Heterogeneity in clinical sequencing tests marketed for autism spectrum disorders.
Ontology highlight
ABSTRACT:
SUBMITTER: Hoang N
PROVIDER: S-EPMC6145925 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
Publications
Heterogeneity in clinical sequencing tests marketed for autism spectrum disorders.
Hoang Ny N Buchanan Janet A JA Scherer Stephen W SW
NPJ genomic medicine 20180919
Similar Datasets
Project description:BACKGROUND: The etiology of autism spectrum disorders (ASD) is largely determined by different genetic factors of variable impact. This genetic heterogeneity could be a factor to explain the clinical heterogeneity of autism spectrum disorders. Here, a first attempt is made to assess whether genetically more homogeneous ASD groups are associated with decreased phenotypic heterogeneity with respect to their autistic symptom profile. METHODOLOGY: The autistic phenotypes of ASD subjects with 22q11 deletion syndrome (22q11DS) and ASD subjects with Klinefelter Syndrome (KS) were statistically compared to the symptom profile of a large (genetically) heterogeneous ASD sample. Autism diagnostic interview-revised (ADI-R) variables were entered in different statistical analyses to assess differences in symptom homogeneity and the feasibility of discrimination of group-specific ASD-symptom profiles. PRINCIPAL FINDINGS: The results showed substantially higher symptom homogeneity in both the genetic disorder ASD groups in comparison to the heterogeneous ASD sample. In addition, a robust discrimination between 22q11-ASD and KS-ASD and idiopathic ASD phenotypes was feasible on the basis of a reduced number of autistic scales and symptoms. The lack of overlap in discriminating subscales and symptoms between KS-ASD and 22q11DS-ASD suggests that their autistic symptom profiles cluster around different points in the total diagnostic space of profiles present in the general ASD population. CONCLUSION: The findings of the current study indicate that the clinical heterogeneity of ASDs may be reduced when subgroups based on a specific genotype are extracted from the idiopathic ASD population. The current strategy involving the widely used ADI-R offers a relatively straightforward possibility for assessing genotype-phenotype ASD relationships. Reverse phenotype strategies are becoming more feasible, given the accumulating evidence for the existence of genetic variants of large effect in a substantial proportion of the ASD population.
| S-EPMC2878316 | biostudies-literature
Project description:Research during the past decade has seen significant progress in the understanding of the genetic architecture of autism spectrum disorders (ASDs), with gene discovery accelerating as the characterization of genomic variation has become increasingly comprehensive. At the same time, this research has highlighted ongoing challenges. Here we address the enormous impact of high-throughput sequencing (HTS) on ASD gene discovery, outline a consensus view for leveraging this technology, and describe a large multisite collaboration developed to accomplish these goals. Similar approaches could prove effective for severe neurodevelopmental disorders more broadly.
| S-EPMC3863639 | biostudies-literature
Project description:In this study, whole genome sequencing was performed in two autistic families (as trio).
| PRJEB34754 | ENA
Project description:Autism spectrum disorders (ASD) display significant heterogeneity. Although most neuroimaging studies in ASD have been designed to identify commonalities among affected individuals, rather than differences, some studies have explored variation within ASD. There have been two general types of approaches used for this in the neuroimaging literature to date: comparison of subgroups within ASD, and analyses using dimensional measures to link clinical variation to brain differences. This review focuses on structural and functional magnetic resonance imaging studies that have used these approaches to begin to explore heterogeneity between individuals with ASD. Although this type of data is yet sparse, recognition is growing of the limitations of behaviorally defined categorical diagnoses for understanding neurobiology. Study designs that are more informative regarding the sources of heterogeneity in ASD have the potential to improve our understanding of the neurobiological processes underlying ASD.
| S-EPMC3812662 | biostudies-literature
Project description:Novel candidate genes, including MIS18BP1, for Autism Spectrum Disorders identified by whole-exome sequencing in the Lebanese population
| PRJEB43914 | ENA
Project description: Not available
| S-EPMC9382353 | biostudies-literature
Project description:Multiple lines of evidence indicate a strong genetic contribution to autism spectrum disorders (ASDs). Current guidelines for clinical genetic testing recommend a G-banded karyotype to detect chromosomal abnormalities and fragile X DNA testing, but guidelines for chromosomal microarray analysis have not been established.A cohort of 933 patients received clinical genetic testing for a diagnosis of ASD between January 2006 and December 2008. Clinical genetic testing included G-banded karyotype, fragile X testing, and chromosomal microarray (CMA) to test for submicroscopic genomic deletions and duplications. Diagnostic yield of clinically significant genetic changes was compared.Karyotype yielded abnormal results in 19 of 852 patients (2.23% [95% confidence interval (CI): 1.73%-2.73%]), fragile X testing was abnormal in 4 of 861 (0.46% [95% CI: 0.36%-0.56%]), and CMA identified deletions or duplications in 154 of 848 patients (18.2% [95% CI: 14.76%-21.64%]). CMA results for 59 of 848 patients (7.0% [95% CI: 5.5%-8.5%]) were considered abnormal, which includes variants associated with known genomic disorders or variants of possible significance. CMA results were normal in 10 of 852 patients (1.2%) with abnormal karyotype due to balanced rearrangements or unidentified marker chromosome. CMA with whole-genome coverage and CMA with targeted genomic regions detected clinically relevant copy-number changes in 7.3% (51 of 697) and 5.3% (8 of 151) of patients, respectively, both higher than karyotype. With the exception of recurrent deletion and duplication of chromosome 16p11.2 and 15q13.2q13.3, most copy-number changes were unique or identified in only a small subset of patients.CMA had the highest detection rate among clinically available genetic tests for patients with ASD. Interpretation of microarray data is complicated by the presence of both novel and recurrent copy-number variants of unknown significance. Despite these limitations, CMA should be considered as part of the initial diagnostic evaluation of patients with ASD.
| S-EPMC4247857 | biostudies-literature
Project description:Here we report metagenomic sequencing data in gut microbiota of autism spectrum disorders (ASD) compared with healthy volunteers (30 for ASD children and 30 for healthy controls, respectively). The genes changed in autistic subjects involved 1,312,364 analytes that compare to 1,335,835 analytes in healthy controls. The number of taxa in autistic subjects were significantly increased as compared to the healthy controls based on the phylum and genus level (P = 0.001). However, the number of species were significantly decreased in autistic subjects (P = 0.001).
2020-09-30 | GSE113540 | GEO
Project description:Our cohort comprised 40 non-syndromic ASD children.We conducted genome wide analysis using Affymetrix Cytoscan-HD microchips. We identified pathogenic CNVs in 7 patients (17.5%), other variant classified as variants of uncertain significance (VUS) or benign.
2025-04-22 | GSE270110 | GEO
Project description:Genetic heterogeneity poses a challenge to research and clinical translation of autism spectrum disorder (ASD). In this study, we conducted a plasma proteomic and metabolomic study of children with ASD with and without risk genes (de novo mutation) and controls to explore the impact of genetic heterogeneity on the search for biomarkers for ASD. In terms of the proteomic and metabolomic profiles, the groups of children with ASD carrying and those not carrying de novo mutation tended to cluster and overlap, and integrating them yielded differentially expressed proteins and differential metabolites that effectively distinguished ASD from controls. The mechanisms associated with them focus on several common and previously reported mechanisms. Proteomics results highlight the role of complement, inflammation and immunity, and cell adhesion. The main pathways of metabolic perturbations include amino acid, vitamin, glycerophospholipid, tryptophan, and glutamates metabolic pathways and solute carriers-related pathways. Integrating the two omics analyses revealed that L-glutamic acid and malate dehydrogenase may play key roles in the pathogenesis of ASD. These results suggest that children with ASD may have important underlying common mechanisms. They are not only potential therapeutic targets for ASD but also important contributors to the study of biomarkers for the disease.
| S-EPMC10518435 | biostudies-literature