Patterns and Strength of Familial Aggregation of ADHD
Dinko Kranjac, PhD, Medical Editor
August 24, 2016
In the largest longitudinal study to date, Swedish researchers affiliated with the Karolinska Institutet and Örebro University showed that familial aggregation of attention deficit hyperactivity disorder (ADHD) increases significantly along with increasing genetic relatedness. These new findings were published in The Journal of Child Psychology and Psychiatry.
The available data indicate that ADHD is one of the most prevalent developmental disorders, and that approximately 11% of children 4-17 years of age (6.4 million) have been diagnosed with ADHD in 2011. It is well established that boys are more likely than girls (13% vs. 6%) to receive the diagnosis.
In the current nation-wide cohort study, investigators identified relative pairs of twins, full and half siblings, and full and half cousins who were born in Sweden between 1985 and 2006 in order to estimate the strength and pattern of the familial aggregation of ADHD in a large, population-based family sample.
“While twin studies have repeatedly reported high heritability estimate of 70% to 80% for ADHD and the significance of both additive genetic and non-shared environmental factors to the phenotypic variance in ADHD, the relative importance of shared environmental factors on the variance remains under debate,” the authors noted in their publication.
Investigators linked 3 different registers (The Medical Birth Register, The Multi-Generation Register, and The Swedish Twin Register) in order to identify monozygotic twin pairs (n=8 618), dizygotic twin pairs (n=26 458), non-twin full-sibling pairs (n=2 030 117), maternal half siblings (n=315 267), paternal half siblings (n=312 593), full cousin pairs (n=4 612 179), and half cousin pairs (n=958 457).
They used the Swedish National Patient Register, the Prescribed Drug Register, and the Clinical Database for Child and Adolescent Psychiatry in Stockholm in order to identify individuals diagnosed with ADHD (31 865 individuals were diagnosed during the follow-up).
Researchers estimated the cumulative incidence of ADHD up to 20 years of age in all siblings and all cousins, and measured the strength of familial aggregation of ADHD by using hazard ratios (ie, the rate of ADHD in relatives of persons affected by ADHD compared with the rate of ADHD in relatives of persons not affected by ADHD). They included the following covariates in their analyses: birth year, sex, maternal and paternal age at childbirth, and maternal and paternal psychiatric history.
Findings indicate that, “For siblings and cousins of ADHD-affected index persons, the cumulative incidences of ADHD diagnosis at age 20 were 25.3% and 10%, respectively.”
With regard to the strength of the familial aggregation of ADHD among relatives of varying degrees of genetic relatedness (GR), birth year-adjusted hazard ratios (HR) were estimated to be: [monozygotic twins, GR=100%, HR=70.45 (95% CI=38.19-129.96); dizygotic twins, GR=50%, HR=8.44 (95% CI=5.87-12.14); full siblings, GR=50%, HR=8.27 (95% CI=7.86-8.70); maternal half siblings, GR=25%, HR=2.86 (95% CI=2.61-3.13); paternal half siblings, GR=25%, HR=2.31 (95% CI=2.07-2.58); full cousins, GR=12.5%, HR=2.24 (95% CI=2.11-2.38); and, half cousins, GR=6.25%, HR=1.47 (95% CI=1.35-1.61)].
“Indeed, our finding that the familial aggregation was significantly higher in maternal half-siblings than in paternal half-siblings suggests that part of the familial aggregation was due to shared environmental factors,” and “This is because the two types of half-siblings are equivalent in their genetic sharing, but maternal half-siblings tend to share more environmental factors related to pregnancy, including intrauterine environment and perinatal conditions,” investigators mentioned.
In order to examine the relative importance of genetic and environmental components to the burden ofADHD, investigators used decomposition methods to “decompose the variance in the liability to ADHD into additive genetic, dominant genetic, shared environmental, and non-shared environmental components.”
It is worth noting here that decomposition method is an econometric technique that is commonly used to examine wage differentials between men and women. This approach allows researchers to better understand intergroup differences (eg, rate of labor force participation for women versus men) by identifying the sources of the gap in wage earnings. In this example, the purpose of this technique is to explain the distribution of wages by a set of factors that vary systematically between men and women (eg, differences between men and women’s career choices, work experience, labor force participation, etc.).