A learning rate parameter

1
Longitudinal twin study of early literacy and
language Brian Byrne University of New
England with Richard Olson, Stefan Samuelsson,
Sally Wadsworth, Robin Corley, John C. Defries.
Erik Willcutt
2
Why study twins?

• Monozygotic (MZ) twins share 100 of all their
  genes
• Dizygotic (DZ) twins share 50 of their
  segregating genes (genes that make us different)
  on average
• MZ and DZ pairs reared together have similar
  shared environment in the home and school

3
Why study twins (cont)?

• Therefore, for traits that are substantially
  heritable, MZ twins will be very similar to each
  other and more alike than DZ twins
• For traits that are substantially influenced by
  early (shared) environment, MZ and DZ twins will
  be highly and equally similar

4
Concordance rates for schizophrenia

• MZ twins 48
• DZ twins 17
• First degree (e.g., sibling) 9
• Second degree (e.g., aunt) 4

5
Correlations for intelligence

• MZ twins .85
• DZ twins .60
• First degree .45
• Second degree .30

6
Structure of project

• Downward extension of existing reading studies to
  preschool-aged children
• Sites in Colorado, Australia, Norway and Sweden
• Four test occasions
• Preschool
• Kindergarten
• Grade 1
• Grade 2
• To date, approx 1700 children included

7
Aims

• To model genetic, shared environment, and unique
  environment effects on known foundations for
  literacy growth, prior to complicating influences
  of literacy levels themselves (ie, prior to
  formal literacy instruction)
• To trace these effects longitudinally as children
  develop in literacy

8
Twins seen in homes or pre-schools prior to
kindergarten
Note Each child assessed by a different tester
9
Twins typically tested at home after kindergarten
year
10
And again after first grade
11
With a final assessment after second grade
12
Some of the preschool test categories

• Phonological analysis and synthesis (PA)
• Print familiarity (PR)
• General verbal ability (GVA)
• Vocabulary (VOC)
• Morphology/syntax (GRAM)
• Working memory (WM)
• Rapid naming (RN)

13
Sample twin correlations (composites)

• MZ DZ
• PA .79 .55
• RN .68 .40
• PR .87 .77
• GVA .85 .68

14
Results of Mx modeling on preschool variables as
latent traits
Phonological awareness
Working memory
Rapid naming
15
Results of Mx modeling on preschool variables as
latent traits (cont.)
Print knowledge
Vocabulary
Grammar/ morphology
16
Summary of univariate preschool

• Phonological awareness, rapid naming, and working
  memory show substantial genetic effects and
  modest shared-environment effects
• Print familiarity, vocabulary, and
  morphology/syntax show substantial
  shared-environment effects and modest genetic
  effects

17
Univariate analysis (the story so far)

• MZ twins
• Twin 1 Twin 2
• X X
• X X
• . .
• . .

• DZ twins
• Twin 1 Twin 2
• X X
• X X
• . .
• . .

If correlation for MZ twins is higher than for DZ
twins, evidence for genetic influence on Variable
X
18
Multivariate analysis (new part of story)

• MZ twins
• Twin 1 Twin 2
• X Y
• X Y
• . .
• . .

• DZ twins
• Twin 1 Twin 2
• X Y
• X Y
• . .
• . .

• If correlation for MZ twins is higher than for DZ
  twins, evidence for genetic influence that is
  common to Variable X and Variable Y
• Y can be a different variable or the same
  variable at a different time

19
Multivariate analyses

• Thus, goal is to identify whether genetic and
  environmental sources influence more than one
  variable
• A commonly-used technique is Cholesky
  decomposition
• It is analogous to multiple regression where the
  influence of a predictor on a dependent variable
  is assessed after the influence of another
  predictor is accounted for

20
Cholesky decomposition ofpreschool latent
traits additive genetic effects
GVA
.64
A1
.45
PA
A2
.57
.35
RN
A3
.72
27
.20
PR
A4
.33

21
Cholesky decomposition ofpreschool latent
traits shared-environment effects
GVA
.76
C1
.61
PA
C2
.23
.22
.28
RN
.58
.58
PR
22
Cholesky decomposition ofpreschool latent
traits unique environment effects
GVA
.13
E1
.23
PA
.
.20
RN
PR
23
Summary of multivariate preschool data

• A single genetic factor affects verbal ability,
  phonological awareness, rapid naming, and print
  familiarity
• A second genetic factor affects phonological
  awareness and print familiarity
• Two additional genetic factors uniquely affect
  rapid naming and print familiarity
• Thus, each of the four latent traits is
  genetically complex

24
Summary of multivariate preschool data (cont.)

• In contrast to genetic influences, where four
  factors affect the latent variables, only two
  shared environment factors are in operation, each
  affecting all or most latent traits

25
Variables assessed after one year of formal
schooling (kindergarten)

• Word and nonword reading efficiency (TOWRE)
• Spelling (words and nonwords)
• Phonological awareness
• Rapid naming
• Grammar (TROG)

26
Results of Mx modeling on kindergarten variables
as latent traits
27
Results of Mx modeling on kindergarten variables
as latent traits (cont.)
28
Summary of kindergarten univariate data

• Reading, phonological awareness, and rapid naming
  show substantial genetic influence and modest
  shared-environment effects
• Spelling is equally affected by genes and shared
  environment
• Grammar is mainly affected by shared environment,
  with modest genetic influence

29
Cholesky decomposition ofkindergarten latent
traits additive genetic effects
PA
.81
A1
.34
RN
A2
.61
.59
.34
READ
A3
.51
.59
.29
SPELL

30
Cholesky decomposition ofkindergarten latent
traits shared-environment effects
PA
.51
C1
.47
RN
.42
READ
.63
SPELL
31
Cholesky decomposition ofkindergarten latent
traits unique environment effects
PA
.28
E1
.27
RN
E2
.43
.26
READ
.32
SPELL
32
Summary of kindergarten multivariate data

• Reading and spelling are influenced by genes that
  also affect phonological awareness and rapid
  naming, and in addition by a third set of genes
• A single shared-environment factor affects all
  four kindergarten latent traits

33
Longitudinal multivariate analyses
34
Cholesky decomposition ofphonological awareness
development
PA1 preschool phonological awareness PA2
kindergarten phonological awareness
.
A1
PA1
.82
.56
C1
.65
A2
PA2
.55
35
Where do the new genes for PA at kindergarten
come from?

• Possibly reciprocally from orthographic
  processes, as implied by the position that there
  is mutual influence between PA and orthography.

36
To test this in our genetically sensitive design,
we entered kindergarten spelling prior to
kindergarten PA
PA1
A1
.79
.
.44
.63
A2
K spell
.61
.42
A3
PA2
NS
There is no genetic influence on PA2 that is
independent of the genetic influence on K spelling
37
Cholesky decomposition ofrapid naming development
RN1 preschool rapid naming--colours,
objects RN2 kindergarten rapid naming--colours,
letters, digits
.
A1
RN1
E1
.79
.46
.13
.59
A2
E2
RN2
53
.47
38
Summary of developmental data for two single
variables

• Phonological awareness and rapid naming both show
  both genetic continuity and genetic change across
  the period of development that we have tracked.
  In the case of PA, the second genetic source may
  be genetic influence on orthographic processes.
  In the case of RN, the change may be due to
  introduction of letters and digits in kindergarten

39
Cholesky decomposition ofmultivariate
preschool-kindergarten development additive
genetic effects
PR1
.47
A1
preschool
.61
PA1
A2
.50
.41
RN1
A2
A3
.58
.
.72
A4
READ
.41
kindergarten
significance uncertain with current sample size

40
Cholesky decomposition ofmultivariate
preschool-kindergarten development shared
environment effects
PR1
.85
C1
preschool
.52
C2
PA1
.28
.40
.24
RN1
.
.31
kindergarten
READ

41
Cholesky decomposition ofmultivariate
preschool-kindergarten development unique
environment effects
PR1
.23
E1
preschool
.16
PA1
E3
.40
RN1
.
.15
kindergarten
READ

42
Summary of developmental multivariate data

• A single set of genes influences preschool PA, RN
  and PRINT and kindergarten READ
• A second genetic factor affects PA but not RN or
  READ
• A third genetic factor affects RN but not READ
• Thus, PA and RN only share genetic variance with
  READ through genes shared with PRINT

43
Summary of developmental multivariate data (cont)

• A shared-environment factor affects preschool PA,
  RN and PRINT and kindergarten READ
• A second preschool factor affect PA and RN (only)
• There is no new shared environment factor
  emerging in kindergarten

44
Results of Mx modeling on Grade 1 literacy
variables as latent traits
45
We see that word reading and reading
comprehension are both substantially affected by
genesbut, are they the same genes?
46
Cholesky decomposition ofGrade 1 word reading
and reading comprehension
.
A1
word
E1
.91
.40
.27
.90
comp
47
Another longitudinal analysis Cholesky
decomposition of kindergarten and Grade 1 word
reading
.
A1
kind.
C1
.82
.50
.77
E paths omitted modest effects at all three
possible paths
A2
Gd 1
.44
48
Grade 1 summary

• Substantial genetic effects on word reading,
  reading comprehension, and spelling in Grade 1
• Genetic effect on word reading accounts for all
  of the genetic effect on reading comprehension
  (Cholesky decomposition, plus genetic correlation
  of .97)
• New genes kick in for word reading in Grade 1
  on top of those shared with kindergarten

49
Grade 1 summary (cont)

• No reliable shared environment effects in
  evidence at Grade 1
• Because our twins almost always share schools,
  little evidence of a differentiating school
  effect, therefore

50
Summary and implications

• Reading is substantially affected by genes as
  early as kindergarten
• Most of these genes are in play prior to school,
  influencing processes foundational for literacy
  growth
• Genes are beyond our control, therefore, we need
  to pull on the environmental levers as
  intelligently as possible

51
Summary and implications 2

• There were no new shared environment effects on
  reading in Kindergarten, and none were detectable
  at all in Grade 1, in our sample
• Twins almost always share schools, if not
  teachers
• Thus, schools may not be contributing to whatever
  differential reading scores exist between schools
• So public policy measures that penalise schools
  for poor reading levels are misguided, perhaps by
  around 180 degrees

52
The future (funds permitting)

• Completion of existing cohorts (completion in
  2009)
• Extension to 4th grade
• More detailed comprehension measures
• More detailed print exposure measures (diary
  methods?)
• Data from other school subjects
• Integration with imagingfMRI, MEG?

53
Acknowledgements

• Australian Research Council, Australian Twin
  Registry, National Institute of Child Health and
  Human Development, Stavanger University College
  and Research Council of Norway, Swedish Research
  Council, and our many testers, coordinators,
  database managers and of course the twins and
  their families

54
Addendum

• So far we have focused on literacy
• What about spoken language in our data?
• Recall that there were modest but significant
  genetic effects on grammar, morphology and
  vocabulary
• Where do they come from?

55
An example

• of a test item from the TROG

56
point to the boy the dog chases is big
57
A hypothesis

• Genetic differences among 4-5 year-old children
  on tests of grammar reflect performance rather
  than competence factors, based on the
  observation that the structures tested are
  already present in the repertoires of normal
  children of this age group

58
Another hypothesis

• Genetic differences among 4-5 year-old children
  in vocabulary derive from genetic differences in
  ability to fix phonetic forms (as assessed by
  nonword repetition)

59
Cholesky decomposition of preschool working
memory, vocabulary and morph/syntax
A1
wm
.76
.51
voc
(No other genetic path close to significance)
.52
mor/syn
60
Cholesky decomposition shared environment
effects (preschool)
C1
wm
.63
.63
C2
voc
.58
.65
mor/syn
61
Cholesky decomposition of preschool working
memory composite and vocabulary and kindergarten
TROG additive genetic effects
A1
wm
.78
.52
voc
(No other genetic path close to significance)
.40
TROG
62
Cholesky decomposition shared environment
effects (Year 1)
C1
wm
.62
.64
C2
voc
.56
.24
.19
TROG
63
Summary and implications

• A working memory composite accounts for all of
  the genetic influence on our vocabulary and
  morphology/syntax measures
• Thus there is no evidence in our data for
  independent genetic influence on higher
  language functions
• The shared environment picture is more complex,
  with a second factor affecting vocabulary (and
  TROG)

64
Summary and implications (cont)

• We speculate that working memory influences
• vocabulary via fixation of phonetic form
• TROG via performance demands of test itself
• In any case, research into genes, environment and
  language needs to be sensitive to complex nature
  of language variables