Genetic Effects on Children’s Conversational Language Use

Abstract

Purpose-The present study examined the extent of genetic and environmental influences on individual differences in children's conversational language use.Method-Behavioral genetic analyses focused on conversational measures and 2 standardized tests from 380 twins (M = 7.13 years) during the 2nd year of the Western Reserve Reading Project (S. A. Petrill, K. Deater-Deckard, L. A. Thompson, L. S. DeThorne, & C. . Multivariate analyses using latent factors were conducted to examine the extent of genetic overlap and specificity between conversational and formalized language.Results-Multivariate analyses revealed a heritability of .70 for the conversational language factor and .45 for the formal language factor, with a significant genetic correlation of .37 between the two factors. Specific genetic effects were also significant for the conversational factor.Conclusions-The current study indicated that over half of the variance in children's conversational language skills can be accounted for by genetic effects with no evidence of significant shared environmental influence. This finding casts an alternative lens on past studies that have attributed differences in children's spontaneous language use to differences in environmental language exposure. In addition, multivariate results generally support the context-dependent construction of language knowledge, as suggested by the theory of activity and situated cognition (J. S. Brown, A. Collins, & P. Duguid, 1989; T. A. Ukrainetz, 1998), but also indicate some degree of overlap between language use in conversational and formalized assessment contexts. Keywordsexpressive language assessment; elementary school pupils; language Contact author: Laura S. DeThorne, University of Illinois at Urbana-Champaign, 901 South Sixth Street, Champaign, IL 61820. E-mail: lauras@uiuc.edu. NIH Public Access NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptA number of twin studies have used quantitative genetic methods to estimate environmental and genetic influences on language development. The twin design hinges on a comparison of monozygotic (MZ) and dizygotic (DZ) twins. Because MZ twins share 100% of their segregating genes and DZ twins share on average 50%, higher similarity between MZ twins is indicative of genetic effects (Plomin, DeFries, McClearn, & McGuffin, 2001). One means of measuring twin similarity is by comparing intraclass correlations for MZ versus DZ twins. The larger the MZ intraclass correlation in comparison with the DZs, the higher heritability (h 2 ) will be. In contrast, shared environmental effects (c 2 ) lead to similarity across all twins. Consequently, similar intraclass correlations between MZ and DZ twins are indicative of shared environmental effects. Finally, the extent to which MZ twins appear dissimilar is attributed to a combination of nonshared environment and error (e 2 ). Nonshared environmental influences are unique to the individual.An underlying assumption of twin methodology is that the nature of genetic and environ...

Longitudinal Effects on Early Adolescent Language: A Twin Study

“…At each home visit, the Productive Language factor was indexed by MLU, NTW, and NDW, whereas the Formal Language factor was indexed by TNL and the three CELF-4 subtests. These factors are consistent with the conceptual framework of prior studies (DeThorne et al, 2008(DeThorne et al, , 2012Miller et al, 2006;Scott & Windsor, 2000) and the phenotypic correlation data from the present study. Latent factors represent the shared variance among measures, independent of measure-specific variance and error.…”

“…The present work represents an extension of prior WRRMP analyses (i.e., DeThorne et al, 2008DeThorne et al, , 2012 by examining the extent and stability of etiological influences on children's language development, using both language samples and standardized measures, across the critical developmental window of early adolescence. We asked the following research questions:…”

“…Although evidence regarding the reliability of productive language-sample measures has been mixed, especially from shorter samples (e.g., Gavin & Giles, 1996;Tilstra & McMaster, 2007), such measures have been associated with evidence of validity through developmental change with age up through age 13 years (Miller et al, 2005;Miller, Freiberg, Holland, & Reeves, 1992; M. L. Rice, Redmond, & Hoffman, 2006); correlation with other measures of linguistic complexity (DeThorne et al, 2008;Nippold, 2009;Nippold et al, 2014; M. L. Rice et al, 2006;Ukrainetz & Blomquist, 2002); and differentiation of clinical groups (e.g., Condouris, Meyer, & Tager-Flusberg, 2003;Scott & Windsor, 2000;Watkins, Kelly, Harbers, & Hollis, 1995).…”

“…The genetic effect size is typically referred to as heritability (a 2 or h 2 ), with shared and nonshared environmental effects represented as c 2 and e 2 , respectively. Estimates of genetic effects on individual differences in language development at different ages have varied widely across studies, with such variability attributed to differences in language domain (e.g., Stromswold, 2001), form of measurement (e.g., DeThorne et al, 2008), environmental circumstances (e.g., Rowe, Jacobson, & Van den Oord, 1999), and child age (e.g., Spinath, Price, Dale, & Plomin, 2004). Specific to child age, multivariate analyses with longitudinal data allow us to examine the stability of genetic and environmental effects over time.…”

“…Using this sample, DeThorne et al (2008) conducted a multivariate genetic analysis of language skills that included 380 twins in first grade. Language measures loaded on two latent factors: a Conversational factor that included language-sample measures such as mean length of utterance (MLU), number of total words (NTW), and number of different words (NDW), and a Formal factor that included two standardized vocabulary tests.…”