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1. The nicotinic receptor alpha5 coding polymorphism rs16969968 as a major target in disease: Functional dissection and remaining challenges

Author

Uwe Maskos, Neurobiologie intégrative des Systèmes cholinergiques / Integrative Neurobiology of Cholinergic Systems (NISC), Sorbonne Université (SU)-Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), he author has received funding to carry out the work of his laboratory described in the Review article, as indicated in the published papers. No funding has been received that is directly relevant to this Review article. The author has no conflict of interest to declare., and Institut Pasteur [Paris] (IP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, human genetics, Single-nucleotide polymorphism, Locus (genetics), Genome-wide association study, Disease, Receptors, Nicotinic, Biology, Bioinformatics, Polymorphism, Single Nucleotide, Biochemistry, nicotine addiction, drug discovery, 03 medical and health sciences, Cellular and Molecular Neuroscience, [SCCO]Cognitive science, 0302 clinical medicine, single nucleotide polymorphism, Animals, Humans, nicotinic acetylcholine receptor, Genetic association, [SCCO.NEUR]Cognitive science/Neuroscience, Human genetics, 3. Good health, schizophrenia, Nicotinic acetylcholine receptor, 030104 developmental biology, Nicotinic agonist, positive allosteric modulator, Genome-wide Association Studies, 030217 neurology & neurosurgery
Abstract

International audience; Nicotinic acetylcholine receptors (nAChRs) are major signalling molecules in the central and peripheral nervous system. Over the last decade, they have been linked to a number of major human psychiatric and neurological conditions, like smoking, schizophrenia, Alzheimer's disease and many others. Human Genome-Wide Association Studies (GWAS) have robustly identified genetic alterations at a locus of chromosome 15q to several of these diseases. In this review, we discuss a major coding polymorphism in the alpha5 subunit, referred to as α5SNP, and its functional dissection in vitro and in vivo. Its presence at high frequency in many human populations lends itself to pharmaceutical intervention in the context of 'positive allosteric modulators' (PAMs). We will present the prospects of this novel treatment, and the remaining challenges to identify suitable molecules.

Published
2020

2. Social and non-social autism symptoms and trait domains are genetically dissociable

Author

Freddy Cliquet, Varun Warrier, Roberto Toro, Hyejung Won, Richard Delorme, Thomas Bourgeron, Anders D. Børglum, Janita Bralten, Claire S. Leblond, Geert Poelmans, Jakob Grove, Ward De Witte, Bhismadev Chakrabarti, David A. Hinds, Simon Baron-Cohen, Toro, Roberto [0000-0002-6671-858X], Cliquet, Freddy [0000-0002-9989-0685], Chakrabarti, Bhismadev [0000-0002-6649-7895], Børglum, Anders D. [0000-0001-8627-7219], Grove, Jakob [0000-0003-2284-5744], Hinds, David A. [0000-0002-4911-803X], Apollo - University of Cambridge Repository, University of Cambridge [UK] (CAM), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), Child and Adolescent Psychiatry Department [AP- HP Hôpital Robert Debré], AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Radboud University Medical Center [Nijmegen], Radboud University [Nijmegen], University of Reading (UOR), The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus University [Aarhus], 23andMe Inc., V.W. was funded by St. John’s College, Cambridge, and the Cambridge Commonwealth Trust. This study was funded by grants to SBC from the Medical Research Council, the Wellcome Trust, the Autism Research Trust, the Templeton World Charity Foundation, and to T.B. from the Institut Pasteur, the CNRS, the INSERM, The Fondamental Foundation, the APHP, the BioPsy Labex and the University Paris Diderot. The research was conducted in association with the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care East of England at Cambridgeshire and Peterborough NHS Foundation Trust. We also received support from the NIHR Cambridge Biomedical Research Centre. We acknowledge with gratitude the generous support of Drs Dennis and Mireille Gillings in strengthening the collaboration between S.B.-C. and T.B., and between Cambridge University and the Institut Pasteur. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Data obtained from 23andMe was supported by the National Human Genome Research Institute of the National Institutes of Health (grant number R44HG006981). The UK Medical Research Council and Wellcome (grant ref: 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. GWAS data were generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. This publication is the work of the authors who will serve as guarantors for the content of this paper. The iPSYCH (The Lundbeck Foundation Initiative for Integrative Psychiatric Research) team acknowledges funding from The Lundbeck Foundation (grant nos. R102-A9118 and R155-2014-1724), the Stanley Medical Research Institute, the European Research Council (project no.: 294838), the Novo Nordisk Foundation for supporting the Danish National Biobank resource, and grants from Aarhus and Copenhagen Universities and University Hospitals, including support to the iSEQ Center, the GenomeDK HPC facility, and the CIRRAU Center. The project leading to this application has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement no. 777394. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA and AUTISM SPEAKS, Autistica, SFARI. We thank the iPSCH-Broad Autism Group and the EU-AIMS LEAP group for sharing data. A full list of the authors and affiliations in the iPSYCH-Broad autism group and the EU-AIMS LEAP group is provided in the Supplementary Information., The 23andMe Research Team : Michelle Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson, Pierre Fontanillas, Nicholas A. Furlotte, Karen E. Huber, Aaron Kleinman, Nadia K. Litterman, Jennifer C. McCreight, Matthew H. McIntyre, Joanna L. Mountain, Carrie A.M. Northover, Steven J. Pitts, J. Fah Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao Tian, Joyce Y. Tung, Vladimir Vacic & Catherine H. Wilson, European Project: 294838,EC:FP7:ERC,ERC-2011-ADG_20110310,EIMS(2012), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), and Radboud university [Nijmegen]

Subjects
Male, DIAGNOSTIC OBSERVATION SCHEDULE, LD SCORE REGRESSION, 45/43, Medicine (miscellaneous), Genome-wide association study, Genome-wide association studies, Developmental psychology, FUNCTIONING AUTISM, Cohort Studies, 0302 clinical medicine, Heritability of autism, MESH: Cohort Studies, lcsh:QH301-705.5, GENERAL-POPULATION, 631/208/366/1373, 0303 health sciences, MESH: Genetic Predisposition to Disease, article, Autism spectrum disorders, MESH: Reproducibility of Results, Phenotype, Autistic traits, 631/208/727/2000, Trait, Female, General Agricultural and Biological Sciences, Psychology, MESH: Social Behavior, EMPATHY QUOTIENT, MESH: Autistic Disorder, 631/208/205/2138, Genetic predisposition to disease, MESH: Phenotype, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, PSYCHOMETRIC ANALYSIS, All institutes and research themes of the Radboud University Medical Center, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], mental disorders, medicine, Humans, REPETITIVE BEHAVIOR, Autistic Disorder, GENOME-WIDE ASSOCIATION, Social Behavior, Association (psychology), 030304 developmental biology, SYSTEMATIZING QUOTIENT, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], MESH: Humans, Reproducibility of Results, SPECTRUM QUOTIENT AQ, medicine.disease, MESH: Male, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, lcsh:Biology (General), MESH: Genome-Wide Association Study, Autism, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], MESH: Female, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

The core diagnostic criteria for autism comprise two symptom domains – social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, though this hypothesis has not yet been tested using molecular genetics. We test this using a genome-wide association study (N = 51,564) of a non-social trait related to autism, systemising, defined as the drive to analyse and build systems. We demonstrate that systemising is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemising. Supporting this, polygenic scores for systemising are significantly and positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism., Varun Warrier et al. report a genome-wide association study of systemising, a non-social trait associated with autism. They find 3 loci associated with systemising and show that this trait has no significant genetic correlations to social phenotypic measures, demonstrating that the social and non-social aspects of autism are genetically distinct.

Published
2019
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3. A test for gene-environment interaction in the presence of measurement error in the environmental variable

Author

Hugues Aschard, Donna Spiegelman, Molin Wang, Vincent Laville, Pete Kraft, Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Harvard T.H. Chan School of Public Health, The authors thank the reviewers for their helpful comments that have improved the paper. This research is supported by grant R01CA050597 from the National Cancer Institute (NCI) and R21HG007687 from the National Human Genome Research Institute (NHGRI). The authors have no conflict of interest to declare., and Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, Epidemiology, Genome-wide association study, Breast Neoplasms, MESH: Logistic Models, Interaction, Logistic regression, 01 natural sciences, Article, Correlation, 010104 statistics & probability, 03 medical and health sciences, Bias, Statistics, Linear regression, MESH: Bias, Humans, normal discriminant analysis, MESH: Genetic Variation, MESH: Models, Genetic, 0101 mathematics, Gene–environment interaction, gene-environment interaction test, Genetics (clinical), Mathematics, [STAT.AP]Statistics [stat]/Applications [stat.AP], Observational error, MESH: Humans, Models, Genetic, Genetic Variation, Reproducibility of Results, MESH: Gene-Environment Interaction, Linear discriminant analysis, 3. Good health, MESH: Reproducibility of Results, 030104 developmental biology, Logistic Models, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, genome-wide association studies, MESH: Genome-Wide Association Study, Gene-Environment Interaction, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [STAT.ME]Statistics [stat]/Methodology [stat.ME], measurement error, MESH: Breast Neoplasms, Genome-Wide Association Study
Abstract

International audience; The identification of gene-environment interactions in relation to risk of human diseases has been challenging. One difficulty has been that measurement error in the exposure can lead to massive reductions in the power of the test, as well as in bias toward the null in the interaction effect estimates. Leveraging previous work on linear discriminant analysis, we develop a new test of interaction between genetic variants and a continuous exposure that mitigates these detrimental impacts of exposure measurement error in ExG testing by reversing the role of exposure and the diseases status in the fitted model, thus transforming the analysis to standard linear regression. Through simulation studies, we show that the proposed approach is valid in the presence of classical exposure measurement error as well as when there is correlation between the exposure and the genetic variant. Simulations also demonstrated that the reverse test has greater power compared to logistic regression. Finally, we confirmed that our approach eliminates bias from exposure measurement error in estimation. Computing times are reduced by as much as fivefold in this new approach. For illustrative purposes, we applied the new approach to an ExGWAS study of interactions with alcohol and body mass index among 1,145 cases with invasive breast cancer and 1,142 controls from the Cancer Genetic Markers of Susceptibility study.

Published
2018