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Autism spectrum disorder (ASD) is an early onset, developmental disorder whose genetic cause is heterogeneous and complex. In total, 70% of ASD cases are due to an unknown etiology. Among the monogenic causes of ASD, fragile X syndrome (FXS) accounts for 2-4% of ASD cases, and 60% of individuals with FXS present with ASD. Epigenetic changes, specifically DNA methylation, which modulates gene expression levels, play a significant role in the pathogenesis of both disorders. Thus, in this study, using the Human Methylation EPIC Bead Chip, we examined the global DNA methylation profiles of biological samples derived from 57 age-matched male participants (2-6 years old), including 23 subjects with ASD, 23 subjects with FXS with ASD (FXSA) and 11 typical developing (TD) children. After controlling for technical variation and white blood cell composition, using the conservatory threshold of the false discovery rate (FDR ≤ 0.05), in the three comparison groups, TD vs. AD, TD vs. FXSA and ASD vs. FXSA, we identified 156, 79 and 3100 differentially methylated sites (DMS), and 14, 13 and 263 differential methylation regions (DMRs). Interestingly, several genes differentially methylated among the three groups were among those listed in the SFARI Gene database, including the PAK2, GTF2I and FOXP1 genes important for brain development. Further, enrichment analyses identified pathways involved in several functions, including synaptic plasticity. Our preliminary study identified a significant role of altered DNA methylation in the pathology of ASD and FXS, suggesting that the characterization of a DNA methylation signature may help to unravel the pathogenicity of FXS and ASD and may help the development of an improved diagnostic classification of children with ASD and FXSA. In addition, it may pave the way for developing therapeutic interventions that could reverse the altered methylome profile in children with neurodevelopmental disorders.

The progression of proteinuric kidney diseases is associated with podocyte loss, but the mechanisms underlying this process remain unclear. Podocytes reenter the cell cycle to repair double-stranded DNA breaks. However, unsuccessful repair can result in podocytes crossing the [G.sub.1]/S checkpoint and undergoing abortive cytokinesis. In this study, we identified Pfn1 as indispensable in maintaining glomerular integrity--its tissue-specific loss in mouse podocytes resulted in severe proteinuria and kidney failure. Our results suggest that this phenotype is due to podocyte mitotic catastrophe (MC), characterized histologically and ultrastructurally by abundant multinucleated cells, irregular nuclei, and mitotic spindles. Podocyte cell cycle reentry was identified using FUCCI2aR mice, and we observed altered expression of cellcycle associated proteins, such as p21, p53, cyclin B1, and cyclin D1. Podocyte-specific translating ribosome affinity purification and RNA-Seq revealed the downregulation of ribosomal RNA-processing 8 (Rrp8). Overexpression of Rrp8 in Pfn1-KO podocytes partially rescued the phenotype in vitro. Clinical and ultrastructural tomographic analysis of patients with diverse proteinuric kidney diseases further validated the presence of MC podocytes and reduction in podocyte PFN1 expression within kidney tissues. These results suggest that profilinl is essential in regulating the podocyte cell cycle and its disruption leads to MC and subsequent podocyte loss., Introduction Podocytes are specialized terminally differentiated epithelial cells that line the kidney filtration barrier. Unlike typical epithelial cells that are compressed against their basement membrane, podocytes are situated on the [...]

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene-trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies.

The TET family of dioxygenases promote DNA demethylation by oxidizing 5-methylcytosine to 5-hydroxymethylcytosine (5hmC). Hypothalamic agouti-related peptide-expressing (AGRP-expressing) neurons play an essential role in driving feeding, while also modulating nonfeeding behaviors. Besides AGRP, these neurons produce neuropeptide Y (NPY) and the neurotransmitter GABA, which act in concert to stimulate food intake and decrease energy expenditure. Notably, AGRP, NPY, and GABA can also elicit anxiolytic effects. Here, we report that in adult mouse AGRP neurons, CRISPR-mediated genetic ablation of Tet3, not previously known to be involved in central control of appetite and metabolism, induced hyperphagia, obesity, and diabetes, in addition to a reduction of stress-like behaviors. TET3 deficiency activated AGRP neurons, simultaneously upregulated the expression of Agrp, Npy, and the vesicular GABA transporter Slc32a1, and impeded leptin signaling. In particular, we uncovered a dynamic association of TET3 with the Agrp promoter in response to leptin signaling, which induced 5hmC modification that was associated with a chromatin-modifying complex leading to transcription inhibition, and this regulation occurred in both the mouse models and human cells. Our results unmasked TET3 as a critical central regulator of appetite and energy metabolism and revealed its unexpected dual role in the control of feeding and other complex behaviors through AGRP neurons., Introduction The capacity of the brain to balance between energy intake and expenditure is a critical aspect of survival. The agouti-related peptide-expressing (AGRP-expressing) neurons located in the hypothalamic arcuate nucleus [...]

Abstract Background Gene set analysis based on Gene Ontology (GO) can be a promising method for the analysis of differential expression patterns. However, current studies that focus on individual GO terms have limited analytical power, because the complex structure of GO introduces strong dependencies among the terms, and some genes that are annotated to a GO term cannot be found by statistically significant enrichment. Results We proposed a method for enriching clustered GO terms based on semantic similarity, namely cluster enrichment analysis based on GO (CeaGO), to extend the individual term analysis method. Using an Affymetrix HGU95aV2 chip dataset with simulated gene sets, we illustrated that CeaGO was sensitive enough to detect moderate expression changes. When compared to parent-based individual term analysis methods, the results showed that CeaGO may provide more accurate differentiation of gene expression results. When used with two acute leukemia (ALL and ALL/AML) microarray expression datasets, CeaGO correctly identified specifically enriched GO groups that were overlooked by other individual test methods. Conclusion By applying CeaGO to both simulated and real microarray data, we showed that this approach could enhance the interpretation of microarray experiments. CeaGO is currently available at http://chgc.sh.cn/en/software/CeaGO/.