Structural Variations Contribute to the Genetic Etiology of Autism Spectrum Disorder and Language Impairments.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by restrictive interests and/or repetitive behaviors and deficits in social interaction and communication. ASD is a multifactorial disease with a complex polygenic genetic architecture. Its genetic contributing factors are not yet fully understood, especially large structural variations (SVs). In this study, we aimed to assess the contribution of SVs, including copy number variants (CNVs), insertions, deletions, duplications, and mobile element insertions, to ASD and related language impairments in the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Within the cohort, ~77% of the families contain SVs that followed expected segregation or de novo patterns and passed our filtering criteria. These SVs affected 344 brain-expressed genes and can potentially contribute to the genetic etiology of the disorders. Gene Ontology and protein-protein interaction network analysis suggested several clusters of genes in different functional categories, such as neuronal development and histone modification machinery. Genes and biological processes identified in this study contribute to the understanding of ASD and related neurodevelopment disorders.

The Rosetta Phenotype Harmonization Method Facilitates Finding a Relationship Quantitative Trait Locus for a Complex Cognitive Trait.

Genetics researchers increasingly combine data across many sources to increase power and to conduct analyses that cross multiple individual studies. However, there is often a lack of alignment on outcome measures when the same constructs are examined across studies. This inhibits comparison across individual studies and may impact the findings from meta-analysis. Using a well-characterized genotypic (brain-derived neurotrophic factor: BDNF) and phenotypic constructs (working memory and reading comprehension), we employ an approach called Rosetta, which allows for the simultaneous examination of primary studies that employ related but incompletely overlapping data. We examined four studies of BDNF, working memory, and reading comprehension with a combined sample size of 1711 participants. Although the correlation between working memory and reading comprehension over all participants was high, as expected (ρ = 0.45), the correlation between working memory and reading comprehension was attenuated in the BDNF Met/Met genotype group (ρ = 0.18, n.s.) but not in the Val/Val (ρ = 0.44) or Val/Met (ρ = 0.41) groups. These findings indicate that Met/Met carriers may be a unique and robustly defined subgroup in terms of memory and reading comprehension. This study demonstrates the utility of the Rosetta method when examining complex phenotypes across multiple studies, including psychiatric genetic studies, as shown here, and also for the mega-analysis of cohorts generally.

Common genetic risk factors in ASD and ADHD co-occurring families.

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are two major neurodevelopmental disorders that frequently co-occur. However, the genetic mechanism of the co-occurrence remains unclear. The New Jersey Language and Autism Genetics Study (NJLAGS) collected more than 100 families with at least one member affected by ASD. NJLAGS families show a high prevalence of ADHD and provide a good opportunity to study shared genetic risk factors for ASD and ADHD. The linkage study of the NJLAGS families revealed regions on chromosomes 12 and 17 that are significantly associated with ADHD. Using whole-genome sequencing data on 272 samples from 73 NJLAGS families, we identified potential risk genes for ASD and ADHD. Within the linkage regions, we identified 36 genes that are associated with ADHD using a pedigree-based gene prioritization approach. KDM6B (Lysine Demethylase 6B) is the highest-ranking gene, which is a known risk gene for neurodevelopmental disorders, including ASD and ADHD. At the whole-genome level, we identified 207 candidate genes from the analysis of both small variants and structure variants, including both known and novel genes. Using enrichment and protein-protein interaction network analyses, we identified gene ontology terms and pathways enriched for ASD and ADHD candidate genes, such as cilia function and cation channel activity. Candidate genes and pathways identified in our study improve the understanding of the genetic etiology of ASD and ADHD and will lead to new diagnostic or therapeutic interventions for ASD and ADHD in the future.

MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders.

Autism spectrum disorder (ASD) is a childhood neurodevelopmental disorder with a complex and heterogeneous genetic etiology. MicroRNA (miRNA), a class of small non-coding RNAs, could regulate ASD risk genes post-transcriptionally and affect broad molecular pathways related to ASD and associated disorders. Using whole-genome sequencing, we analyzed 272 samples in 73 families in the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Families with at least one ASD patient were recruited and were further assessed for language impairment, reading impairment, and other associated phenotypes. A total of 5104 miRNA variants and 1,181,148 3' untranslated region (3' UTR) variants were identified in the dataset. After applying several filtering criteria, including population allele frequency, brain expression, miRNA functional regions, and inheritance patterns, we identified high-confidence variants in five brain-expressed miRNAs (targeting 326 genes) and 3' UTR miRNA target regions of 152 genes. Some genes, such as SCP2 and UCGC, were identified in multiple families. Using Gene Ontology overrepresentation analysis and protein-protein interaction network analysis, we identified clusters of genes and pathways that are important for neurodevelopment. The miRNAs and miRNA target genes identified in this study are potentially involved in neurodevelopmental disorders and should be considered for further functional studies.

Within-task variability on standardized language tests predicts autism spectrum disorder: a pilot study of the Response Dispersion Index.

BACKGROUND: Qualitatively atypical language development characterized by non-sequential skill acquisition within a developmental domain, which has been called developmental deviance or difference, is a common characteristic of autism spectrum disorder (ASD). We developed the Response Dispersion Index (RDI), a measure of this phenomenon based on intra-subtest scatter of item responses on standardized psychometric assessments, to assess the within-task variability among individuals with language impairment (LI) and/or ASD. METHODS: Standard clinical assessments of language were administered to 502 individuals from the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Participants were divided into four diagnostic groups: unaffected, ASD-only, LI-only, and ASD + LI. For each language measure, RDI was defined as the product of the total number of test items and the sum of the weight (based on item difficulty) of test items missed. Group differences in RDI were assessed, and the relationship between RDI and ASD diagnosis among individuals with LI was investigated for each language assessment. RESULTS: Although standard scores were unable to distinguish the LI-only and ASD/ASD + LI groups, the ASD/ASD + LI groups had higher RDI scores compared to LI-only group across all measures of expressive, pragmatic, and metalinguistic language. RDI was positively correlated with quantitative ASD traits across all subgroups and was an effective predictor of ASD diagnosis among individuals with LI. CONCLUSIONS: The RDI is an effective quantitative metric of developmental deviance/difference that correlates with ASD traits, supporting previous associations between ASD and non-sequential skill acquisition. The RDI can be adapted to other clinical measures to investigate the degree of difference that is not captured by standard performance summary scores.

Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds.

Auditory detection thresholds for certain frequencies of both amplitude modulated (AM) and frequency modulated (FM) dynamic auditory stimuli are associated with reading in typically developing and dyslexic readers. We present the first behavioral and molecular genetic characterization of these two auditory traits. Two extant extended family datasets were given reading tasks and psychoacoustic tasks to determine FM 2 Hz and AM 20 Hz sensitivity thresholds. Univariate heritabilities were significant for both AM (h 2  = 0.20) and FM (h 2  = 0.29). Bayesian posterior probability of linkage (PPL) analysis found loci for AM (12q, PPL = 81 %) and FM (10p, PPL = 32 %; 20q, PPL = 65 %). Bivariate heritability analyses revealed that FM is genetically correlated with reading, while AM was not. Bivariate PPL analysis indicates that FM loci (10p, 20q) are not also associated with reading.

A genome scan for loci shared by autism spectrum disorder and language impairment.

OBJECTIVE: The authors conducted a genetic linkage study of families that have both autism spectrum disorder (ASD) and language-impaired probands to find common communication impairment loci. The hypothesis was that these families have a high genetic loading for impairments in language ability, thus influencing the language and communication deficits of the family members with ASD. Comprehensive behavioral phenotyping of the families also enabled linkage analysis of quantitative measures, including normal, subclinical, and disordered variation in all family members for the three general autism symptom domains: social, communication, and compulsive behaviors. METHOD: The primary linkage analysis coded persons with either ASD or specific language impairment as "affected." The secondary linkage analysis consisted of quantitative metrics of autism-associated behaviors capturing normal to clinically severe variation, measured in all family members. RESULTS: Linkage to language phenotypes was established at two novel chromosomal loci, 15q23-26 and 16p12. The secondary analysis of normal and disordered quantitative variation in social and compulsive behaviors established linkage to two loci for social behaviors (at 14q and 15q) and one locus for repetitive behaviors (at 13q). CONCLUSION: These data indicate shared etiology of ASD and specific language impairment at two novel loci. Additionally, nonlanguage phenotypes based on social aloofness and rigid personality traits showed compelling evidence for linkage in this study group. Further genetic mapping is warranted at these loci.

Gene × gene interaction in shared etiology of autism and specific language impairment.

BACKGROUND: To examine the relationship between autism spectrum disorders (ASD) and specific language impairment (SLI), family studies typically take a comparative approach where families with one disease are examined for traits of the other disease. In contrast, the present report is the first study with both disorders required to be present in each family to provide a more direct test of the hypothesis of shared genetic etiology. METHODS: We behaviorally assessed 51 families including at least one person with ASD and at least one person with SLI (without ASD). Pedigree members were tested with 22 standardized measures of language and intelligence. Because these extended families include a nonshared environmental contrast, we calculated heritability, not just familiality, for each measure twice: 1) baseline heritability analysis, compared with; 2) heritability estimates after statistically removing ASD subjects from pedigrees. RESULTS: Significant increases in heritability on four supra-linguistic measures (including Pragmatic Judgment) and a composite language score but not on any other measures were observed when removing ASD subjects from the analysis, indicating differential genetic effects that are unique to ASD. Nongenetic explanations such as effects of ASD severity or measurement error or low score variability in ASD subjects were systematically ruled out, leaving the hypothesis of nonadditive genetics effects as the potential source of the heritability change caused by ASD. CONCLUSIONS: Although the data suggest genetic risk factors common to both SLI and ASD, there are effects that seem unique to ASD, possibly caused by nonadditive gene-gene interactions of shared risk loci.

Combined linkage and linkage disequilibrium analysis of a motor speech phenotype within families ascertained for autism risk loci.

Using behavioral and genetic information from the Autism Genetics Resource Exchange (AGRE) data set we developed phenotypes and investigated linkage and association for individuals with and without Autism Spectrum Disorders (ASD) who exhibit expressive language behaviors consistent with a motor speech disorder. Speech and language variables from Autism Diagnostic Interview-Revised (ADI-R) were used to develop a motor speech phenotype associated with non-verbal or unintelligible verbal behaviors (NVMSD:ALL) and a related phenotype restricted to individuals without significant comprehension difficulties (NVMSD:C). Using Affymetrix 5.0 data, the PPL framework was employed to assess the strength of evidence for or against trait-marker linkage and linkage disequilibrium (LD) across the genome. Ingenuity Pathway Analysis (IPA) was then utilized to identify potential genes for further investigation. We identified several linkage peaks based on two related language-speech phenotypes consistent with a potential motor speech disorder: chromosomes 1q24.2, 3q25.31, 4q22.3, 5p12, 5q33.1, 17p12, 17q11.2, and 17q22 for NVMSD:ALL and 4p15.2 and 21q22.2 for NVMSD:C. While no compelling evidence of association was obtained under those peaks, we identified several potential genes of interest using IPA. CONCLUSION: Several linkage peaks were identified based on two motor speech phenotypes. In the absence of evidence of association under these peaks, we suggest genes for further investigation based on their biological functions. Given that autism spectrum disorders are complex with a wide range of behaviors and a large number of underlying genes, these speech phenotypes may belong to a group of several that should be considered when developing narrow, well-defined, phenotypes in the attempt to reduce genetic heterogeneity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11689-010-9063-2) contains supplementary material, which is available to authorized users.

Increasing genotype-phenotype model determinism: application to bivariate reading/language traits and epistatic interactions in language-impaired families.

While advances in network and pathway analysis have flourished in the era of genome-wide association analysis, understanding the genetic mechanism of individual loci on phenotypes is still readily accomplished using genetic modeling approaches. Here, we demonstrate two novel genotype-phenotype models implemented in a flexible genetic modeling platform. The examples come from analysis of families with specific language impairment (SLI), a failure to develop normal language without explanatory factors such as low IQ or inadequate environment. In previous genome-wide studies, we observed strong evidence for linkage to 13q21 with a reading phenotype in language-impaired families. First, we elucidate the genetic architecture of reading impairment and quantitative language variation in our samples using a bivariate analysis of reading impairment in affected individuals jointly with language quantitative phenotypes in unaffected individuals. This analysis largely recapitulates the baseline analysis using the categorical trait data (posterior probability of linkage (PPL) = 80%), indicating that our reading impairment phenotype captured poor readers who also have low language ability. Second, we performed epistasis analysis using a functional coding variant in the brain-derived neurotrophic factor (BDNF) gene previously associated with reduced performance on working memory tasks. Modeling epistasis doubled the evidence on 13q21 and raised the PPL to 99.9%, indicating that BDNF and 13q21 susceptibility alleles are jointly part of the genetic architecture of SLI. These analyses provide possible mechanistic insights for further cognitive neuroscience studies based on the models developed herein.

Using early standardized language measures to predict later language and early reading outcomes in children at high risk for language-learning impairments.

The aim of the study was to examine the profiles of children with a family history (FH+) of language-learning impairments (LLI) and a control group of children with no reported family history of LLI (FH-) and identify which language constructs (receptive or expressive) and which ages (2 or 3 years) are related to expressive and receptive language abilities, phonological awareness, and reading abilities at ages 5 and 7 years. Participants included 99 children (40 FH+ and 59 FH-) who received a standardized neuropsychological battery at 2, 3, 5, and 7 years of age. As a group, the FH+ children had significantly lower scores on all language measures at 2 and 3 years, on selected language and phonological awareness measures at 5 years, and on phonological awareness and nonword reading at 7 years. Language comprehension at 3 years was the best predictor of later language and early reading for both groups. These results support past work suggesting that children with a positive family history of LLI are at greater risk for future language and reading problems through their preschool and early school-age years. Furthermore, language comprehension in the early years is a strong predictor of future language-learning status.

Functional connectivity of the sensorimotor area in naturally sleeping infants.

Patterns of cortical functional connectivity in normal infants were examined during natural sleep by observing the time course of very low frequency oscillations. Such oscillations represent fluctuations in blood oxygenation level and cortical blood flow thus allowing computation of neurophysiologic connectivity. Structural and resting-state information were acquired for 11 infants, with a mean age of 12.8 months, using a GE 1.5 T MR scanner. Resting-state data were processed and significant functional connectivity within the sensorimotor area was identified using independent component analysis. Unilateral functional connectivity in the developing sensory-motor cortices was observed. Power spectral analysis showed that slow frequency oscillations dominated the hemodynamic signal at this age, with, on average, a peak frequency for all subjects of 0.02 Hz. Our data suggest that there is more intrahemispheric than interhemispheric connectivity in the sensorimotor area of naturally sleeping infants. This non-invasive imaging technique, developed to allow reliable scanning of normal infants without sedation, enabled computation of neurophysiologic connectivity for the first time in naturally sleeping infants. Such techniques permit elucidation of the role of slow cortical oscillations during early brain development and may reveal critical information regarding the normative development and lateralization of brain networks across time.

Assessment of functional development in normal infant brain using arterial spin labeled perfusion MRI.

Arterial spin labeled (ASL) perfusion MRI provides a noninvasive approach for longitudinal imaging of regional brain function in infants. In the present study, continuous ASL (CASL) perfusion MRI was carried out in normally developing 7- and 13-month-old infants while asleep without sedation. The 13-month infant group showed an increase (P<0.05) of relative CBF in frontal regions as compared to the 7-month group using a region of interest based analysis. Using a machine-learning algorithm to automatically classify the relative CBF maps of the two infant groups, a significant (P<0.05, permutation testing) regional CBF increase was found in the hippocampi, anterior cingulate, amygdalae, occipital lobes, and auditory cortex in the 13-month-old infants. These results are consistent with current understanding of infant brain development and demonstrate the feasibility of using perfusion MRI to noninvasively monitor developing brain function.

Examination of potential overlap in autism and language loci on chromosomes 2, 7, and 13 in two independent samples ascertained for specific language impairment.

Specific language impairment is a neurodevelopmental disorder characterized by impairments essentially restricted to the domain of language and language learning skills. This contrasts with autism, which is a pervasive developmental disorder defined by multiple impairments in language, social reciprocity, narrow interests and/or repetitive behaviors. Genetic linkage studies and family data suggest that the two disorders may have genetic components in common. Two samples, from Canada and the US, selected for specific language impairment were genotyped at loci where such common genes are likely to reside. Significant evidence for linkage was previously observed at chromosome 13q21 in our Canadian sample (HLOD 3.56) and was confirmed in our US sample (HLOD 2.61). Using the posterior probability of linkage (PPL) to combine evidence for linkage across the two samples yielded a PPL over 92%. Two additional loci on chromosome 2 and 7 showed weak evidence for linkage. However, a marker in the cystic fibrosis transmembrane conductance regulator (7q31) showed evidence for association to SLI, confirming results from another group (O'Brien et al. 2003). Our results indicate that using samples selected for components of the autism phenotype may be a useful adjunct to autism genetics.

Specific language impairment in families: evidence for co-occurrence with reading impairments.

Two family aggregation studies report the occurrence and co-occurrence of oral language impairments (LIs) and reading impairments (RIs). Study 1 examined the occurrence (rate) of LI and RI in children with specific language impairment (SLI probands), a matched control group, and all nuclear family members. Study 2 included a larger sample of SLI probands, as well as their nuclear and extended family members. Probands and their family members who met specific criteria were classified as language and/or reading impaired based on current testing. In Study 1, the rates of LI and RI for nuclear family members (excluding probands) were significantly higher than those for control family members. In the SLI families, affected family members were more likely to have both LI and RI than either impairment alone. In Study 2, 68% of the SLI probands also met the diagnostic classification for RI. The language and RI rates for the other family members, excluding probands, were 25% and 23% respectively, with a high degree of co-occurrence of LI and RI (46%) in affected individuals. Significant sex ratio differences were found across generations in the families of SLI probands. There were more male than female offspring in these families, and more males than females were found to have both LIs and RIs. Results demonstrate that when LIs occur within families of SLI probands, these impairments generally co-occur with RIs. Our data are also consistent with prior findings that males show impairments more often than females.

A major susceptibility locus for specific language impairment is located on 13q21.

Children who fail to develop language normally-in the absence of explanatory factors such as neurological disorders, hearing impairment, or lack of adequate opportunity-are clinically described as having specific language impairment (SLI). SLI has a prevalence of approximately 7% in children entering school and is associated with later difficulties in learning to read. Research indicates that genetic factors are important in the etiology of SLI. Studies have consistently demonstrated that SLI aggregates in families. Increased monozygotic versus dizygotic twin concordance rates indicate that heredity, not just shared environment, is the cause of the familial clustering. We have collected five pedigrees of Celtic ancestry that segregate SLI, and we have conducted genomewide categorical linkage analysis, using model-based LOD score techniques. Analysis was conducted under both dominant and recessive models by use of three phenotypic classifications: clinical diagnosis, language impairment (spoken language quotient <85) and reading discrepancy (nonverbal IQ minus non-word reading >15). Chromosome 13 yielded a maximum multipoint LOD score of 3.92 under the recessive reading discrepancy model. Simulation to correct for multiple models and multiple phenotypes indicated that the genomewide empirical P value is <.01. As an alternative measure, we also computed the posterior probability of linkage (PPL), obtaining a PPL of 53% in the same region. One other genomic region yielded suggestive results on chromosome 2 (multipoint LOD score 2.86, genomic P value <.06 under the recessive language impairment model). Our findings underscore the utility of traditional LOD-score-based methods in finding genes for complex diseases, specifically, SLI.