We all know that a healthy lifestyle is beneficial for our health. But many of us forget that eating healthy, exercising regularly and getting enough sleep is also important for good mental health. In the Eat2beNICE research project a large team of researchers is investigating the link between food and mental health, specifically impulsivity, compulsivity and aggression. To share this knowledge with the rest of the world, they work together with food consultant Sebastian Lege.
The Eat2beNICE project just released a video to explain what the research is about and why it’s important. In this video Sebastian Lege visits the project coordinator Alejandro Arias-Vasquez, en several other researchers in the consortium.
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.
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:
Have you ever thought that ADHD and autism could perhaps be the same disorder? – Or have you thought that they are way too different, two different planets in the psychiatric universe? Researchers do not agree on this. We know that both ADHD and autism are neurodevelopmental conditions with onset in childhood and that they share some common genetic factors, however, they appear with quite different phenotypical characteristics. We also know that people with ADHD or autism have an increased risk of getting other psychiatric disorders, so-called comorbidities, and smaller studies have shown that individuals with ADHD or autism get different psychiatric disorders, and at a different degree.
How can we utilize this knowledge about different psychiatric comorbidities between ADHD and autism? How can we get closer to an answer to this question; are ADHD and autism similar or different conditions? By using large datasets; unique population-based registries in Norway, we wanted to compare the pattern of psychiatric comorbidities in adults diagnosed with ADHD, autism or both disorders. In addition, we wanted to compare the pattern of genetic correlations between ADHD and autism for the same psychiatric traits, and for this, we exploited summary statistics from relevant genome-wide association studies.
In the registries, we identified 39,000 adults with ADHD, 7,500 adults with autism and 1,500 with both ADHD and autism. We compared these three groups with the remaining population of 1.6 million Norwegian adult inhabitants without either ADHD or autism. The psychiatric disorders we studied were anxiety, bipolar, depression, personality disorder, schizophrenia spectrum (schizophrenia) and substance use disorders (SUD).
Interestingly, we found different patterns of psychiatric comorbidities between ADHD and autism, overall and when stratified by sex (Fig.1). These patterns were also reflected in the genetic correlations, however, only two of the six traits showed a significant difference between ADHD and autism (Fig.2).
Figure 2A: The pattern of prevalence ratios of psychiatric comorbidity in adults with ADHD or autism observed in this study (ADHD; n=38,636, autism; n=7,528). Psychiatric conditions are highly prevalent in both ADHD and ASD, with schizophrenia being most prevalent in ASD and antisocial personality disorders in ADHD. Figure from Solberg et al. 2019, CC-BY-NC-ND.
Figure 2B: Genetic correlations (rg) calculated from genome wide association studies. Genetic correlations are also high with both disorders, with especially high correlations between ADHD and alcohol dependence, smoking behavior and anti-social behavoiur. Major depressive disorder has high genetic correlations with both ADHD and autism. Figure from Solberg et al. 2019, CC-BY-NC-ND.
Figure 2. Left: The pattern of prevalence ratios of psychiatric comorbidity in adults with ADHD or autism observed in this study (ADHD; n=38,636, autism; n=7,528). Right: genetic correlations (rg) calculated from genome wide association studies. Psychiatric conditions are highly prevalent in both ADHD and ASD, with schizophrenia being most prevalent in ASD and antisocial personality disorders in ADHD. Genetic correlations are also high with both disorders, with especially high correlations between ADHD and alcohol dependence, smoking behavior and anti-social behavoiur. Major depressive disorder has high genetic correlations with both ADHD and autism. Figure from Solberg et al. 2019, CC-BY-NC-ND.
The most marked differences were found for schizophrenia and SUD. Schizophrenia was more common in adults with autism, and SUD more common in adults with ADHD. Associations with anxiety, bipolar and personality disorders were strongest in adults with both ADHD and autism, indicating that this group of adults suffers from more severe impairments than those with ADHD or autism only. The sex differences in risk of psychiatric comorbidities were also different among adults with ADHD and ASD.
In conclusion, our study provides robust and representative estimates of differences in psychiatric comorbidities between adults diagnosed with ADHD, autism or both ADHD and autism. With the results from analyses of genetic correlations, this finding contributes to our understanding of these disorders as being distinct neurodevelopmental disorders with partly shared common genetic factors.
Clinicians should be aware of the overall high level of comorbidity in adults with ADHD, autism or both ADHD and autism, and the distinct patterns of psychiatric comorbidities to detect these conditions and offer early treatment. It is also important to take into account the observed sex differences. The distinct comorbidity patterns may further provide information to etiologic research on biological mechanisms underlying the pathophysiology of these neurodevelopmental disorders.
This study was done at Stiftelsen Kristian Gerhard Jebsen Centre for Neuropsychiatric disorders, University of Bergen, Norway, and published OnlineOpen in Biological Psychiatry, April 2019, with the title:
Berit Skretting Solberg is a PhD-candidate at the Department of Biomedicine/Department of Global Health and Primary Care, University of Bergen, Norway. She is also a child- and adolescent psychiatrist/adult psychiatrist. She is affiliated with the CoCa-project, studying psychiatric comorbidities in adults with ADHD or autism, using unique population-based registries in Norway.
Is there an ‘average ADHD brain’? Our research group (from the Radboudumc in Nijmegen) shows that the average patient with ADHD does not exist biologically. These findings were recently published in the journal. Psychological Medicine.
Most biological psychiatry research heavily relies on so-called case-control comparisons. In this approach a group of patients with for instance ADHD is compared against a group of healthy individuals on a number of biological variables. If significant group effects are observed those are related to for instance the diagnosis ADHD. This often results in statements such as individuals with ADHD show differences in certain brain structures. While our results are in line with those earlier detected group effects, we clearly show that a simple comparison of these effects disguises individual differences between patients with the same mental disorder.
Modelling individual brains
In order to show this, we developed a technique called ‘normative modelling’ which allows us to map the brain of each individual patient against typical development. In this way we can see that individual differences in brain structure across individuals with ADHD are far greater than previously anticipated. In future, we hope that this approach provides important insights and sound evidence for an individualized approach to mental healthcare for ADHD and other mental disorders.
Individual differences in ADHD
When we studied the brain scans of individual patients, the differences between those were substantial. Only a few identical abnormalities in the brain occurred in more than two percent of patients. Marquand: “The brains of individuals with ADHD deviate so much from the average that the average has little to say about what might be occurring in the brain of an individual.”
Personalized diagnosis of ADHD
The research shows that almost every patient with ADHD has her or his own biological profile. The current method of making a diagnosis of psychiatric disorders based on symptoms is therefore not sufficient, the authors say: “Variation between patients is reflected in the brain, but despite this enormous variation all these people get the same diagnosis. Thus, we cannot achieve a better understanding of the biology behind ADHD by studying the average patient. We need to understand for each individual what the causes of a disorder may be. Insights based on research at group level say little about the individual patient.”
Re-conceptualize mental disorders
The researchers want to make a fingerprint of individual brains on the basis of differences in relation to the healthy range. Wolfers: “Psychiatrists and psychologists know very well that each patient is an individual with her or his own tale, history and biology. Nevertheless, we use diagnostic models that largely ignore these differences. Here, we raise this issue by showing that the average patient has limited informative value and by including biological, symptomatic and demographic information into our models. In future we hope that this kinds of models will help us to re-conceptualize mental disorders such as ADHD.”
Wolfers, T., Beckmann, C.F., Hoogman, M., Buitelaar, J.K., Franke, B., Marquand, A.F. (2019). Individual differences v. the average patient: mapping the heterogeneity in ADHD using normative models. Psychological Medicine, https://doi.org/10.1017/S0033291719000084 .
This blog was written by Thomas Wolfers and Andre Marquand from the Radboudumc and Donders Institute for Brain, Cognition and Behaviour in Nijmegen, The Netherlands. On 15 March 2019 Thomas Wolfers will defend his doctoral thesis entitled ‘Towards precision medicine in psychiatry’ at the Radboud university in Nijmegen. You can find his thesis at http://www.thomaswolfers.com
The human genome is not a monolithic entity but has been constantly changing throughout the evolution of the species. The main reason behind is that when new copies of the genome of each individual are generated during reproduction, replication errors (mutations) introduced by the cellular replication machinery which can occur spuriously and be inherited from the next generation onwards.
From a genomic point of view, the magnitude of the error can range from a simple nucleotide change (called single nucleotide variant or SNV) to duplicating/deleting large fragments of the genome (called copy number variants or CNVs), as well as switching the orientation in the genome or rearranging a genomic fragment in a new genomic positions. The most common type of mutation in the human genome is SNV. However, humans also show extensive CNVs compared to other species.
From a functional point of view, all these types of changes can have important phenotypic consequences in the offspring and, ultimately, in the fate of the species when affecting functional genomic elements such as genes.
From an evolutionary point of view, new mutations that modify the phenotype of an individual are the substrate of natural selection. In the most simplistic model of selection, a mutation that confers a higher fitness to the carrier compared to non-carrier individuals will tend to non-stochastically rise in frequency in the population and, ultimately, reach fixation. Conversely, a mutation that confers a smaller fitness to the carriers compared to non-carriers will be detrimental and erased from the population. Obviously, much more complex evolutionary patterns exist in nature (i.e. multiple genes contributing to a phenotype, ancient ongoing balancing selection, or selection on standing selection among others). However, detecting the fingerprint of these evolutionary events in the genome is more complex than in a simple selective sweep.
For SNVs, several examples of genomic regions have been reported in the literature (i.e. adulthood lactose tolerance and skin pigmentation among others). Nevertheless, little is known about the selective pressures acting on genomic rearrangements and CNVs and their role in the etiology of current complex phenotypes, including diseases.
In the first instance, the last statement certainly seems a counter-intuitive nonsense. How can something that has been selected for increasing the reproductive fitness and henceforth considered as beneficial for the carriers be associated to a disease? However, when digging a bit in the theory of Natural Selection, this scenario of positively selecting a variant that it is causal of current diseases is more than plausible. We must take into account that natural adaptation is result of genes and environment acting at individual level and mostly before and during reproductive ages. As a consequence, a functional change that increases the reproductive fitness of the carrier but has detrimental effects for the individual after reproductive age would still be under positive selective pressures and increase in frequency in the population. However, this is not a sine qua non condition for a genetic variant under positive selection in the past and showing detrimental effects in the present. Natural Selection does not work following an established master plan, but acting on the available genetic diversity and environmental conditions at the time. This time dimension has dramatic effect in the interpretation of positive selection:
A genetic variant that was ascertained in the past for a given environment could be detrimental nowadays due to an environmental change. For example, the thrifty gene hypothesis proposes that genetic variants associated to metabolic efficiency and energy storage increased in frequency across the populations in the past as a response to recurrent famines. However, these variants could be harmful at present in the rich food energy environment of occidental diet and associated with phenotypes such as obesity or diabetes.
By introgression with other related species such as Neanderthals or Denisovans, our ancestors could have incorporated genetic variants specific from these species. Since these species were well adapted to their environments at the time when anatomically modern humans arrived from Africa, humans could have enhanced their adaptation to the new environments by means of this archaic admixture. Nevertheless, although this scenario has been observed for some loci, the archaic hybridization has also a main negative impact in the genome of humans. Most of the introgression has been lost due to purifying selection and it has been shown that some introgressed genetic variants play a role in complex diseases.
A supported evolutionary genomic change by natural selection in the past could promote nowadays new disease-associated genomic changes that would unlikely to naturally happen otherwise. This scenario is particularly important in the case of rearrangements and CNVs. For example, a rearrangement allowing increasing or decreasing the dosage of a gene or genes could have been selectively advantageous in the past. However, further favourable modifying the gene dosage modification by the pattern of the rearrangement could have negative side effects lately.
Nuttle and colleagues have recently studied the evolutionary history of the 16p11.2 region in humans and the homologous region in other primate species. In previous studies, it was shown that recurrent copy number variation (CNV) at chromosome 16p11.2 accounts for approximately 1% of cases of autism.
Their analyses show that this region has undergone a large number of complex chromosomal rearrangements and duplications during primate evolution and particularly at the human lineage. In particular, the authors have shown that these rearrangements at the primate lineage have provided the genomic scenario for further human-specific rearrangements and fragment duplications. Interestingly, these human-specific duplications have provided the substratum for the rise of a CNV region with a block size of 102-kbp cassette, containing a set of genes — BOLA2, SLX1 and SULT1A3 —. involved in autism. The authors have shown that the number of copies of BOLA2 modifies the degree of expression of the gene and protein levels, thus providing evidence of functional involvement for the CNV.
If these results are interesting per se for understanding the evolutionary history of this genomic region, more astonishing information could be concluded while analyzing the genetic variation present at this locus. Based on the number of copies of BOLA2 in current populations (four or more in 99.8% of humans), the presence of even a higher number of copies in an ancient human sample from ~45,000 years ago, the absence of polyploidy in Neanderthals and Denisovans, the lack of evidence of archaic introgression in this region and the presence of a high frequency of rare variants, Nuttle and colleagues conclude that the presence of such large number of copies in humans is not by a stochastic process, but by the action of positive selection.
What are the implications of these findings for autism risk? According to the authors, human evolution would have directionally promoted the increase in the number of copies of the gene at expenses of creating genomic regions (breakpoints) flanking the CNV of high-identity. A collateral side effect of such high-identity breakpoints would be an increased probability of conducting recurrent unequal crossover during the creation of the gametes and the ultimate creation of microdeletions at the 16p11.2 region that have been associated to autism.
Comorbidity, defined as the simultaneous occurrence of more than one disorder in a single patient, is commonplace in psychiatry and somatic medicine. In research, as well as in routine clinical settings.
In March 2016 the new H2020 collaborative project “CoCA” (Comorbidity in adult ADHD) was officially launched, with a 3-day kick-off meeting in Frankfurt, Germany. This ambitious project, which is coordinated by professor Andreas Reif and is co-maintaining this shared blog, will investigate multiple aspects of comorbidity in ADHD.
For instance, CoCA will “identify and validate mechanisms common to the most frequent psychiatric conditions, specifically ADHD, mood and anxiety disorders, and substance use disorders (SUD), as well as a highly prevalent somatic disorder, i.e. obesity”.
As reflected in this bold mission, most scientists trained in the biological sciences agree that studies of overlapping and concurrent phenomena may reveal some underlying common mechanisms, e.g. shared genetic or environmental risk factors.
However, particularly in psychiatry and psychology, the origins of comorbidity have been fiercely debated. Critics have argued that observed comorbidities are “artefacts” of the current diagnostic systems (Maj, Br J Psychiatry, 2005 186: 182–184).
This discussion relates to fundamental questions of how much of our scientific knowledge reflects an independent reality, or is merely a product of our own epistemological traditions. In psychiatry, the DSM and ICD classification systems have been accused of actively producing psychiatric phenomena, including artificial diagnoses and high comorbidity rates, rather than being “true” representations of underlying phenomena. Thus, the “constructivist” tradition argues that diagnostic systems are projected onto the phenomena of psychiatry, while “realists” acknowledge the presence of an independent reality of psychiatric disorders.
In an attempt to explain these concepts and their implications, psychiatric diagnoses and terminology have been termed “systems of convenience”, rather than phenomena that can be shown to be true or false per se (van Loo and Romeijn, Theor Med Bioeth. 2015, 41-60). It remains to be seen whether such philosophical clarifications will advance the ongoing debate related to the nature of medical diagnoses and their co-occurrence.
CoCA will not resolve these controversies. Neither can we expect that our new data will convince proponents of such opposing perspectives.
It is important to acknowledge the imperfections and limitations of concepts and instruments used in (psychiatric) research.
However, it may provide some comfort that similar fundamental discussions have a long tradition in other scientific disciplines, such as physics and mathematics. Rather than being portrayed as a weakness or peculiarity of psychiatric research, I consider that an active debate, with questioning and criticism is considered an essential part of a healthy scientific culture.
Hereby, you are invited to join this debate on this blog page!