Lack of Association of Rare Functional Variants in TSC1/TSC2 Genes with Autism Spectrum Disorder

Background: Autism spectrum disorder (ASD) is reported in 30 to 60% of patients with tuberous sclerosis complex (TSC) but shared genetic mechanisms that exist between TSC-associated ASD and idiopathic ASD have yet to be determined. Through the small G-protein Rheb, the TSC proteins, hamartin and tuberin, negatively regulate mammalian target of rapamycin complex 1 (mTORC1) signaling. It is well established that mTORC1 plays a pivotal role in neuronal translation and connectivity, so dysregulation of mTORC1 signaling could be a common feature in many ASDs. Pam, an E3 ubiquitin ligase, binds to TSC proteins and regulates mTORC1 signaling in the CNS, and the FBXO45-Pam ubiquitin ligase complex plays an essential role in neurodevelopment by regulating synapse formation and growth. Since mounting evidence has established autism as a disorder of the synapses, we tested whether rare genetic variants in TSC1, TSC2, MYCBP2, RHEB and FBXO45, genes that regulate mTORC1 signaling and/or play a role in synapse development and function, contribute to the pathogenesis of idiopathic ASD. Methods: Exons and splice junctions of TSC1, TSC2, MYCBP2, RHEB and FBXO45 were resequenced for 300 ASD trios from the Simons Simplex Collection (SSC) using a pooled PCR amplification and next-generation sequencing strategy, targeted to the discovery of deleterious coding variation. These detected, potentially functional, variants were confirmed by Sanger sequencing of the individual samples comprising the pools in which they were identified. Results: We identified a total of 23 missense variants in MYCBP2, TSC1 and TSC2. These variants exhibited a near equal distribution between the proband and parental pools, with no statistical excess in ASD cases (P > 0.05). All proband variants were inherited. No putative deleterious variants were confirmed in RHEB and FBXO45. Three intronic variants, identified as potential splice defects in MYCBP2 did not show aberrant splicing upon RNA assay. Overall, we did not find an over-representation of ASD causal variants in the genes studied to support them as contributors to autism susceptibility. Conclusions: We did not observe an enrichment of rare functional variants in TSC1 and TSC2 genes in our sample set of 300 trios

Targeting alphas can make coyote control more effective and socially acceptable

Research at the UC Hopland Research and Extension Center (HREC) has improved our understanding of how to reduce sheep depredation while minimizing the impact on coyotes. Analysis of a 14-year data set of HREC coyote-control efforts found that sheep depredation losses were not correlated with the number of coyotes removed in any of three time scales analyzed (yearly, seasonally and monthly) during corresponding intervals for the next 2 years. Field research using radiotelemetry to track coyotes supported and explained this finding. For example, in 1995, dominant “alphas” from four territories were associated with 89% of 74 coyote-killed lambs; “betas” and transients were not associated with any of these kills. Relatively few coyotes were killing sheep, and these animals were difficult to capture by conventional methods at the time of year when depredation was highest. However, selective removal of only the problem alpha coyotes effectively reduced losses at HREC

Targeting alphas can make coyote control more effective and socially acceptable

Research at the UC Hopland Research and Extension Center (HREC) has improved our understanding of how to reduce sheep depredation while minimizing the impact on coyotes. Analysis of a 14-year data set of HREC coyote-control efforts found that sheep depredation losses were not correlated with the number of coyotes removed in any of three time scales analyzed (yearly, seasonally and monthly) during corresponding intervals for the next 2 years. Field research using radiotelemetry to track coyotes supported and explained this finding. For example, in 1995, dominant “alphas” from four territories were associated with 89% of 74 coyote-killed lambs; “betas” and transients were not associated with any of these kills. Relatively few coyotes were killing sheep, and these animals were difficult to capture by conventional methods at the time of year when depredation was highest. However, selective removal of only the problem alpha coyotes effectively reduced losses at HREC

Whole Genome Sequencing in Psychiatric Disorders: the WGSPD Consortium

As technology advances, whole genome sequencing (WGS) is likely to supersede other genotyping technologies. The rate of this change depends on its relative cost and utility. Variants identified uniquely through WGS may reveal novel biological pathways underlying complex disorders and provide high-resolution insight into when, where, and in which cell type these pathways are affected. Alternatively, cheaper and less computationally intensive approaches may yield equivalent insights. Understanding the role of rare variants in the noncoding gene-regulating genome, through pilot WGS projects, will be critical to determine which of these two extremes best represents reality. With large cohorts, well-defined risk loci, and a compelling need to understand the underlying biology, psychiatric disorders have a role to play in this preliminary WGS assessment. The WGSPD consortium will integrate data for 18,000 individuals with psychiatric disorders, beginning with autism spectrum disorder, schizophrenia, bipolar disorder, and major depressive disorder, along with over 150,000 controls

Approximation of non-linear cost functions in p-graph structures

P-graph employs combinatorial and optimisation algorithms to solve process network synthesis (PNS) problem. However, the P-graph framework requires linear cost functions when optimising PNS problems. As a result, a high error between the user-input linear cost function and the actual non-linear cost function is likely to occur. This paper presents a new method to incorporate multiple linear cost functions in parallel for raw materials, operating units and products in P-graph problems to accurately approximate the non-linear functional form of most cost estimation functions. This was achieved by dividing the original cost functions into multiple equal segments that then could be individually represented by linear sub-functions. Application of the new method to a simple wood-to-fuel processing example influences the optimal P-graph process structure such that a previously uneconomic side-product route (pyrolysis) becomes economic and increases the overall profit. The results also demonstrate that the linear approximation error decreases with increasing numbers of segments and linear cost sub-functions. The time increase to solve the new problem structure, which has over threefold more operating units, is negligible for this simple case, but may be significant for more complex problems

Proteome-wide Mendelian randomization in global biobank meta-analysis reveals multi-ancestry drug targets for common diseases

Proteome-wide Mendelian randomization (MR) shows value in prioritizing drug targets in Europeans but with limited evidence in other ancestries. Here, we present a multi-ancestry proteome-wide MR analysis based on cross-population data from the Global Biobank Meta-analysis Initiative (GBMI). We estimated the putative causal effects of 1,545 proteins on eight diseases in African (32,658) and European (1,219,993) ancestries and identified 45 and 7 protein-disease pairs with MR and genetic colocalization evidence in the two ancestries, respectively. A multi-ancestry MR comparison identified two protein-disease pairs with MR evidence in both ancestries and seven pairs with specific effects in the two ancestries separately. Integrating these MR signals with clinical trial evidence, we prioritized 16 pairs for investigation in future drug trials. Our results highlight the value of proteome-wide MR in informing the generalizability of drug targets for disease prevention across ancestries and illustrate the value of meta-analysis of biobanks in drug development

Joint contributions of rare copy number variants and common SNPs to risk for schizophrenia

Objective: Both rare copy number variants (CNVs) and common single-nucleotide polymorphisms (SNPs) contribute to liability to schizophrenia, but their etiological relationship has not been fully elucidated. The authors evaluated an additive model whereby risk of schizophrenia requires less contribution from common SNPs in the presence of a rare CNV, and tested for interactions. Method: Genetic data from 21,094 case subjects with schizophrenia and 20,227 control subjects from the Psychiatric Genomics Consortium were examined. Three classes of rare CNVs were assessed: CNVs previously associated with schizophrenia, CNVs with large deletions ≥500 kb, and total CNV burden. The mean polygenic risk scores (PRSs) between study subjects with and without rare CNVs were compared, and joint effects of PRS and CNVs on schizophrenia liability were modeled by using logistic regression. Results: Schizophrenia case subjects carrying risk CNVs had a lower polygenic risk than case subjects without risk CNVs but a higher risk than control subjects. For case subjects carrying known risk CNVs, the PRS was diminished in proportion to the effect size of the CNV. The strongly associated 22q11.2 deletion required little added PRS to produce schizophrenia. Large deletions and increased CNV burden were also associated with lower polygenic risk in schizophrenia case subjects but not in control subjects or after removal of known risk CNV carriers. Conclusions: The authors found evidence for interactive effects of PRS and previously associated CNVs for risk for schizophrenia, and the results for large deletions and total CNV burden support an additive model. These findings offer insights into the genetic architecture of schizophrenia by illuminating how different established genetic risk factors act and interact to influence liability to schizophrenia

No Evidence for Association of Autism with Rare Heterozygous Point Mutations in Contactin-Associated Protein-Like 2 (CNTNAP2), or in Other Contactin-Associated Proteins or Contactins

Contactins and Contactin-Associated Proteins, and Contactin-Associated Protein-Like 2 (CNTNAP2) in particular, have been widely cited as autism risk genes based on findings from homozygosity mapping, molecular cytogenetics, copy number variation analyses, and both common and rare single nucleotide association studies. However, data specifically with regard to the contribution of heterozygous single nucleotide variants (SNVs) have been inconsistent. In an effort to clarify the role of rare point mutations in CNTNAP2 and related gene families, we have conducted targeted next-generation sequencing and evaluated existing sequence data in cohorts totaling 2704 cases and 2747 controls. We find no evidence for statistically significant association of rare heterozygous mutations in any of the CNTN or CNTNAP genes, including CNTNAP2, placing marked limits on the scale of their plausible contribution to risk