Genetic Change and Continuity from Fourteen to Twenty...

Genetic Change and Continuity from Fourteen to Twenty Months: The MacArthurLongitudinal Twin StudyAuthor(s): Robert Plomin, Jerome Kagan, Robert N. Emde, J. Steven Reznick, Julia M.Braungart, JoAnn Robinson, Joseph Campos, Carolyn Zahn-Waxler, Robin Corley, David W.Fulker, J. C. DeFriesSource: Child Development, Vol. 64, No. 5 (Oct., 1993), pp. 1354-1376Published by: Blackwell Publishing on behalf of the Society for Research in Child DevelopmentStable URL: http://www.jstor.org/stable/1131539 .Accessed: 24/08/2011 15:18

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Articles

Genetic Change and Continuity from Fourteen to Twenty Months: The MacArthur Longitudinal Twin Study

Robert Plomin The Pennsylvania State University

Robert N. Emde University of Colorado Health Sciences Center

Julia M. Braungart The Pennsylvania State University

Joseph Campos University of California, Berkeley

Robin Corley and David W. Fulker

University of Colorado, Boulder

Jerome Kagan Harvard University

J. Steven Reznick Yale University

JoAnn Robinson University of Colorado, Boulder

Carolyn Zahn-Waxler National Institute of Mental Health

J. C. DeFries

University of Colorado, Boulder

PLOMIN, ROBERT; EMDE, ROBERT N.; BRAUNGART, JULIA M.; CAMPOS, JOSEPH; CORLEY, ROBIN; FULKER, DAVID W.; KAGAN, JEROME; REZNICK, J. STEVEN; ROBINSON, JOANN; ZAHN-WAXLER, CAR- OLYN; and DEFRIES, J. C. Genetic Change and Continuity from Fourteen to Twenty Months: The MacArthur Longitudinal Twin Study. CHILD DEVELOPMENT, 1993, 64, 1354-1376. Genetic change as well as continuity was investigated within the domains of temperament, emotion, and cognition/language for 200 pairs of twins assessed at 14 and 20 months of age in the laboratory and home. The second year of life is marked by change rather than continuity: correlations from 14 to 20 months averaged about .30 for observational measures of temperament and emotion, about .40 for language measures, and about .50 for mental development. 2 types of genetic change were examined: changes in the magnitude of genetic influence (heritability) and genetic contributions to change from 14 to 20 months. In general, heritability estimates were similar at 14 and 20 months. Evidence for genetic influence on change from 14 to 20 months emerged for several measures, implying that heritability cannot be equated with stability. Analyses of continuity indicated that genetic factors are largely responsible for continuity from 14 to 20 months.

It must be borne in mind that the divergence of development, when it occurs, need not be ascribed to the effect of different nurtures, but it is quite possible that it may be due to the appearance of qualities inherited at birth, though dormant.

[Francis Galton, 1875]

The origins of developmental change Francis Galton (1875), the father of human and continuity of individual differences behavioral genetics, and by Thorndike were the focus of the first twin studies by (1905) and Merriman (1924). The question

The MacArthur Longitudinal Twin Study is supported by the John D. and Catherine T. MacArthur Foundation through its Research Network on Early Childhood Transitions. Dr. Emde is supported by Research Scientist Award 5 K02 MH36808. We thank the families who contrib- uted their time and effort, as well as the many research assistants at the University of Colorado, Harvard University, Yale University, and The Pennsylvania State University who were involved in data collection, behavioral coding, data management, and analysis. Correspondence concerning this article should be sent to Robert Plomin, Center for Developmental and Health Genetics, S-211 Henderson Building, The Pennsylvania State University, University Park, PA 16802.

[Child Development, 1993, 64, 1354-1376. ? 1993 by the Society for Research in Child Development, Inc. All rights reserved. 0009-3920/93/6405-0011$01.00]

Plomin et al. 1355

asked was whether the resemblance of twins changes during development. Although the answer was "not much," little confidence can be placed in these early studies because of their small sample sizes and other design problems (Plomin, 1986).

Although genetic effects seem likely to contribute to continuity, genetically influ- enced traits are not necessarily stable, nor are longitudinally stable traits necessarily hereditary. Two types of genetically mediated change can be investigated from the perspective of quantitative genetic theory. The first type involves the magnitude of genetic effects, indexed by the heritability sta- tistic, which can change during development. The second type involves genetic influence on age-to-age change. Genetic factors can contribute to change from age to age even if heritability remains the same across ages. Such age-to-age genetic change can occur, for example, because the changing developmental context of the child engages different sets of genes for a particular trait at different ages. In other words, developmental changes in the genetic underpin- nings can occur because of changes in the nature of a variable which includes changes in its measurement, validity, and reliability.

Both types of genetic change (i.e., in magnitude of heritability from age to age and in genetic influence on age-to-age change) seem most likely during periods of rapid developmental change such as infancy. The present paper investigates genetically mediated change and continuity as well as environmental sources of change and continuity from 14 to 20 months in the MacArthur Lon- gitudinal Twin Study (MALTS). MALTS is a collaborative longitudinal study of twins that focuses on temperament, emotion, and cognition as assessed in the home and laboratory during the second year of life. A previous paper in this journal (Emde et al., 1992) reported results of MALTS twin analyses at 14 months; the present paper compares results at 14 and 20 months and explores genetic and environmental influences on change and continuity from 14 to 20 months.

Little is known about the role of either type of genetic change during infancy. It is usually assumed that the relative magnitude of genetic influence diminishes as the lives of children diverge due to cascading differences in their experiences. For example, this reasonable view, which implies decreasing heritability during development, has been suggested by lifespan theories of develop-

ment. Nonnormative life events are thought to increase throughout the life span as "significant life events take on a more and more important role in determining the course of human development" (Baltes, Reese, & Lip- sitt, 1980, p. 78). The hypothesis of decreasing magnitude of heritability was officially promulgated in the Soviet Union, where it was decreed that genetic influence has little impact after infancy, at which time cultural influences begin to override the animal in- stincts of our species (Mangan, 1982). The reasonableness of this hypothesis of decreasing heritability makes it especially interesting that the meager extant data on the topic suggest the opposite: when heritability changes, it tends to increase rather than de- crease (Plomin, 1986). Heritability increases most clearly in the realm of mental development from infancy to middle childhood (Fulker, DeFries, & Plomin, 1988). For personality, changes in heritability are some- times seen earlier in the life span but seldom in adulthood (Goldsmith, 1983; Loehlin, 1992a; McCartney, Harris, & Bernieri, 1990; Plomin & Nesselroade, 1990).

Developmental change in the magnitude of heritability involves a change in the proportion of phenotypic variance (individual differences for a measured variable) that can be accounted for by genetic variance. It does not address the process by which that change occurs. Most importantly, levels of heritability can be the same at two ages for different genetic reasons. That is, theoreti- cally, the genes that affect a trait at one age could differ entirely from the genes that affect the trait at another age, but the overall magnitude of genetic effects (heritability) could be the same at the two ages.

The second type of genetic change explores the extent to which genetic effects at one age differ from genetic effects at another age. The simplest approach to this type of genetically mediated change is to analyze change scores. For example, each individual's change score can be used to calculate identical and fraternal twin correlations that can be compared in the usual manner to estimate heritability of change scores. Find- ing genetic influence on age-to-age change scores implies that genes contribute to developmental change.

Genetically mediated change from age to age is not merely the flip side of genetic continuity. That is, although traits can show genetic contributions to both change and continuity, it is also possible that genetic in-

1356 Child Development

fluences on a trait at two ages largely contribute to change but not continuity or to continuity but not change. The essence of a twin analysis of cross-age continuity is the cross-twin correlation, that is, the correlation of one twin's score at age 1 and the co-twin's score at age 2. A genetic contribution to continuity is suggested to the extent that such cross-twin correlations are greater for identical twins than for fraternal twins.

These simple approaches to genetic change and continuity are related to more general developmental genetic models that simultaneously analyze genetic contributions to covariance between ages and take into account heritability at both ages as well as phenotypic stability between ages (Boom- sma, Martin, & Molenaar, 1989; Hewitt, Eaves, Neale, & Meyer, 1988; Loehlin, Horn, & Willerman, 1989; Phillips & Fulker, 1989). In the present paper, we emphasize the simpler analyses of change and continuity and then show that more comprehensive model-fitting approaches yield similar conclusions.

Genetic analyses of age-to-age change and continuity require longitudinal genetic designs and, for this reason, reports of such analyses are rare. Nonetheless, evidence to date suggests that heredity contributes to genetic change as well as to continuity, especially in infancy. Most well known are analyses of age-to-age profiles of "spurts and lags" from the Louisville Twin Study (LTS; Wil- son, 1983). The familiar LTS figures of spurts and lags showing greater synchro- nicity for identical twins than for fraternal twins illustrate genetic contributions to change in infancy for temperament (Ma- theny, 1983, 1989) and mental development (Wilson, 1983). After infancy, genetic continuity appears to overwhelm genetic change for both temperament (Plomin & Nessel- roade, 1990) and mental development (De- Fries, Plomin, & LaBuda, 1987).

For these reasons, we expected to find evidence for genetic mediation of change as well as genetic mediation of continuity during infancy. Our previous paper showed significant genetic influence on many of the di- verse MALTS measures of temperament, emotion, and cognition at 14 months (Emde et al., 1992). In the present paper, we examine the extent of genetic change and continuity from 14 to 20 months, a dramatic developmental turning point that marks the

Plomin et al. 1357

of monozygotic (MZ) was made. When two or more features were only somewhat similar (score of 4 or 5), the classification of dizygotic (DZ) was made. In the present analyses, only twins with a consensus endorsement of 90% among raters were used. Zygosity of five twin pairs whose consensus endorsement was ambiguous was de- termined by analysis of genetic markers in blood. The first 100 pairs of monozygotic (MZ) and 100 pairs of dizygotic (DZ) twins who met these criteria and were assessed at both 14 and 20 months were selected for the present analysis.

Procedure At 14 and 20 months, twins and their

mothers were visited at home by two female examiners. One to 3 weeks later, the twin pair was brought by the mother to the laboratory at the Institute for Behavioral Genetics in Boulder. Each visit was completed in less than 3 hours. A 45-min maternal interview was conducted over the phone, usually between home and laboratory visits. Question- naires were given to the parents at the home visit and collected at the laboratory visit. During these visits, multiple observational measures were obtained within the domains of temperament, emotion, and cognition/ language. Details of the procedures are described elsewhere (Emde et al., 1992; Plomin et al., 1990).

Measures The measures used at 20 months are the

same and scored the same as those used at 14 months, which are described in detail by Emde et al. (1992). Only a brief description of each measure is included below. Al- though the measures were designed to be similar at 14 and 20 months, they may not be equally sensitive or valid at both ages, and this may be a source of apparent genetic change from age to age. In other words, conclusions drawn concerning genetic change from age to age were limited to the specific measures at each age.

Temperament.-Measures of temperament include observational measures of behavioral inhibition and shyness, parental ratings of temperament, and tester ratings on the Infant Behavior Record (Bayley, 1969). As in previous work by Kagan, Reznick, Snidman, and their colleagues (e.g., Kagan, Reznick, & Snidman, 1988), behavioral inhibition was indexed by averaging Z-score val- ues for seven measures observed from videotape, such as latency to leave mother upon

entering a playroom (Robinson, Kagan, Reznick, & Corley, 1992). An unrotated first principal component score was used as a composite measure of shyness derived from ratings of videotape recordings of the children's reactions during the first 5 min of the examiners' arrival in the home and the children's entry into the laboratory following a procedure developed by Plomin and Rowe (1979). Both parents rated each child using a modified version (Buss & Plomin, 1984) of the Colorado Childhood Temperament In- ventory (CCTI; Rowe & Plomin, 1977), and scores were averaged across mothers and fa- thers. Examiners used the Infant Behavior Record (IBR; Bayley, 1969) to rate each child's behavior while the Bayley mental scales (Bayley, 1969) were administered and again during the non-Bayley portion of the home visit. IBR items are aggregated on three scales as suggested by Matheny (1980): Affect-Extraversion, Activity, and Task Orientation.

Emotion.-Time-sampled ratings of the child's strongest positive and negative affect were made from videotape recordings of the children during administration of the Bayley test and during free play. The average of these strongest positive and negative affects was computed as measures of positive and negative hedonic tone. The overall mood during each episode was rated on a 7-point scale and averaged. Empathy was assessed using a modification of a scheme by Zahn- Waxler and her colleagues (Zahn-Waxler, Radke-Yarrow, & King, 1979; Zahn-Waxler, Robinson, & Emde, 1992). A composite of several ratings of children's cognitive, af- fective, and behavioral responses to five empathy probes administered in the home responses and in the laboratory was formed based on an unrotated first principal component of these measures. A reactivity composite was formed from an unrotated first principal component based on ratings of children's videotaped responses to restraint and toy re- moval. Expression of discrete emotions was rated by mothers using the Differential Emotions Scale (DES) as modified by Emde and colleagues (Fuenzalida, Emde, Panna- becker, & Stenberg, 1981).

Cognition and language.-Measures in this domain include two standard measures, the Mental Development Index (MDI) of the Bayley Scales of Infant Development (Bayley, 1969) and the Sequenced Inventory of Communication Development (SICD; Hedrick, Prather, & Tobin, 1975) for assess-


ing receptive and productive language. Three measures from observed laboratory tasks were also employed: memory for locations, categorization, and word comprehension. Memory for locations (Kagan, 1981) in- dexes the child's highest level of correct search under conditions of increasing delay and difficulty. Categorization (Mandler, Fi- vush, & Reznick, 1987) was assessed as the number of sequential touches of objects from the same category averaged across categories using objects from four stimulus sets (animals, people, cars, and trucks). Word comprehension (Reznick, 1990) was scored as the number of slide-presented words for which the child showed at least a 15% increase in visual preference for the picture representing the target word followng a word prompt, as compared to preference for that picture before the prompt.

Intercorrelations among measures.-As shown previously at 14 months (Plomin et al., 1990), the measures, both within and across domains, show modest intercorrelations, indicating that none of the measures are redundant. The highest correlations emerged between scales within measures. The largest correlations involved overall mood versus positive hedonic tone (.47 at 14 months and .38 at 20 months) and negative hedonic tone (-.66, -.70). These correlations occurred because overall mood was rated in the same videotape situations as positive and negative hedonic tone. IBR task orientation and IBR affect correlated .34 at 14 months and .38 at 20 months. Several CCTI scales were correlated: emotionality and attention (-.25 at 14 months, -.38 at 20 months), activity and sociability (.24, .34), and shyness and sociability (-.37, -.42). Expressive and receptive SICD correlated .50 at 14 months and .62 at 20 months.

Between measures, the largest correlations were between behavioral inhibition and shyness (.33, .34), IBR task orientation and Bayley MDI (.47, .39), and CCTI emotionality and negative DES (.39, .37). IBR affect correlated with positive hedonic tone (.35, .40), negative hedonic tone (-.52, -.30), overall mood (.58, .39), reactivity (-.26, -.38), Bayley MDI (.38, .30), and expressive SICD (.29 and .35). Within the cognitive domain, Bayley MDI correlated with word comprehension (.17, .36), expressive SICD (.45, .61), and receptive SICD (.44, .67). It is noteworthy that none of the more than 500 other correlations yielded correlations greater than .30, indicating the diver-

sity of behavioral dimensions within each domain. The correlations were generally similar at 14 and 20 months. The full correlation matrix at both ages is available from the first author.

Analysis The twin method compares pairs of

twins who are genetically identical (monozygotic, MZ) to fraternal twins (dizygotic, DZ) who are approximately half as similar genetically (Plomin, DeFries, & McClearn, 1990). If heredity affects a trait, the twofold greater genetic similarity of MZ twins is expected to make them more similar than DZ twins. Thus, for a particular measure, an MZ correlation that is significantly greater than the DZ correlation suggests genetic influence. The effect size of genetic influence can be estimated by doubling the difference between the MZ and DZ correlations. This value is heritability (h2), the extent to which observed variance for a trait can be attributed to genetic influence.

The rest of the variance is attributed to environmental factors, more properly referred to as nongenetic factors because they include all nonheritable influences such as biological influences and accidents as well as systematic psychosocial environmental influences. The environmental component of variance can be decomposed into two sub- components. One subcomponent, referred to as shared or common environmental influence (c2), is estimated in the twin method as twin resemblance not explained by hereditary resemblance. The twin estimate of shared environment can be shown to be twice the DZ correlation minus the MZ correlation, although the twin method by itself only provides power sufficient to detect major effects of shared environment (Martin, Eaves, Kearsey, & Davies, 1978). The other subcomponent is the residual environmental variance which includes error of measurement and nonshared environmental influences that do not make family members similar. Differences within pairs of MZ twins are due to nonshared environment (and error of measurement); this component of variance can be estimated by the extent to which the MZ correlation is less than unity. The distinction between shared and nonshared environment is important because in studies later in life nearly all environmental influence is of the nonshared variety (Dunn & Plomin, 1990; Plomin & Daniels, 1987).

Estimates of components of variance at

Plomin et al. 1359

each age.-In addition to examining MZ and DZ twin correlations at each age, parameter estimates are assessed using the multiple regression model-fitting approach of DeFries and Fulker (1985), which was described in our previous paper (Emde et al., 1992). In the present paper, we also add a correction for gender effects (Cyphers, Phillips, Fulker, & Mrazek, 1990), which could inflate correlations for same-sex twins and thus inflate estimates of shared environmental influence. The following regression model was fitted to the data from MZ and DZ twin pairs simultaneously:

P1 = B1S + B2P2 + B3R + B4P2R + A,

where Pi is one twin's score, S refers to the sex of the twin pair, P2 is the co-twin's score, R is the coefficient of relationship (R = 1.0 for MZ twin pairs and 0.5 for DZ twins), and A is the regression constant. Bi is the partial regression of twins' scores on sex and re- moves variance due to sex from the other parameter estimates. B2, the partial regression of one twin's score on the co-twin's score, estimates c2, and B4 estimates h2. Double entry of the data and a corresponding adjustment of standard errors results in estimates of h2 and c2 that can be tested for statistical significance. When the classic twin model is violated, modified (or "constrained") estimates are presented (Cherny, DeFries, & Fulker, 1992). That is, when the MZ correlation is substantial but the DZ correlation is low or even negative, doubling the difference between MZ and DZ twin correlations can yield heritability estimates that exceed the MZ correlation, and shared environment parameter estimates can be negative. Constrained estimates are obtained by dropping parameters from the model, which is a standard approach in model-fitting. For example, if heritability exceeds 1.0 or if shared environment is negative, the shared environment parameter is constrained to be zero in order to avoid a nonsensical negative variance estimate for shared environment. Refitting a reduced model yields a conservative estimate of heritability. In a corresponding manner, if the unconstrained estimate of heritability is negative (i.e., if the DZ correlation exceeds the MZ correlation), a conservative estimate of shared environment can be obtained by con- straining heritability to be zero.

Assumptions of the twin method that in- troduce cautions about interpreting genetic

influence specifically in relation to the MALTS study were enumerated in our previous paper (Emde et al., 1992). These issues include the equal environments assumption, generalizability of twin data, nonadditive genetic variance, assortative mating, genotype-environment correlation and interaction, and statistical power. De- spite these issues, the twin method remains a valuable screening device for genetic influence. For measures substantially influ- enced by heredity, the approximately twofold difference in genetic similarity for the two types of twins can reasonably be expected to exceed by far the effect of compli- cating factors such as nonadditive genetic variance and unequal environments for MZ and DZ twins.

Estimates of age-to-age components of change and continuity.-A simple approach to the analysis of genetic change is to analyze change scores (Loehlin, 1992a; Plomin & Nesselroade, 1990). That is, identical and fraternal twin intraclass correlations can be calculated using each individual's change score (20 months - 14 months) entered in a double-entry file. Finding genetic influence on age-to-age change scores implies that genes contribute to developmental change. Change scores are more unreliable than the variables from which they are constructed to the extent that those variables are correlated. However, as indicated later, stabilities from 14 to 20 months are generally low. Moreover, results are generally similar from model-fitting analyses that do not use change scores. Finally, it should be noted that conclusions cannot be drawn beyond the particular measure used at the two ages which may change from age to age, for example, in its sensitivity as an index of a con- struct.

The essence of genetic analysis of continuity is the cross-twin intraclass correlation, which is the correlation between one twin's score at 14 months and the co-twin's score at 20 months-again, entered in a double- entry file. In the case of twin analyses of cross-twin correlations, "heritability" indicates the extent to which genetic factors mediate phenotypic continuity from 14 to 20 months (Plomin & DeFries, 1981).

More elegant than analyses of change scores and cross-twin correlations are longitudinal model-fitting analyses that simultaneously consider heritabilities at each age and phenotypic continuity between the two


ages. A standard longitudinal genetic model is illustrated in the path diagram in Figure 1. The phenotype (P) assessed at 14 and 20 months is represented by the two rectangles. Above the rectangles are circles representing latent variables of genetic and environmental influence shared in common at 14 and 20 months. The paths from these common factors to the phenotype at 14 months indicate the relative magnitude of genetic and environmental influence at 14 months. Squaring these path coefficients estimates the proportion of variance at 14 months due to genetic and environmental influence. The paths from these common factors to the phenotype at 20 months indicate the extent to which genetic and environmental influences at 14 months also affect the phenotype at 20 months. The product of the genetic paths from the latent variable G to the phenotype at 14 and at 20 months estimates the genetic contribution to phenotypic continuity from 14 to 20 months.

The circles below the phenotype are re-

sidual latent variables that represent genetic and environmental influence at 20 months independent of genetic and environmental influence at 14 months. In other words, the path from the latent variable g estimates new genetic effects that appear at 20 months. This path represents a type of genetic change from 14 to 20 months, although this index of genetic change can differ from the results of change scores. Squaring these residual path coefficients at 20 months estimates the proportion of variance at 20 months due to change-that is, new genetic effects at 20 months. Squaring the other path coefficients at 20 months from the common factors estimates the proportion of variance at 20 months due to continuity. Maximum- likelihood model-fitting analyses using correlation matrices were performed using LISREL VII (Jbreskog & S6rbom, 1989). These modeling techniques have been explained elsewhere in relation to twin analyses (Boomsma, Martin, & Neal, 1989; Fulker, Baker, & Block, 1983; Neale & Cardon, 1992).

G E S Ln,,

P 14 MONTHS P

20 MONTHS

g s, en

FIG. 1.-Longitudinal path model of genetic and environmental sources of change and continuity. P is a phenotype assessed at 14 and at 20 months. G is a latent variable representing genetic influence that affects the phenotype at both 14 and 20 months. E, and E, are latent variables representing, respectively, shared and nonshared environmental influences common to the two ages. The three

remaining latent variables-g, e., and e,-represent genetic, shared environmental, and nonshared environmental influences that are specific to the phenotype at 20 months independent of effects at 14 months.

Plomin et al. 1361

Results

Descriptive Statistics Table 1 lists means and standard devia-

tions by age and gender. For each variable, MANOVA was conducted with age as a within-subjects variable and gender as a between-subjects variable. Large mean increases from 14 to 20 months on the order of two standard deviations were found for the SICD measures; increases greater than half a standard deviation occurred for other cognitive measures and IBR task orientation. Significant but slight age differences emerged for IBR activity, CCTI activity, positive and negative hedonic tone, mood, and IBR affect. The three variables derived as an unrotated principal component (PC) were standardized within age and thus do not permit age comparisons.

Half of the variables showed significant gender effects with these large sample sizes. However, the size of the gender effects is quite small, with the largest differences ac- counting for less than half a standard deviation. Only three significant interactions between age and gender were found.

The means and standard deviations for the Bayley MDI at 14 and 20 months indicate that the sample is reasonably represen- tative both in terms of means and variances. Comparisons of means for identical and fraternal twins yielded few significant differences and none accounted for more than one-third of a standard deviation.

Phenotypic Change and Continuity The last column of Table 1 lists correla-

tions for all individuals from 14 to 20 months. These correlations indicate some continuity in the face of considerable change in the rank order of individuals during the second year of life. The observational measures of temperament and emotion yield correlations of about .30. Parental ratings of temperament suggest higher correlations (about .55), as do parental ratings of discrete emotions (about .65). Bayley MDI scores correlate .49 from 14 to 20 months, although the experimental measures of memory for lo- cation, categorization, and word comprehension show much lower correlations. The SICD language measures indicate moderate continuity despite the substantial mean change in these measures from 14 to 20 months. As expected, the stability correlations were quite similar for MZ and DZ twin individuals; only three of the measures

yielded significantly (p < .05) different stability correlations for MZ and DZ twins.

Changes and Continuity of Heritability Heritability estimates at 14 and 20

months of age are presented in Table 2; these estimates were derived from the multiple regression model described earlier. The twin correlations at 14 months are the same as those reported in our previous paper (Emde et al., 1992), although the model- fitting results differ slightly because, in the present model, variance due to gender was removed. As would be expected from the finding that gender accounts for only a small amount of variance, the results change only slightly when variance due to gender is removed.

About half of the measures yielded significant heritability estimates at 14 months. Seven of these 12 measures also showed significant heritability at 20 months. The magnitude of heritability is similar on average at 14 and 20 months. These findings suggest that, in general, heritability does not change dramatically from 14 to 20 months.

Nonetheless, some hints of change in heritability are intriguing. Most interesting are the apparent increases in heritability for tester ratings on task orientation and for SICD expressive and receptive language, ar- eas that show substantial mean increases from 14 to 20 months (see Table 1). The twin results also suggest that, for a few dimensions, heritability may decline from 14 to 20 months.

Examination of the twin results by domain suggests some noteworthy findings. In the domain of temperament, several measures show significant heritability at both ages: behavioral inhibition, IBR activity, CCTI emotionality, CCTI shyness, and CCTI sociability. As in other twin studies using parental ratings of broad dispositions, the CCTI scales yield DZ correlations that are low and even slightly negative, suggesting a possible contrast effect in parental temperament ratings of DZ twins (Buss & Plomin, 1984). That is, parents of DZ twins may exaggerate temperament differences between the twins in a way that is not possible for parents to do with MZ twins. This suggests that parental ratings may inflate twin estimates ofheritability (Plomin, Coon, Carey, DeFries, & Fulker, 1991). As is usually the case for temperament, shared family environmental influence that makes children growing up in the same family similar

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Plomin et al. 1363

in temperament is negligible. Significant shared environmental influence at 20 months emerged only for the shyness principal component score.

One of the most interesting findings in the emotion domain at 14 months was repli- cated at 20 months: Parental reports of expression of positive emotions as assessed by the DES show little genetic influence and overwhelming influence of shared environment at both ages. In contrast, parental DES reports of expression of negative emotions indicate substantial genetic influence and negligible influence of shared environment. No other emotion measure showed significant genetic influence at both ages. Shared environmental influence is negligible, with the striking exception of the DES measure of expression of positive emotions for which shared environment explains most of the variance.

In the domain of cognition, the most interesting finding is the increase in heritability for expressive and receptive language, as mentioned earlier. For the Bayley MDI at both 14 and 20 months, the finding of heritabilities in the .30s is compatible with the hypothesis that the heritability of cognitive ability increases to about .40 in early childhood and to .50 in middle childhood (Fulker et al., 1988). Shared environmental influences are also important for the Bayley MDI and expressive and receptive SICD language scores.

Variance not accounted for by genetic or shared environment is attributed to nonshared environment plus error of measurement. This accounts for most of the variance except for shyness, positive DES, Bayley MDI, and expressive and receptive SICD.

Etiology of Age-to-Age Change: Change Scores

The MALTS twin data were employed to investigate genetic and environmental contributions to change and continuity from 14 to 20 months. Although longitudinal model-fitting analyses will be reported, we begin with an easier-to-understand genetic analysis of change using change scores and a genetic analysis of continuity using cross- twin correlations.

Change scores from 14 to 20 months for each individual were submitted to twin analyses using the same model described in relation to Table 2. Table 3 presents MZ and DZ twin correlations and model-fitting pa-

rameter estimates based on these twin correlations for change scores. Estimates of significant genetic influence on these change scores emerged for several measures: CCTI activity, positive hedonic tone, negative DES, memory for locations, and the SICD expressive scale. These findings of significant genetic influence on change scores are not much related to the magnitude of the phenotypic correlation from 14 to 20 months (Table 1) or to the magnitude of heritabilities at each age (Table 2), even though change scores cannot be heritable if stability is very high or if heritabilities are very low. For example, one of the most stable traits, negative DES, shows significant genetic change. Although traits that show significant genetic change are among the most heritable traits at both ages, some traits that are heritable at both ages-such as IBR activity, several CCTI traits, and word comprehension- show no genetic change.

Even though evidence for genetic change is not tightly linked to the magnitude of heritability at each age, it is appropriate to examine the extent to which genetic influence on change scores is a function of heritability at each age. We employed a model-fitting strategy suggested by Loehlin (1992b) to analyze genetic influence on change scores independent of genetic influence on mean scores. It is noteworthy that correlations between change scores from 14 to 20 months and mean scores across 14 and 20 months are significant for only two of the 23 comparisons. As expected from the low correlations between change scores and mean scores, Loehlin's approach yielded significant genetic influence on change scores for the same variables as indicated in Table 3. In summary, evidence for genetic influence on change from 14 to 20 months appears to be independent of heritability at each age. It is also noteworthy that heritabilities of change scores are not tied to mean changes from 14 to 20 months. However, for the two cognitive measures that show significant heritability for change (memory for locations and expressive SICD), large mean increases were observed (see Table 1), suggesting that genetic change for these variables may be due to differential sensitivity of the measures at the two ages.

Two scales-positive DES and the SICD receptive scale-show significant and substantial shared environmental influence on change from 14 to 20 months. Variance in change scores not accounted for by genetics and shared environment is attributed to non-

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shared environment and error. This component of variance accounts for over half of the variance of these change scores with only three exceptions-positive DES and expressive and receptive SICD.

Etiology of Age-to-Age Continuity: Cross-Twin Correlations

As mentioned earlier, the essence of genetic analysis of continuity is the cross-twin correlation, which is the correlation of one twin's score at 14 months with the co-twin's score at 20 months. The cross-twin correlations for MZ twins (the right-hand side of Table 3) are on average nearly as large as the within-individual correlations from 14 to 20 months (Table 1). In other words, the scores of one member of MZ twin pairs at 14 months correlate nearly as highly with the co-twin at 20 months as individuals correlate with themselves from 14 to 20 months. In contrast, for most traits, DZ twin cross-twin correlations are lower, suggesting genetic influence on stability from 14 to 20 months. As shown in Table 3, submitting these cross- twin data to multiple regression model- fitting analysis (predicting 20-month scores from 14-month scores) yielded significant "heritabilities" for behavioral inhibition, IBR task orientation, three of the five CCTI scales, negative hedonic tone, mood, and IBR affect. Of the cognitive measures, only word comprehension showed significant genetic continuity.

In the case of twin analyses of cross- twin correlations, "heritability" represents the genetic contribution to phenotypic stability. We can compare these "heritabilities" to the phenotypic correlations for all individuals from 14 to 20 months (Table 1) in order to estimate the extent to which phenotypic stability is mediated genetically. This com- parison suggests that genetic factors are responsible for nearly all of the phenotypic stability from 14 to 20 months for behavioral inhibition, the three IBR scales, negative hedonic tone, IBR affect, and word comprehension. This implies that environmental factors have little to do with phenotypic stability for these traits, an issue to which we return in the discussion section. Most other traits also showed substantial genetic mediation of phenotypic stability. However, phenotypic stability is not mediated by genetic factors for positive hedonic tone, categorization, and the SICD expressive scale. In other words, for these traits, environmental factors are primarily responsible for stability. Mem- ory for locations showed no phenotypic sta-

bility and thus there can be no genetic contribution to stability for this measure.

In the twin analysis of cross-twin correlations, estimates of shared environmental influence represent the extent to which stability is mediated by shared environment in common to 14 and 20 months. Significant shared environmental sources of stability emerged for reactivity, positive DES, and for the SICD expressive scale, and some shared environmental influence was suggested for positive hedonic tone and negative DES.

To the extent that the phenotypic correlation from 14 to 20 months is not accounted for by genetic and shared environmental sources of stability, stability is attributed to nonshared environment, which, in this case, does not include error because it is a source of systematic covariance from 14 to 20 months. Thus, nonshared environmental sources of stability appear to be important for the CCTI scales and categorization.

Etiology of Age-to-Age Change and Continuity: Model-Fitting

Longitudinal model-fitting, described in the Method section, is a more elegant approach to the analysis of change and continuity because it encompasses in a single analysis all relevant information about phenotypic stability and heritabilities at each age. As illustrated in the path diagram in Figure 1, in this longitudinal model, genetic contributions to change are conceptualized as new genetic effects at 20 months that are independent of genetic effects at 14 months. Al- though this model of genetic change is different from the model implied by the genetic analysis of change scores (Table 3), the results are similar. Genetic contributions to continuity are indexed by paths from a latent variable that represents genetic influences affecting both 14- and 20-month scores.

As an example of model-fitting, Figure 2 shows parameter estimates for behavioral inhibition. The genetic residual (g) at 20 months is significant, suggesting new genetic effects at 20 months. Genetic continuity is indicated because both path coefficients (.76 and .52) from the genetic common factor (G) are significant. The chi-square for the overall model for behavioral inhibition is nonsignificant (X2[14 df] = 0.60), indicating that the model fits the data. For only one of the 23 measures did the model fail to fit the data.

Plomin et al. 1369

Genetic and environmental components of continuity and change can be derived from the model-fitting results. For example, the components of phenotypic continuity for behavioral inhibition are estimated by mul- tiplying the common paths in Figure 2: .76 x .52 = .39 for genetic continuity; .00 x .00 = .00 for shared environmental continuity; .66 x -.06 = -.04 for nonshared environmental continuity. The sum of these components of continuity (.39 + .00 -.04 = .35) is within rounding error of the phenotypic correlation of .34 from 14 to 20 months. These results suggest that the correlation from 14 to 20 months for behavioral inhibition is due entirely to genetic factors.

Genetic and environmental components of change were estimated as the ratio between the variance of each change path and the total variance for change. For example, as shown in Figure 2 for behavioral inhibition, the change path for the unique genetic latent variable is .42; squaring this path (.422 = .18) and dividing by the sum of all the squared change paths (.422 + .002 + .742 = .72) indicates that about a quarter of the change variance is due to genetic variance (.18 + .72 = .24). This model-fitting estimate of change for behavioral inhibition is

greater than the estimate of change scores shown in Table 3. This finding underlines that the two models are different. As noted earlier, the longitudinal model partitions genetic variance at 20 months into two components: genetic variance that covaries with genetic variance at 14 months and the rest of the genetic variance at 20 months. The latter component indicates new genetic effects at 20 months, and in this sense can be interpreted as the genetic contribution to change. Despite the differences in the models, for the other variables, the model-fitting results are quite similar to the results of the analysis of change scores (Table 3). Similar calculations for shared and nonshared environment residuals show no contribution to change for shared environment and a substantial contribution to change for nonshared environment for behavioral inhibition, again similar to the results of change scores shown in Table 3.

Because the results of model-fitting generally confirm the simpler analyses shown in Table 3, details of the model-fitting for all of the variables are not presented but are available from the first author. Full apprecia- tion of these longitudinal analyses of change and continuity is difficult because there are

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so many measures and parameters and because longitudinal correlations must be kept in mind at the same time that genetic and environmental sources of change and continuity are considered. For this reason, Figure 3 summarizes the results of the model-fitting analyses. Although at first glance the figure looks complicated, each row simply represents the variance of a measure divided into genetic and environmental sources of continuity and change. The solid bar (shown with an arrow in the key at the top of the figure) marks the phenotypic correlation from 14 to 20 months which divides the variance into continuity (to the left of the bar) and change (to the right of the bar). For the first measure, behavioral inhibition, the phenotypic correlation is .34, which suggests that about a third of the variance of the measure covaries from 14 to 20 months. (Note that the correlation of .34 is not squared because the correlation represents the extent to which the variance at the two ages covaries; the correlation is squared only if one wishes to estimate the variance at 20 months that can be predicted from scores at 14 months.)

As indicated in the key at the top of the figure, the cross-hatched box to the left of the bar indicates the genetic contribution to continuity. In the case of behavioral inhibition, all of the continuity from 14 to 20 months is mediated genetically. For the other measures, shared and nonshared environmental contributions to continuity are indicated to the left of the bar by the box with diagonal lines and by the open box, respectively.

Genetic and environmental components of change are represented by the similarly marked boxes to the right of the bar. In the case of behavioral inhibition, genetic change accounts for about a quarter of the variance of phenotypic change from 14 to 20 months; the rest is due to nonshared environment plus error.

Model-fitting yielded evidence for significant genetic change (the g residual parameter at 20 months) for behavioral inhibition, CCTI activity, CCTI sociability, positive hedonic tone, DES negative, and SICD expressive. These results are similar to those shown in Table 3 for change scores, with the exception that the latter shows a genetic contribution to change for the memory for locations measure. (The longitudinal model-fitting does not indicate genetic change for memory for locations because

this measure shows little genetic influence at 20 months.) In terms of environmental components of change, change from 14 to 20 months is significantly mediated by shared environment for shyness, positive DES, Bayley MDI, and receptive SICD. The rest of the change from 14 to 20 months is due to nonshared environment and error of measurement.

The model-fitting results also generally confirmed the findings from the analysis of cross-twin correlations (Table 3): most measures show some genetic contribution to stability from 14 to 20 months. In the analysis of cross-twin correlations (Table 3), the average estimate of the genetic contribution to continuity was .24; the average model-fitting estimate is .22. For all measures, the two estimates of genetic continuity are within .10. As a result, both analyses indicate that nearly all of the phenotypic stability is mediated genetically for behavioral inhibition, the three IBR scales, negative hedonic tone, mood, empathy, and word comprehension. In addition, model-fitting analysis suggests that stability for reactivity is mediated genetically. Both analyses find negligible genetic mediation of stability for positive hedonic tone, categorization, and memory for locations (which shows no phenotypic stability). Model-fitting indicates that shared environment significantly mediates continuity for positive hedonic tone, positive DES, Bayley MDI, and expressive and receptive SICD. Nonshared environment significantly mediates continuity only for the CCTI measures and the categorization measure.

Discussion Limitations of Our Findings

Several features of our method limit generalizability of these results. Of course, the results cannot be safely generalized beyond this study's particular sample, design, ages, and measures. Model-fitting, like any analytic strategy, can only apply to the variables we put into the analyses. We must therefore ask the extent to which these measures adequately instantiate our constructs. For example, to what extent do our measures of temperament or emotional expression cover relevant constructs in terms of what we know about them at the psychological level? Of particular concern is the problem of equivalency of measures from 14 to 20 months. One way of addressing this issue empirically is to assess the extent to which

14 - 20 Month Correlation

CONTINUITY CHANGE

.00 .10 .20 .30 .40 .80 .80 .70 80 0 1. 0

Behavioral Inhibition

Shyness PC

IBR Activity

IBR Teeak Orientation

CCTI Emotionallty

CCTI Activity

CCTI Attn/Peralatence

CCTI Shyness

CCTI Sociability

Positive Hedonlc Tone

Negative Hedonic Tone

Overall Mood

Empathy PC

Reactivity PC

IBR Affect

DES Positive Aggregete

DES Negative Aggregate

Bayley MDI

Memory for Locations

Categor Ization

Word Comprehenalon

SICD Expressive

SICD Receptive

FIG. 3.-Summary of genetic and environmental components of continuity and change. As indicated in the key at the top of the figure, the vertical bar (marked with an arrow in the key) indicates the phenotypic correlation from 14 to 20 months. To the left of the bar are the genetic, shared environmental, and nonshared environmental components of the phenotypic correlation; to the right of the bar are the components of change. These components of continuity and change are derived from model- fitting parameter estimates, as described in the text.


the interrelationships among measures change during development. As indicated earlier, the patterns of phenotypic correlations among measures at 14 and 20 months are similar, which suggests some equivalency of measurement. Multivariate genetic analyses will be carried out in the future when we will also extend our longitudinal analyses of continuity and change to 24 and 36 months. Combined longitudinal and multivariate analyses will then explore the genetic and environmental architecture of homotypic and heterotypic continuity and change during the transition from infancy to early childhood.

Another limitation concerns the absence of measures of the environment that would allow us to identify specific sources of shared and nonshared environment. We are just beginning to learn about important environmental processes that directly influence or interact with genetic influences, and we were not able to include such measures at the time we designed our study.

Another limitation is the absence of estimates of reliability from 14 to 20 months. Such estimates would make it possible to disentangle nonshared environment from error variance. Our estimates of heritability and shared environment are also based on total variance rather than reliable variance; correcting for reliability would increase the relative proportion of variance explained by these components of variance.

Finally, our findings are limited to the analysis of individual differences and refer to genetic and environmental influences on average in the population sampled in this study. Although our research indicates that genetic factors in part mediate change on average among individuals in this sample, we cannot capture the dynamic nature of genetic-environmental interactions as they take place within individuals.

Overview of Results The correlations from 14 to 20 months

indicate that individual differences in the second year of life show greater change than continuity for most of our measures. The longitudinal correlations averaged about .30 for observational measures of temperament and emotion, about .40 for language measures, and about .50 for the Bayley MDI. The present analyses focused on the role of genetic factors in change as well as continuity during the second year of life. One type of genetic change involves change in the mag-

nitude of genetic influence, heritability. Although the increases in heritability for expressive and receptive language warrant fur- ther attention, in general, heritability estimates were similar at 14 and 20 months. On average, heritability is .27 at 14 months and .28 at 20 months. In other words, on average about a quarter of the total variance of these measures at these particular ages can be accounted for by genetic factors, although heritabilities range widely, from negligible genetic influence for negative hedonic tone to heritabilities of about 50% for behavioral inhibition and about 60 percent for negative DES.

The longitudinal analysis of age-to-age genetic change and continuity broaches the issue of mechanisms in the development of individual differences. The most novel fea- ture of the results is the evidence that emerged for genetically mediated change. Model-fitting analyses suggested genetic change from 14 to 20 months for behavioral inhibition, CCTI activity and sociability, positive hedonic tone, negative DES, and expressive SICD. For positive hedonic tone and expressive SICD, genetic factors primarily contribute to change rather than continuity.

The contribution of heredity to continuity is less surprising. For 16 of the 23 measures, model-fitting estimates of genetic continuity were significant. Moreover, genetics plays a leading role in continuity. On average, about two-thirds of the phenotypic correlations between 14 and 20 months is mediated genetically, although this varies from the case of behavioral inhibition in which genetic factors completely account for phenotypic continuity to the case of positive hedonic tone in which genetic factors play no part in continuity. Nonetheless, the considerable contribution of genetic factors to phenotypic correlations may appear surprising because it is often assumed that aspects of the home environment mediate continuity. For example, overprotectiveness of parents may be related to children's stability of behavioral inhibition. However, a largely un- examined alternative explanation of such findings is that parents' behavior reflects rather than affects genetic propensities and developmental changes in these genetic propensities (Plomin & Bergeman, 1991).

Genetic and Environmental Sources of Change

Genetic change could mean that certain genes contribute directly to change from 14

Plomin et al. 1373

to 20 months or that the genes that affect a trait at 14 months differ from genes that affect the trait at 20 months. For example, imagine that the tools of molecular genetics could be used to identify specific genes responsible for genetic variance on complex behavioral traits. The evidence for genetic change suggests that, for a trait showing genetic change, genes might be found that are associated with differential change from 14 to 20 months even if the genes are not associated with the trait at either 14 or 20 months. More likely, genes responsible for genetic variation at 14 months might be found that differ from the genes responsible for genetic variation at 20 months. As noted earlier, this could occur because genes turn on and off during development. However, it seems more probable that the dramatic changes in the developmental system from 14 to 20 months result in some genes affecting the organism at 14 months that no longer have an effect at 20 months. Conversely, some genes that had no effect on a trait at 14 months might begin to affect the trait in the 20-month developmental system.

It has recently been hypothesized that genetic influence on developmental change might be greatest in periods of normative change as indexed by mean changes from age to age (McGue, Bacon, & Lykken, in press). Some support was found for this hypothesis in a 10-year longitudinal twin study in adulthood that employed self-report personality questionnaires (McGue et al., in press). Mean changes in infancy are greater than in adulthood and thus provide a better test of the hypothesis. As indicated in Table 1, tester ratings on IBR task orientation yield substantial mean increases from 14 to 20 months, and heritability also increases from 14 to 20 months for IBR task orientation. However, the other temperament and emotion measures that show significant, albeit less substantial, age changes, yield similar heritability estimates at 14 and 20 months. Moreover, contrary to the hypothesis, only two of the measures show any age-to-age genetic change. Although the hypothesis was developed in relation to personality, the greatest normative changes during the life span can be found for mental development during infancy. All of the cognitive and language variables show major mean increases from 14 to 20 months, including raw scores on the Bayley Mental Scale even though the Bayley MDI is an age-standardized scale score. Overall, the hypothesis does not fare well in the cognitive domain either. The two

SICD language measures show increases in heritability and the SICD expressive scale shows significant genetic change. However, none of the other cognitive variables, most notably the Bayley MDI, show heritability changes or significant genetic change from 14 to 20 months.

In terms of environmental components of change, change from 14 to 20 months is significantly mediated by shared environment for positive DES and receptive SICD. Identifying such shared environmental influences that contribute to change represents an interesting challenge for future research because of the constraints imposed on such factors. Such environmental influences must change from 14 to 20 months and yet be shared by children growing up in the same family. One possibility is parental behavior that changes as children develop (Dunn & Plomin, 1986). For example, some parents might not begin to teach their children until the children begin to use language during the middle of the second year of life. For other measures, however, nearly all environmental influence on change is of the nonshared variety or due to error of measurement.

Genetic and Environmental Sources of Continuity

The components of continuity are sum- marized in Figure 3 to the left of the bar which marks the phenotypic correlation from 14 to 20 months. As noted earlier, the figure illustrates the considerable extent to which stability for our measures is mediated genetically. Although genetic effects on change from 14 to 20 months are seen for a few measures, for most measures genetic factors are substantially involved in continuity from 14 to 20 months.

The shared environment component of continuity is signified in Figure 3 by the diagonal-marked box to the left of the bar. The figure shows that shared environment contributes significantly to the phenotypic correlation from 14 to 20 months for five measures: positive hedonic tone, positive DES, Bayley MDI, and expressive and receptive SICD. These are environmental factors shared by children in a family that affect development at both ages. Stable characteris- tics of the parents represent one possible source of such influences.

Just as interesting as finding shared environmental components of change is the finding of significant nonshared environmental components of continuity, indicated


by the open boxes to the left of the bar in Figure 3. Significant nonshared environmental components of continuity were found for all five CCTI parental ratings of temperament and for categorization. The nonshared component of continuity does not include error because it represents systematic covariance from 14 to 20 months. For example, an accident or illness at 14 months might continue to affect development at 20 months. Also, systematic nonshared experiences such as differential treatment by parents might continue from 14 to 20 months. Why do parental ratings of CCTI temperament consistently show significant continuity due to nonshared environment? One possibility is a stable rater bias such as a contrast effect. For example, parents might label one twin as the active one and the other as the inactive one for reasons unrelated to heredity, and such labeling might persist from 14 to 20 months.

Change and Continuity Such analyses of longitudinal change

and continuity are important for at least two reasons. First, quantitative genetic theory and methods provide one of the only research strategies available to go beyond the description of change and continuity in individual differences to address their origins. It takes the reasonable first step of asking about the "bottom line" of genetic and environmental influences. However, this is only a first step. Identifying specific genetic and environmental factors responsible for these anonymous components of covariance represent important, albeit difficult, next steps in understanding etiology. It can be argued that the identification of specific environmental factors that affect development can best be accomplished in the context of quantitative genetic designs that are sensitive to genetic influence (Plomin & Bergeman, 1991). We are also at the dawn of a new era in which techniques from molecular genetics may make it possible to identify development-relevant DNA variation directly in individuals rather than resorting to indirect estimates derived from twin and adoption studies (Plomin, 1990).

Finally, analyses of age-to-age change and continuity shift the focus of quantitative genetics away from outcomes of development toward the process of development itself. Finding evidence of genetic change as- sumes special significance because it shows that heritability cannot be equated with stability or immutability. As in Galton's pre- scient remark over a century ago, it must in-

deed be borne in mind that divergence in development can be due to inherited qualities.

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Genetic Change and Continuity from Fourteen to Twenty...

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