Biology subjects

Pardinas, A. F.

Publications and source records attributed to Pardinas, A. F..

5 recordsLinked to original sources

bioRxiv2018

A Transcriptome Wide Association Study implicates specific pre- and post-synaptic abnormalities in Schizophrenia

Schizophrenia is a complex highly heritable disorder. Genome-wide association studies have identified multiple loci that influence the risk of developing schizophrenia, although the causal variants driving these associations and their impacts on specific genes are largely unknown. Here we link genetic findings to gene expression in the human brain by performing a transcriptome-wide association study (TWAS) in which we integrate the largest published genome-wide association dataset of schizophrenia, with publically available post mortem expression data from the dorsolateral prefrontal cortex (DLPFC). We identify a significant correlation between schizophrenia risk and expression at eighty-nine genes in DLPFC, including forty-two genes not identified in earlier TWAS of this transcriptomic resource. Genes whose expression correlate with schizophrenia were enriched for those involved in nervous system development, abnormal synaptic transmission, reduced long term potentiation, and calcium-dependent cell-cell adhesion. Previous genetic studies have implicated post-synaptic glutamatergic and gabaergic processes in schizophrenia; here we extend this to include molecules that regulate presynaptic transmitter release. We identify specific candidate genes to which we assign predicted directions of effect in terms of expression level, facilitating downstream experimental studies geared towards a better mechanistic understanding of schizophrenia pathogenesis.

genetics↗

bioRxiv2018

Medical consequences of pathogenic CNVs in adults: Analysis of the UK Biobank.

BackgroundGenomic copy number variants (CNVs) increase risk for early-onset neurodevelopmental disorders but their impact on medical outcomes in later life is poorly understood. The UK Biobank, with half a million well-phenotyped adults, presents an opportunity to study the medical consequences of CNV in middle and old age.\n\nMethodsWe called 54 CNVs associated with clinical phenotypes or genomic disorders, including their reciprocal deletions or duplications, in all Biobank participants. We used logistic regression analysis to test CNVs for associations with 58 common medical phenotypes.\n\nFindingsCNV carriers had an increased risk of developing 37 of the 58 phenotypes at nominal levels of statistical significance, with 19 associations surviving Bonferroni correction (p<8{middle dot}6x10-4). Tests of each of the 54 CNVs for association with each of the 58 phenotypes identified 18 associations that survived Bonferroni correction (p<1{middle dot}6x10-5) and a further 57 that were associated at a false discovery rate (FDR) threshold of 0{middle dot}1. Thirteen CNVs had three or more significant associations at FDR=0{middle dot}1, with the largest number of phenotypes (N=15) found for deletions at 16p11{middle dot}2. The most common CNVs (frequency 0{middle dot}5-0{middle dot}7%) have no or minimal impact on medical outcomes in adults.\n\nInterpretationSome of the 54 tested CNVs have profound effects on physical health, even in people who have largely escaped early neurodevelopmental outcomes. Our work provides clinicians with a morbidity map of potential outcomes among carriers of these CNVs.\n\nFundingMRC UK, Wellcome Trust UK

genomics↗

bioRxiv2018

Association between schizophrenia and both loss of function and missense mutations in paralog conserved sites of voltage-gated sodium channels

Sequencing studies have highlighted candidate sets of genes involved in schizophrenia, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-d-aspartate receptor (NMDAR) complexes. Two genes, SETD1A and RBM12, have also been associated with robust statistical evidence. Larger samples and novel methods for identifying disease-associated missense variants are needed to reveal novel genes and biological mechanisms associated with schizophrenia. We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5,207 cases and 4,991 controls. Included were members of ARC and NMDAR post-synaptic protein complexes, as well as voltage-gated sodium and calcium channels. We observed a significant case excess of rare (<0.1% in frequency) loss-of-function (LoF) mutations across all 187 genes (OR = 1.36; Pcorrected = 0.0072) but no individual gene was associated with schizophrenia after correcting for multiple testing. We found novel evidence that LoF and missense variants at paralog conserved sites were enriched in sodium channels (OR = 1.26; P = 0.0035). Meta-analysis of our new data with published sequencing data (11,319 cases, 15,854 controls and 1,136 trios) supported and refined this association to sodium channel alpha subunits (P = 0.0029). Meta-analysis also confirmed association between schizophrenia and rare variants in ARC (P = 4.0 x 10-4) and NMDAR (P = 1.7 x 10-5) synaptic genes. No association was found between rare variants in calcium channels and schizophrenia.\n\nIn one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis, and increase the evidence for association between rare variants in ARC and NMDAR post-synaptic complexes and schizophrenia. Larger samples are required to identify specific genes and variants driving these associations.\n\nAuthor SummaryCommon and rare genetic variations are known to play a substantial role in the development of schizophrenia. Recently, sequencing studies have started to highlight specific sets of genes that are enriched for rare variation in schizophrenia, such as the synaptic gene sets ARC and NMDAR, as well as voltage-gated sodium and calcium channels. To confirm the role of these gene sets in schizophrenia, and identify specific risk genes, we sequenced 187 genes in a new sample of 5,207 schizophrenia cases and 4,991 controls. We find an excess of protein truncating mutations with a frequency <0.1% in all 187 targeted genes, and provide novel evidence that mutations altering amino acids conserved across sodium channel proteins are risk factors for schizophrenia. Through meta-analysing our new data with previously published sequencing data sets, for a total of 11,319 cases, 15,854 controls and 1,136 trios, we increase the evidence for association between rare coding variants and schizophrenia in voltage-gated sodium channels, as well as in synaptic gene sets ARC and NMDAR. Although no individual gene was associated with schizophrenia, these findings suggest larger studies will identify the specific genes driving these associations.

genetics↗

bioRxiv2017

Gene expression imputation across multiple brain regions reveals schizophrenia risk throughout development.

Transcriptomic imputation approaches offer an opportunity to test associations between disease and gene expression in otherwise inaccessible tissues, such as brain, by combining eQTL reference panels with large-scale genotype data. These genic associations could elucidate signals in complex GWAS loci and may disentangle the role of different tissues in disease development. Here, we use the largest eQTL reference panel for the dorso-lateral pre-frontal cortex (DLPFC), collected by the CommonMind Consortium, to create a set of gene expression predictors and demonstrate their utility. We applied these predictors to 40,299 schizophrenia cases and 65,264 matched controls, constituting the largest transcriptomic imputation study of schizophrenia to date. We also computed predicted gene expression levels for 12 additional brain regions, using publicly available predictor models from GTEx. We identified 413 genic associations across 13 brain regions. Stepwise conditioning across the genes and tissues identified 71 associated genes (67 outside the MHC), with the majority of associations found in the DLPFC, and of which 14/67 genes did not fall within previously genome-wide significant loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple pathways associated with porphyric disorders. We investigated developmental expression patterns for all 67 non-MHC associated genes using BRAINSPAN, and identified groups of genes expressed specifically pre-natally or post-natally.

genetics↗

bioRxiv2017

Genetic Identification Of Brain Cell Types Underlying Schizophrenia

With few exceptions, the marked advances in knowledge about the genetic basis for schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. Applying knowledge of the cellular taxonomy of the brain from single-cell RNA-sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. The common variant genomic results consistently mapped to pyramidal cells, medium spiny neurons, and certain interneurons but far less consistently to embryonic, progenitor, or glial cells. These enrichments were due to distinct sets of genes specifically expressed in each of these cell types. Many of the diverse gene sets associated with schizophrenia (including antipsychotic targets) implicate the same brain cell types. Our results provide a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. While some of the genetic risk is associated with GABAergic interneurons, this risk largely does not overlap with that from projecting cells.

genomics↗