accuracy was generally stronger at age 14 than at age 8, and for depression in particular, parental genetic factors appeared relatively more important in childhood, while children’s own genetic liability became more prominent in adolescence.”

Interestingly, the researchers also found that the genes that most contributed to a child’s susceptibility to internalizing problems differed in mothers and fathers. Genes that were found to play a role included father genes linked to well-being and mother genes linked to smoking and cognitive skills.

“Our paper challenges a narrower way of thinking about intergenerational risk,” said Chegeni. “Even in genetics, there has often been an assumption that if we want to understand why depression or anxiety runs in families, we should mainly look at parental depression- or anxiety-related risk. Our results suggest that this can miss a large part of the picture.”

The results of this study highlight the complexity of genetic factors contributing to the emergence of mental health disorders in childhood and adolescence. They also confirm that the risk of developing mental health disorders depends on a series of biological and environmental factors.

“Parental genetic predispositions related to well-being, smoking, cognitive skills, and ADHD also emerged as relevant predictors of offspring internalizing problems,” said Chegeni. “This suggests that intergenerational mental health risk may involve a broader range of parental traits than has often been assumed.”

Avenues for further research

While this study offers some valuable insight, the variance explained by the team’s genetic models was modest. For now, the insight it provides is thus meant to be scientifically informative and is not applicable in clinical settings.

“This study was an important step for me, but I see it as the beginning rather than the end of this line of work,” said Chegeni. “Now that I have a deeper understanding of gene-environment interplay and more experience with machine learning methods, I am moving toward models that bring these pieces together more directly.”

Chegeni and her colleagues are now conducting further studies in which they are combining the parent-child polygenic scores calculated as part of their recent study with a much broader set of environmental factors. For instance, they plan to consider the effects of these scores in conjunction with family history of mental illnesses, adverse life events, peer relationships and parental conflicts.

“Our goal is to better understand how genetic liability and lived experience work together, rather than studying them in isolation,” added Chegeni.

“I am especially interested in identifying which combinations of genetic and environmental factors matter most for adolescent mental health, how these influences change across development, and whether different pathways are more relevant for different outcomes.

“More broadly, I hope this work can help move the field beyond simple one-risk-factor models toward a more realistic understanding of mental health as the product of many small, interacting influences across the family and social environment.”