Genetic risk scores give new insights into the overlap between ADHD and insomnia

Psychiatric disorders, such as ADHD, are defined by categorical diagnostic borders: you either have it or you don’t. Research has shown that these borders do not accurately reflect what is happening on a biological level. In fact, these are complex traits that can be defined as quantitative characteristics that are present in people in different degrees. When you have or experience these traits in a very high degree, you may classify as having a psychiatric disorder. We also know that both genetic and environmental factors contribute to how much an individual is liable to ‘develop’ a psychiatric disorder, and that for each person, it is a different combination of such factors. This large variability between individuals is called heterogeneity.

The fact that ADHD is very often accompanied by other disorders (called comorbidities) also contributes to the notion that these conditions cannot be defined as a simple “yes/no” categorization. This refers to the notion of pleiotropy, meaning that one gene or biological mechanism can result in different outcomes. During my master’s thesis project, we investigated the genetic relationships between ADHD and insomnia, which is one of the most common conditions to co-occur with ADHD. We also looked into the role of depression, another common comorbidity, in the overlap between insomnia and ADHD.

Nowadays, there are very large datasets that we can use to explore such questions. In order to try to disentangle the genetic relationship between ADHD and insomnia, we calculated a genetic risk score for each individual. This method determines the estimated risk that an individual has to develop a certain trait based on their genetic make-up.  We found that the genetic risk score for insomnia was linked to ADHD symptoms, and vice-versa: the genetic risk score for ADHD was linked to insomnia. We also observed a possible distinct genetic relationship between hyperactivity and inattention symptoms and insomnia: while we found that there was a shared genetic risk for insomnia and hyperactivity symptoms, we did not find this link with inattention symptoms.

Next, we tested the effect of depression in these relationships by the inclusion of depression-related variables as covariates in our analyses. We found that the association between genetic risk score for insomnia and ADHD symptoms was no longer considered significant, while the association between the genetic score for ADHD with insomnia was weaker. At last, we analysed the association of cumulative genetic risk for ADHD with insomnia while separating the individuals in two different groups by broad depression. The results suggest that genetic risk for ADHD is similarly associated with insomnia in individuals with and without depression. This indicates that the genetic relationship observed between ADHD and insomnia is not solely a consequence of the comorbidity between depression and the other two conditions.

The take-home message is that with these results we show that there are shared genetic influences between conditions that are traditionally defined as distinct or separate, so all three conditions might be all entangled in their underlying genetic factors. By advancing our understanding of how ADHD and its comorbidities are related, we can better refine the definition of ADHD.  Also, from this research we learn more about the underlying mechanisms of ADHD (and associated conditions) from a biological (genetic) perspective. As the next step, we plan to include genetic data for separate ADHD symptom dimensions (hyperactivity and inattention), as well as depression in our analyses.

Victória Trindade Pons

I have recently concluded my Master’s in Biomedical Sciences at the Radboud University. This work was part of my final internship and was developed under the supervision of Dr. Nina Roth Mota in the Department of Human Genetics of the Radboudumc. This study is part of the CoCa project (Comorbid Conditions of ADHD), which has the aim to gain insight into the mechanisms underlying ADHD comorbidity and calculate the burden associated with such comorbidity for healthcare, economy, and society.

Picture from pixabay.

What do rewards have to do with mental health problems?

Photo by Jacqueline Munguía

What do you think of when I say “rewards”? Perhaps you think of the points you collect every time you shop or the badges you get when playing a videogame. Well, then you’re right!  A reward can be anything. A good grade, going on a trip with friends, a smile, and even that dessert you crave in the middle of the night. Rewards are any stimuli with the potential to make us seek and consume them, and if we like, we will probably want to get them again [1].

Actually, you crave that dessert because you ate it once, and you liked it so much that your brain learned that eating that dessert again will make you feel good. This happens because of a neurotransmitter called “dopamine” released when you eat the dessert, giving you that little rush of pleasure. Now your brain knows what you like and will want more of that.

By now, you probably have realized that rewards are present in virtually everything we do in our daily lives. That is why seeking and consuming rewards are considered to be a fundamental characteristic of human behavior. These rewards that we keep consuming guarantee that we stay alive by eating and drinking water, for example. Rewards also have a huge influence on how we experience positive emotions, motivate ourselves to perform tasks, and learn new things [2].

What about the relationship between rewards and mental health problems?

Although rewards are natural stimuli that make us keep doing healthy and nurturing things, it can also become a problem. Rewards are not the problem itself, but some people can have an unhealthy behavior towards rewards. That’s where mental health problems come in. Did you know that most mental health conditions have alterations in how rewards are processed in the brain? It’s so common that these so-called reward processing alterations are now considered a “transdiagnostic feature,” meaning we can find them across different mental health conditions [3].

Reward processing is a term to refer to all aspects related to how we approach and consume rewards. For instance, how you respond after getting a reward (responsiveness), how motivated you are to go after a reward (drive/motivation), how impulsive you are when trying to get new and intense rewards (fun-seeking/impulsivity). So, as you can see, it’s not only about getting the rewards, but many different things play a role in a simple action we do.

Let’s think of an example: You are going to a party with your best friends. You are motivated to go out with your friends because you’re always happy when you are around them [this is the drive/motivation]. Once you are at the party, you meet your friends, talk, laugh and are happy you decided to join because you’re feeling that rush of pleasure [this is the responsiveness aspect]. At some parties, things can get a bit out of control, and some people might do risky things on the spur of the moment, like binge drinking. You refuse to binge drink because you thought of the risks, and you don’t want to be in trouble later [that’s the third aspect, the fun-seeking/impulsivity].

Now, let’s think of how that party would be for people with reward processing alterations. In the case of a very high drive, they would be super motivated to hang out with friends. On the other hand, if they have low responsiveness, they wouldn’t be able to have fun at the party even though all of their friends are there and the party is super fun. Lastly, in the case of high fun-seeking/impulsivity, they wouldn’t think of the risks and consequences and engage in binge drinking anyways.

As I mentioned before, these alterations play a role in different mental health conditions. They can affect one or more aspects of reward processing, and they can be either lower or higher than average. For example, people with ADHD can show higher risk-taking, meaning that they are more susceptible to take big risks without thinking about the consequences [4]. This impulsive behavior might be a reflection of the altered fun-seeking aspect of reward processing. Another example is the lack of interest in social interactions in people with autism spectrum disorders [5]. This lack of interest might reflect a reduced drive/motivation to go after social rewards.

These are just some examples of what reward processing alterations might look like in the context of mental health problems. There are still a lot of open questions. As part of my PhD research, I am trying to answer some of them. For example, which came first? Are reward processing alterations causing mental health problems, or are they just mere symptoms of these conditions? If you want to learn more about this topic, stay tuned as more blog posts will come!

Dener Cardoso Melo is a PhD candidate at the University Medical Center Groningen (UMCG). He is using data from the CoCA project together with other datasets to investigate the potential causal role of reward processing alterations in different mental health conditions.


  1. Schultz, W. (2015). Neuronal reward and decision signals: From theories to data. Physiological Reviews, 95(3), 853-951. doi:10.1152/physrev.00023.2014
  2. Wise, R. A. (2002). Brain reward circuitry: Insights from unsensed incentives. United States: Elsevier Inc. doi:10.1016/S0896-6273(02)00965-0
  3. Zald, D. H., & Treadway, M. T. (2017). Reward processing, neuroeconomics, and psychopathology. Annual Review of Clinical Psychology, 13(1), 471-495. doi:10.1146/annurev-clinpsy-032816-044957
  4. Luman, M., Tripp, G., & Scheres, A. (2010). Identifying the neurobiology of altered reinforcement sensitivity in ADHD: A review and research agenda. Neuroscience and Biobehavioral Reviews, 34(5), 744-754. doi:10.1016/j.neubiorev.2009.11.021
  5. Stavropoulos, K. K., & Carver, L. J. (2018). Oscillatory rhythm of reward: Anticipation and processing of rewards in children with and without autism. Molecular Autism, 9(1), 4. doi:10.1186/s13229-018-0189-5

Why following instructions is essential for treatment success (and why this is really difficult)


Clara Hausmann, Mental mHealth Lab / Chair of Applied Psychology, Karlsruhe Institute of Technology

When visiting your doctor due to a simple cold you’ve caught, you will probably get the following advice: Get a rest from work, stay in bed for a week, drink a lot of herbal tea and go for a slow walk once a day. Well, you might follow the advice as you’ve been told. But possibly, you can’t stand tea or you are currently under pressure to finish some urgent work and anyway, you don’t feel that bad anymore after one day in bed. The degree to which a patient correctly follows medical advice is called compliance.

            Compliance is also an important term in the psychological and medical research, we are conducting – especially in our ambulatory settings where patients are treated outside of the hospital. In contrast to doing research in very well controlled laboratory settings, embedding research into everyday life  avoids  a lot of methodological disadvantages. For example, participants’ behavior won’t be biased by the presence of a researcher or the artificial situation in the lab. Another great feature of ambulatory assessment lays within the opportunity to gather real time or near real time data. Participants will be regularly asked about their current state of mind, so researchers don’t have to take into account the inaccuracy of patients’ retrospective reports [1] .  Still, we are facing some difficulties when using ambulatory settings – reaching a good compliance is part of it.

            In the CoCA PROUD study, for instance, we are ambulatorily monitoring our ADHD-diagnosed participants’ mental and physical state. Therefore, they are equipped with a smartphone and a small activity sensor. Participants keep an eDiary, by fulfilling repeated questionnaires on the smartphone while the activity sensor on their wrists measures physical activity. Meanwhile, they will take part in some non-pharmalogical interventions (daily physical exercise training or bright light therapy), which promise to alleviate some core symptoms of ADHD and it’s comorbidities such as depression.

            In this study, „compliance“ is what we call the percentage of prompts, that were answered, in order to fulfill the eDiary. All in all, participants receive four prompts per day, including questions about their current mood, social context and ADHD symptomatology. Furthermore, we can analyze how often the sensor was worn. Additionally, checking for the compliance during the interventions allows us to calculate how much time was spend on actively carrying out the instructions (e.g. doing strengthening and aerobic exercises).

In general, we aim to reach a good compliance. The more our participants contribute, the better the quality of data and the understanding of ADHD can be. However, one can imagine that general facts of life such as situational distraction or simple forgetting can be a hindrance for participants, to answer prompts [2].  Apart from this, researchers must be aware, that ambulatory assessment is inherently disruptive to participants’ daily lives. For instance, the activity trackers that participants wear are quite big, and getting daily prompts from the eDiary can be a real nuisance. The art lies in the design of the research: It is unquestionably essential to find a good balance between participants’ expenditure in time and energy and the amount and quality of data collected [3]. In order to find this balance, we’re always first testing the research study on ourselves to check for the feasibility, comfort, and ease of participation.

            Besides that, there are specific challenges for participants diagnosed with ADHD. For instance, the tendency to show irregularities in the day-and-night-rhythm might not always match the time of the smartphone prompts, that are sent in regular intervals. Furthermore, some patients tend to have problems in keeping their belongings organized. Especially for young patients, it might be challenging to keep the phone both charged and on their person. Inattention and lack of concentration as core symptoms of ADHD, are additional burdens to the conscientious and constant work on the questionnaires. Particularly young patients are expected to be quickly bored by the repeated questions, incoming day by day.

            We encounter those difficulties in multiple ways. An important tool is the smartphone’s chat function. Participants can easily reach a contact person and vice versa. Hence, individual or technical problems can be detected and solved quickly. In order to facilitate the start, we send reminding and motivating messages during the first four days of the measurement. To keep participants’ motivation high, they receive daily feedbacks, visualizing how they have performed when exercising.

            Taken as a whole, compliance, whether good or not, provides a lot of important information about the quality of the intervention. A treatment can only be considered as promising and helpful, when patients are able and motivated to include it into their daily lives. Therefore, the combination of ambulatory assessment and compliance monitoring gives us a realistic idea of a treatment’s actual feasibility and – in the consequence – it’s quality.



[1] Trull, T. J., & Ebner-Priemer, U. W. (2013). Ambulatory Assessment. Annual review of clinical psychology, 9, 151–176. doi:10.1146/annurev-clinpsy-050212-185510 

[2] Piasecki et al. (2007). Assessing Clients in Their Natural Environments With Electronic Diaries: Rationale, Benefits, Limitations, and Barriers. Psychological Assessment,19(1), 25-43. doi:10.1037/1040-3590.19.1.25

[3] Carpenter, R. W., Wycoff, A. M., & Trull, T. J. (2016). Ambulatory assessment: New adventures in characterizing dynamic processes. Assessment, 23(4), 414–424.


Is it safe to use ADHD medications during pregnancy?

“Should I discontinue stimulants when I am pregnant?” “Is it harmful to my developing baby if I take ADHD medications during my pregnancy?” “What are the risks both to me and my baby if my ADHD goes untreated?” “What is the best way to manage my ADHD during pregnancy?” – For women with ADHD who become pregnant, especially those with moderate or severe ADHD symptoms, the next few months are filled with questions. One important decision for the pregnant women and their clinician is whether to remain on or cease their ADHD medication treatment before or during pregnancy, or while breastfeeding. Unfortunately, there is no clear ADHD treatment guidelines for pregnant women, which further complicates these decisions. Therefore, there is a need for high-quality evidence to support guidelines for the use of ADHD medication during pregnancy.

Given that, it is unethical to include pregnant and breastfeeding women in clinical trials, evidence-based guidelines need to rely on findings from naturalistic studies. So, what does the available findings from naturalistic studies tell us?  

In our newly published paper in CNS Drugs (, we conducted a systematic review to synthesize all available evidence regarding the safety of ADHD medication use while pregnant, with a focus on how these studies have handled the influence of confounding, which may bias the estimates from observational studies.

We identified eight cohort studies that estimated adverse pregnancy-related and offspring outcomes associated with exposure to ADHD medication during pregnancy. These studies varied a lot in data sources, type of medications examined, definitions of studied pregnancy-related and offspring outcomes etc. Overall, there was no convincing evidence for an association between maternal ADHD medication use during pregnancy and adverse pregnancy and offspring outcomes. Some studies suggested a small increased risk of low Apgar scores, preeclampsia, preterm birth, miscarriage, cardiac malformations, admission to a NICU, and central nervous system (CNS)-related disorder, but other available studies failed to detect similar associations. Because of the limited number of studies and inadequate confounding adjustment, it is currently unclear whether these small associations are due to a causal effect of prenatal exposure to ADHD medication or confounding.

In conclusion, the current evidence does not suggest that the use of ADHD medication during pregnancy results in significant adverse consequences for mother or offspring. However, the data are too limited to make an unequivocal recommendation. Therefore, physicians should consider whether the advantages of using ADHD medication outweigh the potential risks for the developing fetus according to each woman’s specific circumstances.

More information here:

Li, L., Sujan, A.C., Butwicka, A. et al. Associations of Prescribed ADHD Medication in Pregnancy with Pregnancy-Related and Offspring Outcomes: A Systematic Review. CNS Drugs (2020).


Lin Li, MSc, PhD student in the School of Medical Science, Örebro University, Sweden.

Henrik Larsson, PhD, professor in the School of Medical Science, Örebro University and Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Sweden.

The notorious evening chronotype and my master’s thesis

Almost every person, healthy or not, suffers from occasional problems with sleep and circadian rhythm. In the modern days of 24/7 smartphone use and transcontinental flights, our internal body clock is having a hard time adjusting to the external cues. For the persons suffering from mental health issues, their impaired sleep cycle can be one of the cornerstone problems of daily living. Sleep problems have been confirmed to be a first symptom, consequence, or even a cause of such psychiatric conditions as major depression, bipolar disorder, ADHD, autism, substance abuse, and even aggressive behaviour. Their strong relations, however, have not been studied systematically and broadly just yet.

Why study the circadian rhythm?

Circadian rhythm is our inner clock that regulates a lot of important processes in the human body, including the sleep/wake cycle, the release of hormones and even the way we process medicines. This clock is run by the brain region called the hypothalamus, which piles up a protein called CLK (referring to “clock”), during the daytime. CLK, in turn, activates the genes which make us stay awake, but also gradually increases the creation of another protein called PER. When we have a lot PER, it turns off CLK production and makes us ready to sleep. As CLK is getting lower, this causes a decrease in PER, so that the process starts again with elevating CLK waking us up. This cycle happens at around 24-hour intervals and is greatly influenced by so-called zeitgebers, or time-givers, like light, food, noise and temperature. When our retina neurons catch light waves, the suprachiasmatic nucleus in our brain stops the production of the hormone called melatonin that induces sleep and starts producing noradrenaline and vasopressin instead to wake us. This is the exact reason why you cannot fall asleep after watching a movie at night.

Figure 1. The smart protein CLK wakes us up and its friend PER gets us to sleep.

Sometimes our body clock fails to function, as in the case of jetlag when we feel bad after changing a time zone or social jetlag when we have to start work early at 8 am. It can go as far as a circadian rhythm disorder meaning you have either a delay or advancement of sleep phases or an irregular or even non-24-hour daily activities preference. However, in the general population, a small variation in the rhythm is quite normal and is usually referred to as a chronotype. It defines your preference of when to go to sleep and do your daily activities and is divided into 3 distinct versions. The radical points of these variations include a morning chronotype, or “larks”, who go somewhat 2-3 hours ahead of the balanced rhythm, and an evening chronotype, or “owls”, who are a little delayed. The larks feel and function better during the first half of the day and go to bed rather early, while the owls prefer to work in the evenings and go to bed and wake up naturally late. The third chronotype is the in-between, balanced version of these two.

Figure 2. The ‘owls’ seem to have questionable personalities and suffer from psychiatric conditions more often!

What’s my study about?

Previous research has shown that many psychopathologies are linked to an evening circadian preference. For my master thesis research, I am investigating whether we can identify specific profiles in sleep and circadian rhythm problems that are linked to specific mental health problems. There was even a curious study where researchers linked the Dark Triad personalities, which include people with tendencies for manipulation, lack of empathy, and narcissism, to the evening chronotype. Maybe this leaves some evidence for the famous quote that “evil does not rest”. However, there’s a great variation in sleep duration and perceived quality of sleep in patients with various diseases. We hope to divide such persons into more or less accurate groups with a sleep profile that would predict and aid the correct diagnosis of one or the other mental health condition.

The psychopathologies are included in our study as so-called dimensions, which look at each psychiatric syndrome not as with a norm/pathology cut-off but rather as a continuum of symptoms severity. This approach allows us to see if the sleep/circadian profile we identify refers to mental health in general or can be a distinguished part of a certain psychiatric condition. It might be that all dimensions, like depression and autistic spectrum disorders, have an evening chronotype and some non-specific sleep problems. Alternatively, we might find out that a person with symptoms of depression would sleep more or less than average and go to bed later, whereas a person with anxiety would go to sleep later as well but wake up at night very often despite an average summed up sleep duration.

The circadian rhythm changes throughout a lifetime from an early to an evening chronotype towards adolescence and then gradually shift back to the earlier preference with older age. Across the whole lifespan people constantly face varying quality of night sleep. Moreover, each psychiatric condition has a particular age of onset and sometimes changes its character with time. These are the reasons why our study will also look at how the sleep/circadian profiles change within the development phases from children (4-12 years) to adolescents (13-18) to adults (19-64) to the elderly (≥65) and if they affect males and females differently.

Why would it matter?

Should we discover distinct links between the profiles of sleep/circadian problems and certain conditions, other studies can then look into whether these profiles could be the reasons behind developing a mental health condition. It’d be interesting to finally learn what is a chicken and an egg in each profile-disease relation. For instance, should we really treat ADHD patients with melatonin and bright-light lamps instead of stimulants?

Figure 3. Maybe if we adopt a typical cat’s lifestyle, we get less mental health problems. 🙂

Dina Sarsembayeva is a neurologist and a research master’s student at the University of Groningen. She is using the data from the CoCa project to learn if the chronotypes and sleep problems can be turned into profiles to predict specific psychiatric conditions.

Further reading

  1. Walker, W. H., Walton, J. C., DeVries, A. C. & Nelson, R. J. Circadian rhythm disruption and mental health. Transl. Psychiatry 10, (2020).
  2. Logan, R. W. & McClung, C. A. Rhythms of life: circadian disruption and brain disorders across the lifespan. Nature Reviews Neuroscience vol. 20 49–65 (2019).
  3. Jones, S. G. & Benca, R. M. Circadian disruption in psychiatric disorders. Sleep Med. Clin. 10, 481–493 (2015).
  4. Taylor, B. J. & Hasler, B. P. Chronotype and Mental Health: Recent Advances. Curr. Psychiatry Rep. 20, (2018).

On a coalmine and an MRI scanner – Is it fun, participating in DELTA?

About two and a half years ago, Dr. Emma Sprooten started the DELTA project. In DELTA, acronym for Determinants of Long-term Trajectories in ADHD, she investigates factors that contribute to the difference in (severity of) symptoms and impairment in people who were diagnosed with ADHD as a child. Previously, these adults participated in a study called NeuroImage when they were a child. We asked them if they were willing to participate one more time in this study. In the coming three weeks, we will post three blogs about the project. This is blog 1.

2019. Somewhere in autumn. Trees have become all shades of brown, yellow and red. We pass forests while driving on a German highway, all the way from Holland. After a while, the landscape changes from the colored forest to an industrial town. It is grey and gloomy, packed with old-fashioned industry buildings. Soon, the navigation sends us into an even more surreal place. We find ourselves surrounded by rusty brown pipes in a place that feels like an abandoned factory. If we would not know better, we would begin to feel a bit worried about what could happen here… 

What brings us here in this desolate area? To put it short, a bunch of people who were diagnosed with ADHD during their childhood, and a hypermodern 7 Tesla MRI scanner. Over ten years ago, as children, our participants first came in together with their parents and siblings. They played games, were interviewed and got an MRI scan, that was presented to them as ‘ a picture of the inside of your brain’. Now, we are repeating these measurements for a third time, with an upgrade from 3 Tesla to 7 Tesla MRI, allowing even more detailed pictures of their brains.

For scientists it is extremely valuable that people are willing to take part in this research. This is one of the few cohorts in the world in which people with ADHD are followed up for such a long time. It makes it possible to investigate which factors influence the different clinical trajectories that ADHD can take:. We are now testing people for already a third time in the NeuroImage project, that started in 2009. The current follow-up is called the DELTA project. More on the content of the project in our third blog. 

Next week, we’ll give you a peek into what a participant experiences during a test day in Essen. 

If you cannot wait to get some information on NeuroImage, see:

For a peak into Zollverein, the world heritage site where the 7 Tesla scanner is located, see: The photo at the top of this post shows a detail of the coal mine at Zollverein.

“No I do not have ADHD, I am just busy!”, but still very interesting for genetic studies!

Do you sometimes find it difficult to pay attention? Can you be very disorganized at times, or very rigid and inflexible? Although difficulties with attention, organization and rigidity are symptoms of psychiatric disorders, these traits are not unique to people with a diagnosis. And that is very useful for studying the genetics of psychiatric disorders.

Being easily distracted, liking things to go in a certain way, having a certain order in the way you do things, these might all be things you recognize yourself (or someone you know) in, while you (or they) are not diagnosed with any psychiatric disorder. We actually know that many of these symptoms are indeed found in a range in the general population, with some people showing them a lot, some a little and some not at all. If these symptoms are also present in people without a diagnosis then why should we only study people with a diagnosis to learn more about the biology of symptom-based disorders?

Many psychiatric disorders, like attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are disorders that ‘run in the family’. Using family-based and genetic studies it was found that they are actually highly heritable. However the underlying genetic risk factors turned out to be difficult to find. Enormous samples sizes (comparing more than 20 000 people with the disorder to even more individuals without the disorder) were needed to robustly find just a few genetic risk factors, although we know that many more genetic factors contribute. Even though these disorders are highly prevalent, collecting genetic data on psychiatric patients for research is still challenging. Using population-based samples – that include all varieties of people from the general population – can be a good alternative to reach large sample sizes for powerful genetic studies.

Taking together the fact that psychiatric-like symptoms are also, to a certain degree, present in the general population, and the fact that genetic studies can benefit from large(r) sample sizes to find genetic associations, it can be very interesting to study psychiatric-like traits in population-based samples. This is indeed what happened in the field of psychiatric genetics. The first proof-of-concept studies were able to show an astonishing overlap in genetic factors of more than 90% between ADHD and ADHD symptoms in the general population. Our own research group was able to show that certain autistic traits, like rigidity, indeed share a genetic overlap with ASD and that genes that were previously linked to ASD show an association to autistic traits in the population. These results show that genetic factors involved in disorder-like traits are overlapping with genetic factors involved in the clinical diagnosis, and therefore can indeed be used to study the biology of psychiatric disorders.

So next time you feel distracted/rigid/disorganized, don’t get discouraged, but consider signing up for a genetic study. Science might need you!

Janita Bralten is a postdoctoral researcher at the department of Human Genetics in the Radboud university medical center, Nijmegen, the Netherlands. Her research focusses on the genetics of psychiatric disorders.

Further reading:

Bralten J, van Hulzen KJ, Martens MB, Galesloot TE, Arias Vasquez A, Kiemeney LA, Buitelaar JK, Muntjewerff JW, Franke B, Poelmans G. Autism spectrum disorders and autistic traits share genetics and biology. Mol Psychiatry. 2018 May;23(5):1205-1212.

Middeldorp CM, Hammerschlag AR, Ouwens KG, Groen-Blokhuis MM, Pourcain BS, Greven CU, Pappa I, Tiesler CMT, Ang W, Nolte IM, Vilor-Tejedor N, Bacelis J, Ebejer JL, Zhao H, Davies GE, Ehli EA, Evans DM, Fedko IO, Guxens M, Hottenga JJ, Hudziak JJ, Jugessur A, Kemp JP, Krapohl E, Martin NG, Murcia M, Myhre R, Ormel J, Ring SM, Standl M, Stergiakouli E, Stoltenberg C, Thiering E, Timpson NJ, Trzaskowski M, van der Most PJ, Wang C; EArly Genetics and Lifecourse Epidemiology (EAGLE) Consortium; Psychiatric Genomics Consortium ADHD Working Group, Nyholt DR, Medland SE, Neale B, Jacobsson B, Sunyer J, Hartman CA, Whitehouse AJO, Pennell CE, Heinrich J, Plomin R, Smith GD, Tiemeier H, Posthuma D, Boomsma DI. A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts. J Am Acad Child Adolesc Psychiatry. 2016 Oct;55(10):896-905.

If you are interested in joining a scientific study see for example:

or (Dutch only)

Pay Attention to ADHD – Podcast with prof. Stephen Faraone

Professor Stephen Faraone – professor in Psychiatry at SUNY Upstate University and expert on ADHD – was interviewed by dr. Therese Markow for the podcast series ‘Critically Speaking’. In this podcast they discuss myths about ADHD and the scientific evidence that debunks these myths. Stephen Faraone explains why it is so important to diagnose and treat ADHD early. He also explains why ADHD is often undiagnosed in girls, and why sometimes adults are diagnosed with ADHD who have not sought treatment earlier in their life.

Critically Speaking is a podcasts series hosted by dr. Therese Markow who interviews experts to discuss in plain language complex issues that concern our health, society and planet.

You can listen to the podcast here:


Can virtual reality help in the treatment of ADHD?

Virtual-reality (VR) can be defined as an interactive computer-generated experience that can be similar to the real world or fantastical1. For instance, in a VR environment, a person is able to virtually live in the artificial world by looking and moving around it, as well as interacting with virtual characters or items2. Nowadays there are different kinds of VR environments, mainly used for entertainment purposes (e.g. video-games) or professional training (e.g. aviation, military training etc.)3. VR tools usually  range from a headset  (head-mounted displays with a small screens in front of the eyes), to proper full-scale rooms with bigger screens and special equipment  to increase the augmented reality experience.

Virtual reality head-mounted display. Image by Gerd Altmann from Pixabay.

VR has been recently investigated as a potential treatment for different metal health problems or psychiatric disorders such as social anxiety4, specific phobias5, post-traumatic stress disorder (PTSD)6, or persecutory delusions7. The key assumption behind the use of VR tools in mental health practice, relies in the fact that, in VR settings, individuals can repeatedly experience and learn appropriate coping strategies in a controlled environment8,9. For instance, knowing that the exposure is not real, allows people to face difficult situations and learn therapeutic strategies which they can then adopt in the real world.

..but how those VR tools can be used for the treatment of ADHD?

Recent evidence shows that VR can help enhance some of the core therapeutic challenges of ADHD such as attention, problem solving and managing impulsive behaviours10. For example, using VR can create virtual scenarios that can reward and empower skills such as response inhibition and emotional control10. One of the most commonly used scenarios is the class-room environment, which can introduce life-like distractions to asses children’s behaviour in an ecologically-based setting 10-11. In this virtual environment children with ADHD may be more able to use the trial-and-error instructional strategies to train learning skills11. For instance, in these VR settings, children with ADHD can also learn strategies to use in the real world without experiencing failures due to their experiences at school, making them more willing to accept the private feedback of the VR teacher.

Although VR ca be potentially used in ADHD treatment, is still an experimental procedure that needs more research to assess its validity. Also, there are still some concerns regarding potential side effects of long-term VR exposure, such as headaches, seizures, nausea, fatigue, drowsiness, disorientation, apathy, and dizziness10. Overall, despite its therapeutic potential, more studies are needed to assess its long-term treatment efficacy as well as the efficacy of VR environments compared to other non-pharmacological treatments already available for ADHD.

Isabella Vainieri and Jonna Kuntsi

Isabella Vainieri is a PhD student at the Social, Genetic & Developmental Psychiatry Centre at King’s College London.

Jonna Kuntsi is Professor of Developmental Disorders and Neuropsychiatry at King’s College London.


  1. Burdea, Grigore C. and Philippe Coiffet. Virtual Reality Technology. John Wiley & Sons, 2017.
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The cortex and ADHD: the second project of the ENIGMA-ADHD collaboration.

After the first project on subcortical brain volumes in ADHD, published in Lancet Psychiatry in 2017 , ENIGMA-ADHD now analysed cortical data of 2246 people with a diagnosis of ADHD and 1713 people without, aged between four and 63 years old.  The data came from 37 research groups from around the world. FreeSurfer (imaging software) parcellations of thickness and surface area of 34 cortical regions were compared between cases and controls in 3 separate age groups; children, adolescents and adults.


Subtle differences only in the group of children were found. The childhood effects were most prominent and widespread for the surface area of the cortex. More focal changes were found for thickness of the cortex. All differences were subtle and detected only at a group level, and thus these brain images cannot be used to diagnose ADHD or guide its treatment.

These subtle differences in the brain’s cortex were not limited to people with the clinical diagnosis of ADHD: they were also present – in a less marked form – in youth with some ADHD symptoms. This second finding results from a collaboration between the ENIGMA-ADHD Working Group and the Generation-R study from Rotterdam, which has brain images on 2700 children aged 9-11 years from the general population. The researchers found more symptoms of inattention to be associated with a decrease in cortical surface area. In a third study, using the NeuroImage data from Nijmegen and Amsterdam, familial effects on those regions that showed case-control differences were investigated.  Siblings of those with ADHD showed changes to their cortical surface area that resembled their affected sibling. This suggests that familial factors such as genetics or shared environment may play a role in brain cortical characteristics.

We identified cortical differences that are consistently associated with ADHD combining data from many different research groups internationally. We find that the differences extend beyond narrowly-defined clinical diagnoses and are seen, in a less marked manner, in those with some ADHD symptoms and in unaffected siblings of people with ADHD. This finding supports the idea that the symptoms underlying ADHD may be a continuous trait in the population, which has already been reported by other behavioural and genetic studies.’ In the future, the ADHD Working Group, which is led by Martine Hoogman and Barbara Franke from the Radboudumc in Nijmegen, hopes to look at additional key features in the brain- such as the structural connections between brain areas – and to increase the representation of adults affected by ADHD, in whom limited research has been performed to date.

Link to the article: Hoogman et al., Brain Imaging of the Cortex in ADHD: A Coordinated Analysis of Large-Scale Clinical and Population-Based Samples

To learn more about other projects that are carried out using ENIGMA-ADHD data, please also read the paper by Yanli Zhang-James and colleagues on bioRxiv. Here, the ENIGMA-ADHD data of the first and the second project were used to do prediction modelling.  

The ADHD Working Group is one of over 50 working groups of the ENIGMA Consortium, in which international researchers pull together to understand the brain alterations associated with different disorders and the role of genetic and environmental factors in those alterations. For more information about ENIGMA-ADHD please visit our website or contact Martine Hoogman martine.hoogman (at) radboudumc.nlenigma_300dpi