July 4, 2021

Researchers have found the first risk genes for ADHD

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.

Related posts

No items found.

Understanding Attention to Social Images in Children with ADHD and Autism

NEWS TUESDAY: Understanding Attention to Social Images in Children with ADHD and Autism

In the field of mental health, professionals often use a variety of tools to diagnose and understand neurodevelopmental disorders such as Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). One such tool is the Autism Diagnostic Observation Schedule (ADOS), which is specifically designed to help diagnose autism. However, the ADOS wasn't originally intended for children who have both autism and ADHD, though this comorbidity is not uncommon.

A recent study aimed to explore how children with ADHD, autism, or both, pay attention to social images, such as faces. The study focused on using eye-tracking technology to measure where children direct their gaze when viewing pictures, and how long they look at certain parts of the image. This is important because differences in visual attention can provide insights into the nature of these disorders.

The researchers included 84 children in their study, categorized into four groups: those with ASD, those with ADHD, those with both ASD and ADHD, and neurotypical (NT) children without these conditions. During the study, children were shown social scenes from the ADOS, and their eye movements were recorded. The ADOS assessment was administered afterward. To ensure that the results were not influenced by medications, children who were on stimulant medications for ADHD were asked to pause their medication temporarily.

The results of the study showed that children with ASD, whether they also had ADHD or not, tended to spend less time looking at faces compared to children with just ADHD or NT children. The severity of autism symptoms, measured by the Social Communication Questionnaire (SCQ), was associated with reduced attention to faces. Interestingly, ADHD symptom severity, measured by Conners' Rating Scales (CRS-3), did not correlate with how children looked at faces.

These findings suggest that measuring visual attention might be a valuable addition to the assessment process for ASD, especially in cases where ADHD is also present. The study indicates that if a child with ADHD shows reduced attention to faces, it might point to additional challenges related to autism. The researchers noted that more studies with larger groups of children are needed to confirm these findings, but the results are promising. They hope that such measures could eventually enhance diagnostic processes and help in managing the complexities of cases involving comorbidity of ADHD and ASD.

This research opens up the possibility of using eye-tracking as a supplementary diagnostic tool in the assessment of autism, providing a more nuanced understanding of how attentional differences in social settings are linked to ASD and ADHD.

May 14, 2024

NEW STUDY: RASopathies Influences on Neuroanatomical Variation in Children

NEW STUDY: RASopathies Influences on Neuroanatomical Variation in Children

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.

April 30, 2024

News Tuesday: Integrating Cognition and Eye Movement

Integrating Cognitive Factors and Eye Movement Data in Reading Predictive Models for Children with Dyslexia and ADHD-I

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.

April 30, 2024