351
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Kornilov SA, Tan M, Aljughaiman A, Naumova OY, Grigorenko EL. Genome-Wide Homozygosity Mapping Reveals Genes Associated With Cognitive Ability in Children From Saudi Arabia. Front Genet 2019; 10:888. [PMID: 31620175 PMCID: PMC6759945 DOI: 10.3389/fgene.2019.00888] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 08/22/2019] [Indexed: 11/28/2022] Open
Abstract
Recent studies of the genetic foundations of cognitive ability rely on large samples (in extreme, hundreds of thousands) of individuals from relatively outbred populations of mostly European ancestry. Hypothesizing that the genetic foundation of cognitive ability depends on the broader population-specific genetic context, we performed a genome-wide association study and homozygosity mapping of cognitive ability estimates obtained through latent variable modeling in a sample of 354 children from a consanguineous population of Saudi Arabia. Approximately half of the sample demonstrated significantly elevated homozygosity levels indicative of inbreeding, and among those with elevated levels, homozygosity was negatively associated with cognitive ability. Further homozygosity mapping identified a specific run, inclusive of the GRIA4 gene, that survived corrections for multiple testing for association with cognitive ability. The results suggest that in a consanguineous population, a notable proportion of the variance in cognitive ability in the normal range in children might be regulated by population-specific mechanisms such as patterns of elevated homozygosity. This observation has implications for the field's understanding of the etiological bases of intelligence and its variability around the world.
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Affiliation(s)
- Sergey A. Kornilov
- Baylor College of Medicine, Department of Molecular and Human Genetics, Houston, TX, United States
- Department of Psychology, University of Houston, Houston, TX, USA
| | - Mei Tan
- Department of Psychology, University of Houston, Houston, TX, USA
| | | | - Oxana Yu Naumova
- Department of Psychology, University of Houston, Houston, TX, USA
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Elena L. Grigorenko
- Baylor College of Medicine, Department of Molecular and Human Genetics, Houston, TX, United States
- Department of Psychology, University of Houston, Houston, TX, USA
- Child Study Center, Yale University, New Haven, CT, USA
- Moscow State University for Psychology and Education, Moscow, Russia
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352
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Smeland OB, Frei O, Shadrin A, O'Connell K, Fan CC, Bahrami S, Holland D, Djurovic S, Thompson WK, Dale AM, Andreassen OA. Discovery of shared genomic loci using the conditional false discovery rate approach. Hum Genet 2019; 139:85-94. [PMID: 31520123 DOI: 10.1007/s00439-019-02060-2] [Citation(s) in RCA: 92] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 08/08/2019] [Indexed: 02/07/2023]
Abstract
In recent years, genome-wide association study (GWAS) sample sizes have become larger, the statistical power has improved and thousands of trait-associated variants have been uncovered, offering new insights into the genetic etiology of complex human traits and disorders. However, a large fraction of the polygenic architecture underlying most complex phenotypes still remains undetected. We here review the conditional false discovery rate (condFDR) method, a model-free strategy for analysis of GWAS summary data, which has improved yield of existing GWAS and provided novel findings of genetic overlap between a wide range of complex human phenotypes, including psychiatric, cardiovascular, and neurological disorders, as well as psychological and cognitive traits. The condFDR method was inspired by Empirical Bayes approaches and leverages auxiliary genetic information to improve statistical power for discovery of single-nucleotide polymorphisms (SNPs). The cross-trait condFDR strategy analyses separate GWAS data, and leverages overlapping SNP associations, i.e., cross-trait enrichment, to increase discovery of trait-associated SNPs. The extension of the condFDR approach to conjunctional FDR (conjFDR) identifies shared genomic loci between two phenotypes. The conjFDR approach allows for detection of shared genomic associations irrespective of the genetic correlation between the phenotypes, often revealing a mixture of antagonistic and agonistic directional effects among the shared loci. This review provides a methodological comparison between condFDR and other relevant cross-trait analytical tools and demonstrates how condFDR analysis may provide novel insights into the genetic relationship between complex phenotypes.
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Affiliation(s)
- Olav B Smeland
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway.
| | - Oleksandr Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Alexey Shadrin
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Kevin O'Connell
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Chun-Chieh Fan
- Department of Cognitive Science, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA
| | - Shahram Bahrami
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Dominic Holland
- Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, San Diego, CA, 92037, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Wesley K Thompson
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, San Diego, CA, 92093, USA
| | - Anders M Dale
- Department of Cognitive Science, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, San Diego, CA, 92037, USA
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway.
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353
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Comes AL, Senner F, Budde M, Adorjan K, Anderson-Schmidt H, Andlauer TFM, Gade K, Hake M, Heilbronner U, Kalman JL, Reich-Erkelenz D, Klöhn-Saghatolislam F, Schaupp SK, Schulte EC, Juckel G, Dannlowski U, Schmauß M, Zimmermann J, Reimer J, Reininghaus E, Anghelescu IG, Arolt V, Baune BT, Konrad C, Thiel A, Fallgatter AJ, Nieratschker V, Figge C, von Hagen M, Koller M, Becker T, Wigand ME, Jäger M, Dietrich DE, Stierl S, Scherk H, Spitzer C, Folkerts H, Witt SH, Degenhardt F, Forstner AJ, Rietschel M, Nöthen MM, Wiltfang J, Falkai P, Schulze TG, Papiol S. The genetic relationship between educational attainment and cognitive performance in major psychiatric disorders. Transl Psychiatry 2019; 9:210. [PMID: 31462630 PMCID: PMC6713703 DOI: 10.1038/s41398-019-0547-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 06/03/2019] [Accepted: 07/17/2019] [Indexed: 11/13/2022] Open
Abstract
Cognitive deficits are a core feature of psychiatric disorders like schizophrenia and bipolar disorder. Evidence supports a genome-wide polygenic score (GPS) for educational attainment (GPSEDU) can be used to explain variability in cognitive performance. We aimed to identify different cognitive domains associated with GPSEDU in a transdiagnostic clinical cohort of chronic psychiatric patients with known cognitive deficits. Bipolar and schizophrenia patients from the PsyCourse cohort (N = 730; 43% female) were used. Likewise, we tested whether GPSs for schizophrenia (GPSSZ) and bipolar disorder (GPSBD) were associated with cognitive outcomes. GPSEDU explained 1.5% of variance in the backward verbal digit span, 1.9% in the number of correctly recalled words of the Verbal Learning and Memory Test, and 1.1% in crystallized intelligence. These effects were robust to the influences of treatment and diagnosis. No significant associations between GPSSZ or GPSBD with cognitive outcomes were found. Furthermore, these risk scores did not confound the effect of GPSEDU on cognitive outcomes. GPSEDU explains a small fraction of cognitive performance in adults with psychiatric disorders, specifically for domains related to linguistic learning and working memory. Investigating such a proxy-phenotype longitudinally, could give intriguing insight into the disease course, highlighting at what time genes play a more influential role on cognitive performance. Better understanding the origin of these deficits might help identify those patients at risk for lower levels of functioning and poor social outcomes. Polygenic estimates may in the future be part of predictive models for more personalized interventions.
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Affiliation(s)
- Ashley L Comes
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany.
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, 80804, Germany.
| | - Fanny Senner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Kristina Adorjan
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Heike Anderson-Schmidt
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, 37075, Germany
| | - Till F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, 81675, Germany
| | - Katrin Gade
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, 37075, Germany
| | - Maria Hake
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Janos L Kalman
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, 80804, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Daniela Reich-Erkelenz
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Farah Klöhn-Saghatolislam
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Sabrina K Schaupp
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Eva C Schulte
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Georg Juckel
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, 44791, Germany
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, 48149, Germany
| | - Max Schmauß
- Department of Psychiatry and Psychotherapy, Bezirkskrankenhaus Augsburg, Augsburg, 86156, Germany
| | - Jörg Zimmermann
- Psychiatrieverbund Oldenburger Land gGmbH, Karl-Jaspers-Klinik, Bad Zwischenahn, 26160, Germany
| | - Jens Reimer
- Department of Psychiatry and Psychotherapy, University Medical Centre Hamburg-Eppendorf, Martinistr. 52, Hamburg, 20246, Germany
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, 8036, Austria
| | | | - Volker Arolt
- Department of Psychiatry, University of Münster, Münster, 48149, Germany
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, 48149, Germany
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Carsten Konrad
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg, 27356, Germany
| | - Andreas Thiel
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg, 27356, Germany
| | - Andreas J Fallgatter
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, 72076, Germany
| | - Vanessa Nieratschker
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, 72076, Germany
| | - Christian Figge
- Karl-Jaspers Clinic, European Medical School Oldenburg-Groningen, Oldenburg, 26160, Germany
| | - Martin von Hagen
- Clinic for Psychiatry and Psychotherapy, Clinical Center Werra-Meißner, Eschwege, 37269, Germany
| | - Manfred Koller
- Asklepios Specialized Hospital, Göttingen, 37081, Germany
| | - Thomas Becker
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, 89312, Germany
| | - Moritz E Wigand
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, 89312, Germany
| | - Markus Jäger
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, 89312, Germany
| | - Detlef E Dietrich
- AMEOS Clinical Center Hildesheim, Hildesheim, 31135, Germany
- Center für Systems Neuroscience (ZSN) Hannover, Hannover, 30559, Germany
- Dept. of Psychiatry, Medical School of Hannover, Hannover, 30625, Germany
| | | | - Harald Scherk
- AMEOS Clinical Center Osnabrück, Osnabrück, 49088, Germany
| | - Carsten Spitzer
- ASKLEPIOS Specialized Hospital Tiefenbrunn, Rosdorf, 37124, Germany
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, 18051, Germany
| | - Here Folkerts
- Department of Psychiatry, Psychotherapy and Psychosomatics, Clinical Center Wilhelmshaven, Wilhelmshaven, 26389, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68159, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, 53127, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, 53127, Germany
- Center for Human Genetics, University of Marburg, Marburg, 35033, Germany
- Department of Biomedicine, University of Basel, Basel, 4031, Switzerland
- Department of Psychiatry (UPK), University of Basel, Basel, 4002, Switzerland
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68159, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, 53127, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, 37075, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, 37075, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, 3810-193, Portugal
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
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354
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Pacheco A, Berger R, Freedman R, Law AJ. A VNTR Regulates miR-137 Expression Through Novel Alternative Splicing and Contributes to Risk for Schizophrenia. Sci Rep 2019; 9:11793. [PMID: 31409837 PMCID: PMC6692358 DOI: 10.1038/s41598-019-48141-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Accepted: 07/29/2019] [Indexed: 12/12/2022] Open
Abstract
The MIR137HG gene encoding microRNA-137 (miR-137) is genome-wide associated with schizophrenia (SZ), however, the underlying molecular mechanisms remain unknown. Through cloning and sequencing of individual transcripts from fetal and adult human brain tissues we describe novel pri-miR-137 splice variants which exclude the mature miR-137 sequence termed ‘del-miR-137’ that would function to down-regulate miR-137 expression. Sequencing results demonstrate a significant positive association between del-miR-137 transcripts and the length of a proximal variable number tandem repeat (VNTR) element. Additionally, a significantly higher proportion of sequenced transcripts from fetal brain were del-miR-137 transcripts indicating neurodevelopmental splicing regulation. In-silico results predict an independent regulatory function for del-miR-137 transcripts through competitive endogenous RNA function. A case-control haplotype analysis (n = 998) in SZ implicates short VNTR length in risk, with longer lengths imparting a protective effect. Rare high risk haplotypes were also observed indicating multiple risk variants within the region. A second haplotype analysis was performed to evaluate recombination effects excluding the VNTR and results indicate that recombination of the region was found to independently contribute to risk. Evaluation of the evolutionary conservation of the VNTR reveals a human lineage specific expansion. These findings shed further light on the risk architecture of the miR-137 region and provide a novel regulatory mechanism through VNTR length and alternative MIR137HG transcripts which contribute to risk for SZ.
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Affiliation(s)
- Ashley Pacheco
- University of Colorado, School of Medicine, Department of Psychiatry, Aurora, CO, 80045, USA
| | - Ralph Berger
- University of Colorado, School of Medicine, Department of Psychiatry, Aurora, CO, 80045, USA
| | - Robert Freedman
- University of Colorado, School of Medicine, Department of Psychiatry, Aurora, CO, 80045, USA
| | - Amanda J Law
- University of Colorado, School of Medicine, Department of Psychiatry, Aurora, CO, 80045, USA. .,University of Colorado, School of Medicine, Department of Medicine, Aurora, CO, 80045, USA. .,University of Colorado, School of Medicine, Department of Cell and Developmental Biology, Aurora, CO, 80045, USA.
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355
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Gardiner SL, Trompet S, Sabayan B, Boogaard MW, Jukema JW, Slagboom PE, Roos RAC, van der Grond J, Aziz NA. Repeat variations in polyglutamine disease-associated genes and cognitive function in old age. Neurobiol Aging 2019; 84:236.e17-236.e28. [PMID: 31522753 DOI: 10.1016/j.neurobiolaging.2019.08.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 08/03/2019] [Accepted: 08/04/2019] [Indexed: 02/03/2023]
Abstract
Although the heritability of cognitive function in old age is substantial, genome-wide association studies have had limited success in elucidating its genetic basis, leaving a considerable amount of "missing heritability." Aside from single nucleotide polymorphisms, genome-wide association studies are unable to assess other large sources of genetic variation, such as tandem repeat polymorphisms. Therefore, here, we studied the association of cytosine-adenine-guanine (CAG) repeat variations in polyglutamine disease-associated genes (PDAGs) with cognitive function in older adults. In a large cohort consisting of 5786 participants, we found that the CAG repeat number in 3 PDAGs (TBP, HTT, and AR) were significantly associated with the decline in cognitive function, which together accounted for 0.49% of the variation. Furthermore, in an magnetic resonance imaging substudy, we found that CAG repeat polymorphisms in 4 PDAGs (ATXN2, CACNA1A, ATXN7, and AR) were associated with different imaging characteristics, including brain stem, putamen, globus pallidus, thalamus, and amygdala volumes. Our findings indicate that tandem repeat polymorphisms are associated with cognitive function in older adults and highlight the importance of PDAGs in elucidating its missing heritability.
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Affiliation(s)
- Sarah L Gardiner
- Department of Neurology, Leiden University Medical Centre, Leiden, the Netherlands; Department of Human Genetics, Leiden University Medical Centre, Leiden, the Netherlands.
| | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Centre, Leiden, the Netherlands
| | - Behnam Sabayan
- The Ken and Ruth Davee Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Merel W Boogaard
- Department of Clinical Genetics, Leiden University Medical Centre, Leiden, the Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands
| | - P Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Raymund A C Roos
- Department of Neurology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Jeroen van der Grond
- Department of Radiology, Leiden University Medical Centre, Leiden, the Netherlands
| | - N Ahmad Aziz
- Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany; Department of Neurology, University of Bonn, Bonn, Germany
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356
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Ghanbari M, Munshi ST, Ma B, Lendemeijer B, Bansal S, Adams HH, Wang W, Goth K, Slump DE, den Hout MC, IJcken WF, Bellusci S, Pan Q, Erkeland SJ, Vrij FM, Kushner SA, Ikram MA. A functional variant in the miR‐142 promoter modulating its expression and conferring risk of Alzheimer disease. Hum Mutat 2019; 40:2131-2145. [DOI: 10.1002/humu.23872] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 06/13/2019] [Accepted: 07/11/2019] [Indexed: 12/16/2022]
Affiliation(s)
- Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
- Department of Genetics, School of Medicine Mashhad University of Medical Sciences Mashhad Iran
| | - Shashini T. Munshi
- Department of Psychiatry, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Buyun Ma
- Department of Gastroenterology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Bas Lendemeijer
- Department of Psychiatry, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Sakshi Bansal
- Department of Psychiatry, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Hieab H. Adams
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
- Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Wenshi Wang
- Department of Gastroenterology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Kerstin Goth
- Department of Lung Matrix Remodeling, Excellence Cluster Cardio‐Pulmonary System (ECCPS) University Justus Liebig Giessen Giessen Germany
| | - Denise E. Slump
- Department of Psychiatry, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Mirjam C.G.N. den Hout
- Center for Biomics, Department of Cell Biology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Wilfred F.J. IJcken
- Center for Biomics, Department of Cell Biology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Saverio Bellusci
- Department of Lung Matrix Remodeling, Excellence Cluster Cardio‐Pulmonary System (ECCPS) University Justus Liebig Giessen Giessen Germany
| | - Qiuwei Pan
- Department of Gastroenterology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Stefan J. Erkeland
- Department of Immunology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Femke M.S. Vrij
- Department of Psychiatry, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - Steven A. Kushner
- Department of Psychiatry, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam Rotterdam the Netherlands
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357
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Lam M, Hill WD, Trampush JW, Yu J, Knowles E, Davies G, Stahl E, Huckins L, Liewald DC, Djurovic S, Melle I, Sundet K, Christoforou A, Reinvang I, DeRosse P, Lundervold AJ, Steen VM, Espeseth T, Räikkönen K, Widen E, Palotie A, Eriksson JG, Giegling I, Konte B, Hartmann AM, Roussos P, Giakoumaki S, Burdick KE, Payton A, Ollier W, Chiba-Falek O, Attix DK, Need AC, Cirulli ET, Voineskos AN, Stefanis NC, Avramopoulos D, Hatzimanolis A, Arking DE, Smyrnis N, Bilder RM, Freimer NA, Cannon TD, London E, Poldrack RA, Sabb FW, Congdon E, Conley ED, Scult MA, Dickinson D, Straub RE, Donohoe G, Morris D, Corvin A, Gill M, Hariri AR, Weinberger DR, Pendleton N, Bitsios P, Rujescu D, Lahti J, Le Hellard S, Keller MC, Andreassen OA, Deary IJ, Glahn DC, Malhotra AK, Lencz T. Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways. Am J Hum Genet 2019; 105:334-350. [PMID: 31374203 PMCID: PMC6699140 DOI: 10.1016/j.ajhg.2019.06.012] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 06/12/2019] [Indexed: 12/12/2022] Open
Abstract
Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.
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Affiliation(s)
- Max Lam
- Institute of Mental Health, Singapore, 539747, Singapore; Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY 11004, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, EH8 9JZ, United Kingdom; Department of Psychology, University of Edinburgh, Edinburgh, Scotland, EH8 9JZ, United Kingdom
| | - Joey W Trampush
- Department of Psychiatry and the Behavioral Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Jin Yu
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY 11004, USA
| | - Emma Knowles
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, EH8 9JZ, United Kingdom; Department of Psychology, University of Edinburgh, Edinburgh, Scotland, EH8 9JZ, United Kingdom
| | - Eli Stahl
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Laura Huckins
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - David C Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, Scotland, EH8 9JZ, United Kingdom
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, University of Bergen, Bergen 4956, Nydalen 0424, Norway; Norsk Senter for Forskning på Mentale Lidelser, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen 4956, Nydalen 0424, Norway
| | - Ingrid Melle
- Norsk Senter for Forskning på Mentale Lidelser, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen 4956, Nydalen 0424, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo 1039, Blindern 0315, Norway
| | - Kjetil Sundet
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo 1039, Blindern 0315, Norway; Department of Psychology, University of Oslo, Oslo 1094, Blindern 0317, Norway
| | - Andrea Christoforou
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen 7804, N-5020 Bergen, Norway
| | - Ivar Reinvang
- Department of Psychology, University of Oslo, Oslo 1094, Blindern 0317, Norway
| | - Pamela DeRosse
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY 11004, USA
| | - Astri J Lundervold
- Department of Biological and Medical Psychology, University of Bergen, 7807, N-5020, Norway
| | - Vidar M Steen
- Norsk Senter for Forskning på Mentale Lidelser, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen 4956, Nydalen 0424, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen 7804, N-5020 Bergen, Norway
| | - Thomas Espeseth
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo 1039, Blindern 0315, Norway; Department of Psychology, University of Oslo, Oslo 1094, Blindern 0317, Norway
| | - Katri Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, 00014, Finland
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, 00014, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, 00014, Finland; Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SA, United Kingdom; Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, 00014, Finland
| | - Johan G Eriksson
- Department of General Practice, University of Helsinki and Helsinki University Hospital, Helsinki, 00014, Finland; National Institute for Health and Welfare, Helsinki FI-00271, Finland; Folkhälsan Research Center, Helsinki 00290, Finland
| | - Ina Giegling
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle 06108, Germany
| | - Bettina Konte
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle 06108, Germany
| | - Annette M Hartmann
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle 06108, Germany
| | - Panos Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Institute for Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mental Illness Research, Education, and Clinical Center (VISN 2), James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | | | - Katherine E Burdick
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Mental Illness Research, Education, and Clinical Center (VISN 2), James J. Peters VA Medical Center, Bronx, NY 10468, USA; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115
| | - Antony Payton
- Division of Informatics, Imaging, and Data Sciences, School of Health Sciences, University of Manchester, Manchester M139NT, United Kingdom
| | - William Ollier
- Centre for Epidemiology, Division of Population Health, Health Services Research and Primary Care, University of Manchester, Manchester M139PL, United Kingdom; School of Healthcare Sciences, Manchester Metropolitan University, Manchester M15 6BH, United Kingdom
| | - Ornit Chiba-Falek
- Department of Neurology, Bryan Alzheimer Disease Research Center, Duke University Medical Center, Durham, NC 27705, USA; Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27705, USA
| | - Deborah K Attix
- Department of Neurology, Bryan Alzheimer Disease Research Center, Duke University Medical Center, Durham, NC 27705, USA; Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27705, USA; Psychiatry and Behavioral Sciences, Division of Medical Psychology, Duke University Medical Center, Durham, NC 27708, USA; Department of Neurology, Duke University Medical Center, Durham, NC 27708, USA
| | - Anna C Need
- Division of Brain Sciences, Department of Medicine, Imperial College, London W12 0NN, UK
| | | | - Aristotle N Voineskos
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto M6J 1H4, Canada
| | - Nikos C Stefanis
- Department of Psychiatry, National and Kapodistrian University of Athens Medical School, Eginition Hospital, Athens, Greece; University Mental Health Research Institute, Athens 115 27, Greece; Neurobiology Research Institute, Theodor-Theohari Cozzika Foundation, Athens, Greece
| | - Dimitrios Avramopoulos
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA; McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Alex Hatzimanolis
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto M6J 1H4, Canada; Department of Psychiatry, National and Kapodistrian University of Athens Medical School, Eginition Hospital, Athens, Greece; University Mental Health Research Institute, Athens 115 27, Greece
| | - Dan E Arking
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Nikolaos Smyrnis
- Campbell Family Mental Health Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto M6J 1H4, Canada; Department of Psychiatry, National and Kapodistrian University of Athens Medical School, Eginition Hospital, Athens, Greece
| | - Robert M Bilder
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Nelson A Freimer
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, CT 06511, USA
| | - Edythe London
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA 90024, USA
| | | | - Fred W Sabb
- Robert and Beverly Lewis Center for Neuroimaging, University of Oregon, Eugene, OR, 97401, USA
| | - Eliza Congdon
- UCLA Semel Institute for Neuroscience and Human Behavior, Los Angeles, CA 90024, USA
| | | | - Matthew A Scult
- Laboratory of NeuroGenetics, Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Dwight Dickinson
- Clinical and Translational Neuroscience Branch, Intramural Research Program, National Institute of Mental Health, National Institute of Health, Bethesda, MD 20814, USA
| | - Richard E Straub
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD 21205, USA
| | - Gary Donohoe
- Neuroimaging, Cognition, and Genomics Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland, Galway, Ireland
| | - Derek Morris
- Neuroimaging, Cognition, and Genomics Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland, Galway, Ireland
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland; Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland; Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Ahmad R Hariri
- Laboratory of NeuroGenetics, Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD 21205, USA
| | - Neil Pendleton
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, University of Manchester, Manchester Academic Health Science Centre, Salford Royal NHS Foundation Trust, Manchester M13 9PL, United Kingdom
| | - Panos Bitsios
- Department of Psychiatry and Behavioral Sciences, Faculty of Medicine, University of Crete, Heraklion, Crete GR-71003, Greece
| | - Dan Rujescu
- Department of Psychiatry, Martin Luther University of Halle-Wittenberg, Halle 06108, Germany
| | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, 00014, Finland; Helsinki Collegium for Advanced Studies, University of Helsinki, Helsinki 00014, Finland
| | - Stephanie Le Hellard
- Norsk Senter for Forskning på Mentale Lidelser, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen 4956, Nydalen 0424, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen 7804, N-5020 Bergen, Norway
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado, Boulder, CO 80303, USA
| | - Ole A Andreassen
- Norsk Senter for Forskning på Mentale Lidelser, K.G. Jebsen Centre for Psychosis Research, University of Bergen, Bergen 4956, Nydalen 0424, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo 1039, Blindern 0315, Norway; Institute of Clinical Medicine, University of Oslo, Oslo 0318, Norway
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, EH8 9JZ, United Kingdom; Department of Psychology, University of Edinburgh, Edinburgh, Scotland, EH8 9JZ, United Kingdom
| | - David C Glahn
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Anil K Malhotra
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY 11004, USA; Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY 11030, USA
| | - Todd Lencz
- Division of Psychiatry Research, The Zucker Hillside Hospital, Glen Oaks, NY 11004, USA; Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA; Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY 11030, USA.
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358
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Li H, Chang H, Song X, Liu W, Li L, Wang L, Yang Y, Zhang L, Li W, Zhang Y, Zhou DS, Li X, Zhang C, Fang Y, Sun Y, Dai JP, Luo XJ, Yao YG, Xiao X, Lv L, Li M. Integrative analyses of major histocompatibility complex loci in the genome-wide association studies of major depressive disorder. Neuropsychopharmacology 2019; 44:1552-1561. [PMID: 30771788 PMCID: PMC6785001 DOI: 10.1038/s41386-019-0346-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2018] [Revised: 02/01/2019] [Accepted: 02/12/2019] [Indexed: 11/09/2022]
Abstract
Recent European genome-wide association studies (GWAS) have revealed strong statistical correlations between MDD and numerous zero-to-high linked variants in the genomic region containing major histocompatibility complex (MHC) genes (MHC region), but the underlying biological mechanisms are still unclear. To better understand the roles of this genomic region in the neurobiology of MDD, we applied a convergent functional genomics approach to integrate GWAS data of MDD relevant biological phenotypes, gene-expression analyses results obtained from brain samples, and genetic analyses of independent Chinese MDD samples. We observed that independent MDD risk variants in the MHC region were also significantly associated with the relevant biological phenotypes in the predicted directions, including the emotional and cognitive-related phenotypes. Gene-expression analyses further revealed that mRNA expression levels of several MHC region genes in the human brain were associated with MDD risk SNPs and diagnostic status. For instance, a brain-enriched gene ZNF603P consistently showed lower mRNA levels in the individuals carrying MDD risk alleles and in MDD patients. Remarkably, we further found that independent MDD risk SNPs in the MHC region likely converged to affect the mRNA level(s) of the same gene(s), and Europeans and Han Chinese populations have a substantial shared genetic and molecular basis underlying MDD risk associations in the MHC region. These results highlighted several potential pivotal genes at the MHC region in the pathogenesis of MDD. Their common impacts on multiple psychiatric relevant phenotypes also implicated the neurological processes shared by different psychological processes, such as mood and/or cognition, shedding lights on their potential biological mechanisms.
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Affiliation(s)
- Huijuan Li
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China
| | - Hong Chang
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China
| | - Xueqin Song
- grid.412633.1The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan China
| | - Weipeng Liu
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China
| | - Lingyi Li
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China
| | - Lu Wang
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China
| | - Yongfeng Yang
- 0000 0004 1808 322Xgrid.412990.7Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan China
| | - Luwen Zhang
- 0000 0004 1808 322Xgrid.412990.7Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan China
| | - Wenqiang Li
- 0000 0004 1808 322Xgrid.412990.7Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan China
| | - Yan Zhang
- 0000 0004 1808 322Xgrid.412990.7Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan China
| | - Dong-Sheng Zhou
- 0000 0004 1782 599Xgrid.452715.0Department of Psychiatry, Ningbo Kangning Hospital, Ningbo, Zhejiang China
| | - Xingxing Li
- 0000 0004 1782 599Xgrid.452715.0Department of Psychiatry, Ningbo Kangning Hospital, Ningbo, Zhejiang China
| | - Chen Zhang
- 0000 0004 0368 8293grid.16821.3cShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiru Fang
- 0000 0004 0368 8293grid.16821.3cShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Sun
- 0000 0000 9147 9053grid.412692.aWuhan Institute for Neuroscience and Neuroengineering, South-Central University for Nationalities, Wuhan, Hubei China ,Chinese Brain Bank Center, Wuhan, Hubei China
| | - Jia-Pei Dai
- 0000 0000 9147 9053grid.412692.aWuhan Institute for Neuroscience and Neuroengineering, South-Central University for Nationalities, Wuhan, Hubei China ,Chinese Brain Bank Center, Wuhan, Hubei China
| | - Xiong-Jian Luo
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China ,0000000119573309grid.9227.eCenter for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan China
| | - Yong-Gang Yao
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China ,0000000119573309grid.9227.eCAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China. .,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, Henan, China. .,Henan Province People's Hospital, Zhengzhou, Henan, China.
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China. .,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China. .,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.
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359
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Bueno D. Genetics and Learning: How the Genes Influence Educational Attainment. Front Psychol 2019; 10:1622. [PMID: 31354597 PMCID: PMC6635910 DOI: 10.3389/fpsyg.2019.01622] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 06/27/2019] [Indexed: 11/24/2022] Open
Abstract
The brain is the organ of thought. The word thought is defined as the act of thinking about or considering something: an idea or opinion, or a set of ideas about a particular subject. It implicitly includes the processes of learning. Mental functions, including most if not all aspects of human behavior, such as those related to learning, arise from the activity of the brain. Neural connections that generate and support mental functions are formed throughout life, which enables lifelong learning of new concepts and skills. Both brain formation and function, as well as neural plasticity, are influenced by the activity of a variety of genes and also by epigenetic modifications, which contribute to the regulation of gene expression by adapting it to environmental conditions. In this review, aimed especially at education professionals, I discuss the genetic and epigenetic contributions to mental aspects related to learning processes in terms of heritability. I will argue that, despite most if not all aspects related to learning having a clear genetic background, innate abilities can be enhanced or diminished through educational processes. Thus, the importance of education, in the context of the inheritability of learning processes, will be discussed. The conclusion I draw is that, despite the relatively high genetic heritability shown in most brain processes associated with learning, educational practices are a key contributor to student development, allowing genetically based skills to be enhanced or alternatively diminished. Therefore one of the main goals of education in a changing an uncertain world should be to form adaptable and versatile people who can, and want to, make the most of their capabilities. Thus, knowledge derived from genetics and epigenetics, as well as from neuroscience, should be used to enhance education professionals’ understanding of the biological origins of differences in mental capabilities, thereby empowering them with the possibility to adopt more respectful and flexible educational practices to attain the goal mentioned above.
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Affiliation(s)
- David Bueno
- Biomedical, Evolutionary, and Developmental Genetics Section, Faculty of Biology, University of Barcelona, Barcelona, Spain
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360
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Edwards R, Campbell A, Porteous D. Generation Scotland participant survey on data collection. Wellcome Open Res 2019. [DOI: 10.12688/wellcomeopenres.15354.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Background: Generation Scotland (GS) is a population and family-based study of genetic and environmental health determinants. Recruitment to the Scottish Family Health Study component of GS took place between 2006-2011. Participants were aged 18 or over and consented to genetic studies, linkage to health records and recontact. Several recontact exercises have been successfully conducted aimed at a) recruitment to embedded or partner studies and b) the collection of additional data. As the cohort matures in age, we were interested in surveying attitudes to potential new approaches to data collection and recruitment. Methods: A ten-question online survey was sent to those participants who provided an email address. Results: We report a high level of positive responses to encouraging relatives to participate, to remote data and sample collection and for research access to stored newborn dried blood spots. Conclusions: The majority of current and prospective GS participants are likely to respond positively to future requests for remote data and sample collection.
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361
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Martin AR, Daly MJ, Robinson EB, Hyman SE, Neale BM. Predicting Polygenic Risk of Psychiatric Disorders. Biol Psychiatry 2019; 86:97-109. [PMID: 30737014 PMCID: PMC6599546 DOI: 10.1016/j.biopsych.2018.12.015] [Citation(s) in RCA: 142] [Impact Index Per Article: 28.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Revised: 11/18/2018] [Accepted: 12/08/2018] [Indexed: 12/27/2022]
Abstract
Genetics provides two major opportunities for understanding human disease-as a transformative line of etiological inquiry and as a biomarker for heritable diseases. In psychiatry, biomarkers are very much needed for both research and treatment, given the heterogenous populations identified by current phenomenologically based diagnostic systems. To date, however, useful and valid biomarkers have been scant owing to the inaccessibility and complexity of human brain tissue and consequent lack of insight into disease mechanisms. Genetic biomarkers are therefore especially promising for psychiatric disorders. Genome-wide association studies of common diseases have matured over the last decade, generating the knowledge base for increasingly informative individual-level genetic risk prediction. In this review, we discuss fundamental concepts involved in computing genetic risk with current methods, strengths and weaknesses of various approaches, assessments of utility, and applications to various psychiatric disorders and related traits. Although genetic risk prediction has become increasingly straightforward to apply and common in published studies, there are important pitfalls to avoid. At present, the clinical utility of genetic risk prediction is still low; however, there is significant promise for future clinical applications as the ancestral diversity and sample sizes of genome-wide association studies increase. We discuss emerging data and methods aimed at improving the value of genetic risk prediction for disentangling disease mechanisms and stratifying subjects for epidemiological and clinical studies. For all applications, it is absolutely critical that polygenic risk prediction is applied with appropriate methodology and control for confounding to avoid repeating some mistakes of the candidate gene era.
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Affiliation(s)
- Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts.
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
| | - Elise B Robinson
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Steven E Hyman
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts
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362
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Mendizabal I, Berto S, Usui N, Toriumi K, Chatterjee P, Douglas C, Huh I, Jeong H, Layman T, Tamminga CA, Preuss TM, Konopka G, Yi SV. Cell type-specific epigenetic links to schizophrenia risk in the brain. Genome Biol 2019; 20:135. [PMID: 31288836 PMCID: PMC6617737 DOI: 10.1186/s13059-019-1747-7] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 06/25/2019] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND The importance of cell type-specific epigenetic variation of non-coding regions in neuropsychiatric disorders is increasingly appreciated, yet data from disease brains are conspicuously lacking. We generate cell type-specific whole-genome methylomes (N = 95) and transcriptomes (N = 89) from neurons and oligodendrocytes obtained from brain tissue of patients with schizophrenia and matched controls. RESULTS The methylomes of the two cell types are highly distinct, with the majority of differential DNA methylation occurring in non-coding regions. DNA methylation differences between cases and controls are subtle compared to cell type differences, yet robust against permuted data and validated in targeted deep-sequencing analyses. Differential DNA methylation between control and schizophrenia tends to occur in cell type differentially methylated sites, highlighting the significance of cell type-specific epigenetic dysregulation in a complex neuropsychiatric disorder. CONCLUSIONS Our results provide novel and comprehensive methylome and transcriptome data from distinct cell populations within patient-derived brain tissues. This data clearly demonstrate that cell type epigenetic-differentiated sites are preferentially targeted by disease-associated epigenetic dysregulation. We further show reduced cell type epigenetic distinction in schizophrenia.
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Affiliation(s)
- Isabel Mendizabal
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Stefano Berto
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Noriyoshi Usui
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA
- Center for Medical Research and Education, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan
- Department of Neuroscience and Cell Biology, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan
| | - Kazuya Toriumi
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA
- Schizophrenia Research Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, 156-8506, Japan
| | - Paramita Chatterjee
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Connor Douglas
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Iksoo Huh
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA
- College of Nursing, The Research Institute of Nursing Science, Seoul National University, Seoul, 03080, South Korea
| | - Hyeonsoo Jeong
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Thomas Layman
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Carol A Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Todd M Preuss
- Division of Neuropharmacology and Neurologic Diseases, Department of Pathology, Yerkes National Primate Research Center, Emory University School of Medicine, Emory University, Atlanta, GA, 30329, USA
| | - Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, 75390, USA.
| | - Soojin V Yi
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
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363
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Malykh SB, Malykh AS, Karunas AS, Enikeeva RF, Davydova YD, Khusnutdinova EK. Molecular Genetic Studies of Cognitive Ability. RUSS J GENET+ 2019. [DOI: 10.1134/s1022795419070111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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364
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Genetic Contributions to Health Literacy. Twin Res Hum Genet 2019; 22:131-139. [PMID: 31250787 DOI: 10.1017/thg.2019.28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Higher health literacy is associated with higher cognitive function and better health. Despite its wide use in medical research, no study has investigated the genetic contributions to health literacy. Using 5783 English Longitudinal Study of Ageing (ELSA) participants (mean age = 65.49, SD = 9.55) who had genotyping data and had completed a health literacy test at wave 2 (2004-2005), we carried out a genome-wide association study (GWAS) of health literacy. We estimated the proportion of variance in health literacy explained by all common single nucleotide polymorphisms (SNPs). Polygenic profile scores were calculated using summary statistics from GWAS of 21 cognitive and health measures. Logistic regression was used to test whether polygenic scores for cognitive and health-related traits were associated with having adequate, compared to limited, health literacy. No SNPs achieved genome-wide significance for association with health literacy. The proportion of variance in health literacy accounted for by common SNPs was 8.5% (SE = 7.2%). Greater odds of having adequate health literacy were associated with a 1 standard deviation higher polygenic score for general cognitive ability [OR = 1.34, 95% CI (1.26, 1.42)], verbal-numerical reasoning [OR = 1.30, 95% CI (1.23, 1.39)], and years of schooling [OR = 1.29, 95% CI (1.21, 1.36)]. Reduced odds of having adequate health literacy were associated with higher polygenic profiles for poorer self-rated health [OR = 0.92, 95% CI (0.87, 0.98)] and schizophrenia [OR = 0.91, 95% CI (0.85, 0.96)). The well-documented associations between health literacy, cognitive function and health may partly be due to shared genetic etiology. Larger studies are required to obtain accurate estimates of SNP-based heritability and to discover specific health literacy-associated genetic variants.
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365
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Ganeff IMM, Bos MM, van Heemst D, Noordam R. BMI-associated gene variants in FTO and cardiometabolic and brain disease: obesity or pleiotropy? Physiol Genomics 2019; 51:311-322. [PMID: 31199196 DOI: 10.1152/physiolgenomics.00040.2019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Obesity is a causal risk factor for the development of age-related disease conditions, which includes Type 2 diabetes mellitus, cardiovascular disease, and dementia. In genome-wide association studies, genetic variation in FTO is strongly associated with obesity and has been described across different ethnic backgrounds and life stages. To date, much work has been devoted on determining the biological mechanisms via which FTO affects body weight regulation and ultimately contributes to age-related cardiometabolic and brain disease. The main hypotheses of the involved biological mechanisms include the involvement of FTO in habitual food intake and energy expenditure. In this narrative review, our overall aim is to provide an overview on how FTO gene variants could increase the risk of developing age-related disease conditions. Specifically, we will discuss the state of the literature based on the different hypotheses how FTO regulates body weight and ultimately contributes to cardiometabolic disease and brain disease.
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Affiliation(s)
- Ingeborg M M Ganeff
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Maxime M Bos
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands
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366
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Deary IJ, Harris SE, Hill WD. What genome-wide association studies reveal about the association between intelligence and physical health, illness, and mortality. Curr Opin Psychol 2019; 27:6-12. [PMID: 30071465 PMCID: PMC6624475 DOI: 10.1016/j.copsyc.2018.07.005] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 07/17/2018] [Indexed: 01/02/2023]
Abstract
The associations between higher intelligence test scores from early life and later good health, fewer illnesses, and longer life are recent discoveries. Researchers are mapping the extent of these associations and trying to understanding them. Part of the intelligence-health association has genetic origins. Recent advances in molecular genetic technology and statistical analyses have revealed that: intelligence and many health outcomes are highly polygenic; and that modest but widespread genetic correlations exist between intelligence and health, illness and mortality. Causal accounts of intelligence-health associations are still poorly understood. The contribution of education and socio-economic status - both of which are partly genetic in origin - to the intelligence-health associations are being explored.
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Affiliation(s)
- Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, United Kingdom.
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, United Kingdom; Medical Genetics Section, Centre for Genomic & Experimental Medicine, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, United Kingdom
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367
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Younis RM, Taylor RM, Beardsley PM, McClay JL. The ANKS1B gene and its associated phenotypes: focus on CNS drug response. Pharmacogenomics 2019; 20:669-684. [PMID: 31250731 PMCID: PMC6912848 DOI: 10.2217/pgs-2019-0015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Accepted: 04/26/2019] [Indexed: 12/21/2022] Open
Abstract
The ANKS1B gene was a top finding in genome-wide association studies (GWAS) of antipsychotic drug response. Subsequent GWAS findings for ANKS1B include cognitive ability, educational attainment, body mass index, response to corticosteroids and drug dependence. We review current human association evidence for ANKS1B, in addition to functional studies that include two published mouse knockouts. The several GWAS findings in humans indicate that phenotypically relevant variation is segregating at the ANKS1B locus. ANKS1B shows strong plausibility for involvement in CNS drug response because it encodes a postsynaptic effector protein that mediates long-term changes to neuronal biology. Forthcoming data from large biobanks should further delineate the role of ANKS1B in CNS drug response.
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Affiliation(s)
- Rabha M Younis
- Department of Pharmacotherapy & Outcomes Science, Virginia Commonwealth University School of Pharmacy, Richmond, VA 23298, USA
| | - Rachel M Taylor
- Center for Military Psychiatry & Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MA 20910, USA
| | - Patrick M Beardsley
- Department of Pharmacology & Toxicology, Virginia Commonwealth University School of Medicine, Richmond, VA 23298, USA
- Center for Biomarker Research & Personalized Medicine, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Joseph L McClay
- Department of Pharmacotherapy & Outcomes Science, Virginia Commonwealth University School of Pharmacy, Richmond, VA 23298, USA
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368
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Single-cell transcriptomic analysis of Alzheimer's disease. Nature 2019; 570:332-337. [PMID: 31042697 DOI: 10.1038/s41586-019-1195-2] [Citation(s) in RCA: 1293] [Impact Index Per Article: 258.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 04/24/2019] [Indexed: 12/11/2022]
Abstract
Alzheimer's disease is a pervasive neurodegenerative disorder, the molecular complexity of which remains poorly understood. Here, we analysed 80,660 single-nucleus transcriptomes from the prefrontal cortex of 48 individuals with varying degrees of Alzheimer's disease pathology. Across six major brain cell types, we identified transcriptionally distinct subpopulations, including those associated with pathology and characterized by regulators of myelination, inflammation, and neuron survival. The strongest disease-associated changes appeared early in pathological progression and were highly cell-type specific, whereas genes upregulated at late stages were common across cell types and primarily involved in the global stress response. Notably, we found that female cells were overrepresented in disease-associated subpopulations, and that transcriptional responses were substantially different between sexes in several cell types, including oligodendrocytes. Overall, myelination-related processes were recurrently perturbed in multiple cell types, suggesting that myelination has a key role in Alzheimer's disease pathophysiology. Our single-cell transcriptomic resource provides a blueprint for interrogating the molecular and cellular basis of Alzheimer's disease.
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369
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Cornelis MC, Wang Y, Holland T, Agarwal P, Weintraub S, Morris MC. Age and cognitive decline in the UK Biobank. PLoS One 2019; 14:e0213948. [PMID: 30883587 PMCID: PMC6422276 DOI: 10.1371/journal.pone.0213948] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 03/04/2019] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVES Age-related cognitive decline is a well-known phenomenon after age 65 but little is known about earlier changes and prior studies are based on relatively small samples. We investigated the impact of age on cognitive decline in the largest population sample to date including young to old adults. METHOD Between 100,352 and 468,534 participants aged 38-73 years from UK Biobank completed at least one of seven self-administered cognitive functioning tests: prospective memory (PM), pairs matching (Pairs), fluid intelligence (FI), reaction time (RT), symbol digit substitution, trail making A and B. Up to 26,005 participants completed at least one of two follow-up assessments of PM, Pairs, FI and RT. Multivariable regression models examined the association between age (<45[reference], 45-49, 50-54, 55-59, 60-64, 65+) and cognition scores at baseline. Mixed models estimated the impact of age on cognitive decline over follow-up (~5.1 years). RESULTS FI was higher between ages 50 and 64 and lower at 65+ compared to <45 at baseline. Performance on all other baseline tests was lower with older age: with increasing age category, difference in test scores ranged from 2.5 to 7.8%(P<0.0001). Compared to <45 at baseline, RT and Pairs performance declined faster across all older age cohorts (3.0 and 1.2% change, respectively, with increasing age category, P<0.0001). Cross-sectional results yielded 8 to 12-fold higher differences in RT and Pairs with age compared to longitudinal results. CONCLUSIONS Our findings suggest that declines in cognitive abilities <65 are small. The cross-sectional differences in cognition scores for middle to older adult years may be due in part to age cohort effects.
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Affiliation(s)
- Marilyn C. Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
- * E-mail:
| | - Yamin Wang
- Rush Institute for Healthy Aging, Rush University, Chicago, Illinois, United States of America
| | - Thomas Holland
- Rush Institute for Healthy Aging, Rush University, Chicago, Illinois, United States of America
| | - Puja Agarwal
- Rush Institute for Healthy Aging, Rush University, Chicago, Illinois, United States of America
| | - Sandra Weintraub
- Mesulam Cognitive Neurology and Alzheimer’s Disease Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Martha Clare Morris
- Rush Institute for Healthy Aging, Rush University, Chicago, Illinois, United States of America
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370
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Kamboh MI, Fan KH, Yan Q, Beer JC, Snitz BE, Wang X, Chang CCH, Demirci FY, Feingold E, Ganguli M. Population-based genome-wide association study of cognitive decline in older adults free of dementia: identification of a novel locus for the attention domain. Neurobiol Aging 2019; 84:239.e15-239.e24. [PMID: 30954325 DOI: 10.1016/j.neurobiolaging.2019.02.024] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 01/20/2019] [Accepted: 02/28/2019] [Indexed: 12/27/2022]
Abstract
To identify novel loci that affect cognitive decline in older adults free of dementia, we conducted genome-wide and gene-based meta-analyses on longitudinal slopes of 5 cognitive domains (memory, executive function, language, attention/processing speed, and visuospatial ability) derived from 2 population-based cohorts. For decline over time in each cognitive domain, we normalized intraindividual slopes within each cohort, accounting for baseline age, sex, and years of education. Normalized slope for each domain was used in cohort-specific genome-wide analyses after including top principal components as covariates followed by genome-wide and gene-based meta-analyses. Both analyses revealed a novel WDFY2 locus at genome-wide (p = 3.37E-08) and gene-wide (p = 7.10E-07) significance levels for the attention/processing speed domain. In the GTEx eQTL analysis, genome-wide significant single-nucleotide polymorphism was associated with RNA expression levels of WDFY2 in several brain regions: cerebellar hemisphere (p = 1.07E-04), cerebellum (p = 6.92E-04), hippocampus (p = 2.18E-03) and cortex (p = 2.29E-02), and in whole blood (p = 4.41E-05). Our results suggest that WDFY2 genetic variation may affect individual differences in decline over time on tests of attention/processing speed.
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Affiliation(s)
- M Ilyas Kamboh
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Kang-Hsien Fan
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Qi Yan
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joanne C Beer
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Xingbin Wang
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chung-Chou H Chang
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - F Yesim Demirci
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eleanor Feingold
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mary Ganguli
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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371
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Halahakoon DC, Lewis G, Roiser JP. Cognitive Impairment and Depression-Cause, Consequence, or Coincidence? JAMA Psychiatry 2019; 76:239-240. [PMID: 30586143 DOI: 10.1001/jamapsychiatry.2018.3631] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- D Chamith Halahakoon
- Institute of Cognitive Neuroscience, University College London, London, England, United Kingdom
| | - Glyn Lewis
- Division of Psychiatry, University College London, London, England, United Kingdom
| | - Jonathan P Roiser
- Institute of Cognitive Neuroscience, University College London, London, England, United Kingdom
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372
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Perneczky R, Kempermann G, Korczyn AD, Matthews FE, Ikram MA, Scarmeas N, Chetelat G, Stern Y, Ewers M. Translational research on reserve against neurodegenerative disease: consensus report of the International Conference on Cognitive Reserve in the Dementias and the Alzheimer's Association Reserve, Resilience and Protective Factors Professional Interest Area working groups. BMC Med 2019; 17:47. [PMID: 30808345 PMCID: PMC6391801 DOI: 10.1186/s12916-019-1283-z] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 02/06/2019] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND The concept of reserve was established to account for the observation that a given degree of neurodegenerative pathology may result in varying degrees of symptoms in different individuals. There is a large amount of evidence on epidemiological risk and protective factors for neurodegenerative diseases and dementia, yet the biological mechanisms that underpin the protective effects of certain lifestyle and physiological variables remain poorly understood, limiting the development of more effective preventive and treatment strategies. Additionally, different definitions and concepts of reserve exist, which hampers the coordination of research and comparison of results across studies. DISCUSSION This paper represents the consensus of a multidisciplinary group of experts from different areas of research related to reserve, including clinical, epidemiological and basic sciences. The consensus was developed during meetings of the working groups of the first International Conference on Cognitive Reserve in the Dementias (24-25 November 2017, Munich, Germany) and the Alzheimer's Association Reserve and Resilience Professional Interest Area (25 July 2018, Chicago, USA). The main objective of the present paper is to develop a translational perspective on putative mechanisms underlying reserve against neurodegenerative disease, combining evidence from epidemiological and clinical studies with knowledge from animal and basic research. The potential brain functional and structural basis of reserve in Alzheimer's disease and other brain disorders are discussed, as well as relevant lifestyle and genetic factors assessed in both humans and animal models. CONCLUSION There is an urgent need to advance our concept of reserve from a hypothetical model to a more concrete approach that can be used to improve the development of effective interventions aimed at preventing dementia. Our group recommends agreement on a common dictionary of terms referring to different aspects of reserve, the improvement of opportunities for data sharing across individual cohorts, harmonising research approaches across laboratories and groups to reduce heterogeneity associated with human data, global coordination of clinical trials to more effectively explore whether reducing epidemiological risk factors leads to a reduced burden of neurodegenerative diseases in the population, and an increase in our understanding of the appropriateness of animal models for reserve research.
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Affiliation(s)
- Robert Perneczky
- Division of Mental Health in Older Adults and Alzheimer Therapy and Research Center, Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, 80336, Munich, Germany. .,German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany. .,Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK. .,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
| | - Gerd Kempermann
- German Center for Neurodegenerative Diseases (DZNE) Dresden, Dresden, Germany.,Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden, Dresden, Germany
| | - Amos D Korczyn
- Sackler School of Medicine, Tel- Aviv University, Ramat Aviv, Israel
| | - Fiona E Matthews
- Institute of Health and Society, Newcastle University Institute for Ageing, Newcastle University, Newcastle, UK.,MRC Biostatistics Unit, Cambridge University, Cambridge, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Nikolaos Scarmeas
- Department of Social Medicine, Psychiatry and Neurology, 1st Department of Neurology, Aeginition University Hospital, National and Kapodistrian University of Athens, Athens, Greece.,Cognitive Neuroscience Division, Department of Neurology and The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Gael Chetelat
- Université Normandie, Inserm, Université de Caen-Normandie, Inserm UMR-S U1237, GIP Cyceron, Caen, France
| | - Yaakov Stern
- Cognitive Neuroscience Division, Department of Neurology and The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Michael Ewers
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
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373
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Gurney ME. Genetic Association of Phosphodiesterases With Human Cognitive Performance. Front Mol Neurosci 2019; 12:22. [PMID: 30800055 PMCID: PMC6376954 DOI: 10.3389/fnmol.2019.00022] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 01/21/2019] [Indexed: 01/03/2023] Open
Abstract
Recent, large-scale, genome-wide association studies (GWAS) provide a first view of the genetic fine structure of cognitive performance in healthy individuals. These studies have pooled data from up to 1.1 million subjects based on simple measures of cognitive performance including educational attainment, self-reported math ability, highest math class taken, and pooled, normalized scores from cognitive tests. These studies now allow the genome-wide interrogation of genes and pathways for their potential impact on human cognitive performance. The phosphodiesterase (PDE) enzymes regulate key cyclic nucleotide signaling pathways. Many are expressed in the brain and have been the targets of CNS drug discovery. Genetic variation in PDE1C, PDE4B and PDE4D associates with multiple measures of human cognitive function. The large size of the human PDE4B and PDE4D genes allows genetic fine structure mapping to transcripts encoding dimeric (long) forms of the enzymes. Upstream and downstream effectors of the cAMP pathway modulated by PDE4D [adenylate cyclase 1 (ADCY1), ADCY8, PRKAR1A, CREB1, or CREBBP] did not show genetic association with cognitive performance, however, genetic association was seen with brain derived neurotrophic factor (BDNF), a gene whose expression is modulated by cAMP. Notably absent was genetic association in healthy subjects to targets of CNS drug discovery designed to improve cognition in disease states by the modulation of cholinergic [acetylcholinesterase (ACHE), choline acetyltransferase (CHAT), nicotinic alpha 7 acetylcholine receptor (CHRNA7)], serotonergic (HTR6), histaminergic (HRH3), or glutamatergic (GRM5) pathways. These new data provide a rationale for exploring the therapeutic benefit of selective inhibitors of PDE1C, PDE4B and PDE4D in CNS disorders affecting cognition.
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Affiliation(s)
- Mark E Gurney
- Tetra Discovery Partners, Grand Rapids, MI, United States
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374
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Cera I, Whitton L, Donohoe G, Morris DW, Dechant G, Apostolova G. Genes encoding SATB2-interacting proteins in adult cerebral cortex contribute to human cognitive ability. PLoS Genet 2019; 15:e1007890. [PMID: 30726206 PMCID: PMC6364870 DOI: 10.1371/journal.pgen.1007890] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 12/12/2018] [Indexed: 12/16/2022] Open
Abstract
During CNS development, the nuclear protein SATB2 is expressed in superficial cortical layers and determines projection neuron identity. In the adult CNS, SATB2 is expressed in pyramidal neurons of all cortical layers and is a regulator of synaptic plasticity and long-term memory. Common variation in SATB2 locus confers risk of schizophrenia, whereas rare, de novo structural and single nucleotide variants cause severe intellectual disability and absent or limited speech. To characterize differences in SATB2 molecular function in developing vs adult neocortex, we isolated SATB2 protein interactomes at the two ontogenetic stages and identified multiple novel SATB2 interactors. SATB2 interactomes are highly enriched for proteins that stabilize de novo chromatin loops. The comparison between the neonatal and adult SATB2 protein complexes indicates a developmental shift in SATB2 molecular function, from transcriptional repression towards organization of chromosomal superstructure. Accordingly, gene sets regulated by SATB2 in the neocortex of neonatal and adult mice show limited overlap. Genes encoding SATB2 protein interactors were grouped for gene set analysis of human GWAS data. Common variants associated with human cognitive ability are enriched within the genes encoding adult but not neonatal SATB2 interactors. Our data support a shift in the function of SATB2 in cortex over lifetime and indicate that regulation of spatial chromatin architecture by the SATB2 interactome contributes to cognitive function in the general population.
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Affiliation(s)
- Isabella Cera
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck, Austria
| | - Laura Whitton
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition and Genomics (NICOG) Centre and NCBES Galway Neuroscience Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Gary Donohoe
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition and Genomics (NICOG) Centre and NCBES Galway Neuroscience Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Derek W. Morris
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition and Genomics (NICOG) Centre and NCBES Galway Neuroscience Centre, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland
| | - Georg Dechant
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck, Austria
| | - Galina Apostolova
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck, Austria
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375
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Genome-wide analysis reveals extensive genetic overlap between schizophrenia, bipolar disorder, and intelligence. Mol Psychiatry 2019; 25:844-853. [PMID: 30610197 PMCID: PMC6609490 DOI: 10.1038/s41380-018-0332-x] [Citation(s) in RCA: 117] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 10/18/2018] [Accepted: 11/29/2018] [Indexed: 02/08/2023]
Abstract
Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental disorders associated with cognitive impairment, which is considered a major determinant of functional outcome. Despite this, the etiology of the cognitive impairment is poorly understood, and no satisfactory cognitive treatments exist. Increasing evidence indicates that genetic risk for SCZ may contribute to cognitive impairment, whereas the genetic relationship between BD and cognitive function remains unclear. Here, we combined large genome-wide association study data on SCZ (n = 82,315), BD (n = 51,710), and general intelligence (n = 269,867) to investigate overlap in common genetic variants using conditional false discovery rate (condFDR) analysis. We observed substantial genetic enrichment in both SCZ and BD conditional on associations with intelligence indicating polygenic overlap. Using condFDR analysis, we leveraged this enrichment to increase statistical power and identified 75 distinct genomic loci associated with both SCZ and intelligence, and 12 loci associated with both BD and intelligence at conjunctional FDR < 0.01. Among these loci, 20 are novel for SCZ, and four are novel for BD. Most SCZ risk alleles (61 of 75, 81%) were associated with poorer cognitive performance, whereas most BD risk alleles (9 of 12, 75%) were associated with better cognitive performance. A gene set analysis of the loci shared between SCZ and intelligence implicated biological processes related to neurodevelopment, synaptic integrity, and neurotransmission; the same analysis for BD was underpowered. Altogether, the study demonstrates that both SCZ and BD share genetic influences with intelligence, albeit in a different manner, providing new insights into their genetic architectures.
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376
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Russ TC, Woelbert E, Davis KAS, Hafferty JD, Ibrahim Z, Inkster B, John A, Lee W, Maxwell M, McIntosh AM, Stewart R. How data science can advance mental health research. Nat Hum Behav 2019; 3:24-32. [PMID: 30932051 DOI: 10.1038/s41562-018-0470-9] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 10/11/2018] [Indexed: 02/07/2023]
Abstract
Accessibility of powerful computers and availability of so-called big data from a variety of sources means that data science approaches are becoming pervasive. However, their application in mental health research is often considered to be at an earlier stage than in other areas despite the complexity of mental health and illness making such a sophisticated approach particularly suitable. In this Perspective, we discuss current and potential applications of data science in mental health research using the UK Clinical Research Collaboration classification: underpinning research; aetiology; detection and diagnosis; treatment development; treatment evaluation; disease management; and health services research. We demonstrate that data science is already being widely applied in mental health research, but there is much more to be done now and in the future. The possibilities for data science in mental health research are substantial.
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Affiliation(s)
- Tom C Russ
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh, UK.
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK.
- Old Age Psychiatry, Royal Edinburgh Hospital, NHS Lothian, Edinburgh, UK.
| | | | - Katrina A S Davis
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Jonathan D Hafferty
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Zina Ibrahim
- Department of Biostatistics and Health Informatics, King's College London, London, UK
- The Farr Institute of Health Informatics Research, University College London, London, UK
| | - Becky Inkster
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Ann John
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - William Lee
- Community and Primary Care Research Group, Plymouth University Peninsula Schools of Medicine and Dentistry, University of Plymouth, Plymouth, UK
- Devon Partnership NHS Trust, Exeter, UK
| | | | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Rob Stewart
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, London, UK
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377
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Ohi K, Sumiyoshi C, Fujino H, Yasuda Y, Yamamori H, Fujimoto M, Shiino T, Sumiyoshi T, Hashimoto R. Genetic Overlap between General Cognitive Function and Schizophrenia: A Review of Cognitive GWASs. Int J Mol Sci 2018; 19:E3822. [PMID: 30513630 PMCID: PMC6320986 DOI: 10.3390/ijms19123822] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 11/25/2018] [Accepted: 11/26/2018] [Indexed: 11/17/2022] Open
Abstract
General cognitive (intelligence) function is substantially heritable, and is a major determinant of economic and health-related life outcomes. Cognitive impairments and intelligence decline are core features of schizophrenia which are evident before the onset of the illness. Genetic overlaps between cognitive impairments and the vulnerability for the illness have been suggested. Here, we review the literature on recent large-scale genome-wide association studies (GWASs) of general cognitive function and correlations between cognitive function and genetic susceptibility to schizophrenia. In the last decade, large-scale GWASs (n > 30,000) of general cognitive function and schizophrenia have demonstrated that substantial proportions of the heritability of the cognitive function and schizophrenia are explained by a polygenic component consisting of many common genetic variants with small effects. To date, GWASs have identified more than 100 loci linked to general cognitive function and 108 loci linked to schizophrenia. These genetic variants are mostly intronic or intergenic. Genes identified around these genetic variants are densely expressed in brain tissues. Schizophrenia-related genetic risks are consistently correlated with lower general cognitive function (rg = -0.20) and higher educational attainment (rg = 0.08). Cognitive functions are associated with many of the socioeconomic and health-related outcomes. Current treatment strategies largely fail to improve cognitive impairments of schizophrenia. Therefore, further study is needed to understand the molecular mechanisms underlying both cognition and schizophrenia.
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Affiliation(s)
- Kazutaka Ohi
- Department of Neuropsychiatry, Kanazawa Medical University, Uchinada, Ishikawa 920-0293, Japan.
- Medical Research Institute, Kanazawa Medical University, Ishikawa 920-0293, Japan.
| | - Chika Sumiyoshi
- Faculty of Human Development and Culture, Fukushima University, Fukushima 960-1296, Japan.
| | - Haruo Fujino
- Graduate School of Education, Oita University, Oita 870-1192, Japan.
| | - Yuka Yasuda
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo 187-8553, Japan.
| | - Hidenaga Yamamori
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo 187-8553, Japan.
| | - Michiko Fujimoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan.
| | - Tomoko Shiino
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo 187-8553, Japan.
| | - Tomiki Sumiyoshi
- Department of Preventive Interventions for Psychiatric Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo 187-8553, Japan.
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo 187-8553, Japan.
- Osaka University, Suita, Osaka 565-0871, Japan.
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378
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Scientific Autobiography: On Brain Health and Cognitive Fitness Into the Later Years of Life-Journey of a Behavioral Neurologist of Aging. Am J Geriatr Psychiatry 2018; 26:1184-1189. [PMID: 30170789 DOI: 10.1016/j.jagp.2018.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 07/11/2018] [Indexed: 11/22/2022]
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379
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Reis A, Spinath FM. Genetik der allgemeinen kognitiven Fähigkeit. MED GENET-BERLIN 2018. [DOI: 10.1007/s11825-018-0201-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Zusammenfassung
Intelligenz ist eines der bestuntersuchten Konstrukte der empirischen Verhaltenswissenschaften und stellt eine allgemeine geistige Kapazität dar, die unter anderem die Fähigkeit zum schlussfolgernden Denken, zum Lösen neuartiger Probleme, zum abstrakten Denken sowie zum schnellen Lernen umfasst. Diese kognitiven Fähigkeiten spielen eine große Rolle in der Erklärung und Vorhersage individueller Unterschiede in zentralen Bereichen des gesellschaftlichen Lebens, wie Schul- und Bildungserfolg, Berufserfolg, sozioökonomischer Status und Gesundheitsverhalten. Verhaltensgenetische Studien zeigen konsistent, dass genetische Einflüsse einen substanziellen Beitrag zur Erklärung individueller Unterschiede leisten, die über 60 % der Intelligenzunterschiede im Erwachsenenalter erklären. In den letzten Jahren konnten in großen genomweiten Assoziationsstudien mit häufigen genetischen Varianten Hunderte mit Intelligenz assoziierte Loci identifiziert werden sowie über 1300 assoziierte Gene mit differentieller Expression überwiegend im Gehirn. Mehrere Signalwege waren angereichert, vor allen für Neurogenese, Regulation der Entwicklung des Nervensystems sowie der synaptischen Struktur und Aktivität. Die Mehrzahl der assoziierten Loci betraf regulatorische Regionen und interessanterweise lag die Hälfte intronisch. Von den über 1300 Genen überlappen nur 9,2 % mit solchen, die mit monogenen neurokognitiven Störungen assoziiert sind. Insgesamt bestätigen die Befunde ein polygenes Modell Tausender additiver Faktoren, wobei die einzelnen Loci eine sehr geringe Effektstärke aufweisen. Insgesamt erklären die jetzigen Befunde ca. 10 % der Gesamtvarianz des Merkmals. Diese Ergebnisse sind ein wichtiger Ausgangspunkt für zukünftige Forschung sowohl in der Genetik als auch den Verhaltenswissenschaften.
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Affiliation(s)
- André Reis
- Aff1 0000 0001 2107 3311 grid.5330.5 Humangenetisches Institut, Universitätsklinikum Erlangen Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Schwabachanlage 10 91054 Erlangen Deutschland
| | - Frank M. Spinath
- Aff2 0000 0001 2167 7588 grid.11749.3a Fachbereich Psychologie Universität des Saarlandes Saarbrücken Deutschland
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380
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A Further Comment on 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' by Lam et al. Twin Res Hum Genet 2018; 21:538-545. [PMID: 30293537 PMCID: PMC6390408 DOI: 10.1017/thg.2018.55] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Lam et al. (2018) respond to a commentary of their paper entitled ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ Lam et al. (2017). While Lam et al. (2018) have now provided the recommended quality control metrics for their paper, problems remain. Specifically, Lam et al. (2018) do not dispute that the results of their multi-trait analysis of genome-wide association study (MTAG) analysis has produced a phenotype with a genetic correlation of one with three measures of education, but do claim the associations found are specific to the trait of cognitive ability. In this brief paper, it is empirically demonstrated that the phenotype derived by Lam et al. (2017) is more genetically similar to education than cognitive ability. In addition, it is shown that of the genome-wide significant loci identified by Lam et al. (2017) are loci that are associated with education rather than with cognitive ability.
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381
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Elliott LT, Sharp K, Alfaro-Almagro F, Shi S, Miller KL, Douaud G, Marchini J, Smith SM. Genome-wide association studies of brain imaging phenotypes in UK Biobank. Nature 2018; 562:210-216. [PMID: 30305740 PMCID: PMC6786974 DOI: 10.1038/s41586-018-0571-7] [Citation(s) in RCA: 398] [Impact Index Per Article: 66.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2017] [Accepted: 09/04/2018] [Indexed: 12/16/2022]
Abstract
The genetic architecture of brain structure and function is largely unknown. To investigate this, we carried out genome-wide association studies of 3,144 functional and structural brain imaging phenotypes from UK Biobank (discovery dataset 8,428 subjects). Here we show that many of these phenotypes are heritable. We identify 148 clusters of associations between single nucleotide polymorphisms and imaging phenotypes that replicate at P < 0.05, when we would expect 21 to replicate by chance. Notable significant, interpretable associations include: iron transport and storage genes, related to magnetic susceptibility of subcortical brain tissue; extracellular matrix and epidermal growth factor genes, associated with white matter micro-structure and lesions; genes that regulate mid-line axon development, associated with organization of the pontine crossing tract; and overall 17 genes involved in development, pathway signalling and plasticity. Our results provide insights into the genetic architecture of the brain that are relevant to neurological and psychiatric disorders, brain development and ageing.
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Affiliation(s)
| | - Kevin Sharp
- Department of Statistics, University of Oxford, Oxford, UK
| | - Fidel Alfaro-Almagro
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Sinan Shi
- Department of Statistics, University of Oxford, Oxford, UK
| | - Karla L Miller
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Gwenaëlle Douaud
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Jonathan Marchini
- Department of Statistics, University of Oxford, Oxford, UK.
- The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
| | - Stephen M Smith
- Centre for Functional MRI of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
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382
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Hill WD, Harris SE, Deary IJ. What genome-wide association studies reveal about the association between intelligence and mental health. Curr Opin Psychol 2018; 27:25-30. [PMID: 30110665 DOI: 10.1016/j.copsyc.2018.07.007] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 07/11/2018] [Accepted: 07/18/2018] [Indexed: 12/12/2022]
Abstract
Intelligence, as measured by standardised tests of cognitive function, such as IQ-type tests, is predictive of psychiatric diagnosis and psychological wellbeing. Using genome-wide association study (GWAS) data, a measure of the shared genetic effect across traits, can be quantified; because this can be done across samples, the confounding effects of psychiatric diagnosis do not influence the magnitude of these relationships. It is now known that there are genetic effects that act across intelligence and psychiatric diagnoses, which provide a partial explanation for the phenotypic link between intelligence and mental health. Potential causal effects between intelligence and mental health have been identified, and the regions of the genome responsible for some of these cross trait associations have begun to be characterised.
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Affiliation(s)
- W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK.
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK; Medical Genetics Section, Centre for Genomic & Experimental Medicine, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
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383
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Affiliation(s)
- Péter Przemyslaw Ujma
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary
- National Institute of Clinical Neuroscience, Budapest, Hungary
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