Functional DNA methylation signatures for autism spectrum disorder genomic risk loci: 16p11.2 deletions and CHD8 variants.

BACKGROUND: Autism spectrum disorder (ASD) is a common and etiologically heterogeneous neurodevelopmental disorder. Although many genetic causes have been identified (> 200 ASD-risk genes), no single gene variant accounts for > 1% of all ASD cases. A role for epigenetic mechanisms in ASD etiology is supported by the fact that many ASD-risk genes function as epigenetic regulators and evidence that epigenetic dysregulation can interrupt normal brain development. Gene-specific DNAm profiles have been shown to assist in the interpretation of variants of unknown significance. Therefore, we investigated the epigenome in patients with ASD or two of the most common genomic variants conferring increased risk for ASD. Genome-wide DNA methylation (DNAm) was assessed using the Illumina Infinium HumanMethylation450 and MethylationEPIC arrays in blood from individuals with ASD of heterogeneous, undefined etiology (n = 52), and individuals with 16p11.2 deletions (16p11.2del, n = 9) or pathogenic variants in the chromatin modifier CHD8 (CHD8+/-, n = 7). RESULTS: DNAm patterns did not clearly distinguish heterogeneous ASD cases from controls. However, the homogeneous genetically-defined 16p11.2del and CHD8+/- subgroups each exhibited unique DNAm signatures that distinguished 16p11.2del or CHD8+/- individuals from each other and from heterogeneous ASD and control groups with high sensitivity and specificity. These signatures also classified additional 16p11.2del (n = 9) and CHD8 (n = 13) variants as pathogenic or benign. Our findings that DNAm alterations in each signature target unique genes in relevant biological pathways including neural development support their functional relevance. Furthermore, genes identified in our CHD8+/- DNAm signature in blood overlapped differentially expressed genes in CHD8+/- human-induced pluripotent cell-derived neurons and cerebral organoids from independent studies. CONCLUSIONS: DNAm signatures can provide clinical utility complementary to next-generation sequencing in the interpretation of variants of unknown significance. Our study constitutes a novel approach for ASD risk-associated molecular classification that elucidates the vital cross-talk between genetics and epigenetics in the etiology of ASD.

NSD1 mutations generate a genome-wide DNA methylation signature.

Sotos syndrome (SS) represents an important human model system for the study of epigenetic regulation; it is an overgrowth/intellectual disability syndrome caused by mutations in a histone methyltransferase, NSD1. As layered epigenetic modifications are often interdependent, we propose that pathogenic NSD1 mutations have a genome-wide impact on the most stable epigenetic mark, DNA methylation (DNAm). By interrogating DNAm in SS patients, we identify a genome-wide, highly significant NSD1(+/-)-specific signature that differentiates pathogenic NSD1 mutations from controls, benign NSD1 variants and the clinically overlapping Weaver syndrome. Validation studies of independent cohorts of SS and controls assigned 100% of these samples correctly. This highly specific and sensitive NSD1(+/-) signature encompasses genes that function in cellular morphogenesis and neuronal differentiation, reflecting cardinal features of the SS phenotype. The identification of SS-specific genome-wide DNAm alterations will facilitate both the elucidation of the molecular pathophysiology of SS and the development of improved diagnostic testing.

Quantitative 3D analysis of the canal network in cortical bone by micro-computed tomography.

Cortical bone is perforated by an interconnected network of porous canals that facilitate the distribution of neurovascular structures throughout the cortex. This network is an integral component of cortical microstructure and, therefore, undergoes continual change throughout life as the cortex is remodeled. To date, the investigation of cortical microstructure, including the canal network, has largely been limited to the two-dimensional (2D) realm due to methodological hurdles. Thanks to continuing improvements in scan resolution, micro-computed tomography (muCT) is the first nondestructive imaging technology capable of resolving cortical canals. Like its application to trabecular bone, muCT provides an efficient means of quantifying aspects of 3D architecture of the canal network. Our aim here is to introduce the use of muCT for this application by providing examples, discussing some of the parameters that can be acquired, and relating these to research applications. Although several parameters developed for the analysis of trabecular microstructure are suitable for the analysis of cortical porosity, the algorithm used to estimate connectivity is not. We adapt existing algorithms based on skeletonization for this task. We believe that 3D analysis of the dimensions and architecture of the canal network will provide novel information relevant to many aspects of bone biology. For example, parameters related to the size, spacing, and volume of the canals may be particularly useful for investigation of the mechanical properties of bone. Alternatively, parameters describing the 3D architecture of the canal network, such as connectivity between the canals, may provide a means of evaluating cumulative remodeling related change.