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Integrated network analysis reveals genotype-phenotype correlations in Williams syndrome

ABSTRACT: Williams Syndrome (WS) is a rare neurodevelopmental disorder caused by heterozygous deletions in a chromosome 7q11.23 region typically encompassing 26-28 genes. WS patients exhibit a wide spectrum of symptoms, including cardiovascular disease, intellectual disability, visuospatial deficits and hypersociability a behavioral profile that contrasts with autism spectrum disorder (ASD). However, the relationship between neuropsychiatric phenotypes and dysregulated gene networks caused by the 7q11.23 deletion is unknown. We report results from a large-scale integrated transcriptome analysis of peripheral blood in clinically evaluated subjects with WS, ASD and matched controls. We identified significantly differential expressed genes in WS as compared with ASD or controls, even after removing genes spanning the 7q11.23 region. Using weighted gene co-expression network analysis (WGCNA), we found that three co-expression modules were upregulated in WS, and were significantly associated with the intermediate phenotypes such as anxiety and attention problems. Notably, these three co-expression modules were only composed of genes located outside of 7q11.23 critical region. One module was associated with immune systems and B cell proliferation. Its top hub gene, BCL11A, is implicated in ASD and chromatin modification. Another module was enriched with genes associated with astrocytes and oligodendrocytes, and the third module was associated with RNA processing and neurons. MicroRNA (miRNA) profiling revealed differentially expressed miRNAs whose targets were enriched in each co-expression module associated with WS. These results identify genes and potential driver miRNAs, located outside of 7q11.23 critical region, that are novel candidates for mediating the neuropsychiatric phenotypes in WS.

ORGANISM(S): Homo sapiens

PROVIDER: GSE89594 | GEO | 2018/11/06

REPOSITORIES: GEO

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Integrated network analysis reveals genotype-phenotype correlations in Williams syndrome

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