A Role for the Chromatin-Remodeling Factor BAZ1A in Neurodevelopment.

Chromatin-remodeling factors are required for a wide range of cellular and biological processes including development and cognition, mainly by regulating gene expression. As these functions would predict, deregulation of chromatin-remodeling factors causes various disease syndromes, including neurodevelopmental disorders. Recent reports have linked mutations in several genes coding for chromatin-remodeling factors to intellectual disability (ID). Here, we used exome sequencing and identified a nonsynonymous de novo mutation in BAZ1A (NM_182648.2:c.4043T > G, p.Phe1348Cys), encoding the ATP-utilizing chromatin assembly and remodeling factor 1 (ACF1), in a patient with unexplained ID. ACF1 has been previously reported to bind to the promoter of the vitamin D receptor (VDR)-regulated genes and suppress their expression. Our results show that the patient displays decreased binding of ACF1 to the promoter of the VDR-regulated gene CYP24A1. Using RNA sequencing, we find that the mutation affects the expression of genes involved in several pathways including vitamin D metabolism, Wnt signaling and synaptic formation. RNA sequencing of BAZ1A knockdown cells and Baz1a knockout mice revealed that BAZ1A carry out distinctive functions in different tissues. We also demonstrate that BAZ1A depletion influence the expression of genes important for nervous system development and function. Our data point to an important role for BAZ1A in neurodevelopment, and highlight a possible link for BAZ1A to ID.

Transcriptome Analysis of Post-Mortem Brain Tissue Reveals Up-Regulation of the Complement Cascade in a Subgroup of Schizophrenia Patients.

Schizophrenia is a genetically complex neuropsychiatric disorder with largely unresolved mechanisms of pathology. Identification of genes and pathways associated with schizophrenia is important for understanding the development, progression and treatment of schizophrenia. In this study, pathways associated with schizophrenia were explored at the level of gene expression. The study included post-mortem brain tissue samples from 68 schizophrenia patients and 44 age and sex-matched control subjects. Whole transcriptome poly-A selected paired-end RNA sequencing was performed on tissue from the prefrontal cortex and orbitofrontal cortex. RNA expression differences were detected between case and control individuals, focusing both on single genes and pathways. The results were validated with RT-qPCR. Significant differential expression between patient and controls groups was found for 71 genes. Gene ontology analysis of differentially expressed genes revealed an up-regulation of multiple genes in immune response among the patients (corrected p-value = 0.004). Several genes in the category belong to the complement system, including C1R, C1S, C7, FCN3, SERPING1, C4A and CFI. The increased complement expression is primarily driven by a subgroup of patients with increased expression of immune/inflammatory response genes, pointing to important differences in disease etiology within the patient group. Weighted gene co-expression network analysis highlighted networks associated with both synaptic transmission and activation of the immune response. Our results demonstrate the importance of immune-related pathways in schizophrenia and provide evidence for elevated expression of the complement cascade as an important pathway in schizophrenia pathology.

Transcriptome analysis of fibroblasts from schizophrenia patients reveals differential expression of schizophrenia-related genes.

Schizophrenia is a complex neurodevelopmental disorder with high rate of morbidity and mortality. While the heritability rate is high, the precise etiology is still unknown. Although schizophrenia is a central nervous system disorder, studies using peripheral tissues have also been established to search for patient specific biomarkers and to increase understanding of schizophrenia etiology. Among all peripheral tissues, fibroblasts stand out as they are easy to obtain and culture. Furthermore, they keep genetic stability for long period and exhibit molecular similarities to cells from nervous system. Using a unique set of fibroblast samples from a genetically isolated population in northern Sweden, we performed whole transcriptome sequencing to compare differentially expressed genes in seven controls and nine patients. We found differential fibroblast expression between cases and controls for 48 genes, including eight genes previously implicated in schizophrenia or schizophrenia related pathways; HGF, PRRT2, EGR1, EGR3, C11orf87, TLR3, PLEKHH2 and PIK3CD. Weighted gene correlation network analysis identified three differentially co-expressed networks of genes significantly-associated with schizophrenia. All three modules were significantly suppressed in patients compared to control, with one module highly enriched in genes involved in synaptic plasticity, behavior and synaptic transmission. In conclusion, our results support the use of fibroblasts for identification of differentially expressed genes in schizophrenia and highlight dysregulation of synaptic networks as an important mechanism in schizophrenia.

Linkage and exome analysis implicate multiple genes in non-syndromic intellectual disability in a large Swedish family.

BACKGROUND: Non-syndromic intellectual disability is genetically heterogeneous with dominant, recessive and complex forms of inheritance. We have performed detailed genetic studies in a large multi-generational Swedish family, including several members diagnosed with non-syndromic intellectual disability. Linkage analysis was performed on 22 family members, nine affected with mild to moderate intellectual disability and 13 unaffected family members. METHODS: Family members were analyzed with Affymetrix Genome-Wide Human SNP Array 6.0 and the genetic data was used to detect copy number variation and to perform genome wide linkage analysis with the SNP High Throughput Linkage analysis system and the Merlin software. For the exome sequencing, the samples were prepared using the Sure Select Human All Exon Kit (Agilent Technologies, Santa Clara, CA, USA) and sequenced using the Ion Proton™ System. Validation of identified variants was performed with Sanger sequencing. RESULTS: The linkage analysis results indicate that intellectual disability in this family is genetically heterogeneous, with suggestive linkage found on chromosomes 1q31-q41, 4q32-q35, 6p25 and 14q24-q31 (LOD scores of 2.4, simulated p-value of 0.000003 and a simulated genome-wide p-value of 0.06). Exome sequencing was then performed in 14 family members and 7 unrelated individuals from the same region. The analysis of coding variation revealed a pathogenic and candidate variants in different branches of the family. In three patients we find a known homozygous pathogenic mutation in the Homo sapiens solute carrier family 17 member 5 (SLC17A5), causing Salla disease. We also identify a deletion overlapping KDM3B and a duplication overlapping MAP3K4 and AGPAT4, both overlapping variants previously reported in developmental disorders. CONCLUSIONS: DNA samples from the large family analyzed in this study were initially collected based on a hypothesis that affected members shared a major genetic risk factor. Our results show that a complex phenotype such as mild intellectual disability in large families from genetically isolated populations may show considerable genetic heterogeneity.

Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to date more than a hundred risk loci have been identified. Association of environmental factors and schizophrenia has also been reported, while epigenetic analyses have yielded ambiguous and sometimes conflicting results. Here, we analyzed fresh frozen post-mortem brain tissue from a cohort of 73 subjects diagnosed with schizophrenia and 52 control samples, using the Illumina Infinium HumanMethylation450 Bead Chip, to investigate genome-wide DNA methylation patterns in the two groups. Analysis of differential methylation was performed with the Bioconductor Minfi package and modern machine-learning and visualization techniques, which were shown previously to be successful in detecting and highlighting differentially methylated patterns in case-control studies. In this dataset, however, these methods did not uncover any significant signals discerning the patient group and healthy controls, suggesting that if there are methylation changes associated with schizophrenia, they are heterogeneous and complex with small effect.