ADHD – Mind the Gap Blog

What have we learned about ADHD comorbidities?

Posted on July 2, 2021July 2, 2021 by Jeanette Mostert

After 5.5 years, the CoCA project has come to an end. In this large-scale European research project, an interdisciplinary group of researchers investigated comorbid conditions of ADHD. They particularly focussed on depression, anxiety, substance use disorder and obesity, as these conditions frequently co-occur with ADHD in adulthood.

What has this extensive study brought us? Experts dr. Catharina Hartman (University Medical Center Groningen, The Netherlands) and prof. dr. Andreas Reif (University Hospital Frankfurt, Germany) were invited by Jonathan Marx for an interview on the online radio program Go To Health Media. In this program they talk about several aspects of the CoCA project: How often do comorbid conditions co-occur with ADHD? What do the genetics of ADHD comorbidities tell us? What should clinicians do to prevent or reduce these comorbidities in ADHD?

As professor Andreas Reif summarizes at the end of the interview, the main things that we learned from the CoCA project are:

Comorbidity in ADHD is a very big problem. Adults with ADHD frequently have co-occuring conditions such as depression, anxiety, obesity and to a bit lesser extent substance use disorder.
The type and prevalence of comorbidities differ between men and women.
There is considerable genetic overlap between ADHD and comorbid conditions. We think that at least part of the overlap between comorbidities is caused by genetic effects (next to environmental effects that also play a role).
The dopamine system plays an important role in comorbidity, through influencing brain processes.
Disturbances in the circadian system (i.e. sleep cycle) are unlikely to play a causal role in these comorbidities, but they might be a consequence.
Clinicans should look out for comorbidities when they treat ADHD patients, and inform their patients about their increased risk to develop comorbidities so that they can take preventive measures (i.e. be careful with alcohol to avoid substance use disorder). Secondly, clinicians should actively look out for ADHD symptoms when treating conditions such as depression, anxiety, substance use disorder or obesity.

Watch the full interview with both experts by clicking on the image below:

More information about the CoCA project: www.coca-project.eu

Just-in-time-adaptive-interventions

Posted on June 8, 2021 by elenakochkit

Aid for ADHD individuals personal needs, right when it is needed

You might know the tenet of “just in time” from economics. It means bringing goods to a recipient at the right time, exactly when it is needed. But what if we could apply this also to treatments or interventions for mental health problems? Can we provide small interventions at exactly the time when a person needs it? And can this provide us with more insights into what triggers ADHD symptoms?

Just in time economics is possible and required because of dynamic processes in economical markets. Dynamic processes are also present in mental disorders. Attention-deficit/hyperactivity disorder (ADHD) is a condition that is dynamic by nature. Core symptoms of ADHD are hyperactivity, inattention and impulsivity, and many individuals also experience emotion dysregulation. In the past, research focused mainly on how patients with ADHD differ from healthy individuals or other disorders. But what about ADHD individuals’ context or other dynamics, that may trigger symptoms? For this we need to look much more closely at the dynamics of an individual’s life.

Ambulatory Assessment: collecting data in real time and in real life

The Ambulatory Assessment method makes use of smartphones, accelerometers, GPS-tracking and geolocation approaches to track how you feel, what you do, where you go, who you meet, what you eat, and how you’re body is doing (i.e. your heartrate) (1). This method has improved a lot over years and technical progress makes it more and more feasible to investigate associations between variables over time and how these variables interact in everyday life. This provides researchers with new insights into many different factors that can influence a person’s symptoms and mental health.

The importance of context

The Ambulatory Assessment method also enables to better differentiate between real and deceptive associations. Imagine, a person is asked for hyperactivity in the morning at 9:00 am, noon and evening and it turns out that the person is very hyperactive in the morning. Your conclusion may be that this individual is more hyperactive in the morning, but you don’t know why. If you know more about this person’s context, it may turn out that every day at 08:30 am the person drinks two cups of coffee which causes the measured hyperactivity at 9:00 am. This gives you much more insight into what triggers his or her symptoms.

Another example: imagine that a symptom always occurs in a special situation, at a special place or with a special person (e.g., after trying to catch the connecting train every morning at the same time). If you always ask for symptoms at the same time of day, you may miss this special occasion because it always occurs at another time. This way, you may miss out on important associations between symptoms and situations, places or persons. It is therefore very important to measure symptoms at random time points, or when they are triggered by certain events. This gives you much more informative data.

Cause or consequence?

However, the Ambulatory Assessment method is not yet perfect. The main limitation is that it’s difficult to determine what causes what (2). For example, do fluctuations in mood in patients with ADHD lead to impulsivity or hyperactivity? Or does mood change as a consequence of impulsivity? Another example: Do I feel better after exercising or do I move more because I feel good? Researchers recently found evidence for both directions (3,4).

Towards developing just in time treatment

Let’s think about the next step. A better understanding of causes and consequences and associations between symptoms and environmental triggers in an individual’s real world, creates the basis for just-in-time interventions (6). The idea is to react on dynamics in how symptoms are experienced or triggered, by timing the interventions exactly when it is needed. This could be realized by smartphones or wearables, which are already implemented in Ambulatory Assessment research. These devices are then not only used to collect data in real-time, but also to give feedback and provide interventions to reduce or prevent symptoms.

Exercise intervention through a smartphone app

The antecedent of just-in-time-adaptive-interventions are ecological momentary interventions (EMIs). One example of such an EMI or electronic diary intervention with a smartphone and an accelerometer for individuals with ADHD is the PROUD trial of the European funded project CoCA (5). In this trial, individuals with ADHD received a smartphone and a kind of sports watch (that measures your movement) that together measured their behavior, activity, daylight exposure, mood and symptoms during the day. The smartphone also provided an intervention, either in the form of sports exercises or in the form of bright light therapy. During the exercise intervention, participants are given instructions to perform exercises via a smartphone app by which they are guided through their training by weekly goals, motivational reminders, and training videos. Every evening, they get feedback on performed intervention parameters from that day in real time. This system was not yet so developed that it also changed the type or timing of the intervention to the data that was collected during the day, but that would be the next step to create a just-in-time intervention.

In conclusion, it is important to investigate the associations between ADHD individuals’ symptoms and their personal everyday lives. This helps researchers to understand the dynamic processes behind ADHD and to create tailor-made interventions that can easily be integrated in the everyday life of these individuals. A physician cannot support a patient throughout every step he/she takes, but there are already devices that can be supportive around the clock and technical innovations will surely pave the way to improve personal just-in-time interventions in the near future.

This blog was written by Elena Koch. She is a PhD student at Karlsruhe Institute for Technology in Germany.

References

1. Reichert M, Giurgiu M, Koch ED, Wieland LM, Lautenbach S, Neubauer AB, Haaren-Mack B v., Schilling R, Timm I, Notthoff N, Marzi I, Hill H, Brüßler S, Eckert T, Fiedler J, Burchartz A, Anedda B, Wunsch K, Gerber M, Jekauc D, Woll A, Dunton GF, Kanning M, Nigg CR, Ebner-Priemer U, Liao Y. Ambulatory assessment for physical activity research: State of the science, best practices and future directions. Psychology of Sport and Exercise. 2020;50101742. doi:10.1016/j.psychsport.2020.101742

2. Reichert M, Schlegel S, Jagau F, Timm I, Wieland L, Ebner-Priemer UW, Hartmann A, Zeeck A. Mood and Dysfunctional Cognitions Constitute Within-Subject Antecedents and Consequences of Exercise in Eating Disorders. Psychother Psychosom. 2020;89(2):119–21. doi:10.1159/000504061

3. Koch ED, Tost H, Braun U, Gan G, Giurgiu M, Reinhard I, Zipf A, Meyer-Lindenberg A, Ebner-Priemer UW, Reichert M. Relationships between incidental physical activity, exercise, and sports with subsequent mood in adolescents. Scand J Med Sci Sports. 2020;30(11):2234–50.

4. Koch ED, Tost H, Braun U, Gan G, Giurgiu M, Reinhard I, Zipf A, Meyer-Lindenberg A, Ebner-Priemer UW, Reichert M. Mood Dimensions Show Distinct Within-Subject Associations With Non-exercise Activity in Adolescents: An Ambulatory Assessment Study. Front Psychol. 2018;9268. doi:10.3389/fpsyg.2018.00268

5. Mayer JS, Hees K, Medda J, Grimm O, Asherson P, Bellina M, Colla M, Ibáñez P, Koch E, Martinez-Nicolas A, Muntaner-Mas A, Rommel A, Rommelse N, Ruiter S de, Ebner-Priemer UW, Kieser M, Ortega FB, Thome J, Buitelaar JK, Kuntsi J, Ramos-Quiroga JA, Reif A, Freitag CM. Bright light therapy versus physical exercise to prevent co-morbid depression and obesity in adolescents and young adults with attention-deficit / hyperactivity disorder: study protocol for a randomized controlled trial. Trials. 2018;19(1):140. doi:10.1186/s13063-017-2426-1

6. Koch, ED, Moukhtarian, TR, Skirrow, C, Bozhilova, N, Ashersn, P, Ebner-Priemer, UW. Using e-diaries to investigate ADHD – State-of-the-art and the promising feature of just-in-time-adaptive interventions. Neuroscience & Biobehavioral Reviews. 2021. https://doi.org/10.1016/j.neubiorev.2021.06.002

IS GENETICS BEHIND THE CO-OCCURRENCE OF ADHD AND OTHER DISORDERS?

Posted on May 10, 2021May 12, 2021 by Bru Cormand

A group of researchers from Spain, The Netherlands, Germany, Estonia, Denmark and USA have joined efforts to gain insight into the genetics of ADHD and its comorbidities. This ambitious objective was addressed by the Work Package 2 of a big project called CoCA: “Comorbid Conditions of Attention deficit/hyperactivity disorder (ADHD)”, funded by the European Union for the period 2016-2021.

In psychiatry, the co-occurrence of different conditions in the same individual (or comorbidity) is the rule rather than the exception. This is particularly true for ADHD, where conditions like major depressive disorder or substance use disorders frequently add to the primary diagnosis and lead to a worse trajectory across the lifespan.

There are different reasons that may explain the advent of the comorbidities: Sometimes the two conditions have independent origins but coincide in a single patient. Comorbidity can also appear as a consequence of a feature of a primary disorder that leads to a secondary disorder. For example, impulsivity, a trait that is common in ADHD, can be an entry point to substance use. Comorbidity can also be the result of shared genetic causes. The latter has been the focus of our investigations and it involves certain risk genes that act on different pathologies, a phenomenon called pleiotropy.

Our project started with an approach based on the exploration of candidate genes, particularly those involved in neurotransmission (i.e. the connectivity between neurons) and also in the regulation of the circadian rhythm. We used genetic data of more than 160,000 patients with any of eight psychiatric disorders, including ADHD, and identified a set of neurotransmission genes that are involved at the same time in ADHD and in autism spectrum disorder [1]. In another study we identified the same gene set as involved in obesity measures [2].

Then we opened our analyses to genome-wide approaches, i.e. to the interrogation of every single gene in the genome. To do that we used different statistical methods, including the estimation of the overall shared genetics between pairs of disorders (genetic correlation, r_g), the prediction of a condition based on the genetic risk factors for another condition (polygenic risk score analysis, PRS) and the establishment of the causal relationships between disorders (mendelian randomization). As a result, we encountered genetic connections between ADHD and several psychiatric disorders, like cannabis or cocaine use disorders [3, 4, 5], alcohol or smoking-related phenotypes [6, 7, 8], bipolar disorder [9], depression [6], disruptive behavior disorder [10], but also with personality or cognition traits, like neuroticism, risk taking, emotional lability, aggressive behavior or educational attainment [6 , 11, 12, 13], or with somatic conditions, such as obesity [11, 12].

All these results and others, reported in more than 40 (!) scientific publications, support our initial hypothesis that certain genetic factors cut across psychiatric disorders and explain, at least in part, the comorbidity that we observe between ADHD and many other conditions. This information can be very useful to anticipate possible clinical trajectories in ADHD patients, and hence prevent potential negative outcomes.

Dr. Bru Cormand is full professor of genetics and head of the department of Genetics, Microbiology & Statistics at the University of Barcelona. He leads workpackage 2 of the CoCA project (www.coca-project.eu) on the genetics of ADHD comorbidity.

References

Connection between sleep and mental health – a special case for ADHD

Posted on April 22, 2021April 22, 2021 by Dina Sarsembayeva

Bad sleep is… well, bad for you

Ever seen that meme with Homer Simpson lying awake in bed until 4 am and then falling asleep 8 minutes before the alarm rings? If it felt relatable, then you definitely know how relevant sleep problems can be! That situation shows problems with falling asleep (insomnia) as well as very late sleep timing (read more about this in my previous blog about circadian delay). Both are linked to an infinite number of health problems, especially mental illness. In fact, a typical teenager on TV can demonstrate how bad sleep affects you. Remember how moody, bad-tempered, inattentive at school they usually are or how much they drink and smoke? Well, bad sleep relates to very similar mental health problems: mood disorders, anxiety, aggression, attention deficit hyperactivity disorder (ADHD) and bad habits like smoking, drinking alcohol and taking drugs. The connection between bad sleep and ADHD, however, is one of the most studied.

What about sleep in people with ADHD?

We know that up to 80% of ADHD patients suffer from insomnia^1,2 and most of them have a circadian delay³. Researchers commonly find that if a person has insomnia symptoms and later bed times, then this person also suffers from more severe ADHD⁴. Although it’s not clear why exactly this happens, some think that a natural circadian delay doesn’t let you fall asleep at socially acceptable times, so you regularly get insufficient sleep^5,6. Interestingly, people without ADHD who sleep poorly also develop the same symptoms – inattention and hyperactivity⁷. You might even say that insomniacs develop temporary ADHD! This makes the connection between ADHD and sleep even more curious and important.

What did our research find?

My colleagues and I wanted to know if the same association with sleep happens in other mental illness and if it is different from the connection to ADHD. For this, we examined information from around 38,000 persons in The Netherlands with ages from 4 to 91. Each of them filled in a long online survey with questions about their sleep habits and mental health.

Later, we divided all these people into three groups based on their sleep behaviour. The first groups were people who prefer earlier sleep times and reported no insomnia symptoms. The other two groups comprised persons who preferred later sleep times (a sign of circadian delay). These groups differed in one thing: one group had very few symptoms of insomnia and the other a lot.

After that, we measured if some of these groups had more severe symptoms of mental illness, including ADHD. And yes, the groups with circadian delay – even the ones without insomnia – really did have significantly higher severity of all mental illness compared to early sleepers! Moreover, the individuals in the circadian delay group with insomnia had more mental health problems than those who slept well. In ADHD specifically, this link between circadian delay and insomnia was as large for symptoms of inattention as for hyperactivity/impulsivity. Children and adolescents had even stronger relation between poor sleep and mental health problems, just like that moody teenagers I mentioned before.

Why this matters

Insomnia and circadian delay, as we see from these results, is a common problem for different types of mental illness. Good sleep usually means better mental health, so people diagnosed with a mental illness might want to improve their sleep behaviour. The good news is that reducing mild insomnia might be easy: anyone can get blinders to keep their bedroom dark and drink less coffee. Circadian delay, though, is harder to change, because it is mainly ruled by your genes. This means that those born as late-night birds need to adapt their life to a more nocturnal rhythm to avoid worse mental state. Sadly, we all know it is often impossible. Younger people, for whom sleep is so important, still need to wake up unnaturally early for school. Adults go to sleep only late at night, even if they’d happily nap at 9 pm, because they were working all day and need to finish their house chores. Current expectations of a good worker and student fit morning people but fail to help and only cause more insomnia for those with a circadian delay. Unless we want to feed all adolescents melatonin tablets every day, our society needs to be more tolerant to our individual circadian preferences.

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 circadian preferences and sleep problems can be turned into profiles to predict specific psychiatric conditions.

1. Kessler, R. C. et al. Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization’ s. World Psychiatry 2007;6:168-176) 6, 168–176 (2007).

2. Lugo, J. et al. Sleep in adults with autism spectrum disorder and attention deficit/hyperactivity disorder: A systematic review and meta-analysis. Eur. Neuropsychopharmacol. 1–24 (2020) doi:10.1016/j.euroneuro.2020.07.004.

3. Coogan, A. N. & McGowan, N. M. A systematic review of circadian function, chronotype and chronotherapy in attention deficit hyperactivity disorder. Atten. Defic. Hyperact. Disord. 9, 129–147 (2017).

4. Lugo, J. et al. Sleep in adults with autism spectrum disorder and attention deficit/hyperactivity disorder: A systematic review and meta-analysis. Eur. Neuropsychopharmacol. 38, 1–24 (2020).

5. Çetin, F. H. et al. Chronotypes and trauma reactions in children with ADHD in home confinement of COVID-19: full mediation effect of sleep problems. Chronobiol. Int. 37, 1214–1222 (2020).

6. Eng, D. et al. Sleep problems mediate the relationship between chronotype and socioemotional problems during early development. Sleep Med. 64, S104 (2019).

7. Lunsford-Avery, J. R., Krystal, A. D. & Kollins, S. H. Sleep disturbances in adolescents with ADHD: A systematic review and framework for future research. Clin. Psychol. Rev. 50, 159–174 (2016).

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

Posted on November 18, 2020November 19, 2020 by Victória

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?

Posted on September 28, 2020 by Dener Cardoso Melo

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.

References

Schultz, W. (2015). Neuronal reward and decision signals: From theories to data. Physiological Reviews, 95(3), 853-951. doi:10.1152/physrev.00023.2014
Wise, R. A. (2002). Brain reward circuitry: Insights from unsensed incentives. United States: Elsevier Inc. doi:10.1016/S0896-6273(02)00965-0
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
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
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)

Posted on May 20, 2020May 20, 2020 by clarahausmannkit

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.

References:

[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. https://doi.org/10.1177/1073191116632341

Is it safe to use ADHD medications during pregnancy?

Posted on May 12, 2020 by Lin Li

“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 (https://doi.org/10.1007/s40263-020-00728-2), 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). https://doi.org/10.1007/s40263-020-00728-2

Authors:

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

Posted on May 8, 2020May 11, 2020 by Dina Sarsembayeva

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.

arjan-stalpers-itBTNoD1PpA-unsplash — *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?

sabri-tuzcu-KHBvwAnWFmc-unsplash — *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

Walker, W. H., Walton, J. C., DeVries, A. C. & Nelson, R. J. Circadian rhythm disruption and mental health. Transl. Psychiatry 10, (2020).
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).
Jones, S. G. & Benca, R. M. Circadian disruption in psychiatric disorders. Sleep Med. Clin. 10, 481–493 (2015).
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?

Posted on February 8, 2020February 8, 2020 by jannekedammers

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: https://www.ru.nl/donders/vm-site/collaborations/projects/neuroimage/

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