SUMMARY Autism spectrum disorder (ASD) is a complex developmental syndrome of unknown etiology. Recent studies employing exome- and genome-wide sequencing have identified nine high-confidence ASD (hcASD) genes. Working from the hypothesis that ASD-associated mutations in these biologically pleiotropic genes will disrupt intersecting developmental processes to contribute to a common phenotype, we have attempted to identify time periods, brain regions, and cell types in which these genes converge. We have constructed coexpression networks based on the hcASD “seed” genes, leveraging a rich expression data set encompassing multiple human brain regions across human development and into adulthood. By assessing enrichment of an independent set of probable ASD (pASD) genes, derived from the same sequencing studies, we demonstrate a key point of convergence in midfetal layer 5/6 cortical projection neurons. This approach informs when, where, and in what cell types mutations in these specific genes may be productively studied to clarify ASD pathophysiology.

Over 100 genetic loci harbor schizophrenia associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of schizophrenia cases (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ~20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3, or SNAP91. Altering expression of FURIN, TSNARE1, or CNTN4 changes neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yields abnormal migration. Of 693 genes showing significant case/control differential expression, their fold changes are ≤ 1.33, and an independent cohort yields similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases.

73Over 100 genetic loci harbor schizophrenia associated variants, yet how these common 74 variants confer risk is uncertain. The CommonMind Consortium has sequenced dorsolateral 75 prefrontal cortex RNA from schizophrenia cases (n=258) and control subjects (n=279), creating 76 the largest publicly available resource to date of gene expression and its genetic regulation; ~5 77 times larger than the latest release of GTEx. Using this resource, we find that ~20% of the 78 schizophrenia risk loci have common variants that could explain regulation of brain gene 79 expression. In five loci, these variants modulate expression of a single gene: FURIN, TSNARE1, 80 CNTN4, CLCN3 or SNAP91. Experimentally altered expression of three of them, FURIN, 81 TSNARE1, and CNTN4, perturbs the proliferation and apoptotic index of neural progenitors and 82 leads to neuroanatomical deficits in zebrafish. Furthermore, shRNA mediated knock-down of 83 FURIN in neural progenitor cells derived from human induced pluripotent stem cells produces 84 abnormal neural migration. Although 4.2% of genes (N = 693) display significant differential 85 expression between cases and controls, 44% show some evidence for differential expression. 86All fold changes are ≤ 1.33, and an independent cohort yields similar differential expression for 87 these 693 genes (r = 0.58). These findings are consistent with schizophrenia being highly 88 polygenic, as has been reported in investigations of common and rare genetic variation. Co-89 expression analyses identify a gene module that shows enrichment for genetic associations and 90 is thus relevant for schizophrenia. Taken together, these results pave the way for mechanistic 91 interpretations of genetic liability for schizophrenia and other brain diseases. 4The human brain is complicated and not well understood. Seemingly straightforward 93 fundamental information such as which genes are expressed therein and what functions they 94 perform are only partially characterized. To overcome these obstacles, we established the 95 CommonMind Consortium (CMC; www.synpase.org/CMC), a public-private partnership to 96 generate functional genomic data in brain samples obtained from autopsies of cases with and 97 without severe psychiatric disorders. The CMC is the largest existing collection of collaborating 98 brain banks and includes over 1,150 samples. A wide spectrum of data is being generated on 99 these samples including regional gene expression, epigenomics (cell-type specific histone 100 modifications and open chromatin), whole genome sequencing, and somatic mosaicism. 101 102 Schizophrenia (SCZ), affecting roughly 0.7% of adults, is a severe psychiatric disorder 103 characterized by abnormalities in thought and cognition (1). Despite a century of evidence 104 establishing its genetic basis, only recently have specific genetic risk factors been conclusively 105identified, including rare copy number variants (2) and >100 common variants (3). However, 106 there is not a one-to-one Mendelian mapping between these SCZ ris...

Reactive oxygen and nitrogen species (ROS and RNS) produced by macrophages are essential for protecting a human body against bacteria and viruses. Micrometer-sized electrodes coated with Pt black have previously been used for selective and sensitive detection of ROS and RNS in biological systems. To determine ROS and RNS inside macrophages, one needs smaller (i.e., nanometer-sized) sensors. In this article, the methodologies have been extended to the fabrication and characterization of Pt/Pt black nanoelectrodes. Electrodes with the metal surface flush with glass insulator, most suitable for quantitative voltammetric experiments, were fabricated by electrodeposition of Pt black inside an etched nanocavity under the atomic force microscope control. Despite a nanometerscale radius, the true surface area of Pt electrodes was sufficiently large to yield stable and reproducible responses to ROS and RNS in vitro. The prepared nanoprobes were used to penetrate cells and detect ROS and RNS inside macrophages. Weak and very short leaks of ROS/RNS from the vacuoles into the cytoplasm were detected, which a macrophage is equipped to clean within a couple of seconds, while higher intensity oxidative bursts due to the emptying of vacuoles outside persist on the time scale of tens of seconds.amperometry | atomic force microscopy | oxidative stress | electrochemical nanofabrication | intracellular sensor M acrophage cells are essential for the performance of the immune system. Their activation, either under normal biological conditions or by specific biochemical activators in vitro, results in the production of reactive oxygen and nitrogen species (ROS and RNS) and creation of a large number of vacuoles (phagosomes and phagolysosomes; see Fig. 1A and SI Appendix) (1-3). These vacuoles play an important role in phagocytosisa mechanism used by the immune system to remove pathogens and cell debris. A cell (or debris) is engulfed into a vacuole and subjected to an intense oxidative burst (2), and the indigestible debris and excess ROS and RNS are subsequently evacuated from the macrophage (Fig. 1B).The changes in oxygen and hydrogen peroxide concentrations during the oxidative burst of a stimulated macrophage cell were detected previously using the scanning electrochemical microscope (4). Extensive studies with amperometric microelectrodes positioned in the cell proximity showed that the basal release is due to a cocktail composed of several ROS and RNS evolving from the primary production of O 2•− and NO (5-8). However, the concept that ROS and RNS released inside phagolysosomes may diffuse across the vacuole membrane and leak in the cell cytoplasm remains controversial (9-12). In fact, NO and the transisomer of protonated peroxynitrite ion are capable of crossing biological membranes due to their lipophilicity (13,14). This underscores the importance of probing for the intracellular presence of ROS and RNS in activated macrophages.For electrochemical measurements inside an activated macrophage one needs nanometer-sized electrode...

BackgroundDe novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes.MethodsTo accelerate the search for ASD genes, we developed a novel algorithm, DAWN, to model two kinds of data: rare variations from exome sequencing and gene co-expression in the mid-fetal prefrontal and motor-somatosensory neocortex, a critical nexus for risk. The algorithm casts the ensemble data as a hidden Markov random field in which the graph structure is determined by gene co-expression and it combines these interrelationships with node-specific observations, namely gene identity, expression, genetic data and the estimated effect on risk.ResultsUsing currently available genetic data and a specific developmental time period for gene co-expression, DAWN identified 127 genes that plausibly affect risk, and a set of likely ASD subnetworks. Validation experiments making use of published targeted resequencing results demonstrate its efficacy in reliably predicting ASD genes. DAWN also successfully predicts known ASD genes, not included in the genetic data used to create the model.ConclusionsValidation studies demonstrate that DAWN is effective in predicting ASD genes and subnetworks by leveraging genetic and gene expression data. The findings reported here implicate neurite extension and neuronal arborization as risks for ASD. Using DAWN on emerging ASD sequence data and gene expression data from other brain regions and tissues would likely identify novel ASD genes. DAWN can also be used for other complex disorders to identify genes and subnetworks in those disorders.