February 28, 2021
Behavioral disinhibition is a trait associated with both ADHD and several genes that affect dopamine signaling. Anew study by three American medical researchers set out to examine how threaded risk genes – DRD4 (dopamine 4 receptor density), DAT1 (dopamine 1transporter), and DBH (dopamine beta-hydroxylase) – affect estimated life expectancy in young adulthood.
The method used was a longitudinal study of 131 hyperactive children and 71 matched controls through early adulthood. The original evaluations were done in 1979-1980, when both groups were children in the 4 to 12 age range. They were reevaluated in1987-1988 as adolescents aged 12 to 20. The next follow-up was in 1992-1996 in early adulthood, aged 19 to 25. The final follow-up was in 1998-2004, as adults aged 24 to 32. All agreed to physical examinations that formed the basis for calculating estimated life expectancy using actuarial tables that factor in the effects of smoking, body mass index, alcohol, and other risk factors on expected longevity. Participants also provided blood samples that enabled gene typing.
For the DAT1gene, participants who had the homozygous nine-repeat allele (9/9) had an a five-year reduction in estimated life expectancy relative to those with the ten-repeat allele (10/10). Those with the intermediate (9/10) configuration had a three-year reduction in estimated life expectancy.
For the DBHTaq1 gene, those with a heterozygous (A1/A2) combination had almost a three-year reduction in estimated life expectancy relative to those with homozygous (A1/A1 or A2/A2) configurations.
For DRD4, on the other hand, no significant differences were found for estimated life expectancy.
In a related study, several background traits were found to be significantly predictive of variance in estimated life expectancy. The largest of these was behavioral disinhibition, followed by verbal IQ, self-rated hostility, and a nonverbal fluency test. But no significant differences were found between any of the gene polymorphisms on any of these four measures, indicating that the present gene associations were independent of the background traits.
The researchers next sought to determine which variables used in the estimated life expectancy calculations were associated with the two significant genes. For DBH, one variable stood out. Those with the A1/A2 heterozygous pairings had almost twice the alcohol consumption of those with homozygous pairings (p = 0.023).
For DAT1, two variables stood out. Overall, the 9/9 pairings smoked two and a half times as much as the 10/10 pairings, with the 9/10 pairings midway between the extremes(p = 0.036). They were also 73 percent more likely to be smokers relative to the 10/10 pairings, and 61 percent more likely relative to the 9/10 pairings. They also had significantly less education than the 10/10 pairings, with the 9/10pairings again being intermediate (p = 0.027).
An obvious limitation of the study was its small sample size. The authors cautioned, “our findings should be considered quite preliminary and in need of much greater research before being given much weight in the literature or in public policy.
“With these limitations in mind,” they concluded, “the present study demonstrated that two ADHD risk genes (DBH and DAT1) independently contributed to a reduction in ELE [estimated life expectancy] beyond the second order variables of behavioral disinhibition, IQ, hostility, and nonverbal fluency that contributed in the related study to variation in ELE. The gene polymorphisms seemed to be influencing ELE through their affiliation with first-order or more proximal factors related to ELE such as education, smoking, alcohol use, and possibly exercise.”
Russell A. Barkley, Karen Müller Smith, and MariellenFischer, “ADHD risk genes involved in dopamine signaling and metabolism are associated with reduced estimated life expectancy at young adult follow-up hyperactive and control children,” American Journal of Medical Genetics (2019), DOI: 10.1002/ajmg.b.32711.
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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