July 4, 2021
Our genes are very important for the development of mental disorders-including ADHD, where genetic factors capture up to 75% of the risk. Until now, the search for these genes had yet to deliver clear results. In the 1990s, many of us were searching for genes that increased the risk for ADHD because we know from twin studies that ADHD had a robust genetic component. Because I realized that solving this problem required many DNA samples from people with and without ADHD, I created the ADHD Molecular Genetics Network, funded by the US NIMH. We later joined forces with the Psychiatric Genomics Consortium (PTC) and the Danish psych group, which had access to many samples.
The result is a study of over 20,000 people with ADHD and 35,000 who do not suffer from it - finding twelve locations (loci) where people with a particular genetic variant have an increased risk of ADHD compared to those who do not have the variant. The results of the study have just been published in the scientific journal Nature Genetics, https://www.nature.com/articles/s41588-018-0269-7.
These genetic discoveries provide new insights into the biology behind developing ADHD. For example, some genes have significance for how brain cells communicate with each other, while others are important for cognitive functions such as language and learning.
Our study used the genome-wide association study (GWAS)methodology because it allowed us to discover genetic loci anywhere on the genome. The method assays DNA variants throughout the genome and determines which variants are more common among ADHDvs. control participants. It also allowed for the discovery of loci having very small effects. That feature was essential because prior work suggested that, except for very rare cases, ADHD risk loci would individually have small effects.
The main findings are:
A) we found 12 loci on the genome that we can be certain harbor DNA risk variants for ADHD. None of these loci were traditional candidate genes' for ADHD, i.e., genes involved in regulating neurotransmission systems that are affected by ADHD medications. Instead, these genes seem to be involved in the development of brain circuits.
B) we found a significant polygenic etiology in our data, which means that there must be many loci(perhaps thousands) having variants that increase the risk for ADHD. We will need to collect a much larger sample to find out which specific loci are involved;
We also compared the new results with those from a genetic study of continuous measures of ADHD symptoms in the general population. We found that the same genetic variants that give rise to an ADHD diagnosis also affect inattention and impulsivity in the general population. This supports prior clinical research suggesting that, like hypertension and hypercholesteremia, ADHD is a continuous trait in the population. These genetic data now show that the genetic susceptibility to ADHD is also a quantitative trait comprised of many, perhaps thousands, of DNA variants
The study also examined the genetic overlap with other disorders and traits in analyses that ask the questions: Do genetic risk variants for ADHD increase or decrease the likelihood a person will express other traits and disorders. These analyses found a strong negative genetic correlation between ADHD and education. This tells us that many of the genetic variants which increase the risk for ADHD also make it more likely that a person will perform poorly in educational settings. The study also found a positive correlation between ADHD and obesity, increased BMI, and type-2 diabetes, which is to say that variants that increase the risk of ADHD also increase the risk of overweight and type-2 diabetes in the population. This work has laid the foundation for future work that will clarify how genetic risks combine with environmental risks to cause ADHD. When the pieces of that puzzle come together, researchers will be able to improve the diagnosis and treatment of ADHD.
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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