Association of
1 / 1

Acknowledgements This research was supported by grants DC00496 and DC02746 from the National Institute on Deafness and Other Communicative Disorders. - PowerPoint PPT Presentation

Association of FOXP2 genetic markers with Procedural Learning and Language

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

Download Presentationdownload

Acknowledgements This research was supported by grants DC00496 and DC02746 from the National Institute on Deafness and Other Communicative Disorders.

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

Slide1 l.jpg

Association of FOXP2 genetic markers with Procedural Learning and Language

J. B. Tomblin1, M. H. Christiansen2, J. B. Bjork3, S.K. Iyengar4, J.M. Murray3. 1) Dept Speech Pathology and Audiology, U of Iowa, 2) Dept Psychology, Cornell University; 3) Dept Pediatrics, U of Iowa; 4) Dept Epidemiology and Biostatistics, Case Western Reserve University

  • Introduction

  • Statistical learning of sequential relationships has emerged as a paradigm for studying general-purpose learning systems potentially subserving language development.

  • Procedural learning may serve as an important neurocognitive basis of this statistical learning, particularly with respect to grammar.

  • An association between procedural learning and grammar has also been proposed for FOXP2-related language problems. Members of the KE family with a R553H FOXP2 mutation have poor language abilities, especially within grammar. The presence of motor planning difficulties in these individuals and evidence of abnormal basal ganglia support the hypothesis that procedural learning deficits may be an underlying causal factor.

  • The serial reaction time (SRT) task has often been used to measure procedural learning.


Table 1. Tests of genotype effects

For intercept and learning rate

across 6 SNPs

The reaction-time data were analyzed using multilevel statistical modeling (growth-curve analysis) to test for differences in learning rates during the patterned trials as a function of the participant’s genotype at each SNP locus. A significant association was found between variance in SNP genotype and SRT learning rate for SNPs rs1916988 (CC/TT, p<.0004) and rs7785701 (CC/GG, p< .018) (also see Table 1 and Figure 4). One other SNP (rs1005958) approached significance (p=.053). Individuals with the CC genotype at the rs1916988 SNP were generally slower than the other two phenotypes but also showed a significant negative quadratic feature characterized by an initial slowing followed by gains in performance. A similar, but less pronounced, pattern was found for rs7785701.

  • Tomblin et al. (2007) has shown that individuals with SLI are slower at learning probabilistic sequences during a SRT learning task compared to normal language learners (NL). These results are shown in Figure 1. The SLI group presented a significant negative quadratic function, whereas the NL group showed a positive quadratic function.

  • Thus, poorer learning of sequential relations is associated with poor language learning.

Figure 1. Reaction times of adolescents with SLI and normal language controls (NL) in the pattern phase of an SRT task

Figure 4. Reaction times of adolescents during pattern trials on a SRT task grouped according to genotype at SNP rs9196988 (left panel) showing slower learning and a significant negative quadratic function for the members of the CC genotype group in contrast to the TT and TC genotype group. Similar learning differences were found for the GG and CG genotypes at SNP rs7785701 (right panel) where a negative quadratic learning function contrasted with the CC genotype group.

Question: Are individual differences in SRT learning associated with allelic variations in candidate SNPs within FOXP2?

  • Conclusions

  • SRT Learning

  • Learning the sequential probabilities within an SRT task, as reflected by declines in RT, is thought to be attributable to the mechanism of procedural learning. Previously, it has been shown that FOXP2 is expressed in brain structures concerned with procedural learning and mutations in FOXP2 are associated with speech and language deficits that may depend on procedural learning and memory. This study provides the first direct evidence that variation within FOXP2 is likely to contribute to individual differences in procedural learning.

  • Two SNPs were significantly associated with SRT learning rates and one approached a significant association. Of particular significance is the finding that the CC genotype at rs1916988 had the same negative quadratic shape as has been associated with individuals with SLI. This feature of SRT learning is unusual and suggests abnormal dynamics of learning during the early pattern trial blocks. We have previouslyproposed that these abnormalities could be due to excessive buildup of response competition due to ineffective inhibitory neural mechanisms.

  • Genetics

  • We hypothesize that our significant results are associated with variation in potential 5 regulatory elements of FOXP2 (s1, s2, and s3) upstream from the known coding sequence. Future genotyping of SNPs both 5 and 3 of the most significant SNP (rs1916988) could provide further evidence in support of the association of the upstream region of FOXP2 to SRT learning. Additionally, it is hypothesized that the strength of the p-value will decrease significantly as SNPs are genotyped within the major haplotype block of PPP1R3A (see Figure 3), a seemingly unrelated gene whose protein, a glycogen-associated form of protein phosphatase-1, is thought to be involved in noninsulin-dependent diabetes mellitus and obesity.


SRT Learning

The participants were 123 8th-grade adolescents. Stimuli comprised sequences of images which appeared in 1 of 4 horizontally arranged boxes. These first appeared in a random order for 100 trials, followed by 200 trials of patterned sequences, and ending in a sequence of 100 random trials. Participants pressed a button corresponding to the position of the image as soon as they saw it appear. Reaction time, as associated with a button push, declined during pattern learning. (See Figure 1)

  • Genotyping

  • 6 SNPs were selected to cover the principal haplotype block structure of the FOXP2 gene, including blocks of high Linkage Disequilibrium (LD) that continued beyond the exonsin both the 5 and 3 directions (See Figure 3). TaqMan genotyping reactions were then performed on tissue samples obtained from the participants using standard procedures. Finally, statistical analyses were employed to detect any significance in the frequency of specific genotypes between NL and SLI individuals.

Figure 3. Schematic of the principal haplotype block structure of FOXP2 and PPP1R3A from the HapMap database. Red boxes denote the positions of significant, or near-significant, SNPs within major regions of LD within FOXP2.

Figure 2. Schematic of the SRT learning task showing random and pattern trial blocks and the stimulus array with the image in the second box.




2, 4, 1, 3, 4, 2, 1, 4, 3, 1


This research was supported by grants DC00496 and DC02746 from the National Institute on Deafness and Other Communicative Disorders.

100 trials

100 trials

100 trials

100 trials

  • Login