The Genetic and Environmental Origins of Language Disability and Ability

Frank M. Spinath, Thomas S. Price, Philip S. Dale, and Robert Plomin

This study investigated whether genes affect language impairment to the same extent as they affect differences inlanguage ability following up an earlier study of 579 four-year-old twins with low language performance andtheir cotwins (Viding et al., in press). The present study selected low-language twins from 6,963 pairs of twinsfrom the Twins Early Development Study assessed for vocabulary and grammar by their parents at 2, 3, and 4years of age. For impaired groups corresponding to the lowest scoring 5% and 10% at each age, twin concordancesand model-fitting analyses indicated substantial genetic influence on the mean difference between affectedchildren and the population (h2g), generally higher than for individual differences for the entire sample (h2).

The Twins’ Early Development Study (TEDS) in-volves a representative community sample of twinsborn in 1994 and 1995 in England and Wales whohave been screened by their parents for language,cognitive, and behavior problems at 2, 3, and 4 yearsof age (Trouton, Spinath, & Plomin, 2002). Four ear-lier twin studies of language disorders in childrensuggested substantial genetic involvement in lan-guage impairment (Stromswold, 2001). Althoughtheir samples were relatively small (a total of 191monozygotic [MZ] and 101 dizygotic [DZ] pairsacross all four studies), results were consistent eventhough the twins were of a wide age range extendingfrom middle childhood through adulthood and werechosen for the study largely through referrals fromclinics. Clinic-referred samples, however, may not berepresentative of language problems, especially inyoung children (Plomin, Price, Eley, Dale, & Ste-venson, 2002; Toppelberg & Shapiro, 2000).

Previous TEDS analyses suggested substantial ge-netic influence on low vocabulary for the 1994 cohortat 2 years (Dale, Simonoff, et al., 1998) and at 3 years(Eley, Dale, Bishop, Price, & Plomin, 2001). Analyses ofindividual differences in the normal range indicatedonly modest genetic influence on vocabulary at 2 yearsfor the 1994 cohort (Price et al., 2000), in line with the

finding that general cognitive ability shows onlymodest heritability in infancy and early childhoodwith increasing heritability in middle childhood andadolescence (McGue, Bouchard, Iacono, & Lykken,1993; Spinath, Ronald, Harlaar, Price, & Plomin, 2003).

In a recent study, a subsample of 579 four-year-oldTEDS twins with low language performance andtheir cotwins were tested in their homes at 4 years ofage on a battery of language measures, and modestheritability was found for individual differences inthe normal range (Viding et al., in press). In thisstudy, language impairment was defined by scoresbelow the 15th percentile on a general factor derivedfrom an extensive language test battery administeredin the family homes by trained personnel. Languageimpairment of different degrees of severity was in-vestigated by using multiple cutoffs below the 15thpercentile. DeFries-Fulker (DF) extremes analyses,an approach that combines dichotomous diagnosesand quantitative traits by assessing the extent towhich the mean quantitative trait score of cotwins ofaffected children (often called probands) differs fromthe population mean on the quantitative trait (De-Fries & Fulker, 1985, 1988), indicated that languageimpairment as measured by the general languagefactor is under strong genetic influence. In addition,group (differences) heritability (h2g), the extent towhich the quantitative trait score difference betweenthe probands and the population is due to geneticfactors, showed an increasing trend (from 38% to76%) as a function of severity of language impair-ment. The study employed a recently developedmodel-fitting implementation of the basic DF modelallowing the inclusion of opposite-sex twins (DZO)in a sex-limitation model (Purcell & Sham, 2003).Although more boys were impaired than girls, thisstudy found neither significant quantitative nor

r 2004 by the Society for Research in Child Development, Inc.All rights reserved. 0009-3920/2004/7502-0014

Frank M. Spinath, Department of Psychology, University ofBielefeld; Thomas S. Price, The Wellcome Trust Centre for HumanGenetics; Philip S. Dale, Columbia University; Robert Plomin,Social Genetic and Developmental Psychiatry Research Centre,Institute of Psychiatry.The authors are indebted to the parents of the twins in the

Twins’ Early Development Study (TEDS) for making the studypossible. TEDS is supported by a program grant from the UKMedical Research Council to the Institute of Psychiatry, King’sCollege London.Correspondence concerning this article should be addressed to

Frank M. Spinath, University of Bielefeld, Department of Psy-chology, P.O. Box 10 01 31, 33501 Bielefeld, Germany. Electronicmail may be sent to fspin@uni-bielefeld.de.

Child Development, March/April 2004, Volume 75, Number 2, Pages 445 – 454

qualitative differences between boys and girls ingenetic and environmental etiologies.

The goal of the present study was to build on andconfirm pevious TEDS research, particularly thefindings reported by Viding et al. (in press). For thefirst time, data from the entire TEDS sample, that is,from both cohorts and from all three ages, wereavailable for analysis spanning the full range ofverbal ability instead of limiting the analyses to aselected low group. This data set enabled us tocompute a language composite score that includedgrammar as well as vocabulary assessed by parentsthat was aggregated across measurements at ages 2,3, and 4. Availability of data from multiple assess-ments early in life is particularly helpful in studieson language delay because genetic influences may bestronger for language problems that persist beyondage 2 than transient difficulties (Bishop, Price, Dale,& Plomin, 2003). The present article can be regardedas a final and comprehensive report from TEDS onthe etiology of language ability and disability inearly childhood addressing the question of whethergenes affect language impairment in the same way asindividual differences in language ability through-out the normal distribution.

On the basis of our preliminary analyses and theresults of other twin studies, we predicted that lan-guage disability would yield substantial group her-itability at all three years and that group heritabilitywould be greater than individual differences herita-bility for the entire sample. Sex differences in geneticand environmental parameter estimates have notbeen investigated systematically in large twin sam-ples. Our expectations were based on an earlier TEDSanalysis of individual differences in vocabulary atage 2 for the 1994 cohort that suggested greater heri-tability for boys than for girls and some sex-specificgenetic effects (Galsworthy, Dionne, Dale, & Plomin,2000). Similar results were suggested in the analysesof the subsample of TEDS twins tested in their homesat 4 years of age (Viding et al., in press) even thoughthese differences were not significant.

Because this article reports findings that build onand replicate previous research, the presentation iscondensed, with more complete details (e.g., aboutsample, analyses) available in other publications.

Method

Sample

A detailed description of the sample can be foundin Trouton et al. (2002). Families were excluded ifzygosity could not be ascertained or if one twin had

severe medical or genetic problems or severe peri-natal problems. Exclusions were also made if book-lets were incomplete or were returned later than 6months, and if English was not the first languagespoken in the home. The final sample consisted of6,963 families with twins who had participated in atleast one measurement, made up of 2,351 pairs of MZtwins, 2,322 pairs of same-sex DZ (DZS) twin pairs,and 2,290 pairs of DZO twin pairs from the 1994 and1995 cohorts. The equal numbers among the threezygosity groups is an indication of representativenessbecause selection effects in volunteer twin samplesusually favor disproportionate numbers of MZ twins(Lykken, Tellegen, & DeRubeis, 1978). A total of 1,943twin pairs had participated in all three measure-ments, allowing the computation of an aggregatedlanguage score across ages 2, 3, and 4. This sub-sample was made up of 657 pairs of MZ twins, 648pairs of DZS twins, and 638 pairs of DZO twins.

Measure and Procedures

Verbal performance was assessed using age-appropriate vocabulary and grammar scales from theMacArthur Communicative Development Inventory:UK Short Form (MCDI:UKSF). This measure is anabbreviated and anglicized adaptation of the Mac-Arthur Communicative Development Inventory(MCDI), a widely used measure of early languagedevelopment (Dale, Reznick, & Thal, 1998). It hasbeen demonstrated that the MCDI has excellent in-ternal consistency (average alpha values across threevocabulary scales5 .96) and test – retest reliability(average test – retest correlations for the infant formand a test – retest lag of 1.35 months5 .90), as well asconcurrent validity with tester-administered mea-sures (Fenson et al., 1994). The MCDI:UKSF has sim-ilarly been found to offer a valid and cost-effectivemeasure of early linguistic development that ad-ditionally is suitable for use with U.K. samples.

Vocabulary production is assessed in theMCDI:UKSF by means of an item checklist askingparents to report on their children’s production ofroot words. A composite score is calculated bysumming the number of words checked. Grammar isassessed in the MCDI:UKSF through parental reportsabout their children’s sentence complexity. Detailedinformation about the measures and their validity isreported in Spinath et al. (2003).

Analyses

Significant positive correlations between vocabu-lary production and grammar observed across ages

446 Spinath, Price, Dale, and Plomin

(mean r5 .55, po.001) justified the computation of acombined verbal score (V) averaging the two z-standardized scores at each age. In addition to sep-arate V scores at 2, 3, and 4 years, we computed anaggregate V score (Vagg) by taking the mean of thethree V scores across 2, 3, and 4 years for participantswith complete data on all measurement occasions.Although the sample size with complete data at 2, 3,and 4 years is reduced, we computed this aggregatemeasure as a more reliable index of overall languageability that is less affected by fluctuation due tochildren who experience transient delay at somestage during the years under study. In the extremesanalyses, this average score allowed us to selectchildren who were in the lowest 5% and 10% of thedistribution reflecting a stable tendency to score low.Although we do not suggest a priori that the lowgroups we identify by chosing these cutoffs at 5%and 10% are qualitatively distinct from the rest of thedistribution, taking two cutoffs gives an indication ofthe importance of the severity of disability in dem-onstrating any differences in DF extremes analysis.

Before genetic analyses, the covariance on the Vmeasure due to the effects of age and sex was re-moved by linear regression (McGue & Bouchard,1984). Controlling for linear effects of age and sex doesnot constrict sex-limitation analyses to be reportedlater, which can be viewed as an interaction effect ofsex and zygosity. A reflected square-root transforma-tion was applied to the 3- and 4-year vocabularymeasures to allow for the effects of upward skew inthe distributions of scores that would otherwise vio-late the assumption of normality in our analyses.

Genetic Individual Differences Analyses

Genetic analyses across the whole range of quanti-tative trait scores were used to estimate individualdifferences heritability for Vagg as well as for the sepa-rate V scores at each age. For same-sex twins rearedtogether, their resemblance for a measured trait can bedue to influences from additive genetic (A) or shared(or common) environmental (C) factors. Genetic relat-edness is 1.0 for MZ twins, who are genetically iden-tical, and 0.5 for DZ twins, who share half theirsegregating genes. The relatedness for shared environ-mental influences is assumed to be 1.0 for both MZ andDZ twin pairs who grow up in the same family. Non-shared environmental influences (E) contribute to dif-ferences between twins. Our analysis of individualdifferences employed variations on the full ACE modelthat apportions the phenotypic variance into thesethree components, assuming no effects of nonadditivegenetics, nonrandom mating, or gene–environment

interaction. The ACEmodel for same-sexmale (MZM–DZM) and female (MZF–DZF) twins is shown as apath model in the top two thirds of Figure 1.

We tested for sex differences in the genetic andenvironmental parameter estimates by comparingthe fit with the data of a series of nested models. The

rC*

.5 rG*

A C E

Female Twin

e2f c2fa2f

E C A

Male Twin

a2mc2me2m

DZO twins

1.0

MZ = 1.0,DZ = .5

A C E

Male Twin

E C A

Male Twin

a2mc2me2m

MZM/DZM twins

A C E

Female Twin

e2f c2fa2f

E C A

Female Twin

a2fc2fe2f

MZF/DZF twins 1.0

MZ = 1.0,DZ = .5

e2mc2ma2m

Figure 1. Path diagrams for the full sex-limitation model illus-trating parameters estimated in five groups of twins:MZM5monozygotic male pairs, MZF5monozygotic femalepairs, DZM5dizygotic male pairs, DZF5dizygotic female pairs,DZO5 opposite-sex dizygotic pairs. a2m, c2m, and e2m5 additivegenetic, shared, and nonshared environmental estimates for males,respectively; a2f, c2f, and e2f5 additive genetic, shared, and non-shared environmental estimates for females, respectively;rG5genetic relatedness; rC5 shared environmental relatedness.�Either rG or rC are estimated; that is, if rG is estimated, rC is fixedto 1.0, and if rC is estimated, rG is fixed to 1.0 (Neale &Maes, 1999).

Origins of Early Language Disability and Ability 447

modeling is based on dividing the data into fivegroups: MZM twins, MZF twins, DZM twins, DZFtwins, and DZO twins. In the most general model,called the full sex-limitation model (Neale & Maes,1999), parameters for genetic and environmental in-fluence are estimated separately for males andfemales. These differences are referred to asquantitative sex differences because they reflect dif-ferences in the relative magnitude of influences. Inaddition, between opposite-sex twins either thecoefficient of genetic relatedness (rG) or the coeffi-cient of shared environmental relatedness (rC) can beallowed to vary below the values ascribed to them inDZS twins. The two coefficients (rG and rC) cannot beestimated simultaneously because they account forthe same distinct pattern in covariance matrices,which is greater dissimilarity of DZO twins com-pared with DZS twins. In other words, greater dis-similarity among DZO twins compared with DZStwins is attributed to qualitative differences in ge-netic or shared environmental factors operating be-tween the sexes. An example for qualitative sexdifferences involves genetic influences that affectindividual differences in one sex but not the other.The bottom panel of Figure 1 shows the parametersestimated in the full sex-limitation model for theDZO group.

After testing the fit of the full model, a series ofnested models can be evaluated by comparing theirmaximum-likelihood fit with the fit of the full model,including (a) a common effects sex-limitation model,(b) a scalar effects sex-limitation model, and (c) a nullmodel (see Galsworthy et al., 2000, for details).

The parameters depicted in Figure 1 and their 95%confidence intervals were estimated by fitting themodels to variance– covariance matrices using Mx(Neale, 1997). Because the present study employedlarge samples, we used the root mean square errorof approximation (RMSEA) to judge the general fitof the models because RMSEA is relatively in-dependent of sample size. The comparative fitamong the four models was tested by likelihood ra-tio chi-square tests (LRT; Neale & Maes, 1999).

Genetic Extremes Analyses

We used a 5% and a less severe 10% cutoff withthe distribution of our uncorrected verbal measure toidentify children with low language ability. Selectionwas based on the uncorrected verbal score to allowrepresentative gender proportions in the low groupinstead of selecting equal numbers of boys and girls.Probandwise concordance (the ratio of the number ofprobands in concordant pairs to the total number of

probands) was calculated rather than pairwise con-cordance (ratio of concordant pairs to total pairs)because probandwise concordance represents therisk that a cotwin of a proband is affected (Plomin,DeFries, McClearn, & McGuffin, 2001).

The basic DF extremes analysis regression model(DeFries & Fulker, 1985) and the extended model-fitting approach developed by Purcell and Sham(2003) are described in detail in Viding et al. (inpress). Because this new model-fitting approach thatallows multiple group analyses at the extreme hasnot yet been extended to include longitudinal data,we report separate analyses at each age as well as foran aggregate score across ages 2, 3, and 4.

Sex differences were tested in a similar manner asin individual differences analyses. The full sex-lim-itation model was compared with a no-effects modelthat fixed rG and rC to 1.0 in the DZO group andconstrained parameter estimates to be equal formales and females. We did not test additional mod-els because the reduced sample sizes in extremesanalysis limits the power to detect differences be-tween intermediate models.

To compare the results of the extreme group andindividual differences analyses, the following sta-tistical procedure was adopted: Differences in theresults were treated as statistically significant whenthe point parameter estimates for the individualdifferences analysis fell outside the 95% confidenceintervals of the estimate in the extreme group anal-ysis. Simulation procedures were used to evaluatethe plausibility of this approach. Detailed informa-tion on these simulations are available from the firstauthor.

Results

Phenotypic Analyses

Analyses of variance (ANOVAs) indicated that theoverall effect of sex and zygosity on our verbalmeasure was small at all ages. Females showedhigher verbal scores across all three ages but thismean difference tended to diminish with increasingage. MZ twins scored lower than DZ twins. Thelargest effect of sex and zygosity was found at age 2when sex and zygosity together accounted for 5% ofthe variance of our verbal measure.

Age-to-age correlations for language ability werehigh and of similar magnitude. One-year stabilitiesfrom ages 2 to 3 and from ages 3 to 4 were r5 .62 andr5 .64, respectively. The correlation between ages 2and 4 was still substantial (r5 .52). All stability cor-relations were significant (po.001).

448 Spinath, Price, Dale, and Plomin

Genetic Individual Differences Analyses

Twin similarity coefficients (intraclass correlations)for same-sex male and female MZ and DZ twin pairswere highly consistent across the three ages. MZcorrelations (ranging between .87 for females at age 4to .95 for males and females at age 2) were greaterthan DZ correlations (ranging from .72 for males atages 3 and 4 to .82 for males at age 2), suggestinggenetic influence. DZ correlations were greater thanhalf the MZ correlations, indicating shared environ-mental influences. DZS and DZO twins also yielded aconsistent pattern in that DZS twin similarity washigher at all ages compared to DZO twin similarity(ranging from .66 at age 4 to .75 at age 2). We expectedthese differences to be reflected in our sex-limitationmodeling as the sample size of the present studyprovided the power to address even such relativelysmall differences between the sexes.

The full sex-limitation model and its reducedvariants were tested and compared as described inthe Analyses section. Results for the full model in-dicated a good general fit for Vagg as well as sepa-rately for V at ages 2, 3, and 4 judged by the RMSEAindex. In no case did the upper limit of the con-fidence intervals for RMSEA exceed 0.05. For Vagg

and V at ages 2 and 4, the full sex-limitation model(full rG or rC) that allowed all parameters to be esti-mated separately for male and female twins yieldedthe best fit by direct comparison with the nestedmodels (LRT). Only once in 12 model comparisonsdid a reduced model (common effects model at age

3) fit the data equally well, LRT(df5 1)5 1.09, ns. Allother model comparisons favored the full sex-lim-itation model. Because of this and because the pointestimates from the common effects model at age 3were highly similar to those from the full sex-lim-itation model, Table 1 presents the parameter esti-mates from the full sex-limitation models at ages 2, 3,and 4 and for the verbal aggregate. Confidence in-tervals are listed parenthetically in the table.

Quantitative parameter estimates for additivegenetic influences (a2m/f), shared environmental in-fluences (c2m/f), and nonshared environmental in-fluences (e2m/f) were similar across ages. For theaggregate (Vagg), the full model indicated moderategenetic influence of 0.27 in males and 0.18 in females.Shared environmental influences were substantialand nonshared environmental influences were neg-ligible. In no analysis reported in Table 1 did theconfidence intervals of genetic and shared environ-mental estimates overlap, indicating that shared en-vironmental influences explained significantly moreindividual variance than did genetic effects at eachage. In the DZO group, estimates for genetic relat-edness (rG) and environmental correlations (rC)yielded values below 1.0 at ages 2 and 4 and for theaggregate reflecting qualitative sex differences.

To summarize the model-fitting results for in-dividual differences, the full sex-limitation modelsfit the data best, indicating consistent and moderategenetic influences at all ages that tended to be greaterin males (0.27–0.34) than in females (0.18–0.23).Genetic influences were numerically greater for boys

Table 1

Parameter Estimates From the Full Sex-Limitation Model Fit to Language Ability Data

Males Females

Gen. – env.

relatedness

a2m c2m e2m Varm a2f c2f e2f Varf rG rC

Vagg .27 .69 .04 1.06 .18 .76 .06 0.92 .56 .94

N5 1,941 (.21 – .33) (.62 – .74) (.04 – .05) (.14 – .24) (.71 – .80) (.05 – .07) (.20 – .87) (.91 – .98)

V2 .27 .69 .05 1.00 .18 .77 .06 0.99 .61 .93

N5 4,092 (.23 – .31) (.64 – .73) (.04 – .05) (.13 – .23) (.72 – .81) (.05 – .07) (.40 – .79) (.89 – .96)

V3 .34 .57 .08 1.04 .23 .67 .11 0.94 .90 .98

N5 4,097 (.29 – .41) (.51 – .63) (.07 – .09) (.18 – .28) (.61 – .71) (.09 – .12) (.67 – 1.0) (.93 – 1.0)

V4 .29 .59 .12 1.09 .19 .66 .15 0.89 .50 .93

N5 3,995 (.23 – .36) (.52 – .64) (.11 – .14) (.13 – .25) (.62 – .71) (.13 – .17) (.13 – .80) (.89 – .96)

Note. a2m/f5 additive genetic influences (heritability); c2m/f5 shared environmental influences; e2m/f5nonshared environmental in-fluences; Varm/f5predicted variance in males/females; rG, rC5 estimated genetic and shared environmental relatedness among opposite-sex DZ twins. Confidence intervals are listed in parentheses in the table. The full sex-limitation model was tested against: (a) the commoneffects sex-limitation model, (b) the scalar effects sex-limitation model, and (c) the null model. Likelihood ratio tests (LRTs) at age 2 are: (a)20.92 (df5 1, po.01), (b) 24.15 (df5 3, po.01), and (c) 24.15 (df5 4, po.01). LRTs at age 3 are: (a) 1.09 (df5 1, ns), (b) 15.72 (df5 2, po.01),and (c) 26.00 (df5 3, po.01). LRTs at age 4 are: (a) 11.72 (df5 1, po.01), (b) 23.79 (df5 3, po.01), and (c) 66.76 (df5 4, po.01). LRTs for theverbal aggregate are: (a) 8.36 (df5 1, po.01), (b) 21.73 (df5 3, po.01), and (c) 34.67 (df5 4, po.01).

Origins of Early Language Disability and Ability 449

in all analyses; these differences were significant atage 3 and almost significant at age 2. Shared en-vironmental influences were substantial, rangingfrom 0.57 to 0.69 for boys and from 0.66 to 0.77for girls. Nonshared environmental influences ex-plained a small portion of the variance regardless ofgender, although we found a significant increaseacross age in the estimates for nonshared environ-ment or measurement error.

Genetic Extremes Analyses

As expected, almost twice as many boys enteredthe group of low-language-ability children both atthe 5% and 10% cutoffs. For the verbal aggregate anda 5% cutoff, for example, 65.7% of our probands weremale and 34.3% were female. At the 10% cutoff, theproportions of males and females were 61.6% and38.4%, respectively.

Probandwise twin concordances for low languageability at 5% and 10% cutoffs for Vagg and separatelyat ages 2, 3, and 4 showed a clear pattern with sub-stantially greater MZ twin concordance comparedwith DZS twins regardless of gender, indicating ge-netic influences on the risk that cotwins of probandsare themselves affected. At the 5% cutoff, MZ twin

concordance averaged 0.75 (0.63–0.82) across agegroups and gender, whereas DZS twin concordancereached 0.48 (0.38 –0.56) and DZO twin concordanceaveraged 0.40 (0.33 –0.55). For the aggregate mea-sure, a weighted average of the probandwise twinconcordance at the 5% cutoff yielded 0.86 for MZtwins and .52 for DZS twins. Taking these con-cordances as an example, this means that if one MZtwin is diagnosed as low in language ability there isan 86% chance that the cotwin is also low in lan-guage ability. For DZS twins, the risk reduces to 52%.Across age, differences between MZ and DZ twinconcordances tended to become smaller when the10% cutoff was used, suggesting a trend towardless genetic influence for less severe cutoffs. In gen-eral, concordances for DZO twins were lower thanfor DZS twins, suggesting possible gender differ-ences in the etiology of low language ability.This difference was particularly pronounced at ages3 and 4.

Results of our DF extremes analyses includingDZO twins for the verbal aggregate and separately atages 2, 3, and 4 are presented in Table 2. The tableincludes parameter estimates from the best fittingmodel in the sex-limitation extremes analysis andconfidence intervals (in parentheses) for the 5% and

Table 2

Model Comparisons and Parameter Estimates from DeFries-Fulker Extremes Analyses Including Opposite-Sex Twins for Vagg and V at Ages 2, 3, and 4

Males Females DZO

LRT(df) p h2gm c2gm e2gm h2gf c2gf e2gf rG rC

Vagg 5% null 3.12(3) ns .49 .47 .04 .49 .47 .04 1.0 1.0

(.29 – .69) (.31 – .63) (.00 – .11) (.29 – .69) (.31 – .63) (.00 – .11)

10% full 10.13(3) o.05 .41 .52 .07 .17 .76 .07 .11 .81

(.21 – .64) (.32 – .69) (.00 – .14) (.00 – .45) (.54 – .94) (.00 – .16) (.00 – 1.0) (.67 – 1.0)

V2 5% null 0.66(3) ns .34 .62 .04 .34 .62 .04 1.0 1.0

(.17 – .51) (.50 – .75) (.00 – .10) (.17 – .51) (.50 – .75) (.00 – .10)

10% null 0.78(3) ns .33 .64 .03 .33 .64 .03 1.0 1.0

(.22 – .43) (.56 – .72) (.00 – .07) (.22 – .43) (.56 – .72) (.00 – .07)

V3 5% full 8.41(3) o.05 .55 .39 .06 .62 .31 .06 .55 .62

(.35 – .76) (.22 – .57) (.00 – .12) (.33 – .91) (.07 – .56) (.00 – .15) (.00 – 1.0) (.39 – 1.0)

10% null 2.00(3) ns .54 .37 .09 .54 .37 .09 1.0 1.0

(.43 – .66) (.28 – .45) (.05 – .13) (.43 – .66) (.28 – .45) (.05 – .13)

V4 5% full rG 10.13(3) o.05 .38 .54 .08 .34 .50 .16 .00�

(.15 – .59) (.37 – .73) (.00 – .16) (.08 – .58) (.08 – .55) (.31 – .71) (.00 – .52)

5% full rC .32 .59 .09 .25 .58 .17 .63

(.08 – .57) (.39 – .79) (.01 – .17) (.00 – .55) (.33 – .82) (.07 – .27) (.48 – 1.0)

10% full 11.99(3) o.05 .43 .46 .11 .39 .50 .11 .30 .70

(.33 – .67) (.28 – .56) (.03 – .14) (.30 – .73) (.20 – .55) (.04 – .18) (.00 – .75) (.57 – .85)

Note. h2gm/f5 group heritability; c2gm/f5group shared environmental influences; e2gm/f5group nonshared environmental influences;DZO5 opposite-sex dizygotic twins; LRT(df )5 likelihood ratio test and degrees of freedom in the comparison; rG, rC5 estimated geneticand shared environmental relatedness among opposite-sex DZ twins.�Genetic relatedness for DZO twins was estimated at its lower bound causing slight differences in the estimates of the full sex-limitation rGversus rC models.

450 Spinath, Price, Dale, and Plomin

the 10% cutoffs at ages 2, 3, and 4 and for the verbalaggregate. Additionally, LRTstatistics and associatedp values are provided for the comparison betweenthe full and null models. In the null model, male andfemale estimates were equated, and genetic (orshared environmental relatedness) in DZO werefixed at 1.0.

We found evidence for moderate to substantialgenetic influences on low language ability at all agesranging from 0.37 to 0.55 in boys and from 0.25 to0.62 in girls when a 5% cutoff was applied. For ex-ample, for the aggregate score using the 5% cutoff,the group heritability estimate was 0.49 for boys and0.49 for girls. In contrast, the individual differencesheritability estimates were 0.27 for boys and 0.18 forgirls (Table 1). We compared 16 group heritabilityestimates (h2g) from the best fitting extremes modelat 5% and 10% with the heritability estimates fromthe individual differences analyses separately formales and females, 2 (gender) � 2 (cutoffs) � 4 (ages;[2, 3, 41agg]5 16 comparisons). In 15 of 16 com-parisons, the group heritability estimate was nu-merically higher than the individual differencesheritability. From the 12 independent comparisons atages 2, 3, and 4, 2 (gender) � 2 (cutoffs) � 3 (ages; [2,3, 4]5 12 comparisons), all group heritabilities weregreater than the respective individual differencesheritability, a highly significant result pattern(po.001) according to a chi-square test of equalprobability (Bortz, 1993). Testing the significance ofthe difference by comparing the lower bound of the

h2g confidence intervals with the correspondingheritability point estimates yielded 9 (out of 16) sig-nificant differences.

One important finding from our analyses of in-dividual differences etiology was that shared en-vironmental influences explained a major proportionof the phenotypic variance among children’s lan-guage ability. Table 2 indicates that group sharedenvironmental effects were also of major importancewhen the etiology of language delay was in-vestigated. Mirroring the increased importance ofgenetic influences at the extreme, group shared en-vironmental effects were lower than estimates fromindividual differences analyses, resulting in over-lapping confidence intervals for h2g and c2g esti-mates in 13 of 16 comparisons. A summary of theresults from our analyses is depicted graphically forthe verbal aggregate in Figure 2.

To summarize the genetic extremes analyses forgroup versus individual heritability, we found arange of group heritability estimates at the extremes(depending on age group and cutoff), but in almostall cases the individual heritability fell outside theconfidence intervals of the group heritability. Groupheritability at the extremes in these cases was alwayshigher than individual heritability. With regard togender effects, we have put forward a range ofmodels to fit the data, either including gender effectsor restricting them in various ways. In the individualdifferences analyses, the model that included gendereffects fit the data significantly better than models

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Genetic influences Shared Environment Nonshared Environment

M F M F M F

5% 10% 100%

Figure 2. Individual differences etiology (100%) and group etiologies (5% and 10% cutoff) for the verbal aggregate (Vagg) from the bestfitting models depicted separately for males (M) and females (F).

Origins of Early Language Disability and Ability 451

that did not (see p values in Table 1). Althoughgender effects were small, this comparison showsthat they were significant. Where these effects werefound, they indicate that the role of genes is strongerfor boys than for girls.

Discussion

Deficits in language learning represent a problem ofhigh cost to individuals with learning disabilitiesand to society. Most children classified as havinglearning disabilities have basic deficits in oral andwritten language (Hall & Moats, 1999). Althoughmany children grow out of early language problems,longitudinal studies have demonstrated a strikingconvergence between preschool language impair-ments and subsequent reading impairments, in-cluding dyslexia (Leonard, 1998). Nevertheless, theepidemiology of early language problems has re-ceived relatively little attention.

The present study unequivocally demonstratesthe importance of genetic influences in the devel-opment of early disorders of spoken language, con-firming evidence from four previous twin studies ofsubstantial genetic influence on language disability.These results extend previous research in severalways: to multiple measurements in early childhood,to community samples, and to parental-screeningmeasures of vocabulary and grammar. Previous twinstudies have yielded MZ and DZS concordances ofabout 85% and 50%, respectively (Stromswold, 2001).Using a 5% cutoff, the present study found similarconcordances (weighted average scores): 86% and52%, respectively, for scores aggregated across ages2, 3, and 4. Group heritability for language disabilityat the 5% cutoff using this aggregate score in DFextremes analysis was 49% for boys and 49% forgirls. For the 10% cutoff, group heritability was 41%for boys and 17% for girls. This is a noteworthydifference although the overlapping confidence in-tervals indicate that it is not statistically significant.The direction of the difference, however, is in linewith our general pattern of results, indicating atendency for greater genetic influence in boys.

A second finding was that language disabilitytends to be more strongly under the influence ofgenetic factors than does language ability in thenormal range. A clear pattern of greater group her-itability than individual differences heritability wasevident from the results at ages 2, 3, and 4, althoughnot all the differences reached statistical significance.A similar indication of greater genetic influence onlanguage disability has also been obtained for asubsample of TEDS twins who were tested ex-

tensively in their homes at age 4 (Colledge et al.,2002; Viding et al., in press).

This result, which is unique to language pheno-types in the existing behavioral genetic literature,appears to mark a discontinuity between the causesof development in the normal range and the causesof abnormal development. It might be speculatedthat this evidence is consistent with an account oflanguage disability emphasising difference ratherthan merely delay, a view arguing that intellectualdisability represents a fundamental deficit and thatdevelopment in children with intellectual disabilitiesdiffers qualitatively compared with development innonimpaired children (Anderson, 2001). It should benoted, however, that a more cautious interpretationof the reported difference between group heritabilityand individual differences heritability not necessar-ily implies discontinuity rather than delay.

Concerning comparisons between boys and girls,our results indicate some small sex differences bothfor language disability and for language ability. Oneadvantage of the comprehensive TEDS sample in thisfinal report is that it allows detection of such relativelysmall effect sizes. Incorporating DZO twins in theanalysis also suggested some sex-specific effects,confirming similar results from a preliminary TEDSanalysis (Galsworthy et al., 2000). We interpret theevidence of greater heritability in boys than in girls tomean that some genes associated with language dis-ability and language ability may show stronger effectsin boys than in girls. The evidence of gender-specificinfluences may imply that some genes are associatedwith language disability and ability in just one sex.Alternatively, the environments that foster languageacquisition could differ for boys and girls.

Importance of Environmental Influences

Although we have focused on the interpretationof the genetic results of our study, the greatest effecton language disability and ability in early childhoodis shared environmental influence. We have dem-onstrated that shared environment has the biggesteffect on individual differences in normal languageability, and despite the increased genetic influence atthe low end of the language distribution, there is asubstantial shared environmental contribution tolanguage disability as well, a finding with potentialimplications for intervention. An important directionfor future research is to identify the specific en-vironmental factors responsible for these substantialeffects for language ability and disability. Followinga similar line of reasoning described earlier in rela-tion to genetic links between ability and disability,

452 Spinath, Price, Dale, and Plomin

we predict that the same shared environment effectsaffect ability and disability.

Developmental Trends

An interesting developmental finding for generalcognitive ability is that shared environmental influ-ence declines in importance from childhood to ado-lescence, and heritability increases during thisperiod (McGue et al., 1993). In the present study, wedid not see any clear indication that genetic influ-ences increased with age in a linear fashion fromages 2 to 4, though the focus of the present paper wasnot on developmental trends. It will be interesting tofollow the pattern of genetic and environmental in-fluences as the children grow older. Tester assess-ments at age 7 are under way and we predict that theheritability of verbal abilities will increase and en-vironmental influences will decrease as the partici-pants reach school age. This may come about asshared environmental risk factors interact with per-son-specific influences, perhaps peer group influ-ences, in middle childhood and adolescence. Adirection for future research is to investigate whethersimilar developmental trends occur for languageability and disability. Some research suggests thatshared environmental influence is greater for verbalthan for nonverbal components of intelligence testslater in development (Plomin, Chipuer, & Nei-derhiser, 1994). Thus, although general cognitiveability is heavily influenced by language ability, it ispossible that there may be persistent shared en-vironmental influences specific to language ability.Identification of these effects might suggest sites forenvironmental intervention to prevent early lan-guage delay persisting to language impairment orreading disability later in childhood.

Strengths and Limitations

The use of a large community sample of twins is aclear strength of the present study. The twins inTEDS with low language abilities are likely to be amore representative population of young childrenwith language disadvantages than are clinic sam-ples, who typically exhibit multiple behavioral pro-blems. Choosing cutoffs of 5% and 10% might beconsidered arbitrary given that a clear diagnosticcriterion for calling children who fall below thesecutoffs ‘‘impaired’’ does not exist. We believe that thefact that our results for language impairment are sosimilar to those of previous twin studies helps vali-date the definitions of language disability employedin the current study.

An intrinsic limitation of the twin design is thattwins are slower in language development thansingletons, although this delay diminishes duringchildhood (Rutter & Redshaw, 1991). TEDS datasuggest that at 2 years of age, twins are about 3.5months delayed on average compared with resultson a U.S. sample of singletons for parent-assessedMCDI vocabulary (Dale, Simonoff, et al., 1998).These effects vanish with age: By 4 years, a rep-resentative control group of TEDS twins showedverbal IQ, performance IQ, and full IQ means com-parable to McCarthy norms for 4-year-olds (Colledgeet al., 2002). Moreover, a mean language differencebetween twins and singletons would be unlikely toaffect estimates of heritability given equal variances.A more significant concern is that twin estimates ofshared environmental influence may not generalizebecause twins experience more similar postnatalenvironments than do nontwin siblings. For thisreason we are currently assessing younger siblings ofthe TEDS twins in the same manner using the par-ent-assessed MCDI.

Another limitation of the present study is its focuson a general language scale to assess disability andability. However, factor analyses of the MCDI vocab-ulary and grammar scales justify this decision, as domultivariate genetic analyses that suggest sub-stantial genetic correlations between vocabulary andgrammar (Dale, Dionne, Eley, & Plomin, 2000).

Finally, the present analyses are limited to abilityand disability in language per se rather than the re-lation between language and nonverbal cognitivedevelopment. This issue is especially relevant forlanguage disability because research and clinicalwork focuses on specific language impairment thatexcludes other cognitive impairment, assuming that amore specific diagnosis will be more tractable interms of research and treatment and implying that theetiology of specific language impairment differs fromthe etiology of nonspecific language impairment.

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