University of Groningen Gene-environment interactions on the course of Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms Brinksma, Djûke Maaike

Gene-environment interactions on the course of Attention-Deficit/Hyperactivity Disorder

(ADHD) symptoms

Brinksma, Djûke Maaike

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Brinksma, D. M. (2018). Gene-environment interactions on the course of Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms: From early into late adolescence. Rijksuniversiteit Groningen.

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Chapter 3

Parental rejection in early adolescence

predicts a persistent ADHD symptom

trajectory across adolescence

Djûke M. Brinksma Pieter J. Hoekstra Barbara van den Hoofdakker

Annelies De Bildt Jan. K. Buitelaar Catharina A. Hartman

& Andrea Dietrich

ABSTRACT

Background

Despite a general decrease of Attention-Deficit/Hyperactivity Disorder (ADHD) symp-toms during adolescence, these may persist in some individuals but not in others. Cross-sectional studies showed that parenting style and their interaction with candidate genes are associated with ADHD symptoms. However, little is known about the relation of parenting style to the course of ADHD symptoms across adolescence.

Methods

Here we investigated perceived parenting style (i.e., rejection, overprotection, and emotional warmth) at the age of 11, and their interaction with ADHD candidate genes (i.e., DRD4, MAOA, and 5-HTTLPR) on parent-reported ADHD symptoms at three time points (mean ages 11.1, 13.4, and 16.2 years) in 1,730 adolescents from the TRacking Adolescents’ Individual Lives Survey (TRAILS).

Results

Growth Mixture Modeling in Mplus identified four ADHD symptom trajectories: low stable, moderate stable, high decreasing, and high persistent. Perceived parental rejec-tion predicted class membership in the high persistent trajectory compared to the other classes (p = .002, odds ratios between 1.75-3.74). Gene-environment interactions were not significantly related to class membership.

Conclusions

Our results indicate a role of perceived parental rejection in the persistence of ADHD symptoms. Perceived parental rejection should therefore be taken into consideration during prevention and treatment of ADHD in young adolescents.

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INTRODUCTION

Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood-onset disorder with core symptoms of inattention and hyperactivity/impulsivity (American Psychiatric As-sociation, 2013), which may persist into adulthood (Faraone, Biederman, & Mick, 2006; Faraone et al., 2015). ADHD symptoms vary along a continuum, with symptoms in the non-clinical range at the lower end and severe symptoms in the clinical range at the upper end (El-Sayed, Larsson, Persson, Santosh, & Rydelius, 2003; Greven et al., 2016) which have been suggested to share the same etiology (Levy, Hay, McStephen, Wood, & Waldman, 1997). Although ADHD symptoms tend to decrease during adolescence (Biederman, Mick, & Faraone, 2000), the course of symptoms differs between individuals. Various symptom trajectories have been described across adolescence, in clinical and population samples, mostly including a low stable and a high persistent trajectory (e.g., Döpfner et al., 2015; Musser, Karalunas, Dieckman, Peris, & Nigg, 2016; Tandon, Tillmann, Argrawal, & Luby, 2016). However, it remains unclear which factors characterize adoles-cents who remit versus those who have a more persistent course of ADHD symptoms in the transition towards adulthood. Here we focus on the role of parenting style and ADHD candidate genes on the course of ADHD symptoms across adolescence.

Negative parenting styles were cross-sectionally associated with ADHD symptoms in childhood and adolescence; examples are maternal overprotection and control (Gau & Chang, 2013), parental rejection (Kim & Yoo, 2013), as well as high levels of inconsistent parental discipline and low levels of parental involvement (Cussen, Sciberras, Ukou-menne, & Efron, 2012; Ellis & Nigg, 2009). Moreover, parental criticism (Musser et al., 2016), low parental emotional support and intellectual stimulation (Jester et al., 2005), and inconsistent discipline (Sasser, Kalvin, & Bierman, 2016) have been found in rela-tion to trajectories of persistently high ADHD symptom levels from childhood into late adolescence. In contrast, positive parenting (i.e., appropriate parental involvement) has been found to prospectively predict reduced levels of ADHD symptoms at 1-year follow-up in early childhood (Hawes, Dadds, Frost, & Russel, 2013). Also, two longitudinal stud-ies showed that higher levels of parental warmth were related to reduced rates of ADHD over time (Richards et al., 2014; Santesteban-Echarri et al., 2017). Currently, associations of other parenting styles such as parental rejection and overprotection with ADHD symptom trajectories across adolescence remain unclear. A better understanding of the role of perceived negative parenting, such as parental rejection and overprotection or low emotional warmth, as well as of positive parenting, such as high emotional warmth, in relation to the course of ADHD symptoms may help promote youth development.

Moreover, the influence of parenting styles on ADHD symptoms may depend on the adolescent’s genotype, whereby genes influence sensitivity to both supportive as well as adverse environments (Bakermans-Kranenburg & Van IJzendoorn, 2011; Pluess & Belsky,

2010). Cross-sectional support has been found for gene-environment (G×E) interactions between the 7-repeat allele of the dopamine D4 receptor gene (DRD4) and parenting factors (e.g., consistent parenting, sensitive maternal care) in association with ADHD or externalizing symptoms, for better and/or for worse (i.e., positive parenting in those with the 7-repeat allele was associated with fewer symptoms and negative parenting with more symptoms; Bakermans-Kranenburg & Van IJzendoorn, 2006; Janssens et al., 2017; Martel et al., 2011). Similarly, longitudinal studies showed that individuals carrying the

DRD4 7-repeat allele had fewer ADHD symptoms in childhood (Berry, Deater-Deckard,

McCartney, Wang, & Petrill, 2013) and adolescence (Nikitopoulos et al., 2014) when they had experienced higher levels of sensitive and stimulating maternal care in infancy and early childhood, while higher levels of symptoms were found in the face of lower early maternal sensitive care (Berry et al., 2013; Nikitopoulos et al., 2014; see also Windhorst et al., 2015). In relation to parenting and ADHD the literature also suggests a role for the high activity monoamine oxidase A (MAOA) genotype, i.e., negative parenting predicted inattention symptoms only among boys with high-activity MAOA (Li & Lee, 2012); and for the low activity serotonin transporter (5-HTTLPR) genotype, i.e., family conflict predicted inattention symptoms only in those with low activity 5-HTTLPR (Elmore, Nigg, Friderici, Jernigan, & Nikolas, 2016).

In the present study, we investigated whether perceived parenting styles (i.e., rejec-tion, overprotecrejec-tion, and emotional warmth), assessed during early adolescence, would predict different ADHD symptom trajectories across early, middle, and late adolescence, in a large pooled population and clinic-referred cohort. We expected that class member-ship in disadvantageous ADHD symptom trajectories (e.g., high persistent) would be predicted by a higher level of perceived parental rejection and/or overprotection, or a lower level of perceived emotional warmth; whereas we expected a reverse pattern for membership in a more favorable trajectory (e.g., low stable, remitting). As a second aim, we explored the role of the ADHD candidate genes DRD4, MAOA, and 5-HTTLPR in interaction with perceived parenting as a predictor of ADHD symptom trajectories.

METHODS

Sample

Our study included 1,730 adolescents assessed at early (T1; Mage = 11.1, range

10.0-12.6), middle (T2; Mage = 13.4, range 11.6-15.1), and late adolescence (T3; Mage = 16.2,

range 14.4-18.4) as part of the population-based and clinic-referred cohort Tracking Adolescents’ Individual Lives Survey (TRAILS). TRAILS is a prospective cohort study of Dutch adolescents with the aim to chart and explain the development of mental health from early adolescence into adulthood, both at the level of psychopathology and the

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comprised young adolescents from five municipalities in the north of the Netherlands, including urban and rural areas. The inclusion of the clinic-referred cohort, which started two years later, was based on referral to a child and adolescent psychiatric outpatient clinic in the Northern Netherlands. About 20.8% had been referred at age ≤ 5 years, 66.1% between age 6 and 9 years, and 13.1% between age 10 and 12 years. The sam-pling procedures, descriptive statistics, and response rates of both cohorts have been well-documented elsewhere (Oldehinkel et al., 2015; De Winter et al., 2005).

At T1 the total sample consisted of 2,773 adolescents from the population-based (n = 2,230) and clinic-referred cohort (n = 543), with retention rates for both cohorts over 80% at T2 and T3. For the present study only participants with complete genetic data on the DRD4, MAOA, and 5-HTTLPR genotypes were included (n = 1,761) in the analyses. Subsequently, subjects were excluded if there was no information available on perceived parenting (n = 10) or ADHD symptoms (n = 21). The final sample consisted of 1,730 adolescents of which 1,364 adolescents (78.8% of the final sample; 89.6% Dutch ancestry) were from the population-based cohort and 366 adolescents (21.2% of the final sample; 98.6% Dutch ancestry) from the clinic-referred cohort.

Measures

ADHD symptoms. At all three waves, the DSM 5-Oriented subscale Attention-Deficit/

Hyperactivity Problems of the Child Behavioral Checklist (Achenbach, 1991; Verhulst & Achenbach, 1995) consisting of 7 items (3 inattention and 4 hyperactivity-impulsivity items) was used to measure ADHD symptoms. Items were scored on a 3-point Likert-scale ranging from 0 (‘not true’) to 2 (‘very true or often true’). The DSM-oriented subLikert-scale of the CBCL has shown good reliability as well as convergent and discriminative validity in adolescents (Nakamura, Ebesutani, Bernstein, & Chorpita, 2009). For descriptive pur-poses of ADHD symptom trajectories, ASEBA cut-off scores (Achenbach & Rescorla, 2001) were used to categorize adolescents with clinical (>P97), subclinical (between P90-P97), and normal (<P90) ADHD symptom levels. For adolescents of the clinic-referred cohort also information on a life-time diagnosis of ADHD based on the Diagnostic Interview Schedule for Children (DISC-IV parent version; Shaffer, Fisher, Lucas, Dulcan, & Schwab-Stone, 2000) was available.

Perceived parenting. At T1, adolescent’s perception of parental rearing were

as-sessed with the short version of the Egna Minnen Beträffande Uppfostran (My Memories of Upbringing) for Children [EMBU-C; Markus, Lindhout, Boer, Hoogendijk, & Arrindell, 2003; Veenstra, Lindenberg, Oldehinkel, De Winter, & Ormel, 2006). The 47 items were scored on a 4-point Likert-scale ranging from 1 (‘no, never’) to 4 (‘yes, almost always’) separately for perceived father and mother rearing style. The rejection scale included 12 questions about hostility, punishment, and blaming the child (5 of the originally

17 questions were excluded due to low loadings, see Oldehinkel, Veenstra, Ormel, De Winter, & Verhulst, 2006; Cronbach’s α = 0.84). The overprotection scale comprised 12 items about fearfulness and anxiety for the child’s safety, and intrusiveness (Cronbach’s

α = 0.90). The 18 items of the emotional warmth scale refer to giving special attention,

praise, and unconditional love (Cronbach’s α = 0.94). Since the answers for both parents were highly correlated (r = 0.81 for rejection, r = 0.64 for overprotection, and r = 0.77 for emotional warmth) we computed a single mean score as in previous TRAILS studies (e.g., Marsman, Oldehinkel, Ormel, & Buitelaar, 2013).

Genotyping. DNA was extracted from blood samples (n = 1,443) or buccal swabs

with a Cytobrush (n = 287) using a manual salting out procedure as described by Miller, Dykes, and Polesky (1988) and was collected at T2 for the clinic-referred cohort and at T3 for the population-based cohort. Genotyping of the length polymorphisms DRD4,

MAOA, HTTLPR, and SNP rs25331 (A/G SNP in L HTTLPR) was done at the Research lab for

Multifactorial Diseases within the Human Genetics department of the Radboud Univer-sity Nijmegen Medical Centre in Nijmegen, The Netherlands. Genotyping of the HTTLPR polymorphism in the promoter region of SLC6A4 (5-HTT, SERT) gene was performed by simple sequence length analysis. Call rate was 91.6%. A custom-made TaqMan assay (Ap-plied Biosystems) was utilized to genotype the single nucleotide substitution (A to G), which is present in the HTTLPR long (l) allele (rs25531). Call rate was 96.5%. Concordance between DNA replicates showed an accuracy of 100%. All lg alleles were recoded into S, because it has been shown that this polymorphism represents low serotonin expres-sion comparable to the S allele (Hu et al., 2006), while la was recoded as L. Based on these alleles, we will refer to the functionality of the expressed transporter; low (SS), intermediate (LS), and high (LL).

The 48 bp direct repeat polymorphism in exon 3 of DRD4 was genotyped on the Illumina BeadStation 500 platform (Illumina.). Three percent blanks and duplicates between plates were taken along as quality controls during genotyping. Determination of the length of the alleles was performed by direct analysis on an automated capillary sequencer (ABI3730, Applied Biosystems, Nieuwerkerk a/d IJssel, The Netherlands) using standard conditions. Call rate for DRD4 was 99.4%.

The 30bp variable number of tandem repeat polymorphism (called MAOA-LPR or

MAOA-uVNTR) was also genotyped on the Illumina BeadStation 500 platform. Three

percent blanks as well as duplicates between plates were taken along as quality controls during genotyping. Call rate was 100% for MAOA. All polymorphisms were well within Hardy-Weinberg equilibrium (HWE; p values ranged from 0.77 to 0.87).

Genotype model. Based on previous G×E research examining differential susceptibil-ity (Belsky & Pluess, 2009), we considered the 7-repeat of DRD4, the low expression of

5-HTTLPR, and the low activity alleles of MAOA as plasticity alleles for our G×E analyses.

classifica-3

MAOA is X-linked. Based on previous findings (Reif et al., 2014), heterozygous females

carrying at least one long allele (3.5, 4, or 5 repeats; Deckert et al., 1999) were catego-rized in the high transcription group.

Covariates. Sex (0 = female, 1 = male), age at T1 in years, socio-economic status (SES;

0 = high, 1 = intermediate, 2 = low), Dutch ancestry (0 = both parents born in the Neth-erlands, 1 = at least one parent not born in the Netherlands), and ADHD medication use (methylphenidate, dexamphetamine, and atomoxetine; 0 = no use, 1 = use at any time in preceding year at T1, T2, or T3), and two genetic principal component analysis scores to correct for genetic population stratification were used as covariates. SES was based on five indicators (professional occupation and educational attainment for both father and mother, and household income), and thereafter divided into three groups: low (< 25%), medium (25%-75%), and high (>75%; following other TRAILS-articles such as Creemers and colleagues, 2011).

Statistical Analyses

Descriptive statistics and intercorrelations among variables were examined using SPSS for Windows (Version 24.0). Due to the relatively low number of missing data (ranging from 0 to 2.3%) and to avoid the limitation of Multiple Imputation which does not give pooled results of the omnibus test, we performed the Expectation Maximization algorithm in SPSS (Tabachnick & Fidell, 2001). We conducted Growth Mixture Modeling (GMM) analyses using Mplus Version 6.12 (Muthén & Muthén, 1998-2010) to deter-mine groups with distinct longitudinal trajectories (i.e., latent classes). GMM analyses identify multiple classes with distinct developmental trajectories, while allowing for within-group heterogeneity in initial ADHD symptom levels and longitudinal change in ADHD symptoms, which facilitates a realistic representation of complex data (Muthén, 2006). To account for the non-normal distribution of the ADHD symptoms, we used the MLR estimator (Muthén & Muthén, 1998-2010). To decide upon the optimal number of latent classes we used the Bayesian Information Criterion (BIC; Schwartz, 1978), and the Lo-Mendell-Rubin adjusted Likelihood Ratio Test (aLRT; Lo, Mendell, & Rubin, 2001). For the BIC, a lower value represents a better fitting model, taking into account increased model complexity. A significant aLRT test result indicates that a model with k classes is better than a model with k-1 classes. Despite the use of these fit indices as a guide to identify the number of classes, the substantive and theoretical meaning of the classes is also important. In addition, we evaluated entropy with values approaching 1 indicating a clear separation between the latent classes.

Next, separate multinomial logistic regression analyses were performed in SPSS to investigate whether perceived parenting (i.e., rejection, overprotection, and emotional warmth) as well as their interactions with the three plasticity genes (i.e., DRD4, MAOA,

and 5-HTTLPR) predicted adolescent’s class membership in ADHD symptom trajectories. We investigated (1) all perceived parenting styles in one model given their inter-correlations, and (2) their G×E’s per plasticity gene in three separate models on ADHD symptom trajectories across adolescence. We provide estimates (odds ratio’s, including 95% confidence intervals) of the included predictors, adjusted for all covariates. The significance level corrected for multiple comparisons regarding the overall effect (i.e., likelihood ratio tests) of our predictors of interest was p < 0.004 (0.05/12, i.e., three main parenting factors plus 3x3 G×E’s); for the remaining analyses we used a p-value of .05. Finally, all results with and without Expectation Maximization were checked with no notable change in findings or conclusions. Of note, to adjust for the potential effects of covariates, we included all covariates×G, and covariates×E interaction terms in the G×E models (Keller, 2014).

Two sensitivity analyses were performed to check whether the findings were due to methodological choices. First, we investigated the perceived parenting styles separately to find out whether they were potentially overruled by the other parenting styles in the model (e.g., that negative parenting styles may be more important predictors than posi-tive parenting). Second, we reran the analyses with conduct problems covarying at T1 to investigate whether results were explained by comorbid conduct problems as measured by the DSM-oriented subscale of the CBCL using median split to avoid multicollinearity.

RESULTS

ADHD Symptom Trajectories

A four-class solution fitted best to the data (Loglikelihood = -1580.40, BIC = 3287.54, aLRT = 71.47, p = .02) as the BIC was smaller than that of the two-class (Loglikelihood = -1696.90, BIC = 3475.82, aLRT = 307.78, p < .001) and three-class solutions (Loglikeli-hood = -1617.72, BIC = 3339.83, aLRT = 151.58, p < .001). The five-class model did not converge without adjusting the model by constraining variances, therefore it was not possible to compare it with the four-class solution.

The ADHD symptom trajectories are shown in Figure 1. The low stable class consisted of participants with consistently low ADHD symptoms throughout adolescence (59.0%,

n = 1.021; Intercept: M = .35, SE = .02, p < .001; Linear Slope: M = -.08, SE = .01, p < .001).

The moderate stable class showed stable, moderately severe ADHD symptoms across adolescence (19.1%, n = 331; Intercept: M = 0.76, SE = .08, p < .001; Linear Slope: M = -.001, SE = .04, p = .97). Two classes presented with high initial levels of ADHD symptoms; one with high decreasing levels (10.6%, n = 183; Intercept: M = 1.28, SE = .90, p < .001; Linear Slope: M = -.33, SE = .05, p < .001), and one with stable, high persistent (11.3%, n =

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across adolescence.

Chapter 3: Figure 1

Figure 1. Graphical presentation of the estimated trajectories of attention-deficit/hyperactivity disorder

(ADHD) symptoms from early (T1) to late (T3) adolescence using Growth Mixture Modeling analyses, ad-justed for sex, Dutch ancestry, socio-economic status, and ADHD medication use.

Sample Characteristics

Correlations between study variables in the total study sample are presented in Table 1. Table 2 shows significant differences between the ADHD symptom trajectories in the main study variables and the covariates age, sex, Dutch ancestry, SES, and ADHD medication use between members of the various ADHD symptom trajectories. Table 3 details the genotypic distribution of all examined plasticity genes of which MAOA dif-fered between the classes. There were no significant G×E interactions (p-values ranging from .10 to .84).

Table 1 Descriptive statistics and inter-correlations between study variables in the total sample (n = 1,730)

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13

1. Age T1

-2. Sexa _.03

-3. Dutch ancestrya,b _{-.04 .02} -4. SESa,c _{-.03 -.02 -.05*} -5. ADHD medicationa,d _{.02 .16** .07** .08**} -6. Rejectione _{-.03 .14** .03 .06* .13**} -7. Overprotectione _{-.02 .05* -.11** .08** .09** .44**} -8. Emotional warmthe _{.02 -.13** -.02 -.12** -.04 -.33** .19**} -9. DRD4f _{.01 .05* -.01 .01 -.03 -.02 -.02 .02} -10. 5-HTTLPRf _{.01 -.03 .05 -.02 -.03 -.02 -.02 -.01 -.01} -11. MAOAf _{-.02 -.24** .004 .02 -.03 -.02 -.04 -.01 -.03 .004} -12. ADHDg _{T1 .01 .22** .01 .23** .41** .24** .12** -.15** -.01 -.04 -.09**} -13. ADHDg_{T2 .02 .20** .04 .19** .44** .22** .10** -.15** .002 -.04 .08** .81**} -14. ADHDg _{T3 -.002 .20** .06* .16** .46** .22** .11** -.13** -.02 -.04 -.07** .72** .78**}

Note. ADHD = Attention-Deficit/Hyperactivity Disorder symptoms, SES = Socio-Economic Status, DRD4 =

dopamine D4 receptor, 5-HTTLPR = serotonin transporter, MAOA = monoamine oxidase A

a _{The zero-coded categories (i.e., females, adolescents from Dutch ancestry, high socio-economic status,} non-users of ADHD medication) were used as a reference group

b _{Both parents were born in the Netherlands}

c _{Groups based on sum score of five indicators (household income and both parents’ occupation and} educa-tion; score range 0-2)

d _{Methylphenidate, dexamphetamine, and/or atomoxetine use (1) or non-use (0) during (part of) the year} before the measurement of T1, T2, and/or T3

e _{Egna Minnen Betraffande Uppfostran (EMBU-C; Markus et al., 2003; Veenstra et al., 2006) subscale sum} scores (score range 0-4), assessed at T1

f _{DRD4 coded as absence (0) or presence of 7-repeat (1); 5-HTTLPR coded as SS-carriers (0), LS-carriers (1), or} LL-carriers (2); MAOA coded as low (0) or high activity (1)

g _{Mean of 7-items DSM-IV-oriented ADHD subscale of the Child Behavior Checklist (CBCL; Achenbach, 1991)} sum scores (score range 0-2).

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ership of ADHD sympt

om tr ajec tories Lo w St able n = 1021 (59.0%) Mo der at e St able n = 331 (19.1%) High D ec reasing n = 195 (11.3%) High P ersist ent n =183 (10.6%) Test st atistic P-value Popula tion-based c ohor t, n (%) 937 (91.7%) a 248 (74.9%) a 120 (61.2%) a 59 (32.2%) a χ²(3) = 378.65 <.001 Co variat es Age in y ears , M (SD ) T1 11.08 (.56) 11.08 (.51) 11.17 (.56) 11.10 (.50) F(3) = 1.49 .22 T2 13.45 (.57) b,c ,d 13.33 (.63) b 13.30 (.63) c 13.08 (.70) d F(3) = 22.68 < .001 T3 16.18 (.65) 16.12 (.70) 16.25 (.76) e 16.05 (.75) e F(3) = 3.04 .03 M ale se x, n (%) 433 (42.4%) f,g ,h 194 (58.6%) f,i 123 (63.1%) g,j 132 (72.1%) h,i,j χ²(3) = 81.90 < .001 D ut ch anc estr y, n (%) 929 (91%) k 300 (90.6%) l 176 (90.3%) m 178 (97.3%) k,l ,m χ²(3) = 8.88 .03 Socio -ec onomic sta tus , n (%) high 360 (35.3%) n,o ,p 83 (25.1%) n,q ,r 32 (16.4%) o,s 30 (16.4%) r,s medium 490 (48.0%) t,u ,v 168 (50.8%) t,w 103 (52.8%) u,x 110 (60.1%) v,w ,x χ²(6) = 60.87 <.001 lo w 171 (16.7%) y,z,A 80 (24.2%) y 60 (30.8%) z,B 43 (23.5%) A,B ADHD medica tion use , n (%) 74 (7.2%) a 72 (21.8%) a 63 (32.3%) a 117 (63.9%) a χ²(3) = 358.01 < .001 ADHD sympt oms , M (SD ) ADHD sympt om sev er ity T1 0.36 (.30) a 0.77 (.28) a 1.36 (.27) a 1.52 (.32) a F(3) = 1214.54 < .001 T2 0.22 (.23) a 0.73 (.28) a 0.96 (.31) a 1.44 (.32) a F(3) = 1385.39 < .001 T3 0.18 (.68) a 0.80 (.19) a 0.63 (.21) a 1.43 (.25) a F(3) = 2187.33 < .001 Ina tt en tion sympt om sev er ity T1 0.43 (.41) C,D ,E 0.89 (.44) C,F ,G 1.48 (.37) D ,G 1.56 (.44) E,F F(3) = 613.72 < .001 T2 0.30 (.37) a 0.95 (.44) a 1.13 (.43) a 1.53 (.42) a F(3) = 403.93 < .001 T3 0.28 (.33) a 1.09 (.39) a 0.88 (.34) a 1.59 (.38) a F(3) = 361.83 < .001 H yper ac tivit y/impulsivit y sympt om sev er ity T1 0.30 (.32) a 0.67 (.36) a 1.26 (.38) a 1.48 (.40) a F(3) = 429.24 < .001 T2 0.16 (.24) a 0.56 (.34) a 0.83 (.38) a 1.36 (.39) a F(3) = 375.64 < .001 T3 0.12 (.19) a 0.57 (.29) a 0.44 (.29) a 1.30 (.38) a F(3) = 326.50 < .001 Per ceiv ed par enting , M (SD ) Rejec tion T1 1.46 (.28) H,I,J 1.54 (.32) H,K 1.56 (.34) I,L 1.66 (.37) J,K ,L F(3) = 28.35 < .001 O ver pr ot ec tion T1 1.83 (.36) M,N 1.88 (.39) 1.95 (.42) M 1.94 (.39) N F(3) = 8.59 < .001 Emotional w ar m th T1 3.27 (.47) O ,P,Q 3.16 (.53) O 3.15 (.50) P 3.09 (.54) Q F(3) = 10.12 < .001 Not e. S ee Table 1 f or abbr evia tions and e xplana tion of v ar iables . a Sig nifican t diff er enc es bet w

een all class memberships a

t p

< .05.

b-L V

alues b

y the same lett

er indica tes a sig nifican t diff er enc e bet w

een class memberships a

t p

Table 3. Genotype distribution of n = 1,730 participants split by class membership in ADHD symptom trajectories Low Stable n = 1021 (59.0%) Moderate Stable n = 331 (19.1%) High Decreasing n = 195 (11.3%) High Persistent n =183 (10.6%)

Test statistic P-value

DRD4a _{(n, %) 7}- _carriers 7+ _carriers 641 (62.8%)_{380 (37.2%)} 217 (65.6%)_{114 (34.4%)} 119 (61.0%)_{76 (39.0%)} 117 (63.9%)_{66 (36.1%) χ²(3) = 1.31 .73} 5-HTTLPRb (n, %) SS LS LL 255 (25.0%) 508 (49.8%) 258 (25.2%) 72 (21.8%) 170 (51.3%) 89 (27.9%) 53 (27.2%) 94 (48.2%) 48 (24.6%) 59 (32.2%) 87 (47.5%) 37 (20.2%) χ²(6) = 8.06 .23

MAOAc _{(n, %) Low activity}

High activity 228 (22.3%) 793 (77.7%) 81 (24.4%) 250 (75.6%) 65 (33.3%) 130 (66.7%) 63 (34.4%) 120 (65.6%) χ²(3) = 19.63 < .001

Note. See Table 1 for abbreviations of included genes.

a_{DRD4 coded as absence (0) or presence 7-repeat (1)}

b_{5-HTTLPR coded as SS-carriers (0), LS-carriers (1), or LL-carriers (2)} c_{MAOA coded as low (0) or high activity (1).}

At T1, 316 (18.3%) adolescents of the total sample (n = 1,730) had clinical (n = 180, 10.4%) or subclinical (n = 136, 7.9%) ADHD symptom levels based on the respective ASEBA cut-off values (Achenbach & Rescorla, 2001). Of these 316 adolescents with sub(clinical) ADHD symptom levels at T1, 144 (10.6%) and 172 (47.0%) individuals were from the population-based (n = 1,364) and clinic-referred cohort (n = 366), respectively. In the high persistent ADHD symptom trajectory, respectively 109 (61.2%) of the 183 adolescents were in the clinical range at T1 and 75 (47.8%) at T3; and 42 (23.6%) at T1 and 75 (47.8%) at T3 in the subclinical range. Likewise, in the high decreasing trajectory, respectively 67 (33.7%) of the 195 adolescents were in the clinical range at T1 and in T3 none of the adolescents was in the clinical range. Furthermore, from the adolescents in the high decreasing group, 74 (38.9%) and (5.2%) had subclinical levels of ADHD symptoms at T1 and T3, respectively.

Our data further indicate that 4.3% (i.e., 59 out of 1,364) of the adolescents from the population cohort and 33.9% (i.e., 124 out of 366) adolescents from the clinic-referred cohort were following a high persistent trajectory (Table 2). Of note, the patterns of inat-tentive and hyperactive-impulsive symptoms were similar at T1, T2, and T3 (see Table 2).

Predicting Class Membership in ADHD Symptom Trajectories

Perceived parenting styles. In the model including all three parenting factors

simul-taneously, only perceived parental rejection appeared to be a significant predictor of differentiating ADHD symptom trajectories (χ²(3) = 15.28, p = .002). Perceived parental emotional warmth was trend-significant in the overall model (χ²(3) = 7.07, p = .07), and perceived parental overprotection was not significant (χ²(3) = 5.09, p = .17). Subsequent class comparisons (Table 4) showed that adolescents who perceived more parental rejection at T1 had substantially higher odds (ORs from 1.75 to 3.74) to be a member

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stable, or high decreasing classes.

Furthermore, while perceived parental emotional warmth was only trend-significant in the overall model (p = .07), the sensitivity analyses without perceived parental rejec-tion and overprotecrejec-tion in the model showed a significant effect for emorejec-tional warmth (χ²(3) = 16.79, p < .001). Adolescents in the moderate stable (OR = 0.71, 95% CI(0.55-0.91),

p = .008), high decreasing (OR = 0.69, 95% CI(0.50-0.95), p = .02), and high persistent

(OR = 0.52, 95% CI(0.37-0.74), p < .001) classes perceived less emotional warmth from their parents than those in the low stable class. Results thus suggest an opposite pattern for emotional warmth, predicting membership in the low stable trajectory, compared to parental rejection which was related to a high persistent trajectory. Of note, the other sensitivity analyses with a sole parenting predictor on ADHD symptom trajectories showed that perceived parental rejection was still significant (χ²(3) = 38.59, p < .001) whereas perceived parental overprotection was not (χ²(3) = 3.85, p = .28).

The pattern of results remained the same when conduct problems at T1 were added to the model, with perceived parental rejection still being significant (χ²(3) = 8.70, p = .03), but not parental emotional warmth (χ²(3) =3.64, p = .30) and overprotection (χ²(3) = 3.58,

p = .31). However, the high persistent trajectory was only significantly different from the

low stable (OR = 2.28, 95% CI(1.23-5.84), p = .01) and high decreasing (OR = 3.11, 95% CI(1.35-7.17), p = .008) classes.

Plasticity genes × perceived parenting styles. There were no significant interactions

between the DRD4 genotypes and perceived parental rejection (χ²(3) = 2.70, p = .44), overprotection (χ²(3) = 1.05, p = .79), and emotional warmth (χ²(3) = 1.80, p = .62) in predicting class membership in ADHD symptom trajectories. Also, no significant inter-actions were found between the 5-HTTLPR genotype and perceived parental rejection (χ²(6) = 2.06, p = .92), overprotection (χ²(6) = 2.55, p = .86), and emotional warmth (χ²(6) = 6.56, p = .36) nor between the MAOA genotype and perceived parental rejection (χ²(3) = 1.73, p = .63), overprotection (χ²(3) = 0.57, p = .90), and emotional warmth (χ²(3) = 3.19, p = .36). Note that there were also no significant main effects of DRD4 and 5-HTTLPR geno-types in differentiating between the ADHD symptom trajectories, although we found a significant effect for MAOA genotype (see Table 3). This encouraged us to further explore a potential main effect of MAOA genotype on ADHD symptom trajectories by perform-ing several multinomial logistic regressions. When corrected for two genetic principal components for population stratification, the effect of the MAOA genotype remained significant (p < .001). However, when additionally correcting for sex, or conducting analyses separately for boys and girls, which is important as the MAOA genotype is linked to the X chromosome, results became non-significant (p-values > .05).

Table 4. Par amet er estimat es and o dds r atios for p er ceiv ed par enting st yles as pr edic

tors of class memb

ership in ADHD sympt

om tr ajec tories Class memb ership Lo w Stable a vs . Mo der at e Stable Lo w Stable a vs . High D ecr easing Lo w Stable a vs . High P ersist ent Mo der at e Stable a vs . High D ecr easing Mo der at e Stable a vs . High P ersist ent High D ecr easing a vs . High P ersist ent B (SE) OR (95% CI) B (SE) OR (95% CI) B (SE) OR (95% CI) B (SE) OR (95% CI) B (SE) OR (95% CI) B (SE) OR (95% CI) Rejec tion .56 (.27)* 1.75 (1.04-2.94) .45 (.32) 1.57 (0.84-2.95) 1.32 (.35)** 3.74 (1.89-7.42) -.11 (.35) 0.90 (0.45-1.79) .76 (.37)* 2.14 (1.05-4.38) .87 (.39)* 2.38 (1.10-5.14) O ver pr ot ec tion .11 (.21) 1.11 (0.74-1.69) .58 (.26)* 1.78 (1.08-2.95) .12 (.30) 1.13 (0.63-2.02) .47 (.29) 1.60 (0.92-2.80) .02 (.31) 1.02 (0.55-1.88) -.46 (.33) 0.63 (0.33-1.22) Emotional w ar m th b -.26 (.15) b 0.77 (0.57-1.04) -.39 (.19)* b 0.67 (0.46-0.98) -.40 (.21) b 0.67 (0.44-1.01) -.13 (.21) 0.88 (0.58-1.32) -.14 (.22) 0.87 (0.56-1.35) -.008 (.24) 0.99 (0.62-1.60) Se x c .55 (.13)** 1.74 (1.34-2.26) .71 (.17)** 2.04 (1.46-2.84) .94 (.20)** 2.57 (1.74-3.79) .16 (.19) 1.17 (0.81-1.70) .39 (.21) 1.48 (0.97-2.24) .23 (.23) 1.26 (0.80-1.98) Age c .04 (.12) 1.01 (0.82-1.32) .36 (.15)* 1.44 (1.07-1.93) .17 (.18) 1.18 (0.34-1.67) .32 (.17) 1.38 (0.99-1.92) .13 (.19) 1.13 (0.79-1.64) -.20 (.20) 0.82 (0.56-1.22) SES c _Low .67 (.19)** 1.96 (1.35-2.85) 1.13 (.25)** 3.72 (2.28-6.07) 1.04 (.29)** 2.83 (1.60-5.00) .64 (.28)* 1.90 (1.11-3.25) .37 (.30) 1.44 (0.80-2.62) -.27 (.34) 0.76 (0.39-1.47) M edium .42 (.16)* 1.52 (1.12-2.06) .91 (.22)** 2.48 (1.60-3.83) 1.0 (.25)** 2.86 (1.77-4.62) .49 (.25)* 1.63 (1.01-2.64) .63 (.26)* 1.89 (1.13-3.14) .14 (.30) 1.16 (0.64-2.07) D ut ch anc estr y b -.09 (.23) 0.92 (0.59-1.43) -.03 (.29) 0.97 (0.55-1.69) .92 (.50) 2.57 (0.96-6.86) .05 (.32) 1.06 (0.57-1.97) 1.03 (.52)* 2.80 (1.02-7.70) .98 (.53) 2.65 (0.94-7.54) ADHD medica tion b 1.19 (.18)** 3.27 (2.28-4.69) 1.68 (.20)** 5.36 (3.60-7.98) 2.96 (.21)** 19.22 (12.86-28.74) .49 (.21)* 1.64 (1.09-2.46) 1.78 (.21)** 5.88 (3.91-8.84) 1.28 (.22)** 3.58 (2.32-5.54) Not e. S ta tistically sig nifican t diff er enc es bet w

een pairs of ADHD sympt

om tr ajec tor ies sho wn a t p < .05. Bold sta tistics r ef er t o the pr ec eding sig nifican t o ver all eff ec t a t p < .004 c or rec ted f or multiple t esting . See Table 1 f or abbr evia tions and e xplana tion of v ar iables . O dd r atios ( OR) and 95% c onfidenc e in ter vals (CI) fr om multiv ar ia te multinominal log istic r eg

ression. A higher OR (> 1) indica

tes tha t a higher per ceiv ed par en ting sc or e is associa

ted with a higher r

isk t

o be a member of the higher or

der tr ajec tor y, wher eas a lo w er OR (< 1) is associa ted with a lo w er r isk . Nagelker ke R² = .27 a R ef er enc e g roup b Not e tha t emotional w ar m th r etained sig nifican t eff ec

ts in a model without including par

en tal r ejec tion and o ver pr ot ec tion. F or r esults

, see the main t

ex t. c T he z er o-coded ca tegor ies (i.e ., f emales , adolesc en ts fr om D ut ch anc estr y, high socio -ec onomic sta tus ,

non-users of ADHD medica

tion) w er e used as a r ef er enc e g roup . *p < .05, ** p < .001 pr esen ts sig nifican t within-gr oup diff er enc es

3

controlled for conduct problems: the interaction with the DRD4 (p-values between .10 and .27), the 5-HTTLPR (p-values between .74 and .90), and the MAOA genotype (p-values between .10 and .77) remained non-significant.

DISCUSSION

In the present study, we examined perceived parental rejection, overprotection, and emotional warmth, as well as their interaction with three plasticity genes as predictors of class membership in ADHD symptom trajectories from early to late adolescence (age range 10-18 years) in a large pooled population and clinic-referred sample. We identi-fied four different ADHD symptom trajectories across adolescence: low stable, moderate stable, high decreasing, and high persistent. While G×E’s with three different plasticity genes did not predict class membership in ADHD symptom trajectories, perceived pa-rental rejection discriminated between the high persistent and the other three classes. More specifically, adolescents following the high persistent ADHD symptom trajectory perceived more parental rejection during early adolescence than adolescents in the other trajectories. In contrast, higher perceived parental emotional warmth was linked to the low stable ADHD symptom trajectory, suggesting a protective role.

Our study points to developmentally distinct patterns of ADHD symptoms between early and late adolescence, showing that a small group (10.6%) of youth from the gen-eral population and an additional high-risk sample is at risk of persistently high levels of ADHD symptoms. This percentage should be seen in light of our mixed sample, pointing to persistence of a high class of ADHD symptom levels in 4.3% of adolescents from the general population cohort and 33.9% of adolescents from the clinic-referred cohort, respectively. Therefore, the high persistent trajectory confers to the broader spectrum of ADHD symptoms and includes adolescents with clinical and subclinical levels of ADHD symptoms, as well as a small proportion with non-clinical symptom levels which were yet higher than those of others in the non-clinical range. Nevertheless, our findings are broadly in line with previous studies that also identified four ADHD symptom trajectories across childhood or adolescence, with 2.8%-5% following a high persistent ADHD symp-tom trajectory in population-based samples (Döpfner et al., 2015; Riglin et al., 2016; Van Lier, Van der Ende, Koot, & Verhulst, 2005) and 17.5%-22% in clinical samples (Musser et al., 2016; Tandon et al., 2016). Unlike our study, trajectories with increasing symptom severity have also been reported in a variety of samples (see Arnold et al., 2014; Robbers et al., 2011). This may be explained by the younger age of the study subjects in those samples, given that ADHD symptomatology typically peaks during childhood, but tends to remit mainly during adolescence (Döpfner et al., 2015), while recently reported

late-onset ADHD typically manifests beyond 16 years (Agnew-Blais et al., 2016; Caye et al., 2016). In line with our study, other reports covering adolescence also did not show an increasing ADHD symptom trajectory (Döpfner et al., 2015; Riglin et al., 2016; Van Lier et al., 2007).

An important new contribution of this study to the existing literature is that perceived parental rejection in early adolescence is linked to risk of a trajectory of persistently high ADHD symptoms across adolescence. Our study thus points to a long-term predictive role of perceived parental rejection beyond childhood in adolescents transitioning towards adulthood. Our finding is in line with Sasser and colleagues (2016) who demonstrated that inconsistent parenting in childhood was associated with a persistently high class of clinically significant ADHD symptoms into late adolescence. It also fits with findings of negative parenting in early childhood (i.e., lower emotional support and lower intellec-tual stimulation), predicting class membership of consistently high levels of inattention/ hyperactivity throughout adolescence (Jester et al., 2005). Of note, the role of perceived parental rejection on ADHD symptom trajectories in our study remained significant after adjusting for conduct problems, in line with Keown (2012).

Although our study does not allow for making inferences about causality of parenting, as is inherent to observational studies, some literature does suggest causality between parenting and child behavior over time. For example, a twin study found that hostile parenting behavior of adoptive mothers prospectively predicted ADHD symptoms 1.5 years later in 6-year old children (Harold et al., 2013). In reverse, adolescent’s ADHD and associated difficult behavior (e.g., moodiness, uncooperativeness) may place a high strain on the family system and possibly increase parental stress facilitating rejection that often occurs in families of children with ADHD (Johnston & Mash, 2001). Thus, parenting styles and adolescent’s own behavior may reinforce each other in a vicious cycle over time. Indeed, in a longitudinal study with a 1-year time interval involving 194 school-aged children, children’s ADHD symptoms led to increased mother-child rejection, whereas paternal rejection exacerbated children’s ADHD symptoms (Lifford, Harold, & Thapar, 2008). Most likely, therefore, is the existence of bidirectional relations between ADHD symptoms and parental rejection. One possibility to explain the impact of parental rejection on the persistence of ADHD symptoms is that rejecting parents may fail to provide an emotionally supportive environment, which is a crucial aspect in parenting a child with ADHD symptoms. Furthermore, because ADHD is highly heritable (Faraone & Mick, 2010), adolescents with ADHD more often have parents with ADHD which is associated with more negative parenting (Chronis-Tuscano et al., 2008; Psycho-giou, Daley, Thompson, & Sonuga-Barke, 2007). Clearly, more longitudinal bidirectional studies across adolescence are needed to support a causal role of parental rejection on persisting ADHD symptom trajectories. Further, more studies with sophisticated family designs (e.g., twin, sibling studies) are necessary to control for unmeasured genetic

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experi-ence of the home environment and the adolescent’s ADHD symptoms may be (partly) explained by shared genetic factors, thus not implying causality (see e.g., Hanscombe, Haworth, Davis, Jaffee, & Plomin, 2011).

Perceived parental overprotection did not predict class membership in ADHD symptom trajectories, while emotional warmth was significant only when examined as a single parenting predictor in the model. Thus, negative parenting (i.e., rejection) seems more strongly related to ADHD symptom trajectories than positive parenting. Still, adolescents following the low stable trajectory of ADHD symptoms perceived more emotional warmth from their parents in early adolescence as compared to ado-lescents in the moderate stable, high decreasing, and high persistent trajectories who experienced lower emotional warmth. The association of parental emotional warmth in our study with a low stable ADHD symptom trajectory is in line with a study that showed that positive parenting was linked with good adolescent mental health over time (Smokowski, Bacallao, Cotter, & Evans, 2015). It has been suggested that positive parenting is even more critical in the early years of children’s development (Dvorsky & Langberg, 2016). Indeed, a longitudinal study in 5-to-13 year-old children found that the association between higher parental warmth and ADHD declined over a 2-year period (Santesteban et al., 2017). Our focus on adolescence may explain why we did not find a promotive role of emotional warmth with regard to remission of ADHD symptoms. Finally, whereas other studies showed that overprotection was associated with higher levels of externalizing behavior (Marsman et al., 2013; Muris, Meesters, & Van den Berg, 2003) and that adolescents with and without persisting ADHD received more maternal overprotection (Gau & Chang, 2013), our findings do not support a role of perceived parental overprotection in predicting ADHD symptom trajectories across adolescence. This is in line with Musser and colleagues (2016) who also found no differences for any of the ADHD symptom trajectory groups ranging from 7-13 years of age regarding a comparable measure of overprotection (i.e., emotional over-involvement).

We did not find G×E interactions involving the DRD4, MAOA, and 5-HTTLPR genotype on ADHD symptom trajectories across adolescence and, although not part of our main objectives, we found just one main gene association: the low activity MAOA genotype was more prevalent in adolescents in the high persistent trajectory. This is consistent with a recent finding of attention problems during adolescence being particularly stable over time in those with the low activity MAOA genotype (Zohsel et al., 2015). The absence of an interaction with the DRD4 genotype was in contrast with Berry and colleagues (2013) who found that in the context of highly sensitive early maternal care, the DRD4 7-repeat was associated with trajectories with low levels of inattention across childhood, whereas insensitive early maternal care in children with the DRD4 7-repeat polymorphism was associated with high levels of inattention. Unlike our study, Berry

and colleagues (2013) examined to what extent parenting was “tuned” to the child’s demands in a given situation. Another explanation for the absence of G×Parenting interactions may be that childhood is a more critical period for influences of parent-ing than adolescence (Sameroff, 2010). This might explain why the childhood study of Berry and colleagues (2013) showed significant results and our adolescent study did not. Also, all other cross-sectional G×Parenting findings on ADHD symptoms (Elmore et al., 2016; Li & Lee, 2011) were conducted in childhood with one exception (Nikitopoulos et al., 2014), which examined the long-term effect of early maternal care at age of three months at ADHD symptoms in adolescence. It is possible, therefore, that especially early caregiving is of importance in examining G×E on the course of ADHD symptoms across development.

Strengths and Limitations

A strength of this study was the use of a large longitudinal dataset of adolescents, which consisted of a population sample enriched by data from a clinic-referred cohort. This enabled us to identify ADHD symptom trajectories in relation to parenting style cover-ing the full continuum from non-clinical to clinical ADHD symptom levels between early and late adolescence, an age range that is still underrepresented in the ADHD literature. A potential limitation may have been the use of the DSM-oriented ADHD subscale as it does not capture all 18 ADHD symptoms of the DSM; however, this subscale has been shown to have adequate diagnostic accuracy (Nakamura, Ebesutani, Bernstein, & Chorpita, 2009). Moreover, despite the EMBU’s good psychometric properties (Markus et al., 2003; Muris, Bosma, Meesters, & Schouten, 1998), the assessment of adolescent’s subjective perception of parenting styles may lead to possible biases (e.g., depressed children may have a negatively biased perception of their parental rearing; Stein et al., 2000), compared to measurements of observed parental behavior. Another limitation is that we measured perceived parenting only at baseline. Furthermore, while we did not define trajectories as per ADHD subdimensions (i.e., separately for inattentive and hyperactive/impulsive symptoms), the pattern of inattention symptom severity and hyperactivity-impulsivity severity were comparable in the four trajectories.

Finally, the literature has raised criticism about inconsistent G×E studies with likely false positive findings (Duncan & Keller, 2011; Duncan, Pollastri, & Smoller, 2014). How-ever, given the large (methodological) differences between studies (e.g., in parenting variables or plasticity genes examined), it is difficult to determine whether findings are truly inconsistent or are simply incomparable (Weeland, Overbeek, Orobio de Castro, & Matthys, 2015). Considering differences across studies, a first attempt has been made to address one of these issues using polygenic risk scores (Riglin et al., 2016).

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Conclusions

Our study highlights that perceived parental rejection in early adolescence is a predictor of persistently high ADHD symptoms into late adolescence. In contrast, positive parent-ing may have a protective role associated with low symptom levels. To address causality, future studies are needed to clarify the specific directions through which effects between parenting and adolescents’ ADHD symptoms are operating, preferably investigating a broad set of parenting variables across multiple time-points. Clinical interventions may focus on the prevention of parental rejection and improvement of parenting skills in mitigating ADHD symptoms which might have beneficial long-term effects.

We could not find support for a role of the individual plasticity genes DRD4, MAOA, and 5-HTTLPR in interaction with parenting in the prediction of ADHD symptom trajec-tories. Future family-based studies that separate genetic and familial influences, as well as genetic studies utilizing polygenic risk scores or gene-sets, may be better suited to capture the contribution of genes

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