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Associations of Prenatal Nicotine Exposure and the Dopamine Related Genes ANKK1 and DRD2 to Verbal Language John D. Eicher1, Natalie R. Powers1, Kelly Cho2,3,4, Laura L. Miller5, Kathryn L. Mueller6, Susan M. Ring5,

J. Bruce Tomblin6, Jeffrey R. Gruen1,7*

1 Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, United States of America, 2 Departments of Epidemiology and Public Health, Yale

University School of Medicine, New Haven, Connecticut, United States of America, 3 Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston,

Massachusetts, United States of America, 4 Massachusetts Veterans Epidemiology Research and Information Center, Boston, Massachusetts, United States of America,

5 School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom, 6 Departments of Speech, Pathology, and Audiology, University of Iowa, Iowa

City, Iowa, United States of America, 7 Departments of Pediatrics and Investigative Medicine, Yale Child Health Research Center, Yale University School of Medicine, New

Haven, Connecticut, United States of America

Abstract

Language impairment (LI) and reading disability (RD) are common pediatric neurobehavioral disorders that frequently co- occur, suggesting they share etiological determinants. Recently, our group identified prenatal nicotine exposure as a factor for RD and poor reading performance. Using smoking questionnaire and language data from the Avon Longitudinal Study of Parents and Children, we first determined if this risk could be expanded to other communication disorders by evaluating whether prenatal nicotine exposure increases risk for LI and poor performance on language tasks. Prenatal nicotine exposure increased LI risk (OR = 1.60; p = 0.0305) in a dose-response fashion with low (OR = 1.25; p = 0.1202) and high (OR = 3.84; p = 0.0002) exposures. Next, hypothesizing that the effects of prenatal nicotine may also implicate genes that function in nicotine related pathways, we determined whether known nicotine dependence (ND) genes associate with performance on language tasks. We assessed the association of 33 variants previously implicated in ND with LI and language abilities, finding association between ANKK1/DRD2 and performance on language tasks (p#0.0003). The associations of markers within ANKK1 were replicated in a separate LI case-control cohort (p,0.05). Our results show that smoking during pregnancy increases the risk for LI and poor performance on language tasks and that ANKK1/DRD2 contributes to language performance. More precisely, these findings suggest that prenatal environmental factors influence in utero development of neural circuits vital to language. Our association of ANKK1/DRD2 further implicates the role of nicotine-related pathways and dopamine signaling in language processing, particularly in comprehension and phonological memory.

Citation: Eicher JD, Powers NR, Cho K, Miller LL, Mueller KL, et al. (2013) Associations of Prenatal Nicotine Exposure and the Dopamine Related Genes ANKK1 and DRD2 to Verbal Language. PLoS ONE 8(5): e63762. doi:10.1371/journal.pone.0063762

Editor: Baohong Zhang, East Carolina University, United States of America

Received December 21, 2012; Accepted April 5, 2013; Published May 15, 2013

Copyright: � 2013 Eicher et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The UK Medical Research Council, the Wellcome Trust and the University of Bristol provide core support for ALSPAC. This research was funded by R01NS43530 (J.R.G.), T32 MH014235 (K.C.), and T32 GM007223 (J.D.E.) from the National Institutes of Health (NIH) along with F31DC012270 from the National Institute on Deafness and Other Communication Disorders (J.D.E.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: [email protected]

Introduction

Language impairment (LI) and reading disability (RD) have

prevalences of 5–8% and 5–17%, respectively, in schoolchildren

[1–2], and together comprise the majority of learning disabilities.

LI and RD are characterized by difficulty in the understanding

and/or utilization of verbal and written language, respectively,

despite normal development and adequate educational opportu-

nity [1–2]. LI and RD are related disorders, as both involve

deficits in the integration and utilization of communicative tools.

Impaired phonological skills have been implicated in both LI and

RD [1–7]. LI and RD are frequently comorbid; as children with

LI are at higher risk of developing RD than their typically

developing peers [1–2,8]. The degree of relatedness and the

frequent comorbidity of LI and RD indicate they may share risk

factors. Twin and family studies have shown that both LI and RD

have a significant genetic component, with heritability estimates of

45–73% and 54–84%, respectively [8–10]. However, specific

environmental and genetic risk factors for LI and RD, and the

extent to which they are shared between the two disorders, remain

largely unknown.

One possible environmental risk factor for LI and RD is

exposure of the developing fetus to toxins and substances in utero

via the maternal environment and behavior, specifically smoking

or nicotine exposure. The harm of prenatal nicotine exposure has

been well-documented [11–13]. Despite this, studies estimate 14–

37% of women smoke during pregnancy [14]. Prenatal nicotine

exposure is a risk factor for several neurobehavioral conditions

such as Attention Deficit-Hyperactivity Disorder (ADHD), learn-

ing disabilities, and substance abuse [15–17]. Some studies have

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expanded these findings to RD, LI, and neurocognition [18–

19,21]; while others have argued that nicotine variables may

capture factors not adequately controlled for in statistical models,

such as socioeconomic status [20–21]. Our recent work showed an

association between prenatal nicotine exposure and poor reading

performance in schoolchildren, after adjustment for a wide range

of confounders, including socioeconomic status, type of school

attended, birth weight, and gestational age [22]. However, further

study is necessary to determine whether prenatal nicotine exposure

also influences language abilities and LI.

The implication of prenatal nicotine exposure in communica-

tion performance raises the question of how this exposure exerts its

effects. One possibility is that genetic variants previously associated

with nicotine dependence (ND) and nicotine-related pathways

may have pleiotropic effects. That is, genetic variants that

predispose individuals to ND may also contribute to communi-

cation processes. Studies of ND have revealed that it has a

significant genetic component and identified several candidate

genes, including DRD2, ANKK1, CHRNA4, and CHRNB2. Many of

these genes are involved in neuronal signaling pathways, including

the cholinergic and dopaminergic neurotransmitter pathways. The

implication of various signaling pathways further suggests that

variation in these genes may affect multiple cerebral processes,

such as addiction, language, and reading. Several of these ND

genes, including BDNF, DRD2, and ANKK1, have been associated

with neurobehavioral phenotypes [23–24]. ANKK1 and DRD2

have been associated with autism, executive functioning, and

verbal ability [25–26]. However, these reports are few in number,

and replication in larger cohorts is needed.

The present study expands on our previous work to examine

prenatal nicotine exposure and its related pathways with regard to

LI and its associated language domains. First, we analyze the

relationship of prenatal nicotine exposure with performance on

language tasks and LI. Due to nicotine’s detrimental effects on

brain function, we hypothesize that prenatal smoking exposure will

also be a risk factor for poor language performance and LI.

Second, we assess whether known ND variants contribute to

language abilities. ND genes have known neurological functions,

particularly in neuronal signaling; therefore, we also hypothesize

ND variants associate with language performance and LI.

Materials and Methods

Subjects The Avon Longitudinal Study of Parents and Children

(ALSPAC) is a population-based, birth cohort in Avon, United

Kingdom. Subjects were recruited before birth, resulting in a total

of 15,458 fetuses, of whom 14,701 were alive at 1 year of age.

Recruitment, participants, and study methodologies are described

in detail elsewhere (http://www.bristol.ac.uk/alspac) [27–28].

7170 subjects completed language measures at age 8 years.

Subjects with IQ #75 on the Wechsler Intelligence Scale for

Children (WISC-III) Total IQ were excluded from the present

study [29]. To prevent population stratification in genetic analyses,

subjects of non-European descent were also removed. Addition-

ally, samples with genotyping call rate ,0.80 were excluding from

analyses, leaving a final sample size of 5579 individuals. Ethical

approval was obtained from ALSPAC Ethics and Law Committee,

Local UK Research Ethics Committees, and Yale Human

Investigation Committee.

ALSPAC Language Measures Language measures were collected during clinical interviews at

age 8 years. An adaptation of the Nonword Repetition Task

(NWR), in which subjects repeated recordings of nonwords, was

used to assess short-term phonological memory and processing

abilities [30]. Children also completed the Wechsler Objective

Language Dimensions (WOLD) verbal comprehension task at age

8 years [31], where they answered questions about a paragraph

read aloud by an examiner describing a presented picture. We

focused on these measures because individuals with LI are known

to consistently perform poorly on NWR and WOLD comprehen-

sion tasks, and these tasks are commonly used in genetic and

epidemiologic studies of LI [32–33]. Z-scores were calculated for

each subject on each individual measure, and to capture deficits in

two of the primary domains of LI, the average z-score of NWR

and WOLD comprehension tasks was calculated. To assess the

risk imparted to severe LI, we defined LI cases as scoring $2.0

standard deviations below sample means on either task.

Exposure and Covariate Variables Questionnaires for smoking frequency and cigarette brand were

completed by mothers at gestational age 8, 18, and 32 weeks and

at 8 weeks following birth. Although cigarettes contain thousands

of compounds, nicotine is the most prevalent, pharmacologically

active ingredient that is likely responsible for smoking’s deleterious

effects. Therefore, we calculated the level of nicotine exposure for

each time point based upon the nicotine content of the cigarette

brands smoked. Because of limited power to divide nicotine

exposure into trimesters, we used the maximum nicotine exposure

to derive prenatal nicotine exposure [22,34–35]. First, prenatal

nicotine exposure was dichotomized into exposed and non-

exposed groups. To examine dose-response, prenatal nicotine

exposure was further categorized into three groups: no exposure

(0 mg*day 21

), low exposure (#17 mg*day 21

), and high exposure

(.17 mg*day 21

) [36]. 17 mg was chosen as it is the average

amount of nicotine in one pack of cigarettes.

Due to the interdependence between overall cognition and

communication, subjects with WISC-III Total IQ scores #75

were excluded from analysis [37]. To further control for the effects

of IQ, WISC-III Performance IQ scores were included as a

covariate in analyses [29]. Performance IQ was chosen to prevent

controlling for language abilities captured by Verbal and Total IQ

scores. In addition to Performance IQ, we adjusted for the

following 11 covariates to control for known confounding

relationships with language: mother’s age at delivery, maternal

prenatal alcohol consumption [38], maternal social class, child-

parent interaction time, mother’s attendance at antenatal classes,

sex, ADHD status, school type, gestational age, birthweight, and

resuscitation status [39] (Table S1).

Statistical and Genetic Analyses First, SAS 9.2 was used to statistically analyze the association of

prenatal nicotine exposure with language performance in the

ALSPAC cohort. Dichotomized prenatal nicotine exposure status

was examined first, followed by dosage categories. For quantitative

measures, we fitted crude linear regression models, with prenatal

nicotine exposure as the predictor for each language outcome.

Next, multivariable regression models adjusted for covariates were

used to identify specific effects of prenatal nicotine exposure. We

used logistic regression models to fit prenatal nicotine exposure

and covariates for each dichotomized language measure. Odds

ratios (OR) were calculated for exposed/non-exposed, then for the

low and high dosage categories.

Next, 33 single nucleotide polymorphisms (SNPs) in 12 genes,

previously implicated in ND, nicotine pathways, and/or substance

dependencies, were genotyped on the Sequenom platform (San

Diego, CA), following the manufacturers guidelines at the Yale

Smoking Exposure and ANKK1/DRD2 Influence Language

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Center for Genome Analysis (Orange, CT) (Table 1). 32 of the

33 ND variants had call rates $90%, were biallelic, had minor

allele frequencies $0.01, and were in Hardy-Weinberg equilibri-

um (p$0.001). To correct for the 32 genetic association tests

performed in the ALSPAC cohort, Bonferroni correction was

applied to adjust for multiple testing (a = 0.05/32 = 1.5661023). Since these ND variants have a prior relationship with nicotine

and/or addiction, we created a subsample of subjects not exposed to

nicotine and repeated associations to avoid possible confounding.

Associated variants were then examined in the Iowa LI cohort.

The Iowa LI cohort is comprised of 219 LI cases and 209 sex- and

age-matched, unrelated controls collected at the University of

Iowa. Subjects completed various language measures, including

the Peabody Picture Vocabulary Test (PPVT) and NWR, which

were used to derive a composite language score, which was

dichotomized into case-control status at 21.14 standard deviations

[40]. Single marker analysis in both cohorts was performed with

linear and logistic regression under additive models using SNP &

Variation Suite (SVS) v7.6.4 (Golden Helix, Bozeman, MT).

Haplotype regions were constructed following the 4-gamete rule

using HaploView v4.2, and haplotype association tests were

performed using PLINK v1.07.

Results

Prenatal Nicotine Exposure and Language In the ALSPAC sample, subjects exposed to prenatal nicotine

performed on average 4.75–5.39% worse on language measures

compared to non-exposed subjects (Table 2). When separated into

nicotine dosage categories, those exposed to high levels of prenatal

nicotine performed on average the worst on all measures

compared to low (ranging from 6.20–7.95% worse) and no

exposure (ranging from 9.63–11.58%) groups (Table 2).

Crude linear regression analyses comparing groups exposed to

prenatal nicotine to the non-exposed groups showed that prenatal

nicotine exposure is associated with performance on NWR and

comprehension tasks (p#0.0002) (Table 3). After adjusting for

covariates, the association with average performance on the

NWR/comprehension tasks persisted (p = 0.0262), while there was

a trend with the NWR task (p = 0.0799). Crude analyses for

exposure dosage showed a deleterious effect of prenatal nicotine

exposure on NWR and comprehension tasks (p#0.0002) (Table 4).

After covariate adjustment, there was a negative effect of high dose

of prenatal nicotine exposure on comprehension (p = 0.0011) and

average performance on NWR/comprehension (p = 0.0011), with

trend toward a negative effect of high exposure for the NWR task

alone (p = 0.0729).

Table 1. Nicotine dependence (ND) markers genotyped in the ALSPAC sample.

Variant Gene Location MAF Variant Gene Location MAF

rs2072660 CHRNB2 1q21.3 0.240 rs10893365 PKNOX2 11q24.2 0.171

rs2072661 CHRNB2 1q21.3 0.244 rs10893366 PKNOX2 11q24.2 0.168

rs12466358 CHRND 2q31 0.253 rs11220015 PKNOX2 11q24.2 0.174

rs13277254 CHRNB3 8p21 0.212 rs11602925 PKNOX2 11q24.2 0.176

rs4950 CHRNB3 8p21 0.214 rs12284594 PKNOX2 11q24.2 0.170

rs6474413 CHRNB3 8p21 0.214 rs1426153 PKNOX2 11q24.2 0.174

rs4075274 NTRK2 9q21.33 0.434 rs750338 PKNOX2 11q24.2 0.227

rs2030324 BDNF 11p14.1 0.469 rs1051730 CHRNA3 15q25 0.329

rs4274224 DRD2 11q23.1 0.493 rs1317266 CHRNA3 15q25 0.226

rs4648318 DRD2 11q23.1 0.239 rs578776 CHRNA3 15q25 0.281

rs7131056 DRD2 11q23.1 0.425 rs6495308 CHRNA3 15q25 0.231

rs6278 DRD2 11q23.1 0.153 rs8034191 LOC123688 15q25 0.331

rs11604671 ANKK1 11q23.1 0.488 rs16969968 CHRNA5 15q25 REMOVED

rs1800497 ANKK1 11q23.1 0.197 rs2229959 CHRNA4 20q13.33 0.113

rs2734849 ANKK1 11q23.1 0.485 rs2236196 CHRNA4 20q13.33 0.252

rs4938013 ANKK1 11q23.1 0.321 rs2273504 CHRNA4 20q13.33 0.162

rs7118900 ANKK1 11q23.1 0.185

Abbreviations: ND, nicotine dependence; MAF, minor allele frequency. doi:10.1371/journal.pone.0063762.t001

Table 2. Descriptive statistics of language scores among exposure groups.

Non-smoking Any Exposure Low High

N Mean(SD) N Mean(SD) N Mean(SD) N Mean(SD)

NWR 4720 7.37(2.43) 758 7.02(2.48) 615 7.10(2.45) 143 6.66(2.56)

Comprehension 4724 7.60(1.91) 760 7.19(1.93) 617 7.30(1.93) 143 6.72(1.88)

Abbreviations: SD, standard deviation; NWR, nonword repetition. doi:10.1371/journal.pone.0063762.t002

Smoking Exposure and ANKK1/DRD2 Influence Language

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In ALSPAC, LI had a prevalence of 4.90%, which is consistent

with estimates in the general population [1–2]. Exposure to

prenatal nicotine increased risk for LI, after controlling for

covariates (OR = 1.60 [1.04–2.45]; p = 0.0305) (Table 5). Risk of

developing LI occurred in a dose response fashion with low

(OR = 1.25 [0.76–2.04]; p = 0.1202) and high (OR = 3.85 [1.87–

7.94]; p = 0.0009) prenatal nicotine exposure levels (Table 6).

Association of ND Markers to Language Single-marker analysis revealed associations between SNPs

within ANKK1 and language performance as measured by the

average z-score on NWR/comprehension tasks (p#1.961023) (Table 7). Haplotype associations were similar, showing association

between a haplotype containing ANKK1 and DRD2 markers and

language performance (Table 8). This haplotype included a

majority of the significant SNPs from single marker analysis,

suggesting these markers captured the same variability in the

locus. Interestingly, the ANKK1 haplotype block contained a

marker in the DRD2 gene located adjacent to ANKK1 (rs6278)

(Figure 1). These associations persisted when examined in

ALSPAC subjects not exposed to prenatal nicotine (Table 7).

There was no evidence of interaction between prenatal nicotine

exposure and ND variants in the ALSPAC sample. Associations

of SNPs within ANKK1 (rs2734849 and rs11604671) were

replicated in the Iowa LI cohort with LI case-control status

(OR = 1.4 [1.1–2.0]; p#7.4161023) (Table 9).

Discussion

Our investigation examined the effects of prenatal nicotine

exposure and nicotine-related genetic variants on LI and

performance on language tasks. We found increased risk of LI

and poor performance on language tasks in subjects exposed to

prenatal nicotine. In addition, there was a genetic association

between single markers within ANKK1 and a haplotype spanning

ANKK1/DRD2 and language performance, further implicating

nicotine-related and dopamine pathways in language. These

findings show the importance of the prenatal environment and

dopamine to language and cognitive development.

Prenatal Nicotine Exposure and Language We found an association of prenatal nicotine exposure on

language performance and LI, after adjusting for known

covariates, such as socioeconomic status, type of school attended,

and parent interaction. This relationship appears to be specific to

language skills and independent of overall cognitive skills, as

Performance IQ was accounted for in all final models. These

results expand upon our previous findings, showing the detrimen-

tal effects of prenatal nicotine exposure on phonology, reading

fluency, reading comprehension, and reading accuracy. These

components are foundational to the development of reading and

language skills in children. Our previous study found that deficits

in reading comprehension similar to the ones we found in verbal

comprehension, suggesting prenatal nicotine exposure exerts an

effect on how children ascertain meaning in verbal and written

language.

The negative effects of prenatal nicotine exposure on reading

and language may reflect changes in gene expression resulting

from epigenetic modifications due to the nicotine exposure [41].

Future studies should examine how nicotine exposure interacts

with genes associated with communication, such as DCDC2,

KIAA0319, and FOXP2, and their epigenetic regulation. One

investigation demonstrated the contribution of 59 regions marked

by acetylated H3 histones in KIAA0319 to RD, suggesting the

importance of epigenetic regulation to language [42]. Epigenetic

studies in combination with neurotoxicological studies should be

explored to determine whether and how nicotine exposure alters

gene expression and cellular function.

Table 3. Effects of any prenatal nicotine exposure on language performance.

Crude Model Adjusted Model

Exposed Overall Exposed Overall

Measure Beta p-value p-value Beta p-value p-value

NWR 20.14 0.0002 0.0002 20.09 0.0799 0.0799

Comprehension 20.21 ,0.0001 ,0.0001 20.08 0.1123 0.1123

Avg NWR Comp 20.18 ,0.0001 ,0.0001 20.09 0.0262 0.0262

Abbreviations: NWR, nonword repetition; Avg NWR Comp. average of z-scores of nonword repetition and verbal comprehension tasks. doi:10.1371/journal.pone.0063762.t003

Table 4. Effects of prenatal nicotine dosage on language performance.

Crude Model Adjusted Model

Low High Overall Low High Overall

Measure Beta p-value Beta p-value p-value Beta p-value Beta p-value p-value

NWR 20.11 0.0102 20.29 0.0006 0.0002 20.07 0.2174 20.22 0.0729 0.1085

Comprehension 20.16 ,.0002 20.46 ,0.0001 ,0.0001 20.02 0.7426 20.47 0.0002 0.0011

Avg NWR Comp 20.13 ,0.0001 20.37 ,0.0001 ,0.0001 20.05 0.2868 20.35 0.0003 0.0011

Abbreviations: NWR, nonword repetition; Avg NWR Comp. average of z-scores of nonword repetition and verbal comprehension tasks. doi:10.1371/journal.pone.0063762.t004

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In addition to possible changes directly to gene regulation,

mouse and rat models have shown that prenatal nicotine exposure

permanently affects neurochemical signaling pathways, including

dopaminergic pathways, and alter their developmental trajectories

over the lifespan [43–45]. Animals exposed to gestational nicotine

have higher dopamine turnover in the frontal cortex [44,46].

These results from animal models, in conjunction with our

findings implicating prenatal nicotine and dopamine signaling in

LI, suggest that deficits and permanent changes in dopamine

activity resulting from exposure and genetic variants have a

substantial influence upon language skills and development. These

implications, however, still must be explored and confirmed in

human studies, possibly through magnetic resonance spectroscopy

(MRS). MRS would permit in vivo monitoring of dopamine

signaling in the human brain. MRS could specifically interrogate

the influence of prenatal nicotine exposure on dopaminergic

signaling, gene expression, and language in the same subjects.

ANKK1/DRD2 and Language Single marker and haplotype analyses showed association

between language performance and ANKK1-DRD2. In addition

to past associations with ND, ANKK1 and DRD2 have been

associated with other neurobehavioral traits including alcohol

dependence, reinforcement learning, working memory, and

executive function [47–51]. Dopamine is a key neurotransmitter

in the corticostriatal system that subserves procedural and

reinforcement learning. Animal and human studies, using

dopamine agonists and/or antagonists, show that alterations in

dopamine receptor function change reinforcement learning [52].

Recently, reinforcement learning was shown to be associated with

individual differences in language in a task influenced by

dopamine signaling [53–54]. Additionally, past studies have

associated ANKK1/DRD2 to working memory. Working memory

is directly associated with language skills in children, and in fact,

impairments in working memory have been proposed to play a

direct role in the development of language deficits seen in children

with LI [55–56]. Changes in dopaminergic function, whether from

genetic predisposition (ANKK1/DRD2) or environmental exposure

(prenatal nicotine), yield alterations in working memory and

reinforcement learning. These changes, which arise via permanent

alterations in dopamine function, appear to then influence

language development as well as other neurobehavioral domains,

including nicotine and substance use.

Despite the wide range of literature examining ANKK1/DRD2

and neurobehavioral traits, there have been limited reports

examining the role of ANKK1 and DRD2 specifically in language

and language-related domains. Beaver et al. reported an associ-

ation between DRD2 and performance on an abbreviated form of

the PPVT [26]. The PPVT is a standardized measure of

expressive and receptive vocabulary, which may be analogous to

deficits measured in our verbal and reading comprehension tasks,

although the tasks in this study measure higher order cognitive

processing. Our findings expand the role of ANKK1 and DRD2

from known effects on working memory, reinforcement learning,

and predisposition to nicotine use to now include verbal language.

Additionally, these findings point to a role for dopamine as a

mechanism in processes involved in language development. In this

regard, these findings and the implications of prenatal nicotine

exposure on brain neurochemistry support the notion that

procedural learning, rooted in the dopamine rich basal ganglia,

plays an important role in language development [57–59].

The relationship between the neighboring genes ANKK1 and

DRD2 has been a source of controversy. In our study, we found

association between language and a haplotype block stretching

across ANKK1 and DRD2, suggesting that we, like most studies, are

unable to refine our associations to a single gene. However,

previous work has shown that the rs1800497 polymorphism is

associated with the number of D2 dopamine binding sites and

glucose metabolism in the central nervous system [60–62].

Reduced dopamine signaling and glucose metabolism may

adversely affect high order cognitive functioning including verbal

language processing. Functionally, there is limited evidence on

how ANKK1 and DRD2 may interact. Huang et al. suggested

ANKK1 may influence DRD2 expression via NF-kB signaling [63].

However, evidence supporting this hypothesis is limited and in vivo

analyses are needed to discern any functional relationship between

ANKK1 and DRD2. Additionally, associations of ANKK1 and DRD2

Table 5. LI risk based on prenatal nicotine exposure.

Crude Model Adjusted Model

OR p-value OR p-value

1.77 (1.31–2.40) 0.0002 1.60 (1.04–2.45) 0.0305

Abbreviation: OR, odds ratio. doi:10.1371/journal.pone.0063762.t005

Table 6. LI risk based on prenatal nicotine dosage.

Crude Model Adjusted Model

Low OR p-value High OR p-value Low OR p-value High OR p-value

1.43 (1.00–2.05) 0.2514 3.33 (2.02–5.52) ,0.0001 1.25 (0.76–2.04) 0.1202 3.85 (1.87–7.94) 0.0009

Abbreviation: OR, odds ratio. doi:10.1371/journal.pone.0063762.t006

Table 7. Single marker genetic associations with average of Nonword Repetition and Verbal Comprehension tasks.

Variant Gene p-value No SMK p-value a

rs2734849 ANKK1 2.061024 1.961024

rs11604671 ANKK1 2.361024 2.261024

rs4938013 ANKK1 1.261023 6.861024

rs7118900 ANKK1 1.261023 1.261023

rs1800497 ANKK1 1.961023 2.661023

rs6278 DRD2 8.861023 1.761022

a No SMKg p-value refer to associations in cohort of subjects not exposed to

prenatal nicotine. doi:10.1371/journal.pone.0063762.t007

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may reflect linkage disequilibrium in the locus, and may be

capturing the signal from a single, unidentified causative variant.

Limitations This investigation is subject to several limitations. First, the use

of maximum amount of prenatal nicotine exposure may be an

overestimation due to possible reductions and cessations of

smoking during the prenatal period. However, the smoking data

obtained accurately reflects the exposure since the information was

collected in the pre/perinatal period. Second, although we

controlled for many factors associated with language, this study

cannot control for all possible, unmeasured factors that may

confound associations. However, our models encompass a broad

range of covariates relative to other previous studies. Third, due to

the design of the ALSPAC cohort and amount of time following

subjects, missing data are to be expected. The subsample used to

complete association analyses has various demographic and

environmental differences compared to the overall sample, which

is more representative of the general population in the Avon

region of the United Kingdom (Table S2). These factors were

controlled for in the analysis of prenatal nicotine exposure, but our

findings must be replicated in a more diverse, representative

sample before being expanded to the general population. Fourth,

there are inherent differences between our discovery cohort,

ALSPAC, and our replication cohort, Iowa LI. Subjects in

ALSPAC were recruited during the prenatal period, and

investigators aimed to collect a sample that reflected the general

population in the Avon region of the United Kingdom. Iowa LI is

a case-control cohort that recruited cases with LI and matched

controls. Therefore, genetic associations of ANKK1/DRD2 in the

two cohorts are not identical. However, the initial and replicated

associations do suggest that ANKK1/DRD2 and dopamine

signaling modulate language skills in children.

Figure 1. Linkage disequilibrium between ANKK1 and DRD2. Linkage disequilibrium (LD), as measured by D’, among markers in the ANKK1 and DRD2 genes. There is a 12kb haplotype block spanning the two genes (markers: rs11604671, rs2734849, rs1800497, and rs6278). doi:10.1371/journal.pone.0063762.g001

Table 8. Haplotype Association of ANKK1/DRD2 with average of Nonword Repetition and Verbal Comprehension tasks.

Variants Genes Haplotype Beta p-value

rs11604671, rs2734849, rs1800497, rs6278

ANKK1/ DRD2

ACCG 0.053 3.261024

doi:10.1371/journal.pone.0063762.t008

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Conclusions

Prenatal nicotine exposure has a negative effect on language

abilities in schoolchildren. These results support the growing body

of evidence that the development of communication skills begins

during fetal development. Future studies should determine the

effects of exposure to first-hand nicotine exposure and other

prenatal and postnatal toxins. The genetic associations of ANKK1

and DRD2 with language performance further suggest that

nicotine-related pathways modulate verbal language processing.

More specifically, we implicate dopamine signaling in the

comprehension and processing of verbal language. Other factors

in dopamine and other major neurotransmitter signaling pathways

should be examined.

Supporting Information

Table S1 Distribution of covariates among smoking groups. Values are either percentages or means (SD). *Indicates x

2 two-tailed p-value ,0.05 from univariate analyses of each

covariate and prenatal nicotine exposure outcome. **Indicates

ANOVA p-value ,0.05 from comparison of each covariate and

prenatal nicotine exposure outcome.

(DOC)

Table S2 Comparison of those included in analyses and the overall ALSPAC cohort. Data are presented as either percentages or mean (SD). (DOC)

Acknowledgments

We thank all the families and participants who took part in these studies.

We also wish to acknowledge the midwives for their help in recruiting

them, and the whole ALSPAC team, which includes interviewers,

computer and laboratory technicians, clerical workers, research scientists,

volunteers, managers, receptionists and nurses. We thank Dr. David E.

Odd for useful clarifications on the resuscitation data. We are also grateful

to the Yale Center for Genome Analysis, specifically Irina Tikhonova and

Anna Rogers, for genotyping services.

Author Contributions

Conceived and designed the experiments: JDE NRP KC JRG. Performed

the experiments: JDE NRP KC JRG. Analyzed the data: JDE. Contributed

reagents/materials/analysis tools: LLM KM SMR JBT. Wrote the paper:

JDE JRG.

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