On the Spectrum

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A Prospective Study of Fetal Head Growth in Children, Autistic Traits and Autism Spectrum Disorder Prenatal head growth and autistic traits We examined whether fetal HC growth trajectories were related to later autistic traits (Table 2A). This was addressed in a separate model for each of the cohorts, in which autistic trait scores were regressed on the latent growth parameters of gestational-age-adjusted SD scores of HC. Models were adjusted for sex, ethnicity of the child, maternal educational level, maternal age, maternal alcohol use and maternal smoking during pregnancy. These models had good fit indices: comparative fit index = 0.987 and root mean square error of approximation = 0.021 for the Generation R Study and comparative fit index = 0.966 and root mean square error of approximation = 0.029 for the Raine Study. We found evidence for a consistent negative association of the slope of growth (i.e., growth rate) with autistic traits when the results for both cohorts were pooled (pooled z = -2.20, p = .03). For the Generation R Study, in the fully adjusted model, the intercept and slope of HC growth during pregnancy were negatively associated with autistic traits: children with growth trajectories characterized by a lower slope and intercept had more autistic traits at age 6 (β slope= -0.043, p = .04, β intercept= -0.049, p = .03). For the Raine Study, we found the same direction of effect for the association of the slope of growth with autistic traits, although not statistically significant (β slope= -0.075, p = .41). Since postnatal studies of children with ASD have found both larger and smaller HC, we tested whether the relation between growth and autistic traits was nonlinear. For both studies, the addition of quadratic terms of the growth parameters did not add significantly to the models. In a sensitivity analysis, we assessed whether this effect was specific to HC by examining trajectories of HC-FL difference scores. Results were broadly consistent (pooled z = -2.11, p = .04). In separate cross-sectional analyses for each cohort, HC in mid- and late pregnancy, but not early pregnancy, were related to autistic traits (Table 2B). Pooled results indicate that children with smaller HC in mid- and late pregnancy had higher levels of autistic traits later in life (mid pregnancy: pooled z = -2.19, p = .03, late pregnancy pooled z = -2.11, p =.04). When examining difference scores, results were consistent (pooled z = -2.79, p
Chapter 3 Table 2. Prenatal head growth and autistic traits later in life A. Head growth Generation R Raine (SRS) (AQ) Pooled z-statistic p n = 4,533 n = 1,186 Intercept (SE); p -0.049 (0.023); .03 0.002 (0.043); .96 -1.90 .06 Slope (SE); p -0.043 (0.021); .04 -0.075 (0.090); .41 -2.20 .03 B. Head size Generation R Raine Pooled z-statistic p Early pregnancy n = 3,108 n = 889 B (SE), β -0.024 (0.016),-0.026 0.123 (0.070), 0.059 p .13 .08 -0.51 .61 Mid pregnancy n = 4,329 n = 753 B (SE), β -0.023 (0.014),-0.024 -0.131 (0.077),-0.063 p .10 .09 -2.19 .03 Late pregnancy n = 4,407 n = 662 B (SE), β -0.039 (0.015),-0.038 0.067 (0.074), 0.037 p .01 .36 -2.11 .04 Note: A. Values are standardized regression coefficients from latent growth curve analyses on gestational age adjusted SD scores for head circumference (constructed using growth reference curves). Models were adjusted for age, sex, ethnicity of the child, maternal educational level, maternal age, maternal alcohol and maternal smoking. Fit indices for the Generation R model were RMSEA 0.021 and CFI 0.987. Fit indices for the Raine Study model were RMSEA: 0.029 and CFI 0.966. B. Values are regression coefficients from linear regression analysis of autistic traits on gestational age adjusted SD scores for head size. Models were adjusted for ethnicity of the child, maternal educational level, maternal age, maternal alcohol and maternal smoking. Table 3. Prenatal head growth and ASD A. Head growth Generation R Raine Pooled z-statistic p n ASD/ n controls n ASD/ n controls 75/4,409 15/1,177 Intercept OR (95% CI) 1.04 (0.69; 1.57) 0.76 (0.30; 1.91) P .86 .56 -0.08 .94 Slope OR (95% CI) 1.07 (0.80; 1.44) 0.21 (0.02; 1.90) P .63 .16 0.48 .63 B. Head size Generation R Raine Pooled z-statistic p n ASD/ n controls n ASD/ n controls Early pregnancy 52/3,024 13/881 OR (95% CI) 0.86 (0.66; 1.11) 1.34 (0.43; 4.17) P .25 .61 -0.81 .42 Mid pregnancy 72/4,210 11/745 OR (95% CI) 1.16; (0.92;1.46) 0.62 (0.18; 2.10) P .20 .44 0.91 .36 Late pregnancy 72/4,287 10/656 OR (95% CI) 1.03 (0.81; 1.31) 0.62 (0.19; 2.05) P .81 .43 -0.05 .96 Note: A. Values are standardized Odd’s ratios from latent growth curve analyses of ASD on gestational age adjusted SD scores for head circumference. Regression coefficients and Odd’s ratios are standardized for slope and intercept. Models were adjusted for sex, ethnicity of the child, maternal educational level, maternal age, maternal alcohol and maternal smoking. B. Values are Odds ratio’s from logistic regression analysis of ASD on gestational age adjusted SD scores for head size. Models were adjusted for sex, ethnicity of the child, maternal educational level, maternal age, maternal alcohol and maternal smoking. 68
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On the Spectrum the neurobiology of
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ISBN: 978-94-6233-336-9 © Laura Bl
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PROMOTIECOMMISSIE Promotoren Overig
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MANUSCRIPTS THAT FORM THE BASIS OF
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Chapter 1 10
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Chapter 1 Cuthbert, Garvey, Heinsse
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Chapter 1 folding of the brain into
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6 Cognitive functioning in children
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Chapter 7 ABSTRACT Objectives: In c
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Chapter 7 Next, we examined associa
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Chapter 7 Table 2 Brain morphology
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Chapter 7 Table 3 Cortical thicknes
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Chapter 7 Using empirically defined
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Chapter 7 Fischl, B. and A. M. Dale
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Chapter 7 Supplement Table 1 Brain
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IIIPart III
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Chapter 8 stable relationships, and
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Chapter 8 gyrification changes in p
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Chapter 8 genetic or environmental
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Chapter 8 symptoms could be more sp
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Chapter 8 association of maternal v
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Chapter 8 REFERENCES Abrahams, B. S
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Chapter 8 Goddard, M. N., S. van Ri
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Chapter 8 Sebat, J., B. Lakshmi, D.
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SSummary Samenvatting
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Summary SUMMARY Despite evidence fr
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Summary along a continuum were used
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Samenvatting SAMENVATTING Genetisch
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Addendum Mous SE, Schoemaker NK, Bl
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Addendum Zoeken in andere databases
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Addendum Graag wil ik Dr. Marion Sm
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Addendum hebben. Dank in het bijzon
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On the Spectrum

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