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Purpose Pathogenic variants in SCN2A cause a wide range of neurodevelopmental phenotypes. Reports of genotype–phenotype correlations are often anecdotal, and the available phenotypic data have not been systematically analyzed. Methods We extracted phenotypic information from primary descriptions of SCN2A-related disorders in the literature between 2001 and 2019, which we coded in Human Phenotype Ontology (HPO) terms. With higher-level phenotype terms inferred by the HPO structure, we assessed the frequencies of clinical features and investigated the association of these features with variant classes and locations within the NaV1.2 protein. Results We identified 413 unrelated individuals and derived a total of 10,860 HPO terms with 562 unique terms. Protein-truncating variants were associated with autism and behavioral abnormalities. Missense variants were associated with neonatal onset, epileptic spasms, and seizures, regardless of type. Phenotypic similarity was identified in 8/62 recurrent SCN2A variants. Three independent principal components accounted for 33% of the phenotypic variance, allowing for separation of gain-of-function versus loss-of-function variants with good performance. Conclusion Our work shows that translating clinical features into a computable format using a standardized language allows for quantitative phenotype analysis, mapping the phenotypic landscape of SCN2A-related disorders in unprecedented detail and revealing genotype–phenotype correlations along a multidimensional spectrum.

Two Cancers in CHIP A patient with clonal hematopoiesis of indeterminate potential (CHIP) received the diagnosis of lymphoma with activation of RHOA. Approximately 1 year later, NPM1-mutated acute ...

Cardiogenics Consortium, IDEM Leducq Consortium CADGenomics; International audience; Macrophages are key players involved in numerous pathophysiological pathways and an in-depth characterization of their gene regulatory networks can help in better understanding how their dysfunction may impact on human diseases. We here conducted a cross-species network analysis of macrophage gene expression data between human and mouse to identify conserved networks across both species, and assessed whether such networks could reveal new disease-associated regulatory mechanisms. From a sample of 684 individuals processed for genome-wide macrophage gene expression profiling, we identified 27 groups of coexpressed genes (modules). Six modules were found preserved (P , 10 24) in macrophages from 86 mice of the Hybrid Mouse Diversity Panel. One of these modules was significantly [false discovery rate (FDR) = 8.9 · 10 211 ] enriched for genes belonging to the oxidative phosphorylation (OXPHOS) pathway. This pathway was also found significantly (FDR , 10 24) enriched in susceptibility genes for Alzheimer, Parkinson, and Huntington diseases. We further conducted an expression quantitative trait loci analysis to identify SNP that could regulate macrophage OXPHOS gene expression in humans. This analysis identified the PARK2 rs192804963 as a transacting variant influencing (minimal P-value = 4.3 · 10 28) the expression of most OXPHOS genes in humans. Further experimental work demonstrated that PARK2 knockdown expression was associated with increased OXPHOS gene expression in THP1 human macrophages. This work provided strong new evidence that PARK2 participates to the regulatory networks associated with oxidative phosphorylation and suggested that PARK2 genetic variations could act as a trans regulator of OXPHOS gene macrophage expression in humans.

Aims Lipid phosphate phosphatase 3; type 2 phosphatidic acid phosphatase β (LPP3; PPAP2B ) is a transmembrane protein dephosphorylating and thereby terminating signalling of lipid substrates including lysophosphatidic acid (LPA) and sphingosine-1-phosphate (S1P). Human LPP3 possesses a cell adhesion motif that allows interaction with integrins. A polymorphism (rs17114036) in PPAP2B is associated with coronary artery disease, which prompted us to investigate the possible role of LPP3 in human endothelial dysfunction, a condition promoting atherosclerosis. Methods and results To study the role of LPP3 in endothelial cells we used human primary aortic endothelial cells (HAECs) in which LPP3 was silenced or overexpressed using either wild type or mutated cDNA constructs. LPP3 silencing in HAECs enhanced secretion of inflammatory cytokines, leucocyte adhesion, cell survival, and migration and impaired angiogenesis, whereas wild-type LPP3 overexpression reversed these effects and induced apoptosis. We also demonstrated that LPP3 expression was negatively correlated with vascular endothelial growth factor expression. Mutations in either the catalytic or the arginine-glycine-aspartate (RGD) domains impaired endothelial cell function and pharmacological inhibition of S1P or LPA restored it. LPA was not secreted in HAECs under silencing or overexpressing LPP3. However, the intra- and extra-cellular levels of S1P tended to be correlated with LPP3 expression, indicating that S1P is probably degraded by LPP3. Conclusions We demonstrated that LPP3 is a negative regulator of inflammatory cytokines, leucocyte adhesion, cell survival, and migration in HAECs, suggesting a protective role of LPP3 against endothelial dysfunction in humans. Both the catalytic and the RGD functional domains were involved and S1P, but not LPA, might be the endogenous substrate of LPP3.

We identified murine miR-322, orthologous to human miR-424, as a new regulator of insulin receptor, IGF-1 receptor and sirtuin 4 mRNA in vitro and in vivo in the heart and found that miR-322/424 is highly expressed in the heart of mice. C57Bl/6N mice fed 10weeks of high fat diet (HFD) presented signs of cardiomyopathy and a stable miR-322 cardiac level while cardiac function was slightly affected in 11week-old ob/ob which overexpressed miR-322. We thus hypothesized that mmu-miR-322 could be protective against cardiac consequences of hyperinsulinemia and hyperlipidemia. We overexpressed or knocked-down mmu-miR-322 using AAV9 and monitored cardiac function in wild-type C57Bl/6N mice fed a control diet (CD) or a HFD and in ob/ob mice. The fractional shortening progressively declined while the left ventricle systolic diameter increased in HFD mice infected with an AAVcontrol or with an AAVsponge (decreasing miR-322 bioavailability) but also in ob/ob mice infected with AAVsponge. Similar observations were also found in CD-fed mice infected with AAVsponge. On the contrary over-expressing miR-322 with AAVmiR-322 was efficient in protecting the heart from HFD effects in C57Bl/6N mice. This cardioprotection could be associated with the regulation of identified targets IGF1R, INSR and CD1, a decrease in insulin signaling pathway and an enrichment of genes involved in mitochondrial function and fatty acid oxidation as demonstrated by transcriptome analysis. Altogether, these results emphasize miR-322 as a new potential therapeutic target against cardiac consequences of metabolic syndrome, which represents an increasing burden in the western countries.

Cardiovascular diseases (CVD) and type 2 diabetes (T2D) are closely interrelated complex diseases likely sharing overlapping pathogenesis driven by aberrant activities in gene networks. However, the molecular circuitries underlying the pathogenic commonalities remain poorly understood. We sought to identify the shared gene networks and their key intervening drivers for both CVD and T2D by conducting a comprehensive integrative analysis driven by five multi-ethnic genome-wide association studies (GWAS) for CVD and T2D, expression quantitative trait loci (eQTLs), ENCODE, and tissue-specific gene network models (both co-expression and graphical models) from CVD and T2D relevant tissues. We identified pathways regulating the metabolism of lipids, glucose, and branched-chain amino acids, along with those governing oxidation, extracellular matrix, immune response, and neuronal system as shared pathogenic processes for both diseases. Further, we uncovered 15 key drivers including HMGCR, CAV1, IGF1 and PCOLCE, whose network neighbors collectively account for approximately 35% of known GWAS hits for CVD and 22% for T2D. Finally, we cross-validated the regulatory role of the top key drivers using in vitro siRNA knockdown, in vivo gene knockout, and two Hybrid Mouse Diversity Panels each comprised of >100 strains. Findings from this in-depth assessment of genetic and functional data from multiple human cohorts provide strong support that common sets of tissue-specific molecular networks drive the pathogenesis of both CVD and T2D across ethnicities and help prioritize new therapeutic avenues for both CVD and T2D., Author summary Cardiovascular disease (CVD) and type 2 diabetes (T2D) are two tightly interrelated diseases that are leading epidemics and causes of deaths around the world. Elucidating the mechanistic connections between the two diseases will offer critical insights for the development of novel therapeutic avenues to target both simultaneously. Because of the challenging complexity of CVD and T2D, involving numerous risk factors, multiple tissues, and multidimensional molecular alterations, few have attempted such an investigation. We herein report a comprehensive and in-depth data-driven assessment of the shared mechanisms between CVD and T2D by integrating genomics data from diverse human populations including African Americans, Caucasian Americans, and Hispanic Americans with tissue-specific functional genomics information. We identified shared pathways and gene networks informed by CVD and T2D genetic risks across populations, confirming the importance of well-established processes, as well as unraveling previously under-appreciated processes such as extracellular matrix, branched-chain amino acid metabolism, and neuronal system for both diseases. Further incorporation of tissue-specific regulatory networks pinpointed potential key regulators that orchestrate the biological processes shared between the two diseases, which were cross-validated using cell culture and mouse models. This study suggests potential new therapeutic targets that warrant further investigation for both CVD and T2D.

Coronary artery disease (CAD) remains one of leading causes of death worldwide. Although the genetic heritability of CAD has been estimated to be 40 to 60%, only ~10% can be explained by the genetic loci uncovered from recent large-scale human GWAS. To elucidate the missing mechanisms, we leveraged aorta transcriptome data from 372 mice profiled in an Atherosclerosis Hybrid Mouse Diversity Panel (ath-HMDP), human CAD GWAS from CARDIoGRAM+C4D, and human expression quantitative loci (eQTL) from the Genotype-Tissue Expression (GTEx) and the Cardiogenics transcriptomic studies. We first constructed aorta coexpression networks based on the ath-HMDP transcriptome data using MEGENA (Multiscale Embedded Gene Co-expression Network Analysis) and WGCNA (Weighted Gene Coexpression Network Analysis) to define coexpression modules with various levels of coherency and compactness. The coexpression modules from MEGENA and WGCNA were then correlated with the aortic lesion trait measured in ath-HMDP to reveal 29 coexpression modules demonstrating significant correlations with aortic lesions (p < 1e-3). We further integrated these aortic lesion-correlated modules with eQTLs from aortic and coronary arteries examined in the GTEx study and monocyte and macrophage eQTLs from Cardiogenics to map module genes to functional SNPs that likely affect the expression levels of these genes. When further incorporating the CARDIoGRAM+C4D CAD GWAS, 13 lesion-correlated modules in mouse ath-HMDP were enriched for functional SNPs demonstrating stronger association with CAD in humans. These modules were over-represented with genes in multiple biological pathways, including both known CAD processes (e.g., lipid & lipoprotein metabolisms, fatty acid triacylglycerol & ketone body metabolism, TCA cycle, vascular smooth muscle contraction, antigen processing, focal adhesion) and novel pathways (e.g., adipocytokine signaling, type I & II diabetes mellitus, neurotrophic factor signaling, lysosome). In conclusion, this cross-species integrative analysis that takes advantage of aorta profiling from a well-controlled mouse atherosclerosis study in conjunction with human genomics provides insights into the aorta-related mechanisms underlying CAD.

Objective— Genome-wide association studies have to date identified 159 significant and suggestive loci for coronary artery disease (CAD). We now report comprehensive bioinformatics analyses of sequence variation in these loci to predict candidate causal genes. Approach and Results— All annotated genes in the loci were evaluated with respect to protein-coding single-nucleotide polymorphism and gene expression parameters. The latter included expression quantitative trait loci, tissue specificity, and miRNA binding. High priority candidate genes were further identified based on literature searches and our experimental data. We conclude that the great majority of causal variations affecting CAD risk occur in noncoding regions, with 41% affecting gene expression robustly versus 6% leading to amino acid changes. Many of these genes differed from the traditionally annotated genes, which was usually based on proximity to the lead single-nucleotide polymorphism. Indeed, we obtained evidence that genetic variants at CAD loci affect 98 genes which had not been linked to CAD previously. Conclusions— Our results substantially revise the list of likely candidates for CAD and suggest that genome-wide association studies efforts in other diseases may benefit from similar bioinformatics analyses.