Rare coding variants in ten genes confer substantial risk for schizophrenia

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3–50, P < 2.14 × 10−6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-d-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach

Sub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals

Both mild and severe epilepsies are influenced by variants in the same genes, yet an explanation for the resulting phenotypic variation is unknown. As part of the ongoing Epi25 Collaboration, we performed a whole-exome sequencing analysis of 13,487 epilepsy-affected individuals and 15,678 control individuals. While prior Epi25 studies focused on gene-based collapsing analyses, we asked how the pattern of variation within genes differs by epilepsy type. Specifically, we compared the genetic architectures of severe developmental and epileptic encephalopathies (DEEs) and two generally less severe epilepsies, genetic generalized epilepsy and non-acquired focal epilepsy (NAFE). Our gene-based rare variant collapsing analysis used geographic ancestry-based clustering that included broader ancestries than previously possible and revealed novel associations. Using the missense intolerance ratio (MTR), we found that variants in DEE-affected individuals are in significantly more intolerant genic sub-regions than those in NAFE-affected individuals. Only previously reported pathogenic variants absent in available genomic datasets showed a significant burden in epilepsy-affected individuals compared with control individuals, and the ultra-rare pathogenic variants associated with DEE were located in more intolerant genic sub-regions than variants associated with non-DEE epilepsies. MTR filtering improved the yield of ultra-rare pathogenic variants in affected individuals compared with control individuals. Finally, analysis of variants in genes without a disease association revealed a significant burden of loss-of-function variants in the genes most intolerant to such variation, indicating additional epilepsy-risk genes yet to be discovered. Taken together, our study suggests that genic and sub-genic intolerance are critical characteristics for interpreting the effects of variation in genes that influence epilepsy

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice

A Chemical Kinetic Study of Tertiary-Butanol in a Flow Reactor and a Counterflow Diffusion Flame

The combustion chemistry of tertiary-butanol is studied experimentally in a high pressure flow reactor and in counterflow diffusion flames. Princeton Variable Pressure Flow Reactor results show that t-butanol does not exhibit low temperature chemistry, and thus has no negative temperature coefficient behavior under the studied conditions. The onset of gas phase chemistry at high pressure occurs at ∼780 K. Over the temperature range of 780–950 K, t-butanol primarily reacts through hydrogen abstraction − alkyl or alkoxy radical beta-scission pathways to form methyl and propen-2-ol, which likely tautomerizes in the sampling system to form acetone. A species sampling study of a t-butanol counterflow diffusion flame reveals that the high temperature consumption routes of t-butanol lead to the stable intermediates isobutene, acetone, and methane, with isobutene existing in the highest concentrations. The extinction limits of t-butanol, isobutene, acetone, and methane diffusion flames are also reported. On a transport-weighted enthalpy basis, t-butanol extinguishes more readily than any of its primary intermediates, signifying that it is kinetically less resistant to extinction than the products of its initial reactions. Numerical simulation of these t-butanol flames reveals that the isobutene and acetone chemistry sub-models significantly affect the computed extinction limits. Improvement in the current understanding of isobutene oxidation kinetics, in particular, appears necessary to developing reliable kinetic models for t-butanol combustion

Macroscopic multi-dimensional modelling of electrochemically promoted systems

The objective of this work is the construction of macroscopic models for electrochemically promoted catalytic systems, i.e. systems where the catalytic performance is improved by application of potential between the anode and cathode electrodes in the cell. This polarization effect leads to a formation of an effective double layer over the catalytic film due to migration of ‘backspillover’ species from the electrolyte to the working electrode when potential difference is applied in the system. In this paper, we propose a multidimensional, isothermal, dynamic solid oxide single pellet model, which describes the chemical and electrochemical phenomena taking place under polarization conditions. The electrochemically promoted oxidation of CO over Pt/YSZ is used as an illustrative system. The partial differential equation-based 2- and 3-dimensional macroscopic models that describe the simultaneous mass and charge transport in the pellet are constructed and solved in COMSOL Multiphysics. The model predicts species coverage on the catalytic surface, electronic and ionic potential curves across the pellet, gas mixture concentration within the reactor and CO2 production rate. Parameter estimation is undertaken so as to provide us with values of parameters, which are necessary for the simulation of the model. Subsequent sensitivity analysis is performed to investigate the effect of the percentage change of each estimated parameter on the CO2 production rate. As it is shown, the reaction rate curves obtained from the current modelling framework are in good agreement with values found in the literature