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.
There has been consistent evidence of an association between ADHD and subjectively reported sleep problems even in patients not medicated for the disorder. There have also been studies using wrist-worn actigraphy (a wrist watch-like device that measures gross motor activity) and sleep lab-based polysomnography that measure objective sleep parameters.
What has been missing are large population-based cohort studies to explore the prevalence rates of different sleep disorders and medical prescriptions in ADHD.
Methods Used:
Sweden has a single-payer health insurance system and a series of national population registers that track virtually its entire population. Using the Swedish Total Population Register, a local research team created a cohort of all 6,470,658 persons born between 1945 and 2008. They linked this to the Swedish National Patient Register, which includes inpatient hospitalizations from 1975 to 2013, and outpatient specialist diagnoses from 2001 to 2013, to identify diagnoses of sleep disorders. They also linked to the Prescribed Drug Register, covering 2005 to 2013, to identify prescriptions for sleep medications.
Summary of Findings:
Overall, persons with ADHD were eight times more likely to be diagnosed with any sleep disorder relative to normally developing peers. Broken down by age, adolescents with ADHD were 16 times more likely to receive such diagnoses, young adults (18-30) twelve times more likely, children and mid-age adults (31-45) eight times more likely, and older adults six times more likely.
Broken down by specific sleep disorder diagnoses, relative to normally developing peers, persons with ADHD were:
As for sleep medication, relative to normally developing peers, persons with ADHD were:
Conclusion:
The team concluded, “Our findings also suggest that greater clinical attention should be directed towards addressing sleep problems in individuals with ADHD. This entails implementing proactive measures through sleep education programmes and providing both pharmacological and non-pharmacological approaches such as cognitive behavioural therapy and parental sleep training.”
Attention is a critical determinant of academic achievement, influencing domains such as language, literacy, and mathematics. To explore whether physical activity can improve attention in children with ADHD, an international team conducted a meta-analysis of peer-reviewed studies. The goal was to evaluate the impact of various physical activity regimens on attention-related outcomes in this population.
The researchers performed a comprehensive search of the medical literature to identify studies examining the effects of physical activity on attention in schoolchildren with ADHD. They included 10 studies with a total of 474 participants in their meta-analysis. The studies evaluated two main types of physical activity:
Additionally, they examined variations based on the frequency, duration, and type of control groups used in the studies. To assess consistency, they also analyzed heterogeneity (variability of outcomes) and checked for potential publication bias.
Key findings from the meta-analysis include:
The authors concluded that mentally engaging exercise is more effective than aerobic exercise in improving attention problems in schoolchildren with ADHD. Furthermore, higher frequency and longer duration of physical activity do not necessarily yield better outcomes.
This research underscores the importance of tailoring physical activity interventions to emphasize cognitive engagement over intensity or duration. By refining strategies, educators and parents can better support children with ADHD in achieving academic success. But take note: given the results from controlled studies, it seems clear that if there is a positive effect of exercise, it is very small so should not replace standard treatments for ADHD.
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Previous studies have examined how stimulant medications affect the brain in controlled settings, but less is known about their impact in real-world conditions, where children may not always take their medication consistently or may combine it with other treatments. A new study leverages data from the Adolescent Brain Cognitive Development (ABCD) study to explore how real-world stimulant use impacts brain connectivity and ADHD symptoms over two years.
Changes in Brain Connectivity Researchers used brain imaging data from the ABCD study to examine the functional connectivity—communication between brain areas—of six regions within the striatum, a brain area involved in motivation and movement control. They focused on how stimulant use influenced connectivity between the striatum and other networks involved in executive functioning and visual-motor control.
The study found that stimulant exposure was linked to reduced connectivity between key striatal areas (such as the caudate and putamen) and large brain networks, including the frontoparietal and visual networks. These changes were more pronounced in children taking stimulants compared to those who were not medicated, as well as compared to typically developing children. Importantly, this reduction in connectivity seemed to regulate certain brain networks that are typically altered in children with ADHD.
Symptom Improvement In addition to brain changes, 14% of children taking stimulants experienced a significant reduction in ADHD symptoms over the two-year period. These children showed the strongest connectivity reductions between the right putamen and the visual network, suggesting that stimulant-induced connectivity changes may contribute to improvements in visual attentional control, which is a common challenge for children with ADHD.
Why This Matters This study is one of the first to examine how stimulant use in real-world conditions affects brain networks in children with ADHD over time. The findings suggest that stimulants may help normalize certain connectivity patterns associated with ADHD, particularly in networks related to attention and control. These insights could help clinicians better understand the potential long-term effects of stimulant treatment and guide personalized approaches to ADHD management.
Conclusion Stimulant medications appear to alter striatal-cortical connectivity in children with ADHD, with some changes linked to symptom improvement. This research highlights the potential for stimulant medications to impact brain networks in ways that support attention and control, highlighting the importance of understanding how real-world medication use influences ADHD treatment outcomes.
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