Communication Disorders are common in children, may persist into adulthood, and are recognized as causing pervasive and lifelong disabilities. Three communication disorders, speech sound disorder, reading disorder and language impairment, are often observed as a triumvirate in individuals who have severe disability. Speech sound disorder is diagnosed first in early childhood, and likely forms the cornerstone of the tri-level deficit, although the exact biological root of these comorbidities is unknown. Individuals with the most severe forms of speech sound disorder that persist into adulthood, with or without other comorbidities, show the greatest shortfalls in terms of academic achievements. Difficulties during the scholastic years effectively influence the realization and sustenance of professional careers, and these individuals tend to have higher unemployment rates, and lower earning potential. In previous work, we have shown that speech sound disorder has a genetic basis and clusters in families, particularly among children affected with severe forms of the disorder. Using our database of 24-year longitudinal data, we propose to find families with affecteds followed by whole exome sequencing of two parents and affected children at an average coverage of >50X. We will use state-of-the-art statistical and bioinformatic methods to find biologically meaningful variants that cause speech sound disorder. This approach has been spectacularly successful for unsolved recessive and dominant Mendelian diseases that run in families, but also among sporadic cases of rare diseases. In medical genetics, the first step towards translation is finding clinically actionable variants that can be validated, and developed into diagnostic tools. A decade ago, identification of a highly penetrant, discrete genetic variant in FOXP2 in a single family was the first step for the field of speech and language disorders. In our current plan, we are scaling the search neighborhood to the level of the entire protein-coding exome, rather than starting with single genes. Our design is based on examination of exomes of two families which do not show mutations in FOXP2, and a vast supporting literature that suggests that mutations in this gene are not typical in speech sound disorder. Approximately 2.5 million markers will be typed in all members of the family. Using the scaffold of the 2.5 million markers, and exome data from the trio, exomic information will be imputed in all family members. We will use this information to confirm segregation of variants in affected and unaffected individuals, and examine modes of inheritance. This suite of techniques will allow us to identify new genes for speech sound disorder. It may ultimately be feasible to use these newly identified variants for early diagnosis, and to subtype speech sound disorders into more homogeneous categories, subsets of which could proactively be targeted for intensive behavioral or other therapy.

Public Health Relevance

Communication disorders are highly prevalent in the US with approximately 42 million people (1 in 6) reporting some type of communication disorder. Of these the three most common are Speech Sound Disorder (SSD), Reading Disorder (RD) and Language Impairment (LI), and these bear high societal and personal costs. The research in this application will help us (a) discover novel loci specific to severe SSD, (b) clarify subtypes f SSD, and (c) lead to development of new statistical strategies for complex disorders that may universally be applicable to RD and LI and other unsolved neurodevelopmental disorders.

National Institute of Health (NIH)
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Language and Communication Study Section (LCOM)
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Shekim, Lana O
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Case Western Reserve University
Schools of Medicine
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Stein, Catherine M; Truitt, Barbara; Deng, Fenghua et al. (2014) Association between AVPR1A, DRD2, and ASPM and endophenotypes of communication disorders. Psychiatr Genet 24:191-200
Hayes, Matthew; Li, Jing (2013) Bellerophon: a hybrid method for detecting interchromosomal rearrangements at base pair resolution using next-generation sequencing data. BMC Bioinformatics 14 Suppl 5:S6