Relative Burden of Large CNVs on a Range of Neurodevelopmental Phenotypes

While numerous studies have implicated copy number variants (CNVs) in a range of neurological phenotypes, the impact relative to disease severity has been difficult to ascertain due to small sample sizes, lack of phenotypic details, and heterogeneity in platforms used for discovery. Using a customized microarray enriched for genomic hotspots, we assayed for large CNVs among 1,227 individuals with various neurological deficits including dyslexia (376), sporadic autism (350), and intellectual disability (ID) (501), as well as 337 controls. We show that the frequency of large CNVs (>1 Mbp) is significantly greater for ID–associated phenotypes compared to autism (p = 9.58×10−11, odds ratio = 4.59), dyslexia (p = 3.81×10−18, odds ratio = 14.45), or controls (p = 2.75×10−17, odds ratio = 13.71). There is a striking difference in the frequency of rare CNVs (>50 kbp) in autism (10%, p = 2.4×10−6, odds ratio = 6) or ID (16%, p = 3.55×10−12, odds ratio = 10) compared to dyslexia (2%) with essentially no difference in large CNV burden among dyslexia patients compared to controls. Rare CNVs were more likely to arise de novo (64%) in ID when compared to autism (40%) or dyslexia (0%). We observed a significantly increased large CNV burden in individuals with ID and multiple congenital anomalies (MCA) compared to ID alone (p = 0.001, odds ratio = 2.54). Our data suggest that large CNV burden positively correlates with the severity of childhood disability: ID with MCA being most severely affected and dyslexics being indistinguishable from controls. When autism without ID was considered separately, the increase in CNV burden was modest compared to controls (p = 0.07, odds ratio = 2.33)

Environmental monitoring

© Springer International Publishing AG 2018. Environmental monitoring has been defined as the observation and study of the environment. This entails objective observations that produce sound data, which in turn provide valuable information that is useful, e.g., in supporting the protection of public water supplies, hazardous, non-hazardous, and radioactive waste management, natural resource protection and management, weather forecasting, and global climate change (Artiola et al, Environmental monitoring and characterization, 2004, [1]) studies. From such a definition, what exactly does the term “monitoring” mean within an environmental perspective? Is it synonymous to measuring or observing? A sound definition of monitoring is essential at this point so as to clearly understand the theme of this book, which intents to highlight the uses of GNSS (Global Navigation Satellite Systems) satellites, which have at times been largely regarded as military assets, to monitor the environment. This can be achieved by using GNSS signals to measure and observe changes in the environment

Genomic analyses implicate noncoding de novo variants in congenital heart disease

A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction of noncoding DNV transcriptional impact identified a burden of DNVs in individuals with CHD (n = 2,238 DNVs) compared to controls (n = 4,177; P = 8.7 × 10-4). Independent analyses of enhancers showed an excess of DNVs in associated genes (27 genes versus 3.7 expected, P = 1 × 10-5). We observed significant overlap between these transcription-based approaches (odds ratio (OR) = 2.5, 95% confidence interval (CI) 1.1-5.0, P = 5.4 × 10-3). CHD DNVs altered transcription levels in 5 of 31 enhancers assayed. Finally, we observed a DNV burden in RNA-binding-protein regulatory sites (OR = 1.13, 95% CI 1.1-1.2, P = 8.8 × 10-5). Our findings demonstrate an enrichment of potentially disruptive regulatory noncoding DNVs in a fraction of CHD at least as high as that observed for damaging coding DNVs

De novo variants in neurodevelopmental disorders with epilepsy

Epilepsy is a frequent feature of neurodevelopmental disorders (NDDs), but little is known about genetic differences between NDDs with and without epilepsy. We analyzed de novo variants (DNVs) in 6,753 parent-offspring trios ascertained to have different NDDs. In the subset of 1,942 individuals with NDDs with epilepsy, we identified 33 genes with a significant excess of DNVs, of which SNAP25 and GABRB2 had previously only limited evidence of disease association. Joint analysis of all individuals with NDDs also implicated CACNA1E as a novel disease-associated gene. Comparing NDDs with and without epilepsy, we found missense DNVs, DNVs in specific genes, age of recruitment, and severity of intellectual disability to be associated with epilepsy. We further demonstrate the extent to which our results affect current genetic testing as well as treatment, emphasizing the benefit of accurate genetic diagnosis in NDDs with epilepsy