November 29, 2021
Sweden has a national single-payer health insurance system that includes virtually the entire population. It also has a system of national registers that track every resident from birth to death. That makes it possible to conduct nationwide population studies with a very high degree of precision and reliability.
In addition, one of the national registers is the Swedish Twin Register. Tracking all twins in the population enables studies to evaluate the degree to which observed associations may be attributable to genetic influences and to familial confounding. The twin method relies on the different levels of genetic relatedness between monozygotic ("identical") twins, who are genetically identical, and dizygotic ("fraternal") twins, who share on average half of their genetic variation (as do ordinary full siblings).
A Swedish team of researchers identified 42,582 Swedish twins born between 1959 and 1985, and who were, therefore, adults by the time of the study (20-47 years old). Of these, 24,872 (three out of five) completed a web-based survey with 1,300 questions covering lifestyle and mental and physical health. Out of this group, 17,999 provided information on ADHD symptoms and food frequency.
Self-reported ADHD symptoms came from nine inattention components and nine hyperactivity/impulsivity components, covering the 18 DSM- IV symptoms of ADHD.
The food frequency questionnaire included 94 food items, with the following frequency categories: never, 1-3 times/month, 1-2 times/week, 3-4 times/week, 5-6 times/week, 1 time/day, 2 times/day, 3 times/day.
In the raw data, the two subtypes of ADHD exhibited very similar associations. Both had significant associations with unhealthy diets. Both were more likely to be eating foods high in added sugar, and neglecting fruits and vegetables while eating more meat and fats.
After adjusting for the degree of relatedness of twins (whether monozygotic or dizygotic) and controlling for the other ADHD subtype, the associations remained statistically significant for inattention, but diminished to negligible levels or became statistically non-significant for hyperactivity/impulsivity.
Even for persons with inattention symptoms, adjusted correlations were small (never exceeding r = 0.10), with the strongest associations being for overall unhealthy eating habits (r = 0.09), eating foods high in added sugar (r = 0.10) or high in fat (r = 0.05), and neglecting fruits and vegetables (r = 0.06). All other associations became statistically non-significant.
For persons with hyperactivity/impulsivity symptoms, the only associations that remained statistically significant - but at tiny effect sizes - were unhealthy dietary patterns (r = 0.04) and consumption of foods high in added sugar (r = 0.03).
The further genetic analysis, therefore, focused on the strongest associations, between ADHD subtypes on the one hand, and unhealthy dietary patterns and eating foods high in added sugar on the other hand. The heritability estimates (the fraction of phenotypic covariance explained by genetic influences) were 44%, 40%, and 37% for inattention and high-sugar food, inattention and unhealthy dietary patterns, and hyperactivity/impulsivity and high-sugar food, respectively.
When examining only differences between pairs of monozygotic("identical") twins, the correlations became stronger for inattention, rising to r = 0.12 for unhealthy eating habits and r = 0.13 for consumption of foods high in added sugar. For hyperactivity/impulsivity symptoms, the association with unhealthy eating habits was weaker, and the association with consumption of foods high in added sugar became statistically insignificant.
The authors concluded, "we identified positive associations between self-reported trait dimensions of ADHD and intake of seafood, high-fat food, high-sugar food, high-protein food, and an unhealthy dietary pattern, and negative associations with consumption of fruits, vegetables, and a healthy dietary pattern. However, all the associations are small in magnitude. These associations were stronger for inattention compared to hyperactivity/ impulsivity. This pattern of associations was also reflected at the etiological level, where we found a slightly stronger genetic correlation between inattention with dietary habits and hyperactivity/impulsivity with dietary habits. Non-shared environmental influences also contributed to the overlap between ADHD symptom dimensions and consumption of high-sugar food and unhealthy dietary pattern. However, shared environmental influences probably contributed relatively little to the associations between ADHD symptoms and dietary habits. ... significant MZ twin intraplate differences also provided support for a potential causal link between inattention and dietary habits.
Lin Li, Mark J. Taylor, Katarina Bälter, Ralf Kuja-Halkola, Qi Chen, Tor-Arne Hegvik, Ashley E. Tate, Zheng Chang, Alejandro Arias-Vásquez, Catharina A. Hartman, Henrik Larsson, "Attentiondeficit/hyperactivity disorder symptoms and dietary habits in adulthood: A large populationbased twin study in Sweden," American Journal of Medical Genetics (2020) Vol.183, Issue 8, 475-485, https://doi.org/10.1002/ajmg.b.32825.
This study investigates how certain genetic disorders, called RASopathies, affect the structure of the brain in children. RASopathies are conditions caused by mutations in a specific signaling pathway in the body. Two common RASopathies are Noonan syndrome (NS) and neurofibromatosis type 1 (NF1), both of which are linked to a higher risk of autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD).
The researchers analyzed brain scans of children with RASopathies (91 participants) and compared them to typically developing children (74 participants). They focused on three aspects of brain structure: surface area (SA), cortical thickness (CT), and subcortical volumes.
The results showed that children with RASopathies had both similarities and differences in their brain structure compared to typically developing children. They had increased SA in certain areas of the brain, like the precentral gyrus, but decreased SA in other regions, such as the occipital regions. Additionally, they had thinner CT in the precentral gyrus. However, the effects on subcortical volumes varied between the two RASopathies: children with NS had decreased volumes in certain structures like the striatum and thalamus, while children with NF1 had increased volumes in areas like the hippocampus, amygdala, and thalamus.
Overall, this study highlights how RASopathies can impact the development of the brain in children. The shared effects on SA and CT suggest a common influence of RASopathies on brain development, which could be important for developing targeted treatments in the future.
In summary, understanding how these genetic disorders affect the brain's structure can help researchers and healthcare professionals develop better treatments for affected children.
In a recent study, researchers delved into the complex interplay of cognitive processes and eye movements in children with dyslexia and Attention-Deficit/Hyperactivity Disorder. Their findings shed light on predictive models for reading outcomes in these children compared to typical readers.
The study involved 59 children: 19 typical readers, 21 with ADHD, and 19 with developmental dyslexia (DD), all in the 4th grade and around 9 years old on average. Each group underwent thorough neuropsychological and linguistic assessments to understand their psycholinguistic profiles.
During the study, participants engaged in a silent reading task where the text underwent lexical manipulation. Researchers then analyzed eye movement data alongside cognitive factors like memory, attention, and visual processes.
Using multinomial logistic regression, the researchers evaluated predictive models based on three key measures: a linguistic model focusing on phonological awareness, rapid naming, and reading fluency; a cognitive neuropsychological model incorporating memory, attention, and visual processes; and an additive model combining lexical word properties with eye-tracking data, specifically examining word frequency and length effects.
By integrating eye movement data with cognitive factors, the researchers enhanced their ability to predict the development of dyslexia or ADHD, in comparison to typically developing readers. This approach significantly improved the accuracy of predicting reading outcomes in children with learning disabilities.
These findings have profound implications for understanding and addressing reading challenges in children. By considering both cognitive processes and eye movement patterns, educators and clinicians can develop more effective interventions tailored to the specific needs of children with dyslexia and ADHD.
The Study Setup
The researchers recruited children aged 6-12 years diagnosed with ASD and/or ADHD, along with their non-ASD/ADHD siblings and the unrelated non-ASD/ADHD volunteers. The diagnoses were confirmed using standardized assessments like the Autism Diagnostic Observation Schedule-2 (ADOS-2). The study looked at gut microbial diversity using advanced DNA extraction and sequencing techniques, comparing alpha-diversity indices (which reflect the variety and evenness of microbial species within each gut sample) across different groups. They also assessed dietary diversity through standardized questionnaires.
Key Findings
The study included 98 subjects, comprising children with ASD, ADHD, both ASD and ADHD, their non-ASD/ADHD siblings, and the unrelated controls. Here's what they discovered:
What Does This Mean?
The study highlights intriguing connections between gut microbiota and neurodevelopmental disorders like ASD and ADHD. The lower gut microbial diversity observed in children with ASD points towards potential links between gut health and the pathophysiology of ASD. Understanding these connections is crucial for developing targeted therapeutic interventions.
Implications and Future Directions
This research underscores the importance of considering gut microbiota in the context of neurodevelopmental disorders. Moving forward, future studies should account for factors like co-occurrence of ASD and ADHD, as well as carefully control for dietary influences. This will help unravel the complex interplay between gut microbiota, diet, and neurodevelopmental disorders, paving the way for innovative treatments and interventions.
In summary, studies like this shed light on the intricate relationship between our gut health, diet, and brain function. By unraveling these connections, researchers are opening new avenues for understanding and potentially treating conditions like ASD and ADHD.
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