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Petrill SA, Klamer BG, Buyske S, Willcutt EG, Gruen JR, Francis DJ, Flax JF, Brzustowicz LM, Bartlett CW. The Rosetta Phenotype Harmonization Method Facilitates Finding a Relationship Quantitative Trait Locus for a Complex Cognitive Trait. Genes (Basel) 2023; 14:1748. [PMID: 37761888 PMCID: PMC10531321 DOI: 10.3390/genes14091748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 08/28/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023] Open
Abstract
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.
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Affiliation(s)
- Stephen A. Petrill
- Department of Psychology, College of Arts and Sciences, The Ohio State University, Columbus, OH 43210, USA;
| | - Brett G. Klamer
- Center for Biostatistics, The Ohio State University, Columbus, OH 43210, USA;
| | - Steven Buyske
- Department of Statistics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA;
| | - Erik G. Willcutt
- Department of Psychology, University of Colorado Boulder, Boulder, CO 80309, USA;
| | - Jeffrey R. Gruen
- Departments of Pediatrics and of Genetics, Yale Medical School, New Haven, CT 06511, USA;
| | - David J. Francis
- Texas Institute for Measurement, Evaluation, and Statistics, University of Houston, Houston, TX 77004, USA;
| | - Judy F. Flax
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (J.F.F.); (L.M.B.)
| | - Linda M. Brzustowicz
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (J.F.F.); (L.M.B.)
| | - Christopher W. Bartlett
- The Steve & Cindy Rasmussen Institute for Genomic Medicine in the Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH 43205, USA
- Department of Pediatrics, College of Medicine, The Ohio State University, Columbus, OH 43205, USA
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Alibutud R, Hansali S, Cao X, Zhou A, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Structural Variations Contribute to the Genetic Etiology of Autism Spectrum Disorder and Language Impairments. Int J Mol Sci 2023; 24:13248. [PMID: 37686052 PMCID: PMC10487745 DOI: 10.3390/ijms241713248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 08/24/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
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.
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Affiliation(s)
- Rohan Alibutud
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Sammy Hansali
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Xiaolong Cao
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Anbo Zhou
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Vaidhyanathan Mahaganapathy
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Marco Azaro
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Christine Gwin
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Sherri Wilson
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Steven Buyske
- Department of Statistics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA;
| | - Christopher W. Bartlett
- The Steve Cindy Rasmussen Institute for Genomic Medicine, Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH 43205, USA;
- Department of Pediatrics, College of Medicine, The Ohio State University, Columbus, OH 43205, USA
| | - Judy F. Flax
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Linda M. Brzustowicz
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
- The Human Genetics Institute of New Jersey, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jinchuan Xing
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (R.A.); (S.H.); (X.C.); (A.Z.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
- The Human Genetics Institute of New Jersey, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
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3
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Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. Common genetic risk factors in ASD and ADHD co-occurring families. Hum Genet 2023; 142:217-230. [PMID: 36251081 PMCID: PMC10177627 DOI: 10.1007/s00439-022-02496-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 10/10/2022] [Indexed: 12/01/2022]
Abstract
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.
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Affiliation(s)
- Anbo Zhou
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Xiaolong Cao
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.,Division of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | | | - Marco Azaro
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Christine Gwin
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Sherri Wilson
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Steven Buyske
- Department of Statistics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Christopher W Bartlett
- The Steve Cindy Rasmussen Institute for Genomic Medicine, Battelle Center for Computational Biology, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA.,Department of Pediatrics, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Judy F Flax
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Linda M Brzustowicz
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.,The Human Genetics Institute of New Jersey, Rutgers, The State University of New Jersey, 145 Bevier Road, Piscataway, NJ, 08854, USA
| | - Jinchuan Xing
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA. .,The Human Genetics Institute of New Jersey, Rutgers, The State University of New Jersey, 145 Bevier Road, Piscataway, NJ, 08854, USA.
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4
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Wong A, Zhou A, Cao X, Mahaganapathy V, Azaro M, Gwin C, Wilson S, Buyske S, Bartlett CW, Flax JF, Brzustowicz LM, Xing J. MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders. Genes (Basel) 2022; 13:genes13081329. [PMID: 35893067 PMCID: PMC9329941 DOI: 10.3390/genes13081329] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 07/19/2022] [Accepted: 07/22/2022] [Indexed: 12/13/2022] Open
Abstract
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.
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Affiliation(s)
- Anthony Wong
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Anbo Zhou
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Xiaolong Cao
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Vaidhyanathan Mahaganapathy
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Marco Azaro
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Christine Gwin
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Sherri Wilson
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Steven Buyske
- Department of Statistics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA;
| | - Christopher W. Bartlett
- The Steve & Cindy Rasmussen Institute for Genomic Medicine, Battelle Center for Computational Biology, Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH 43215, USA;
- Department of Pediatrics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Judy F. Flax
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
| | - Linda M. Brzustowicz
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
- Human Genetics Institute of New Jersey, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Jinchuan Xing
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA; (A.W.); (A.Z.); (X.C.); (V.M.); (M.A.); (C.G.); (S.W.); (J.F.F.); (L.M.B.)
- Human Genetics Institute of New Jersey, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
- Correspondence:
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Hare-Harris AE, Mitchel MW, Myers SM, Mitchel AD, King BR, Ruocco BG, Martin CL, Flax JF, Brzustowicz LM. Within-task variability on standardized language tests predicts autism spectrum disorder: a pilot study of the Response Dispersion Index. J Neurodev Disord 2019; 11:21. [PMID: 31519145 PMCID: PMC6744656 DOI: 10.1186/s11689-019-9283-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Accepted: 08/28/2019] [Indexed: 11/30/2022] Open
Abstract
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. Electronic supplementary material The online version of this article (10.1186/s11689-019-9283-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Abby E Hare-Harris
- Department of Biological and Allied Health Sciences, Hartline Science Center, Bloomsburg University, 400 East Second St, Bloomsburg, PA, 17815, USA.
| | - Marissa W Mitchel
- Autism & Developmental Medicine Institute, Geisinger Health System, 120 Hamm Drive, Suite 2A, Lewisburg, PA, 17837, USA
| | - Scott M Myers
- Autism & Developmental Medicine Institute, Geisinger Health System, 120 Hamm Drive, Suite 2A, Lewisburg, PA, 17837, USA
| | - Aaron D Mitchel
- Psychology Department, O'Leary Center, Bucknell University, Lewisburg, PA, 17837, USA
| | - Brian R King
- Computer Science Department, Breakiron Building, Bucknell University, Lewisburg, PA, 17837, USA
| | - Brittany G Ruocco
- Genetics Department, Life Sciences Building, Rutgers University, 145 Bevier Road, Piscataway, NJ, 08854, USA
| | - Christa Lese Martin
- Autism & Developmental Medicine Institute, Geisinger Health System, 120 Hamm Drive, Suite 2A, Lewisburg, PA, 17837, USA
| | - Judy F Flax
- Genetics Department, Life Sciences Building, Rutgers University, 145 Bevier Road, Piscataway, NJ, 08854, USA
| | - Linda M Brzustowicz
- Genetics Department, Life Sciences Building, Rutgers University, 145 Bevier Road, Piscataway, NJ, 08854, USA
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Bruni M, Flax JF, Buyske S, Shindhelm AD, Witton C, Brzustowicz LM, Bartlett CW. Behavioral and Molecular Genetics of Reading-Related AM and FM Detection Thresholds. Behav Genet 2016; 47:193-201. [PMID: 27826669 DOI: 10.1007/s10519-016-9821-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2015] [Accepted: 09/28/2016] [Indexed: 12/24/2022]
Abstract
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.
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Affiliation(s)
- Matthew Bruni
- The Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Judy F Flax
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers The State University of New Jersey, Piscataway, NJ, USA
| | - Steven Buyske
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers The State University of New Jersey, Piscataway, NJ, USA.,Department of Statistics, Rutgers The State University of New Jersey, Piscataway, NJ, USA
| | - Amber D Shindhelm
- The Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Caroline Witton
- Aston Brain Centre, School of Life and Health Sciences, Aston University, Birmingham, B4 7ET, UK
| | - Linda M Brzustowicz
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers The State University of New Jersey, Piscataway, NJ, USA
| | - Christopher W Bartlett
- Department of Pediatrics, College of Medicine, The Ohio State University, Columbus, OH, USA. .,Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital & The Ohio State University, 575 Children's Crossroad, Columbus, OH, 43205, USA.
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7
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Bartlett CW, Hou L, Flax JF, Hare A, Cheong SY, Fermano Z, Zimmerman-Bier B, Cartwright C, Azaro MA, Buyske S, Brzustowicz LM. A genome scan for loci shared by autism spectrum disorder and language impairment. Am J Psychiatry 2014; 171:72-81. [PMID: 24170272 PMCID: PMC4431698 DOI: 10.1176/appi.ajp.2013.12081103] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
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.
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Affiliation(s)
- Christopher W. Bartlett
- The Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital and Department of Pediatrics, The Ohio State University, Columbus, OH
| | - Liping Hou
- The Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital and Department of Pediatrics, The Ohio State University, Columbus, OH
| | - Judy F. Flax
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ
| | - Abby Hare
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ
| | - Soo Yeon Cheong
- The Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital and Department of Pediatrics, The Ohio State University, Columbus, OH
| | - Zena Fermano
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ
| | - Barbie Zimmerman-Bier
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ,Department of Pediatrics, Saint Peter's University Hospital, New Brunswick, NJ
| | - Charles Cartwright
- Department of Psychiatry, University of Medicine and Dentistry of New Jersey – New Jersey Medical School, Newark, NJ
| | - Marco A. Azaro
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ
| | - Steven Buyske
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ,Department of Statistics and Biostatistics, Rutgers University, Rutgers University, Piscataway, NJ
| | - Linda M. Brzustowicz
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ,Corresponding Author:
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Simmons TR, Flax JF, Azaro MA, Hayter JE, Justice LM, Petrill SA, Bassett AS, Tallal P, Brzustowicz LM, Bartlett CW. Increasing genotype-phenotype model determinism: application to bivariate reading/language traits and epistatic interactions in language-impaired families. Hum Hered 2010; 70:232-44. [PMID: 20948219 PMCID: PMC3085518 DOI: 10.1159/000320367] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2010] [Accepted: 08/13/2010] [Indexed: 11/19/2022] Open
Abstract
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.
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Affiliation(s)
- Tabatha R Simmons
- Battelle Center for Mathematical Medicine, Research Institute at Nationwide Children's Hospital and Department of Pediatrics, Ohio State University, Columbus, OH 43205, USA
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Flax JF, Realpe-Bonilla T, Roesler C, Choudhury N, Benasich A. Using early standardized language measures to predict later language and early reading outcomes in children at high risk for language-learning impairments. J Learn Disabil 2009; 42:61-75. [PMID: 19011122 DOI: 10.1177/0022219408326215] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
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.
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Liu WC, Flax JF, Guise KG, Sukul V, Benasich AA. Functional connectivity of the sensorimotor area in naturally sleeping infants. Brain Res 2008; 1223:42-9. [PMID: 18599026 DOI: 10.1016/j.brainres.2008.05.054] [Citation(s) in RCA: 87] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2008] [Revised: 05/09/2008] [Accepted: 05/12/2008] [Indexed: 11/16/2022]
Abstract
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.
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Affiliation(s)
- Wen-Ching Liu
- Department of Radiology, University of Medicine and Dentistry of New Jersey-New Jersey Medical School, 150 Bergen Street, Newark, NJ 07103, USA.
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Bartlett CW, Flax JF, Logue MW, Smith BJ, Vieland VJ, Tallal P, Brzustowicz LM. Examination of potential overlap in autism and language loci on chromosomes 2, 7, and 13 in two independent samples ascertained for specific language impairment. Hum Hered 2004; 57:10-20. [PMID: 15133308 PMCID: PMC2976973 DOI: 10.1159/000077385] [Citation(s) in RCA: 82] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2003] [Accepted: 08/25/2003] [Indexed: 01/19/2023] Open
Abstract
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.
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Flax JF, Realpe-Bonilla T, Hirsch LS, Brzustowicz LM, Bartlett CW, Tallal P. Specific language impairment in families: evidence for co-occurrence with reading impairments. J Speech Lang Hear Res 2003; 46:530-543. [PMID: 14696984 DOI: 10.1044/1092-4388(2003/043)] [Citation(s) in RCA: 55] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
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.
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Affiliation(s)
- Judy F Flax
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark 07102, USA.
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Bartlett CW, Flax JF, Logue MW, Vieland VJ, Bassett AS, Tallal P, Brzustowicz LM. A major susceptibility locus for specific language impairment is located on 13q21. Am J Hum Genet 2002; 71:45-55. [PMID: 12048648 PMCID: PMC384992 DOI: 10.1086/341095] [Citation(s) in RCA: 162] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2002] [Accepted: 04/04/2002] [Indexed: 11/03/2022] Open
Abstract
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.
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Affiliation(s)
- Christopher W Bartlett
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Piscataway, NJ 08854-8095, USA.
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Tallal P, Hirsch LS, Realpe-Bonilla T, Miller S, Brzustowicz LM, Bartlett C, Flax JF. Familial aggregation in specific language impairment. J Speech Lang Hear Res 2001; 44:1172-1182. [PMID: 11708534 DOI: 10.1044/1092-4388(2001/091)] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
A case-control family study design, in which the current language-related abilities of all biological, primary relatives (mother, father, siblings) of probands with specific language impairment (SLI) and matched controls were assessed, was used to investigate familial aggregation for language disorders. Current test data from each family member showed the rate of language impairment for mothers, fathers, sisters, and brothers of the SLI probands to be significantly higher than for members of control families. Impairment rates for fathers and mothers were approximately equal, whereas rates for brothers were significantly higher than for sisters. In SLI proband families, Language Impairment (LI) occurred in 13.0% of offspring (excluding proband) with neither parent affected, 40% of offspring with one parent affected, and 71.4% of offspring in families in which both parents were language impaired. Rates of impairment as determined in current testing were compared directly to impairment rates estimated from family-history questionnaires collected from the same families. Group data showed impairment rates estimated from the family-history questionnaires to be similar to the rates based on actual testing. Furthermore, both appeared in line with rates based primarily on questionnaire data as reported previously in the literature. However, case-by-case analyses showed poor intrasubject agreement on classification as language impaired on the basis of current testing as compared to history information.
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Affiliation(s)
- P Tallal
- Center for Molecular and Behavioral Neuroscience, Rutgers, The State University of New Jersey, Newark 07102, USA.
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