March 16, 2024
A Swedish-Danish-Dutch team used the Swedish Medical Birth Register to identify the almost 1.7 million individuals born in the country between 1980 and 1995. Then, using the Multi-Generation Register, they identified 341,066 pairs of full siblings and 46,142 pairs of maternal half-siblings, totaling 774,416 individuals.
The team used the National Patient Register to identify diagnoses of ADHD, as well as neurodevelopmental disorders (autism spectrum disorder, developmental disorders, intellectual disability, motor disorders), externalizing psychiatric disorders (oppositional defiant and related disorders, alcohol misuse, drug misuse), and internalizing psychiatric disorders (depression, anxiety disorder, phobias, stress disorders, obsessive-compulsive disorder).
The team found that ADHD was strongly correlated with general psychopathology overall (r =0.67), as well as with the neurodevelopmental (r = 0.75), externalizing (r =0.67), and internalizing (r = 0.67) sub factors.
To tease out the effects of heredity, shared environment, and non-shared environment, a multivariate correlation model was used. Genetic variables were estimated by fixing them to correlate between siblings at their expected average gene sharing (0.5for full siblings, 0.25 for half-siblings). Non-genetic environmental components shared by siblings (such as growing up in the same family) were estimated by fixing them to correlate at 1 across full and half-siblings. Finally, non-shared environmental variables were estimated by fixing them to correlate at zero across all siblings.
This model estimated the heritability of the general psychopathology factor at 49%, with the contribution of the shared environment at 7 percent and the non-shared environment at 44%. After adjusting for the general psychopathology factor, ADHD showed a significant and moderately strong phenotypic correlation with the neurodevelopmental-specific factor (r = 0.43), and a significantly smaller correlation with the externalizing-specific factor (r = 0.25).
For phenotypic correlation between ADHD and the general psychopathology factor, genetics explained 52% of the total correlation, the non-shared environment 39%, and the shared familial environment only 9%. For the phenotypic correlation between ADHD and the neurodevelopmental-specific factor, genetics explained the entire correlation because the other two factors had competing effects that canceled each other out. For the phenotypic correlation between ADHD and the externalizing-specific factor, genetics explained 23% of the correlation, shared environment 22%, and non-shared environment 55%.
The authors concluded that "ADHD is more phenotypically and genetically linked to neurodevelopmental disorders than to externalizing and internalizing disorders, after accounting for a general psychopathology factor. ... After accounting for the general psychopathology factor, the correlation between ADHD and the neurodevelopmental-specific factor remained moderately strong, and was largely genetic in origin, suggesting substantial unique sharing of biological mechanisms among disorders. In contrast, the correlation between ADHD and the externalizing-specific factor was much smaller and was largely explained by-shared environmental effects. Lastly, the correlation between ADHD and the internalizing subfactor was almost entirely explained by the general psychopathology factor. This finding suggests that the comorbidity of ADHD and internalizing disorders are largely due to shared genetic effects and non-shared environmental influences that have effects on general psychopathology."
Ebba Du Rietz, Erik Pettersson, Isabell Brickell, LauraGhirardi, Qi Chen, Catharina Hartman, Paul Lichtenstein, Henrik Larsson, and Ralf Kuja-Halkola, "Overlap between attention-deficit hyperactivity disorder and neurodevelopmental, externalizing and internalizing disorders: separating unique from general psychopathology effects," British Journal of Psychiatry (2020),https://doi.org/10.1192/bjp.2020.152.
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.
A commonly reported risk associated with ADHD medication is reduced growth in height. But studies to date have generally not adequately described or measured possible confounders, such as genetic factors, prenatal factors, or socioeconomic factors. What if ADHD were associated with reduced height even in the absence of medications?
An international study team explored this question by performing a nationwide population study comparing data from before (1968-1991) and after (1992-2020) the adoption of stimulant therapy for ADHD in Sweden.
The country’s single-payer health insurance system that connects patient records with all other national registers through unique personal identification numbers makes such analysis possible. Sweden also has military service conscription, which records the heights of 18-year-old males.
The participants were all 14,268 Swedish males with a diagnosis of ADHD who were drafted into military service at any time from 1968 through 2020.
Up to five non-ADHD controls were identified for each ADHD case, matched by sex (they had to be male), birth year, and county. The total number of controls was 71,339.
Among 34,586 participants in the period before adoption of stimulant medications (1968-1991), those diagnosed with ADHD had roughly 30% greater odds of being shorter than normal (166-172 vs. 173-185 cm) than typically developing controls. That dropped to 20% greater odds among the 34,714 participants in the cohort following adoption of stimulant medications.
The odds of those diagnosed with ADHD being much shorter than normal (150-165 vs. 173-185 cm) remained identical (about 55% greater) among the almost 30,000 participants in both cohorts.
In other words, there was no increase in the odds of ADHD individuals being shorter than normal after adoption of stimulant therapy in Sweden compared with before such adoption.
Furthermore, after adjusting for known confounders, including birth weight, inflammatory bowel disease, celiac disease, hypothyroidism, anxiety disorders, depression, substance use disorder, and highest parental education, the odds of those diagnosed with ADHD being shorter than normal or much shorter than normal in the 1992-2020 cohort dropped to roughly 10% and 30% greater, respectively.
Could it be the disorder itself rather than stimulant treatment that is associated with reduced height in individuals diagnosed with ADHD?
To address effects of environmental and familial/genetic confounding, the team then compared the entire cohort of males diagnosed with ADHD from 1968 through 2020 with typically developing male relatives, ranging from first cousins to full siblings.
Among full siblings, the odds of those with ADHD diagnoses being shorter (over 90,000 participants) or much shorter (over 77,000 participants) were a statistically significant 14% and 18%, respectively.
The authors concluded, “Our findings suggest that ADHD is associated with shorter height. On a population level, this association was present both before and after ADHD-medications were available in Sweden. The association between ADHD and height was partly explained by prenatal factors, psychiatric comorbidity, low SES [socioeconomic status] and a shared familial liability for ADHD.”
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