@article {434,
	title = {Genetically informed regression analysis: Application to aggression prediction by inattention and hyperactivity in children and adults},
	journal = {Behavior Genetics},
	volume = {51},
	year = {2021},
	pages = {250{\textendash}263},
	abstract = {<p>We present a procedure to simultaneously fit a genetic covariance structure model and a regression model to multivariate data from mono- and dizygotic twin pairs to test for the prediction of a dependent trait by multiple correlated predictors. We applied the model to aggressive behavior as an outcome trait and investigated the prediction of aggression from inattention (InA) and hyperactivity (HA) in two age groups. Predictions were examined in twins with an average age of 10 years (11,345 pairs), and in adult twins with an average age of 30 years (7433 pairs). All phenotypes were assessed by the same, but age-appropriate, instruments in children and adults. Because of the different genetic architecture of aggression, InA and HA, a model was fitted to these data that specified additive and non-additive genetic factors (A and D) plus common and unique environmental (C and E) influences. Given appropriate identifying constraints, this ADCE model is identified in trivariate data. We obtained different results for the prediction of aggression in children, where HA was the more important predictor, and in adults, where InA was the more important predictor. In children, about 36\% of the total aggression variance was explained by the genetic and environmental components of HA and InA. Most of this was explained by the genetic components of HA and InA, i.e., 29.7\%, with 22.6\% due to the genetic component of HA. In adults, about 21\% of the aggression variance was explained. Most was this was again explained by the genetic components of InA and HA (16.2\%), with 8.6\% due to the genetic component of InA.</p>
},
	keywords = {Aggression, Genetic and environmental prediction, Hyperactivity, Inattention, Regression, Structural equation model},
	doi = {10.1007/s10519-020-10025-9},
	author = {Boomsma, Dorret I and van Beijsterveldt, Toos C E M and Odintsova, Veronika V and Neale, Michael C and Dolan, Conor V}
}
@article {421,
	title = {The (broad-sense) genetic correlations among four measures of inattention and hyperactivity in 12 year Olds},
	journal = {Behavior Genetics},
	volume = {50},
	year = {2020},
	pages = {273{\textendash}288},
	abstract = {<p>We estimated the genetic covariance matrix among four inattention (INATT) and four hyperactivity (HYP) measures in the classical twin design. Data on INATT and HYP symptom counts were obtained in mono- and dizygotic twin pairs (N = 1593) with an average age of 12.2 years (sd = .51). We analyzed maternal ratings of INATT and HYP based on the Conners\&$\#$39; Parent Rating Scale (CPRS), the Strengths and Weaknesses of ADHD-symptoms and Normal-behavior (SWAN), and teacher ratings based on the Conners\&$\#$39; Teacher rating scale (CTRS) and the ASEBA Teacher Rating Form (TRF). Broad-sense heritabilities, corrected for the main effects of sex and for random teacher rater effects, were large (ranging from .658 to .912). The results reveal pervasive and strong broad-sense genetic effects on INATT and HYP phenotypes with the phenotypic covariance among the phenotypes largely due to correlated genetic effects. Specifically between 79.9 and 99.9\% of the phenotypic covariance among the HYP measures, and between 81.0 and 93.5\% of the INATT measures are attributable to broad-sense genetic effects. Overall, the present results, pertaining to the broad-sense heritabilities and shared genetic effects, support the current genome-wide association meta-analytic approach to identifying pleiotropic genetic variants.</p>
},
	keywords = {ADHD, Genetic correlation, Hyperactivity, Inattention, Multivariate genetic model, Twin design},
	doi = {10.1186/s12966-019-0779-4},
	author = {Dolan, Conor V and de Zeeuw, Eveline L and Zayats, Tetyana and van Beijsterveldt, C E M and Boomsma, Dorret I}
}
