Rosenthal SB et al. (2021), A convergent molecular network underlying autis...

XB-ART-58303

Cell Syst 2021 Nov 17;1211:1094-1107.e6. doi: 10.1016/j.cels.2021.07.009.

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A convergent molecular network underlying autism and congenital heart disease.

Rosenthal SB , Willsey HR , Xu Y , Mei Y , Dea J , Wang S , Curtis C , Sempou E , Khokha MK , Chi NC , Willsey AJ , Fisch KM , Ideker T .

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Patients with neurodevelopmental disorders, including autism, have an elevated incidence of congenital heart disease, but the extent to which these conditions share molecular mechanisms remains unknown. Here, we use network genetics to identify a convergent molecular network underlying autism and congenital heart disease. This network is impacted by damaging genetic variants from both disorders in multiple independent cohorts of patients, pinpointing 101 genes with shared genetic risk. Network analysis also implicates risk genes for each disorder separately, including 27 previously unidentified genes for autism and 46 for congenital heart disease. For 7 genes with shared risk, we create engineered disruptions in Xenopus tropicalis, confirming both heart and brain developmental abnormalities. The network includes a family of ion channels, such as the sodium transporter SCN2A, linking these functions to early heart and brain development. This study provides a road map for identifying risk genes and pathways involved in co-morbid conditions.

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Species referenced: Xenopus tropicalis
Genes referenced: adnp ankrd11 arid1b atp1b2 atrx bptf braf cacna1a cdk13 chd4 chd7 chrd crebbp dnm1 dscam dyrk1a ehmt1 ep300 foxp1 grin2a grin2b igf1r kansl1 kat6a kcnq2 kdm5b kdm6a kmt2a kmt2c kmt2d kmt5b macrod2 mapt mecp2 med13l msl3 nalcn nf1 notch1 nsd1 pik3ca pogz prkce pten ptpn11 rabgap1l raf1 ret ryr3 scn2a setbp1 setd1a setd5 slc45a2 slc6a1 son sos1 srcap stx1b syn1 syngap1 thoc2 tiam1 trim9 trip12 usp34 wac zeb2
GO keywords: brain development [+]

???displayArticle.disOnts??? autism spectrum disorder [+]
???displayArticle.omims??? AUTISM

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	Figure 1. Overview of genetic data and workflow (A) Study workflow. We determined the network intersection of two sets of disorder risk genes, autism spectrum disorder (ASD, left, green) and congenital heart disease (CHD, right, pink); red denotes network proximity to both. Gene variants in the shared network are over-represented in patients from an independent replication cohort with co-morbid neurodevelopmental disorders (NDDs) and heart conditions, and disruptions to these genes give rise to brain and heart defects in a Xenopus tropicalis model of development. Analysis of ASD-CHD network architecture reveals a hierarchical organization of functional modules. SSC, Simons simplex collection; PCGC/PHN, Pediatric Cardiac Genomics Consortium/Pediatric Heart network. (B) Numbers of patients in the ASD and CHD cohorts with neurodevelopmental and heart conditions, with numbers of de novo coding variants and established disorder risk genes. The ASD cohort has not been systematically examined for heart phenotypes. (C) Bar chart displaying the fraction of patients in ASD and CHD cohorts with putatively damaging de novo variants (dDNVs) in ASD or CHD risk genes, dDNVs outside of these ‘‘risk’’ genes, and with no dDNVs yet identified.
	Figure 2. ASD and CHD de novo risk variants converge on common network regions. (A) Scatterplot of human proteins based on network proximity to established ASD risk genes or established CHD risk genes (y versus x). Proteins at the network intersection are shown in orange, with high confidence (HC; adjusted p < 0.1 and zASD > 1.5 and zCHD > 1.5) proteins shown in red. (B) Visualization of ASD-CHD network intersection, with the largest connected component shown. Node size is mapped to the number of variants observed for that gene, node color is the minimum of the brain or heart percentile expression from GTEx (The GTEx Consortium, 2015). Triangles indicate genes harboring at least one dual-condition variant. Edges are drawn for gene pairs with a network neighborhood similarity > 0.95 (percentile cosine similarity), with a purple-yellow color gradient indicating percentile above this threshold. Network layout was determined by a spring-embedding algorithm with edge bundling in cytoscape (Shannon et al., 2003). The spring layout was subsequently modified to enable visualization of the ASD and CHD seed nodes, where the seed nodes were manually translated to the left (ASD), right (CHD), and down (ASD and CHD) from the original layout. Selected genes are labeled. High confidence network intersection genes are indicated with a white border. (C) Number of genes found at the ASD-CHD network intersection compared with the number expected by chance. *empirical p = 4 3 10–141. (D) Enrichment for dDNVs associated with dual NDD and CHD phenotypes is shown for ASD-specific network genes (zASD R 2, zCHD < 2, zASD-CHD < 3), CHD- specific network genes (zCHD R 2, zASD < 2, zASD-CHD < 3), or genes at the ASD-CHD network intersection, and high confidence network intersection p < 0.001, p < 0.01, p < 0.05. Vertical bars indicate one standard deviation.
	Figure 3. Validation of the ASD-CHD network in independent patient cohorts (A) Distribution of minimum percentile mRNA expression of ASD-CHD network genes in GTEx brain or heart tissues (orange), compared with all expressed genes (gray). (B) Distribution of minimum percentile mRNA expression of ASD-CHD network genes in mouse developmental brain or heart tissues (orange), compared with all expressed genes (gray). (C) Heatmap showing the degree of network intersection among ASD rare variants, CHD rare variants, ASD common variants, and common variants from an unrelated control disease, atherosclerosis. Color bar shows enrichment in units of log 2 (observed/expected) number of genes. * denotes larger-than-expected intersection at p < 0.05. (D) Receiver operator characteristic (ROC) showing recovery of damaging variants associated with dual brain and heart phenotypes in the independent DECIPHER cohort. Genes are ranked by network proximity to ASD and CHD established risk genes (zASD-CHD). Results for all ranked genes in maroon (AUC = 0.71, p = 5 3 10–22); results excluding established risk genes in salmon (AUC = 0.66, p = 5 3 10–14, empirical p values). Black circles highlight the sets of genes at the zASD-CHD R 3 cutoffs used to define the ASD-CHD network intersection in previous figures. Examined variants are damaging single nucleotide variants and indels. (E) The number of dual-condition variants in DECIPHER is listed for all ASD-CHD network genes with four or more such variants. High confidence ASD-CHD network genes not previously identified in one or both disorders (Table S4) labeled in red.
	Figure 4. Functional validation in Xenopus tropicalis (A) CRISPR mutagenesis strategy. CRISPR reagents and a tracer dye (red) are injected at the two-cell stage, either into both cells (bilateral mutants, heart phenotyping) or into one cell (unilateral mutants, brain phenotyping). Animals are grown to tadpole stages and phenotyped for the brain (top) or heart (bottom) anatomy. The brain is normally bilaterally symmetric. Note leftward heart looping direction. Telencephalon (tel), outflow tract (OFT), ventricle (V), right atrium (RA), and left atrium (LA). (B) Quantification of brain and heart phenotype penetrance by gene mutant (percent observed in mutagenized animals). Negative control pigmentation gene slc45a2 shows few heart or brain phenotypes, while positive control genes ankrd11 and nsd1 show both phenotypes. All predicted ASD-CHD network genes show some evidence of heart and brain phenotypes, albeit at differing penetrances. Sample sizes are presented per gene, with brain phenotyping sample size first, followed by heart phenotyping sample size. (C) Brain telencephalon (top, b-tubulin staining in green) and heart (bottom, phalloidin actin staining in pink) images for three gene disruptions representative of the twelve total gene disruptions conducted and quantified in (B). Gene symbols are indicated at the lower right of each image. Shown is a negative control pigmentation gene slc45a2 (far left), positive control gene nsd1 (middle), and ASD-CHD network-implicated genes (right). For brain images, note the change in brain size on the injected half (red dotted outline) compared with control (white dotted outline). For heart categories, note changes in heart ventricle size (white dotted outline) and/or outflow tract looping direction (arrow) and size compared with control. Size differences in the total heart and outflow tract size can be readily seen in nsd1, ptpn11, and kansl1 heart images. Scale bars are 100 mm. Sample sizes and quantification of telencephalon size variance and heart phenotypes are in Figure S5.
	Figure 5. Hierarchical organization of the ASD-CHD network (A) Representation of the network data as a hierarchy of densely interacting gene systems. Nodes represent distinct systems, with the size showing the number of genes (min 6, max 844) and color showing the fraction of these genes in which dual-condition variants were identified. Large nodes with bold outlines contain at least one Xenopus validated gene. Systems mentioned elsewhere in the text are indicated with a gray or blue background. The gene systems are labeled with a unique identification (represented as a number next to each system). Parent-child containment relationships were defined by the CliXO algorithm, with genes in child systems contained completely within parent systems. Systems mentioned elsewhere in the text are indicated with a gray or blue background. (B) Pie chart demonstrating the fractions of identified systems that are well-characterized, new/extended subprocesses, new superprocesses, or new processes. (C) Genes and interactions from four ion-channel modules are highlighted in (A). Triangles indicate genes in which dual-condition variants have been identified. High confidence network intersection genes are indicated with a white border. Node color mapped to the minimum brain or heart percentile expression for that gene (blue gradient). Edges with network cosine similarity >0.95 are shown, with color indicating the magnitude of similarity above this threshold.
	Figure 6. SCN2A is required for heart and brain development (A) Unilateral mutagenesis of scn2a leads to an in- crease in telencephalon size on the mutated (right) side. B-tubulin staining. (B) High magnification of boxed region in (A). Note increase in the size of the olfactory bulb (ob) and rest of telencephalon (tel). (C) Control tadpole with proper organ situs (gall- bladder, GB, on the image left and gut on image right) and proper heart looping (toward image left). (D) High magnification of boxed region in (C) showing heart. Note outflow tract loops toward the image left. (E) scn2a bilateral mutant shows organ situs inver- sion (GB and gut in opposite positions from control) and heart looping defects. (F) High magnification of boxed region in (E) showing heart. Note outflow tract defects (elongated, looping toward image right) and abnormal ventricle morphology. (G) Adult human expression of SCN2A by tissue, using data from GTEx. Note strong expression in the brain but not the heart. (H) Adult Xenopus laevis expression of scn2a by tissue. Note strong expression in the brain but not the heart. (I) Embryonic expression of scn2a in Xenopus tro- picalis. Numbers on x axis represent the develop- mental stage. Note expression during mesoderm specification (pink, late blastula/early gastrula stages) as well as during left-right patterning and heart morphogenesis. (J) Embryonic human expression of SCN2A. Note expression during the blastocyst stage when mesoderm specification occurs (pink), similar to Xenopus

References [+] :

Abrahams, SFARI Gene 2.0: a community-driven knowledgebase for the autism spectrum disorders (ASDs). 2013, Pubmed