Department of Psychiatry, Washington University School of Medicine Stability and Changes in Familial Influences on Attention and Activity during Adolescence: A longitudinal twin study using the SWAN Chun-Zi Peng, ph.D., Julia D. Grant, ph.D., Andrew C. Heath, D.phil., Angela M. Reiersen, M.D., M.P.E., Richard C. Mulligan, Ph.D., Andrey P. Anokh in, Ph.D. Department of Psychiatry, Washington University School of Medicine St Louis, MO 63108

In the general population, 70-85% of children diagnosed with ADHD may continue to have the disorder during adolescence The twin studies indicated: ADHD is highly heritable (60%-90%) The two symptoms (Inattention and Hyperactivity) were affected by different type of genetic influences The heritability estimates were strongly influenced by rater effects and assessment instruments used in the studies Symptomatic end only, non-affected phenotypes largely collapsed into one class qualitative quantitative

The Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale (SWAN) “Listen when spoken to directly” symptomatic ends far below=3 below=2 slightly below=1 Adaptive end slightly above=-1 above=-2 far above=-3 average=0

Twin studies on the SWAN Significant “C” affect found (Hay, Bennett, Levy, Sergeant, & Swanson, 2007) The SWAN captures variance hidden in the “0” ratings of the CBCL (Polderman et al., 2007) No longitudinal genetic study on the SWAN

Table1 Sample characteristics and means of Attention and activity   N % male % MZ ATTa M(SD) ACTb Age 12 434 52.3% 55.3% -0.36 (0.95) -0.50(0.95) Age 14 592 51.3% 46.5% -0.56 (1.08) -0.68(1.09) Age 16 369 52.6% 47.3% -0.81(1.15) -0.96(1.14) note: a all ATT means significantly different from each other, p<0.05; b all ACT means significantly different from each other, p<0.05.

* significant at the 0.05 level. Table2 Cross-age within individual correlations (95% Confidence Interval) for attention(above diagonals) and activity (below diagonals) Age 12 Age 14 Age 16 -- 0.71 (0.66-0.76)* 0.66 (0.56-0.74)* 0.65 (0.59-0.71)* 0.74 (0.68-0.78)* 0.63 (0.53-0.71)* 0.67 (0.60-0.72)* * significant at the 0.05 level.

Table3 Cross-twin correlations (95% Confidence Interval) for Attention and Activity   ATT ACT Age 12 MZ 0.74 (0.64-0.81)* 0.87(0.82-0.91)* DZ 0.01(-0.19-0.21) 0.48 (0.31-0.62)* Age 14 0.77 (0.69-0.83)* 0.88(0.83-0.91)* 0.36(0.22-0.49)* 0.70(0.61-0.77)* Age 16 0.84(0.76-0.89)* 0.94(0.91-0.96)* 0.48(0.31-0.62)* 0.74(0.63-0.82)* Note: MZ: Monozygotic twins; DZ: Dizygotic twins; * correlation is significant at the 0.05 level

FIGURE1 Best fitting linear structural equation model for genetic and environmental determinants of Attention score. Note: Rectangular represent the observed variance for each age. The circles represent the latent factors including additive genetic influences (A12, A14 and A16) and shared environmental influences (C12, C14 and C16). A Simplex model is shown. A Cholesky (triangular decomposition) model is shown for the non-shared environmental effects (E12, E14 and E16)

FIGURE2 Best fitting linear structural equation model for genetic and environmental determinants of Activity score. Note: The rectangular represent the observed variance for each age. The circles represent the latent factors. For Additive genetic influences (A12, A14 and A16), shared environmental influences (C12, C14 and C16) and non-shared environmental effects (E12, E14 and E16), a simplex model is shown.

FIGURE1 Best fitting linear structural equation model for genetic and environmental determinants of Attention score. Note: Rectangular represent the observed variance for each age. The circles represent the latent factors including additive genetic influences (A12, A14 and A16) and shared environmental influences (C12, C14 and C16). A Simplex model is shown. A Cholesky (triangular decomposition) model is shown for the non-shared environmental effects (E12, E14 and E16).

Conclusions ATT and ACT traits measured by SWAN are highly stable phenotypes affected by substantial familial influences Their developmental mechanism consisted of transmission of previously existing genetic effects interacting with new genetic influences The shared environmental influences also contribute to their stability and changes, which highlights the importance of using fully quantitative measure in behavior genetics study