@article{105, abstract = {Clinical Utility Gene Card. 1. Name of Disease (Synonyms): Pontocerebellar hypoplasia type 9 (PCH9) and spastic paraplegia-63 (SPG63). 2. OMIM# of the Disease: 615809 and 615686. 3. Name of the Analysed Genes or DNA/Chromosome Segments: AMPD2 at 1p13.3. 4. OMIM# of the Gene(s): 102771.}, author = {Marsh, Ashley and Novarino, Gaia and Lockhart, Paul and Leventer, Richard}, journal = {European Journal of Human Genetics}, pages = {161--166}, publisher = {Springer Nature}, title = {{CUGC for pontocerebellar hypoplasia type 9 and spastic paraplegia-63}}, doi = {10.1038/s41431-018-0231-2}, volume = {27}, year = {2019}, } @article{6088, abstract = {P-Glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2) are two efflux transporters at the blood–brain barrier (BBB), which effectively restrict brain distribution of diverse drugs, such as tyrosine kinase inhibitors. There is a crucial need for pharmacological ABCB1 and ABCG2 inhibition protocols for a more effective treatment of brain diseases. In the present study, seven marketed drugs (osimertinib, erlotinib, nilotinib, imatinib, lapatinib, pazopanib, and cyclosporine A) and one nonmarketed drug (tariquidar), with known in vitro ABCB1/ABCG2 inhibitory properties, were screened for their inhibitory potency at the BBB in vivo. Positron emission tomography (PET) using the model ABCB1/ABCG2 substrate [11C]erlotinib was performed in mice. Tested inhibitors were administered as i.v. bolus injections at 30 min before the start of the PET scan, followed by a continuous i.v. infusion for the duration of the PET scan. Five of the tested drugs increased total distribution volume of [11C]erlotinib in the brain (VT,brain) compared to vehicle-treated animals (tariquidar, + 69%; erlotinib, + 19% and +23% for the 21.5 mg/kg and the 43 mg/kg dose, respectively; imatinib, + 22%; lapatinib, + 25%; and cyclosporine A, + 49%). For all drugs, increases in [11C]erlotinib brain distribution were lower than in Abcb1a/b(−/−)Abcg2(−/−) mice (+149%), which suggested that only partial ABCB1/ABCG2 inhibition was reached at the mouse BBB. The plasma concentrations of the tested drugs at the time of the PET scan were higher than clinically achievable plasma concentrations. Some of the tested drugs led to significant increases in blood radioactivity concentrations measured at the end of the PET scan (erlotinib, + 103% and +113% for the 21.5 mg/kg and the 43 mg/kg dose, respectively; imatinib, + 125%; and cyclosporine A, + 101%), which was most likely caused by decreased hepatobiliary excretion of radioactivity. Taken together, our data suggest that some marketed tyrosine kinase inhibitors may be repurposed to inhibit ABCB1 and ABCG2 at the BBB. From a clinical perspective, moderate increases in brain delivery despite the administration of high i.v. doses as well as peripheral drug–drug interactions due to transporter inhibition in clearance organs question the translatability of this concept.}, author = {Traxl, Alexander and Mairinger, Severin and Filip, Thomas and Sauberer, Michael and Stanek, Johann and Poschner, Stefan and Jäger, Walter and Zoufal, Viktoria and Novarino, Gaia and Tournier, Nicolas and Bauer, Martin and Wanek, Thomas and Langer, Oliver}, journal = {Molecular Pharmaceutics}, number = {3}, pages = {1282--1293}, publisher = {American Chemical Society}, title = {{Inhibition of ABCB1 and ABCG2 at the mouse blood-brain barrier with marketed drugs to improve brain delivery of the model ABCB1/ABCG2 substrate [11C]erlotinib}}, doi = {10.1021/acs.molpharmaceut.8b01217}, volume = {16}, year = {2019}, } @article{6470, abstract = {Investigating neuronal activity using genetically encoded Ca2+ indicators in behaving animals is hampered by inaccuracies in spike inference from fluorescent tracers. Here we combine two‐photon [Ca2+] imaging with cell‐attached recordings, followed by post hoc determination of the expression level of GCaMP6f, to explore how it affects the amplitude, kinetics and temporal summation of somatic [Ca2+] transients in mouse hippocampal pyramidal cells (PCs). The amplitude of unitary [Ca2+] transients (evoked by a single action potential) negatively correlates with GCaMP6f expression, but displays large variability even among PCs with similarly low expression levels. The summation of fluorescence signals is frequency‐dependent, supralinear and also shows remarkable cell‐to‐cell variability. We performed experimental data‐based simulations and found that spike inference error rates using MLspike depend strongly on unitary peak amplitudes and GCaMP6f expression levels. We provide simple methods for estimating the unitary [Ca2+] transients in individual weakly GCaMP6f‐expressing PCs, with which we achieve spike inference error rates of ∼5%. }, author = {Éltes, Tímea and Szoboszlay, Miklos and Szigeti, Margit Katalin and Nusser, Zoltan}, issn = {14697793}, journal = {Journal of Physiology}, number = {11}, pages = {2925–2947}, publisher = {Wiley}, title = {{Improved spike inference accuracy by estimating the peak amplitude of unitary [Ca2+] transients in weakly GCaMP6f-expressing hippocampal pyramidal cells}}, doi = {10.1113/JP277681}, volume = {597}, year = {2019}, } @article{6896, abstract = {Until recently, a great amount of brain studies have been conducted in human post mortem tissues, cell lines and model organisms. These researches provided useful insights regarding cell-cell interactions occurring in the brain. However, such approaches suffer from technical limitations and inaccurate modeling of the tissue 3D cytoarchitecture. Importantly, they might lack a human genetic background essential for disease modeling. With the development of protocols to generate human cerebral organoids, we are now closer to reproducing the early stages of human brain development in vitro. As a result, more relevant cell-cell interaction studies can be conducted. In this review, we discuss the advantages of 3D cultures over 2D in modulating brain cell-cell interactions during physiological and pathological development, as well as the progress made in developing organoids in which neurons, macroglia, microglia and vascularization are present. Finally, we debate the limitations of those models and possible future directions.}, author = {Oliveira, Bárbara and Yahya, Aysan Çerağ and Novarino, Gaia}, issn = {18726240}, journal = {Brain Research}, publisher = {Elsevier}, title = {{Modeling cell-cell interactions in the brain using cerebral organoids}}, doi = {10.1016/j.brainres.2019.146458}, volume = {1724}, year = {2019}, } @article{7415, author = {Morandell, Jasmin and Nicolas, Armel and Schwarz, Lena A and Novarino, Gaia}, issn = {0924-977X}, journal = {European Neuropsychopharmacology}, number = {Supplement 6}, pages = {S11--S12}, publisher = {Elsevier}, title = {{S.16.05 Illuminating the role of the e3 ubiquitin ligase cullin3 in brain development and autism}}, doi = {10.1016/j.euroneuro.2019.09.040}, volume = {29}, year = {2019}, } @article{7414, author = {Knaus, Lisa and Tarlungeanu, Dora-Clara and Novarino, Gaia}, issn = {0924-977X}, journal = {European Neuropsychopharmacology}, number = {Supplement 6}, pages = {S11}, publisher = {Elsevier}, title = {{S.16.03 A homozygous missense mutation in SLC7A5 leads to autism spectrum disorder and microcephaly}}, doi = {10.1016/j.euroneuro.2019.09.039}, volume = {29}, year = {2019}, } @misc{6074, abstract = {This dataset contains the supplementary data for the research paper "Haploinsufficiency of the intellectual disability gene SETD5 disturbs developmental gene expression and cognition". The contained files have the following content: 'Supplementary Figures.pdf' Additional figures (as referenced in the paper). 'Supplementary Table 1. Statistics.xlsx' Details on statistical tests performed in the paper. 'Supplementary Table 2. Differentially expressed gene analysis.xlsx' Results for the differential gene expression analysis for embryonic (E9.5; analysis with edgeR) and in vitro (ESCs, EBs, NPCs; analysis with DESeq2) samples. 'Supplementary Table 3. Gene Ontology (GO) term enrichment analysis.xlsx' Results for the GO term enrichment analysis for differentially expressed genes in embryonic (GO E9.5) and in vitro (GO ESC, GO EBs, GO NPCs) samples. Differentially expressed genes for in vitro samples were split into upregulated and downregulated genes (up/down) and the analysis was performed on each subset (e.g. GO ESC up / GO ESC down). 'Supplementary Table 4. Differentially expressed gene analysis for CFC samples.xlsx' Results for the differential gene expression analysis for samples from adult mice before (HC - Homecage) and 1h and 3h after contextual fear conditioning (1h and 3h, respectively). Each sheet shows the results for a different comparison. Sheets 1-3 show results for comparisons between timepoints for wild type (WT) samples only and sheets 4-6 for the same comparisons in mutant (Het) samples. Sheets 7-9 show results for comparisons between genotypes at each time point and sheet 10 contains the results for the analysis of differential expression trajectories between wild type and mutant. 'Supplementary Table 5. Cluster identification.xlsx' Results for k-means clustering of genes by expression. Sheet 1 shows clustering of just the genes with significantly different expression trajectories between genotypes. Sheet 2 shows clustering of all genes that are significantly differentially expressed in any of the comparisons (includes also genes with same trajectories). 'Supplementary Table 6. GO term cluster analysis.xlsx' Results for the GO term enrichment analysis and EWCE analysis for enrichment of cell type specific genes for each cluster identified by clustering genes with different expression trajectories (see Table S5, sheet 1). 'Supplementary Table 7. Setd5 mass spectrometry results.xlsx' Results showing proteins interacting with Setd5 as identified by mass spectrometry. Sheet 1 shows protein protein interaction data generated from these results (combined with data from the STRING database. Sheet 2 shows the results of the statistical analysis with limma. 'Supplementary Table 8. PolII ChIP-seq analysis.xlsx' Results for the Chip-Seq analysis for binding of RNA polymerase II (PolII). Sheet 1 shows results for differential binding of PolII at the transcription start site (TSS) between genotypes and sheets 2+3 show the corresponding GO enrichment analysis for these differentially bound genes. Sheet 4 shows RNAseq counts for genes with increased binding of PolII at the TSS.}, author = {Dotter, Christoph and Novarino, Gaia}, publisher = {Institute of Science and Technology Austria}, title = {{Supplementary data for the research paper "Haploinsufficiency of the intellectual disability gene SETD5 disturbs developmental gene expression and cognition"}}, doi = {10.15479/AT:ISTA:6074}, year = {2019}, } @article{456, abstract = {Inhibition of the endoplasmic reticulum stress pathway may hold the key to Zika virus-associated microcephaly treatment. }, author = {Novarino, Gaia}, journal = {Science Translational Medicine}, number = {423}, publisher = {American Association for the Advancement of Science}, title = {{Zika-associated microcephaly: Reduce the stress and race for the treatment}}, doi = {10.1126/scitranslmed.aar7514}, volume = {10}, year = {2018}, } @article{5888, abstract = {Despite the remarkable number of scientific breakthroughs of the last 100 years, the treatment of neurodevelopmental disorders (e.g., autism spectrum disorder, intellectual disability) remains a great challenge. Recent advancements in genomics, such as whole-exome or whole-genome sequencing, have enabled scientists to identify numerous mutations underlying neurodevelopmental disorders. Given the few hundred risk genes that have been discovered, the etiological variability and the heterogeneous clinical presentation, the need for genotype — along with phenotype- based diagnosis of individual patients has become a requisite. In this review we look at recent advancements in genomic analysis and their translation into clinical practice.}, author = {Tarlungeanu, Dora-Clara and Novarino, Gaia}, issn = {2092-6413}, journal = {Experimental & Molecular Medicine}, number = {8}, publisher = {Springer Nature}, title = {{Genomics in neurodevelopmental disorders: an avenue to personalized medicine}}, doi = {10.1038/s12276-018-0129-7}, volume = {50}, year = {2018}, } @article{546, abstract = {The precise control of neural stem cell (NSC) proliferation and differentiation is crucial for the development and function of the human brain. Here, we review the emerging links between the alteration of embryonic and adult neurogenesis and the etiology of neuropsychiatric disorders (NPDs) such as autism spectrum disorders (ASDs) and schizophrenia (SCZ), as well as the advances in stem cell-based modeling and the novel therapeutic targets derived from these studies.}, author = {Sacco, Roberto and Cacci, Emanuele and Novarino, Gaia}, journal = {Current Opinion in Neurobiology}, number = {2}, pages = {131 -- 138}, publisher = {Elsevier}, title = {{Neural stem cells in neuropsychiatric disorders}}, doi = {10.1016/j.conb.2017.12.005}, volume = {48}, year = {2018}, }